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This paper investigates the impacts of the El Niño Southern Oscillation (ENSO) on various aspects of heat waves (HWs), including frequency, duration, and magnitude, over China during 1961-2014. Results show that El Niño (La Niña) significantly amplifies (weakens) the HW activities in most areas of China. Such influences are particularly strong in southern China. HW activities are enhanced (weakened) during the summers following mature El Niño (La Niña) episodes, with increased (reduced) occurrence of HW events and number of HW days, as well as prolonged (shortened) duration and elevated (decreased) amplitude of such events. These amplifying effects are substantially stronger for severe HWs (i.e., hottest and longest episodes) than for those events of average duration and intensity. Diagnosis by compositing reanalysis data over ENSO events indicates that the atmospheric circulation during the summers following El Niño is characterized by anomalous rising motion over the tropical central Pacific and Indian Oceans, and sinking motion over the western North Pacific (WNP). The anomalous subsidence over the WNP is accompanied by reduced precipitation and condensational heating, as well as anomalous anticyclonic flows in the lower troposphere. El Niño also induces a stronger South Asian high, which can strengthen the WNP anticyclone and subtropical high. These changes provide a favorable environment for the occurrence and sustenance of HWs in China. Analogous arguments apply to changes with the opposite polarity in association with La Niña events. [ABSTRACT FROM AUTHOR]

Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances. [ABSTRACT FROM AUTHOR]

Quantifying the urbanization effect on trends in climate extremes is important both for detection and attribution studies and for human adaptation; however, a fundamental problem is how to accurately estimate a trend and its statistical significance, especially for non-Gaussian and serially dependent data. In this paper, the choice of trend estimation and significance testing method is suggested as important for these kinds of studies, as illustrated by quantifying the urbanization effect on trends in seven hot-extreme indices for the megacity of Shanghai during 1961-2013. Both linear and nonlinear trend estimation methods were used. The trends and corresponding statistical significances were estimated by taking into account potential non-Gaussian and serial dependence in the extreme indices. A new method based on adaptive surrogate data is proposed to test the statistical significance of the ensemble empirical mode decomposition (EEMD) nonlinear trend. The urbanization contribution was found to be approximately 34 % (43 %) for the trend in the non-Gaussian distributed heat wave index based on nonparametric linear trend (EEMD nonlinear trend) estimation. For some of the other six hot-extreme indices analyzed, the urbanization contributions estimated based on linear and nonlinear trends varied greatly, with as much as a twofold difference between them. For the linear trend estimation itself, the ordinary least squares fit can give a substantially biased estimation of the urbanization contribution for some of the non-Gaussian extreme indices. [ABSTRACT FROM AUTHOR]

Extreme heat events happen frequently in East Asia, and may cause great damage to the ecosystem and society. The synergistic effect of the summer positive North Atlantic Oscillation (pNAO) and positive northwest Pacific (pNWP) sea surface temperature anomaly (SSTA) on the interannual variability of the extreme heat events in the central–eastern China (CEC) is investigated in this study. The two factors act synergistically in strengthening the extreme heat events in the CEC via a series of atmospheric bridges, and the CEC is likely to experience a hotter summer when both the summer pNAO and pNWP SSTA occur. The pNWP SSTA increases the strength of pNAO via the eastward propagating Rossby wave from the western Pacific. The enhanced pNAO induces a stronger eastward Rossby wave propagation across the Eurasian continent, and leads to a strong anomalous anticyclone over the CEC. The significantly increased atmosphere thickness increases the air temperature of the layer, and favors the extreme heat events in the CEC. Besides, the pNWP SSTA also has adjacent effect on the atmospheric circulation over the CEC, which could lead to a positive geopotential height anomaly. Therefore, the summer pNAO and pNWP SSTA act synergistically in influencing the atmospheric circulation over the CEC, and thereby significantly increase the extreme heat events in the CEC. [ABSTRACT FROM AUTHOR]

Heatwaves can have significant negative socioeconomic impacts and damage ecosystems. Consequently, accurate forecasts of such events are of great importance. In this study, the backward nonlinear local Lyapunov exponent (BNLLE) is used to investigate the local predictability of summer (June, July, and August) heatwave events over south China (SC). The predictability of the summer 2-m temperature (T2m) was quantified first. The results show that the summer T2m has a high predictability, and its predictability limit can reach 12 days, which is close to the upper limit of atmospheric predictability. Nine major heatwave events that occurred over SC were analysed, and their error dynamics and local predictabilities were studied using the BNLLE method. The local predictability limits covered a wide range, varying from 4 to 12 days. Analysis of the forecast error growth and associated rates revealed that the nine major heatwave events showed different error dynamics, thereby leading to the different local predictability limits. In addition, the regional dynamical information associated with these nine heatwave events was investigated and the error dynamics were found to have a heterogeneous spatial distribution. That is, both the error growth and their rates in the northern regions were larger than those in the southern regions. The regional dynamical information associated with the summer T2m also showed the same pattern. Therefore, the northern regions of SC are sensitive to error growth and limit the heatwave forecast skill. [ABSTRACT FROM AUTHOR]

We investigate a record-breaking heat wave in southern China (SC) and explore its association with the South China Sea (SCS) summer monsoon (SCSSM), using station observations and various reanalysis products. This heat wave event started in mid-May 2018 and persisted more than 15 days, when the maximum air temperature anomaly exceeded 6 °C. Meanwhile, the onset of the SCSSM was extremely late in 2018, primarily due to the intrusion of easterly winds over the SCS. We show that the anomalous easterlies over the SCS associated with the delayed SCSSM could block the moisture transport from the tropical oceans to SC, which led to decreased rainfall, increased surface radiation, and elevated probability of heat wave in SC during May 2018. Further analysis reveals that both SC heat waves and SCSSM were significantly affected by the Pacific subtropical high (PSH). The westward extension of the PSH can hinder the establishment of SCSSM via inducing easterly anomalies over the SCS, which reduces SC rainfall and results in a drier surface condition. Moreover, the westward displacement of the PSH may cause anomalously high pressures, descending air motions, and divergent winds over SC, which triggers above-normal air temperatures that are conducive to the occurrences of SC heat waves. This study also underlines the importance of Eurasian planetary wave trains in bridging the upstream climate variability and the changes in PSH during boreal spring, which could be used to improve the intra-seasonal predictions of SC heat wave and SCSSM onset. [ABSTRACT FROM AUTHOR]

The sharp rise in temperature has increased the frequency, intensity, duration, and timing of heat waves (HWs) over different regions of the world. Due to climate change, the China–Pakistan Economic Corridor (CPEC) is one of the highly vulnerable regions to HWs and needs comprehensive research studies to investigate the HW phenomenon in the region. This study analyzed the spatial and temporal changes in the daytime and nighttime HW characteristics based on multiple indices over the CPEC region. We used daily maximum and minimum temperatures (hereafter Tmax and Tmin) of 48 meteorological stations for the time period of 1980–2016. The non-parametric modified Mann–Kendall, Theil–Sen's test, least square method, student t-test, and chi-square goodness-of-fit test techniques were used to analyze the long-term spatiotemporal changes in the daytime and nighttime HW characteristics. The results of the study show that the number of annual daytime/nighttime HW events, annual sum of participating daytime/nighttime HW days, the average length of annual daytime/nighttime HW events, duration of the longest annual daytime/nighttime HW event, the average magnitude of all annual daytime/nighttime HW events, amplitude of the hottest annual daytime/nighttime HW event, and the ending date of annual last daytime/nighttime HW event exhibited significant increasing trends at the rate of 0.78/1.43 events decade−1, 10/11.82, 2/1.74, 2.16/1.52 days decade−1, 0.40/0.59, 0.24/0.73 °C decade−1, and 12.29/10 days decade−1, respectively. Despite all, the onset date of the annual first daytime/nighttime HW event has shown a significant decreasing trend of − 5.71/− 5 days decade−1. The obvious positive trend of HW behaviors indicates that the country has experienced more frequent, stronger, more intense, and longer HWs during the study period. The spatial pattern of the trend indicates that the southern, central and eastern parts of Pakistan exhibited prominent and consistent HW activities, while the northwestern mountainous regions showed high spatial variability with some stations exhibited decreasing trends in HW indices. The findings of this study will be a base for the projection and mitigation of HWs in the region. Based on the study findings, we recommend that the mechanism of HW and its natural and anthropogenic drivers should be thoroughly investigated over the study region. [ABSTRACT FROM AUTHOR]

The changes in three aspects of frequency, intensity and duration of the compound, daytime and nighttime heat waves (HWs) over China during extended summer (May–September) in a future period of the mid-21st century (FP; 2045–2055) under RCP4.5 scenario relative to present day (PD; 1994–2011) are investigated by two models, MetUM-GOML1 and MetUM-GOML2, which comprise the atmospheric components of two state-of-the-art climate models coupled to a multi-level mixed-layer ocean model. The results show that in the mid-21st century all three types of HWs in China will occur more frequently with strengthened intensity and elongated duration relative to the PD. The compound HWs will change most dramatically, with the frequency in the FP being 4–5 times that in the PD, and the intensity and duration doubling those in the PD. The changes in daytime and nighttime HWs are also remarkable, with the changes of nighttime HWs larger than those of daytime HWs. The future changes of the three types of HWs in China in two models are similar in terms of spatial patterns and area-averaged quantities, indicating these projected changes of HWs over the China under RCP4.5 scenario are robust. Further analyses suggest that projected future changes in HWs over China are determined mainly by the increase in seasonal mean surface air temperatures with change in temperature variability playing a minor role. The seasonal mean temperature increase is due to the increase in surface downward longwave radiation and surface shortwave radiation. The increase in downward longwave radiation results from the enhanced greenhouse effect and increased water vapour in the atmosphere. The increase in surface shortwave radiation is the result of the decreased aerosol emissions, via direct aerosol–radiation interaction and indirect aerosol–cloud interaction over southeastern and northeastern China, and the reduced cloud cover related to a decrease in relative humidity. [ABSTRACT FROM AUTHOR]

With the consideration of spatial extension of heatwave events, two kind of regional heatwaves using absolute and relative thresholds, namely RHWs-A and RHWs-R, are investigated during 1959-2013. The temperature data is derived from the daily maximum temperatures (DMTs) of 587 stations in China. Totally 298 RHWs-A and 374 RHWs-R are identified during the past 55 years, and both of them are growing more frequent since the mid-1980s. By utilizing the cluster analysis, several typical spatial distributions of RHWs-A/RHWs-R are obtained. For RHWs-A, there are three clusters covering the southeastern, northwestern China and the lower reaches of Yangtze River, of which the southeastern cluster groups the most heatwaves. For RHWs-R, there are seven clusters distributed throughout the whole regions of China. The clusters in the northwestern and northeastern China are more stable than others for both RHWs-A and RHWs-R, and the northern clusters are of larger intensity than that of the southern ones. All RHWs-A/RHWs-R are accompanied by the anomalous high systems along with the reduced soil moisture. The southern clusters are controlled by Northwestern Pacific subtropical high (WPSH), and the northern ones are influenced by the mid-latitude high systems. The influences of atmospheric circulations and soil moisture on regional heatwaves are further demonstrated by two case analyses of the severe RHW-A in 2003 and the RHW-R in 2013. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) can have disastrous impacts on human activities and natural systems, and are one of the current foci of scientific research, particularly in the context of global warming. However, there is no standard definition of a HW, which makes assessment of temporal trends a challenge. In this study, based on daily mean, maximum and minimum temperature, and relative humidity datasets from China Meteorological Administration, the patterns, trends and variations of HW in China during 1961-2014 are investigated. Sixteen previously published HW indices (HIs) are calculated, which are divided into two types using relative and absolute threshold temperatures, respectively. During 1961-2014, both relative and absolute threshold HIs show the highest number of HW in Jianghua and South China, geographically consistent with the climate characteristics of China. The majority of HIs shows negative/positive trends of HW days before/after 1990 over the whole of China, but especially in Jianghua and South China, which reflects rapid warming since 1990. There are significant correlations among different HIs in the same type (both absolute and relative), but correlations are weak between relative and absolute threshold HIs. Because relative and absolute HIs show contrasting trends, the choice of HI is therefore critical for future analysis [ABSTRACT FROM AUTHOR]

Summer heat waves with persistent extreme high temperatures have been occurring with increasing frequency in recent decades. These extreme events have disastrous consequences for human health, economies, and ecosystems. In this study, we examine three summers with intense and protracted heat waves: the summers of 2003, 2006, and 2013, with high temperatures located mainly in southeastern, southwestern, and eastern China, respectively. The synoptic-scale characteristics of these heat waves and associated atmospheric circulation anomalies are investigated. In the early heat wave episode of 2003, a heat center was located in the southeast coastal provinces during the first 20 days of July. The maximum southward displacement of the East Asian jet stream (EAJS) induced anticyclonic anomalies to the south, associated with southwestward intensification of the western North Pacific subtropical high (WNPSH), and extreme high temperatures were found only to the south of the Yangtze River. In the later episode, a poleward displacement of the EAJS and an enhanced WNPSH over the midlatitudes of eastern China resulted in a 'heat dome' over the region, and the heat wave extended northward to cover a larger area of eastern China. The coupling between the westward-enhanced WNPSH and poleward-displaced EAJS was found in the East China heat wave of 2013 as well. But the area of high temperatures reached far to the north in August 2013, with below-normal temperatures located in a small region of South China. In the 2006 southwestern drought and heat wave, extreme poleward displacement of the EAJS, associated with extraordinary westward extension of the WNSPH, resulted in further blocking of the moisture supply from the southwest monsoon. Large-scale moisture deficiencies, dry conditions, and downslope winds were common features of all investigated heat wave episodes. But in 2006, low-level heat lows associated with a well-mixed layer due to intensive daytime heating and atmospheric turbulence were emphasized. [ABSTRACT FROM AUTHOR]