GPM-Based Multitemporal Weighted Precipitation Analysis Using GPM_IMERGDF Product and ASTER DEM in EDBF Algorithm Article Swipe
Sana Ullah
,
Zhengkang Zuo
,
Feizhou Zhang
,
Jianghua Zheng
,
Shifeng Huang
,
Yi Lin
,
Imran Iqbal
,
Yiyuan Sun
,
Ming Yang
,
Lei Yan
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/rs12193162
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/rs12193162
To obtain the high-resolution multitemporal precipitation using spatial downscaling technique on a precipitation dataset may provide a better representation of the spatial variability of precipitation to be used for different purposes. In this research, a new downscaling methodology such as the global precipitation mission (GPM)-based multitemporal weighted precipitation analysis (GMWPA) at 0.05° resolution is developed and applied in the humid region of Mainland China by employing the GPM dataset at 0.1° and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m DEM-based geospatial predictors, i.e., elevation, longitude, and latitude in empirical distribution-based framework (EDBF) algorithm. The proposed methodology is a two-stepped process in which a scale-dependent regression analysis between each individual precipitation variable and the EDBF-based weighted precipitation with geospatial predictor(s), and to downscale the predicted multitemporal weighted precipitation at a refined scale is developed for the downscaling of GMWPA. While comparing results, it shows that the weighted precipitation outperformed all precipitation variables in terms of the coefficient of determination (R2) value, whereas they outperformed the annual precipitation variables and underperformed as compared to the seasonal and the monthly variables in terms of the calculated root mean square error (RMSE) value. Based on the achieved results, the weighted precipitation at the low-resolution (e.g., at 0.75° resolution) along-with the original resolution (e.g., at 0.1° resolution) is employed in the downscaling process to predict the average multitemporal precipitation, the annual total precipitation for the year 2001 and 2004, and the average annual precipitation (2001–2015) at 0.05° resolution, respectively. The downscaling approach resulting through proposed methodology captured the spatial patterns with greater accuracy at higher spatial resolution. This work showed that it is feasible to increase the spatial resolution of a precipitation variable(s) with greater accuracy on an annual basis or as an average from the multitemporal precipitation dataset using a geospatial predictor as the proxy of precipitation through the weighted precipitation in EDBF environment.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs12193162
- https://www.mdpi.com/2072-4292/12/19/3162/pdf?version=1601363298
- OA Status
- gold
- Cited By
- 30
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3090202509
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Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3090202509Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs12193162Digital Object Identifier
- Title
-
GPM-Based Multitemporal Weighted Precipitation Analysis Using GPM_IMERGDF Product and ASTER DEM in EDBF AlgorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-26Full publication date if available
- Authors
-
Sana Ullah, Zhengkang Zuo, Feizhou Zhang, Jianghua Zheng, Shifeng Huang, Yi Lin, Imran Iqbal, Yiyuan Sun, Ming Yang, Lei YanList of authors in order
- Landing page
-
https://doi.org/10.3390/rs12193162Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/12/19/3162/pdf?version=1601363298Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-4292/12/19/3162/pdf?version=1601363298Direct OA link when available
- Concepts
-
Downscaling, Precipitation, Environmental science, Global Precipitation Measurement, Advanced Spaceborne Thermal Emission and Reflection Radiometer, Climatology, Algorithm, Remote sensing, Meteorology, Geology, Mathematics, Digital elevation model, GeographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
30Total citation count in OpenAlex
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2025: 5, 2024: 2, 2023: 2, 2022: 3, 2021: 18Per-year citation counts (last 5 years)
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61Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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