Occurrence Of Extremes Research Articles

Amplified Upward Trend of the Joint Occurrences of Heat and Ozone Extremes in China over 2013–20

Abstract Climate change and air pollution are two intimately interlinked global concerns. The frequency, intensity, and duration of heat waves are projected to increase globally under future climate change. A growing body of evidence indicates that health risks associated with the joint exposure to heat waves and air pollution can be greater than that due to individual factors. However, the cooccurrences of heat and air pollution extremes in China remain less explored in the observational records. Here we investigate the spatial pattern and temporal trend of frequency, intensity, and duration of cooccurrences of heat and air pollution extremes using China’s nationwide observations of hourly PM2.5 and O3, and the ERA5 reanalysis dataset over 2013–20. We identify a significant increase in the frequency of cooccurrence of wet-bulb temperature (Tw) and O3 exceedances (beyond a certain predefined threshold), mainly in the Beijing–Tianjin–Hebei (BTH) region (up by 4.7 days decade−1) and the Yangtze River delta (YRD). In addition, we find that the increasing rate (compared to the average levels during the study period) of joint exceedance is larger than the rate of Tw and O3 itself. For example, Tw and O3 coextremes increased by 7.0% in BTH, higher than the percentage increase of each at 0.9% and 5.5%, respectively. We identify same amplification for YRD. This ongoing upward trend in the joint occurrence of heat and O3 extremes should be recognized as an emerging environmental issue in China, given the potentially larger compounding impact to public health.

High impact compound events in Australia

Many natural disasters in Australia occur as a result of meteorological drivers occurring in combination. These Compound Events (CEs) amplify risk to socio-economic and ecological systems relative to single meteorological events. We undertake a bivariate assessment for two hazard combinations important in Australia: heatwaves and drought, and strong winds and heavy precipitation. We use observations and reanalysis data to build a high-resolution climatology spanning the period from 1980 to 2014 and identify the north-western Australian coast as a region particularly prone to the joint occurrence of wind and precipitation extremes. Heatwaves and drought frequently co-occur multiple times per year over most of Australia with shorter return periods in the tropical north. We show that CMIP6 models capture the return periods of both CEs well. We then examine projected changes in both CEs under future conditions (2066–2 100) under a moderate and high emission scenario. All CMIP6 models project decreases in the return periods (i.e. more frequent events) of co-occurring heatwaves and droughts with the south of Australia particularly affected. Northern Australia is projected to become more at risk from wind and precipitation extremes while southern Australia experiences lower risk. The high level of skill in simulating the two CEs examined, combined with the coherent spatial patterns projected by the CMIP6 models suggest there is merit in using these models to examine the large-scale risk of CEs in the future, and that these can be used to support national scale planning for the changing risk of CEs.

The impacts of the East Asian subtropical westerly jet on weather extremes over China in early and late summer

Summer weather extremes (e.g., heavy rainfall, heat waves) in China have been linked to anomalies of summer monsoon circulations. The East Asian subtropical westerly jet (EASWJ), an important component of the summer monsoon circulations, was investigated to elucidate the dynamical linkages between its intraseasonal variations and local weather extremes. Based on EOF analysis, the dominant mode of the EASWJ in early summer is characterized by anomalous westerlies centered over North China and anomalous easterlies centered over the south of Japan. This mode is conducive to the occurrence of precipitation extremes over Central and North China and humid heat extremes over most areas of China except Northwest and Northeast China. The centers of the dominant mode of the EASWJ in late summer extend more to the west and north than in early summer, and induce anomalous weather extremes in the corresponding areas. The dominant mode of the EASWJ in late summer is characterized by anomalous westerlies centered over the south of Lake Baikal and anomalous easterlies centered over Central China, which is favorable for the occurrence of precipitation extremes over northern and southern China and humid heat extremes over most areas of China except parts of southern China and northern Xinjiang Province. The variability of the EASWJ can influence precipitation and humid heat extremes by driving anomalous vertical motion and water vapor transport over the corresponding areas in early and late summer.摘要东亚副热带西风急流是影响中国极端天气的重要原因之一, 然而之前的研究主要关注整个夏季急流的变率, 对其早夏和晚夏变率的区别及其对极端天气的影响关注较少. 本文研究了早夏和晚夏东亚副热带西风急流季节内变化特征的区别, 以及这种区别带来的极端天气的差异及其可能的动力学机制. 研究结果表明, 相比于早夏, 晚夏急流季节内变化中心位置偏西偏北, 通过改变垂直运动和水汽输送可以影响极端降水和湿热浪在相应区域的发生概率.

Spatiotemporal nonhomogeneous poisson model with a seasonal component applied to the analysis of extreme rainfall

This paper develops an extension of spatiotemporal models that handle count data using nonhomogeneous Poisson processes. In this new proposal, we incorporate a seasonal cycle component in the definition of the intensity function to control possible effects produced by the occurrence of the event of interest in regular periods. The seasonal cycle can cause problems in estimating the shape parameter of the Weibull and generalized Goel intensity functions. This shape parameter serves to confront the research hypothesis that seeks to identify a trend in the occurrence rate of an event of interest. In the case of the Weibull intensity function, a value significantly equal to one of the shape parameters indicates a constant rate of occurrence, less than one indicates a decreasing rate, and greater than one indicates an increasing rate. In the case of the Goel intensity function, parameter values less than or equal to one indicate a decreasing occurrence rate, and values greater than one indicate the presence of a change point. We also built a spatial model using the Musa-Okumoto intensity function as an alternative to approximate counting processes for which there is a decreasing trend in the occurrence rate of the event of interest. We estimated the parameters of the proposed method from a Bayesian perspective. Finally, we fitted the proposed model and compared it with other approximations to analyze the frequency of extreme rainfall in the northern region of the states of Maranhão and Piauí in northeastern Brazil over ten years. Among the main results, we found that (1) the proposed method has proven superior in terms of fit and prediction performance than the other models, and (2) unlike other approximations, the proposed model does not detect changes in the rate of extreme rainfall occurrences.

Central Asian Precipitation Extremes Affected by an Intraseasonal Planetary Wave Pattern

Abstract The characteristics and mechanisms of extreme precipitation events over central Asia are investigated based on daily data and percentile criteria. The composited extreme precipitation events have a life cycle of about 10 days. The precipitation signal is weak but significant from eight to two days before the peak. Then it amplifies rapidly and reaches its peak in two days. The earliest precipitation signal appears over the northwest of central Asia and moves southeastward. It maximizes over northern central Asia and the windward side of the mountainous region, suggesting the role of orography in the precipitation extremes. Diagnosis suggests that the precipitation extremes are closely tied to a quasi-stationary planetary wave train emanating from the North Atlantic and the resultant disturbed Asian subtropical jet. The sharpened and accelerated Atlantic jet 10 days before the precipitation peak feeds a cyclonic anomaly at its exit region, which disperses energy downstream and forms a well-defined barotropic Rossby wave train in the Asian subtropical jet, resulting in an anomalous cyclone to the west of central Asia. On the one hand, the cyclone-induced water vapor transport into central Asia enhances the moisture content and increases the convective instability in the lower troposphere, providing a favorable thermodynamical condition for deep convections. On the other hand, the vorticity and temperature advection induced by this cyclone and the mechanical lifting on the windward side of mountains provide a favorable dynamical condition for ascending motion, which triggers the release of convective instability and the occurrence of precipitation extremes in central Asia.

Formation, radiative forcing, and climatic effects of severe regional haze

Abstract. Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remain unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox]=[O3]+[NO2]), and the mean [OOA] / [Ox] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol–PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze–PBL interaction and the aerosol regional climatic effect, contributing to more than 30 % of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of −63 to −88 W m−2 at the surface and strong positive radiative forcing (warming) of 57 to 82 W m−2 in the atmosphere, with a slightly negative net radiative forcing of about −6 W m−2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing.

The Mesoscale Response to Global Warming over the Pacific Northwest Evaluated Using a Regional Climate Model Ensemble

AbstractThis paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century.Significance StatementThis paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation.

Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models

Abstract. Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r>0.95 for ML and r=0.14∼0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r=0.74 for ML and r<0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.

Dynamic estimates of extreme-case CO2 storage capacity for basin-scale heterogeneous systems under geological uncertainty

Geological CO2 storage is expected to grow dramatically in the coming decades to meet global climate targets. Assessment of worldwide storage resources using static methods indicates significant theoretical potential for large-scale deployment. Dynamic capacity estimates are needed at the basin-scale that fully capture the impact of geological uncertainty and account for regional limits on pressure buildup. Accurate quantification of the risk of low or critically low capacity under extreme occurrences of heterogeneity will be increasingly important. There are significant challenges associated with efficient computation of low probability capacity within Monte Carlo frameworks at these scales. In this paper, we propose a workflow for uncertainty quantification that is able to efficiently estimate increasingly outer percentiles of dynamic capacity such as P1, P0.1, or even lower probability events. Our approach is based on the rare-event methodology that uses a subset simulation approach to concentrate sampling of the parameter space in the tail regions of the capacity distributions. This approach greatly speeds up uncertainty quantification for very small probabilities compared to standard Monte Carlo. We demonstrate the method by introducing a correlated heterogeneity field to a highly prospective basin-scale system that can support regional injection rates of 100 million tons annually. We find that the outer quantiles are more sensitive to the underlying geostatistical model compared to the median P50 capacity. This implies that for large-scale systems, well characterized heterogeneity is essential to identify the likelihood of very rare yet still relevant dynamic estimates of storage capacity.

Analysis of hydrological extremes in the Guaíba hydrographic region: an application of extreme values theory

Knowing the behavior of extreme hydrological phenomena is essential so that the impacts resulting from these natural events are minimized. Rio Grande do Sul has frequently been hit by extreme events such as droughts and floods, and these events are associated with several consequences, such as energy or water rationing, urban flooding and damage to hydraulic structures. In this context, the analysis of historical series extremes of hydrometeorological data through the Extreme Values Theory (EVT) is one of the ways to determine the variability due to climate change, enabling the modeling of extreme events. EVT makes it possible to know the frequency with which extreme events occur, allowing extrapolation beyond the historical series, generating occurrence probabilities of such an event. Therefore, the purpose of this work was to apply the Extreme Values Theory in hydrological the data historical series of flow and precipitation in the Guaíba hydrographic region and to carry out occurrence probabilities of intense events return, helping in the planning of the hydrographic watersheds that are in this region, as well as to verify whether the EVT has return periods similar to the climate projections of CMIP5 models. The results demonstrate that the values of flow and precipitation, in the historical series used, have already presented changes regarding the volume and frequency of extreme events occurrence and, in the future, for some stations, values can be expected both above and below the extremes already observed in the historical series.

Generating an ensemble of mutually exclusive and exhaustive waves targeted for extreme responses

To examine the reliability or performance of marine systems related to dynamic time-varying responses, time domain simulation may be required. But for long durations, brute-force simulation is clearly not feasible from a computational point of view to examine converged extreme value statistics. An additional challenge is defining a set of mutually exclusive and exhaustive wave excitation records which excite the desired extreme response(s). To address these challenges, this work develops a non-linear Design Loads Generator (NL-DLG) process which links wave profiles targeted for extreme responses generated via response-conditioning wave techniques to a probabilistic framework which examines the possible correlation or mutual exclusivity between those wave profiles. The end result is an ensemble of short targeted wave profiles which excite converged extreme value return-period statistics of a defined response that may be excited by multiple correlated processes. The method of the NL-DLG process is explained by applying it towards rare wave groups, where the result is an ensemble of short wave profiles which contain extreme occurrences of different wave groups targeted for the defined exposure duration. These generated wave excitation profiles are compared to physical data from the Pt. Reyes buoy and then numerical simulations are employed to consider rarer events.

Population management in an urban center using the dynamic integrated solution for an adequate atmospheric environmental quality

Accelerated growth in urban populations has become a powerful force for human development, particularly in developed countries. Metropolitan cities are centers for technical and economic advancement, but air pollution, overflowing of water, and other climate effects still pose significant problems related to nature, climate, and the environment. Cities are vulnerable to increasingly dense, diverse, and interdependent urban systems. A single extreme occurrence can contribute to a systemic break-up of a city's infrastructure, often like dominoes. In this paper, a dynamic integration-assisted population management solution (DI-PMS) has been proposed. DI-PMS recognizes that the latest facilities' optimal usage of knowledge and technologies is needed to increase urbanization. They are one of the critical priorities of the weather community. Such integrated urban weather, environmental, and climate services will help cities address dangers including storms, floods, heatwaves, and air pollution, especially in climate change. The goal is to create urban facilities that satisfy communities' unique needs by high-resolution forecasting and pollution reduction climate services, which allow the construction of durable, robust, and thriving cities that support the Sustainable Development Goals. Several recent international surveys to explore these topics have been undertaken. DI-PMS gives a brief description of urban hydrometeorological, climate and air pollution activities, outlines the new urban integrated weather and environmental services concept, and emphasizes the need for science to be implemented.

Compound hot temperature and high chlorophyll extreme events in global lakes

An emerging concern for lake ecosystems is the occurrence of compound extreme events i.e. situations where multiple within-lake extremes occur simultaneously. Of particular concern are the co-occurrence of lake heatwaves (anomalously warm temperatures) and high chlorophyll-a extremes, two important variables that influence the functioning of aquatic ecosystems. Here, using satellite observations, we provide the first assessment of univariate and compound extreme events in lakes worldwide. Our analysis suggests that the intensity of lake heatwaves and high chlorophyll-a extremes differ across lakes and are influenced primarily by the annual range in surface water temperature and chlorophyll-a concentrations. The intensity of lake heatwaves is even greater in smaller lakes and in those that are shallow and experience cooler average temperatures. Our analysis also suggests that, in most of the studied lakes, compound extremes occur more often than would be assumed from the product of their independent probabilities. We anticipate compound extreme events to have more severe impacts on lake ecosystems than those previously reported due to the occurrence of univariate extremes.

Coastal Wave Extremes around the Pacific and Their Remote Seasonal Connection to Climate Modes

At first order, wind-generated ocean surface waves represent the dominant forcing of open-coast morpho-dynamics and associated vulnerability over a wide range of time scales. It is therefore paramount to improve our understanding of the regional coastal wave variability, particularly the occurrence of extremes, and to evaluate how they are connected to large-scale atmospheric regimes. Here, we propose a new “2-ways wave tracking algorithm” to evaluate and quantify the open-ocean origins and associated atmospheric forcing patterns of coastal wave extremes all around the Pacific basin for the 1979–2020 period. Interestingly, the results showed that while extreme coastal events tend to originate mostly from their closest wind-forcing regime, the combined influence from all other remote atmospheric drivers is similar (55% local vs. 45% remote) with, in particular, ~22% coming from waves generated remotely in the opposite hemisphere. We found a strong interconnection between the tropical and extratropical regions with around 30% of coastal extremes in the tropics originating at higher latitudes and vice-versa. This occurs mostly in the boreal summer through the increased seasonal activity of the southern jet-stream and the northern tropical cyclone basins. At interannual timescales, we evidenced alternatingly increased coastal wave extremes between the western and eastern Pacific that emerge from the distinct seasonal influence of ENSO in the Northern and SAM in the Southern Hemisphere on their respective paired wind-wave regimes. Together these results pave the way for a better understanding of the climate connection to wave extremes, which represents the preliminary step toward better regional projections and forecasts of coastal waves.

Variations in relative humidity across Poland and its possible impacts on outdoor thermal comfort: An analysis based on hourly data from 1995 to 2020

AbstractThis study investigated the variations in relative humidity (RH) and its impacts on outdoor thermal comfort in Poland. The study considered hourly RH data from 44 stations over the period 1995–2020. A countrywide declining trend in average RH was seen over the above period. This trend was more pronounced at stations in central and northwestern Poland. In the majority of the stations, in spring and summer, a statistically significant decline in the average RH was seen in the period 2008–2020 (second half of data) in comparison to that in the period 1995–2007 (first half of data). In all seasons, during the period 1995–2020, frequency distributions of RH corresponding to all stations were heavily left‐skewed and the peak occurred at an RH around about 90–95% or even higher. This indicated that high RH values are frequent in Poland. In the majority of the stations, an increase in the average number of hours per year above high percentiles of RH (95, 96th, 97th, 98th, 99th and 99.5th) and an increase in the average number of hours per year below low percentiles of RH (0.5th, 1st, 2nd, 3rd, 4th and 5th) were seen in the period 2008–2020 compared to that in the period 1995–2007. The above findings lead to the conclusion that occurrences of low and high extremes of RH have increased though the average of RH shows a decline. Also, in the majority of the stations, the number of hot–humid hours and the number of cold–dry hours have increased in the period 2008–2020 compared to those in the period 1995–2007. According to the Discomfort Index, over the period 1995–2020, the outdoor warm thermal comfort in Poland has declined due to high temperature and high humidity.

Spatio-temporal variability of climatic parameters across different altitudes of North- Western Himalaya

Climate change impact varies across different altitudinal ranges and demands local specific management strategies for water resource and farming system management. The present study analyses spacio-temporal climate parameters across different altitudes of Himachal Pradesh a hilly state of India. Analysis shows that annually, minimum temperature has significantly decreased by -0.09°C at altitude I (350 - 400 m) while maximum temperature has significantly increased by 0.05°C at altitudes I and II (1400-1500 m) and decreased significantly by -0.08°C at altitude III (2000- 2100 m). Higher regions Altitude – IV (2900-3000 m) received lowest rainfall (746.1 mm) with 30.2 % variation. Seasonal rainfall variability was higher in post monsoon (102 - 174%) and least in monsoon (21 - 57%). Annual rainfall at altitude I is strongly irregular (PCI 20.1 to 22.3), followed by altitude – IV (PCI 15-25); altitude – II irregular (PCI 15-20) and altitude – III moderate to irregular (PCI 12 -19) rainfall. Seasonal Index values for four altitudes fall between 0.91-0.96 revealed that rainfall is irregular and markedly seasonal with longer drier season. Higher wavelet powers in altitude - I and II after 2005 suggests frequency of extreme rainfall occurrence had increased.

Possible influence of the warm pool ITCZ on compound climate extremes during the boreal summer

In a globally changing climate, there is a growing concern for understanding and predicting compound climate extremes. However, the relationship of compound climate extremes with each other has been mostly analyzed in isolation and/or on regional scales. Little attention has been paid to their simultaneous occurrence and compound impacts worldwide. Here we demonstrate that the compound climate extremes in the Northern Hemisphere during the boreal summer are interconnected from the tropics to the Arctic. This connection originates from the interannual variations of the Indo-Pacific warm pool’s intertropical convergence zone (ITCZ). We demonstrate that the warm pool ITCZ (WPI) convection possibly influences three major teleconnection patterns (i.e. zonal, meridional, and circumglobal) where compound climate extremes occur along the wave train excited by the WPI convection. Most notably, the WPI can sufficiently explain climate variabilities in the North Atlantic region, which influences the occurrence of compound climate extremes in many parts of Europe and North America. Our findings advance the understanding of the interannual global/regional variability of climate extremes and are potentially valuable for predicting seasonal high-impact climate extremes.

Recent Increases in Exposure to Extreme Humid‐Heat Events Disproportionately Affect Populated Regions

AbstractExtreme heat research has largely focused on dry‐heat, while humid‐heat that poses a substantial threat to human‐health remains relatively understudied. Using hourly high‐resolution ERA5 reanalysis and HadISD station data, we provide the first spatially comprehensive, global‐scale characterization of the magnitude, seasonal timing, and frequency of dry‐ and wet‐bulb temperature extremes and their trends. While the peak dry‐ and humid‐heat extreme occurrences often coincide, their timing differs in climatologically wet regions. Since 1979, dry‐ and humid‐heat extremes have become more frequent over most land regions, with the greatest increases in the tropics and Arctic. Humid‐heat extremes have increased disproportionately over populated regions (∼5.0 days per‐person per‐decade) relative to global land‐areas (∼3.6 days per‐unit‐land‐area per‐decade) and population exposure to humid‐heat has increased at a faster rate than to dry‐heat. Our study highlights the need for a multivariate approach to understand and mitigate future harm from heat stress in a warming world.

The COVID-19 crisis worsens with the occurrence of climate extremes and disasters

Climate change and the associated weather extreme events are a major threat to humanity as it affects agriculture and food security. Climate change disaster is on the increase as the global temperature keeps rising. Sub-Saharan Africa is one of the most vulnerable regions to climate change. The coronavirus (COVID-19) pandemic has been complicated by climate change and related extreme events especially with the imposed lockdown which has affected the global economy. The COVID-19 has killed over 4 million persons with the USA, Brazil and India being the worst affected nations. Thus, the multi-hazard scenario presented by extreme events like drought, flood and cyclones this period of the pandemic worsened its spread as it affected social distancing and personal hygiene as many people are crammed in camps and water become scarce for handwashing. It is suggested for countries to strengthen their emergency department by boosting the staff component, provide adequate technical support and develop detailed plans for multi-hazard preparedness.

Factors Responsible for the Increase of Winter Low Temperature Extremes from the Mid-1990s to the Early 2010s in Northern China

AbstractIt is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s, northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over mid- and high-latitude Eurasia acts as an important thermal background. It is characterized by two dominant modes, the “consistent cooling” pattern and the “warm high-latitude Eurasia and cold midlatitude Eurasia” pattern, from the mid-1990s to the early 2010s. The two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of the Arctic Oscillation (AO), Ural blocking (UB), and Siberian high (SH) are all highly correlated with the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO directly affects the occurrence of LTE because of its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of UB and SH. Further analyses show that the winter temperature in mid- and high-latitude Eurasia and the AO are independent factors that influence the increase of LTE in northern China from the mid-1990s to the early 2010s.