Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula

Immerzeel, Walter W.; Rutten, Martine; Droogers, P.

doi:10.1016/j.rse.2008.10.004

Cited by 247 publications

(250 citation statements)

References 22 publications

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“…The precipitation on days with an average daily temperature below 1 • C was taken as snowfall, otherwise as rainfall [39]. The grid precipitation data was statistically downscaled using a multiple linear regression model with five terrain factors (longitude, latitude, elevation, slope, and aspect) as independent variables for individual years [40].…”

Section: Datamentioning

confidence: 99%

Snowmelt Water Alters the Regime of Runoff in the Arid Region of Northwest China

Bai

Shi³

et al. 2018

Water

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Seasonal snowmelt water from mountainous areas is critical for water supply in arid regions. Snowmelt profoundly affects the parameterization of the Budyko framework, which describes the long-term relationship between precipitation and runoff. This is true in Xinjiang, a representative arid region in Northwest China. However, the effects of snowmelt water on the water balance in this region remain unclear. Based on observed runoff data in 64 catchments of Xinjiang during 2000-2010, we analyzed the effects of meltwater in the local water balance both spatially and temporally through the Budyko curve and redundancy analysis (RDA) methods, and then investigated the influences of changing meltwater on runoff. Inclusion of snowmelt water into the item of the water availability significantly improved the performance of the Budyko equation for predicting runoff. The results of RDA showed that snowmelt water, potential evaporation (PET), and rainfall combined explained 66% of the spatial variations in runoff, while the individual effects of snowmelt water, PET, and rainfall were 19%, 13%, and 1%, respectively, with the interactions among the three variables being 16%. These results suggest that the accelerating changes of meltwater due to climate warming will significantly alter the regimes of runoff in these regions.

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Section: Datamentioning

confidence: 99%

Snowmelt Water Alters the Regime of Runoff in the Arid Region of Northwest China

Bai

Shi³

et al. 2018

Water

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“…The main assumption for some recently developed downscaling methods for satellite-based products is the relationship between spatial variability of rainfall and environmental factors such as topography and land surface conditions. Immerzeel et al (2009) improved average annual TRMM3B43 from 25 to 1 km grid resolution by establishing an exponential relationship between TRMM3B43 and nor-malized difference vegetation index (NDVI). Jia et al (2011) developed a statistical downscaling scheme based on the relationship between rainfall, terrain elevation, and NDVI.…”

Section: Introductionmentioning

confidence: 99%

Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications

Seyyedi

Anagnostou

Beighley

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Deriving flood hazard maps for ungauged basins typically requires simulating a long record of annual maximum discharges. To improve this approach, precipitation from global reanalysis systems must be downscaled to a spatial and temporal resolution applicable for flood modeling. This study evaluates such downscaling and error correction approaches for improving hydrologic applications using a combination of NASA's Global Land Data Assimilation System (GLDAS) precipitation data set and a higher resolution multi-satellite precipitation product (TRMM). The study focuses on 437 flood-inducing storm events that occurred over a period of ten years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) in the Susquehanna River basin located in the northeastern United States. A validation strategy was devised for assessing error metrics in rainfall and simulated runoff as function of basin area, storm severity, and season. The WSR-88D gauge-adjusted radar-rainfall (stage IV) product was used as the reference rainfall data set, while runoff simulations forced with the stage IV precipitation data set were considered as the runoff reference. Results show that the generated rainfall ensembles from the downscaled reanalysis product encapsulate the reference rainfall. The statistical analysis consists of frequency and quantile plots plus mean relative error and root-mean-square error statistics. The results demonstrated improvements in the precipitation and runoff simulation error statistics of the satellite-driven downscaled reanalysis data set compared to the original reanalysis precipitation product. Results vary by season and less by basin scale. In the fall season specifically, the downscaled product has 3 times lower mean relative error than the original product; this ratio increases to 4 times for the simulated runoff values. The proposed downscaling scheme is modular in design and can be applied on any gridded satellite and reanalysis data set.

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“…Precipitation plays an indispensable role in global and regional hydrological cycles [1,2]. However, it is currently difficult to develop an accurate precipitation product with high spatiotemporal resolution at the watershed scale for complex terrains using solely the traditional ground-based observations, remote sensing products, or regional climate modeling [3,4].…”

Section: Introductionmentioning

confidence: 99%

Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin

Pan

Cheng

et al. 2017

Remote Sensing

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Individually, ground-based, in situ observations, remote sensing, and regional climate modeling cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrains. Data assimilation techniques can be used to bridge the gap between observations and models by assimilating ground observations and remote sensing products into models to improve precipitation simulation and forecasting. However, only a small portion of satellite-retrieved precipitation products assimilation research has been implemented over complex terrains in an arid region. Here, we used the weather research and forecasting (WRF) model to assimilate two satellite precipitation products (The Tropical Rainfall Measuring Mission: TRMM 3B42 and Fengyun-2D: FY-2D) using the 4D-Var data assimilation method for a typical inland river basin in northwest China's arid region, the Heihe River Basin, where terrains are very complex. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly over regions with complex terrains.

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Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula

Cited by 247 publications

References 22 publications

Snowmelt Water Alters the Regime of Runoff in the Arid Region of Northwest China

Snowmelt Water Alters the Regime of Runoff in the Arid Region of Northwest China

Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications

Effects of 4D-Var Data Assimilation Using Remote Sensing Precipitation Products in a WRF Model over the Complex Terrain of an Arid Region River Basin

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