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Updated: May 28, 2026

Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
Published on: December 12, 2013
A high-resolution historical long-term gridded daily meteorological data set for agricultural climate change analysis
Yasushi Ishigooka1, Tsuneo Kuwagata1, Mayumi Yoshimoto1
1Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization (NARO), 3-1-3 Kannondai, Tsukuba, Ibaraki 305-8604, Japan.
Abstract:
We created a high-resolution (approximately 1 km x 1 km) historical (from 1978) gridded daily meteorological dataset, called the Historical Gridded Meteorological Dataset in Japan (HGMD-Japan), as basic information infrastructure for analyzing the impact of climate change on agricultural productivity in Japan. By adding wind speed and relative humidity to a previously developed dataset, a comprehensive dataset that contains the input meteorological data needed for existing major agricultural impact assessment models was developed. To maintain the time-series homogeneity of each variable, possible sources of time-series heterogeneities unrelated to climate change, such as changes in statistical methods and instrument types, were eliminated as far as possible. Additionally, some specific agro-meteorological variables that are related strongly to crop development environments, and seasonal or yearly indices that can indicate potential crop productivity (mainly for paddy rice) or risk of damage due to meteorological extreme events, such as the heat stress index, the water temperature of paddy fields, and the panicle temperature, are provided.
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