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Faisal Hossain

Bio: Faisal Hossain is an academic researcher from University of Washington. The author has contributed to research in topics: Precipitation & Flood forecasting. The author has an hindex of 38, co-authored 230 publications receiving 5251 citations. Previous affiliations of Faisal Hossain include University of Chittagong & Tennessee Technological University.


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Journal ArticleDOI
TL;DR: The authors summarizes the changes in landscape structure because of human land management over the last several decades, and using observed and model-eddata, documents how these changes have altered biogeophysical and biogeochemical surface fluxes on the local, mesoscale, and regional scales.
Abstract: This article summarizes the changes in landscape structure because of human land managementoverthelastseveralcenturies,andusingobservedandmodeleddata, documents how these changes have altered biogeophysical and biogeochemical surface fluxes on the local, mesoscale, and regional scales. Remaining research issues are presented including whether these landscape changes alter large-scale atmospheric circulation patterns far from where the land use and land cover changes occur. We conclude that existing climate assessments have not yet adequately factored in this climate forcing. For those regions that have undergone intensive human landscape change, or would undergo intensive change in the future, we conclude that the failure to factor in this forcing risks a misalignment of investment in climate mitigation and adaptation.  2011 John Wiley & Sons, Ltd.

672 citations

BookDOI
01 Jan 2010
TL;DR: In this article, the authors present a practical guide to a Space-Time Stochastic Error Model for Simulation of High-Resolution Satellite Rainfall Data, which is used in real-time decision support systems.
Abstract: Evolution of High Resolution Precipitation Products.- The TRMM Multi-Satellite Precipitation Analysis (TMPA).- CMORPH: A "Morphing" Approach for High Resolution Precipitation Product Generation.- The Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) for High-Resolution, Low-Latency Satellite-Based Rainfall Estimates.- Extreme Precipitation Estimation Using Satellite-Based PERSIANN-CCS Algorithm.- The Combined Passive Microwave-Infrared (PMIR) Algorithm.- The NRL-Blend High Resolution Precipitation Product and its Application to Land Surface Hydrology.- Kalman Filtering Applications for Global Satellite Mapping of Precipitation (GSMaP).- Evaluation of High Resolution Precipitation Products.- Neighborhood Verification of High Resolution Precipitation Products.- A Practical Guide to a Space-Time Stochastic Error Model for Simulation of High Resolution Satellite Rainfall Data.- Regional Evaluation Through Independent Precipitation Measurements: USA.- Comparison of CMORPH and TRMM-3B42 over Mountainous Regions of Africa and South America.- Evaluation Through Independent Measurements: Complex Terrain and Humid Tropical Region in Ethiopia.- Error Propagation of Satellite-Rainfall in Flood Prediction Applications over Complex Terrain: A Case Study in Northeastern Italy.- Probabilistic Assessment of the Satellite Rainfall Retrieval Error Translation to Hydrologic Response.- Real Time Operations for Decision Support Systems.- Applications of TRMM-Based Multi-Satellite Precipitation Estimation for Global Runoff Prediction: Prototyping a Global Flood Modeling System.- Real-Time Hydrology Operations at USDA for Monitoring Global Soil Moisture and Auditing National Crop Yield Estimates.- Real-Time Decision Support Systems: The Famine Early Warning System Network.

173 citations

Journal ArticleDOI
TL;DR: In this article, the authors report 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.
Abstract: 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.

170 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily "remote sensing" measurements derived from hydraulic models corrupted with minimal observational errors, and found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-ofbank flows, multichannel planforms, and backwater effects.
Abstract: The Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relative residuals across the 16 nonbraided rivers was only 125% SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results

164 citations

Journal ArticleDOI
TL;DR: In this article, the spatial gradients of atmospheric variables related to precipitation formation are identified around the reservoir shoreline for 92 large dams of North America, and the authors report that large dams influence local climate most in Mediterranean, arid and semi-arid climates, while for humid climates the influence is least.
Abstract: Understanding the forcings exerted by large dams on local climate is key to establishing if artificial reservoirs inadvertently modify precipitation patterns in impounded river basins. Using a 30 year record of reanalysis data, the spatial gradients of atmospheric variables related to precipitation formation are identified around the reservoir shoreline for 92 large dams of North America. Our study reports that large dams influence local climate most in Mediterranean, arid and semi-arid climates, while for humid climates the influence is least. During the growing season, large dams in Mediterranean climates increase CAPE 2-3 times near the reservoir compared to the non-growing season. Clear spatial gradients of CAPE, specific humidity and surface evaporation are also observed around the fringes between the reservoir shoreline and further from these dams. Because of the increasing correlation observed between higher percentile of rain and CAPE, our findings point to the possibility of storm intensification in impounded basins of the Mediterranean and arid climates of the United States.

143 citations


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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI

7,335 citations

01 Jan 1989
TL;DR: In this article, a two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea.
Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

3,813 citations