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

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$A 10 year climatology of cloud fraction and vertical distribution ...$

esolution lidar-derived DEM was compared to the NED 10m resolution DEM, the streams delineated with the 10 mlidar data were significantly better than those modeled withthe 10 m NED data, showing that significant improvementin accuracy can be achieved with no increase in data storage.When topographic index was modeled with multipleresolutions of lidar-derived DEMs, the spatial and statisticaldistributions were both very different, with finer resolutionDEMs not accurately modeling areas of high TI.Additionally, depending on the flow accumulationalgorithm used, there were differences in the change instatistical resolution with response to initial DEMresolution.Brutsaert, WilfriedSome Indirect Estimates of Changes in HydrologicConditions During the Past Century INVITEDBrutsaert, Wilfried 11. Civil & Environmental Eng, Cornell Univ, Ithaca, NY,USAThe water budget of a natural river basin can beformulated as P - Q - E = dS/dt, where P is the precipitationrate, Q the net surface outflow rate per unit area, E theevaporation rate and S the water stored per unit area in thebasin. The variables P and Q can be and have been measureddirectly and many long-term data sets are available for basinsall over the world, with which their evolution over time canbe studied in great detail. The construction of reliable longterm data sets for E and S for climate change purposes ismore challenging; indeed, the direct and routinemeasurement of these variables is still very difficult, so thatin practice to gain information on past trends they mustinvariably be estimated by indirect methods. In the case of E,attempts have been made to estimate past trends oflandscape evaporation from available pan evaporationrecords. Because pan and landscape evaporation areintrinsically different especially under drying conditions,there is still no unanimity regarding the interpretation ofthese studies. In the case of S, it is generally agreed thatterrestrial storage in a basin is related to the baseflows or dryweather river flows from the basin; this has allowed todocument the evolution of groundwater storage in manylarge basins under widely different climate conditions fromavailable streamflow records. While these approaches toestimate E and S involve obvious challenges, they can beovercome.Castro, Lina M.Assessment of TRMM Multi-satellite PrecipitationAnalysis (TMPA) in the South of Chile’s AndesMountainsCastro, Lina M. 1 ; Miranda, Marcelo 2 ; Fernandez, Bonifacio 11. Department of Hydraulic and EnvironmentalEngineering, Pontificia Universidad Catolica de Chile,Santiago de Chile, Chile2. Department of Forest Science, Pontificia UniversidadCatólica de Chile, Santiago De Chile, ChilePrecipitation is the most crucial variable in applicationof hydrological models because it provides most of themoisture input for hydrologic processes over land.Hydrological models require accurate rainfall data at thehighest possible resolution for streamflow predictions.Nevertheless, due to the high variability in space and time ofprecipitation it is necessary to have a dense rain gaugesnetwork to achieve high accuracy. The gauge network inChile is sparse or nonexistent, especially in the AndesMountains where the most Chilean rivers are born.Although the rain gauges have the advantage of a hightemporal resolution, the scarcity and difficulty of getting thedata in real time limit their application into hydrologicalmodels for simulation and forecasting in real time. This gapcan be solved using data from space-borne sensors. In recentyears, several satellite-based, near global, high-resolutionprecipitation estimates have become available withincreasing temporal and spatial resolution. Rainfallestimates from space-borne sensors offer a valuable source ofinformation for capturing the rainfall and for understandingof terrestrial rainfall behavior over some regions that areungauged like some parts of the Andes Mountains. Thepresent work aims to assess the rainfall estimations ofTropical Rainfall Measurement Mission (TRMM) MultisatellitePrecipitation Analysis (TMPA) in a region in theSouth of Chile over the Andes Mountains. The assessmentbetween TMPA product and gauge measurements was madeusing statistical error (Bias, Root Mean Square Error, andCorrelation Coefficient) and detection measurements (FalseAlarm Ratio - FAR and Frequency Bias Index - FBI). TheTMPA product represents 50% of total rainfall in almost allground truth stations, with the highest bias values in winterseason. When the TMPA estimates show high FAR and FBIvalues, it means that satellite has overestimated the numberof rain events with highest FAR and FBI values in the dryseason. Bias, RMSE, FAR and FBI show a spatial patternwhich increases with elevation because of the orographiceffect in the rainfall distribution and intermittentoccurrence. The temporal aggregation improves Bias, RMSEand Coefficient of Correlation values. For a monthly timescale the coefficient of correlation and bias reach values 0.95and 28% respectively. Improvements on a monthly scale mayarise from the TMPA processing algorithm which usesmonthly histograms to calibrate the satellite data. TMPAproducts like other ones (STAR or CMORH) have coarsespatial resolution (between 4km – 27 km) and represent asnapshot at a given time. The spatial and temporal44
characteristics of rainfall in this zone is highly variable andin winter season the rainfall inside one cell of TMPA productcan be strongly variable as well. The use of the monthlyTMPA product can be feasible in hydrological models with amonthly time step; however daily satellite data is restricteddue to the time scale by which it was obtained and thealgorithm used to calibrate the TMPA estimates.Chan, SamuelSMAP Instrument Design For High Resolution SoilMoisture And Freeze/Thaw State MeasurementsChan, Samuel 1 ; Spencer, Michael 11. Jet Propulsion Laboratory, Pasadena, CA, USASoil moisture controls water cycles fluxes, such as runoffand evapotranspiration, and modulates the energy cyclethrough the exchange of energy between the land and theatmosphere. Near-surface soil moisture and its freeze/thawstate are also the primary determinants of carbon exchangeat the land surface. Consequently, measuring theseparameters globally is vital to understanding the globalwater, energy and carbon cycles. The Soil Moisture ActivePassive (SMAP ) mission has the scientific objective ofmeasuring and monitoring both soil moisture andfreeze/thaw state globally from space with unprecedentedresolution and accuracy. SMAP will provide estimates ofsurface soil moisture with an accuracy of 0.04 [cm3/cm3], at10 km resolution, and with 3-day average revisit-time overthe global land area. The requirements for 10 km spatialresolution and 3 day temporal resolution are driven byphenomena in hydrologic and atmospheric science whichhave distinguishing features or significant physicalinteractions at the hydrometeorological scale of 10 km. Inthe past, soil moisture measurements have primarily utilizedpassive microwave data, because of the greater sensitivity ofbrightness temperature to surface soil moisture. Thedisadvantage of this approach is the coarse resolution ofmeasurement. For example, a spatial resolution of 35 km isthe best case for the recently launched SMOS mission. Toaccomplish the requirement for higher resolution, SMAPemploys a radar instrument in addition to a radiometer.Both instruments are operated at L-band, rather than C-band or higher frequencies, to cover a much larger range ofvegetation conditions. The radar and radiometer share asingle feedhorn and parabolic mesh reflector, which is offsetfrom nadir and rotates at a constant rate. A swath of 1000km is covered with this conical scanning geometry. Inaddition, the scanning antenna beam has a constant surfaceincidence angle and this reduces the complexity of the soilmoisture retrieval algorithm. The SMAP radar is designed toallow synthetic aperture radar (SAR) processing, and theresolution of the resulting measurement is less than 1 kmover the outer 70% of the swath. Data collected include bothco-pol signals, HH and VV, and one cross-pol, HV or VH. Thebackscattering coefficients measured by the radar will beused to retrieve soil moisture with a time series algorithm.The L-band radar measurements are effected by vegetationand surface roughness. The cross-pol measurements willhelp to identify and correct for the presence of surfacevegetation. Because the radar data alone is still unlikely tomeet the overall soil moisture accuracy requirement, SMAPwill utilize an algorithm which merges the active and passivemeasurements to derive the soil moisture product. Thisalgorithm will combine the spatial resolution advantage ofthe radar with the sensitivity advantage of the radiometer toachieve an optimal blend of resolution and accuracy.Freeze/thaw state will also be derived from the radar data toyield high resolution spatial and temporal mapping of thefrozen or thawed condition of the surface soil and vegetationin the boreal zones.Chávez Jara, Steven P.CHARACTERIZATION OF HEAVY STORMS INTHE PERUVIAN ANDES USING THE TRMMPRECIPITATION RADARChávez Jara, Steven P. 1 ; Takahashi Guevara, Ken 11. Research in Natural Disaster Prevention, PeruvianGeophysical Institute, Lima, PeruIn the Peruvian Andes, the great geographicalheterogeneity and the sparcity of raingauge networksprecludes an adequate characterization of the precipitationdistribution and estimation techniques based in remotesensing satellite cloud observations have not been successfulin this region. However, the available data indicates verystrong year-long rainfall in the eastern slopes of the Andesthat is probably a substantial contribution to the Amazondischarge, whereas rainfall in the internal Andean valleys issubstantially weaker but has great importance for the localpopulation, In this study we characterize storms in bothregions using data from the precipitation radar (PR)onboard TRMM, particularly the products 2A25 and 2A23,which allows us to obtain the three-dimensional spatialdistribution of rainfall, an estimated surface rainfall, as wellas other properties such as rain type (i.e. convective vsstratiform) and storm depth. Images from the GOESgeostationary satellite also provide information of cloudsand their brightness temperature. Field measurements of theDrop Size Distribution (DSD) using the filter papertechnique in the Mantaro Valley in the central Andes ofPeru, are used to validate the PR 2A25 algorithm for this theregion, particularly the a and b parameters in the relationbetween rain rate (R) and reflectivity (Z), i.e. R=aZ^b, findingan excelent agreement for b, but an overestimation of a inthe 2A25 algorithm We found than in the TRMM PR datafor the central Andes, the overall majority of the rainingpixels are stratiform and only a few pixels are convective, yetthe total rain associated to the convective pixels equals to thestratiform ones. On the other hand, for a orographicallyforcedrainfall core in the eastern slope of the Andes, wefound that although there is a larger fraction of convectivepixels than in the highlands, the total stratiform andconvective rainfall are similar highlighting the importance ofstratiform precipitation in this heavily raining region. Thus,rainfall estimation techniques that assume a relationshipbetween storm height and rainfall rates do not work. It was45
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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 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 and 88: fraction of the fresh water resourc
Page 89 and 90: to determine the source of the wate
Page 91 and 92: hydrologists, was initially assigne
Page 93 and 94: Sturm et al. (1995) introduced a se
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calendar day are then truncated and
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climate associated with hydrologica
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California Institute of Technology
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egion in Northern California that i
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Moller, DelwynTopographic Mapping o
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obtained from the Fifth Microwave W
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a constraint that is observed spati
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groundwater degradation, seawater i
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approach to estimate soil water con
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Norouzi, HamidrezaLand Surface Char
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Painter, Thomas H.The JPL Airborne
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Pavelsky, Tamlin M.Continuous River
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interferometric synthetic aperture
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elevant satellite missions, such as
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support decision-making related to
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oth the quantification of human wat
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parameter inversion of the time inv
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ground-based observational forcing
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Selkowitz, DavidExploring Landsat-d
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Shahroudi, NargesMicrowave Emissivi
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well as subsurface hydrological con
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Sturm, MatthewRemote Sensing and Gr
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Sutanudjaja, Edwin H.Using space-bo
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which can be monitored as an indica
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tools and methods to address one of
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Vanderjagt, Benjamin J.How sub-pixe
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Vila, Daniel A.Satellite Rainfall R
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and landuse sustainability. In this
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e very significant as seepage occur
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Wood, Eric F.Challenges in Developi
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Xie, PingpingGauge - Satellite Merg
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Yebra, MartaRemote sensing canopy c
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used. PIHM has ability to simulate
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2012 AGU Chapman Conference on Remote Sensing of the ...

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