Abstract

Abstract. This study examines the uncertainty in calculating the fundamental climatological characteristics of precipitation in the East Asia region from multiple fine-resolution gridded analysis data sets based on in situ rain gauge observations and data assimilations. Five observation-based gridded precipitation data sets are used to derive the long-term means, standard deviations in lieu of interannual variability and linear trends over the 28-year period from 1980 to 2007. Both the annual and summer (June–July–August) mean precipitation is examined. The agreement amongst these precipitation data sets is examined using two metrics including the signal-to-noise ratio (SNR) defined as the ratio between long-term means and the corresponding standard deviations, and Taylor diagrams, which allow examinations of the pattern correlation, the standard deviation, and the centered root mean square error. It is found that the five gauge-based precipitation analysis data sets agree well in the long-term mean and interannual variability in most of the East Asia region including eastern China, Manchuria, South Korea, and Japan, which are densely populated and have fairly high-density observation networks. The regions of large inter-data-set variations include Tibetan Plateau, Mongolia, northern Indo-China, and North Korea. The regions of large uncertainties are typically lightly populated and are characterized by severe terrain and/or extremely high elevations. Unlike the long-term mean and interannual variability, agreement between data sets in the linear trend is weak, both for the annual and summer mean values. In most of the East Asia region, the SNR for the linear trend is below 0.5: the inter-data-set variability exceeds the multi-data ensemble mean. The uncertainty in the spatial distribution of long-term means among these data sets occurs both in the spatial pattern and variability, but the uncertainty for the interannual variability and time trend is much larger in the variability than in the pattern correlation. Thus, care must be taken in using long-term trends calculated from gridded precipitation analysis data for climate studies over the East Asia region.

Highlights

  • Long-term means, standard deviations in lieu of interannual variability, and trends calculated from observed data are among the fundamental fields in representing the characteristics of regional climates

  • We examined uncertainties including the coarseresolution Global Precipitation Climatology Project (GPCP) data (Adler et al, 2003) to get essentially the same conclusions that are obtained with the original five data sets only; the results including the GPCP data are not presented here to focus on fine-resolution data sets

  • The summer rainfall climatology (Fig. 1d–f) resembles the annual mean climatology but with larger magnitudes. This shows that the precipitation climatology over the East Asia region is primarily determined by the summer rainfall

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Summary

Introduction

Long-term means, standard deviations in lieu of interannual variability, and trends calculated from observed data are among the fundamental fields in representing the characteristics of regional climates. These climatological properties play crucial roles in defining climatological norms, occurrence of extreme events, detection of climate change, and projecting future climate variations and change as well as their impacts (Giorgi et al, 1994; Groisman et al, 2001; Kim, 2005). Reliability of the climate change detection is examined by comparing the long-term means and trends calculated from observations against those simulated in climate model sensitivity experiments (e.g., IPCC, 2001, 2007). Park: Uncertainties in calculating precipitation climatology in East Asia and the impacts of such changes on regionally important sectors

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