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Discussion papers
https://doi.org/10.5194/essd-2019-250
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-250
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 10 Feb 2020

Submitted as: data description paper | 10 Feb 2020

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This preprint is currently under review for the journal ESSD.

AIMERG: a new Asian precipitation dataset (0.1°/half-hourly, 2000–2015) by calibrating GPM IMERG at daily scale using APHRODITE

Ziqiang Ma1, Jintao Xu2, Siyu Zhu1, Guoqiang Tang3,4, Yuanjian Yang5, Zhou Shi2, and Yang Hong1,6 Ziqiang Ma et al.
  • 1Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
  • 2Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China
  • 3University of Saskatchewan Coldwater Lab, Canmore, Alberta, T1W 3G1, Canada
  • 4Centre for Hydrology, University of Saskatchewan, Saskatoon, Saskatchewan, S7N 1K2, Canada
  • 5School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 6School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, 73019, USA

Abstract. Precipitation estimates with finer quality and spatio-temporal resolutions play significant roles in understanding the global and regional cycles of water, carbon and energy. Satellite-based precipitation products are capable of detecting spatial patterns and temporal variations of precipitation at finer resolutions, which is particularly useful over poorly gauged regions. However, satellite-based precipitation product are the indirect estimates of precipitation, inherently containing regional and seasonal systematic biases and random errors. In this study, focusing on the potential drawbacks in generating Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and its recently updated retrospective IMERG in Tropical Rainfall Measuring Mission (TRMM) era (finished in July, 2019), which were only calibrated at monthly scale using ground observations, Global Precipitation Climatology Centre (GPCC, 1.0°/Monthly), we aimed to propose a new calibration algorithm for IMERG at daily scale, and to provide a new AIMERG precipitation dataset (0.1°/half-hourly, 2000–2015, Asia) with better quality, calibrated by Asian Precipitation Highly Resolved Observational Data Integration (APHRODITE, 0.25°/Daily) at daily scale for the Asian applications. And the main conclusions included but not limited to: (1) the proposed daily calibration algorithm (Daily Spatio-Temporal Disaggregation Calibration Algorithm, DSTDCA) was effective in considering the advantages from both satellite-based precipitation estimates and the ground observations; (2) AIMERG performed better than IMERG at different spatio-temporal scales, in terms of both systematic biases and random errors, over the China Main land; and (3) APHRODITE demonstrated significant advantages than GPCC in calibrating the IMERG, especially over the mountainous regions with complex terrain, e.g., the Tibetan Plateau. Additionally, Results of this study suggests that it is a promising and applicable daily calibration algorithm for GPM in generating the future IMERG in either operational scheme or retrospective manner. The AIMERG data record (0.1°/half-hourly, 2000–2015, Asia) is freely available at http://argi-basic.hihanlin.com:8000/d/d925fecf60/. Additionally, the AIMERG data is also freely accessible at https://doi.org/10.5281/zenodo.3609352 (for the period from 2000 to 2008) and https://doi.org/10.5281/zenodo.3609507 (for the period from 2009 to 2015) (Ma et al., 2020).

Ziqiang Ma et al.

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Ziqiang Ma et al.

Data sets

The AIMERG data record (0.1°/half-hourly, 2000-2015, Asia) (2000-2008) Z. Ma, J. Xu, S. Zhu, G. Tang, Y. Yang, Z. Shi, and Y. Hong https://doi.org/10.5281/zenodo.3609352

The AIMERG data record (0.1°/half-hourly, 2000-2015, Asia) (2009-2015) Z. Ma, J. Xu, S. Zhu, G. Tang, Y. Yang, Z. Shi, and Y. Hong https://doi.org/10.5281/zenodo.3609507

Ziqiang Ma et al.

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Short summary
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both TRMM and GPM era, a new daily calibration algorithm on IMERG was proposed, as well as a new AIMERG precipitation dataset (0.1°/ half-hourly, 2000–2015, Asia) with better quality than IMERG for the Asian scientific research and applications. The proposed daily calibration algorithm for GPM is promising and applicable in generating the future IMERG in either operational scheme or retrospective manner.
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both TRMM...
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