terrestrial water storage are c<strong>on</strong>sistent with increased netprecipitati<strong>on</strong> over <strong>the</strong> Eurasian Pan-Arctic regi<strong>on</strong>. At finerspatial scales, in particular in <strong>the</strong> central Lena basin,terrestrial water storage change detected by GRACE showsincreases over regi<strong>on</strong>s <strong>of</strong> disc<strong>on</strong>tinuous permafrost,potentially indicating changes in <strong>the</strong> active layer thickness inthose areas. We also use GRACE total water storageanomalies to evaluate biases in <strong>the</strong> net precipitati<strong>on</strong> from<strong>the</strong> re-analysis data, as well as <strong>the</strong> cold-seas<strong>on</strong> precipitati<strong>on</strong>estimates from two global, merged satellite–gaugeprecipitati<strong>on</strong> analyses—Global Precipitati<strong>on</strong> ClimatologyProject (GPCP) and Climate Predicti<strong>on</strong> Center MergedAnalysis <strong>of</strong> Precipitati<strong>on</strong> (CMAP). In general, spatial patternsand interannual variability are highly correlated between <strong>the</strong>datasets, although significant differences are also observed.Differences vary by regi<strong>on</strong> but typically increase at higherlatitudes. Fur<strong>the</strong>rmore, results indicate that <strong>the</strong> gaugeundercatch correcti<strong>on</strong> used by GPCP may be overestimated.These comparis<strong>on</strong>s may be useful for assessing precipitati<strong>on</strong>estimates over large regi<strong>on</strong>s, where in-situ gauge networksmay be sparse.Lars<strong>on</strong>, Kristine M.GPS Snow <strong>Sensing</strong>Lars<strong>on</strong>, Kristine M. 1 ; Nievinski, Felipe 1 ; Gutmann, Ethan 2 ;Small, Eric 11. Aerospace Engineering Sciences, University <strong>of</strong> Colorado,Boulder, CO, USA2. NCAR, Boulder, CO, USAThe Global Positi<strong>on</strong>ing System c<strong>on</strong>tinuously transmitsL-band signals to support real-time navigati<strong>on</strong> users. Thesesame signals are being tracked by networks <strong>of</strong> high-precisi<strong>on</strong>GPS instruments that were installed by geophysicists andgeodesists to measure plate moti<strong>on</strong>s. Many states andcounties also operate GPS networks to supporttransportati<strong>on</strong> engineers and land surveyors. Over 2500 <strong>of</strong><strong>the</strong>se systems have been deployed in <strong>the</strong> United States. Theyoperate c<strong>on</strong>tinuously, and data are made publicly availablewithin 24 hours. Geodesists model <strong>the</strong> direct signal betweeneach GPS satellite and <strong>the</strong> ground antenna to calculate <strong>the</strong>positi<strong>on</strong> <strong>of</strong> each GPS site.Some <strong>of</strong> <strong>the</strong> signal reflects from<strong>the</strong> ground and arrives at <strong>the</strong> antenna late. The interferencebetween <strong>the</strong> direct and reflected GPS signal is what we use toinfer snow depth. For most sites <strong>the</strong> footprint <strong>of</strong> <strong>the</strong> methodis 30 meters in radius with a snow depth precisi<strong>on</strong> <strong>of</strong>approximately 3 cm. These data complement small-scale insitu snow depth sensors and satellite methods. We currentlyoperate 5 calibrati<strong>on</strong> sites in Utah, Idaho, and Colorado.Comparis<strong>on</strong>s between GPS snow depth retrievals and o<strong>the</strong>rin situ sensors will be discussed. We will also dem<strong>on</strong>strate<strong>the</strong> GPS snow sensing method at sites from <strong>the</strong> NSFEarthScope Plate Boundary Observatory (PBO). Thisnetwork c<strong>on</strong>sists <strong>of</strong> 1100 receivers in <strong>the</strong> western UnitedStates and Alaska.http://xen<strong>on</strong>.colorado.edu/reflecti<strong>on</strong>s/GPS_reflecti<strong>on</strong>s/Intro.htmlLebsock, Mat<strong>the</strong>w D.The Complementary Role <strong>of</strong> Observati<strong>on</strong>s <strong>of</strong> LightRainfall from CloudSatLebsock, Mat<strong>the</strong>w D. 1 ; Stephens, Graeme 1 ; L’Ecuyer, Tristan 21. Jet Propulsi<strong>on</strong> Lab, Pasadena, CA, USA2. University <strong>of</strong> Wisc<strong>on</strong>sin, Madis<strong>on</strong>, WI, USAThe CloudSat rainfall algorithms are presented as auseful complementary data source to <strong>the</strong> more establishedPrecipitati<strong>on</strong> Radar (PR) and passive microwaveprecipitati<strong>on</strong> sensors. The specific strengths <strong>of</strong> <strong>the</strong> CloudSatinstrument including it’s excellent sensitivity and resoluti<strong>on</strong>highlight its ability to fill in <strong>the</strong> light end <strong>of</strong> Earth’s rainfallspectrum that escapes detecti<strong>on</strong> by o<strong>the</strong>r sensors. Todem<strong>on</strong>strate <strong>the</strong> complementary nature <strong>of</strong> <strong>the</strong> CloudSatobservati<strong>on</strong>s, a comparis<strong>on</strong> <strong>of</strong> warm rainfall from CloudSatwith AMSR-E shows <strong>the</strong> dramatic improvement <strong>of</strong> <strong>the</strong>Goddard Pr<strong>of</strong>iling algorithm (GPROF)-2010 algorithm overGPROF-2004 at quantifying warm rain. Despite <strong>the</strong>significant improvement <strong>of</strong> <strong>the</strong> passive microwave algorithmsubstantial regi<strong>on</strong>al biases in GPROF-2010 that are relatedto variati<strong>on</strong>s in Sea Surface Temperature (SST) and ColumnWater Vapor (CWV) persist. These regi<strong>on</strong>al biases are relatedto <strong>the</strong> fundamental detecti<strong>on</strong> capabilities <strong>of</strong> <strong>the</strong> PR, which isused to create <strong>the</strong> rainfall database employed by <strong>the</strong> passivemicrowave algorithm. A series <strong>of</strong> sensitivity calculati<strong>on</strong>sindicate that <strong>the</strong> Dual-frequency Precipitati<strong>on</strong> Radar (DPR)that will fly as part <strong>of</strong> <strong>the</strong> Global Precipitati<strong>on</strong> Missi<strong>on</strong>(GPM) will significantly mitigate <strong>the</strong>se detecti<strong>on</strong> issues.Colocati<strong>on</strong> <strong>of</strong> <strong>the</strong> DPR with <strong>the</strong> GPM Microwave Imager(GMI) will have <strong>the</strong> added benefit <strong>of</strong> improving <strong>the</strong> GPROFrainfall database and thus <strong>the</strong> climate data record providedby passive microwave instruments.Lee, Hy<strong>on</strong>gkiCharacterizati<strong>on</strong> <strong>of</strong> Terrestrial Water Dynamics in<strong>the</strong> C<strong>on</strong>go Basin Using GRACE and Satellite RadarAltimetryLee, Hy<strong>on</strong>gki 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, K<strong>on</strong>stantinos 61. University <strong>of</strong> Houst<strong>on</strong>, Houst<strong>on</strong>, TX, USA2. FM Global, Norwood, MA, USA3. Ohio State University, Columbus, OH, USA4. NASA Goddard Space Flight Center, Greenbelt, MD, USA5. University <strong>of</strong> Tokyo, Tokyo, Japan6. Jet Propulsi<strong>on</strong> Laboratory, Pasadena, CA, USAThe C<strong>on</strong>go Basin is <strong>the</strong> world’s third largest in size (~3.7milli<strong>on</strong> km^2), and sec<strong>on</strong>d <strong>on</strong>ly to <strong>the</strong> Amaz<strong>on</strong> River indischarge (~40,200 cms annual average). However, <strong>the</strong>hydrological dynamics <strong>of</strong> seas<strong>on</strong>ally flooded wetlands andfloodplains remains poorly quantified. Here, we separate <strong>the</strong>C<strong>on</strong>go wetland into four 3° 3° regi<strong>on</strong>s, and use remotesensing measurements (i.e., GRACE, satellite radar altimeter,GPCP, JERS-1, SRTM, and MODIS) to estimate <strong>the</strong> amounts<strong>of</strong> water filling and draining from <strong>the</strong> C<strong>on</strong>go wetland, and88
to determine <strong>the</strong> source <strong>of</strong> <strong>the</strong> water. We find that <strong>the</strong>amount <strong>of</strong> water annually filling and draining <strong>the</strong> C<strong>on</strong>gowetlands is 111 km^3, which is about <strong>on</strong>e-third <strong>the</strong> size <strong>of</strong><strong>the</strong> water volumes found <strong>on</strong> <strong>the</strong> mainstem Amaz<strong>on</strong>floodplain. Based <strong>on</strong> amplitude comparis<strong>on</strong>s am<strong>on</strong>g <strong>the</strong>water volume changes and timing comparis<strong>on</strong>s am<strong>on</strong>g <strong>the</strong>irfluxes, we c<strong>on</strong>clude that <strong>the</strong> local upland run<strong>of</strong>f is <strong>the</strong> mainsource <strong>of</strong> <strong>the</strong> C<strong>on</strong>go wetland water, not <strong>the</strong> fluvial process <strong>of</strong>river-floodplain water exchange as in <strong>the</strong> Amaz<strong>on</strong>. Ourhydraulic analysis using altimeter measurements alsosupports our c<strong>on</strong>clusi<strong>on</strong> by dem<strong>on</strong>strating that watersurface elevati<strong>on</strong>s in <strong>the</strong> wetlands are c<strong>on</strong>sistently higherthan <strong>the</strong> adjacent river water levels. Our research alsohighlights differences in <strong>the</strong> hydrology and hydrodynamicsbetween <strong>the</strong> C<strong>on</strong>go wetland and <strong>the</strong> mainstem Amaz<strong>on</strong>floodplainLemoine, Frank G.M<strong>on</strong>itoring Mass Change Using Global HighResoluti<strong>on</strong> GRACE Masc<strong>on</strong> Soluti<strong>on</strong>sLemoine, Frank G. 1 ; Sabaka, Terence J. 1 ; Boy, Jean-Paul 2 ;Luthcke, Scott B. 1 ; Carabajal, Claudia C. 3, 1 ; Rowlands, DavidD. 11. Planetary Geodynamics Lab., NASA GSFC, Greenbelt,MD, USA2. EOST/IPGS, (UMR 7516 CNRS-UdS), Strasbourg, France3. Sigma Space Corp., Lanham, MD, USAThe Gravity Recovery And Climate Experiment(GRACE) missi<strong>on</strong> has been launched in March 2002, and hasmeasured since <strong>the</strong> Earth’s time-variable gravity field at highspatial and temporal resoluti<strong>on</strong>. Am<strong>on</strong>g <strong>the</strong> applicati<strong>on</strong>s hasbeen <strong>the</strong> m<strong>on</strong>itoring <strong>of</strong> <strong>the</strong> changes in terrestrial waterstorage (TWS). The standard product developed by <strong>the</strong>GRACE project and various analysis centers has beenm<strong>on</strong>thly unc<strong>on</strong>strained spherical harm<strong>on</strong>ic soluti<strong>on</strong>s, whichcan be c<strong>on</strong>verted to grids <strong>of</strong> surface water changes. Thesoluti<strong>on</strong>s are affected by str<strong>on</strong>g correlated noise (striping),which can be removed by various filtering techniques. Thisfiltering reduces <strong>the</strong> amplitude <strong>of</strong> <strong>the</strong> retrieved TWS, whichis can be corrected by “re-scaling” <strong>the</strong> signal using hydrologymodels. At GSFC we have developed global soluti<strong>on</strong>s using alocalized masc<strong>on</strong> (mass c<strong>on</strong>centrati<strong>on</strong>s) approach. Usingappropriate c<strong>on</strong>straints, <strong>the</strong>se global soluti<strong>on</strong>s allow bettertemporal (10 days) and spatial (2 degree) resoluti<strong>on</strong>s, than<strong>the</strong> classical spherical harm<strong>on</strong>ic soluti<strong>on</strong>s and do not requireany post-processing. We have developed global soluti<strong>on</strong>swith and without a priori forward-modeling <strong>of</strong> hydrology.We inter-compare <strong>the</strong>se soluti<strong>on</strong>s <strong>on</strong> a c<strong>on</strong>tinent and riverbasin basis to global hydrology models, as well as o<strong>the</strong>rgridded products derived from <strong>the</strong> GRACE missi<strong>on</strong>.Lenters, JohnAn internati<strong>on</strong>al collaborati<strong>on</strong> to examine globallake temperature trends from in situ and remotesensing data: Project objectives and preliminaryresultsLenters, John 1 ; Adrian, Rita 2 ; Allan, Ma<strong>the</strong>w 3 ; de Eyto,Elvira 4 ; D<strong>on</strong>g, Bo 1 ; Hamilt<strong>on</strong>, David 3 ; Hook, Sim<strong>on</strong> 12 ;Izmestyeva, Lyubov 5 ; Kraemer, Benjamin 6 ; Kratz, Tim 6 ;Livingst<strong>on</strong>e, David 7 ; Mcintyre, Peter 6 ; M<strong>on</strong>tz, Pam 6 ; Noges,Peeter 8 ; Noges, Tiina 8 ; O’Reilly, Ca<strong>the</strong>rine 14 ; Read, Jordan 6 ;Sandilands, Ken 9 ; Schindler, Daniel 10 ; Schneider, Philipp 11 ;Silow, Eugene 5 ; Straile, Dietmar 13 ; Van Cleave, Ka<strong>the</strong>rine 1 ;Zhdanov, Fedor 51. School <strong>of</strong> Natural Resources, Univ. <strong>of</strong> Nebraska-Lincoln,Lincoln, NE, USA2. Leibniz-Institute <strong>of</strong> Freshwater Ecology and InlandFisheries, Berlin, Germany3. The Univ. <strong>of</strong> Waikato, Hamilt<strong>on</strong>, New Zealand4. Marine Institute, Newport, Ireland5. Irkutsk State Univ., Irkutsk, Russian Federati<strong>on</strong>6. Univ. <strong>of</strong> Wisc<strong>on</strong>sin-Madis<strong>on</strong>, Madis<strong>on</strong>, WI, USA7. Eawag, Dubendorf, Switzerland8. Est<strong>on</strong>ian Univ. <strong>of</strong> Life Sciences, Tartu, Est<strong>on</strong>ia9. Fisheries and Oceans Canada, Winnipeg, MB, Canada10. Univ. <strong>of</strong> Washingt<strong>on</strong>, Seattle, WA, USA11. Norwegian Institute for Air Research, Kjeller, Norway12.JPL, California Institute <strong>of</strong> Technology, Pasadena, CA,USA13.Univ. <strong>of</strong> K<strong>on</strong>stanz, K<strong>on</strong>stanz, Germany14. Illinois State Univ., Normal, IL, USARecent studies have revealed significant warming <strong>of</strong>lakes throughout <strong>the</strong> world, and <strong>the</strong> observed rate <strong>of</strong> lakewarming is – in many cases – more rapid than that <strong>of</strong> <strong>the</strong>ambient air temperature. These large changes in laketemperature have pr<strong>of</strong>ound implicati<strong>on</strong>s for lakehydrodynamics, productivity, and biotic communities. Thescientific community is just beginning to understand <strong>the</strong>global extent, regi<strong>on</strong>al patterns, physical mechanisms, andecological c<strong>on</strong>sequences <strong>of</strong> lake warming. Although many insitu lake temperature records are available, <strong>on</strong>ly a fewencompass l<strong>on</strong>g time periods. Most datasets are collected byindividual investigators, have varying sampling protocols,and do not have extensive geographic or temporal coverage.<strong>Remote</strong> sensing methods, <strong>on</strong> <strong>the</strong> o<strong>the</strong>r hand, have beenincreasingly used to characterize global trends in lake surfacetemperature, and <strong>the</strong>y provide an invaluable counterpart toin situ measurements. However, <strong>the</strong> existing satellite recordsdo not extend as far back in time as some <strong>of</strong> <strong>the</strong> l<strong>on</strong>ger insitu datasets, and remotely sensed measurements capture<strong>on</strong>ly surface temperature, ra<strong>the</strong>r than vertical pr<strong>of</strong>iles. Inthis study, we present project objectives and preliminaryresults from an internati<strong>on</strong>al collaborative effort tosyn<strong>the</strong>size global records <strong>of</strong> lake temperature from in situand satellite-based measurements. Surface watertemperature data are analyzed from over 120 lakesdistributed across 40 countries. Data from 20 <strong>of</strong> <strong>the</strong> lakesare based <strong>on</strong> in situ measurements, while <strong>the</strong> remaining89
- Page 5 and 6:
SCIENTIFIC PROGRAMSUNDAY, 19 FEBRUA
- Page 7 and 8:
1600h - 1900hMM-1MM-2MM-3MM-4MM-5MM
- Page 9 and 10:
GM-7GM-8GM-9GM-10GM-11GM-12GM-13160
- Page 11 and 12:
EM-25EM-26EM-27EM-28EM-29EM-301600h
- Page 13 and 14:
SMM-8SMM-9SMM-10SMM-11SMM-12SMM-13S
- Page 15 and 16:
SCM-24SCM-251600h - 1900hPM-1PM-2PM
- Page 17 and 18:
1030h - 1200h1030h - 1200h1030h - 1
- Page 19 and 20:
ET-13ET-14ET-15ET-16ET-17ET-18ET-19
- Page 21 and 22:
SWT-19SWT-201600h - 1900hSMT-1SMT-2
- Page 23 and 24:
SCT-14SCT-15SCT-16SCT-17SCT-18SCT-1
- Page 25 and 26:
MT-2MT-3MT-4MT-5MT-6MT-7MT-8MT-9MT-
- Page 27 and 28:
1330h - 1530h1530h - 1600h1600h - 1
- Page 29 and 30:
esilience to hydrological hazards a
- Page 31 and 32:
Alfieri, Joseph G.The Factors Influ
- Page 33 and 34:
Montana and Oregon. Other applicati
- Page 35 and 36:
accuracy of snow derivation from si
- Page 37 and 38: seasonal trends, and integrate clou
- Page 40 and 41: a single mission, the phrase “nea
- Page 42 and 43: climate and land surface unaccounte
- Page 44 and 45: esolution lidar-derived DEM was com
- Page 46 and 47: further verified that even for conv
- Page 48 and 49: underway and its utility can be ass
- Page 50 and 51: Courault, DominiqueAssessment of mo
- Page 52 and 53: used three Landsat-5 TM images (05/
- Page 55: storage change solutions in the for
- Page 59 and 60: Famiglietti, James S.Getting Real A
- Page 61 and 62: can be thought of as operating in t
- Page 63 and 64: mission and will address the follow
- Page 65 and 66: Gan, Thian Y.Soil Moisture Retrieva
- Page 67 and 68: match the two sets of estimates. Th
- Page 69 and 70: producing CGF snow cover products.
- Page 71 and 72: performance of the AWRA-L model for
- Page 73 and 74: oth local and regional hydrology. T
- Page 75 and 76: Euphorbia heterandena, and Echinops
- Page 77 and 78: the effectiveness of this calibrati
- Page 79 and 80: presents challenges to the validati
- Page 81 and 82: long period time (1976-2010) was co
- Page 83 and 84: has more improved resolution ( ) to
- Page 85 and 86: in the flow over the floodplain ari
- Page 87: fraction of the fresh water resourc
- Page 91 and 92: hydrologists, was initially assigne
- Page 93 and 94: Sturm et al. (1995) introduced a se
- Page 95 and 96: calendar day are then truncated and
- Page 97 and 98: climate associated with hydrologica
- Page 99 and 100: California Institute of Technology
- Page 101 and 102: egion in Northern California that i
- Page 103 and 104: Moller, DelwynTopographic Mapping o
- Page 105 and 106: obtained from the Fifth Microwave W
- Page 107 and 108: a constraint that is observed spati
- Page 109 and 110: groundwater degradation, seawater i
- Page 111 and 112: approach to estimate soil water con
- Page 113 and 114: Norouzi, HamidrezaLand Surface Char
- Page 115 and 116: Painter, Thomas H.The JPL Airborne
- Page 117 and 118: Pavelsky, Tamlin M.Continuous River
- Page 119 and 120: interferometric synthetic aperture
- Page 121 and 122: elevant satellite missions, such as
- Page 123 and 124: support decision-making related to
- Page 125 and 126: oth the quantification of human wat
- Page 127 and 128: parameter inversion of the time inv
- Page 129 and 130: ground-based observational forcing
- Page 131 and 132: Selkowitz, DavidExploring Landsat-d
- Page 133 and 134: Shahroudi, NargesMicrowave Emissivi
- Page 135 and 136: well as subsurface hydrological con
- Page 137 and 138: Sturm, MatthewRemote Sensing and Gr
- Page 139 and 140:
Sutanudjaja, Edwin H.Using space-bo
- Page 141 and 142:
which can be monitored as an indica
- Page 143 and 144:
tools and methods to address one of
- Page 145 and 146:
Vanderjagt, Benjamin J.How sub-pixe
- Page 147 and 148:
Vila, Daniel A.Satellite Rainfall R
- Page 149 and 150:
and landuse sustainability. In this
- Page 151 and 152:
e very significant as seepage occur
- Page 153 and 154:
Wood, Eric F.Challenges in Developi
- Page 155 and 156:
Xie, PingpingGauge - Satellite Merg
- Page 157 and 158:
Yebra, MartaRemote sensing canopy c
- Page 159 and 160:
used. PIHM has ability to simulate