Projecting Changes in Temperature Extremes in the Han River Basin of China Using Downscaled CMIP5 Multi-Model Ensembles

Estimating the changes in the spatial–temporal characteristics of extreme temperature events under future climate scenarios is critical to provide reference information to help mitigate climate change. In this study, we analyzed 16 extreme temperature indices calculated based on downscaled data from 28 Global Climate Models (GCMs) that were obtained from Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios in the Han River Basin (HRB). The results indicate that the downscaled data from 28 GCMs reproduced a consistent sign of recent trends for all extreme temperature indices except the DTR for the historical period (1961–2013). We found significantly increasing trends for the warm extreme indices (i.e., TXx, TNx, TX90p, TN90p, SU, TR, and WSDI) and considerably decreasing trends for the cold extreme indices (i.e., TX10p, TN10p, CSDI, FD, ID) under both the RCP4.5 and 8.5 scenarios for 2021–2100. Spatially, great changes in warm extremes will occur in the west and southeast of the HRB in the future. The projected changes in extreme temperatures will impact the eco-environment and agricultural production. Our findings will help regional managers adopt countermeasures and strategies to adapt to future climate change, especially extreme weather events.

Analysis of Anomalies and Trends of Climate Change Indices in Zacatecas, Mexico

Sufficient evidence is currently available to demonstrate the reality of the warming of our planet’s climate system. Global warming has different effects on climate at the regional and local levels. The detection of changes in extreme events using instrumental data provides further evidence of such warming and allows for the characterization of its local manifestations. The present study analyzes changes in temperature and precipitation extremes in the Mexican state of Zacatecas using climate change indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). We studied a 40-year period (1976–2015) using annual and seasonal time series. Maximum and minimum temperature data were used, as well as precipitation statistics from the Mexican climatology database (CLICOM) provided by the Mexican Meteorological Service. Weather stations with at least 80% of data availability for the selected study period were selected; these databases were subjected to quality control, homogenization, and data filling using Climatol, which runs in the R programming language. These homogenized series were used to obtain daily grids of the three variables at a resolution of 1.3 km. Results reveal important changes in temperature-related indices, such as the increase in maximum temperature and the decrease in minimum temperature. Irregular variability was observed in the case of precipitation, which could be associated with low-frequency oscillations such as the Pacific Decadal Oscillation and the El Niño–Southern Oscillation. The possible impact of these changes in temperature and the increased irregularity of precipitation could have a negative impact on the agricultural sector, especially given that the state of Zacatecas is the largest national bean producer. The most important problems in the short term will be related to the difficulty of adapting to these rapid changes and the new climate scenario, which will pose new challenges in the future.

Prediction of Autumn Precipitation over the Middle and Lower Reaches of the Yangtze River Basin Based on Climate Indices

Autumn precipitation (AP) has important impacts on agricultural production, water conservation, and water transportation in the middle and lower reaches of the Yangtze River Basin (MLYRB; 25°–35° N and 105°–122° E). We obtain the main empirical orthogonal function (EOF) modes of the interannual variation in AP based on daily precipitation data from 97 stations throughout the MLYRB during 1980–2015. The results show that the first leading EOF mode accounts for 30.83% of the total variation. The spatial pattern shows uniform change over the whole region. The variance contribution of the second mode is 16.13%, and its spatial distribution function shows a north-south phase inversion. Based on previous research and the physical considerations discussed herein, we include 13 climate indices to reveal the major predictors. To obtain an acceptable prediction performance, we comprehensively rank the climate indices, which are sorted according to the values of the new standardized algorithm of information flow (NIF, a causality-based approach) and correlation coefficient (a traditional climate diagnostic tool). Finally, Tropical Indian Ocean Dipole (TIOD), Arctic Oscillation (AO), and other four indicators are chosen as the final predictors affecting the first mode of AP over the MLYRB; NINO3.4 SSTA (NINO3.4), Atlantic-European Circulation E Pattern (AECE), and other four indicators are the major predictors for the second mode. In the final prediction experiment, considering the time series prediction of principal components (PCs) to be a small-sample problem, the Bayesian linear regression (BLR) model is used for the prediction. The experimental results reveal that the BLR model can effectively capture the time series trends of the first two modes (the correlation coefficients are greater than 0.5), and the overall performance is significantly better than that of the multiple linear regression (MLR) model. The prediction factors and precipitation prediction results identified in this study can be referenced to rapidly obtain climatological information for AP over the MLYRB and improve the regional prediction of AP elsewhere, which will also help policymakers prepare appropriate adaptation and mitigation measures for future climate change.

Context-dependent effects of relative temperature extremes on bill morphology in a songbird

Species increasingly face environmental extremes. Morphological responses to changes in average environmental conditions are well documented, but responses to environmental extremes remain poorly understood. We used museum specimens to investigate relationships between a thermoregulatory morphological trait, bird bill surface area (SA) and a measure of short-term relative temperature extremity (RTE), which quantifies the degree that temperature maxima or minima diverge from the 5-year norm. Using a widespread, generalist species, Junco hyemalis, we found that SA exhibited different patterns of association with RTE depending on the overall temperature regime and on precipitation. While thermoregulatory function predicts larger SA at higher RTE, we found this only when the RTE existed in an environmental context that opposed it: atypically cold minimum temperature in a warm climate, or atypically warm maximum temperature in a cool climate. When environmental context amplified the RTE, we found a negative relationship between SA and RTE. We also found that the strength of associations between SA and RTE increased with precipitation. Our results suggest that trait responses to environmental variation may qualitatively differ depending on the overall environmental context, and that environmental change that extremifies already-extreme environments may produce responses that cannot be predicted from observations in less-extreme contexts.

Tendency of Runoff and Sediment Variety and Multiple Time Scale Wavelet Analysis in Hongze Lake during 1975–2015

Hongze Lake plays a key role in flood and waterlogging prevention, analyzing the variation process and characteristics of multi-time scales will have a great practical significance to water resources management and regulation in the Huaihe River basin of China. This research proposed a combinatorial mutation test method to study the interannual variation trends and change points of runoff and sediment flowing into and out of Hongze Lake during the period 1975–2015. It is concluded that the annual variation trend of the inflow and outflow runoff time series is consistent, with no obvious decreasing trend and change point, while the inflow and outflow sediment time series showed a decreasing trend, and the change point was 1991. Then, the runoff and sediment time series were analyzed by the wavelet method. The results showed that the time series has multi-time scale characteristics. The annual inflow runoff and sediment would enter into the dry period in a short time after 2015, and both would be in the valley floor stage. Among the influencing factors, the variation of rainfall in the basin was the main factor affecting the runoff variation. Changes in heavy rainfalls pattern, the construction of hydraulic engineering projects, and land use/cover change (LUCC) are the main reasons for the significant decrease and mutation variation of inflow sediment.

Assessing Redundancy in Stormwater Structures Under Hydraulic Design

As environmental change is happening at an unprecedented pace, a reliable and proper urban drainage design is required to alleviate the negative effects of unexpected extreme rainfall events occurring due to the natural and anthropogenic variations such as climate change and urbanization. Since structure/configuration of a stormwater network plays an imperative role in the design and hydraulic behavior of the system, the goal of this paper is to elaborate upon the significance of possessing redundancy (e.g., alternative flow paths as in loops) under simultaneous hydraulic design in stormwater pipe networks. In this work, an innovative approach based on complex network properties is introduced to systematically and successively reduce the number of loops and, therefore, the level of redundancy, from a given grid-like (street) network. A methodology based on hydrodynamic modelling is utilized to find the optimal design costs for all created structures while satisfying a number of hydraulic design constraints. As a general implication, when structures are subject to extreme precipitation events, the overall capability of looped configurations for discharging runoff more efficiently is higher compared to more branched ones. The reason is due to prevailing (additional) storage volume in the system and existing more alternative water flow paths in looped structures, as opposed to the branched ones in which only unique pathways for discharging peak runoff exist. However, the question arises where to best introduce extra paths in the network? By systematically addressing this question with complex network analysis, the influence of downstream loops was identified to be more significant than that of upstream loops. Findings, additionally, indicated that possessing loop and introducing extra capacity without determining appropriate additional pipes positions in the system (flow direction) can even exacerbate the efficiency of water discharge. Considering a reasonable and cost-effective budget, it would, therefore, be worthwhile to install loop-tree-integrated stormwater collection systems with additional pipes at specific locations, especially downstream, to boost the hydraulic reliability and minimize the damage imposed by the surface flooding upon the metropolitan area.

Homogeneity in Patterns of Climate Extremes Between Two Cities—A Potential for Flood Planning in Relation to Climate Change

Information about potential scenarios and causes of floods is important for future planning. Historical weather data of Fredericton (New Brunswick) and Charlottetown (Prince Edward Island), the two coastal cities of Atlantic Canada, were analyzed using RClimDex, Mann–Kendall test, and Sen’s slope estimates for potential scenarios and causes of floods. Flood hazard analyses were conducted using GIS (Geographical Information System) and ArcSWAT software. The watersheds of Fredericton and Charlottetown were delineated from 25 × 25 m resolution DEMs (Digital Elevation Models) of the two cities followed by percent watershed area calculations for different elevation classes for flood generation. Over the past 100 years, there was a significant decreasing trend in the high intensity precipitation in Charlottetown supported by a significant decrease in the number of heavy precipitation days. However, maximum one-day precipitation and maximum five-day precipitation significantly increased in Charlottetown and Fredericton, respectively. Charlottetown received more annual precipitation than Fredericton. In the last 30 years, there was an event exceeding 50 mm precipitation (considered as a threshold for the return period of urban floods) in Charlottetown; Fredericton experienced such events for more than 1.5 times. For twelve times, these events occurred more than once in a year in Charlottetown as compared to fourteen times in Fredericton. Despite statistically proven similarities in the occurrence of extreme events in the two cities, the visualized flood hazards, and the mapping of watershed characteristics, no devastating floods were reported for Charlottetown. This does not necessarily mean that there had never been risks of flooding in Charlottetown. These findings may help policymakers for future developments.

Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.

Simulating and Predicting Crop Yield and Soil Fertility under Climate Change with Fertilizer Management in Northeast China Based on the Decision Support System for Agrotechnology Transfer Model

The risks of climate change and soil degradation for the agricultural environment and crop production are increasingly prominent. Based on the limitations of land resources, it is important to explore a sustainable and effective fertilization strategy to reduce risks and ensure there is a high yield of grain and sustainable development of agriculture. Soil fertility underpins cultivated land, which is the most important resource of agricultural production, and is also the key for maintaining agricultural sustainability. The central elements of soil fertility are soil organic carbon (SOC) and soil nitrogen (SN). This study applied the Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) and the CENTURY-based soil module to simulate the trends of crop yields, SN storages and SOC storages until the end of this century under different climate change circumstances, based on a 36-year long-term experiment established at Shenyang site, China. Four fertilizer practices were applied: control (CK), combined chemical fertilizer of nitrogen, phosphorus, and potassium (NPK), NPK with manure (MNPK), and NPK fertilizers plus a high application rate of manure (hMNPK). The outcomes indicated that the DSSAT model can fully simulate the yields of maize and soybean as well as the dynamic stocks of the SN and SOC. Three Representative Concentration Pathways (RCP 2.6, RCP 4.5, RCP 8.5) for future development were chosen from the fifth assessment report of the United Nations Intergovernmental Panel on Climate Change (IPCC). Moreover, a baseline was installed. Crop yields, SN, and SOC storages from 2016 to 2100 were estimated under four climate scenarios (RCP 2.6, RCP 4.5, RCP 8.5, and Baseline). The RCP scenarios in some treatments reduced SN and SOC stocks and maize yield, and had no effect on soybean yield. However, the application of NPK with manure could improve crop yields, while it increased SN and SOC storages substantially. To some extent, the negative effects of climate scenarios could be mitigated by applying manure. In the RCP 4.5, maize yields of NPK, MNPK, and hMNPK treatments declined by 14.8%, 7.7%, and 6.2%, respectively, compared with that of NPK under Baseline. The NPK fertilizers plus manure treatments could cut the reduction of maize yield caused by climate change in half. Additionally, the SOC storage and SN of chemical fertilizers plus manure treatments under RCP scenarios increased by 20.2%–33.5% and 13.7%–21.7% compared with that of NPK under baseline, respectively. It was concluded that a rational combination of organic and inorganic fertilizer applications is a sustainable and effective agricultural measure to maintain food security and relieve environmental stresses.

CAM plant expansion favored indirectly by asymmetric climate warming and increased rainfall variability

Recent observational evidence suggests that nighttime temperatures are increasing faster than daytime temperatures, while in some regions precipitation events are becoming less frequent and more intense. The combined ecological impacts of these climatic changes on crassulacean acid metabolism (CAM) plants and their interactions with other functional groups (i.e., grass communities) remain poorly understood. Here we developed a growth chamber experiment to investigate how two CAM-grass communities in desert ecosystems of the southwestern United States and northern Mexico respond to asymmetric warming and increasing rainfall variability. Grasses generally showed competitive advantages over CAM plants with increasing rainfall variability under ambient temperature conditions. In contrast, asymmetric warming caused mortality of both grass species (Bouteloua eriopoda and Bouteloua curtipendula) in both rainfall treatments due to enhanced drought stress. Grass mortality indirectly favored CAM plants even though the biomass of both CAM species Cylindropuntia imbricata and Opuntia phaeacantha significantly decreased. The stem's volume-to-surface ratio of C. imbricata was significantly higher in mixture than in monoculture under ambient temperature (both P < 0.0014); however, the difference became insignificant under asymmetric warming (both P > 0.1625), suggesting that warming weakens the negative effects of interspecific competition on CAM plant growth. Our findings suggest that while the increase in intra-annual rainfall variability enhances grass productivity, asymmetric warming may lead to grass mortality, thereby indirectly favoring the expansion of co-existing CAM plants. This study provides novel experimental evidence showing how the ongoing changes in global warming and rainfall variability affect CAM-grass growth and interactions in dryland ecosystems.

Transgenerational effects of parental light environment on progeny competitive performance and lifetime fitness

Plant and animal parents may respond to environmental conditions such as resource stress by altering traits of their offspring via heritable non-genetic effects. While such transgenerational plasticity can result in progeny phenotypes that are functionally pre-adapted to the inducing environment, it is unclear whether such parental effects measurably enhance the adult competitive success and lifetime reproductive output of progeny, and whether they may also adversely affect fitness if offspring encounter contrasting conditions. In glasshouse experiments with inbred genotypes of the annual plant Polygonum persicaria, we tested the effects of parental shade versus sun on (a) competitive performance of progeny in shade, and (b) lifetime reproductive fitness of progeny in three contrasting treatments. Shaded parents produced offspring with increased fitness in shade despite competition, as well as greater competitive impact on plant neighbours. Inherited effects of parental light conditions also significantly altered lifetime fitness: parental shade increased reproductive output for progeny in neighbour and understorey shade, but decreased fitness for progeny in sunny, dry conditions. Along with these substantial adaptive and maladaptive transgenerational effects, results show complex interactions between genotypes, parent environment and progeny conditions that underscore the role of environmental variability and change in shaping future adaptive potential. This article is part of the theme issue 'The role of plasticity in phenotypic adaptation to rapid environmental change'.

Assessing Changes in Characteristics of Hot Extremes Over India in a Warming Environment and their Driving Mechanisms

Change in hot extremes is one of the accepted evidence and also a global indicator of an anthropogenic climate change, which has serious environmental and economic impacts. In the present study, the India Meteorological Department gridded temperature data is used to characterize hot extremes over India in terms of frequency and intensity. Results provide compelling evidence that large parts of India, except the Indo-Gangetic plains, have experienced more occurrences of hot days (upsurge by 24.7%) having higher temperatures in the recent period (1976–2018), compared to the past (1951–1975), which suggests a shift in climate. Strong positive geopotential height anomalies at 500 hPa over the northern parts of India, which dynamically produces subsidence and clear sky conditions along with reduced precipitable water and depleted soil moisture are identified to be the crucial factors responsible for an increase of hot extremes in recent decades. Furthermore, the preceding December-February Niño-3.4 sea surface temperature (SST) anomalies are strongly connected with hot days frequency and the mechanism for the lag of several months is related to 3–4 months delayed response of Indian Ocean SSTs to El Niño/Southern Oscillation. Thus, post-Niño hot extremes over India can be potentially anticipated in advance and this will help society to prepare for such extremes.

Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

Extreme weather events can cause a lot of damage in highly populated regions, such as in the Beijing–Tianjin–Hebei Region (BTHR) in northern China. To understand where and how extreme precipitation and temperature events are changing within the BTHR, data for 1959–2018 from 25 mereological stations were used to detect trends in the intensity, frequency, and duration of these events. The results showed that intensity, accumulated amount, the duration of extreme precipitation events, and the annual number of days with precipitation greater than 50 mm decreased on a regional scale over this 60-year period. Changes in extreme precipitation events at most stations were not statistically significant, although a few stations had a significant downward trend. The combined effects of the East Asian summer monsoon and rapid urbanization are possible reasons for these trends. Both the annual maximum and minimum temperature increased on a regional and local scale. The frequency of extreme hot and cold weather also, respectively, increased and decreased, with consistent patterns on a regional and local scale. However, the spatial changes of these trends were different, reflecting the effects of irrigation and urbanization on the regional surface energy balance. These findings are valuable to decisionmakers involved in disaster prevention in the BTHR and in other highly populated regions worldwide.

Trends in extreme rainfall and hydrogeometeorological disasters in the Metropolitan Area of São Paulo: a review

Our paper reviews recent progress in the study and understanding of observed trends in extreme rainfall events in the Metropolitan Area of São Paulo (MASP). These are discussed in relation to hydrometeorological hazards that trigger natural disasters, such as flash floods, landslides, and droughts, that affect the population and local economies. A review of the most updated literature on rainfall and extremes in the MASP shows a significant increase in the total volume of rainy-season rainfall during the last seven decades. While there were practically no days with heavy rain (more than 50 mm) in the 1950s, these days have been occurring two to five times a year in the last 10 years. This, together with the inappropriate occupation of risky areas, such as slopes and banks of watercourses, leads to inundation, flooding, and landslides. Changes in extremes can be partly due to natural climate variability but can also be related to global warming and/or urbanization. There is ample evidence of an increasing risk of rainfall-related hazards in the MASP. This is particularly so for landslides in vulnerable areas. Exposure will continue to lead to risk increases. This calls for significant improvement in climate and disaster risk reduction and management efforts in the MASP region.

A Consistent Methodology to Evaluate Temperature and Heat Wave Future Projections for Cities: A Case Study for Lisbon

Heat waves are large-scale atmospheric phenomena that may cause heat stress in ecosystems and socio-economic activities. In cities, morbidity and mortality may increase during a heat wave, overloading health and emergency services. In the face of climate change and associated warming, cities need to adapt and mitigate the effects of heat waves. This study suggests a new method to evaluate heat waves’ impacts on cities by considering some aspects of heat waves that are not usually considered in other similar studies. The method devises heat wave quantities that are easy to calculate; it is relevant to assessing their impacts and permits the development of adaptation measures. This study applies the suggested method to quantify various aspects of heat waves in Lisbon for future climate projections considering future mid-term (2046–2065) and long-term (2081–2100) climates under the RCP8.5 greenhouse emission scenario. This is achieved through the analysis of various regional climate simulations performed with the WRF model and an ensemble of EURO-CORDEX models. This allows an estimation of uncertainty and confidence of the projections. To evaluate the climate change properties of heat waves, statistics for future climates are compared to those for a reference recent climate. Simulated temperatures are first bias corrected to minimize the model systematic errors relative to observations. The temperature for mid and long-term futures is expected to increase relative to the present by 1.6 °C and 3.6 °C, respectively, with late summer months registering the highest increases. The number of heat wave days per year will increase on average from 10, in the present climate, to 38 and 63 in mid and long-term climates, respectively. Heat wave duration, intensity, average maximum temperature, and accumulated temperature during a heat wave will also increase. Heat waves account for an annual average of accumulated temperature of 358 °C·day in the present climate, while in the mid and long-term, future climates account for 1270 °C·day and 2078 °C·day, respectively. The largest increases are expected to occur from July to October. Extreme intensity and long-duration heat waves with an average maximum temperature of more than 40 °C are expected to occur in the future climates.

Extreme Temperature Events during 1960–2017 in the Arid Region of Northwest China: Spatiotemporal Dynamics and Associated Large-Scale Atmospheric Circulation

Studying the dynamic changes of extreme temperatures and associated large-scale atmospheric circulation is important for predicting the occurrence of extreme temperatures and reducing their adverse impact and damage. Based on the surface temperature data sets collected from 87 weather stations over the arid region of Northwest China (ARNC) during 1960–2017, the Sen’s slope estimator, Mann–Kendall test, Cumulative anomaly, Moving t-test, and Synthetic analysis methods were used to analyze the spatiotemporal dynamics and breaking-point change characteristics of extreme temperatures, and to discuss its associated large-scale atmospheric circulation. The results revealed that at the temporal scale, summer days (SU25), warm days (TX90p), warm nights (TN90p), and warm spell duration indicator (WSDI) showed a remarkable increasing trend at the rates of 2.27, 1.49, 3, and 2.28 days/decade, respectively. The frost days (FD), cold days (TX10p), cold nights (TN10p), and cold spell duration indicator (CSDI) significantly decreased at the rates of −3.71, −0.86, −1.77, and −0.76 days/decade, respectively, during the study period. Spatially, the warming trend in the study area is very obvious as a whole, despite pronounced spatial differences in warming rate. After the breakpoint years, the frequency and probability distribution for extreme warm and cold indices were all inclined to the hotter part of the density distribution. This indicates that the climate over the study region shifted sharply and tended to be warmer. The analysis of large-scale atmospheric circulation indicates that the warming trend in the arid region of Northwest China (ARNC) is positively correlated with geopotential height at 500 hPa and negatively correlated with total cloudiness. The findings from this study have important implications for forecasting extreme temperature events and mitigating the impacts of climatological disasters in this region.

Statistical Modelling of Temperature-Attributable Deaths in Portuguese Metropolitan Areas under Climate Change: Who Is at Risk?

Several studies emphasize that temperature-related mortality can be expected to have differential effects on different subpopulations, particularly in the context of climate change. This study aims to evaluate and quantify the future temperature-attributable mortality due to circulatory system diseases by age groups (under 65 and 65+ years), in Lisbon metropolitan area (LMA) and Porto metropolitan area (PMA), over the 2051–2065 and 2085–2099 time horizons, considering the greenhouse gas emissions scenario RCP8.5, in relation to a historical period (1991–2005). We found a decrease in extreme cold-related deaths of 0.55% and 0.45% in LMA, for 2051–2065 and 2085–2099, respectively. In PMA, there was a decrease in cold-related deaths of 0.31% and 0.49% for 2051–2065 and 2085–2099, respectively, compared to 1991–2005. In LMA, the burden of extreme heat-related mortality in age group 65+ years is slightly higher than in age group <65 years, at 2.22% vs. 1.38%, for 2085–2099. In PMA, only people aged 65+ years showed significant temperature-related burden of deaths that can be attributable to hot temperatures. The heat-related excess deaths increased from 0.23% for 2051–2065 to 1.37% for 2085–2099, compared to the historical period.

A Study of Precipitation Patterns through Stochastic Ordering

The study of spatial and temporal changes in precipitation patterns is important to agriculture and natural ecosystems. These changes can be described by some climate change indices. Because these indices often have skewed probability distributions, some common statistical procedures become either inappropriate or less powerful when they are applied to the indices. A nonparametric approach based on stochastic ordering is proposed, which does not make any assumption on the shape of the distribution. This approach is applied to the average length of the period between two adjacent precipitation days, which is called the average number of consecutive dry days (ACDD). This approach is shown to be able to reveal some patterns in precipitation that other approaches do not. Using daily precipitations at 756 stations in China from 1960 to 2015, this work compares the ACDDs in three periods, 1960–1965, 1985–1990, and 2010–2015 for each province in China. The results show that ACDD increases stochastically from the period 1960–1965 to either the period 1985–1990 or the period 2010–2015, or from the period 1985–1990 to the period 2010–2015 in all but three provinces in China.

Streamflow Intensification Driven by the Atlantic Multidecadal Oscillation (AMO) in the Atrato River Basin, Northwestern Colombia

The impact of the Atlantic Multidecadal Oscillation (AMO) on the variations in the streamflow in the Atrato River Basin (ARB) during the 1965–2016 period was analyzed here by considering the cold (1965–1994) and warm (1995–2015) phases of this oscillation. The mean streamflow increased after 1994 (AMO phase change). This increase is related to the strengthening of the zonal gradients of the sea surface temperature (SST) and sea level pressure (SLP) between the tropical central Pacific and the tropical Atlantic after 1994 (warm AMO phase). These gradients contributed to strengthen the Walker cell related upward movement over northern and northwestern South America, in particular during November-December (ND). Consistently, the frequency (R20 mm) and intensity (SDII) of extreme daily rainfall events increased during the 1995–2015 period. Our results show a connection between the AMO and the increase in the streamflow in the ARB during the last five decades. These results contribute to the studies of resilience and climate adaptation in the region.

Demonstration of an online web services tool incorporating automatic retrieval and comparison of precipitation data

Input data acquisition and preprocessing is time-consuming and difficult to handle and can have major implications on environmental modeling results. US EPA's Hydrological Micro Services Precipitation Comparison and Analysis Tool (HMS-PCAT) provides a publicly available tool to accomplish this critical task. We present HMS-PCAT's software design and its use in gathering, preprocessing, and evaluating precipitation data through web services. This tool simplifies catchment and point-based data retrieval by automating temporal and spatial aggregations. In a demonstration of the tool, four gridded precipitation datasets (NLDAS, GLDAS, DAYMET, PRISM) and one set of gauge data (NCEI) were retrieved for 17 regions in the United States and evaluated on 1) how well each dataset captured extreme events and 2) how datasets varied by region. HMS-PCAT facilitates data visualizations, comparisons, and statistics by showing the variability between datasets and allows users to explore the data when selecting precipitation datasets for an environmental modeling application.

Developing PIDF Curves From Dynamically Downscaled WRF Model Fields to Examine Extreme Precipitation Events in Three Eastern U.S. Metropolitan Areas

Extreme precipitation events influence watershed, agriculture, and urban management. The probability of extreme precipitation is estimated for storm water management using precipitation intensity-duration-frequency (PIDF) curves. This study explores developing PIDF curves from dynamically downscaled 36- and 12-km simulations using the Weather Research and Forecasting (WRF) model. Three modeled data sets are examined: 36-km WRF model forced with 2.5° (~275-km) NCEP-DOE AMIP-II Reanalysis (R2); 36-km WRF model forced with 0.75° (~80-km) ERA-Interim; and 12-km WRF model forced with ERA-Interim. The WRF outputs are verified against historical observations for three cities in the Eastern United States using a 23-year period (1988-2010). The 36-km WRF data set driven by R2 produced PIDF curves that were acceptable at the 12- to 24-hr durations, but those WRF data could not realistically simulate extremes represented by the high-intensity, short-duration precipitation events. Increasing the resolution of WRF's driving data from R2 to ERA-Interim did not improve WRF's representation of precipitation events. Using 12-km grid spacing enhances WRF's ability to reproduce PIDF curves developed from observations. Finer grid spacing dramatically improves the frequency and intensity of the 1- to 3-hr events and improves the 6- to 24-hr events. However, improvements with the 12-km WRF data did not apply equally to all study sites, suggesting further modifications to the WRF configuration and/or methodology are necessary. Although imperfect, the results here lend confidence to using modeled data to construct PIDF curves, which could be valuable for projecting changes to parameters used in urban and environmental planning.

Comprehensive climate factor characteristics and quantitative analysis of their impacts on grain yields in China's grain-producing areas

Climate change elements are important indicators for assessing the impact of climate change on the agricultural economy. A Comprehensive Climate Factor (CCF) that is composed of three indicators, growing season mean temperature, precipitation and sunshine hours indicators was developed. These indicators are aggregated into a single index that is a measure of the sensitivity of regionally integrated climate change. This paper uses this factor to explore the integrated climate variations over China's grain-producing areas in 1981–2015, divide the areas into climate change-sensitive zones, and quantitatively assess the impact intensity of CCF variation on grain yield. The results indicate that the growing season mean CCF basically increased in most grain-producing areas. The climatic tendency of the North plate is greater than that of the South plate, reaching 0.52 decade⁻¹, and the South plate has a quasi-4a periodic variation. The patterns of the impact of climate change on grain yield show that the impact intensity of climate change gradually decreased in each decade (from 0.25 to 0.2) and was stronger in the southwest than in the northeast. This research can be applied to improve the accuracy of economic-climate model simulations and predictions and to provide a theoretical reference and scientific support for assessing the impact and risk of climate change.

Change-Point Analysis of Precipitation and Drought Extremes in China over the Past 50 Years

Increases in climate extremes and their impacts have attracted global attention recently. In this study, the change-point years of precipitation extremes (PEs) and drought extremes (DEs) were investigated by Moving t-Test at 500 stations across the six regions in China. The detailed temporal change processes of them were demonstrated by the cumulative deviation method based on the data from nine typical stations. The results showed that: 1) DEs were more significantly and widely increased than PEs, the stations with increasing trends of PEs and DEs accounted for greater than 52.6% and 61.6% of the total, respectively; 2) increasing trends of DEs were mainly distributed in the east of Hu Huanyong Line. In this area, the increasing change-point years of DEs often occurred in the early 1980s in the south of the Yangzi River, while occurred in the 1990s in the north of the Yangzi River; 3) increasing trends of PEs were mainly distributed in Qing-Tibet Platen, Northwest China, and the southeastern area of Hu Huanyong Line. In these areas, the increasing change-point years of PEs often occurred around 1990 in the southeast of Hu Huanyong Line, while often occurred in the early 1980s in Qing-Tibet Platen. The results indicated that the area in the southeast of Hu Huanyong Line was under the threats of both PEs and DEs, this may produce severe impacts on agriculture, environment, water resources management, human society, etc.

Observed Changes in Temperature and Precipitation Extremes Over the Yarlung Tsangpo River Basin during 1970–2017

Twenty-five climate indices based on daily maximum and minimum temperature and precipitation at 15 meteorological stations were examined to investigate changes in temperature and precipitation extremes over the Yarlung Tsangpo River Basin (1970–2017). The trend-free prewhitening (TFPW) Mann–Kendall test and Pettitt’s test were used to identify trends and abrupt changes in the time series, respectively. The results showed widespread significant changes in extreme temperature indices associated with warming, most of which experienced abrupt changes in the 1990s. Increases in daily minimum and maximum temperature were detected, and the magnitude of daily minimum temperature change was greater than that of the daily maximum temperature, revealing an obvious decrease in the diurnal temperature range. Warm days and nights became more frequent, whereas fewer cold days and nights occurred. The frequency of frost and icing days decreased, while summer days and growing season length increased. Moreover, cold spell length shortened, whereas warm spell length increased. Additionally, changes in the precipitation extreme indices exhibited much less spatial coherence than the temperature indices. Spatially, mixed patterns of stations with positive and negative trends were found, and few trends in the precipitation extreme indices at individual stations were statistically significant. Generally, precipitation extreme indices showed a tendency toward wetter conditions, and the contribution of extreme precipitation to total precipitation has increased. However, no significant regional trends and abrupt changes were detected in total precipitation or in the frequency and duration of precipitation extremes.

Population dynamics modify urban residents' exposure to extreme temperatures across the United States

Exposure to extreme temperatures is one primary cause of weather-related human mortality and morbidity. Global climate change raises the concern of public health under future extreme events, yet spatiotemporal population dynamics have been long overlooked in health risk assessments. Here, we show that the diurnal intra-urban movement alters residents' exposure to extreme temperatures during cold and heat waves. To do so, we incorporate weather simulations with commute-adjusted population profiles over 16 major U.S. metropolitan areas. Urban residents' exposure to heat waves is intensified by 1.9° ± 0.7°C (mean ± SD among cities), and their exposure to cold waves is attenuated by 0.6° ± 0.8°C. The higher than expected exposure to heat waves significantly correlates with the spatial temperature variability and requires serious attention. The essential role of population dynamics should be emphasized in temperature-related climate adaptation strategies for effective and successful interventions.

Testing three climate datasets for dendroclimatological studies of oaks in the South Carpathians

Three gridded datasets containing interpolated daily and monthly precipitation and temperature values over the past five decades were tested against four tree-ring chronologies of oak (Quercus robur and Q. petraea). The objective of this research was to investigate the climate-growth relationship and whether the Pearson's product-moment correlation coefficients differ significantly if mean monthly precipitation and temperature data from the different climate databases, CRU, E-OBS and ROCADA are used. To this end, we selected two representative oak ecosystems in the South Carpathians, Romania, and analysed earlywood, latewood and tree-ring widths. Climate time series trends for the South Carpathians coldest, warmest days and wettest days were assessed with datasets from E-OBS and ROCADA, which differed in the density of their meteorological station network and their interpolation methods. The observed climatic parameters showed changes towards wetter conditions after the mid-1980s. For 1961-2013, E-OBS underestimated the mean daily temperature and daily precipitation compared with ROCADA. The results showed that higher extreme temperatures from January-March affected earlywood growth. In the investigated study region, latewood formation seemed to be affected by water availability mainly in May. Periods of drought associated with higher temperatures have limiting effects on tree growth, but these events are captured in different ways by each climate database analysed. Similarly, the results showed the discrepancy among datasets for earlywood and climate relationships. The results emphasize the importance of proper selection of climate data for assessing climate-tree growth relationships. For future dendroclimatological and dendroecological studies of oak in Romania, we recommend the ROCADA database, while E-OBS is recommended if an up-to-date climate dataset is needed.

Changes in the Risk of Extreme Climate Events over East Asia at Different Global Warming Levels

Limiting the global temperature increase to a level that would prevent “dangerous anthropogenic interference with the climate system” is the focus of intergovernmental climate negotiations, and the cost-benefit analysis to determine this level requires an understanding of how the risk associated with climate extremes varies with different warming levels. We examine daily extreme temperature and precipitation variances with continuous global warming using a non-stationary extreme value statistical model based on the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results show the probability of extreme warm and heavy precipitation events over East Asia (EA) will increase, while that of cold extremes over EA will decrease as global warming increases. A present-day 1-in-20-year heavy precipitation extreme in EA is projected to increase to 1.3, 1.6, 2.5, and 3.4 times more frequently of the current climatology, at the global mean warming levels of 1.5 °C, 2 °C, 3 °C, and 4 °C above the preindustrial era, respectively. Moreover, the relative changes in probability are larger for rarer events. These results contribute to an improved understanding of the future risk associated with climate extremes, which helps scientists create mitigation measures for global warming and facilitates policy-making.

Assessment of Precipitation Estimation from the NWP Models and Satellite Products for the Spring 2019 Severe Floods in Iran

Precipitation monitoring and early warning systems are required to reduce negative flood impacts. In this study, the performance of ensemble precipitation forecasts of three numerical weather prediction (NWP) models within the THORPEX interactive grand global ensemble (TIGGE) as well as the integrated multi-satellite retrievals for global precipitation measurement (GPM), namely IMERG, for precipitation estimates were evaluated in recent severe floods in Iran over the March–April 2019 period. The evaluations were conducted in three aspects: spatial distribution of precipitation, mean areal precipitation in three major basins hard hit by the floods, and the dichotomous evaluation in four precipitation thresholds (25, 50, 75, and 100 mm per day). The results showed that the United Kingdom Met Office (UKMO) model, in terms of spatial coverage and satellite estimates as well as the precipitation amount, were closer to the observations. Moreover, with regard to mean precipitation at the basin scale, UKMO and European Center for Medium-Range Weather Forecasts (ECMWF) models in the Gorganrud Basin, ECMWF in the Karkheh Basin and UKMO in the Karun Basin performed better than others in flood forecasting. The National Centers for Environmental Forecast (NCEP) model performed well at low precipitation thresholds, while at high thresholds, its performance decreased significantly. On the contrary, the accuracy of IMERG improved when the precipitation threshold increased. The UKMO had better forecasts than the other models at the 100 mm/day precipitation threshold, whereas the ECMWF had acceptable forecasts in all thresholds and was able to forecast precipitation events with a lower false alarm ratio and better detection when compared to other models.

Bioclimatology, Structure, and Conservation Perspectives of Quercus pyrenaica, Acer opalus subsp. Granatensis, and Corylus avellana Deciduous Forests on Mediterranean Bioclimate in the South-Central Part of the Iberian Peninsula

The plant variability in the southern Iberian Peninsula consists of around 3500 different taxa due to its high bioclimatic, geographic, and geological diversity. The deciduous forests in the southern Iberian Peninsula are located in regions with topographies and specific bioclimatic conditions that allow for the survival of taxa that are typical of cooler and wetter bioclimatic regions and therefore represent the relict evidence of colder and more humid paleoclimatic conditions. The floristic composition of 421 samples of deciduous forests in the south-central part of the Iberian Peninsula were analyzed. The ecological importance index (IVI) was calculated, where the most important tree species were Quercus pyrenaica, Acer opalus subsp. Granatensis, and Corylus avellana. These species are uncommon in the south-central part of the Iberian Peninsula, forming forests of little extension. An analysis of the vertical distribution of the species (stratum) shows that the majority of the species of stratum 3 (hemicriptophics, camephytes, geophites, and nanophanerophytes) are characteristic of deciduous forests, and their presence is positively correlated with high values of bioclimatic variables related to humidity and presence of water in the soil (nemoral environments), while they are negatively correlated with high values ​​of bioclimatic variables related to high temperatures, evapotranspiration, and aridity. This work demonstrates that several characteristic deciduous forest taxa are more vulnerable to disappearance due to the loss of their nemoral conditions caused by gaps in the tree or shrub canopy. These gaps lead to an increase in evapotranspiration, excess insolation, and a consequent loss of water and humidity in the microclimatic conditions.

On the need to integrate uncertainty into U.S. water resource planning

A changing climate is expected to introduce uncertainty into water resource management decision making. We examined the latest publicly-available, state-level guidance regarding the management of water supplies and demands concerning risks associated with drought, flooding, and climate change. We found state-level guidance supplementing the federally-backed flood mitigation program to be updated most regularly (54% in the last 5 years; 84% in the last decade). Yet, the underlying floodplain mapping data these local planning efforts rely on are acknowledged by the Federal Emergency Management Agency (FEMA) to be chronically outdated. Drought planning guidance was found to be most outdated (16% last updated in the last 5 years; 18% almost two decades ago), and across the U.S., almost universally (94%) reactive (emergency response) rather than proactive (mitigation or management). Although 79-94% of states provide some level of guidance regarding water supply and demand, the projections themselves may significantly predate the guidance. Many (70%) U.S. states still lack climate change impact guidance, particularly non-coastal states and those impacted by increased water scarcity rather than flooding. Strategies are rare (4%) for addressing the impacts of increased variability and uncertainty to meet inelastic demands with finite supplies. We conclude significant gaps exist in planning to address known or projected risks of climate-related impacts. Specific recommendations, including the implementation of a nationwide water census, are provided to improve both the data and knowledge base of water management and reduce current vulnerabilities.

The impact of extremely hot weather events on all-cause mortality in a highly urbanized and densely populated subtropical city: A 10-year time-series study (2006-2015)

BACKGROUND

The impact of heatwaves on public health has led to an urgent need to describe extremely hot weather events (EHWEs) and evaluate their health impacts.

METHODS

In Hong Kong, a very hot day (VHD) can be defined when the daily maximum temperature ≥ 33 °C, and a hot night (HN) can be identified if the daily minimum temperature ≥ 28 °C. Three lengths of time, nine combinations of VHD and HN, and four categories of occurrence intervals between two EHWEs were considered over 2006-2015. The daily relative risk (RR) of all-cause mortality was estimated using Poisson generalized additive regression models, controlling for both short-term and long-term trends in temperature as well as four air pollutants. Lagged effects of the representative EHWEs were further examined for their association with mortality. Subgroup analysis was conducted for different sex and age groups.

RESULTS

Significant associations with raised mortality risks were observed for a single HN, while stronger associations with mortality were observed as significant for five or more consecutive VHDs/HNs. More HNs between the consecutive VHDs also significantly amplified the impact on mortality, with the strongest association observed for EHWEs characterized as 2D3N, and the effect significantly lagged for five days. Therefore, with identifiable health impacts, three thresholds (5VHDs, 5HNs, & 2D3N) were determined to be representative of identical types of EHWEs in Hong Kong. Furthermore, by taking 2 (3) consecutive VHDs (HNs) as one daytime (nighttime) EHWE event, those occurring consecutively without non-hot days (nights) in between were found to be significantly associated with excess mortality risks. Moreover, females and older adults were determined to be relatively more vulnerable to all defined EHWEs.

CONCLUSIONS

Among all the observed significant heat-mortality associations in highly urbanized cities, EHWEs that occurred during the nighttime, with extended length, consecutively without any break in between, or in the pattern of 2D3N might require the meteorological administration, healthcare providers, and urban planners to work interactively.

Evaluation and Projection of Extreme Precipitation over Northern China in CMIP5 Models

This study evaluates 32 climate models from CMIP5 compared with a daily gridded observation dataset of extreme precipitation indices including total extreme precipitation (R95p), maximum consecutive five days of precipitation (RX5day) and wet days larger than 10 mm of precipitation (R10mm) over Northern China during the historical period (1986–2005). Results show the majority models have good performance on spatial distribution but overestimate the amplitude of precipitation over Northern China. Most models can also capture interannual variation of R95p and RX5d, but with poor simulations on R10mm. Considering both spatial and temporal factors, the best multi-model ensemble (Group 1) has been selected and improved by 42%, 34%, and 37% for R95p, RX5d, and R10mm, respectively. Projection of extreme precipitation indicates that the fastest-rising region is in Northwest China due to the enhanced rainfall intensity. However, the uncertainty analysis shows the increase of extreme rainfall over Northwest China has a low confidence level. The projection of increasing extreme rainfall over Northeast China from Group 1 due to the longer extreme rainfall days is more credible. The weak subtropical high and southwest winds from Arabian Sea lead to the low wet biases from Group 1 and the cyclonic anomalies over Northeast China, which result in more extreme precipitation.

Magnitude and Frequency of Temperature and Precipitation Extremes and the Associated Atmospheric Circulation Patterns in the Yellow River Basin (1960–2017), China

Since there are many destructive effects caused by extreme climate events in the Yellow River, it is of great theoretical and practical significance to explore the variations of climatic extremes in this key basin. We used a meteorological dataset from 66 stations within the Yellow River basin (YRB) for the period 1960–2017 to calculate magnitude and frequency of precipitation/temperature extremes. We also analyzed the relationships between the main large-scale atmospheric circulation patterns (ACPs) and precipitation/temperature extremes. The trends in precipitation extremes were nonsignificant, only a few stations were characterized by significantly increasing or decreasing anomalies; this indicates the precipitation intensity may have been strengthened, and the extreme rainfall duration appears to have been reduced during 1960–2017. The trends of magnitudes for “cold” extremes were larger than those for “warm” extremes, changes of trends in frost days were higher than those for summer days, and the trends in increasing warm nights were higher than those of warm days. The influence of the El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) on temperature extremes outweighed the influence of the North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) for the other extreme climate indices. The YRB might be at risk of increased extreme high temperature events, and more attention should be paid to this higher risk of extreme climatic events.

Climate Extremes over the Arabian Peninsula Using RegCM4 for Present Conditions Forced by Several CMIP5 Models

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region.

Dataset of global extreme climatic indices due to an acceleration of ice sheet melting during the 21st century

This article describes extreme indices maps (Data Cube, raster X Time) for different scenarios with a more important contribution to the sea level rise from Greenland and/or Antarctica during the 21st century under the Representative Concentration Pathway (RCP) 8.5 emission scenario. The indices are produced annually and globally with a resolution of 0.5° × 0.5° from 1951 to 2099. The data were generated by simulating daily maximum and minimum temperature and precipitation from the IPSL-CM5A-LR model from Coupled Model Intercomparison Project Phase 5 (CMIP5). These climatic data are unbiased and downscaled to the 0.5°x0.5 scale with the Cumulative Distribution Function transform (CDFt) and EWEMBI dataset compiled to support the bias correction of climate input data for ISIMIP. Finally, each extreme indice is computed on the unbiased data on each grid cell on all continents.

Exploring high temperature responses of photosynthesis and respiration to improve heat tolerance in wheat

High temperatures account for major wheat yield losses annually and, as the climate continues to warm, these losses will probably increase. Both photosynthesis and respiration are the main determinants of carbon balance and growth in wheat, and both are sensitive to high temperature. Wheat is able to acclimate photosynthesis and respiration to high temperature, and thus reduce the negative affects on growth. The capacity to adjust these processes to better suit warmer conditions stands as a potential avenue toward reducing heat-induced yield losses in the future. However, much remains to be learnt about such phenomena. Here, we review what is known of high temperature tolerance in wheat, focusing predominantly on the high temperature responses of photosynthesis and respiration. We also identify the many unknowns that surround this area, particularly with respect to the high temperature response of wheat respiration and the consequences of this for growth and yield. It is concluded that further investigation into the response of photosynthesis and respiration to high temperature could present several methods of improving wheat high temperature tolerance. Extending our knowledge in this area could also lead to more immediate benefits, such as the enhancement of current crop models.

Changes of Annual Precipitation and Probability Distributions for Different Climate Types of the World

Analysis of Spatio-temporal changes in precipitation (Pre) on the land surface of the earth was the focus of this study. Thiel-Sen median slopes and Modified Mann-Kendall (MMK) test were utilized to draw inferences. Majority of the regions were identified to show an increasing trend of annual precipitation except some of the low to mid-latitude regions in Northern hemisphere. The trends of wet-day frequency (Wet) were found in agreement with precipitation for most of the regions, but the inverse relationship was found for the subtropical regions of Northern hemisphere. These changes were examined for the world climate types based on Koppen-Gieger climate classes. Also, it was tried to find the probability distribution, which best describes the annual precipitation pattern in different climate types of the world among 21 commonly assumed probability distributions.

Intercomparison of the Surface Energy Partitioning in CMIP5 Simulations

The warming climate significantly modifies the global water cycle. Global evapotranspiration has increased over the past decades, yet climate models agree on the drying trend of land surface. In this study, we conducted an intercomparison analysis of the surface energy partitioning across Coupled Model Intercomparison Phase 5 (CMIP5) simulations and evaluated its behaviour with surface temperature and soil moisture anomalies, against the theoretically derived thermodynamic formula. Different responses over land and sea surfaces to elevated greenhouse gas emissions were found. Under the Representative Concentration Pathway of +8.5 W m−2 (RCP8.5) warming scenario, the multi-model mean relative efficiency anomaly from CMIP5 simulations is 3.83 and −0.12 over global sea and land, respectively. The significant anomaly over sea was captured by the thermodynamic solution based on the principle of maximum entropy production, with a mean relative error of 14.6%. The declining trend over land was also reproduced, but an accurate prediction of its small anomaly will require the inclusions of complex physical processes in future work. Despite increased potential evapotranspiration under rising temperatures, both CMIP5 simulations and thermodynamic principles suggest that the soil moisture-temperature feedback cannot support long-term enhanced evapotranspiration at the global scale. The dissipation of radiative forcing eventually shifts towards sensible heat flux and accelerates the warming over land, especially over South America and Europe.

Impacts of a changing earth on microbial dynamics and human health risks in the continuum between beach water and sand

Although infectious disease risk from recreational exposure to waterborne pathogens has been an active area of research for decades, beach sand is a relatively unexplored habitat for the persistence of pathogens and fecal indicator bacteria (FIB). Beach sand, biofilms, and water all present unique advantages and challenges to pathogen introduction, growth, and persistence. These dynamics are further complicated by continuous exchange between sand and water habitats. Models of FIB and pathogen fate and transport at beaches can help predict the risk of infectious disease from beach use, but knowledge gaps with respect to decay and growth rates of pathogens in beach habitats impede robust modeling. Climatic variability adds further complexity to predictive modeling because extreme weather events, warming water, and sea level change may increase human exposure to waterborne pathogens and alter relationships between FIB and pathogens. In addition, population growth and urbanization will exacerbate contamination events and increase the potential for human exposure. The cumulative effects of anthropogenic changes will alter microbial population dynamics in beach habitats and the assumptions and relationships used in quantitative microbial risk assessment (QMRA) and process-based models. Here, we review our current understanding of microbial populations and transport dynamics across the sand-water continuum at beaches, how these dynamics can be modeled, and how global change factors (e.g., climate and land use) should be integrated into more accurate beachscape-based models.

Spatio-Temporal Variations in Precipitation Extremes in the Endorheic Hongjian Lake Basin in the Ordos Plateau, China

Precipitation extremes have important implications for regional water resources and ecological environment in endorheic (landlocked) basins. The Hongjian Lake Basin (HJLB), as the representative inflow area in the Ordos Plateau in China, is suffering from water scarcity and an ecosystem crisis; however, previous studies have paid little attention to changes in precipitation extremes in the HJLB. In this study, we investigated the spatio-temporal variations of the core extreme precipitation indices (i.e., PRCTOT, R99p, Rx1day, Rx5day, SDII, R1, R10, CWD, and CDD) recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), and analyzed the climatic dry–wet regime indicated by these extreme indices during 1960–2014 in the HJLB. The results show that the nine extreme indices had large differences in temporal and spatial variation characteristics. All the nine extreme precipitation indices showed a large fluctuation, both in the whole period and in the three detected different sub-periods, with variation magnitudes of 13%–52%. Most extreme indices had non-significant downward trends, while only the consecutive wet days (CWD) had a significant upward trend. The eight extreme wet indices increased from northwest to southeast, while the consecutive dry days (CDD) had the opposite change direction. Each index had a different trend with different spatial distribution locations and areas. The nine extreme indices revealed that the climate in the HJLB has become a drought since the early 1980s. This was specifically indicated by all four extreme precipitation quantity indices (PRCTOT, R99p, Rx1day, Rx5day) and the extreme intensity index (SDII) declining, as well as the number of heavy precipitation days (R10) decreasing. When the dry–wet variations was divided into the different sub-periods, the climatic dry–wet changes of each index demonstrated more inconsistency and complexity, but most indices in the first sub-period from 1960 to the late 1970s could be regarded as a wet high-oscillation phase, the second sub-period after the early 1980s was a relatively dry low-oscillation phase, and the third sub-period after the late 1990s or early 21st century was a dry medium-oscillation phase. It is worth noting that most extreme indices had an obvious positive linear trend in the third sub-period, which means that in the last 20 years, the precipitation extremes showed an increasing trend. This study could provide a certain scientific reference for regional climate change detection, water resources management, and disaster prevention in the HJLB and similar endorheic basins or inland arid regions.

Modified Palmer Drought Severity Index: Model improvement and application

Monitoring of droughts is the first step into human adaptation and related management of drought hazards. Therefore, drought index is critical in drought monitoring practice. However, the standing drought indices include no information about agricultural irrigation. In this case, based on the Palmer Drought Severity Index (PDSI) and the Self-Calibrating Palmer Drought Severity Index (sc-PDSI), here we proposed the Modified Palmer Drought Severity Index (MPDSI) by considering agricultural irrigation such as irrigation quotas and soil water deficits. We compared changes of droughts monitored by MPDSI and other drought indices considered in this study, and found that MPDSI can well monitor drought conditions in irrigated regions. In this sense, MPDSI can monitor the actual drought conditions under human influences such as irrigation. Besides, we also found that MPDSI can well lessen overestimation of drought conditions by PDSI in terms of drought duration and drought intensity. Therefore, we can conclude that MPDSI can be accepted in drought monitoring practice across China. It should be noted here that the idea behind development of MPDSI and also the MDPSI proposed in this study can be well referenced in drought monitoring in other regions of the globe.

Multiscale Spatio-Temporal Changes of Precipitation Extremes in Beijing-Tianjin-Hebei Region, China during 1958–2017

In this study, based on daily precipitation records during 1958–2017 from 28 meteorological stations in the Beijing-Tianjin-Hebei (BTH) region, the spatio-temporal variations in precipitation extremes defined by twelve indices are analyzed by the methods of linear regression, Mann-Kendall test and continuous wavelet transform. The results showed that the spatial patterns of all the indices except for consecutive dry days (CDD) and consecutive wet days (CWD) were similar to that of annual total precipitation with the high values in the east and the low value in the west. Regionally averaged precipitation extremes were characterized by decreasing trends, of which five indices (i.e., very heavy precipitation days (R50), very wet precipitation (R95p), extreme wet precipitation (R99p), max one-day precipitation (R × 1day), and max five-day precipitation (R × 5day)) exhibited significantly decreasing trends at 5% level. From monthly and seasonal scale, almost all of the highest values in R × 1day and R × 5day occurred in summer, especially in July and August due to the impacts of East Asian monsoon climate on inter-annual uneven distribution of precipitation. The significant decreasing trends in annual R×1day and R×5day were mainly caused by the significant descend in summer. Besides, the possible associations between precipitation extremes and large-scale climate anomalies (e.g., ENSO (El Niño Southern Oscillation), NAO (North Atlantic Oscillation), IOD (Indian Ocean Dipole), and PDO (Pacific Decadal Oscillation)) were also investigated using the correlation analysis. The results showed that the precipitation extremes were significantly influenced by ENSO with one-year ahead, and the converse correlations between the precipitation extremes and climate indices with one-year ahead and 0-year ahead were observed. Moreover, all the indices show significant two- to four-year periodic oscillation during the entire period of 1958–2017, and most of indices show significant four- to eight-year periodic oscillation during certain periods. The influences of climate anomalies on precipitation extremes were composed by different periodic components, with most of higher correlations occurring in low-frequency components.

Regional Temperature Response in Central Asia to National Committed Emission Reductions

National committed greenhouse gas emission reduction actions are the center of the Paris Agreement, and are known as 'Intended Nationally Determined Contributions' (INDC) that aim to slow down global warming. The climate response to INDC emission reduction is a focus in climate change science. In this study, data from 32 global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were applied to investigate the changes in the mean and extreme high temperatures in Central Asia (CA) under the INDC scenario above the present-day level. The results show that the magnitude of warming in CA is remarkably higher than the global mean. Almost all the regions in CA will experience more intense, more frequent, and longer-lasting extreme high-temperature events. In comparison with the INDC scenario, the reduced warming of the 2.0 °C/1.5 °C target scenarios will help avoid approximately 44-61%/65-80% of the increase in extreme temperature events in terms of the intensity, frequency, and duration in CA. These results contribute to an improved understanding of the benefits of limiting global warming to the 2.0 °C/1.5 °C targets, which is paramount for mitigation and adaptation planning.

Spatial and Temporal Patterns of the Extreme Precipitation across the Tibetan Plateau (1986–2015)

The Tibetan Plateau is one of the most vulnerable areas to extreme precipitation. In recent decades, water cycles have accelerated, and the temporal and spatial characteristics of extreme precipitation have undergone dramatic changes across the Tibetan Plateau, especially in its various ecosystems. However, there are few studies that considered the variation of extreme precipitation in various ecosystems, and the impact of El Niño-Southern Oscillation (ENSO), and few researchers have made a quantitative analysis between them. In this study, we analyzed the spatial and temporal pattern of 10 extreme precipitation indices across the Tibetan Plateau (including its four main ecosystems: Forest, alpine meadow, alpine steppe, and desert steppe) based on daily precipitation from 76 meteorological stations over the past 30 years. We used the linear least squares method and Pearson correlation coefficient to examine variation magnitudes of 10 extreme precipitation indices and correlation. Temporal pattern indicated that consecutive wet days (CWD) had a slightly decreasing trend (slope = −0.006), consecutive dry days (CDD), simple daily intensity (SDII), and extreme wet day precipitation (R99) displayed significant increasing trends, while the trends of other indices were not significant. For spatial patterns, the increasing trends of nine extreme precipitation indices (excluding CDD) occurred in the southwestern, middle and northern regions of the Tibetan Plateau; decreasing trends were distributed in the southeastern region, while the spatial pattern of CDD showed the opposite distribution. As to the four different ecosystems, the number of moderate precipitation days (R10mm), number of heavy precipitation days (R20mm), wet day precipitation (PRCPTOT), and very wet day precipitation (R95) in forest ecosystems showed decreasing trends, but CDD exhibited a significant increasing trend (slope = 0.625, P < 0.05). In the other three ecosystems, all extreme precipitation indices generally exhibited increasing trends, except for CWD in alpine meadow (slope = −0.001) and desert steppe (slope = −0.005). Furthermore, the crossover wavelet transform indicated that the ENSO had a 4-year resonance cycle with R95, SDII, R20mm, and CWD. These results provided additional evidence that ENSO play an important remote driver for extreme precipitation variation in the Tibetan Plateau.

Distinguishing the Relative Contribution of Environmental Factors to Runoff Change in the Headwaters of the Yangtze River

The change in river flows at the basin scale reflects the combined influences of changes in various environmental factors associated with climatic and underlying surface properties. Distinguishing the relative contribution of each of these factors to runoff change is critical for sustainable water resource management, but it is also challenging. The headstream region of the Yangtze River, known as “China’s Water Tower”, has undergone a significant runoff change over the past decades. However, the relative contribution of environmental factors to runoff change is still unclear. Here, we designed a series of detrending experiments based on a grid-based hydrological model to quantify the combined influences of multiple environmental factors on runoff change and the relative contribution of an individual factor to runoff change. The results indicate that changes in climate and vegetation significantly increased water yield in the study basin over the past three decades, and the increase in water yield primarily came from the contribution from the upstream of the basin. On the basin scale, the change in precipitation dominated the runoff change that contributed up to 113.2% of the runoff change, followed by the wind speed change with a contribution rate of −15.1%. Other factors, including changes in temperature, relative humidity, sunshine duration (as a surrogate for net radiation), and albedo (as a surrogate for vegetation) had limited effects on runoff change, and the contribution rate of these factors to runoff change ranged from −5% to 5%. On spatial patterns, the influences of changes in some environmental factors on runoff changes were affected by elevation, particularly for temperature. The rising temperature had mixed effects on runoff change, which generally increased water yield at high altitudes of the basin but decreased water yield at low altitudes of the basin.