Los puntos clave no están disponibles para este artículo en este momento.
A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5, 000–12, 000 stations, which represent 2. 3–4. 5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, verification of high-resolution model simulations and satellite precipitation estimates, and improvement of precipitation forecasts. The APHRODITE project carries out outreach activities with Asian countries, and communicates with national institutions and world data centers. We have released open-access APHROV1101 datasets for monsoon Asia, the Middle East, and northern Eurasia (at 0. 5° × 0. 5° and 0. 25° × 0. 25° resolution) and the APHROJPV1005 dataset for Japan (at 0. 05° × 0. 05° resolution; see www. chikyu. ac. jp/precip/ and http: //aphrodite. suiri. tsukuba. ac. jp/). We welcome cooperation and feedback from users.
Building similarity graph...
Analyzing shared references across papers
Loading...
Akiyo Yatagai
Hirosaki University
Kenji Kamiguchi
Japan Meteorological Agency
Osamu Arakawa
Nagasaki University
Bulletin of the American Meteorological Society
The University of Tokyo
University of Tsukuba
Meteorological Research Institute
Building similarity graph...
Analyzing shared references across papers
Loading...
Yatagai et al. (Mon,) studied this question.
synapsesocial.com/papers/69dcf75498c6111533e5474e — DOI: https://doi.org/10.1175/bams-d-11-00122.1