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Based on the daily maximum temperature (DMT) records at 512 stations during 1961-2007, the geographical patterns and temporal variations of hot days (HDs) and heat waves (HWs, including those persisting for 3-5 days and longer) over mainland China were studied. The HD (and hence HW) was defined in two ways, one by an absolute criterion, DMT >35°C, as applied in the nationwide meteorological agencies and another in a relative sense, DMT > the 90th percentile threshold of a local daily temperature distribution around the day. Two centers of high frequencies (over 5 days per year) of the absolute HDs during June-September were found in the regions of Xinjiang and the mid-lower reaches of the Yangtze River. The highest frequencies of the absolute HWs were about 1.5 times per year in the Xinjiang region and to the south of the mid-lower reaches of the Yangtze River. The frequencies of the relative HWs were about 1-1.5 times per year in most of China. The HDs and HWs increased significantly during the studied period in most of China, especially over the southeastern coast and northern China (by over 4 days per decade for relative HDs and 0.4 times per decade for relative HWs), but decreased significantly at some stations in the lower reaches of the Yellow River. Over most of China except northwestern China, the frequency of HDs was high during the 1960s-1970s, low in the 1980s, and high afterwards, with strong interannual variations. A remarkable increasing trend of HDs occurred after the 1990s in all regions. The changes in HDs and HWs were closely related to those in rain days and atmospheric circulation patterns at the interannual and interdecadal scales.

Dengue, a viral infection transmitted between people by mosquitoes, is one of the most rapidly spreading diseases in the world. Here, we report the analyses covering 11 y (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) from the city of Guangzhou in southern China. Using the first 8 y of data to develop an ecologically based model for the dengue system, we reliably predict the following 3 y of dengue dynamics-years with exceptionally extensive dengue outbreaks. We demonstrate that climate conditions, through the effects of rainfall and temperature on mosquito abundance and dengue transmission rate, play key roles in explaining the temporal dynamics of dengue incidence in the human population. Our study thus contributes to a better understanding of dengue dynamics and provides a predictive tool for preventive dengue reduction strategies.D engue is one of the most rapidly spreading diseases in the world (1), including within the Guangdong province of southern China (2). During the last 50 y, the incidence of dengue has increased 30-fold with increasing geographic expansion to new countries (1). In 2010, an estimated 390 million dengue infections occurred, of which around 96 million showed symptoms (3). Dengue outbreaks in China were previously thought to be imported and initiated by people traveling to China from dengue-endemic areas elsewhere (4); however, recent studies suggest that dengue may now be endemic to China as well (2). The epidemiological triangle of both dengue fever and dengue hemorrhagic fever, which is the more serious form of dengue, includes hosts (humans), pathogens (one or more of five dengue virus serotypes) (5), and mosquito vectors (Aedes albopictus and Aedes aegypti) with their ecological interactions (6). The dengue outbreaks are qualitatively known to be strongly influenced by temperature (7), humidity, rainfall, and socioeconomic factors like urbanization (8). However, a full understanding of the quantitative nature of such effects is largely lacking. With this paper, we provide such a quantitative understanding of dengue dynamics.In 2014, an extensive dengue outbreak hit China, with 47,127 dengue cases diagnosed, a new record since 1986 (9). Since the 1990s, dengue epidemics have gradually spread from Guangdong, Hainan, and Guangxi provinces (9). We present here a time series analysis of dengue dynamics, using dengue surveillance data for the years 2005−2015 from Guangzhou, the largest city in Guangdong and the city with the most dengue cases in China. We split the main analysis by using the first 8 y to develop a model, and the three remaining years to test that model, as these latter years encompass exceptionally extensive dengue outbreaks.Monthly human dengue incidence data (number of diagnosed cases) were obtained from the China National Notifiable Disease Surveillance System (10) (Fig. 1). Monthly surveillance data of A. albopictus density, the only dengue vector species in Guangzhou, were obtained from local Centers for Disease Control and Prevention (11) (Metho...

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Based on daily rainfall and temperature data for the summer monsoon season in mainland China during 1961–2005, this paper demonstrated an overall decreasing trend in the frequency of light rain events in association with regional warming, and different local trends in the frequency of moderate rain events in association with atmospheric circulation anomalies. The frequencies of moderate and extreme rain events increase in eastern China centered over the middle‐lower reaches of the Yangtze River, but decrease in North China and Southwest China. This pattern of rainfall trends in China is different from that in the Indian monsoon area, where an increase of extreme rain events in the monsoon season during 1951–2000 was found, indicating different responses of regional monsoons to a warming environment.

Compared to individual hot days/nights, compound hot extremes that combine daytime and nighttime heat are more impactful. However, past and future changes in compound hot extremes as well as their underlying drivers and societal impacts remain poorly understood. Here we show that during 1960-2012, significant increases in Northern Hemisphere average frequency (~1.03 days decade −1 ) and intensity (~0.28°C decade −1 ) of summertime compound hot extremes arise primarily from summer-mean warming. The forcing of rising greenhouse gases (GHGs) is robustly detected and largely accounts for observed trends. Observationally-constrained projections suggest an approximate eightfold increase in hemispheric-average frequency and a threefold growth in intensity of summertime compound hot extremes by 2100 (relative to 2012), given uncurbed GHG emissions. Accordingly, endof-century population exposure to compound hot extremes is projected to be four to eight times the 2010s level, dependent on demographic and climate scenarios.

ABSTRACT:A new homogenized temperature data set called the China Homogenized Historical Temperature Dataset (CHHTD-V1.0) has been developed, and it includes daily and monthly mean temperature series from 2419 national stations distributed throughout mainland China for the period from 1951 to the present. The inhomogeneities in individual station series were detected using a penalized maximum t-test (PMT) that accounted for the first-order autocorrelation. Detailed metadata information was applied to validate the changepoints caused by changes in local observation systems. Comparative analyses suggested that the quantile-matching (QM) adjustments that accounted for high-order discontinuities led to more reasonable results than the MEAN adjustments for the daily temperature series. Therefore, the QM method was applied to adjust the discontinuities caused by non-climate changes such as changing of observing site, instrumentation and observation environments. The physical consistency among the daily maximum, mean and minimum temperatures (T max , T m and T min ) was also checked for each station. Based on the new homogenized data set, linear trends in the annual and seasonal temperature series from 1960 to 2014 were calculated. In comparison with the original data set, the homogenized data set improves the geographical consistency of the long-term climate trends over the region. The updated nationwide mean warming rate reached 0.22 ∘ C per 10 years for the T max , 0.27 ∘ C per 10 years for the T m and 0.38 ∘ C per 10 years for the T min from 1960 to 2014, which are considerably larger than the previous estimates that were based on the more frequently used networks of a few hundred stations in China.

[1] In this paper, the Weather Research and Forecasting Model, coupled to the Urban Canopy Model, is employed to simulate the impact of urbanization on the regional climate over three vast city agglomerations in China. Based on high-resolution land use and land cover data, two scenarios are designed to represent the nonurban and current urban land use distributions. By comparing the results of two nested, high-resolution numerical experiments, the spatial and temporal changes on surface air temperature, heat stress index, surface energy budget, and precipitation due to urbanization are analyzed and quantified. Urban expansion increases the surface air temperature in urban areas by about 1 C, and this climatic forcing of urbanization on temperature is more pronounced in summer and nighttime than other seasons and daytime. The heat stress intensity, which reflects the combined effects of temperature and humidity, is enhanced by about 0.5 units in urban areas. The regional incoming solar radiation increases after urban expansion, which may be caused by the reduction of cloud fraction. The increased temperature and roughness of the urban surface lead to enhanced convergence. Meanwhile, the planetary boundary layer is deepened, and water vapor is mixed more evenly in the lower atmosphere. The deficit of water vapor leads to less convective available potential energy and more convective inhibition energy. Finally, these combined effects may reduce the rainfall amount over urban areas, mainly in summer, and change the regional precipitation pattern to a certain extent.