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Wenguang Wei, Zhongwei Yan, and P. D. Jones

Abstract

The potential predictability of seasonal extreme precipitation accumulation (SEPA) across mainland China is evaluated, based on daily precipitation observations during 1960–2013 at 675 stations. The potential predictability value (PPV) of SEPA is calculated for each station by decomposing the observed SEPA variance into a part associated with stochastic daily rainfall variability and another part associated with longer-time-scale climate processes. A Markov chain model is constructed for each station and a Monte Carlo simulation is applied to estimate the stochastic part of the variance. The results suggest that there are more potentially predictable regions for summer than for the other seasons, especially over southern China, the Yangtze River valley, the north China plain, and northwestern China. There are also regions of large PPVs in southern China for autumn and winter and in northwestern China for spring. The SEPA series for the regions of large PPVs are deemed not entirely stochastic, either with long-term trends (e.g., increasing trends in inland northwestern China) or significant correlation with well-known large-scale climate processes (e.g., East Asian winter monsoon for southern China in winter and El Niño for the Yangtze River valley in summer). This fact not only verifies the claim that the regions have potential predictability but also facilitates predictive studies of the regional extreme precipitation associated with large-scale climate processes.

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Xuan Tong, Zhongwei Yan, Jiangjiang Xia, and Xiao Lou

Abstract

Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns.

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Zhongwei Yan, Steven Bate, Richard E. Chandler, Valerie Isham, and Howard Wheater

Abstract

The basic climatological pattern and recent trends in daily maximum wind speed (DMWS) for the region 47.5°–65°N and 12.5°W–22.5°E are studied using gamma distributions within a generalized linear model. Between 1958 and 1998, DMWS has increased over the ocean in winter but weakened over continental Europe in summer. Large-scale circulation changes such as those of the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) account for the strengthening wind over the ocean. Global warming may have impacted the regional wind climate. In particular, Southern Hemisphere temperature exhibits a significant effect on the distinct oceanic and continental trends in DMWS. It is suggested that the steady warming of the Southern Hemisphere during the last few decades may have forced the North Atlantic storm track to shift in such a way that storms are enhanced toward the northwestern oceanic area, but weakened throughout most of the European continent.

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Ping Zhao, Phil Jones, Lijuan Cao, Zhongwei Yan, Shuyao Zha, Yani Zhu, Yu Yu, and Guoli Tang

Abstract

Using the reconstructed continuous and homogenized surface air temperature (SAT) series for 16 cities across eastern China (where the greatest industrial developments in China have taken place) back to the nineteenth century, the authors examine linear trends of SAT. The regional-mean SAT over eastern China shows a warming trend of 1.52°C (100 yr)−1 during 1909–2010. It mainly occurred in the past 4 decades and this agrees well with the variability in another SAT series developed from a much denser station network (over 400 sites) across this part of China since 1951. This study collects population data for 245 sites (from these 400+ locations) and split these into five equally sized groups based on population size. Comparison of these five groups across different durations from 30 to 60 yr in length indicates that differences in population only account for between 9% and 24% of the warming since 1951. To show that a larger urbanization impact is very unlikely, the study additionally determines how much can be explained by some large-scale climate indices. Anomalies of large-scale climate indices such as the tropical Indian Ocean SST and the Siberian atmospheric circulation systems account for at least 80% of the total warming trends.

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Adam A. Scaife, Elizabeth Good, Ying Sun, Zhongwei Yan, Nick Dunstone, Hong-Li Ren, Chaofan Li, Riyu Lu, Peili Wu, Zongjian Ke, Zhuguo Ma, Kalli Furtado, Tongwen Wu, Tianjun Zhou, Tyrone Dunbar, Chris Hewitt, Nicola Golding, Peiqun Zhang, Rob Allan, Kirstine Dale, Fraser C. Lott, Peter A. Stott, Sean Milton, Lianchun Song, and Stephen Belcher

Abstract

We present results from the first 6 years of this major UK government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between UK and Chinese climate scientists and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modelling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over three hundred peer reviewed studies generated jointly by UK and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skilful predictions of important aspects of Chinese climate such as East Asian Summer Monsoon rainfall. In addition, the development of improved modelling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real time climate services. Participation of dozens of institutes through sub-projects in this programme, which is governed by the Met Office Hadley Centre, the China Meteorological Administration and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services.

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