ALBERT

Description: Following the launch of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009, SMOS soil moisture products need to be rigorously validated at the satellite's approximately 45 km scale and disaggregation techniques for producing maps with finer resolutions tested. The Australian Airborne Cal/val Experiments for SMOS (AACES) provide the basis for one of the most comprehensive assessments of SMOS data world-wide by covering a range of topographic, climatic and land surface variability within an approximately 500 × 100 km2 study area, located in South-East Australia. The AACES calibration and validation activities consisted of two extensive field experiments which were undertaken across the Murrumbidgee River catchment during the Australian summer and winter season of 2010, respectively. The datasets include airborne L-band brightness temperature, thermal infrared and multi-spectral observations at 1 km resolution, as well as extensive ground measurements of near-surface soil moisture and ancillary data, such as soil temperature, soil texture, surface roughness, vegetation water content, dew amount, leaf area index and spectral characteristics of the vegetation. This paper explains the design and data collection strategy of the airborne and ground component of the two AACES campaigns and presents a preliminary analysis of the field measurements including the application and performance of the SMOS core retrieval model on the diverse land surface conditions captured by the experiments. The data described in this paper are publicly available from the website: http://www.moisturemap.monash.edu.au/aaces.

Description: A Land Data Assimilation System (LDAS) able to ingest surface soil moisture (SSM) and Leaf Area Index (LAI) observations is tested at local scale to increase prediction accuracy for water and carbon fluxes. The ISBA-A-gs Land Surface Model (LSM) is used together with LAI and the soil water content observations of a grassland at the SMOSREX experimental site in southwestern France for a seven-year period (2001–2007). Three configurations corresponding to contrasted model errors are considered: (1) best case (BC) simulation with locally observed atmospheric variables and model parameters, and locally observed SSM and LAI used in the assimilation, (2) same as (1) but with the precipitation forcing set to zero, (3) real case (RC) simulation with atmospheric variables and model parameters derived from regional atmospheric analyses and from climatological soil and vegetation properties, respectively. In configuration (3) two SSM time series are considered: the observed SSM using Thetaprobes, and SSM derived from the LEWIS L-band radiometer located 15m above the ground. Performance of the LDAS is examined in the three configurations described above with either one variable (either SSM or LAI) or two variables (both SSM and LAI) assimilated. The joint assimilation of SSM and LAI has a positive impact on the carbon, water, and heat fluxes. It represents a greater impact than assimilating one variable (either LAI or SSM). Moreover, the LDAS is able to counterbalance large errors in the precipitation forcing given as input to the model.

Description: The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data of global coverage every three days. Product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and soil temperature sensor network was established in the Skjern River Catchment, Denmark. The objectives of this article are to describe a method to implement a network suited for SMOS validation, and to present sample data collected by the network to verify the approach. The design phase included (1) selection of a single SMOS pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes representing the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature and precipitation between the north-east and south-west were found to be small. A first comparison between the 0–5 cm network averages and the SMOS soil moisture (level 2) product is in range with worldwide validation results, showing comparable trends for SMOS retrieved soil moisture (R2 of 0.49) as well as initial soil moisture and temperature from ECMWF used in the retrieval algorithm (R2 of 0.67 and 0.97, respectively). While retrieved/initial SMOS soil moisture indicate significant under-/overestimation of the network data (biases of −0.092/0.057 m3 m−3), the initial temperature is in good agreement (bias of −0.2 °C). Based on these findings, the network performs according to expectations and proves to be well-suited for its purpose. The discrepancies between network and SMOS soil moisture will be subject of subsequent studies.

Description: The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data globally, and thus product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and temperature network of Decagon ECH2O 5TE capacitance sensors was established in the Skjern River Catchment, Denmark. The objectives of this article are to describe a method to implement a network suited for SMOS validation, and to present sample data collected by the network to verify the approach. The design phase included (1) selection of a single SMOS pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes representing the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature and precipitation between the north-east and south-west were found to be small. A first comparison between the 0–5 cm network averages and the SMOS soil moisture (level 2) product is in range with worldwide validation results, showing comparable trends for SMOS retrieved/initial soil moisture and initial temperature (R2 of 0.49/0.67 and 0.97, respectively). While retrieved/initial soil moisture indicate significant under-/overestimation of the network data (biases of −0.092/0.057 m3 m−3), temperature is in good agreement (bias of −0.2 °C). Consequently, the network performs according to expectations and proves to be well-suited for its purpose. The discrepancies between network and SMOS soil moisture will be subject of subsequent studies.

Description: A Land Data Assimilation System (LDAS) able to ingest surface soil moisture (SSM) and Leaf Area Index (LAI) observations is tested at local scale to increase prediction accuracy for water and carbon fluxes. The ISBA-A-gs Land Surface Model (LSM) is used together with LAI and the soil water content observations of a grassland at the SMOSREX experimental site in southwestern France for a seven-year period (2001–2007). Three configurations corresponding to contrasted model errors are considered: (1) best case (BC) simulation with locally observed atmospheric variables and model parameters, and locally observed SSM and LAI used in the assimilation, (2) same as (1) but with the precipitation forcing set to zero, (3) real case (RC) simulation with atmospheric variables and model parameters derived from regional atmospheric analyses and from climatological soil and vegetation properties, respectively. In configuration (3) two SSM time series are considered: the observed SSM using Thetaprobes, and SSM derived from the LEWIS L-band radiometer located 15 m above the ground. Performance of the LDAS is examined in the three configurations described above with either one variable (either SSM or LAI) or two variables (both SSM and LAI) assimilated. The joint assimilation of SSM and LAI has a positive impact on the carbon, water, and heat fluxes. It represents a greater impact than assimilating one variable (either LAI or SSM). Moreover, the LDAS is able to counterbalance large errors in the precipitation forcing given as input to the model.

Description: Following the launch of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009, SMOS products need to be rigorously validated at the satellite's approximately 45 km scale, and disaggregation techniques for maps with finer resolutions tested. The Australian Airborne Cal/val Experiments for SMOS (AACES) provide the basis for one of the most comprehensive assessments of SMOS data world-wide by covering a range of topographic, climatic and land surface variability within an approximately 500 × 100 km2 study area, located in South-East Australia. The AACES calibration and validation activities consisted of two extensive field experiments which were undertaken across the Murrumbidgee River catchment during the Australian summer and winter season of 2010, respectively. The data sets include airborne L-band brightness temperature, thermal infrared and multi-spectral observations at 1 km resolution, as well as extensive ground measurements of near-surface soil moisture and ancillary data, such as soil temperature, soil texture, surface roughness, vegetation water content, dew amount, leaf area index and spectral characteristics of the vegetation. This paper explains the design and data collection strategy of the airborne and ground component of the two AACES campaigns and presents a preliminary analysis of the field measurements including the application and performance of the SMOS core retrieval model on the diverse land surface conditions captured by the experiments. The data described in this paper are publicly available from the website: http://www.moisturemap.monash.edu.au/aaces.