. In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu ) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

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The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

ESA CCI Soil Moisture for improved Earth system understanding : State-of-the art and future directions

Trend-preserving blending of passive and active microwave soil moisture retrievals

Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe

Evaluation of the ESA CCI soil moisture product using ground-based observations

A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from low-frequency passive microwave observations. The error estimate is based on a basic error propagation equation which uses the partial derivatives of the radiative transfer equation and estimated errors for each individual input parameter. Results similar to those of the Monte Carlo approach show that the developed time-efficient methodology could substitute computationally intensive methods. This procedure is therefore a welcome solution for near-real-time data assimilation studies where both the soil moisture product and error estimate are needed. The developed method is applied to the C-, X-, and Ku-bands of the Aqua/Advanced Microwave Scanning Radiometer for Earth Observing System sensor to study differences in errors between frequencies.

Error Estimates for Near-Real-Time Satellite Soil Moisture as Derived From the Land Parameter Retrieval Model

Two different remotely sensed land surface temperature (T s) products are compared with in situ observations from the National Airborne Field Experiment research site in the western part of the Murrumbidgee catchment, Australia. The remotely sensed T s products are retrieved from the following: 1) Ka-band passive microwave (MW) observations using several of space-based MW radiometers and 2) thermal infrared observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) on two satellite platforms. Both methods show similar accuracy when compared to ground observations, although the dynamic range and mean differ significantly. However, a direct comparison of the two products at the same overpass time reveals a strikingly constant relation, with a standard error of ~ 4 K. The results of this study indicate that a merged T s product of both MODIS and MW observations is feasible and would decrease the amount of data gaps and increase the sampling frequency for this region to 12 observations a day.

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R. M. Parinussa

Papers

Error Estimates for Near-Real-Time Satellite Soil Moisture as Derived From the Land Parameter Retrieval Model

Comparison of Microwave and Infrared Land Surface Temperature Products Over the NAFE'06 Research Sites