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

using multiple looks over one or two days. Other issuesinclude the relatively coarse scale of the MODIS imagery(250 meters), the difficulty of detecting flood waters in areaswith continuous canopy cover, confusion of cloud shadowwith water, and accurately identifying detected water asflood as opposed to normal water extents (typically only anedge issue). We have made progress on some of these issues,and are working to develop higher resolution flooddetection using alternate sensors, including Landsat andvarious radar sensors (Radarsat, ENVISAT). Although theseprovide better spatial resolution, this usually comes at thecost of being less timely. As of late 2011, the systemexpanded to fully global daily flood monitoring, with freepublic access to the generated products. These include GISvector files of flood and normal water extent (KML,shapefile), and small scale graphic maps (10 degrees square)showing a zoomed out view of regional flood extent. Weplan to expand to distributing the information via live webservices (WMS, etc), in the near future. In the medium term(2-3 years) we hope to transition this system to anoperational partner.https://oas.gsfc.nasa.gov/floodmapSmall, Eric E.Sensing Vegetation Growth with Reflected GPSSignalsSmall, Eric E. 1 ; Larson, Kristine 2 ; Evans, Sarah 1 ; Vikram,Praveen 21. Dept of Geology, Univ of Colorado Boulder, Boulder, CO,USA2. Aerospace Engineering, CU Boulder, Boulder, CO, USAMeasurements of vegetation state are required tovalidate satellite estimates of soil moisture and as boundaryconditions for hydrometeorological modeling. We havedeveloped a new technique to estimate vegetation statususing reflected GPS signals (multipath) measured bygeodetic-quality GPS stations. The sensing footprint is~1000 m2, larger than that provided by typical in situobservations but smaller than that from space-basedproducts. Because GPS satellites transmit L-band signals, thevegetation estimates derived from GPS reflections are ameasure of vegetation water content, not greenness as is thecase for optical remote sensing methods. We present resultsbased on two distinct attributes of the multipath signal: (1)signal attenuation observed as the amplitude of the signalto-noise(SNR) interference pattern; and (2) diffusescattering measured via an operational GPS noise statistic,MP1rms. We have compared GPS multipath to biweeklymeasurements of biomass, vegetation height, and watercontent at ten test sites that span a range of vegetationcharacteristics. These field campaigns were conducted in2010 and 2011. Vegetation height and water content areinversely correlated with amplitude of the SNR signal. Thereflected signal is completely suppressed when vegetationwater content exceeds 3 kg m-2, for example at peak growthat irrigated corn and alfalfa sites. We evaluated theoperational MP1rms statistic at hundreds of sites in NSF’sPlate Boundary Observatory (PBO) network for a five-yeartime period. MP1rms is a measure of multipath scattering; itexhibits a clear seasonal cycle as expected for vegetationgrowth and senescence. MP1rms is inversely correlated withNormalized Difference Vegetative Index (NDVI) at most PBOsites: there is more scattering of L-band signals at timeswhen vegetation is greener. The MP1rms variations lagNDVI by approximately three weeks, consistent with the ideathat green-up precedes plant growth. Once lag effects areconsidered, r2 values are typically > 0.8 at sites withconsiderable seasonal cycles in NDVI. Multipath statisticsare calculated daily from existing GPS stations and could beused to estimate biophysical properties to help constrainremotely sensed estimates of soil moisture.http://xenon.colorado.edu/reflections/GPS_reflections/Vegetation.htmlStephens, GraemeA CloudSat perspective of the atmospheric watercycle: recent progress and grand challengesIm, Eastwood 1 ; Stephens, Graeme 11. Jet Propulsion Laboratory, Pasadena, CA, USAThe CloudSat mission is unique in its view of theatmospheric processes of central importance tounderstanding the planetary water cycle. The sensitivity ofthe CloudSat radar (CPR) to all modes of precipitation andthe unique ability to connect this to cloud properties haveprovided important insights on precipitation formingprocesses in the atmosphere. The observations have yieldedthe first real global survey of snowfall, new insights on midlatitudeprecipitation and have provided stunning examplesof how aerosol affect warm rain processes in layered clouds.The results have further exposed a common problem in allGCMs in the over-occurrence of light precipitation rates(drizzle) at the surface. This is not only an issue forprecipitation forecasting, but can play a crucial role in therepresentation of low cloud layers over the oceans and it hasbeen shown is the reason for long-standing and significantmoisture biases in model, essential for the lifecycle ofstratocumulus among a number of factors. This talk willhighlight how global satellite observations are providing keyinsights on the planets water cycle and will provide a view ofwhat major challenges exist and future observational needsthat will address these challenges.136