H-SAF soil moisture products based on METOP-ASCAT scatterometer data Stefan Hasenauer (1), Wolfgang Wagner (1), Barbara Zeiner (2), Alexander Jann (2),

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H-SAF soil moisture products based on METOP-ASCAT scatterometer data Stefan Hasenauer (1), Wolfgang Wagner (1), Barbara Zeiner (2), Alexander Jann (2), Patricia de Rosnay (3), Clement Albergel (3) (1) Institute of Photogrammetry and Remote Sensing (TU Wien), Vienna, Austria (2) Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria (3) European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK EGU General Assembly Vienna, 6 April 2011

 Satellite Application Facility (SAF) in a nutshell  Requirements on satellite soil moisture  Product characteristics and generation chains Large-scale soil moisture Downscaled soil moisture Assimilated soil moisture  Recent validation activities and results In-situ measurements Hydrological model data  Conclusions Contents EGU, 6 April 2011H-SAF Soil Moisture 2

EUMETSAT SAF Overview  SAF: Satellite Application Facility  Specialization on topics and themes  Providing products and services to users  Part of the EUMETSAT application ground segment  Location: at the Weather Services in EUMETSAT Member and Co-operating States 3 EGU, 6 April 2011

EUMETSAT SAF Overview 4 SAF Continuous Development and Operations Phase ( )Initial Operations PhaseDevelopment Phase SAF Project SAF in support to Nowcasting & Very Short Range Forecasting SAF on Ocean and Sea Ice SAF on Ozone and Atmospheric Chemistry Monitoring SAF on Numerical Weather Prediction SAF on Climate Monitoring SAF on GRAS Meteorology SAF on Land Surface Analysis H-SAF EGU, 6 April 2011H-SAF Soil Moisture

H-SAF in a nutshell  Project timeline: Sep Mar 2012  Consortium: Host institute: Italian Meteorological Service EUMETSAT member states and 4 cooperating states  Main satellite sensors: Meteosat MSG and Metop ASCAT  Total of 13 products: Precipitation products (liquid, solid, rate, cumulative) Soil moisture products (at surface, downscaled, in roots region) Snow products (cover, melting conditions, water equivalent) 5 EGU, 6 April 2011H-SAF Soil Moisture

 Application and users (Operational) Hydrology, Climate monitoring  Spatio-temporal resolution Near real-time, Europe  Specification Standardized file formats: BUFR, GRIB  Characterisation Validation programmes, EUMETSAT reviews User Requirements EGU, 6 April End-user requirements for soil moisture products Test sites hydrological validation

 Instrument Advanced Scatterometer  Frequency 5.26 GHz (C-Band)  Polarisation VV  Spatial Resolution 25/50 km  Temporal Resolution 8-15 files/day over Europe, full coverage within 1.6 days  Data format BUFR, native EPS METOP ASCAT EGU, 6 April 2011H-SAF Soil Moisture 7

Soil Moisture Products: SM-OBS-3 8  Large-scale surface soil moisture observed by radar scatterometer (TU-Wien/ZAMG) Sensor: METOP-ASCAT Cycle: 36 hours for full coverage over Europe Resolution: 25 km, Timeliness: 130 min (potentially 30 min using the EARS service) Dissemination: EUMETCast Format: BUFR

 Small-scale surface soil moisture observed by radar scatterometer (TU-Wien/ZAMG) Sensor: METOP-ASCAT, together with ENVISAT ASAR Cycle: 36 hours for full coverage over Europe Resolution: Basic 25 km, sampling to 1 km Timeliness: ~130 min Format: BUFR Concept: Temporal stability of backscatter with ENVISAT ASAR (C-Band) SM-OBS-2 EGU, 6 April

 Volumetric soil moisture (roots region) by assimilation in NWP model (ECMWF) Sensor: METOP-ASCAT Format: GRIB (regular reduced Gaussian grid or latitude/longitude grid) Content: 4 different soil layers (covering the root zone from the surface to 2.9m) Cycle: 24 hours Resolution: 23 km Timeliness: 36 hours SM-DAS-2 EGU, 6 April

 Ground based systems (in-situ) Single campaign datasets Continuous monitoring sites  e.g. ISMN (International Soil Moisture Network)  Modelled data Hydrological model data Soil-vegetation-atmosphere-transfer model  Inter-comparison with other satellite products Active vs. passive microwave products Validation Approaches EGU, 6 April 2011H-SAF Soil Moisture 11

SM-OBS-3 vs. in-situ and model  Continuous rainfall-runoff model (MISDc)  Upper Tiber River, Italy  Assimilation improves runoff prediction H-SAF Soil Moisture 12 Results with and without ASCAT SWI* assimilation for the NIC (a, b) catchment in the period Jan-2007 – Jun-2009: a) observed rainfall and simulated saturation degree; b) observed versus simulated discharge for the sequence of the most significant flood events occurred in the period. Brocca, L., F. Melone, et al. (2010): "Improving runoff prediction through the assimilation of the ASCAT soil moisture product" Hydrol. Earth Syst. Sci. (14), doi: /hessd

SM-OBS-2 vs. model  Filtered and bias-corrected ASCAT data Bibeschbach-catchment in Luxembourg, 16 probes  ASCAT has potential to help monitoring how river systems approach critical thresholds, operational perspective 13 EGU, 6 April 2011H-SAF Soil Moisture Matgen P., S. Heitz, S. Hasenauer, C. Hissler, L. Brocca, L. Hoffmann, W. Wagner, H. Savenije: „On the potential of METOP ASCAT-derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg” (submitted)

 South-western France R=0.85, bias =0.104, RMSE=0.195 Relative error = m 3 m -3 SM-DAS-2 vs. in-situ EGU, 6 April SM-DAS-2 (0-7 cm) vs. in-situ (5 cm) R (-) Bias (-) RMSE (-) SBR URG CRD PRG CDM LHS SVN MNT SFL MTM LZC NBN Courtesy of C. Albergel (ECMWF)

In-situ data source  Freely available, online data viewer H-SAF Soil Moisture 15

 SM-OBS-3 (large-scale)  SM-OBS-2 (small-scale)  SM-DAS-1 (assimilated) Validation compliance EGU, 6 April 2011H-SAF Soil Moisture 16

Conclusions  H-SAF: new satellite soil moisture products for Europe Large-scale soil moisture (surface, relative index, BUFR):01 May 2009 – now Downscaled soil moisture (with ENVISAT ASAR, BUFR): 22 Sep 2009 – now Assimilated soil moisture (root zone, GRIB):01 Jul 2008 – 31 Aug 2010  Validated datasets First results with in-situ and hydrological model data comparison Further work ongoing with hydrological model data/data assimilation  Challenges and research needs File sizes and large amount of data sets Investigating spatial variability and error characterisation of scaling approaches  H-SAF project web-page:  International Soil Moisture Network:  Stefan Hasenauer: H-SAF Soil Moisture 17 EGU, 6 April 2011

H-SAF Soil Moisture 18

Backup slides EGU, 6 April 2011H-SAF Soil Moisture 19

SM-OBS-3 vs. in-situ and model  ASCAT considered reliable, well reproduced the in-situ ‚observed‘ temporal pattern.  SWI correlation coefficients R >0.90  RMSE <0.035 m³/m³ (linear rescaled) H-SAF Soil Moisture 20 Simulated saturation degree for a layer depth of 3 cm versus the three ASCAT saturation degree products, ms, SWI, and SWI* and for the three investigated sites: a) Vallaccia, b) Cerbara, and c) Spoleto Brocca, L., F. Melone, et al. (2010): "ASCAT soil wetness index validation through in situ and modeled soil moisture data in central Italy“, Remote Sensing of Environment 114(11): doi: /j.rse

SM-OBS-3 vs. SIM H-SAF Soil Moisture 21 Draper, C., Mahfouf, J.-F., Calvet, J.-C., and Martin, E. (2010): Assimilation of ASCAT soil moisture products into the SIM hydrological platform. Final Report for the H-SAF Associated Scientist Program (AS09_01), 50 p. Maps of the mean (left) and standard deviation (right) of the near-surface soil moisture (m3m-3) from January 2007 to May 2010, from SIM (left) and ASCAT (right).

SM-OBS-2 vs. In-situ H-SAF Soil Moisture 22 Green: Development Phase, Red: Recent

Results Development Phase H-SAF Soil Moisture 23

Results Development Phase H-SAF Soil Moisture 24

Downscaling concept  Temporal stability (Vachaud et al., 1985) Local soil moisture is often highly correlated with the regional soil moisture Soil moisture patterns tend to persist in time  Hypothesis Temporally stable soil moisture patterns lead to temporally stable radar backscatter patterns (Wagner et al., 2008) time domain reflectometry (TDR) stations (5 cm depth), Duero basin (Spain) and their mean (bold black diamonds),

Downscaling of ASCAT SM-OBS-2 26 Pre-processing ASAR Processing ASCAT 1 km 25 km In near real-time (<2 h) at ZAMG Irregular, offline EGU, 6 April 2011H-SAF Soil Moisture

Downscaling of ASCAT SM-OBS-2 27 Correlation between local and regional ASAR GM backscatter Left: SM-OBS-1 (25 km ASCAT), right: SM-OBS-2 (1 km downscaled surface soil moisture). No-data values are masked and given a quality flag information. ASAR GM coverage of European Database (March 2011) Applying linear regression model: DSSM(local) = c + d * SSM(regional), where: DSSM…downscaled surface soil moisture; c,d…intercept, slope; SSM……surface soil moisture resampled.

Hydrological downscaling  Fingerprint-method, from Blöschl et al EGU, 6 April 2011 Blöschl, G., Komma, J., Hasenauer, S. (2009): Hydrological downscaling of soil moisture. Final report of the Visiting Scientist Activity to the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). 64 p.

 Blöschl, G., Komma, J., Hasenauer, S. (2009): “Hydrological downscaling of soil moisture”. Final report of the Visiting Scientist Activity to the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). 64 p.  Draper, C., Mahfouf, J.-F., Calvet, J.-C., and Martin, E. (2010): Assimilation of ASCAT soil moisture products into the SIM hydrological platform. Final Report for the H-SAF Associated Scientist Program (AS09_01), 50 p.  Vachaud, G., A. Passerat de Silans, P. Balabanis, M. Vauclin (1985): Temporal Stability of Spatially Measured Soil Water Probability Density Function, Soil Sci. Soc. Am. J., 1985, 49,  Wagner, W., C. Pathe, M. Doubkova, D. Sabel, A. Bartsch, S Hasenauer, G. Blöschl, K. Scipal, J. Martínez-Fernández, A. Löw (2008): Temporal stability of soil moisture and radar backscatter observed by the Advanced Synthetic Aperture Radar (ASAR), Sensors, 8, References EGU, 6 April 2011H-SAF Soil Moisture 29