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NASA NTRS2004

Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Realtime and Research Products and Applications

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 deg latitude-longitude resolution over the latitude range from 50 deg N-50 deg S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Adler, Robert↗
NASA NTRS2005

Visualization of Space-Time Ambiguities to be Explored by the NASA GEC Mission with a Critique of Synthesized Measurements for Different GEC Mission Scenarios

The objective of this grant was to study how a multi-satellite mission configuration can be optimized for maximum exploratory scientific return. NASA's Solar Terrestrial Probe (STP) concept mission Geospace Electrodynamic Connections (GEC) was the target mission for this pilot study. GEC prime mission characteristics were two fold: (i) a series of three satellites in the same orbit plane with differential spacing, and (ii) a deep-dipping phase in which these satellites could dip to altitudes as low as 130 km to explore the lower ionosphere and thermosphere. Each satellite would carry a full suite of plasma and neutral in-situ sensors and have the same dipping capability. This latter aspect would be envisaged as a series, up to 10, of deep-dipping campaigns, each lasting 10 days during which the perigee would be lowered to the desired probing depth. The challenge in optimization is to establish the scientific problems that can best be addressed by varying or selecting satellite spacing during a two-year mission while also interspersing, in this two year time frame, the deep-dipping campaigns. Although this sounds like a straightforward trade-off situation, it is complicated by the orbit precession in local time, the location of perigee, and that even the dipping campaigns will have preferred satellite spacing requirements.

Sojka, Jan J.↗
NASA NTRS2006

A Possible Magnetar Nature for IGR J16358-4726

We present detailed spectral and timing analysis of the hard x-ray transient IGR J16358-4726 using multi-satellite archival observations. A study of the source flux time history over 6 years, suggests that this transient outbursts can be occurring in intervals of at most 1 year. Joint spectral fits using simultaneous Chandra/ACIS and INTEGRAL/ISGRI data reveal a spectrum well described by an absorbed cut-off power law model plus an Fe line. We detected the pulsations initially reported using Chandra/ACIS also in the INTEGRAL/ISGRI light curve and in subsequent XMM-Newton observations. Using the INTEGRAL data we identified a pulse spin up of 94 s (P = 1.6 x 10(exp -4), which strongly points to a neutron star nature for IGR J16358-4726. Assuming that the spin up is due to disc accretion, we estimate that the source magnetic field ranges between 10(sup 13) approximately 10(sup 15) depending on its distance, possibly supporting a magnetar nature for IGR J16358-4726.

Patel, S.↗
NASA NTRS2006

Monthly-Diurnal Water Budget Variability Over Gulf of Mexico-Caribbean Sea Basin from Satellite Observations

This study presents results from a multi-satellite/multi-sensor retrieval system design d to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective in identifying problems in estimating vapor transports from a "leaky" operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system. Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January- 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Smith, E. A.↗
NASA NTRS2006

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗
NASA NTRS2007

Flood and Landslide Applications of Near Real-time Satellite Rainfall Products

Floods and associated landslides are one of the most widespread natural hazards on Earth, responsible for tens of thousands of deaths and billions of dollars in property damage every year. During 1993-2002, over 1000 of the more than 2,900 natural disasters reported were due to floods. These floods and associated landslides claimed over 90,000 lives, affected over 1.4 billion people and cost about $210 billion. The impact of these disasters is often felt most acutely in less developed regions. In many countries around the world, satellite-based precipitation estimation may be the best source of rainfall data due to lack of surface observing networks. Satellite observations can be of essential value in improving our understanding of the occurrence of hazardous events and possibly in lessening their impact on local economies and in reducing injuries, if they can be used to create reliable warning systems in cost-effective ways. This article addressed these opportunities and challenges by describing a combination of satellite-based real-time precipitation estimation with land surface characteristics as input, with empirical and numerical models to map potential of landslides and floods. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg. By careful integration of remote sensing and in-situ observations, and assimilation of these observations into hydrological and landslide/debris flow models with surface topographic information, prediction of useful probabilistic maps of landslide and floods for emergency management in a timely manner is possible. Early results shows that the potential exists for successful application of satellite precipitation data in improving/developing global monitoring systems for flood/landslide disaster preparedness and management. The scientific and technological prototype can be first applied in a representative test-bed and then the information deliverables for the region can be tailored to the societal and economic needs of the represented affected countries.

Hong, Yang↗
NASA NTRS2007

A First Approach to Global Runoff Simulation using Satellite Rainfall Estimation

Many hydrological models have been introduced in the hydrological literature to predict runoff but few of these have become common planning or decision-making tools, either because the data requirements are substantial or because the modeling processes are too complicated for operational application. On the other hand, progress in regional or global rainfall-runoff simulation has been constrained by the difficulty of measuring spatiotemporal variability of the primary causative factor, i.e. rainfall fluxes, continuously over space and time. Building on progress in remote sensing technology, researchers have improved the accuracy, coverage, and resolution of rainfall estimates by combining imagery from infrared, passive microwave, and space-borne radar sensors. Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports a ballpark assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conservation Service (NRCS) runoff Curve Number (CN) method. Using an Antecedent Precipitation Index (API) as a proxy of antecedent moisture conditions, this note estimates time-varying NRCS-CN values determined by the 5-day normalized API. Driven by multi-year (1998-2006) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis, quasi-global runoff was retrospectively simulated with the NRCS-CN method and compared to Global Runoff Data Centre data at global and catchment scales. Results demonstrated the potential for using this simple method when diagnosing runoff values from satellite rainfall for the globe and for medium to large river basins. This work was done with the simple NRCS-CN method as a first-cut approach to understanding the challenges that lie ahead in advancing the satellite-based inference of global runoff. We expect that the successes and limitations revealed in this study will lay the basis for applying more advanced methods to capture the dynamic variability of the global hydrologic process for global runoff monlto~ngin real time. The essential ingredient in this work is the use of global satellite-based rainfall estimation.

Hong, Yang↗
NASA NTRS2007

A-Train Data Search and Visualization to Facilitate Multi-Instrument Cloud Studies

Now that the A-Train suite of datasets have become more mature, new and innovative science utilizing the various products has become more reliable and challenging. To perform multi-satellite research with A-Train data originating from heterogenous missions, scientists must access, subset visualize and analyze user specified datasets in ways unique to the dataset. Then hte datasets need to be co-registered and maybe merged. The A-Train Data Depot (ATDD) has been developed to save each scientist the effort and expense of developing these functions individually.

Kempler, Steven↗
NASA NTRS2007

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗
NASA NTRS2007

Detailed Analysis of Indian Summer Monsoon Rainfall Processes with Modern/High-Quality Satellite Observations

We examine, in detail, Indian Summer Monsoon rainfall processes using modernhigh quality satellite precipitation measurements. The focus here is on measurements derived from three NASA cloud and precipitation satellite missionslinstruments (TRMM/PR&TMI, AQUNAMSRE, and CLOUDSATICPR), and a fourth TRMM Project-generated multi-satellite precipitation measurement dataset (viz., TRMM standard algorithm 3b42) -- all from a period beginning in 1998 up to the present. It is emphasized that the 3b42 algorithm blends passive microwave (PMW) radiometer-based precipitation estimates from LEO satellites with infi-ared (IR) precipitation estimates from a world network of CEO satellites (representing -15% of the complete space-time coverage) All of these observations are first cross-calibrated to precipitation estimates taken from standard TRMM combined PR-TMI algorithm 2b31, and second adjusted at the large scale based on monthly-averaged rain-gage measurements. The blended approach takes advantage of direct estimates of precipitation from the PMW radiometerequipped LEO satellites -- but which suffer fi-om sampling limitations -- in combination with less accurate IR estimates from the optical-infrared imaging cameras on GEO satellites -- but which provide continuous diurnal sampling. The advantages of the current technologies are evident in the continuity and coverage properties inherent to the resultant precipitation datasets that have been an outgrowth of these stable measuring and retrieval technologies. There is a wealth of information contained in the current satellite measurements of precipitation regarding the salient precipitation properties of the Indian Summer Monsoon. Using different datasets obtained from the measuring systems noted above, we have analyzed the observations cast in the form of: (1) spatially distributed means and variances over the hierarchy of relevant time scales (hourly I diurnally, daily, monthly, seasonally I intra-seasonally, and inter-annually), (2) time series at these different time scales taken as area-averages over the hierarchy of relevant space scales (Indian sub-Division, Indian sub-continent, and Circumambient Indian Ocean), (3) principal autocorrelation and cross-correlation structures over various monsoon space-time domains, (4) diurnally modulated amplitude-phase properties of rain rates over different monsoon space-time domains, (5) foremost rain rate probability distributions intrinsic to monsoon precipitation, and (6) behavior of extreme events including occurrences of flood and drought episodes throughout the course of inter-annual monsoon processes.

Smith, Eric A.↗
NASA NTRS2008

Contributions of TRMM and GPM to GEOSS

Two international satellite missions have a major role in the development of global precipitation data under the auspices of the Global Earth Observation System of Systems (GEOSS) to meet the needs of several Societal Benefit Areas set forth by the Group on Earth Observations (GEO). One is the joint U.S.-Japan Tropical Rainfall Measuring Mission (TRMM), launched in 1997, which provides combined radar/radiometer measurements to serve as a benchmark for tropical precipitation measurements by passive microwave radiometers and has played a key role in the development of the current generation of multi-satellite global rainfall products. The other is the Global Precipitation Measurement (GPM) Mission, an international satellite mission to be launched in 2013 to deliver the next-generation global precipitation observations from a constellation of dedicated and operational microwave sensors. GPM is a science mission with integrated applications goals aimed at (1) advancing the knowledge of the global water/energy cycle variability and freshwater availability and (2) improving weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation. The GPM Mission is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA), with additional partners in satellite constellation and ground validation under discussion. With NASA and JAXA science team activities providing the framework and infrastructures for international collaboration on satellite inter-calibration, retrieval algorithm development, and ground validation, GPM has been identified as the cornerstone for the development of the Precipitation Constellation for the Committee on Earth Observation Satellites (CEOS). An overview of current accomplishments by TRMM and anticipated contributions by GPM to GEOSS activities will be presented.

Hou, Arthur Y.↗
NASA NTRS2010

Opportunities for Utilizing the International Space Station for Studies of F2- Region Plasma Science and High Voltage Solar Array Interactions with the Plasma Environment

The near circular, 51.6deg inclination orbit of the International Space Station (ISS) is maintained within an altitude range of approximately 300 km to 400 km providing an ideal platform for conducting in-situ studies of space weather effects on the mid and low-latitude F-2 region ionosphere. The Floating Potential Measurement Unit (FPMU) is a suite of instruments installed on the ISS in August 2006 which includes a Floating Potential Probe (FPP), a Plasma Impedance Probe (PIP), a Wide-sweep Langmuir Probe (WLP), and a Narrow-sweep Langmuir Probe (NLP). The primary purpose for deploying the FPMU is to characterize ambient plasma temperatures and densities in which the ISS operates and to obtain measurements of the ISS potential relative to the space plasma environment for use in characterizing and mitigating spacecraft charging hazards to the vehicle and crew. In addition to the engineering goals, data from the FPMU instrument package is available for collaborative multi-satellite and ground based instrument studies of the F-region ionosphere during both quiet and disturbed periods. Finally, the FPMU measurements supported by ISS engineering telemetry data provides a unique opportunity to investigate interactions of the ISS high voltage (160 volt) solar array system with the plasma environment. This presentation will provide examples of FPMU measurements along the ISS orbit including night-time equatorial plasma density depletions sampled near the peak electron density in the F2-region ionosphere, charging phenomenon due to interaction of the ISS solar arrays with the plasma environment, and modification of ISS charging due to visiting vehicles demonstrating the capabilities of the FPMU probes for monitoring mid and low latitude plasma processes as well as vehicle interactions with the plasma environment.

Minow, Joseph I.↗
NASA NTRS2010

Evidence of Convective Redistribution of Carbon Monoxide in Aura Tropospheric Emission Sounder (TES) and Microwave Limb Sounder (MLS) Observations

Vertical convective transport is a key element of the tropospheric circulation. Convection lofts air from the boundary layer into the free troposphere, allowing surface emissions to travel much further, and altering the rate of chemical processes such as ozone production. This study uses satellite observations to focus on the convective transport of CO from the boundary layer to the mid and upper troposphere. Our hypothesis is that strong convection associated with high rain rate regions leads to a correlation between mid level and upper level CO amounts. We first test this hypothesis using the Global Modeling Initiative (GMI) chemistry and transport model. We find the correlation is robust and increases as the precipitation rate (the strength of convection) increases. We next examine three years of CO profiles from the Tropospheric Emission Sounder (TES) and Microwave Limb Sounder (MLS) instruments aboard EOS Aura. Rain rates are taken from the Tropical Rainfall Measuring Mission (TRMM) 3B-42 multi-satellite product. Again we find a correlation between mid-level and upper tropospheric CO, which increases with rain rate. Our result shows the critical importance of tropical convection in coupling vertical levels of the troposphere in the transport of trace gases. The effect is seen most clearly in strong convective regions such as the Inter-tropical Convergence Zone.

Manyin, Michael↗
NASA NTRS2010

Magnetar Observations in the Swift-Fermi/GBM Era

NASA's Fermi Observatory was launched June 11, 2008; the Fermi Gamma Ray Burst Monitor (GBM) began normal operations on July 14, about a month after launch, when the trigger algorithms were enabled. Since then, and against all odds, GBM recorded over 600 bursts from 4 SGRs. Of these four sources, only one was an old magnetar: SGR J1806+20. SGR J0501+4516, was discovered with Swift and extensively monitored with GBM. A source originally classified as AXP 1E1547.0-5408 exhibited SGR-like bursting behavior and we reclassified it as SGR J1550-5418. Finally, GBM discovered SGR J0418+5729 on 2009 June. Finally, on March 2010, a third new magnetar was discovered with Swift, SGR J1833-0832. I report below on the current status of the field and on several results combining multi-satellite and ground-based data

Kouveliotou, Chryssa↗
NASA NTRS2010

Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

Su, Fengge↗
NASA NTRS2010

Magnetar Observations in the Swift-Fermi Era

This slide presentation reports on the current status of Magnetar observations, and on the results combining multi-satellite. Magnetars are magnetically powered neutron stars. There is discussion about several Soft Gamma Repeaters (SGR) also known as Magnetars, though there aer other neutron stars that may be considered as magnetars (i.e., Anomalous X-ray Pulsars (AXPs) Dim Isolated Neutron Stars (DINs) Compact Central X-ray Objects (CCOs) Rotation Powered Pulsars.) An example of a Rotation Powered PSRs, (i.e., PSR J1846-0258) is reviewed, and examples of SGRs are reviewed (i.e., SGR 0501+4516, SGR 0501+4516, SGR J1550-5418, and SGR 0418+5729). There is also discussion about Photospheric Radius Expansion (PRE) in thermonuclear bursts.

Kouveliotou, Chryssa↗
NASA NTRS2010

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

Zhang, Xiaodong↗
NASA NTRS2010

Transfer of Satellite Rainfall Uncertainty from Gauged to Ungauged Regions at Regional and Seasonal Timescales

Hydrologists and other users need to know the uncertainty of the satellite rainfall data sets across the range of time/space scales over the whole domain of the data set. Here, uncertainty' refers to the general concept of the deviation' of an estimate from the reference (or ground truth) where the deviation may be defined in multiple ways. This uncertainty information can provide insight to the user on the realistic limits of utility, such as hydrologic predictability, that can be achieved with these satellite rainfall data sets. However, satellite rainfall uncertainty estimation requires ground validation (GV) precipitation data. On the other hand, satellite data will be most useful over regions that lack GV data, for example developing countries. This paper addresses the open issues for developing an appropriate uncertainty transfer scheme that can routinely estimate various uncertainty metrics across the globe by leveraging a combination of spatially-dense GV data and temporally sparse surrogate (or proxy) GV data, such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and the Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar. The TRMM Multi-satellite Precipitation Analysis (TMPA) products over the US spanning a record of 6 years are used as a representative example of satellite rainfall. It is shown that there exists a quantifiable spatial structure in the uncertainty of satellite data for spatial interpolation. Probabilistic analysis of sampling offered by the existing constellation of passive microwave sensors indicate that transfer of uncertainty for hydrologic applications may be effective at daily time scales or higher during the GPM era. Finally, a commonly used spatial interpolation technique (kriging), that leverages the spatial correlation of estimation uncertainty, is assessed at climatologic, seasonal, monthly and weekly timescales. It is found that the effectiveness of kriging is sensitive to the type of uncertainty metric, time scale of transfer and the density of GV data within the transfer domain. Transfer accuracy is lowest at weekly timescales with the error doubling from monthly to weekly.However, at very low GV data density (<20% of the domain), the transfer accuracy is too low to show any distinction as a function of the timescale of transfer.

Tang, Ling↗