SCIRoCCo runs an educational programme aimed at fostering the next-generation scatterometer community.

Grants, stages, and training initiatives related to scatterometer data exploitation and evolution have been set up with special consideration to proposals and activities based on scatterometry and showing innovation and cross-domain applicability (e.g. Land, Oceanography).

• Download Introduction to the Spaceborne Scatterometry
• Ocean Winds
  • Scatterometer Winds | EUMeTrain
  • Assimilation of Scatterometer Winds | EUMeTrain
  • Satellite Derived Ocean Surface | EUMeTrain
  • Hurricanes over the Atlantic | EUMeTrain
  • The Xynthia Storm by ASCAT | EUMeTrain
• Ocean Winds - Other Resources
  • Download Advances in Microwave Remote Sensing: Ocean wind speed and direction (20.2 MB zip)
  • Download Using scatterometer wind and altimeter wave estimates in marine forecasting (76.3 MB zip)
  • Download Introduction to tropical meteorology (533.3 MB zip)
  • EUMETSAT/IODE Training Course - video lectures
• Sea Ice
  • Download Introduction to sea ice: Process, Observations and Model (11.4 MB PDF)
• Soil Moisture
  • Lecture materials about the TU-Wien soil moisture retrieval from C-band fan-beam scatterometer
  • Download the Tutorials complementing the lectures (32.4 MB zip)
  • Download the entire Soil Moisture educational material (47.9 MB zip)

Title: Examining the validity of ERA-Interim for tropical hurricanes over the course of time

Author: Tim Bijsterbosch (KNMI, 2016)

Abstract: Validity of ERA-Interim for tropical hurricanes over the course of time is examined. ERA-Interim is a reanalysis which uses one of the leading weather prediction models to reforecast the state of the atmosphere several times per day. This means that the only thing that changes the way ERA-Interim calculates these reforecasts are the input measurements used as initial state, which improves in quantity and quality with time. To examine if the validity of ERA-Interim for tropical hurricanes also improves with time the 10 m height wind product modeled by ERA-Interim will be compared to 10 m height wind product derived from satellite observations over a period of time. The satellite observations which are used are from the ERS-2 (1996 – 2001) and ASCAT (2007 – 2014) scatterometers.

Title: Neural-network based sea/ice discrimination using ERS scatterometer data

Author: Khaoula Hmamouche (RMA, 2015)

Abstract:  The primary objective of the scatterometer is to determine the wind fields over oceans using empirical Geophysical Model Functions (GMF). These models are only valid over open sea, they are not valid over land and sea-ice. Land is easily discarded using land masks. Over sea-ice it is more difficult to discriminate open water and the ice due to the dynamic extent of the sea-ice which result from the freezing and melting through the seasons. So as to remove spurious wind vectors we have to discriminate the sea and the ice at a real time.
A neural-network has been developed, to compute the sea/ice probability P(H1|mc) at each
node of the grid. (where: H1 is the hypothesis the measurement corresponds to ice, given the measurement vector mc =(Cc; n), n is the node number in which the measurement Cc was made).
Some criteria can be used such as: derivative of sigma, backscatter isotropy, distance to the wind model and distance to ice model. This work is an attempt to enhance the sea-ice detection algorithm by adding other criteria while the stateless strategy will be the same.

Title: Comparison of ERS-2 ESCAT sea backscattering coefficients with electromagnetic models of sea surface scattering and other empirical models under challenging geophysical conditions

Author: Federica Aveta (SERCO/Sapienza/KNMI, 2016)

Abstract: Rain effect can distort the signal and cause errors in the wind retrieval. In fact, rain modifies the measured radar cross section in several ways and the most important rain effects are the splash effects and the atmospheric effects. Rain modifies the ocean surface by impinging on it with an increase of the surface roughness due to the generation of the ring waves and with an induced wave damping due to the generation of an upper turbulence layer. Meanwhile rain modifies the scatterometer signal when it passes through the atmosphere by attenuating it and by increasing the signal due to volume scattering.
The electromagnetic model Small Slope Approximation up to the second order (SSA2), that simulates the ocean surface backscattering coefficient, has been modified by including these rain effects. The splash effects, i.e. generation of ring waves and rain-induced wave damping [6], that modify the ocean surface roughness, have been considered by modifying the Elfouhaily sea wind wave spectrum in the region of the capillary waves.

Title: Daily vegetation modelling to improve the ERS ESCAT soil moisture retrieval (27.7 MB PDF)

Author: Dorothea Ko (TU Wien, 2016)

Abstract: Soil moisture is a crucial driver for many physical, chemical and biological processes and feedback loops taking place at the land surface and within the atmosphere. Thus soil moisture becomes an important parameter to understand and forecast earth climate changes and was added to the list of Essential Climate Variables (ECV) in 2010. A feasible global implementation of soil moisture retrieval is the physically motivated empirical change detection method developed at TU-Wien (Wagner, Lemoine, et al., 1999; Wagner, Noll, et al., 1999).

Title: Comparison of satellite soil moisture products, models and on-site observation by triple / quadruple collocation including ERS-ESCAT data over H-SAF region (Europe) and "globally" (for ESCAT regional scenario)

Author:  Fabio Fascetti (TU Wien/SERCO/Sapienza, 2016)

Abstract: The first part of this research activity was carried out at the Technical University of Wien (TU Wien, Research Group Remote Sensing, Department for Geodesy and Geoinformation) for a period of three months, starting by March 2016, and it was continued at Sapienza University of Rome, until August 2016. The managing institution was Serco S.p.A. and Sapienza University. The aim of this work was to assess the quality of soil moisture products provided by active and passive satellite sensors, as ERS-2 ESCAT and SMOS data, in order to consolidate current methodologies for scatterometer data processing and calibration. For such purpose, several techniques, as Triple (TC) and Quadruple (QC) collocation, were used.

Title: Diurnal difference in retrieved scatterometer soil moisture (23.3 MB PDF)

Author: Romina Messner  (TU Wien, 2016)

Abstract: This activity focuses on the evaluation and comparison of three different soil moisture products over the USDA Watershed in the period from January 2010 to July 2011. Soil moisture products investigated in this study are derived from: the Soil Moisture Ocean and Salinity (SMOS) mission, the scatterometer (ESCAT) on board of the European Remote Sensing Scatterometer (ERS-2) and in-situ stations. For the scatterometer are used data products at nominal resolution (~50 km) and at high resolution (~25 km) developed by TU Wien, and for the radiometer are used the data developed with processor version v620. The in-situ stations data have been downloaded from the International Soil Moisture Network (ISMN) and Natural Resources Conservation Service (NRCS), without considering the soil moisture products at Hawaii islands.

Title: Comparison of satellite soil moisture products, models and on-site observation by intercomparison of ERS-ESCAT vs SMOS over the USDA Watershed in the period January 2010 / July 2011

Author: Ivano  Rossicone (TU Wien/SERCO/Sapienza, 2016)

Abstract: This activity focuses on the evaluation and comparison of three different soil moisture products over the USDA Watershed in the period from January 2010 to July 2011. Soil moisture products investigated in this study are derived from: the Soil Moisture Ocean and Salinity (SMOS) mission, the scatterometer (ESCAT) on board of the European Remote Sensing Scatterometer (ERS-2) and in-situ stations. For the scatterometer are used data products at nominal resolution (~50 km) and at high resolution (~25 km) developed by TU Wien, and for the radiometer are used the data developed with processor version v620.