TY - JOUR
T1 - AIMERG
T2 - A new Asian precipitation dataset (0.1°/half-hourly, 2000-2015) by calibrating the GPM-era IMERG at a daily scale using APHRODITE
AU - Ma, Ziqiang
AU - Xu, Jintao
AU - Zhu, Siyu
AU - Yang, Jun
AU - Tang, Guoqiang
AU - Yang, Yuanjian
AU - Shi, Zhou
AU - Hong, Yang
N1 - Publisher Copyright:
© Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
PY - 2020/7/8
Y1 - 2020/7/8
N2 - Precipitation estimates with fine 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 fine resolutions, which is particularly useful over poorly gauged regions. However, satellite-based precipitation products 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 the Tropical Rainfall Measuring Mission (TRMM) era (finished in July 2019), which were only calibrated at a monthly scale using ground observations, Global Precipitation Climatology Centre (GPCC, 1.0/monthly), we aim to propose a new calibration algorithm for IMERG at a 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 Towards Evaluation of Water Resources (APHRODITE, 0.25/daily) at the daily scale for the Asian applications. The main conclusions include but are not limited to the following: (1) the proposed daily calibration algorithm (Daily Spatio-Temporal Disaggregation Calibration Algorithm, DSTDCA) is effective in considering the advantages from both satellite-based precipitation estimates and the ground observations; (2) AIMERG performs better than IMERG at different spatio-temporal scales, in terms of both systematic biases and random errors, over mainland China; and (3) APHRODITE demonstrates significant advantages compared to GPCC in calibrating IMERG, especially over mountainous regions with complex terrain, e.g. the Tibetan Plateau. Additionally, results of this study suggest that it is a promising and applicable daily calibration algorithm for GPM in generating the future IMERG in either an operational scheme or a retrospective manner.
AB - Precipitation estimates with fine 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 fine resolutions, which is particularly useful over poorly gauged regions. However, satellite-based precipitation products 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 the Tropical Rainfall Measuring Mission (TRMM) era (finished in July 2019), which were only calibrated at a monthly scale using ground observations, Global Precipitation Climatology Centre (GPCC, 1.0/monthly), we aim to propose a new calibration algorithm for IMERG at a 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 Towards Evaluation of Water Resources (APHRODITE, 0.25/daily) at the daily scale for the Asian applications. The main conclusions include but are not limited to the following: (1) the proposed daily calibration algorithm (Daily Spatio-Temporal Disaggregation Calibration Algorithm, DSTDCA) is effective in considering the advantages from both satellite-based precipitation estimates and the ground observations; (2) AIMERG performs better than IMERG at different spatio-temporal scales, in terms of both systematic biases and random errors, over mainland China; and (3) APHRODITE demonstrates significant advantages compared to GPCC in calibrating IMERG, especially over mountainous regions with complex terrain, e.g. the Tibetan Plateau. Additionally, results of this study suggest that it is a promising and applicable daily calibration algorithm for GPM in generating the future IMERG in either an operational scheme or a retrospective manner.
UR - https://www.scopus.com/pages/publications/85091852647
U2 - 10.5194/essd-12-1525-2020
DO - 10.5194/essd-12-1525-2020
M3 - Article
AN - SCOPUS:85091852647
SN - 1866-3508
VL - 12
SP - 1525
EP - 1544
JO - Earth System Science Data
JF - Earth System Science Data
IS - 3
ER -