Using the Special Sensor Microwave/Imager to Monitor Land Surface Temperatures, Wetness, and Snow Cover

Basist, Alan; Grody, Norman C.; Peterson, Thomas C.; Williams, Claude N.

doi:10.1175/1520-0450(1998)037<0888:utssmi>2.0.co;2

Cited by 164 publications

(92 citation statements)

References 29 publications

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“…Therefore the range goes from 0 to 100, where 100 means the entire surface is liquid water (Basist et al 1998). This index is derived from a linear relationship between channel measurements (Equation 1), where a channel measurement is the value observed at a particular frequency and polarization (i.e.…”

Section: Surface Wetness (Bwi)mentioning

confidence: 99%

Assessing the Economic and Political Impacts of Climate Change on International River Basins Using Surface Wetness in the Zambezi and Mekong Basins

et al. 2014

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Resource Data Incorporated, Asheville, North Carolina, USA Terms of use: Documents inMany river basins will likely face higher hydrologic variability, including extreme floods and droughts, due to climate change, with economic and political consequences. Water treaties that govern international basins could face non-compliance among riparians and inter-state tensions as hydrologic variability increases. Accurate monitoring of water resources is essential to cope with these fluctuations in flow. This paper demonstrates a simple yet robust procedure-the Basist Wetness Index-to predict gauge station (actual water resources) measurements of surface wetness values derived from satellite data (for 1988-2013) and empirically derived flow distributions in two international river basins: Zambezi and Mekong. The paper further undertakes an economic analysis (applied to the Mekong), which identifies not only the economic costs and losses due to extreme flow events, but likewise showcases the benefits countries could potentially reap should they be able to make use of such flow data in real time. An illustrative application, using the wetness data and socio-political data, is also performed to highlight the utility of the procedure for research in the field of conflict and cooperation over water. The paper concludes that satellite data modeled with gauge station flow can help reduce the uncertainty inherent in negotiating international water issues. Moreover, the satellite observations can provide near real time monitoring of water resources, and provide valuable lead time for impending droughts and floods. Thus, the approach presented in the article can assist policy makers to devise more efficient and cooperative institutional apparatus.

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Section: Surface Wetness (Bwi)mentioning

confidence: 99%

Assessing the Economic and Political Impacts of Climate Change on International River Basins Using Surface Wetness in the Zambezi and Mekong Basins

et al. 2014

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“…Many of the algorithms developed for AMSU derive from past experiences acquired with SSM/I (Special Sensor Microwave Imager) (Ferraro et al, 1986 andTeng et al, 1993;Scofield and Achutuni, 1996;Lakshmi et al, 1997;Prigent et al, 1997;Basist et al, 1998 andWilliam et al, 2000), which is the radiometer aboard DMSP (Defence Meteorological Satellite Program) satellites (Hollinger et., 1997).…”

Section: The Advanced Microwave Sounding Unit (Amsu)mentioning

confidence: 99%

“…Primarily, adding water into a soil produces a decrease in the surface emissivity (Lakshmi et al, 1997), precisely, for the same soil water content, the emissivity is higher for higher frequencies (Prigent et al, 1997). Specifically, the slope between the low and high frequencies directly responds to the amount of the radiating surface that is liquid water (Basist et al, 1998, andWilliam et al, 2000).…”

Section: The Advanced Microwave Sounding Unit (Amsu)mentioning

confidence: 99%

“…Then the microwave emissivity of wet soil in each pixel can be calculated as (Basist et al, 1998;Songyan et al, 2000):…”

Section: The Advanced Microwave Sounding Unit (Amsu)mentioning

confidence: 99%

“…As the fractional amount of wet land increases, the emissivity decreases and its difference between low and high frequencies increases (Basist et al, 1998). In this sense, a combination of two properly selected window AMSU channels may give us useful information about superficial emissivity variations (Songyan et al, 2000;Grody, 2002 1 ).…”

Section: The Advanced Microwave Sounding Unit (Amsu)mentioning

confidence: 99%

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Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Lacava

Greco

Leo

et al. 2005

Nat. Hazards Earth Syst. Sci.

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Abstract. Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltrationrunoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weatherrelated satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards.Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques.Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past.Correspondence to: N. Pergola (pergola@imaa.cnr.it)In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the SWVI was able to identify the presence of a sort of "early" signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability.

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Estimation of Surface Soil Moisture Using Microwave Sensors

Jackson

2005

Encyclopedia of Hydrological Sciences

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Soil moisture has been particularly difficult to measure and map using conventional ground‐based point sampling. Microwave remote sensing–based soil moisture retrieval has been demonstrated using tower and aircraft instruments. The translation of this approach to satellites and the implementation in hydrologic applications has been limited by both the technology and the satellite systems that were available. Recent developments in both science and associated technologies now make the exploitation of the microwave region for soil moisture mapping feasible. A number of new and potential satellite missions are reviewed and evaluated for soil moisture applications.

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Using the Special Sensor Microwave/Imager to Monitor Land Surface Temperatures, Wetness, and Snow Cover

Cited by 164 publications

References 29 publications

Assessing the Economic and Political Impacts of Climate Change on International River Basins Using Surface Wetness in the Zambezi and Mekong Basins

Assessing the Economic and Political Impacts of Climate Change on International River Basins Using Surface Wetness in the Zambezi and Mekong Basins

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Estimation of Surface Soil Moisture Using Microwave Sensors

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