Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR)

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R-2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments

The ASCAT soil moisture product: a review of its specifications, validation results, and emerging applications

Many physical, chemical and biological processes taking place at the land surface are strongly influenced by the amount of water stored within the upper soil layers. Therefore, many scientific disciplines require soil moisture observations for developing, evaluating and improving their models. One of these disciplines is meteorology where soil moisture is important due to its control on the exchange of heat and water between the soil and the lower atmosphere. Soil moisture observations may thus help to improve the forecasts of air temperature, air humidity and precipitation. However, until recently, soil moisture observations had only been available over a limited number of regional soil moisture networks. This has hampered scientific progress as regards the characterisation of land surface processes not just in meteorology but many other scientific disciplines as well. Fortunately, in recent years, satellite soil moisture data have increasingly become available. One of the freely available global soil moisture data sets is derived from the backscatter measurements acquired by the Advanced Scatterometer (ASCAT) that is a C-band active microwave remote sensing instrument flown on board of the Meteorological Operational (METOP) satellite series. ASCAT was designed to observe wind speed and direction over the oceans and was initially not foreseen for monitoring soil moisture over land. Yet, as argued in this review paper, the characteristics of the ASCAT instrument, most importantly its wavelength (5.7 cm), its high radiometric accuracy, and its multiple-viewing capabilities make it an attractive sensor for measuring soil moisture. Moreover, given the operational status of ASCAT, and its promising long-term prospects, many geoscientific applications might benefit from using ASCAT soil moisture data. Nonetheless, the ASCAT soil moisture product is relatively complex, requiring a good understanding of its properties before it can be successfully used in applications. To provide a comprehensive overview of the major characteristics and caveats of the ASCAT soil moisture product, this paper describes the ASCAT instrument and the soil moisture processor and near-real-time distribution service implemented by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). A review of the most recent validation studies shows that the quality of ASCAT soil moisture product is – with the exception of arid environments –comparable to, and over some regions (e.g. Europe) even better than currently available soil moisture data derived from passive microwave sensors. Further, a review of applications studies shows that the use of the ASCAT soil moisture product is particularly advanced in the fields of numerical weather prediction and hydrologic modelling. But also in other application areas such as yield monitoring, epidemiologic modelling, or societal risks assessment some first progress can be noted. Considering the generally positive evaluation results, it is expected that the ASCAT soil moisture product will increasingly be used by a growing number of rather diverse land applications.The Austrian Science Fund (FWF) through the Vienna Doctoral Programme on Water Resource Systems (http://www.waterresources.at/,DK-plusW1219-N22

BioSimulators: a central registry of simulation engines and services for recommending specific tools

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations

Circumpolar Scaling Layer for downscaling of Scatterometer derived soil moisture with links to geotiff images and NetCDF files (2005-01 to 2011-12)

This dataset provides scaling information applicable to satellite derived coarse resolution surface soil moisture datasets following the approach by Wagner et al. (2008). It is based on ENVISAT ASAR data and can be utilized to apply the Metop ASCAT dataset (25 km) for local studies as well as to assess the representativeness of in-situ measurement sites and thus their potential for upscaling. The approach based on temporal stability (Wagner et al. 2008) consists of the assessment of the validity of the coarse resolution datasets at medium resolution (1 km, product is the so called 'scaling layer')

An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations

The scatterometers onboard the European Remote Sensing satellites (ERS-1 ERS-2) and the METeorological OPerational satellite (METOP) have been shown to be useful for surface soil moisture retrieval using the so-called TU-Wien change detection method. This paper presents an improved soil moisture retrieval algorithm based on the existing TU-Wien method but with new parameterization as well as a series of modifications. The new algorithm, WAter Retrieval Package 5 (WARP5), copes with some limitations identified in the earlier method WARP4 and provides the possibility of migrating soil moisture retrieval from ERS-SCAT to METOP-ASCAT data. The WARP5 algorithm results in a more robust and spatially uniform soil moisture product, thanks to its new processing elements, including a method for the correction of azimuthal anisotropy of backscatter, a comprehensive noise model, and new techniques for calculation of the model parameters. Cross-comparisons of WARP4 and WARP5 data sets with the Oklahoma Mesonet in situ observations and also with European Centre of Medium Range Weather Forcast (ECMWF) ReAnalysis (ERA-Interim) global modeled data show that the new algorithm has a better performance and effectively corrects retrieval errors in certain areas. © 2006 IEEE.1999201315European Organization for the Exploitation of Meteorological SatellitesAustrian Science Fund (FWF

Multi-source satellite data facilitating disaster management during the 2003 forest fires in Portugal

After devastating forest fires in central Portugal in July and August 2003 forced the Portuguese government to declare a public calamity for the affected districts, the "International Charter on Space and Major Disasters" was activated on August 4, 2003. For this Charter Call (No. 43) the project management was taken over by the German Aerospace Center (DLR). For monitoring forest fires and burned areas in near-real-time, satellite images from different sensors were ordered, processed, geocorrected and partially analysed. A large scale overview was realised with NOAA-AVHRR, TERRA-MODIS, ENVISAT-MERIS and BIRD imagery. For a more detailed survey of the worst affected areas, SPOT and IKONOS imagery were used. The feedback from the local authorities shows that the combination of satellite imagery with different spatial and temporal resolutions can effectively facilitate on-site crisis management

Analysis of C-Band Scatterometer Moisture Estimations Derived Over a Semiarid Region

International audienceSpatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport, and vegetation productivity. Their characterization offers numerous possibilities for the improvement of our understanding of complex land-surface-atmosphere interactions. In this paper, soil moisture dynamics at the soil's surface (the first centimeters) and in its root zone (at depths down to 1 m) are investigated using 25 × 25 km2 scale data (Advanced Scatterometer (ASCAT)/METorological OPerational (METOP) scatterometer), for a semiarid region in North Africa. Our study highlights the quality of the surface and root-zone soil moisture products, derived from ASCAT data recorded over a two-year period. Surface soil moisture tends to be highly variable because it is strongly influenced by atmospheric conditions (rain and evaporation). On the other hand, rootzone moisture is considerably less variable. A statistical droughtmonitoring index, referred to as the "moisture anomaly index," is derived from ASCAT and European Remote Sensing (ERS) time series. This index was tested with ERS and ASCAT products during the 1991-2010 study period. A strong correlation is found between the proposed index and the standardized precipitation index