Prizes from the European Meteorological Society (EMS) were awarded to the three best posters:-
1) Ana Carvalho - University of Azores [video feedback]
2) Anthony Bloom - University of Edinburgh [video feedback]
3) Pieter-Jan Baeck - Royal Meteorological Institute of Belgium (RMI) [video feedback]
2010 Earth Observation Summer School Posters
SEOSAR/PAZ SAR Mission: Panel Design and Performance
EADS ASTRIUM Spain - CASA Espacio (firstname.lastname@example.org)
SEOSAR/PAZ is a highly flexible X-Band Synthetic Aperture Radar (SAR) satellite, which primary objective is global Earth Observation to serve the Spanish Government under the National Earth Observation Programme. PAZ will be capable to provide high quality SAR images with a variety of sizes and resolution ranging from medium resolution over wide regions up to very high resolution (e.g. meter and sub-meter). This paper presents a general description of the functional architecture of the instrument front-end followed by an overview of the foreseen panel qualification campaign. Besides, a brief summary of the instrument performances and verification strategy is presented.
Preliminary investigation in the use of NAME atmospheric dispersion model in conjunction with surface measurements for investigating the surface fluxes of methane
Annual global emission of methane (CH4) is fairly well constrained to 550 (±50) Tg from the study of tropospheric OH which is the dominant sink for atmospheric CH4. However, the quantification of individual methane sources and sinks is still largely uncertain. These uncertainties are particularly large for the various biogenic CH4 sources, such as wetland emissions or emissions from rice paddies due to their large spatial and temporal variation.
Satellite instruments can provide a top-down view of the integrated signals of atmospheric CH4 thus constraining the magnitude of emissions from larger regions. Here the potential for using the NAME Lagrangian dispersion model with satellite data to advance our understanding of the highly uncertain biogenic sources of methane is investigated using a forward modelling approach. Utilisation of CH4 data observed from the Total Carbon Column Observing Network (TCCON) has allowed preliminarily testing of this model. The NAME model output is coupled with pre-existing flux estimates and the output is compared with the observations at the TCCON site in Park Falls, WI. The results will pave the way to using CH4 observed by the Greenhouse gases Observing SATellite (GOSAT) in conjunction with the NAME model to investigate the surface fluxes of methane.
Regional distinctions in the global mean pattern of terrestrial CO2 fluxes due to missing observational constraints
University of Bristol (email@example.com)
The Carbon Cycle Data Assimilation System (CCDAS) allows the current fluxes of CO2 to the atmosphere to be mapped and the evolution of these fluxes into the future to be predicted. In this work we concentrate on the calibration mode of CCDAS where an optimal parameter set is derived from 25 years of atmospheric CO2 concentration observations using an adjoint approach. Global and regional process parameters are considered via a mapping routine. The parameters are then optimised by calculating the mismatch of the observations and prior knowledge of the parameters via a defined cost function. Further, parameter uncertainty estimates, which are obtained during the parameter optimisation step, can be propagated in order to estimate uncertainties of any given output such as of the predicted net CO2 fluxes. We find that the regional differentiation of one of the parameters, the key carbon storage parameter, leads to a significantly improved fit to the observations. This suggests that the key carbon storage parameter is not a universal parameter and that it is sensitive to the regionalisation process.
Detection of systematic errors on different time scales in land surface model using Artificial Neutral Network
Since the advent of FLUXNET, land surface models are often evaluated on a handful of EC sites. Previous studies characterized the model-data errors on different time scales and pointed out that the large relative model-data errors occurred in low frequencies. However, the share of model-data error which is not random at and across different time scales is still not well understood. In this study, taking a land surface model (ORCHIDEE) as an example, we resort to time series decomposition method (SSA) and artificial neural network (ANN) for quantifying time-scale transitivity and space transitivity of model systematic errors on different time scales (diurnal, annual and interannual) based on 500 site-years of eddy covariance data from 123 sites across the global in FLUXNET database. The main results are: (1) inter-annual time scale has the largest share of model error in the frequencies we considered; (2) model systematic errors are poorly transferable across different time scales, which can be expected due to climate-driven processes regulating ecosystem fluxes across time scales in ORCHIDEE are different; (3) model systematic errors is more shared within PFT and within climate zone at all frequencies, implying that model improvement based on specific sites can enhance the model behavior for the sites covered by the same PFT within the same climate zone. Our study also enables LSM community to have an idea of the theoretical bound for the space of model improvement and model uncertainties reduction, and provides the clues on how much of the benefits can be obtained for the overall model performance from site-based model calibration.
Surface mass balance of the Greenland ice sheet simulated with CESM
University of California at Berkeley (firstname.lastname@example.org)
The interactive coupling between an ice sheet model and a climate model allows the modeling of the impacts of changes on the ice sheets on the climate system and on its own mass balance. The Community Earth System Model (CESM, previous version is CCSM4.0) includes interactive ice sheets for assessment of the contribution of the Greenland ice sheet to 21st century sea level rise and its impacts on the climate system (e.g. thermohaline circulation, local Greenland climate). The model has been developed at the National Center for Atmospheric Research, Los Alamos National Lab, University of Montana and UC Berkeley (myself).
Here we present the simulated pre-industrial surface mass balance of the Greenland ice sheet when the land component is forced with ~1º CCSM4.0 data downscaled to the present-day topography at 10 km resolution. Results are validated against data from the regional model RACMO and the reanalysis NCEP/NCAR (1948-1998). The model captures well present-day snowfall and ablation patterns. Because of the use of an energy balance calculation for melting, this model is well suited to simulate climates different than present-day, avoiding the use of highly empirical methods (degree-day) and anomaly forcing.
Characterizing seasonal dynamics and inter-annual variability of different vegetation types in Central Africa with SPOT-VEGETATION NDVI time series
Universitéatholique de Louvain (email@example.com)
In a global change context, it becomes essential to develop a following capacity of the behaviour of ecosystems and of their variability in relation with climatic variability. Land phenology which can be estimated with remote sensing time series, is expected to be an useful and easily observable climate-sensitive variable. Study of the vegetation in tropical areas in particular can benefit from this long term source of data. Based on ten days NDVI time series acquired during the last 10 years by the VEGETATION sensor, the seasonal dynamics of Central African vegetation types will be characterized. These vegetation types are delimited thanks to a new 300m resolution land cover map for this region. Their reference seasonality and inter-annual variability, representing the intrinsic proprieties of each vegetation type, are described by temporal metrics derived from the time series. The spatial homogeneity of the seasonality is also studied for similar vegetation types into different ecoregions. If trends are observed in the vegetation seasonality, these trends will be compared to the expected evolutions due to climate change. Finally, a comparison with in-situ data will be made for a site in Ngotto, a semi-deciduous forest in the Central African Republic.
Atmospheric Sounding using IASI
The Infra-red Atmospheric Sounding Interferometer (IASI) instrument on board the METOP-A satellite is a nadir viewing Fourier transform spectrometer, which measures the radiance from the Earth's surface and atmosphere and provides atmospheric temperature and water vapour profiles for use in Numerical Weather Prediction (NWP).
This study investigates how accurately an atmospheric profile can be retrieved by IASI for different atmospheric gases. Through analysis of both the information content and degrees of freedom, using inverse methods, an optimal set of channels is selected for the retrieval of each gas. From the selected sets of channels, total column amounts and their associated errors are calculated, expanding this to a full profile retrieval for the well retrieved gases. The propagation of errors through the retrieval due to inaccuracies in atmospheric parameters is explored as is the effect of using principal components to decrease the volume of data used.
Determining tropospheric ozone columns from space by assimilation of GOME-2 ozone profiles
Jacob van Peet
GOME-2 ozone profiles are assimilated with the TM5 chemical transport model using the Kalman filter technique to incorporate the profiles into the model. Various adaptations to an existing assimilation algorithm for GOME ozone profiles are applied in order to keep the computational load within reasonable limits.
The algorithm that is used for retrieving the GOME-2 ozone profiles is called OPERA, which is an acronym for Ozone ProfilE Retrieval Algorithm. It solves the inverse problem that is inherent to profile retrieval by optimal estimation, which combines the satellite measurements, radiative transfer model results and a priori information of the atmosphere. Currently, the retrieval is done near-operationally on ground pixels of 640X40 km with a vertical grid of 40 layers ranging from the surface up to 0.1 hPa.
All GOME-2 ozone profiles that are produced by OPERA each day (about 20000 profiles) can be assimilated within a few hours by the global chemistry Transport Model (TM5). TM5 is set up to allow two-way nested zooming, but for the current research the model grid is set to 2X3 degrees.
The tropospheric ozone column can be determined directly from the assimilation output. It is also possible to determine the stratospheric ozone column from the assimilation output and subtract it from the GOME-2 total ozone column product to obtain the tropospheric column.
Calibration and Estimation of Extreme Wave Heights in the Southern Ocean using Altimeter Data
The Southern Ocean is consistently the roughest ocean. Reliable description and prediction of extreme wave conditions there is urgently required. Satellite observations are crucial in such isolated, hostile areas; however, validation studies have been mainly performed for the N.H. due to lack of wave information in the S.H., particularly in the Southern Ocean. The availability of buoy measurements from the Agulhas Bank offers for the first time the potential for the calibration/validation of altimeter-derived wave data in the Southern Ocean. In the present work, we estimate the quality of Hs and Tz from TOPEX, Jason-1 and Envisat in the S.H, while a new calibration model which accounts for the influence of seasonal variability in the data is also presented. This, in turn, opens up possibilities for accurate and thorough examination of the extreme wave climatology off South Africa, and in the wider region of Southern Ocean. Using the POT method, the 50-year return value is estimated for both the buoy and the combined calibrated altimeter dataset, as well as on a seasonal basis with different selected thresholds. The resulting maps of the 50-year return value in the Southern Ocean are compared between them and against the in situ return values.
Investigating the validity of Sverdrup Balance in determining the Meridional Overturning Circulation
University of East Anglia (firstname.lastname@example.org)
Since its conception in the 1940's, Sverdrup Balance has become a cornerstone of oceanography, forming the basis of much oceanic theory. If Sverdrup Balance were to hold it would also provide a significant tool for remotely determining the subtropical gyre by linking the surface wind stress to the meridional mass flux at any geographical location. Until recently it has not been possible to verify the accuracy of Sverdrup Balance due to the practical difficulties of obtaining observational data with sufficient spatial and temporal resolution. In this study we use the ECCO reanalysis data to quantify the extent to which Sverdrup Balance holds and to determine the dynamical mechanisms responsible for any discrepancies. The chioce of ECCO was motivated by the dynamic consistency retained between the ocean and atmosphere following the adjoint assimilation procedure. Averaging between 1992 and 2007, we found that, away from western boundaries between 40S and 40N, the deviation from the zonally averaged Sverdrup Balance is between 15% and 40%, but a pointwise balance is far reduced with deviations in many areas exceeding 100%. We argue that these discrepancies are largely due to non-linearity rather than the assumption of a level of no motion.
Temperature and Lapse Rate Changes over the IPCC Regions and Large Scale Zonal Bands
Wegener Center for Climate and Global Change (email@example.com)
Global warming will likely cause inhomogeneous tropospheric temperature changes at different altitude levels and can thus affect atmospheric stability and cloud formation processes. Therefore, projected temperature lapse rate changes are of major interest.
In this study temperature changes and variability are investigated for the 30 IPCC regions and 7 large scale zonal bands, together referred to as IPCC+ regions. For the analysis two global climate models of the IPCC fourth assessment report are employed, ECHAM5 and HadCM3. A combination of the 20th century run and the A2 scenario is used for the period 1980 to 2060. Since three ECHAM5 simulations have been available, an ensemble mean was used in the analysis. Here we present the evolution of temperature and lapse rate at different altitudes. The temperature changes considered are surface temperature and the temperature at 8 km geopotential height (gpkm). Lapse rates are based on the one hand on differences between surface and 8 gpkm and on the other hand on the difference between two upper tropospheric altitude levels, which vary with the latitude of the regions. For better comparison with radio occultation science, which is an accurate measurement method between 8 km and 30 km, for the 8 gpkm temperature evolution and the upper tropospheric lapse rates, 'dry' and physical atmospheric states were considered. Dry temperature is a parameter commonly utilized in radio occultation science and it is calculated from refractivity assuming that atmospheric water vapor content is very small and its contribution to refractivity can be neglected. It turns out that in most IPCC regions a steepening of the physical lapse rate occurs, while in some high latitude regions a lapse rate flattening takes place. This indicates on average higher atmospheric stability in most regions, while few change towards higher atmospheric instability. According to this projections the average cloud building processes through convection could become somewhat weaker.
Validation of Regional Climate Models for Hydrological Impact Studies at the Catchment-Scale
Stockholm University (firstname.lastname@example.org)
The assessment of climate-change impacts on regional hydrology is subject to uncertainties from various sources, including uncertainties related to (1) greenhouse gas (GHG) emission scenarios, (2) global climate models (GCMs), (3) regional climate models (RCMs), (4) downscaling techniques, (5) bias-correction methods, (6) hydrological models, (7) natural variability and (8) error-prone data. It is still a major challenge to quantify and reduce these individual uncertainties as they can propagate through the entire modeling chain and interfere with each other. We assessed the resulting uncertainties in simulated streamflow, a fundamental hydrological variable, based on a so-called ensemble approach: Various RCMs combined with different bias-correction methods were used to transfer climate data from several coarse-scale GCMs under different GHG emission scenarios to local scale. The downscaled climatological variables were then used to simulate (1) monthly mean streamflow and (2) flood peaks for five Swedish catchments under current and future climate conditions with the hydrological model HBV. Our results show that RCMs are to a certain extent only able to provide sufficient data for hydrological simulations. Although the simulated streamflow fits partly well with observations in terms of flood timing, the magnitude differs considerably with up to ±100% for several RCMs. Our multi-RCM approach for hydrological impact studies clearly demonstrates the large inter-model variability and underlines the need for RCM ensembles in combination with appropriate bias corrections.
Extension of an airplane- and ground-based Sun photometer into the NIR spectrum
Freie UniversitäBerlin (email@example.com)
The continuously-measuring, multi-spectral Sun and aureole photometer FUBISS-ASA2 was developed by the Institute for Space Sciences of the Freie UniversitäBerlin to be used on the Institute's Cessna 207T research aircraft in order to derive optical and microphysical properties of aerosols at a high spatial (including vertical) and spectral resolution in the visible part of the electromagnetic spectrum. It has now been upgraded to include a near-infrared spectrometer that measures the direct Sun-radiance. Its aim is to allow a better characterization of larger aerosol particles, as Mie scattering theory allows for a better approximation of their scattering behavior in the NIR than in the visible part of the spectrum. Furthermore, the broadened spectral range of the photometer permits the concentrations of trace gases that have absorption bands in the NIR to be derived. The NIR-extension of FUBISS-ASA2 has so far been employed on the transatlantic transect ANT-XVI/1 of the FS Polarstern, on the campaign Cloud and Aerosol Characterization Experiment 2010 below and on the Jungfraujoch near Bern, as well as on ground-based measurements while a plume of ash from the eruption of Eyjafjallajöl was sweeping over Europe. FUBISS-ASA2 was also flown during the volcanic ash event aboard the Institute's airplane.
Application of CMEM to SMOS data over Polesie and Biebrza
Space Research Center Polish Academy of Sciences (firstname.lastname@example.org)
Since the launch of SMOS satellite in November 2009, space-borne passive microwave observations at L-band (1.4 GHz) has become available. SMOS provides global mapping of brightness temperature at wide range of incidence angles, provides data for angular signatures, and is dedicated to provide estimations retrieved from measurements in near-real-time global soil moisture products. Now we work on validating SMOS data to support critical evaluation of the trust to it.
Polesie and Biebrza wetlands are two examples of areas selected for SMOS Cal/Val campaigns over territory of Poland. These areas belong to the group of the largest wetland ecosystems in Europe and may have significant influence on vegetation cycle, as well as are very good representation of vegetation test sites. In our studies and approaches to validations, we have undertaken a use of Common Microwave Emission Model (CMEM), elaborated at ECMWF for that purpose. The modelling approach description is based on Radiative Transfer Equation (RTE) in layered media, including land cover by means of the tau-omega model to combine contributions from different elementary models on physical and biological properties. Testing contributions from common vegetation indexes, physical properties and the land coverage, to SMOS data in terms of BT (Brightness Temperature), leads us to the domain of electromagnetic polarization modes, and focus the work on different aspects of data processing, from enormous range of the require data fusion, through large scale requirements, and up to advanced statistical aspects of the work. Simple comparisons of real SMOS L1C data interpretations with conclusions shall be given for two different test sites and in the time evolution from April till June 2010.
Studies on late Quaternary environmental dynamics on Mt. Kilimanjaro - first results
Dep. of Palynology and Climate Dynamics. GAUG (email@example.com)
In our project, we study pollen found in peat and sediment cores from different key areas at Mt. Kilimanjaro to reconstruct former and to predict future landscape dynamics. We would like to better understand local and regional ecosystems, climate and fire dynamics in a larger context, ecosystem dynamics and their reaction on environmental changes, connections and disjunctions of different ecosystems and their role for the development of the biodiversity hot spots in East Africa.
Our first study site, Maundi Crater at 2780m a.s.l., is located on the SE slope of Mt Kilimanjaro within Ericacous vegetation. So far, we have analyzed 32 pollen samples of the ~ 6m long peat core. First results reveal that the vegetation belt composition, classified as lowland woodland, Afromontane forest, subalpine Ericacous shrub, and afroalpine grassland, has remained rather stable for the past 37,000 yrs. The taxa composition within the vegetation types has varied. The increase in Ericacous vegetation in the late Holocene indicates more frequent (anthropogenic?) fire events. Three phases with no pollen records may be related to droughts that disabled pollen preservation. We will analyse pollen, charcoal and chemical composition to investigate more samples of the Maundi core, and follow-up cores along the slopes of Mt Kilimanjaro. Modern vegetation and pollen rain data will help us calibrate, interpret and model our results.
Aerosol Layer Height Retrieval using the O2-A and O2-O2 Band
KNMI - Royal Netherlands Meteorological Institute (firstname.lastname@example.org)
KNMI is the principal investigator institute for the TROPOspheric Monitoring Instrument. TROPOMI, which is the payload on the ESA/GMES Sentinel-5 Precursor mission, will be the follow-on to the Ozone Monitoring Instrument (OMI). Whereas OMI measures in the ultraviolet and visible (270-500 nm) wavelength range, TROPOMI will also measure in the near-infrared (675-775 nm) and short wave infrared (2305-2385 nm) ranges. The O2-O2 absorption band in the UV is used by OMI to retrieve cloud pressure. It might potentially also be used for retrieving aerosol layer height. However, the O2-A absorption band in the NIR offers another possibility to retrieve aerosol height. We will present a comparative sensitivity analysis of the O2-A and O2-O2 band for retrieving aerosol height using optimal estimation. The analysis is done with DISAMAR (Determining Instrument Specifications and Analyzing Methods for Atmospheric Retrieval). DISAMAR is a software package which simulates measured backscattered radiances and applies retrieval algorithms under different assumptions. We will focus on the question to what extent specific knowledge of the aerosol type is needed for accurate and precise layer height retrieval. Applications are in desert dust transport, biomass burning and volcanic ash plume height.
Population dynamics model of Culicoides imicola in Sardinia
Epidemiologists have demonstrated a large number of variations in the meaningful variables describing the distribution of C. imicola, the main vector of the bluetongue disease in the Mediterranean basin. This may be unimportant for the production of preliminary risk maps, but detailed maps require finer investigations on the relationship between satellite-derived variables and biological processes that determine population performance. We decided to build a population dynamic model that can predict variations of C. imicola population levels in space and time, as a function of remotely-sensed eco-climatic predictors. Our population model was developed and trained using the 2001-2006 longitudinal trap catch data from Sardinia. We developed a discrete-time population model where the population in each month is estimated by its intrinsic growth rate. Accounting only for Modis LST, the preliminary results showed our model takes into account seasonality. In addition it captures well the changes in population levels as a function of elevation. Preliminary attempts to try to apply it to Tuscany resulted in a poor fit, with a general tendency to overpredict populations. This suggests that the variables considered in the model should be complemented by factors constraining populations in Tuscany region. The added value of other environmental variables is discussed.
Sensor intercalibration for the ESA GlobAlbedo project using QA4EO protocols
University College London (email@example.com)
Sensor inter-calibration is required in order to facilitate the merging of ATSR2, MERIS, AATSR, VEGETATION and VEGETATION2 spectral surface directional reflectance into a fifteen year land surface broadband albedo map of the entire Earth´s land-surface (snow and snow-free) for use in Global Climate Model initialisation and verification as part of the ESA GlobAlbedo project (Muller et al., awaiting publication).
To achieve this, a measure of the accuracy of every element in the processing chain needs to be made, so that the final broadband albedo contains as accurate as possible an estimate of uncertainty. The Quality Assurance for Earth Observation (QA4EO) protocols, described elsewhere (Fox et al., awaiting publication) are an attempt to establish standardised methods for tasks of this nature. As part of this, an uncertainty assessment is currently being demonstrated using 2 months of data from December 2008-January 2009 for numerous satellites over the Antarctic CEOS endorsed ´landnet´ test-site, Dome C.
Using multi- and hyperspectral data from AATSR, MERIS, AVNIR-2, CBERS, CHRIS-PROBA, Landsat-7, NigeriaSat-1, SPOT and UK-DMC-1, spectral radiance is corrected for atmospheric (mainly O3) and BRDF effects in preparation for intercomparison.
The site selection and method of the group project is discussed and some preliminary results are shown.
State estimation using the particle filter with mode tracking
University of Reading (firstname.lastname@example.org)
Data assimilation is the incorporation of observational data into a numerical model to estimate the model state which accurately describes the observed reality. Traditional data assimilation schemes assume that data is modelled by a Gaussian state space model. A particle filter (PF) is an ensemble data assimilation scheme that allows the probability density function (pdf) of non-Gaussian state space models to be approximated. Here we consider if the efficiency of the PF in high dimensional space can be improved by the introduction of mode tracking. When mode tracking we must split the model state into two subspaces. One subspace is forecast using the ordinary PF, the other is estimated using the mode of the marginal pdf. We discover that the results from the particle filter with mode tracking (PF-MT) are sensitive to the choice of state splitting. Once we have determined how to split the state we carry out experiments using the stochastic Lorenz equations. When the assimilating model is perfect we find that the PF-MT provides more accurate results than the PF. However, when the model is biased the performance of the PF-MT is degraded.
SST decrease on the San Matí Gulf coast, Argentina. Possible upwelling events.
University of Buenos Aires (UBA) and Patagonic Nacional Center (CENPAT). (email@example.com)
The San Matí Gulf (GSM) is the second largest gulf in the Argentinian Patagonian Shelf and it is highly productive, constituting an outstanding foraging and breeding area for many species of birds, marine mammals and commercially valuable resources. This biodiversity is because in these latitudes of the Argentinian Sea is located the transition zone between two different biogeographic provinces. A part of this region is situated within the World Heritage area declared by UNESCO in 1999.
By mean of remote sensing thermal frontal systems have been identified. These areas are involved in the majority of fish production in the region. Some of these frontal systems are spatially and temporally persistent and they are attributed to tidal vertical mixing, but others, located near the west coast of GSM, are more intermittent and are believed to be caused by upwelling favorable wind events. In the present work these are analyzed through AVHRR images of SST and QuikSCAT winds, taking into account the difficulty of studying very intermittent coastal processes, such as upwelling events, by mean of different time separation images and sometimes covered with clouds.
Application of a LUE Model to estimate GPP 8-d by using MERIS Products in a Spanish Agricultural Ecosystem
University of Valladolid (firstname.lastname@example.org)
In the context of climate change predicting the total amount of CO2 assimilated by crops, GPP, is of crucial importance. GPP is indirectly derived by eddy covariance flux towers as the difference between respiration, RE, and net ecosystem exchange, NEE. NEE is directly measured and RE may also be measured using chambers or parameterised using NEE nocturnal data on soil or air temperature. An alternative for estimating GPP is based on the application of Light Use Efficiency, LUE, models.
The aim of this research is to derive GPP from fAPAR MERIS product, by means of MGVI algorithm, using a LUE model in an agricultural ecosystem located in the upper Spanish plateau over selected periods between 2003 and 2006, especially during the growing season. The LUE model is based on ground PAR measurements, fAPAR and a scalar varying between 0 and 1 to take into account water stress, the evaporative fraction, EF. The fourth parameter, the maximum light use efficiency of the dominant land use at the measuring site, has been fitted throughout a linear fit between the calculated and observed GGP 8-d values. Big gaps were refilled using the results GPP-LAI MERIS linear regression.
Vertical distribution of clouds and aerosols over the eastern Mediterranean basin: its spatial and temporal variability based on CALIPSO data
University of Ioannina (email@example.com)
Clouds are among the primary determinants of the Earth-atmosphere climate system. Aerosols remain a great uncertainty as to whether they cause global warming or cooling. The relative position of aerosol and clouds has also revealed a significant effect, the semi-direct effect. This is the effect that aerosols have on microphysical structure of clouds. Recent advances in Earth observation from space have greatly enhanced our ability to detect clouds and aerosols throughout the globe. CALIPSO along with CLOUDSAT provide an in-depth knowledge of the vertical distribution of clouds.
This study uses cloud and aerosol data from CALIPSO Level 2 products to investigate the cloud and aerosol vertical distribution over the eastern Mediterranean basin (30°-41° N, 19°-37° E). This is an important study area, since it is sensitive to climate changes, whereas it undergoes frequent transport of aerosols from Sahara desert which possibly affect the formation of clouds. The procedure is applied to two year (13/06/2006-14/09/2008) data. It is the first time that clouds and aerosols are presented in such a fine vertical spatial resolution for the Mediterranean basin. Moreover, a comparison between CALIPSO and the well-established ISCCP cloud data is attempted.
Geological Mapping by the Use of Satellite Images, Compared with GIS Geological Data. Case Studies from Macedonia Area, Northern Greece
Aristotle University of Thessaloniki (firstname.lastname@example.org)
Geological mapping is one of the fundamental acts that a geologist should perform in order to proceed to higher levels of a research. This includes basically, mapping of lithological units and tectonic lines (faults). Satellite images give geologists a unique opportunity to observe the complex interaction of largescale geological structures that make up Earth´s landscape. Furthermore, digital satellite data can be manipulated and enhanced in order to accentuate the surface expressions of certain geological features. In most of the cases, this is usually done in ´ideal´ test sites, with absence of vegetation, soil cover, etc. In this paper, various digital image processing techniques were applied on Landsat-7/ETM+ and Terra/ASTER satellite images, acquired on different dates, in order to produce the most appropriate images for geological mapping, in typical Mediterranean terrain. Two areas were chosen as case studies, the Kassandra peninsula and Thassos island. Boundaries of photo-lithological units and photo-lineaments are drawn on the above satellite images. The results are compared with digitized geological maps of 1/50.000 scale and are evaluated.
Observations of Sun-Earth connections using Solar and EO satellites
For more than a century, studies have focused on the hunt for a signal indicating transmission of a solar activity signal to the lower atmosphere and the subsequent effects such a signal would hold over a wide range of timescales in relation to weather and climate. Recent examples include modification of cloud properties, modulation of the global electric circuit, as well as effects on northern hemisphere temperatures, water vapour, and Amazonian stream flow, etc. A number of the recent studies have concluded that there is a strong correlation between solar activity sunspots, solar irradiance (F10.7), and cosmic ray flux and the generation and discharge of lightning.
The precise mechanism, however, for this interaction is still in debate, and lacks specific examples to demonstrate these connections. Utilising data from MODIS, in combination with data from the Lightning Imaging Sensor (LIS) on-board NASA´s TRMM Observatory, the relationship between the intense solar storm of October 2003 or more so, the associated discharges known as Coronal Mass Ejections (CMEs) which intercepted the Earth ? and convection in the tropics is analysed in relation to the correlation of solar events to lightning discharge events.
Monitoring Vegetation Seasonality in Ireland from Envisat MERIS
Brian O' Connor
Coastal and Marine Resources Centre, Environmental Research Institute, University College Cork (email@example.com)
Evidence from the Irish phenological gardens suggests that tree growth is occurring earlier due to a rise in average spring air temperature. This has lead to an extended growing season with impacts on agriculture, forestry and ecosystems.
This research has developed a methodology to explore the potential of the reduced resolution Envisat MERIS Global Vegetation Index (MGVI) to monitor this greening phenomenon across the island of Ireland. The MGVI has been optimised to estimate a geophysical measure of vegetation growth, derived from data in the visible and near-infrared spectral bands, known as the fraction of absorbed photosynthetically active radiation (FAPAR). A 10-day composite period was found to be appropriate to produce cloud-reduced imagery for a national-scale study.
Time series analysis of the FAPAR composites from 2003 to 2009 showed spatial patterns in the start of season (SOS) across the island which exhibited consistencies with the CORINE 2006 landcover classes. Estimated SOS was earliest in managed vegetation classes, e.g. pasture, while it was between twenty and forty days later in natural grassland. The season start was latest in upland areas regardless of landcover type.
A seasonality-climate correlation study, using average air temperature, will be used to characterise the spatio-temporal relationship between SOS and climate.
Tropical Forests Carbon Dynamicq using 10-y SPOT-VEGETATION Time Series and Land-Surface Modelling
Universitéatholique de Louvain (UCL) (firstname.lastname@example.org)
Vegetation is a major carbon sink and is as such a key component of the international response to climate change caused by the build-up of greenhouse gases in the atmosphere. However, anthropogenic disturbances like deforestation or fires are the primary mechanism that changes ecosystems from carbon sinks to sources, and are hardly included in the current carbon modelling approaches. Moreover, in tropical regions, the seasonal/interannual variability of carbon fluxes is still uncertain.
The overall objectives of this research is to dynamically assimilate the land surface characterisation obtained from long SPOT-VEGETATION time series (e.g. plant functional type, phenology, Leaf Area Index, land cover change) as well as in-situ carbon flux data into the ORCHIDEE global vegetation model, which simulate vegetation dynamics and carbon balance, in order to improve the forecast of the terrestrial carbon cycle in tropical regions under different anthropogenic forcings. Such approaches will allow determining whether the african terrestrial carbon balance will remain a net sink or become a carbon source, according to different climate-change and deforestation scenarios. The challenge of this research is to bridge the gap between the land cover and land surface model communities.
Using radar altimetry in catchment models ?- Example application on the Zambezi River Basin
Technical University of Denmark (email@example.com)
The assimilation of remote sensing data in hydrological models helps reduce predictive uncertainty of the models and enables the use of all available data in real-time. This is particularly useful for large poorly or un-gauged basins, such as the Zambezi River basin, where remote sensing offers spatially distributed and temporally continuous data sets which are otherwise unavailable. The aim of this study is to establish stage-discharge relationships for virtual stations corresponding to radar altimetry targets from the Envisat mission on the Zambezi River and its tributaries for later assimilation of the altimetry data to a hydrological model of the basin.
A field campaign was carried out in Zambia to visit some of the altimetry targets on the Zambezi River and its tributaries to collect cross section and discharge data. Water levels from altimetry were converted to discharge using two methods: one using rating-curves derived from the field-measurements and one using remotely sensed data only. The discharge values calculated are compared to each other and to in situ discharge data from the Zambian Department of Water Affairs where available. The usability of radar altimetry data for rivers of different widths is also studied.
Antarctic postglacial rebound rates from a combination of remote sensing measurements
Centre for Polar Observation and Modelling, University College London (firstname.lastname@example.org)
The rebounding of the lithosphere after a period of glaciation (Postglacial Rebound) can by directly measured in previously glaciated parts of the Northern Hemisphere. In Antarctica, remote sensing measurements are required to gain insight into postglacial rebound rates. In this work, gravity measurements from the GRACE (Gravity Recovery and Climate Experiment) project are combined with measurements of ice thickness from the ERS-2 and Envisat altimeters. Gravity coefficients were obtained from the Center for Space Research (CSR) in Texas, the Geoforschungszentrum Potsdam (GFZ), the Jet Propulsion Laboratory (JPL) and the Groupe de Recherche de Geodesie Spatial (CNES/GRGS) in Toulouse. These coefficients were transformed into equivalent water heights. Certain coefficients were replaced with those obtained from Satellite Laser Ranging (SLR) or models. The effect of atmospheric background models applied to the gravity coefficients during processing is examined. In Antarctica these effects are larger than in the Arctic.
ASSIMILATION OF SVM-BASED ESTIMATES OF LAND SURFACE TEMPERATURE FOR THE RETRIEVAL OF SURFACE ENERGY BALANCE COMPONENTS
Data-assimilation methods play a crucial role for exploiting remote sensing in dynamic physical models for the prediction of hydrological-process evolution. Here, a novel method is proposed to assimilate land-surface temperature estimates, derived by applying support-vector regression to infrared satellite data, into a variational iterative technique for mass and energy exchange estimation at the soil surface. Recent techniques to fully automate support vector regression and to estimate the pixelwise statistics of the regression error are incorporated in the proposed method. As compared to the use of a standard LST product, the assimilation of the SVM estimates granted performance improvements in terms of convergence of the DA method and reduced error between assimilated and input LST estimates. Since the considered DA method was previously validated and calibrated with observations, this suggests an improved consistency of the SVM estimates with the considered physical surface processes. A further validation by comparison with ground measurements of saturation level, which is correlated with evaporative fraction and then with fluxes, has been made.
Airborne Soil Moisture Determination: Data fusion approach at regional level
Centre Suport Programa Català'Observació la Terra Institut Cartogràc de Catalunya (email@example.com)
Water cycle is considered to be a key factor in the study of climate change and its associated effects on society. In turn, soil moisture holds an important share of the overall water cycle. Is for this reason that at present missions like ESA´s SMOS, and future NASA´s SMAP aim to estimate soil moisture at a global level, offering spatial reso-lutions of 40 km for SMOS, and 10 km for SMAP. Such resolutions do not adequately match at a regional/local levels. At this point the Supporting Centre of the Catalan Earth Observation Program (PCOT), within the structure of the Cartographic Institute of Catalonia (ICC) and with the collaboration of the Remote Sensing Laboratory of the Polytechnic University of Catalonia (RSLAB UPC), runs the HUMID program to retry the soil moisture at a regional level based on radiometry and data fusion with VNIR and thermal sensors on board ICC airborne plat-forms.
Integrating InSAR and GPS for monitoring geologic CO2 sequestration
Delft University of Technology (firstname.lastname@example.org)
Various human activities such as burning of fossil fuels and deforestation have led to increasing carbon dioxide (CO2) and other greenhouse gas concentrations in the atmosphere. This accumulation can lead to global warming, sea level rise and serious ecological effects in the coming decades. A possible way towards reducing this buildup is to capture CO2 at stationary sources and inject it into underground geologic formations such as depleted oil or gas reservoirs for long-term storage (geologic sequestration).
However, owing to the high degree of urbanization in some of the proposed sequestration sites (e.g. Barendrecht in the Netherlands), it is imperative to be able to monitor the risks associated with geologic sequestration accurately. This includes precise measurement of ground deformation and subsidence effects, if any, in order to assess the propagation (and possible leakage) of CO2 in the storage reservoirs.
Space-geodetic observation techniques such as Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) have the potential of measuring ground deformation with sub-millimetric accuracy. The feasibility of monitoring the dynamics of gas injection in reservoirs using an integrated InSAR-GPS approach, which aims to combine the spatial resolution advantage of InSAR with the high temporal resolution of GPS, will be assessed.
Comparison of MISR and Meteosat-9 Cloud Motion Winds
Max Planck Institute for Meteorology (email@example.com)
This study of cloud motion winds (CMWs) exceeds previous investigations relying on sparse radiosonde or wind profiler observations in detail and extent. A detailed comparison of CMWs, retrieved with the Multi-angle Imaging SpectroRadiometer (MISR) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat-9 in the visible and infrared channels, is performed. The purely geometric stereo technique of MISR retrieves cloud motion and height simultaneously, and is potentially more accurate than traditional satellite winds relying on ancillary information for height assignment, like Meteosat-9.
225,155 collocated wind pairs, including only good quality retrievals from both data sets and filtering of so-called ``MISR clear sky winds'', are obtained for the year 2008. We have found that MISR winds have no substantial speed bias compared to Meteosat-9; however, the meridional (MISR along-track) wind components show significantly larger rms differences than the zonal (MISR cross-track) components. Also, there is a land-ocean contrast with vector differences being larger over land. In general, the worst agreements between wind retrievals are observed in the tropical regions. Additionally a case study, which shows big differences in cloud top height (CTH) in the South Atlantic between MISR and Meteosat-9, is performed.
ON THE VALUE OF HIGH-RESOLUTION WEATHER MODELS FOR ATMOSPHERIC MITIGATION IN SAR INTERFEROMETRY
Delft University of Technology (firstname.lastname@example.org)
The Earth's atmosphere manifests itself as a slant range delay in repeat-pass SAR Interferometry (InSAR). Mitigation of the delay is crucial for accurate deformation monitoring using InSAR. In this study, we use the WRF (Weather Research and Forecasting) weather model to hindcast atmospheric delays at SAR acquisition times. The value of the model for atmosphere mitigation is evaluated by comparing its predicted delay difference to atmosphere only interferograms (i.e. Bt <= 4 months). The areas chosen in our case studies are Mexico City where strong surface topography is present and the Netherlands which has almost flat terrain. The results of our case studies show that NWM may effectively estimate vertical stratification of the delay in mountainous but not always. For flat terrains, NWM not only fails to correctly estimate atmospheric delay in magnitude and location but also largely underestimates the spatial variability of the delay.
MERIS images coastline correction
Tartu Observatory (email@example.com)
Background: Importance of the location of the coastline in MERIS images becomes clear when information about coastal areas is needed. Also various algorithms calculating the atmospheric correction use the coastline as base. Algorithms for estimating different water quality parameters assume that pixels away from the coastline are all water. Specific algorithm to correct for neighboring land pixel s? ICOL - is applied for distance up to 30 kilometers from the coast.
Problem: When processing MERIS images with BEAM software, then the coastline is calculated from the reflectances of level-1 image. The pixels are flagged as water and as land. We have figured out for Estonian coastline that in the Level-1 images these pixels are not located correctly. In standard Level-2 the flagging is proceeded better, but the coordinates for recorded coastline are still incorrect as in Level-1. The atmospheric correction and specific algorithms use the Level-1 image for input and the corresponding flags. Therefor they also put the coastline position as difference between water and land to the wrong place.
Solutions: We'll try to find out why the Level-1 flags are wrong or insert an alternative coastline from independent source.
Monitoring of fast mine subsidence in Northern Moravia (CZ) using SAR interferometry
Vysoka skola banska - Technicka univerzita Ostrava (firstname.lastname@example.org)
The Northern Moravia region's 1500 km2 large black coal deposit has been extracted since 18th century. Accordingly to the mining approach, even that mines were not situated directly in populated areas, the region copes with a plenty of civil structures damages.
The real terrain deformation is monitored on places known to subside geodetically - mostly using levelling (mm precision). Testing of C-band satellite synthetic aperture radar interferometry (InSAR) techniques has proven its usability for regional subsidence monitoring. The main difficulties are ? a fast subsidence (even more than 2 m/year) undetectable in current InSAR resolution limits and strong regional decorrelation sources (a dense vegetation cover, high moisture changes in annual periods).
This poster contains a comparison set of different InSAR techniques (differential InSAR, multitemporal InSAR-MTI) using C-band (ERS-2 SAR, Envisat ASAR - wavelength 5.6 cm) or L-band (ALOS PALSAR - wavelength 23.6 cm) radar images and results of levelling in several selected places known to subside in the Northern Moravia region.
Sensitivity analysis and application of KLIMA algorithm to GOSAT validation
Lucia Maria Laurenza
CNR - Institute of Applied Physics Nello Carrara (email@example.com)
The primary objective of the project is to investigate the capabilities of IASI-METOP observations for the retrieval of CO2 total abundance averaged over a time and spatial scale compatible with the requirements of a comparison with the CO2 products of the GOSAT mission.
The study is organized in two phases:
Phase 1: adaptation of the KLIMA algorithm for retrieval of CO2 from IASI spectra; sensitivity assessment and evaluation of the performances of the optimized code.
Phase 2: integration of the optimized KLIMA/IASI CO2 retrieval code into the G-POD operational environment; inter-comparison of CO2 products retrieved from collocated IASI and GOSAT measurements for cross-validation of the two instruments.
The main elements of innovation introduced by the KLIMA-IASI Retrieval Model and by its application to the retrieval of CO2 column from IASI can be recognized in the following aspects: feasibility of a retrieval approach exploiting all spectral channels of IASI to extract information on carbon dioxide and other targets with no need for channel selection and use of a global-fit, multi-target retrieval scheme which removes the systematic errors due to the interfering unknowns.
Comparing Stratospheric Temperature Records from GPS Radio Occultation, MSU/AMSU and Radiosondes
Wegener Center, Karl-Franzens University of Graz (firstname.lastname@example.org)
The upper troposphere-lower stratosphere (UTLS) region reacts sensitively to climate change. Detecting the anthropogenic climate change there requires high quality observations. Upper air temperature time series exist primarily from radiosondes (since 1958) and from satellite measurements, the latter provided by the (Advanced) Microwave Sounding Unit (A)MSU (since 1979). Neither of the instruments was originally intended for climate monitoring. Thus, demanding intercalibration and homogenization procedures are required to establish a climate record. Though improved agreement in UTLS trends of these records was achieved recently, uncertainties concerning the magnitude of upper air temperature trends still remain.
The relatively new radio occultation (RO) technique is well suited to overcome these problems. It uses Global Positioning System (GPS) radio signals in limb sounding geometry to deliver observations in the UTLS region with high accuracy, global coverage, and high vertical resolution. Additionally it is self-calibrating, avoiding the need of error-prone intercalibration routines. In this comparison, the most recent RO records are used to calculate synthetic MSU layer-average brightness temperatures for the lower stratosphere (TLS). Monthly-mean zonal-mean synthetic temperatures are then compared to recent (A)MSU and radiosonde data sets. Significant differences between the data sets are found.
Modelling and Remote Sensing of Varying Global Sea Level Distributions
GFZ Potsdam (email@example.com)
Sea level is a crucial variable in oceanography and climate science both in itself (consider coastal populations and ecosystems) and as an easy-to-measure proxy for subsurface processes (variations in currents, temperature, and salinity distributions). I use data from altimetric satellites (TOPEX/Poseidon, Jason) that have been measuring sea level anomalies beginning in the early 1990s and I compare it to output from reanalysis-driven ocean models (OMCT, MPI-OM). Examining different signals in the sea level datasets, e.g. ENSO, the Madden-Julian-Oscillation, the annual signal, and comparing different geographic regions, I identify the processes that state-of-the-art ocean models are able to resolve and those that they don't. Spectral analysis and Empirical Orthogonal Functions are helpful tools in this context. The next step is the improvement of the models by implementing additional processes such as loading and gravitational self-attraction of seawater which might alter regional distributions of sea level considerably.
Modelling and Remote Sensing of Varying Global Sea Level Distributions
Canada Centre for Remote Sensing (firstname.lastname@example.org)
Identification of clouds in satellite imagery is essential for estimation of surface state variables. Several cloud identification algorithms exist for data from the AATSR sensor on Envisat (e.g. , ), but none currently identify both clouds and cloud shadows consistently well, especially in the presence of snow or ice. This is an obvious concern in the Canadian context. To improve cloud identification for AATSR, we are implementing and testing the SPARC algorithm  for AATSR data. Potential improvements to SPARC may include use of both the 1.6 and 3.7 µm channels, improved weighting of individual test results, and use of AATSR’s dual-view system for cloud height derivation and haze identification. Improved cloud identification also allows AATSR to function as cloud screen for MERIS. Ultimately the work prepares CCRS for the launch of Sentinel-3, which will carry successors for both AATSR and MERIS.
 Gomez-Chova, L. et al. 2008, "Cloud screening methodology for MERIS/AATSR synergy products"
 Plummer, S. 2008, "The GLOBCARBON Cloud Detection System for the Along-Track Scanning Radiometer (ATSR)"
 Khlopenkov, K. and Trishchenko, A. 2007, "SPARC: New cloud, snow, and cloud shadow detection scheme for historical 1-km AVHHR data over Canada"
Diurnal Variability of Sea Surface Temperature and Wind
Risø, VEA (email@example.com)
Sea surface temperature is an important parameter governing the interaction between air and sea as far as heat, momentum, moisture and gas exchange is concerned as well as the atmospheric stability and the marine boundary layer height. Strong solar insolation and low wind speeds are favouring conditions for the diurnal variability of sea surface temperature. Exact knowledge of SST is required for applications such as climate monitoring, operational weather forecasting, ocean and atmospheric modelling. Thus, the diurnal variability of SST is important if SST applicability complications are to be resolved.
Satellite based remote sensing techniques are gaining ground as direct and operationally feasible methods for obtaining global wind vector and sea surface temperature information. QuikSCAT, in orbit since 1999, recorded daily information on global wind speed and direction until 2009. Surface wind is an important parameter for air-sea interactions, influencing heat and gas fluxes as well as the diurnal cycle of sea surface temperature. The SEVIRI instrument on board the MSG satellites, has been recording hourly SST fields since July, 2006.
The aim of the present study is to combine satellite data of SST from SEVIRI and wind vector from QuikSCAT to obtain an overview of diurnal warming in the North Sea and the Baltic. Night-time reference fields generated from the SEVIRI dataset, were utilized in order to compute the hourly SST anomaly fields of each day. Diurnal warming exceeding 2 [K], occurring most frequently at 15:00 local solar time, was identified during the spring and summer months of every year, starting as early as March and reaching maximum observations in June and July. The two daily passes of QuikSCAT from the areas of interest are not expected to adequately resolve the diurnal cycle. Nonetheless, diurnal wind variability, defined as mean morning minus mean afternoon wind speeds, was found to be in the order of 0.06 [m/s] in favour of morning winds for certain areas.
Determination of the Effective Resolution of Regional Climate Models
Kathrin Lisa Kapper
University Graz (firstname.lastname@example.org)
The spatial resolution of climate models is generally determined by their grid spacing (?x) or spectral truncation and the numerical implementation.
For example, features of the scale 2?x and 3?x are smoothed to avoid numerical instabilities (e.g., aliasing effects). Moreover, studies show an effective grid resolution of around 4?x.
In order to determine the effective resolution variance spectra of regional climate models (RCMs) are derived. The variance spectra are constructed by applying the Discrete Cosine Transform (DCT) on the model fields.
At first variance spectra of three non-hydrostatic high-resolution RCMs (the PSU/NCAR model MM5, its successor WRF, and the German model of the national weather services CCLM) with three different grid spacings (1 km, 3 km, 10 km) on two vertical levels (near the surface and at 700 hPa) are compared.
Furthermore the model spectra are compared to variance spectra of their driving data, the Integrated Forecast System (IFS, 25 km grid spacing) of the European Centre for Medium-Range Weather Forecasts (ECMWF).
Preliminary results show that the effective resolution varies from 3?x to 7?x, that it depends on the investigated parameter as well as on the model formulation, and it is particularly sensitive to the distance from the surface.
Changes in chemical composition of the middle atmosphere caused by sudden January 2006 stratospheric warming
Finnish Meteorological Institute, Earth Observation (email@example.com)
Sudden stratospheric warmings (SSW) are large-scale transient events which have a profound effect on the northern hemisphere stratospheric circulation in winter. During the SSW events the temperature in stratosphere increases by several tens of degrees and zonal winds decelerate or reverse in direction. Changes in temperature and dynamics significantly affect the chemistry of the middle atmosphere.
In this presentation, the response of the middle-atmosphere trace gases during sudden stratospheric warming January 2006 is investigated using measurements from GOMOS instrument aboard Envisat satellite.
Spatial and temporal changes in trace gas concentrations are analyzed in stratosphere, mesosphere and lower termosphere.
Changes in chemistry were found not to be restricted to stratosphere, but to extend to mesosphere and lower termosphere. The tertiary ozone maximum in the mesosphere often disappears with the onset of SSW, probably because of strong mixing processes. There are also significant changes in the secondary ozone maximum in the lower thermosphere. Enhancements in stratospheric NO3 strongly correlate with enhancements in temperature.
Using Sea surface height to track heat and salt content anomalies in the North Atlantic: Comparing coupled models to observations.
ESSC, University of Reading (firstname.lastname@example.org)
It has been estimated that the upper ocean (0-3000 m) global heat content increased over the last half of the twentieth century by 14.5 x 1022 J (Levitus et al., 2005). This has had an impact on global sea level rise through thermal expansion. Studies using altimeter data and in-situ temperature data suggest however, that altimeter data underestimates the sea level rise due to warming in the North Atlantic. The contribution of haline contraction has been cited as a possible explanation for this discrepancy. If we are to fully exploit altimeter data to help make future climate predictions it is important to know the relative roles of salinity and temperature in thermosteric sea level variability. In this study we look at an ensemble of transient climate runs of the Hadley Centre climate model HadCM3 and compare these to a 900 year control run. Areas in the North Atlantic are identified in which separate regimes of haline or thermal dominance in steric height anomalies exist. The causes and consequences of these regimes are examined in the context of the modern climate and variability in the altimeter record.
Monitoring of sea ice drift and deformation with SAR Satellite Data of different resolution
Alfred Wegener Institute for Polar and Marine Research (email@example.com)
Using a method based on pattern recognition, sea ice drift and deformation fields were obtained from sequences of synthetic aperture radar (SAR) images. Monitoring of sea ice drift with SAR is independent from weather and illumination conditions. Employing correlation-based methods for the estimation of motion, it is necessary to identify corresponding patterns in temporal consecutive datasets. Hence, temporal pattern stability is required. Sea ice is influenced by multiple forces like wind, currents, the Coriolis effect and internal stresses causing to drift and deformation. Deformation processes change existing patterns and consequently violate this constancy constraint. To minimise this effect it is necessary to increase the temporal resolution depending on the existing forces within the relevant region. One possibility to increase it is to employ ?Wide Swath? data instead of ?Image Mode? data, covering larger regions at a coarser spatial resolution. Thus it is important to understand how characteristics of sea ice drift change between different spatial resolutions. The error induced by the implemented pattern tracking algorithm is estimated, and differences between motion fields extracted from images of different spatial resolution are discussed. Preliminary results for the calculation of deformation fields based on the calculated shift information are presented.
Collocating satellite-based radar and radiometer measurements ? methodology and usage examples.
Luleåniversity of Technology (firstname.lastname@example.org)
Collocations between two satellite sensors are occasions where both sensors observe the same place at roughly the same time.
We study collocations between the Microwave Humidity Sounder (MHS) on-board NOAA-18 and the Cloud Profiling Radar (CPR) on-board CloudSat.
We present some statistical properties of the collocations, with particular attention to the effects of the differences in footprint size.
For 2007, we find approximately two and a half million MHS measurements with CPR pixels close to their centrepoints.
In the second part, we present possible applications for the collocations.
In particular, we use the collocations to train an Artificial Neural Network and describe how we can use it to develop a new MHS-based Ice Wateer Path (IWP) product.
With such a product, we aim to reproduce CloudSat IWP using only passive, operational sensors, so that we can improve the temporal and spatial coverage of a high-quality IWP product.
The collocations described in the article are available for public use.
Monitoring Land Subsidence in HO CHI MINH City usnign Radar Interferometry Techniques
Dinh Ho Tong Minh
Dipartimento di Elettronica e Informazione, Politecnico Di Milano (email@example.com)
The level of the ground water has been constantly lowering and the urbanization has been rapidly developing during the last decades due to the strong groundwater extraction which has led to the subsidence of some areas in the Ho Chi Minh City. Land deformation at the rate of few centimetres per year can be measured at the heavy ground water pumping stations.
Most existing techniques for monitoring ground subsidence base on (using) methods of precise leveling, and more recently the GPS. These methods are generally expensive and inefficient for monitoring large areas. Besides, sparsely distributed data points are often insufficient to provide information on every localized ground subsidence.
Recent advances in the Radar interferometry, especially with the Permanent Scatterer InSAR (PSInSAR) are appropriate remote sensing techniques for measuring ground subsidence in urban areas at high accuracy and low costs.
This poster demonstrates the effectiveness of radar interferometry to detect the deformations in HCMC. The goal is to employ this powerful new technique to measure the land subsidence phenomenon in HCMC using ERS SAR SLC scenes acquired over HCMC.
Assimilation of DIAL water vapour observations into the ECMWF global model
DLR Oberpfaffenhofen (firstname.lastname@example.org)
A new 4-wavelength differential absorption lidar (DIAL) system for water vapour measurements was developed at Deutsches Zentrum füt- und Raumfahrt (DLR). Installed on board of the DLR Falcon 20 aircraft, the system measured a large data set of water vapour observations during the T-PARC field campaign which took place in summer 2008 in the West Pacific Basin.
This new set of high-resolution humidity observations was assimilated into the ECMWF model using the operational 4-D variational data assimilation system.
A detailed analysis of biases between the model and the observations is performed to achieve the most efficient usage of the observations. The assimilation system successfully extracted the information content of the observations and the analysis was modified including the humidity measurements. It was found that observed water vapour structures with horizontal length scales smaller than the resolution of the assimilation system (T255; ~80 km) could not be corrected in the model analysis.
Verification with independent measurements showed a reduction of the analysis error using DIAL water vapour observations. However, in most cases only a small influence on the forecast fields verified with model analyses was found.
OMI SO2 and UVAI observations of Eyjafjallajöl volcanic eruption
Finnish Meteorological Institute (Janne.Hakkarainen@fmi.FI)
Eyjafjallajöl volcanic eruption took place on March 14th 2010 in Iceland. On the next day vulcanic ash was dispersed in Northern Europe and the air space was closed in many European countries. In this work we show SO2 and Ultraviolet Aerosol Index (UVAI) observations derived from the Ozone Measurement instrument (OMI). OMI observations provided useful information to scientists and decision makers all over the world. For example at Finnish Meteorological Institute (FMI) the OMI data was used to calibrate SILAM dispersion model.
Optical Turbulence - The influence of the atmosphere on ground-based astronomy
Uppsala University, Department of Earth Sciences (email@example.com)
The optical turbulence is responsible for the distortion of the images taken by ground-based telescopes. In this study the mesoscale non-hydrostatical model Meso-NH is used to characterize the optical turbulence at Mt Graham International Observatory (AZ, USA). The simulations are compared to measurements of the vertical distribution of the optical turbulence performed with a Generalized Scidar. These measurements cover 41 nights which are evenly distributed over different seasons of the year so we can better evaluate the performance of the model.
The Meso-NH model is shown to be able to describe the vertical distribution of the optical turbulence from the ground up to 20 km as well as the total integrated value with reasonable, small discrepancies from the measurements. Improvements can be done in the reconstruction of the seasonal variation trend of the vertical distribution of the optical turbulence.
Aerosol-cloud interaction studies using ATHAM
Aerosol-cloud interactions are important to both the radiative properties of clouds and their lifetime. The description of mixed-phase clouds within numerical models remains a challenge, due to to the difficulty in incorporating them accurately within numerical models and to a lack of knowledge of the relative importance of the various processes involved.
My PhD project involves developing a new comprehensive aerosol-cloud microphysical module that describes as far as possible the relevant dynamical and microphysical processes from first principles. The module will combine an existing aerosol microphysical module that simulates particle size distributions with a synthesis of several existing cloud-microphysical schemes that predict mass and number of various hydrometeor classes, including the formation of precipitation. It involves an numerical integrator with user-defined accuracy and adaptive time-stepping enabling accurate treatment of the short timescale processes involved.
The Active Tracer High Resolution Atmospheric Model (ATHAM) of Graf, Herzog and coworkers is used to simulate cloud formation in both warm and mixed-phase clouds. I will present initial results describing warm-rain formation using a new two-moment (mass and number) approach and a single-moment mixed phase scheme. The schemes have been tested within a single-parcel framework and within a 2D version of ATHAM.
Earth Observation for Quantifying Eco-hydrological Fluxes and Inter-Relations (The Konya Closed Basin, Turkey)
ITC, Faculty of Geo-information Science and Earth Observation (firstname.lastname@example.org)
Disproportional water demand and use in semi-arid regions cause serious environmental consequences such as degradation of natural vegetation, draining of wetlands, desertification, depletion of groundwater resources, soil erosion and salinization. This figure keeps worsening globally in the semi-arid regions considering the increasing population and the related demand on water by human activities.
Located in central part of Turkey, the Konya Closed Basin represents a typical case for semi-arid regions with an average yearly precipitation of 380 mm and potential evapotranspiration of 1200 mm. Agricultural activity (both dry and irrigated) is dominant in the basin, posing high human pressure on the limited surface and groundwater resources. Besides, there are important natural sites with high ecological value in the upstream and downstream of the basin. Environmental degradation occurred over the last decade; from significantly declining groundwater tables to drying out wetlands and desertification problems. However, hydrological and environmental variables, and the interaction between them have not been quantified spatio-temporally yet to get a holistic insight into the human-hydrology-ecology dynamics in the basin.
Main objective of this research study is to effectively utilize earth observation methods to quantify the hydrological fluxes and environmental variables in the Konya closed basin spatio-temporally and with good accuracy. It is further aimed to quantitatively analyze the long term eco-hydrological relations/changes at regional and local scale through integrating remote sensing, field and time-series analysis techniques.
EarthCARE: The Earth Cloud, Aerosol and Radiation Explorer Mission
Beatriz Garcia Bernal
European Space Agency (Beatriz.Garcia.Bernal@esa.int)
Clouds, aerosols, and convection are factors that determine the radiation balance and the Earth temperature, directly influencing the precipitation and controlling the hydrological cycle. The difficulties in representing these factors in numerical models limit the ability to obtain accurate weather forecasts and reliable predictions of future climate.
The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) mission is one of the Earth Explorers of the ESA´s Earth Observation Envelope Program (EOEP). This joint European-Japanese mission will help in understanding the interactions between clouds, aerosols and radiation and improving their parametrization in climate and Numerical Weather Prediction models by providing detailed global observations of vertical cloud and aerosol profiles.
EarthCARE´s approach combines the measurements of two active instruments: an atmospheric lidar for the aerosols and thin clouds, and a high frequency doppler radar for clouds; with the observations of two passive instruments: a multi-spectral imager for cross-track coverage of aerosol and cloud optical properties and a broad-band radiometer to measure radiances, which can be converted into fluxes. These instruments will be employed in a synergistic way.
ESA is developing the EarthCARE Simulator (ECSIM) to provide an End-to-End simulation environment to allow the scientific community to early assess the system and instruments performance by improving the current engineering and scientific models and algorithms.
Sub-pixel stereo matching using the phase correlation method for the extraction of cloud top heights from AATSR
Mullard Space Science Laboratory (email@example.com)
Clouds play a significant role in the Earths energy balance and climate. Cloud fraction and cloud top heights (CTH) are, therefore, important inputs into climate models.
Numerous methods are employed to determine CTH and cloud fraction, one of the most effective is the use of parallax from multi-view sensors with stereo capabilities. Stereo derivation of CTH requires no ancillary information and can be resolved purely from the geometry of a stereo-pair of images. The current predominant method for image matching involves the use of area based correlation methods. An example being the M4 matcher which is effective at deriving CTH and is very fast, however this method only operates at pixel level acuity. The M4 matcher is also susceptible to image noise and areas of low contrast, which is a problem common across all cross correlation methods.
These drawbacks lead to a degradation of the quality of the CTH and cloud fraction products derived for input into climate models. The work presented in this poster will show an improved method for the derivation of CTH using phase correlation as the image matching technique, a method which is robust against image noise and areas of low contrast and also provides sub-pixel accuracy.
Aboveground biomass retrieval in tropical forests - the potential of synergistic X- and L-band SAR data use
RSS GmbH (firstname.lastname@example.org)
In the context of reducing emissions from deforestation and forest degradation (REDD) projects and the international effort of reducing anthropogenic greenhouse gas emissions, the assessment of aboveground forest biomass is very important, as forests (especially tropical forests) store a huge amount of carbon. This study investigates the potential of X- and L-band SAR data to estimate aboveground biomass in intact tropical forests and degraded forest areas in Indonesia. The main study site is located in Central Kalimantan and another study area in West Kalimantan on Borneo, Indonesia. LIDAR (light detection and ranging) derived aboveground biomass data were related to TerraSAR-X and ALOS PALSAR backscatter values, analyzing the mono- and multi-temporal as well as single-frequency and synergistic relationships. The relationships were independently validated and the temporal and spatial transferability was demonstrated. The results show that synergistic models are more accurate than single-frequency ones and mono-temporal models are less accurate than multi-temporal ones. In contrast to previous studies, the models are valid up to a maximum of 600 t/ha, but with increasing biomass there is a decrease in the accuracy of these biomass predictions. The overall accuracy of these models is mainly influenced by radiometric accuracy and error propagation of LIDAR derived aboveground biomass predictions.
The Role of Structural, Biochemical and Ecophysiological Plant Acclimation in the Eco-Hydrologic Response of Agro-Ecosystems to Global Change in the Central US
University of Illinois (email@example.com)
Recent field campaigns at the SoyFACE Free Air Carbon Enrichment (FACE) facility in central Illinois have provided clear evidence of the modification of structural, biochemical and ecophysiological properties of key agricultural species at CO2 concentrations projected for the middle of this century. While these acclamatory responses have been linked to changes in leaf-level gas exchange and leaf states (ie. leaf temperature and stomatal conductance), determining the implications for these changes at the canopy-scale has remained a challenge. Here we present a simulation analysis, using the multi-layer MLCan canopy-root-soil system model, that examines the role of observed plant acclimation in two key mid-west US agricultural species, soy (C3 photosynthetic pathway) and corn (C4 photosynthetic pathway). Model skill in capturing the sub-diurnal variability in canopy-atmosphere fluxes is demonstrated using multi-year records of eddy covariance CO2, water vapor and heat fluxes collected at the Bondville (Illinois) AmeriFlux site. FACE observations are used to examine the ability of the model to capture future changes in plant ecophysiological functioning. An analysis of the combined acclamation effects at 550 [ppm CO2] on carbon dioxide uptake, surface energy partitioning and vegetation water use are presented for both crops.
Analysis of temperature maps of water bodies obtained from ASTER TIR images
University of Modena and Reggio Emilia, (firstname.lastname@example.org)
The ASTER sensor is, currently, the main radiometer that acquires information in the Thermal Infrared (TIR) region with a spatial resolution of 90 m. The purpose of this work is to develop a working methodology for the analysis of water temperature obtained from ASTER images. Images were initially processed with an algorithm that improves spatial resolution from 90 m to 30 m using information drawn from the Visibile-Near infrared (VNIR) ASTER bands. Then data were analyzed and classified with an object-oriented approach. Specific procedures were developed in order to automate the monitoring process and to better interpret and display water temperature of the analyzed images. The studies were performed both on images at 90 m and at 30 m (computed with the algorithm for improving the spatial resolution). In this way it was possible to test the effectiveness and validity of the algorithm. For example, watercourses in the image at 90 m were barely visible while in the image at 30 m can be easily analyzed.
This study is not concluded: the procedures will be soon applied to a wider range of case studies. Thus it will be possible to verify the versatility of the procedures themselves, and the advantages from the use of the algorithm for improving the spatial resolution.
Data assimilation and targeting : Observability and positioning of the sensitivity functions
Association francophone pour le savoir (ACFAS) (email@example.com)
Data assimilation combines information from the global observation system and a background forecast to establish the initial conditions of numerical prediction models. Its restriction to the unstable subspace generated by leading singular vectors makes the method compatible with existing computing resources and allow identification of sensitivity functions related to error amplification.
Our research objective is to develop an assimilation algorithm to correct the positioning of sensitivity functions. To succeed, we need to characterize the influence of the interaction of planetary and synoptic waves on the evolution of singular vectors, especially their phase, but also to circumvent the feeble signal to noise ratio of the initial sensitivity functions. We propose to establish the necessary evolving time for sensitivity functions to become observable and then assimilate measurement information on their structure. Foreseen improvements are two-fold: identifying well positioned sensitive area to target supplementary observations and adapting a priori covariances to include a flow dependent structure function component.
The poster will present the the 4D-Var algorithm, the unstable subspace structure, its relation to targeting and some issues on observability.
Sub-pixel Precision Image Matching for Displacement Measurement of Mass Movements Using Normalised Cross-Correlation
University of Oslo (firstname.lastname@example.org)
This study evaluates the performance of two fundamentally different approaches to achieve sub-pixel precision of normalised cross-correlation when measuring surface displacements on mass movements from repeat optical images. In the first approach, image intensities are interpolated to a desired sub-pixel resolution using a bi-cubic interpolation scheme prior to the actual displacement matching. In the second approach, the image pairs are correlated at the original image resolution and the peaks of the correlation coefficient surface is then located at the desired sub-pixel resolution using three techniques, namely bi-cubic interpolation, parabola fitting and Gaussian fitting. Both principal approaches are applied to three typical mass movement types: rockglacier creep, glacier flow and rock sliding. Their performance is evaluated in terms of matching accuracy and in reference to the images of the resolution they are expected to substitute. Our results show that intensity interpolation using bi-cubic interpolation (first approach) performs best followed by bi-cubic interpolation of the correlation surface (second approach). Both Gaussian and parabolic peak locating perform weaker. By increasing the spatial resolution of the matched images by intensity interpolation using factors of 2 to 16, 40% to 80% reduction in mean error could be achieved in reference to the same resolution original image.
Method to remove illumination effects from multispectral satellite images of mountain areas without using a digital elevation model
Space Agency at DLR (German Aerospace Center) (email@example.com)
Optical satellite images of mountain areas generally show effects of slope orientation: slopes facing the sun appear much brighter than other surfaces. Therefore, a topographic normalisation should generally be carried out before the spectral behaviour of the earth surface is examined, e.g. for land cover studies. For this purpose, an adequate digital elevation model (DEM) is indispensable. The spatial resolution of the DEM should at least be as good as the spatial resolution of the satellite image.
However, accurate high-resolution DEMs of high-mountain areas are often quite expensive or not available at all. Therefore, a method was developed to cope with illumination effects in a Landsat-TM image of parts of the European Alps which is not based on a DEM. Based on three satellite image layers, the IHS (Intensity-Hue-Saturation) transformation was used to concentrate illumination differences in one layer and produce three transformed image layers not showing these differences. This method is explained, and advantages and drawbacks are outlined.
Predicting Impact of Climate Change on Intra-annual Groundwater Dynamics
Vrije Universiteit Brussel (firstname.lastname@example.org)
Dept. of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium Climate models predict for North-West Europe a significant rise in potential evapotranspiration (PET) while the precipitation is expected to increase during winter but to decrease during summer. Changes in PET and precipitation directly influence groundwater recharge, which is on its turn controlling the availability of groundwater. Because the groundwater system is of major importance for drinking water availability and is vital for the ecological value of many nature reserves it is important to assess the sensitivity of the groundwater system to possible climate change scenarios. Here we show that for a lowland catchment in Belgium groundwater discharges are expected to decrease during late summer and autumn while simulations for winter and early spring period fluctuate around the groundwater discharge simulated for the reference period 1960-1991. While a decrease in groundwater head is predicted from September to January, the total groundwater reserves of the basin seem to decrease only slightly due to climate change. As groundwater dependent terrestrial ecosystems (GWDTE) are influenced by temporal dynamics of the groundwater systems, we suggest close monitoring of those GWDTE to prevent ecological loss due to climate change.
In-flight Spectral Performance Monitoring of an Imaging Spectrometer
Remote Sensing Laboratories, University of Zurich (email@example.com)
Spectral performances of airborne imaging spectrometers cannot be assumed to be stable over a whole flight season given the environmental stresses present during flight. Spectral performance monitoring during flight is commonly accomplished by so called scene-based approaches, looking at selected absorption features present in the sun, atmosphere, or ground, and their stability. The assessment of instrument performance in two different environments, e.g., laboratory and airborne, using precisely the same calibration reference, has not been possible so far. APEX, an airborne dispersive pushbroom imaging spectrometer, uses an onboard In-Flight Characterization (IFC) facility that allows monitoring the overall sensor?s performance stability on-ground and in-flight. We present a new method for the monitoring of spectral shifts by comparing instrument-induced movements of absorption features. Absorption lines originate from spectral filters, which intercept the full Field of View illuminated using an internal light source. A feature-fitting algorithm is used for the shift estimation based on the optimization of a cost function. Environmental parameter monitoring, co-registered on board with the image and calibration data, were fundamental for the understanding of the instrument behavior. These findings provided the necessary indications for the realization of instrument design changes, aimed at minimizing the effects we have investigated.
Sea Surface Temperature Measurement with the Sea and Land Surface Temperature Radiometer
Sea surface temperature (SST) is an essential climate variable, needed to track any changes in both global mean temperature and ocean circulation patterns. A long-term (19 year), global dataset of SST has been made possible with the Along Track Radiometer (ATSR) series of instruments (ATSR-1, ATSR-2 and Advanced ATSR). Currently SST retrievals are performed with an accuracy of 0.3K, made possible due to the dual-view capabilities of the ATSR instruments. This dataset will be continued with the future launch of the Sea and Land Surface Temperature Radiometer (SLSTR) which is part of ESA?s Sentinel 3 program. SLSTR has several improvements over previous ATSR instruments, while still maintaining consistency for the long term climate record. For example, there are additional channels for fire detection and improved cloud clearing. A description of SLSTR is presented, including information on SST retrieval methods, specific design features and scientific justification.
Validation of Atmospheric CO2 and CH4 retrieved from GOSAT
Human activities such as fossil fuel combustion and land use change have led to a dramatic increase in atmospheric CO2 and CH4 concentrations since a pre-industrial age [IPCC, 2007]. Networks of surface in situ greenhouse gas sensors provide accurate measurements of the global greenhouse gas concentrations and their large scale temporal, seasonal and latitudinal variations. However, these are too sparse to allow the establishment of sub-continental carbon budgets and key questions remain unresolved, limiting the accuracy of future climate change forecasts and the ability to manage future levels of atmospheric CO2 and CH4. Satellites observations, if acquired with high accuracy and precision, have the potential to overcome such limitations by providing globally densely-sampled datasets of column CO2 and CH4. The first observations of greenhouse gases from a dedicated satellite sensor are now available with the launch of the Japanese Greenhouse gases Observing SATellite (GOSAT) on 23 January 2009. GOSAT provides global measurements of total column CO2 and CH4 from its shortwave infrared (SWIR) bands and of mid-tropospheric sub-columns from its thermal-IR bands. Here we present the validation for retrievals of CO2 and CH4 columns from the GOSAT SWIR channels against observations of the Total Column Carbon Observation Network (TCCON).
Measurements of spatial variability of rain drop size distribution
Institute Environmental Sciences University Castilla-La Mancha (firstname.lastname@example.org)
The spatial variability of the raindrop size distribution (RDSD) at kilometer scale is analyzed for five events of precipitation using the experimental estimations provided by a network of laser disdrometers. The main conclusion is that variability of RDSD in a single event, represented by the spatial variability of the moments of the distribution, could be as large as variability between the different events. This result is relevant to ground based radars and precipitation satellite radars, as TRMM-PR or GPM-DPR, because the quantitative precipitation estimation rely on information contained on RDSD. Also is useful for numerical weather prediction models and regional climate models whose the parametrizations schemes typically require analytical forms of RDSD.
Recreating an Icy Past; Modelling the Quaternary Galtrim Moraine
National University of Ireland Maynooth (National Centre for Geocomputation & Dept. of Geography) (email@example.com)
This work sets out to ultimately reconstruct a model of the glacial past of Ireland centred around Galtrim, Co. Meath. This is an important area comprising a complex system of depositional features of the late Quaternary period in Ireland. Moraines formed at the margins of the ice sheet in a NE-SW alignment and locate an area where there was a temporarily stabilised halt in the recession of the ice. It is also associated with well defined esker systems and related to pro-glacial Lake Summerhill where delta moraines formed. Much of the research in this area and indeed on much of the glacial deposits in Ireland has been largely from a geomorphological point of view. The reconstruction of the glacial evolution in this region and the subsequent deglacial processes are greatly constrained because of the lack of 3?dimensional morphology for this area and furthermore because sedimentalogical studies have not been conducted in this area due to lack of exposure. In order to address these challenges in trying to recreate an inclusive model for this period, techniques which have been used only sparingly so far in investigations of this nature in Ireland will be implemented and combined. Geophysical investigations and remote sensing analysis are discussed in terms of their usefulness and expected value. Preliminary results of resistivity and ground penetrating radar fieldwork are examined with particular reference to training sites including forward modelling and initial time lapse resistivity work. Plans and ideas for continued work on the area are introduced and discussed.
CONDOR Seamount (SW Faial Island, Azores): Time Variability using Ocean Colour and SST imagery variability from 2002 to 2010
Department of Oceanography and Fisheries (U. Azores) (firstname.lastname@example.org)
In the framework of CONDOR Project (PT-0040 EEA Grant), nine years of MODIS-derived near-surface Ocean Colour (OC or chlorophyll a concentrations in mg m-3) and Sea Surface Temperature (SST in °C) imagery are used to study surface temporal variability around Condor Seamount (SW of Faial Island, Azores). Condor rises from 1500-2000 m to 200 m depth at its elongated summit. This study uses monthly and seasonal 1-km resolution MODIS/Aqua OC and SST imagery for the Condor area (38.2 º N - 38.8 º N; 28.5 º W - 29.4 º W) (60 x 90 pixels) from years 2002 to 2010. Daily MODIS images were obtained at the Ocean Colour Web Level 1/2 browser (NASA/GSFC) and processed at DOP/UAz with HAZO system. Monthly and seasonal variability is evident for both OC and SST with highest OC concentrations observed during spring and lowest during summer, while SST increase from May to August and decrease onwards. Ocean Colour maximum and minimum averages range between 0.6554 and 0.0705 mg m-3 on May and September 2004, respectively, and between 0.4684 and 0.0907 mg m-3 during spring 2003 and autumn 2008, respectively. For SST these range between 23.9976 and 14.7065°C on August 2008 and March 2010, respectively, and between 22.7588 and 15.5742°C during summer 2003 and spring 2010, respectively. High inter-annual variability is also evident, with monthly averages indicating a general trend of decreasing SST and increasing OC with time, while seasonal OC averages show a pronounced decreasing trend. Ocean Colour and SST seasonal anomalies reveal nearly inverse patterns with positive OC anomalies associated to negative SST anomalies. These results suggest the influence of the North Atlantic Oscilation (NAO) on Condor seamount dynamics. Further analyses will be extended to further investigate this relationship.
Science Ground Segment for ESA Solar System missions: Mars Express and Venus Express
Alejandro Cardesin Moinelo
This work shows a summary of the activities performed by the author in the past years in the framework of the ESA Solar System division, in particular focused on the development and implementation of the Science Ground Segments of the planetary missions Venus and Mars Express, and comparison with the Earth Observation missions.
The first part of the work presented here is a description of the activities performed for the Mars Express Science Ground Segment, within the Science Operations Deparment at ESAC-Madrid. A summary is given for the science operations planning of the spacecraft and its experiments, taking into account the scientific observation requests from the Principal Investigators and the operational and technical constraints from the mission operations team.
The second part of the research shown here covers the work performed in collaboration with IASF-INAF Rome for the development of the data processing chain of the VIRTIS imaging spectrometer onboard Venus Express, with an overview of the individual activities of data generation, calibration and archiving of the instrument, including the final high level scientific products produced with valuable information for atmospheric studies, like analysis of the thermal profiles, airglow emissions and cloud morphology all over the planet.
Methane Emissions from Wetlands and Rice Paddies Inferred from Satellite Observations of Methane and Gravity
A Anthony Bloom
University of Edinburgh (email@example.com)
Wetlands and rice paddies account for up to half the total atmospheric methane (CH4) source, but the magnitude and distribution of these sources are poorly understood on continental scales. We isolated the wetland and rice paddy contributions to spaceborne CH4 measurements over 2003?2005 (SCIAMACHY) using satellite observations of gravity anomalies (GRACE), a proxy for water-table depth, and surface temperature analyses (NCEP/NCAR re-analyses). We find that tropical and higher-latitude CH4 variations are largely described by gravity and temperature variations, respectively. We also find that tropical wetlands account for more than half of global wetland emissions. Our work suggests a 7% rise in wetland CH4 emissions over 2003?2007, mostly due to warming of mid-latitude and Arctic wetland regions, which we find is consistent with recent trends in atmospheric CH4.
Storm surge forecast in Venice through an hydrodynamic model
Consorzio Venezia Ricerche (firstname.lastname@example.org)
Since the end of 2002 a finite element hydrodynamic model, called SHYFEM, is operational at the Office for the tidal forecast of the Venice municipality (ICPSM). It solves the 2D shallow water equations in a computational grid of the Mediterranean Sea. Wind and atmospheric pressure fields, provided by the ECMWF Centre, are used as forcing. Since December 2007 a routine for a local data assimilation, based on the use of an Artificial Neural Network (ANN), is also operational. The routine runs after the hydrodynamic model. The input data are the modeled surge forecast, several level observations and model errors, estimated for the day before each run. The ANN provide a new estimation of the surge in one location near the Venice lagoon. Database composed by observations and model results for the years 2003, 2004, 2005 have been used for the training phase. The testing phase was made with a database of 2006 and the validation with one of 2007. Results of this simple assimilation procedure show a double of the accuracy for short term forecast ( about 1 day), and good improvements also for the next days.
GERB: measuring the Earth's energy balance
Royal Meteorological Institute of Belgium (RMI) (email@example.com)
Since December 2002, the Geostationary Earth Radiation Budget (GERB) instrument has been a science 'passenger' on the European Meteosat Second Generation satellites. This broad-band radiometer makes accurate (up to 50km resolution) and rapid (every 15 minutes) measurements of the radiation coming from the Sun and the outgoing Earth radiation to space. The resulting energy balance provides important information on climate forcing and feedback mechanisms such as clouds, aerosols and water vapour.
The aim of this study is to improve the current GERB image processing, especially in the field of geolocation and resolution enhancement. Also, the development of an objective analysis system to estimate near real-time radiative fluxes and its use in climatology and weather modeling applications are discussed.
Monitoring of the Antarctic middle atmosphere by microwave radiometry
British Antarctic Survey/University of Cambridge (firstname.lastname@example.org)
The British Antarctic Survey (BAS) microwave radiometer is a ground-based instrument that simultaneously observes nitric oxide (NO) and ozone (O3) in the middle atmosphere (25-90km). It has collected two years of data (February 2008 ? January 2010) from Troll station, Antarctica (72°S, 1.5°E, 1275m asl). My research focuses on the retrieval and application of the ozone profiles. The main aim of my research is to retrieve a high temporal resolution ozone dataset above Antarctica, which can be used for the calibration of satellite measurements. Observations will be validated against ozonesonde launches from Neumayer station, Antarctica (70°S, 8°W) and compared to satellite data from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and Microwave Limb Sounder (MLS). They will also be used to confront atmospheric chemistry models with observations; in particular the ozone data will be used to assess the performance of the Sodankyläon Chemistry (SIC) model under solar minimum conditions when energetic particle precipitation impacts on stratospheric ozone are expected to be small. To date we have retrieved ozone data at 1-hour and 15-minute resolution for 2008 days 080-094 and compared observations against the SIC model.
Significance of cloud coverage in the creation of a database over the Tropics for forest estimates
European Space Agency (email@example.com)
In spite of the importance of forests for the global climate, our knowledge of the state and changes of forests over the last two decades remains surprisingly limited.
The European Space Agency, with its TropForest project (funded by the ESA?s Data User Element), is teaming up with the JRC?s ACTION 3 - TREES (funded by the EC 7th Research Framework Program), also called TREES-3 project, and with the FAO?s UN-REDD to have a joint action on the estimates of forests cover changes and degradation in the tropical forests of Latin America and South East Asia.
The TropForest project will at first create an harmonized remote sensing orthorectified/pre-processed imagery geo-database based on satellite data acquisitions (ALOS AVNIR-2, DMC DEIMOS-1, KOMPSAT-2 MSC) performed during the years 2009 and 2010.
This poster presents the status of the database, discusses the use of the different satellite sensors, and identifies the problematic areas related to cloud coverage in the tropics for forest estimates.
Least Dependent Component Analysis for trace gases retrieval from satellite data
Recent research has proved that hyperspectral satellite observations can be successfully used to map atmospheric trace gases throughout the planet and that an appropriate processing of the retrieved information is, in turn, essential for understanding the global environmental changes.
Several techniques have been developed for the retrieval of the major atmospheric and pollution constituents; among them, Differential Optical Absorption Spectroscopy (DOAS) is the most widely used approach.
The contribution of this work moves from the consideration that a more robust and precise analysis can be carried out if the observed spectral waveform is more thoroughly exploited.
We propose a new technique that mainly consist of a semi-blind recovery of concentrations and pure spectra from their linear mixtures. This decomposition is based on the Least Dependent component Analysis (LDA) technique, a method, generalizing the well known Independent Component Analysis, to find least dependent components, after a proper preprocessing for reducing some residual dependencies.
We also show some results related to the retrieval of sulphur dioxide volcano emission using data from the NASA Ozone Monitoring Instrument (OMI).