Climatology Meteorology Atmosphere
This ASCAT Multi-parameter product contains surface wind vectors over ocean and soil moisture index over land. Additionally, the backscatter values involved in the retrieval of the geophysical parameters above are also included, as well as several quality flags to facilitate the use of the data. For NWP users this product is provided in BUFR format. The netCDF version of this product contains Winds ONLY. For users interested in either ASCAT backscatter, wind or soil moisture index data in other formats, please refer to the relevant product entries available for the specific parameters. Finally, note that although the OSI SAF is identified as the originating centre for this product, it is not responsible for the processing of soil moisture index values, which is currently carried out at EUMETSAT. The product archive (EUMETSAT Data Centre and the SAF archive) stopped on 28 April 2015, when the product was discontinued. Please note that the product has been replaced by the ASCAT Coastal Winds (EO:EUM:DAT:METOP:OSI-104). Better than using this archived NRT product, please use the reprocessed ASCAT winds data records (EO:EUM:DAT:METOP:OSI-150-A, EO:EUM:DAT:METOP:OSI-150-B).
ASCAT Winds and Soil Moisture at 12.5 km Swath Grid - Metop
geossDataCore
geossNoMonetaryCharge
geossuserRegistration
geossAttribution
FedEO
EARTH SCIENCE>LAND SURFACE
EARTH SCIENCE>AGRICULTURE>SOILS>SOIL MOISTURE/WATER CONTENT
METOP-A
METOP-B
ASCAT
Metop-A
Metop-B
Land
Ocean
Ocean Surface Wind
Radar Backscatter NRCS
Soil Moisture
Avenue de Lorraine, BP 50747
France
EUMETSAT/OSISAF

Climatology Meteorology Atmosphere
This ASCAT Multi-parameter product contains surface wind vectors over ocean and soil moisture index over land. Additionally, the backscatter values involved in the retrieval of the geophysical parameters above are also included, as well as several quality flags to facilitate the use of the data. For NWP users this product is provided in BUFR format. The netCDF version of this product contains Winds ONLY. For users interested in either ASCAT backscatter, wind or soil moisture index data in other formats, please refer to the relevant product entries available for the specific parameters. Finally, note that although the OSI SAF is identified as the originating centre for this product, it is not responsible for the processing of soil moisture index values, which is currently carried out at EUMETSAT.
ASCAT Winds and Soil Moisture at 25 km Swath Grid - Metop-C
geossDataCore
geossNoMonetaryCharge
geossuserRegistration
geossAttribution
FedEO
EARTH SCIENCE>LAND SURFACE
EARTH SCIENCE>AGRICULTURE>SOILS>SOIL MOISTURE/WATER CONTENT
METOP-A
METOP-B
ASCAT
Metop-A
Metop-B
Land
Ocean
Ocean Surface Wind
Radar Backscatter NRCS
Soil Moisture
Avenue de Lorraine, BP 50747
France
EUMETSAT/OSISAF

Climatology Meteorology Atmosphere
Winds at all heights below the tropopause in the polar regions (latitudes higher than 55Âº), derived from the METOP AVHRR instrument IR 10.8 channel. Atmospheric motion vectors (AMVs) are a valuable observation type for providing dynamical information for forecast models.Metop-A data are available in the Data Centre up to 15/11/2021.
AVHRR Atmospheric Motion Vectors - Metop - Polar
geossDataCore
geossNoMonetaryCharge
geossuserRegistration
geossAttribution
FedEO
EARTH SCIENCE>ATMOSPHERE
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC WINDS
METOP-A
METOP-B
AVHRR
Metop-A
Metop-B
Atmosphere
Wind
EUMETSAT Allee 1
Germany
EUMETSAT

Winds at all heights below the tropopause in the polar regions (latitudes higher than 55Âº), derived from the METOP AVHRR instrument IR 10.8 channel. Atmospheric motion vectors (AMVs) are a valuable observation type for providing dynamical information for forecast models.Metop-A data are available in the Data Centre up to 15/11/2021.
AVHRR Atmospheric Motion Vectors (BUFR) - Metop - Polar
EARTH SCIENCE>ATMOSPHERE
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC WINDS
AVHRR
Atmosphere
Wind
Level 2 Data
EUMETSAT Allee 1
Germany
EUMETSAT

Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
RAL Space, STFC Rutherford Appleton Laboratory, Harwell Campus
United Kingdom
CEDA
This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. The global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.The SCFG time series provides daily products for the period 1979-2023. The product V4.0 is based on EUMETSAT Fundamental Data Record (FDR) medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the CLARA-A3 cloud product. The retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by MetsÃ¤mÃ¤ki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 Âµm and 1.61 Âµm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 Âµm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied using dynamic reference reflectance values (snow, forest, ground) temporally and spatially adapted to consider angle dependencies (sun, view). Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. The following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground. RMSE is retrieved from a statistical model and added as pixel-wise information. The SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.The Remote Sensing Research Group of the University of Bern, in cooperation with Gamma Remote Sensing is responsible for the SCFG product development and generation. ENVEO (ENVironmental Earth Observation IT GmbH) developed and prepared all auxiliary data sets used for the product generation.The SCFG AVHRR product comprises a few data gaps in 1979 â 1986 (1979: 22.-24.Feb.; 01.-07.Oct.; 03.-04.Nov.; 07.Nov.; 17.-18.Nov.; 1980: 22.-27.Feb.; 01.March; 03.March; 15.-20.March; 30.March â 02.April; 26.-29.June; 12.-19.July; 12.-18.Dec.; 1981: 09.-11.May; 01.-03.Aug.; 14.-23.Aug.; 1982: 28.- 31.May; 25.-26. Oct.; 1983: 27.- 31. July; 01.- 02. and 06. Aug.; 1984: 14.-15.Jan.; 06. Dec.; 1985: 01.- 24.Feb; 1986: 15. March), resulting in a 99% data coverage over the entire study period of 43 years.
ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from AVHRR (1979 - 2023), version 4.0
Under the following licence appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
The snow_cci SCFG product based on AVHRR was developed and processed at the University of Bern in the frame of ESA CCI+ Snow project. The AVHRR baseline FCDR was pre-processed using pyGAC and pySTAT in the frame of the ESA CCI Cloud project (Devasthale et al. 2017). The final product is quality checked.Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).
Devasthale, A. et al. PyGac: An open-source, community-driven Python interface to preprocess nearly 40-year AVHRR Global Area Coverage (GAC) data record. Quarterly 11, 3â5 (2017).
Wu, Xiaodan; Naegeli, Kathrin; Premier, Valentina; Marin, Carlo; Ma, Dujuan; Wang, Jingping; Wunderle, Stefan (2021). Evaluation of snow extent time series derived from Advanced Very High Resolution Radiometer global area coverage data (1982â2018) in the Hindu Kush Himalayas. The Cryosphere, 15(9), pp. 4261-4279. Copernicus Publications
MetsÃ¤mÃ¤ki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann, A., Solberg R. and Ripper, E. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment, 156, 96â108.
EUMETSAT, 2023b. PyGAC Fundamental Data Record Algorithm Theoretical Basis Document.
Karlsson, K.-G., Stengel, M., Meirink, J.F., RiihelÃ¤, A., Trentmann, J., Akkermans, T., Stein, D., Devasthale, A., Eliasson, S., Johansson, E., HÃ¥kansson, N., Solodovnik, I., Benas, N., Clerbaux, N., Selbach, N., SchrÃ¶der, M., Hollmann, R., 2023. CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023. Earth Syst. Sci. Data 15, 4901â4926.
EARTH SCIENCE>CLIMATE INDICATORS>CRYOSPHERIC INDICATORS>SNOW COVER
EARTH SCIENCE>SPECTRAL/ENGINEERING>INFRARED WAVELENGTHS
METOP-C
TIROS-N
AVHRR
Metop-C
Level 3C
snow
Public data: access to these data is available to both registered and non-registered users.
ESA
CCI
Snow
Snow Cover Fraction
orthoimagery
Unavailable

Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
Rutherford Appleton Laboratory, Harwell
United Kingdom
CEDA
The CCI SST Analysis Product consists of daily, spatially complete fields of SST, obtained by combining the orbit data from the AVHRR (Advanced Very High Resolution Radiometer) and ATSR (Along Track Scanning Radiometer) Long Term products, using optimal interpolation to provide SSTs where there were no measurements (a single file per day; 0.05Â° regular latitude- longitude grid). These data start in September 1991. The SSTs correspond approximately to the daily average of the temperature of the water at 20 cm depth. Uncertainty estimates are provided for each value.The data are stored in NetCDF-4 format files. Data arrays in NetCDF files are known as âvariablesâ and each variable has metadata stored with it. Please read the ESA CCI SST Product User Guide, available in the linked documentation before using the data. There is also a Quick Start Guide.
The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010, using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research.The ESA SST CCI Analysis Long Term Product consists of daily, spatially complete fields of sea surface temperature (SST), obtained by combining the orbit data from the AVHRR and ATSR ESA SST CCI Long Term Products, using optimal interpolation to provide SSTs where there were no measurements. These data cover the period between 09/1991 and 12/2010.The Version 1.1 data is an update of the Version 1.0 dataset.Version 1.0 of this dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20
ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Analysis long term product version 1.1
Under the following licence appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were processed by the ESA CCI SST project team and supplied to CEDA by the UK Met Office.
EARTH SCIENCE>OCEANS>OCEAN TEMPERATURE>SEA SURFACE TEMPERATURE
EARTH SCIENCE>SPECTRAL/ENGINEERING>INFRARED WAVELENGTHS
ENVISAT
ATSR
AATSR
Environmental Satellite
Metop
Envisat
Level 4
sea surface temperature
sea water temperature
day
OSTIA
ERS
Advanced Along-Track Scanning Radiometer
Along Track Scanning Radiometer - 2
Along Track Scanning Radiometer - 1
Advanced Very High Resolution Radiometer - 1
Public data: access to these data is available to both registered and non-registered users.
SST
CCI
orthoimagery
Unavailable

Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
Rutherford Appleton Laboratory, Harwell
United Kingdom
CEDA
The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.The v05.3 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.The data set should be cited using all three of the following references:1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-20192. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.0013. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 05.3
Under the following licence appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project
Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001
Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-2019
EARTH SCIENCE>SPECTRAL/ENGINEERING>RADAR
EARTH SCIENCE>AGRICULTURE>SOILS>SOIL MOISTURE/WATER CONTENT
ERS WIND SCATTEROMETER
ASCAT
AMI-SCAT
AMI/Scatterometer
Public data: access to these data is available to both registered and non-registered users.
ESA
Soil Moisture
CCI
Active
orthoimagery
Unavailable

Rutherford Appleton Laboratory, Harwell
This dataset contains Level 3 nadir profile ozone data from the ESA Ozone Climate Change Initiative (CCI) project. The Level 3 data are monthly averages on a regular 3D grid derived from level 2 ozone profiles. In this version 2 of the dataset, data are available for 1997 and 2007 and 2008 only, and use data from the GOME instrument on ERS (1997) and the GOME-2 instrument on METOP-A (2007, 2008).
ESA Ozone Climate Change Initiative (Ozone CCI): Level 3 Nadir Ozone Profile Merged Data Product, version 2
Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC CHEMISTRY>OXYGEN COMPOUNDS>ATMOSPHERIC OZONE
ENVISAT
Aura
OMI
SCIAMACHY
GOME
Environmental Satellite
EOS
Metop
Royal Netherlands Meteorological Institute
ozone
Level 3
Envisat
MERGED
ozone nadir profile
month
ERS
SCanningÂ ImagingÂ Absorption spectroMeter forÂ Atmospheric CHartographY
Global Monitoring of Atmospheric Ozone
Ozone Monitoring Instrument
Global Monitoring of Atmospheric Ozone - 2
ESA
ESA/CCI

This dataset is a monthly mean gridded total ozone data record (level 3) produced by the ESA Ozone Climate Change Initiative project (Ozone CCI). The dataset is a prototype of a merged harmonised ozone data record combining ozone data from the GOME instrument on ERS-2, the SCIAMACHY instrument on ENVISAT and the GOME-2 instrument on METOP-A, and covers the period between April 1996 to June 2011.
ESA Ozone Climate Change Initiative (Ozone CCI): Level 3 Total Ozone Merged Data Product, version 01
Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC CHEMISTRY>OXYGEN COMPOUNDS>ATMOSPHERIC OZONE
ENVISAT
SCIAMACHY
GOME
Environmental Satellite
Metop
Deutsches Zentrum fuer Luft- und Raumfahrt
Level 3S
ozone
Level 3
Envisat
MERGED
day
ozone total column
ERS
SCanningÂ ImagingÂ Absorption spectroMeter forÂ Atmospheric CHartographY
Global Monitoring of Atmospheric Ozone
Global Monitoring of Atmospheric Ozone - 2
ESA/CCI

The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.The v05.2 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.The data set should be cited using all three of the following references:1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-20192. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.0013. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 05.2
Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project. This dataset forms part of the ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection. doi: 10.5285/b11f3fa3303e46e6b0d44b058947a3f5. http://dx.doi.org/10.5285/b11f3fa3303e46e6b0d44b058947a3f5 .
Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001
Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-2019
EARTH SCIENCE>CLIMATE INDICATORS>LAND SURFACE/AGRICULTURE INDICATORS>SOIL MOISTURE
EARTH SCIENCE>SPECTRAL/ENGINEERING>MICROWAVE
EARTH SCIENCE>SPECTRAL/ENGINEERING>RADAR
Aqua
CORIOLIS
DMSP 5D-2/F8
DMSP 5D-2/F11
DMSP 5D-2/F13
SMOS
TRMM
ERS WIND SCATTEROMETER
MIRAS
AMSR-E
SMMR
SSM/I
TMI
WINDSAT
soil moisture
Coriolis
AMI-SCAT
SMAP
AMSRE
WindSat
AQUA
AMI/Scatterometer
Combined