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Marjuki, Gerard van der Schrier, Albert M. G. Klein Tank, Else J.M. van den Besselaar, Nurhayati, and Y. S. Swarinoto

Abstract

Climate indices are analyzed using a newly developed dataset with station-based daily data for Southeast Asia. With rice the staple food of the diet in the region, the indices used are aimed at agriculture, specifically rice production, and include the onset of the wet season and the nighttime temperature. Three indices are used to estimate the onset of the wet season. Despite a quantitative lack of similarity between these indices (although they are strongly correlated), the progression of the wet season over the area matches existing descriptions. Trends in the onset date of the wet season calculated over 1971–2012 are only statistically significant for a few stations; there are no signs that a wide spread delay as anticipated by future climate scenarios is already taking place. A positive trend in the nighttime temperature over the region is observed with values up to 0.7°C decade−1. For a selection of stations the change in distribution of nighttime temperatures is analyzed when comparing the 1971–90 period with the 1991–2010 period. They show a shift of the median to higher temperatures, and the decline in the number of relatively cool nights is stronger than the increase in the number of relatively warm nights.

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Else J. M. van den Besselaar, Gerard van der Schrier, Richard C. Cornes, Aris Suwondo Iqbal, and Albert M. G. Klein Tank

Abstract

This study introduces a new daily high-resolution land-only observational gridded dataset, called SA-OBS, for precipitation and minimum, mean, and maximum temperature covering Southeast Asia. This dataset improves upon existing observational products in terms of the number of contributing stations, in the use of an interpolation technique appropriate for daily climate observations, and in making estimates of the uncertainty of the gridded data. The dataset is delivered on a 0.25° × 0.25° and a 0.5° × 0.5° regular latitude–longitude grid for the period 1981–2014. The dataset aims to provide best estimates of grid square averages rather than point values to enable direct comparisons with regional climate models. Next to the best estimates, daily uncertainties are quantified. The underlying daily station time series are collected in cooperation between meteorological services in the region: the Southeast Asian Climate Assessment and Dataset (SACA&D). Comparisons are made with station observations and other gridded station or satellite-based datasets (APHRODITE, CMORPH, TRMM). The comparisons show that vast differences exist in the average daily precipitation, the number of rainy days, and the average precipitation on a wet day between these datasets. SA-OBS closely resembles the station observations in terms of dry/wet frequency, the timing of precipitation events, and the reproduction of extreme precipitation. New versions of SA-OBS will be released when the station network in SACA&D has grown further.

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