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Song, Yanling, et al.
(author)
Rain-season trends in precipitation and their effect in different climate regions of China during 1961–2008
2011
In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 6:3, s. 1-8
Journal article (peer-reviewed) abstract
Using high-quality precipitation data from 524 stations, the trends of a set of precipitation variables during the main rain season (May–September) from 1961 to 2008 for different climate regions in China were analysed. However, different characteristics were displayed in different regions of China. In most temperate monsoon regions (north-eastern China), total rain-season precipitation and precipitation days showed decreasing trends; positive tendencies in precipitation intensity were, however, noted for most stations in this region. It is suggested that the decrease in rain-season precipitation is mainly related to there being fewer rain days and a change towards drier conditions in north-eastern China, and as a result, the available water resources have been negatively affected in the temperate monsoon regions. In most subtropical and tropical monsoon climate regions (south-eastern China), the rain-season precipitation and precipitation days (11–50, with > 50 mm) showed slightly positive trends. However, precipitation days with ≤ 10 mm decreased in these regions. Changes towards wetter conditions in this area, together with more frequent heavy rainfall events causing floods, have a severe impact on peoples' lives and socio-economic development. In general, the rain-season precipitation, precipitation days and rain-season precipitation intensity had all increased in the temperate continental and plateau/mountain regions of western China. This increase in rain-season precipitation has been favourable to pasture growth.
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Rayner, D.P. 1973, et al.
(author)
A multi-state weather generator for daily precipitation for the Torne River basin, northern Sweden/western Finland
2016
In: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 7:1-2, s. 70-81
Journal article (peer-reviewed) abstract
This paper describes a new weather generator e the 10-state empirical model e that combines a 10-state, first-order Markov chain with a non-parametric precipitation amounts model. Using a doubly-stochastic transition-matrix results in a weather generator for which the overall precipitation distribution (including both wet and dry days) and the temporal-correlation can be modified independently for climate change studies. This paper assesses the ability of the 10-state empirical model to simulate daily area-average precipitation in the Torne River catchment in northern Sweden/western Finland in the context of 3 other models: a 10-state model with a parametric (Gamma) amounts model; a wet/dry chain with the empirical amounts model; and a wet/dry chain with the parametric amounts model. The ability to accurately simulate the dis- tribution of multi-day precipitation in the catchment is the primary consideration. Results showed that the 10-state empirical model represented accumulated 2- to 14-day precipitation most realistically. Further, the dis- tribution of precipitation on wet days in the catchment is related to the placement of a wet day within a wet-spell, and the 10-state models represented this realistically, while the wet/dry models did not. Although all four models accurately reproduced the annual and monthly averages in the training data, all models underestimated inter-annual and inter-seasonal variance. Even so, the 10-state empirical model performed best. We conclude that the multi-state model is a promising candidate for hydrological applications, as it simulates multi-day precipitation well, but that further development is required to improve the simulation of interannual variation.
