International Program of Collaborative Research, CSEAS

Integration of Reanalysis Meteorological Data and Village Level Historical Information about Agricultural Activities in Southeast Asia over the Last 50 years
Project Leader: NAGANO, Takanori, Graduate School of Agriculture, Kobe University
（Term：2011 - 2012）

• Outline of Joint Research
• Purpose of Joint Research
• Outline of Result

• Joint Seminars in 2011 Fiscal Year

Outline of Joint Research

The Reanalysis of meteorological data (reanalysis products) that are made through the assimilation of observed data throughout the world are widely used in studies on climate change mechanisms. This study aims to analyze the relations between the reanalysis data and local agricultural activities in Southeast Asia for the past five decades through the following steps.
(1) The history of agricultural production and damages will be obtained through interviews with local farmers and the analysis of agricultural statistics.
(2) The relation between observed precipitation data and information about agricultural activities obtained through (1) will be analyzed.
(3) Meteorological mechanisms that created local agricultural damages will be clarified through an analysis of relations between the reanalysis data and local observed precipitation data.

Purpose of Joint Research

Climate change estimated through Global Circulation Model (GCM). This shows change in water balance (precipitation – evaporation). In areas of darker red (blue), climate will be dryer (more humid).

Annual change of annual precipitation and rice planting area in Khon Kaen Province, the northeastern Thailand. In rain-fed rice cultivation areas, rice cultivation areas vary due to the amount of precipitation. Drought (upper right) is a dominant factor of the instability. Floods (upper left) also affect rice production.

The purpose of this research project is to evaluate relations between meso-synoptic scale meteorological mechanisms and local climate disasters that severely affected agricultural production and farmers’ livelihoods in the Southeast Asia over the last five decades through the integration of reanalysis meteorological data (NCEP/NCAR, JRA25, etc.), observed local meteorological data, agricultural statistics and information obtained through interviews to local people.

As reanalysis products and climate projection datasets under global warming scenarios have a similar data structure and time-spatial resolution, accumulation of case studies about the relation between reanalysis data and phenomena on the ground surface would forman important base for assessments of impacts of climate changes in the future. While there have been a number of studies conducted on the relations between reanalysis products and local hydrological observations, studies on relations between reanalysis products and local human activities are still rare.

A collection of cases of relation between four elements: “meso-synoptic circulation based on reanalysis products”, “local weather conditions based on observations”, “agricultural damages caused by meteorological disaster” and “adaptation of local people” will be published as a final report.

Outline of Result

Reliability of reanalysis data covering Southeast Asia was examined. Seasonal patterns of observed rainfall on the ground were fairly represented by reanalysis data. Influences of El Nino and La Niña were clearly seen in the local climate system in Indochina region.
Resolution of reanalysis data (a few hundred kilometers) was found too coarse to make direct comparison to agricultural activities on the ground. A new downscale method of reanalysis data with use meso-scale climate and hydrological datasets needs to be implemented.
ALOS L-band SAR image data (PALSAR) was found useful as meso-scale hydrological data which indicate soil water condition. Multi-temporal images of PALSAR can be effectively used to classify different hydrological conditions and types of paddy fields in Indochina region.

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