A methodological approach for spatial downscaling of TRMM precipitation data in North China

Zheng, Xunhua; Zhu, Jiaojun

doi:10.1080/01431161.2014.995275

Cited by 28 publications

(20 citation statements)

References 37 publications

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“…Regarding rainfall data, the major limitation for their spatial interpolation based on satellite data, as done by AgCFSR, AgMERRA, and NASA/POWER, is the low or inadequate resolution of the images which is not good enough to capture extreme events [56,57] and local spatial variability associated with the topography [58,59]. Similarly, the poor performance of all databases to estimate WS 2m is related to two main aspects: the small magnitude of this variable, which leads to large errors even with small deviations, and its high spatial variability associated with the topography and land cover [60].…”

Section: Gridded Databasementioning

confidence: 99%

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Bender

Sentelhas

2018

Advances in Meteorology

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e quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid-and end-of-century periods (2040-2069 and 2070-2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. e Bristow-Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.

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Section: Gridded Databasementioning

confidence: 99%

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Bender

Sentelhas

2018

Advances in Meteorology

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“…Estimation of annual precipitation A regression model with a residual correction method was obtained to downscale the spatial precipitation fields of the TRMM 3B43 product from 0.25°× 0.25°(approximately 25 km × 25 km) to 1 km × 1 km pixel precipitation fields for each year from 2001 to 2009 (Immerzeel et al 2009;Jia et al 2011;Duan and Bastiaanssen 2013;Zheng and Zhu 2015b). According to the relationships between TRMM 3B43 annual precipitation and vegetation in the TNR, we divided the TNR into two parts: one part where the TRMM 3B43 annual precipitation and NDVI were significantly correlated (i.e., precipitationrecharged area) and the other part where the correlation was disturbed, such as various water bodies (i.e., no precipitationrecharged area).…”

Section: Determination Of Parameters Of Hargreaves Equation (C O )mentioning

confidence: 99%

“…The TRMM 3B43 was a calendar-month temporal resolution and a 0.25°× 0.25°spatial resolution, and spatial coverage extends from 50°south to 50°north by latitude. In this study, the Version 7 TRMM 3B43 product was used and was downloaded from the website of NASA Goddard Earth Sciences Data and Information Services Center (http:// mirador.gsfc.nasa.gov/) (Zheng and Zhu 2015b).…”

Section: Trmm Datamentioning

confidence: 99%

A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data

Zheng

Zhu

2015

Theor Appl Climatol

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Afforestation and reforestation activities achieve high attention at the policy agenda as measures for carbon sequestration in order to mitigate climate change. The ThreeNorth Shelter Forest Program, the largest ecological afforestation program worldwide, was launched in 1978 and will last until 2050 in the Three-North regions (accounting for 42.4 % of China's territory). Shelter forests of the Three-North Shelter Forest Program have exhibited severe decline after planting in 1978 due to lack of detailed climatic classification. Besides, a comprehensive assessment of climate adaptation for the current shelter forests was lacking. In this study, the aridity index determined by precipitation and reference evapotranspiration was employed to classify climatic zones for the afforestation program. The precipitation and reference evapotranspiration with 1-km resolution were estimated based on data from the tropical rainfall measuring mission and moderate resolution imaging spectroradiometer, respectively. Then, the detailed climatic classification for the afforestation program was obtained based on the relationship between the different vegetation types and the aridity index. The shelter forests in 2008 were derived from Landsat TM in the Three-North regions. In addition, climatic zones and shelter forests were corrected by comparing with natural vegetation map and field surveys. By overlaying the shelter forests on the climatic zones, we found that 16.30 % coniferous forests, 8.21 % broadleaved forests, 2.03 % mixed conifer-broadleaved forests, and 10.86 % shrubs were not in strict accordance with the climate conditions. These results open new perspectives for potential use of remote sensing techniques for afforestation management.

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“…Also, the zonal average of each predictor was calculated at a spatial resolution of 0.25 ∘ , to produce a dataset with the same spatial resolution. The same data preparation process was applied by Nichol and Abbas [10], by Zheng and Zhu [7], and by Duan and Bastiaanssen [1].…”

Section: Data Preparationmentioning

confidence: 99%

“…Although TRMM data was restricted starting from October 7, 2014, due to the end of its fuel, this source of information still constitutes an important axis of research and is still applied in different studies [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Downscaling of Open Coarse Precipitation Data through Spatial and Statistical Analysis, Integrating NDVI, NDWI, Elevation, and Distance from Sea

Ezzine

Bouziane

Ouazar

et al. 2017

Advances in Meteorology

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This study aims to improve the statistical spatial downscaling of coarse precipitation (TRMM 3B43 product) and also to explore its limitations in the Mediterranean area. It was carried out in Morocco and was based on an open dataset including four predictors (NDVI, NDWI, DEM, and distance from sea) that explain TRMM 3B43 product. For this purpose, four groups of models were established based on different combinations of the four predictors, in order to compare from one side NDVI and NDWI based models and the other side stepwise with multiple regression. The models that have given rise to the best approximations and best fits were used to downscale TRMM 3B43 product. The resulting downscaled and calibrated precipitations were validated by independent RGS. Aside from that, the limitations of the proposed approach were assessed in five bioclimatic stages. Furthermore, the influence of the sea was analyzed in five classes of distance. The findings showed that the models built using NDVI and NDWI have a high correlation and therefore can be used to downscale precipitation. The integration of elevation and distance improved the correlation models. According to 2 , RMSE, bias, and MAE, the study revealed that there is a great agreement between downscaled precipitations and RGS measurements. In addition, the analysis showed that the contribution of the variable (distance from sea) is evident around the coastal area and decreases progressively. Likewise, the study demonstrated that the approach performs well in humid and arid bioclimatic stages compared to others.

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A methodological approach for spatial downscaling of TRMM precipitation data in North China

Cited by 28 publications

References 37 publications

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data

Downscaling of Open Coarse Precipitation Data through Spatial and Statistical Analysis, Integrating NDVI, NDWI, Elevation, and Distance from Sea

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