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

terrestrial water storage are consistent with increased netprecipitation over the Eurasian Pan-Arctic region. At finerspatial scales, in particular in the central Lena basin,terrestrial water storage change detected by GRACE showsincreases over regions of discontinuous permafrost,potentially indicating changes in the active layer thickness inthose areas. We also use GRACE total water storageanomalies to evaluate biases in the net precipitation fromthe re-analysis data, as well as the cold-season precipitationestimates from two global, merged satellite–gaugeprecipitation analyses—Global Precipitation ClimatologyProject (GPCP) and Climate Prediction Center MergedAnalysis of Precipitation (CMAP). In general, spatial patternsand interannual variability are highly correlated between thedatasets, although significant differences are also observed.Differences vary by region but typically increase at higherlatitudes. Furthermore, results indicate that the gaugeundercatch correction used by GPCP may be overestimated.These comparisons may be useful for assessing precipitationestimates over large regions, where in-situ gauge networksmay be sparse.Larson, Kristine M.GPS Snow SensingLarson, Kristine M. 1 ; Nievinski, Felipe 1 ; Gutmann, Ethan 2 ;Small, Eric 11. Aerospace Engineering Sciences, University of Colorado,Boulder, CO, USA2. NCAR, Boulder, CO, USAThe Global Positioning System continuously transmitsL-band signals to support real-time navigation users. Thesesame signals are being tracked by networks of high-precisionGPS instruments that were installed by geophysicists andgeodesists to measure plate motions. Many states andcounties also operate GPS networks to supporttransportation engineers and land surveyors. Over 2500 ofthese systems have been deployed in the United States. Theyoperate continuously, and data are made publicly availablewithin 24 hours. Geodesists model the direct signal betweeneach GPS satellite and the ground antenna to calculate theposition of each GPS site.Some of the signal reflects fromthe ground and arrives at the antenna late. The interferencebetween the direct and reflected GPS signal is what we use toinfer snow depth. For most sites the footprint of the methodis 30 meters in radius with a snow depth precision ofapproximately 3 cm. These data complement small-scale insitu snow depth sensors and satellite methods. We currentlyoperate 5 calibration sites in Utah, Idaho, and Colorado.Comparisons between GPS snow depth retrievals and otherin situ sensors will be discussed. We will also demonstratethe GPS snow sensing method at sites from the NSFEarthScope Plate Boundary Observatory (PBO). Thisnetwork consists of 1100 receivers in the western UnitedStates and Alaska.http://xenon.colorado.edu/reflections/GPS_reflections/Intro.htmlLebsock, Matthew D.The Complementary Role of Observations of LightRainfall from CloudSatLebsock, Matthew D. 1 ; Stephens, Graeme 1 ; L’Ecuyer, Tristan 21. Jet Propulsion Lab, Pasadena, CA, USA2. University of Wisconsin, Madison, WI, USAThe CloudSat rainfall algorithms are presented as auseful complementary data source to the more establishedPrecipitation Radar (PR) and passive microwaveprecipitation sensors. The specific strengths of the CloudSatinstrument including it’s excellent sensitivity and resolutionhighlight its ability to fill in the light end of Earth’s rainfallspectrum that escapes detection by other sensors. Todemonstrate the complementary nature of the CloudSatobservations, a comparison of warm rainfall from CloudSatwith AMSR-E shows the dramatic improvement of theGoddard Profiling algorithm (GPROF)-2010 algorithm overGPROF-2004 at quantifying warm rain. Despite thesignificant improvement of the passive microwave algorithmsubstantial regional biases in GPROF-2010 that are relatedto variations in Sea Surface Temperature (SST) and ColumnWater Vapor (CWV) persist. These regional biases are relatedto the fundamental detection capabilities of the PR, which isused to create the rainfall database employed by the passivemicrowave algorithm. A series of sensitivity calculationsindicate that the Dual-frequency Precipitation Radar (DPR)that will fly as part of the Global Precipitation Mission(GPM) will significantly mitigate these detection issues.Colocation of the DPR with the GPM Microwave Imager(GMI) will have the added benefit of improving the GPROFrainfall database and thus the climate data record providedby passive microwave instruments.Lee, HyongkiCharacterization of Terrestrial Water Dynamics inthe Congo Basin Using GRACE and Satellite RadarAltimetryLee, Hyongki 1 ; Beighley, R. Edward 2 ; Alsdorf, Douglas 3 ; Jung,Hahn Chul 4 ; Shum, C. k. 3 ; Duan, Jianbin 3 ; Guo, Junyi 3 ;Yamazaki, Dai 5 ; Andreadis, Konstantinos 61. University of Houston, Houston, TX, USA2. FM Global, Norwood, MA, USA3. Ohio State University, Columbus, OH, USA4. NASA Goddard Space Flight Center, Greenbelt, MD, USA5. University of Tokyo, Tokyo, Japan6. Jet Propulsion Laboratory, Pasadena, CA, USAThe Congo Basin is the world’s third largest in size (~3.7million km^2), and second only to the Amazon River indischarge (~40,200 cms annual average). However, thehydrological dynamics of seasonally flooded wetlands andfloodplains remains poorly quantified. Here, we separate theCongo wetland into four 3° 3° regions, and use remotesensing measurements (i.e., GRACE, satellite radar altimeter,GPCP, JERS-1, SRTM, and MODIS) to estimate the amountsof water filling and draining from the Congo wetland, and88