2012 AGU Chapman Conference on Remote Sensing of the ...

demonstrate that effective roughness parameters are apromising tool for soil moisture retrieval, both for bare soilsand soils underlying wheat vegetation throughout the entiregrowth cycle.Lin, Yao-ChengRemote Sensing of Soil Moisture with Signals ofOpportunityLin, Yao-Cheng 1 ; Garrison, James 1 ; Cherkauer, Keith 11. Purdue university, West Lafayette, IN, USAAbstract Measurement of soil moisture is very essentialfor studying the hydrological cycle. Passive microwaveradiometry is the most mature technology for the remotesensing of soil moisture, as demonstrated on ESA’s SMOSsatellite and the upcoming SMAP mission from NASA. L-band (1.4GHz) is the frequency used for thesemeasurements, a compromise between the required antennasize and the sensitivity to soil moisture. The frequenciesselected for SMOS and SMAP also enjoy strong isolationfrom radio frequency interference (RFI) in bands protectedfor radio astronomy. L-band radiometry, however, onlysenses the moisture within the top few cm of the soil andrequires a relatively large antenna to meet requirements onsurface resolution. Recently, alternative approaches tomeasure soil moisture, through reflectometry of GlobalNavigation Satellite System (GNSS-R) signals have beendemonstrated, both from airborne receivers and groundbasedtowers. This paper will present a study on theextension of reflectometry techniques to other satellitetransmissions, so-called “signals of opportunity” (SoOp).Recent experiments in ocean remote sensing have shownthat the methods developed for GNSS-R can be applied tosome digital satellite transmission, demonstrated on the S-band (2.3 GHz) signals from the XM radio satellites.Presently, an experiment is being prepared to test the use ofSoOp for soil moisture sensing, making use of high-powersatellite transmissions on frequencies both above and belowthose protected in L-band. This combination of frequencieswould allow sensitivity at multiple soil depths. The crosscorrelationtechniques inherent in GNSS-R methods are alsovery robust against RFI. This experiment will obtain directand reflected measurements from a set of antennas installedon a tower at a height of 30-35 meters. In situ sensors will beinstalled in the soil, at the location of the specular reflectionpoint, at various depths to provide calibration as close aspossible to the reflectivity measurement. In thispresentation, we will present the theoretical background ofSoOp remote sensing of soil moisture, the expectedperformance of this technique, and the development of thefield experiment.Link, PercyVariability of oceanic and terrestrial water vaporsources in the Amazon Basin: An investigationusing TES satellite and MERRA reanalysis atvarying temporal resolutionsLink, Percy 1 ; Goldner, Aaron 2 ; Whadcoat, Siobhan 3 ; Fiorella,Rich 41. Earth and Planetary Science, UC Berkeley, Berkeley, CA,USA2. Earth and Atmospheric Sciences, Purdue University, WestLafayette, IN, USA3. Earth Sciences, Syracuse University, Syracuse, NY, USA4. Earth and Environmental Sciences, University ofMichigan, Ann Arbor, MI, USAPrecipitation in the Amazon region depends on both thelarge-scale circulation (Hadley and Walker cells) and local- toregional-scale dynamics of evapotranspiration, whichrecycles moisture from the land surface. We will use remotelysensed observations to investigate the sources ofatmospheric water vapor over the Amazon Basin and toexamine the relative contributions of oceanic and terrestrialwater vapor sources. By comparing isotopic data from theTropospheric Emission Spectrometer (TES) with ModernEra Retrospective Analysis for Research and Applications(MERRA) reanalysis data, we will investigate the spatial andtemporal variability of water vapor sources and the factorsthat drive the variability. We will focus on two timescales. Inthe first, we will analyze individual storm tracks as theymove west across the basin to study the impacts of waterrecycling on the isotopic signature of vapor of the air mass.In the second, we will analyze seasonal climatologies toconstrain interannual variability. From this perspective, wewill investigate the sources of variability, such as the El NiñoSouthern Oscillation (ENSO), shown by the climatologies.Using high resolution TES data, we will isolate isotopicshifts over the Amazon region in comparison to the MERRAreanalysis, which should describe the dynamics controllingthe flux of moisture into the region. This study will exploreat very high temporal resolution how precipitation andisotopic concentrations evolve during El Niño and La Niñaevents, and during years when equatorial Pacific sea surfacetemperatures are in their neutral mode. The use of highresolution observational data should help determine thesources of moisture in the Amazon region and how thesesources shift during El Niño and La Niña.Liston, Glen E.An Improved Global Snow Classification Datasetfor Hydrologic ApplicationsListon, Glen E. 1 ; Sturm, Matthew 21. Colorado State University, Fort Collins, CO, USA2. U. S. Army Cold Regions Research and EngineeringLaboratory, Ft. Wainwright, AK, USAOut of a need to improve our description andunderstanding of snow covers found around the world,92