Impacts of Climate Change and Land-Use Change on Hydrological Extremes in the Jinsha River Basin

Hydrological extremes are closely related to extreme hydrological events, which have been and continue to be one of the most important natural hazards causing great damage to lives and properties. As two of the main factors affecting the hydrological cycle, land-use change and climate change have attracted the attention of many researchers in recent years. However, there are few studies that comprehensively consider the impacts of land-use change and climate change on hydrological extremes, and few researchers have made a quantitative distinction between them. Regarding this problem, this study aims to quantitatively distinguish the effects of land-use change and climate change on hydrological extremes during the past half century using the method of scenarios simulation with the soil and water assessment tool (SWAT). Furthermore, the variations of hydrological extremes are forecast under future scenarios by incorporating the downscaled climate simulations from several representative general circulation models (GCMs). Results show that: (1) respectively rising and declining risks of floods and droughts are detected during 1960–2017. The land use changed little during 1980–2015, except for the water body and building land. (2) The SWAT model possesses better simulation effects on high flows compared with low flows. Besides, the downscaled GCM data can simulate the mean values of runoff well, and acceptable simulation effects are achieved for the extreme runoff indicators, with the exception of frequency and durations of floods and extreme low flows. (3) During the period 1970–2017, the land-use change exerts little impact on runoff extremes, while climate change is one of the main factors leading to changes in extreme hydrological situation. (4) In the context of global climate change, the indicators of 3-day max and 3-day min runoff will probably increase in the near future (2021–2050) compared with the historical period (1970–2005). This research helps us to better meet the challenge of probably increased flood risks by providing references to the decision making of prevention and mitigation measures, and thus possesses significant social and economic value.

Multifractal analysis of diurnal temperature range over Southern Spain using validated datasets

Multifractal properties of diurnal temperature range (DTR) have been analyzed in this work, using validated data of maximum and minimum temperature from 197 weather stations in Southern Spain (Andalusia region). DTR is a crucial factor to characterize the regional climate, providing more information than the average daily temperature. Apart from climate change studies, one of the most important applications of DTR in Agrometeorology is as an input variable in the solar radiation or reference evapotranspiration estimation models based on the temperature. With the aim of obtaining a detailed information for different time scales, different multifractal approaches have been applied. Different quality control methods such as range/limits or persistence tests were previously applied in order to detect incorrect and anomalous values, being discarded in the subsequent analysis. The DTR scaling of moments has been analyzed and the moment scaling exponent function K(q) has been obtained, finding some differences between weather stations. In addition, multifractal dimension (D1) and multifractal degree (MD) were also estimated, revealing differences at coastal and inland locations that show heterogeneity across the region, including its multifractal nature and its invariance for a range of scales. The nonlinear characterization carried out in this work improves the understanding of DTR as an indicator of climate changes, and it can have a very positive impact on the calibration of regional models for estimating solar radiation or reference evapotranspiration based on the temperature. This multifractal characterization can be used to group stations with similar nonlinear dynamics, regardless of their geographical features, in such a way that more accurate coefficients than conventional ones are used.

The Evolution of Climate Changes in Portugal: Determination of Trend Series and Its Impact on Forest Development

Climate changes are a phenomenon that can affect the daily activities of rural communities, with particular emphasis on those directly dependent on the agricultural and forestry sectors. In this way, the present work intends to analyse the impact that climate changes have on forest risk assessment, namely on how the occurrence of rural fires are affecting the management of the forest areas and how the occurrence of these fires has evolved in the near past. Thus, a comparative analysis of the data provided by IPMA (Portuguese Institute of the Sea and the Atmosphere), was carried out for the period from 2001 to 2017 with the climatic normal for the period between 1971 to 2000, for the variables of the average air temperature, and for the precipitation. In this comparative study, the average monthly values were considered and the months in which anomalies occurred were determined. Anomalies were considered in the months in which the average air temperature varied by 1 °C than the value corresponding to the climatic norm, in at least 50% of the national territory. The same procedure was repeated for the variable precipitation, counting as anomaly the occurrence of a variation in precipitation of 50%, also in 50% of the national territory. Then the calculation of the moving averages for cycles of 3, 5 and 7 periods were applied, and the trend lines were projected. Subsequently, the relationship between the results obtained and the occurrence of rural fires as well as the spatial distribution of forest area, species and structure were analyzed. From the results obtained it was possible to confirm the existence of a tendency for the occurrence of climatic anomalies, highlighting the occurrence of an increasing number of months with temperatures higher by at least 1 °C. It was possible to foresee the relation between the occurrence of rural fires and the periods of anomaly and absence of precipitation. From the results obtained it is also possible to infer that, analyzing the tendency for these phenomena to occur, it can be necessary to change the “critical period of rural fires”, since it is verified that what is currently in use does not covers the entire period where anomalies occur and where large-scale rural fires potentially can happen.

Characterization and Spatial Coverage of Heat Waves in Subtropical Brazil

Given the increase in the frequency, intensity, and persistence of heat waves since the 1970s, and in view of the impacts that extreme temperatures may cause for society and the economy, this study aims to characterize heat waves in the subtropical region of Brazil and compare findings with the criterion defined by the World Meteorological Organization (WMO). Daily maximum temperature data was used. By using the percentile methodology, the subtropical region was divided into two regions: region 1 and region 2. We identified 54 heat waves in region 1 and 34 in region 2, which occurred more frequently in winter and spring, and less frequently in summer. A close relationship was observed between the Pacific Decadal Oscillation (PDO) and El Niño–Southern Oscillation (ENSO), both of which are able to modulate the heat waves in each of the different regions. Region 1 presented the highest number of heat waves during the warm (cold) phase of the PDO. As for ENSO, heat waves were more frequent in the neutral phase in both regions. Finally, there was shown to be an increase in the frequency and persistence of heat waves since the 1980s, especially in region 2. The methodology used in this study allows the identification and characterization of heat waves in several regions of different climates.

Projection of future precipitation extremes across the Bangkok Metropolitan Region

There is a pressing need to develop local-scale climate projection profiles for supporting climate impact assessments. This study contributes plausible future precipitation scenarios for the Bangkok Metropolitan Region (BMR), which builds on the existing evidence base that projects increasing future precipitation. Meteorological data sets from 16 stations located within the BMR and nearby provinces were used for bias correcting five regional climate model scenarios, and future extreme indices were graphed and spatially interpolated to interpret how precipitation extremes may develop to the end of the 21st century. Results indicate that over the coming century, total annual rainfall will increase, with the volume and number of days with heavy/very heavy rainfall also increasing. Total monthly and monthly heavy/very heavy rainfall are projected to increase in the late monsoon, and monthly five-day cumulative and one-day maxima project higher amounts of late monsoonal rains. Spatial interpolation of selected indices indicate substantial projected increases in extreme rainfall across the BMR, with its northern part receiving the heaviest amounts of precipitation. In comparison to the past period (1980–2009), over the long-term (2070–2098) the total monthly heavy/very heavy precipitation during October is projected to increase by 100–120% over Pathum Thani province and 80–100% over the remainder of the BMR. Together with the study's associated R and Python scripts, this study aims to provide an open and reproducible approach to deriving plausible future projections of climate variables at the city scale.

Global exposure to rainstorms and the contribution rates of climate change and population change

Quantifying global population exposure to rainstorms is a key component of population risk assessments for rainstorms and induced floods. Based on daily precipitation data from the NEX-GDDP dataset, rainfall from rainstorms is first calculated by a multi-model ensemble method for four periods from 1986 to 2100. Combined with population data from the SSP2 scenario, the global population exposure to rainstorms is then calculated and analyzed. Finally, the contribution rates of climate change effect, population change effect, and joint change effect on exposure change are quantitatively assessed. The results showed that (1) Population exposure to rainstorms shows a linear upward trend from base period to the late 21st century period in most regions, and the mid-21st century period compared with base period has the fastest rate of increase. (2) The spatial patterns of population exposure to rainstorms are very similar for the four periods and the areas with high exposure are mainly distributed in Asia, population exposure of Africa is gradually increasing. The countries with high exposure show little volatility, especially the top eight countries. (3) The change in total exposure is mainly due to population change. Based on the composition of the total exposure change for each country, the number of countries whose climate change effect is greater than that of population change is gradually increasing, and this number reaches more than a quarter of the total when the late 21st century period is compared with the mid-21st century period.

Trend Analysis of Temperature and Precipitation Extremes during Winter Wheat Growth Period in the Major Winter Wheat Planting Area of China

In this study, the major winter wheat planting area of China is selected as the study area, with the time scale of the growth period of winter wheat (a total of 56 growth periods during October 1961 to May 2016). The significance, stability, magnitude of the trend and the average trend of the study area with eight temperature indices and seven precipitation indices of 453 meteorological stations are tested by Mann–Kendall method and Sen’s nonparametric method. The following observation can be made: (1) the cold extreme indices show strong and stable downward trend in most of the stations in the study area, while the hot extreme indices show a strong and stable upward trend, especially in the northern winter wheat planting area and the north of the southern winter wheat planting area. (2) The trends of extreme precipitation indices in most of the sites in the study area are insignificant and unstable. Only in R20mm, a significant and stable decreasing trend is shown in some stations, which is mainly located in the northern winter wheat planting area and part of the central and western regions in the study area. The results in some ways could enrich the references for understanding the climate change in the growth period of winter wheat in the region and help to formulate a better agronomic management practice of winter wheat.

Global Heat Wave Hazard Considering Humidity Effects during the 21st Century

Humidity is a significant factor contributing to heat stress, but without enough consideration in studies of quantifying heat hazard or heat risk assessment. Here, the simplified wet-bulb globe temperature (WBGT) considering joint effects of temperature and humidity was utilized as a heat index and the number of annual total heat wave days (HWDs) was employed to quantify heat hazard. In order to evaluate the humidity effects on heat waves, we quantified the difference in the number of HWDs over global land based on air temperature and WBGT. Spatial and temporal changes in surface air temperature, relative humidity, WBGT, and the difference in HWDs were analyzed using multi-model simulations for the reference period (1986-2005) and different greenhouse gas emission scenarios. Our analysis suggests that annual mean WBGT has been increasing since 1986, which is consistent with the rising trend in surface air temperature despite a slight decrease in relative humidity. Additionally, changes in annual mean WBGT are smaller and more spatially uniform than those in annual mean air temperature as a cancelation effect between temperature and water vapor. Results show that there is an underestimation of around 40-140 days in the number of HWDs per year in most regions within 15° latitude of the equator (the humid and warm tropics) during 2076-2095 without considering humidity effects. However, the estimation of HWDs has limited distinction between using WBGT and temperature alone in arid or cold regions.

Climate Change Projections of Extreme Temperatures for the Iberian Peninsula

The comprehensive characterization of heat waves and extreme hot days is fundamental for policymakers due to its vast implications for human health. This study evaluates extreme temperature changes over the Iberian Peninsula for the present climate and future projections, considering extreme temperature indices, cold/heat waves, and a recovery factor, using the Weather Research and Forecasting model. The projected temperatures show an increase of over 6 °C. An increase in the number of summer days and tropical nights and a decrease in frost days is expected. The number of heat waves and their duration and intensity are expected to increase. The number of heat wave days are expected to increase, with much of the average summer season being under heat wave conditions. The recovery factor is expected to decrease. Cold spells are projected to decrease in terms of number, intensity, duration, and number of spell days, whereas the recovery factor is expected to increase. Heat wave analysis was combined with maximum temperature thresholds to isolate extreme heat waves. The results show an increase in extreme heat wave days, with regions experiencing over 10 heat wave days with maximum temperature surpassing 45 °C for the long-term future.

Regional Climatic Features of the Arabian Peninsula

The climate of the Arabian Peninsula is characterized by significant spatial and temporal variations, due to its complex topography and the large-scale atmospheric circulation. Furthermore, the role of dust in the formation of regional climate is considered to be crucial. In this work, the regional climatology for the Arabian Peninsula has been studied by employing a high resolution state of the art atmospheric model that included sophisticated physical parameterization schemes and online treatment of natural aerosol particles. The simulations covered a 30-year period (1986–2015) with a temporal resolution of 3 h and a spatial distance of 9 km. The main focus was given to the spatial and temporal variations of mean temperature and temperature extremes, wind speed and direction, and relative humidity. The results were evaluated using in situ measurements indicating a good agreement. An examination of possible climatic changes during the present climate was also performed through a comprehensive analysis of the trends of mean temperature and temperature extremes. The statistical significant trend values were overall positive and increased over the northwestern parts of the examined area. Similar spatial distributions were found for the daily minimum and maximum temperatures. Higher positive values emerged for the daily maxima.

Deciphering impacts of climate extremes on Tibetan grasslands in the last fifteen years

Climate extremes have emerged as a crucial driver of changes in terrestrial ecosystems. The Tibetan Plateau, facing a rapid climate change, tends to favor climate extremes. But we lack a clear understanding of the impacts of such extremes on alpine grasslands. Here we show that extreme events (drought, extreme wet, extreme cold and extreme hot) occurred at a frequency of 0.67-4 months decade^-1 during 2001-2015, with extreme precipitation predominantly occurring in June-to-August and extreme temperatures in May. Drought and extreme wet cause opposite and asymmetric effects on grassland growth, with drought-induced reductions greater than increases due to extreme wet. Grassland responses to extreme temperatures, which predominantly occur in May, show a dipole-like spatial pattern, with extreme hot (cold) events enhanced (reduced) growth in the eastern plateau but slightly reduced (enhanced) growth in the western plateau. These opposite responses to extreme temperatures over the eastern plateau are explained by the possibility that the occurrence of extreme cold slows the preseason temperature accumulation, delaying the triggering of spring phenology, while extreme hot hastens the accumulation. In the western plateau, in contrast, positive responses to extreme cold are induced by accompanying high precipitation. Furthermore, high extremeness of climate events generally led to a much lower extremeness in growth response, implying that the Tibetan grasslands have a relatively high resistance to climate extremes. The ecosystem models tested could not accurately simulate grassland responses to drought and extreme temperatures, and require re-parameterization before trust can be placed in their output for this region.

Changes in Precipitation and Drought Extremes over the Past Half Century in China

Changes in climate extremes have become a hot issue in the research field of climate change recently. Many studies have reported that climate extremes have occurred more frequently and with increasing intensity in recent decades. In this study, thresholds of precipitation and drought extremes were determined by the cumulative distribution function, and their spatiotemporal changes over the past half-century in China were analyzed by relative change rate. The results show that: (1) precipitation extremes increased in all regions except North China, while increasing trends of drought extremes were detected in all regions except Northwest China and the Qing–Tibet Plateau; (2) the maximum change rates in frequency of precipitation extremes were found in Northwest China and the Qing–Tibet Plateau, with values of 16.13% and 8.12%, and the maximum change rates in frequency of drought extremes were in Southwest and Southeast China, whose increases in intensity of drought extremes were also the maximum; (3) variation in precipitation extremes showed a relatively mixed pattern with higher heterogeneity compared to that of drought extremes; and (4) changes in precipitation and drought extremes relate to mid-intensity, lower-intensity, and annual precipitation.

Statistical Analysis of Extreme Events in Precipitation, Stream Discharge, and Groundwater Head Fluctuation: Distribution, Memory, and Correlation

Hydrological extremes in the water cycle can significantly affect surface water engineering design, and represents the high-impact response of surface water and groundwater systems to climate change. Statistical analysis of these extreme events provides a convenient way to interpret the nature of, and interaction between, components of the water cycle. This study applies three probability density functions (PDFs), Gumbel, stable, and stretched Gaussian distributions, to capture the distribution of extremes and the full-time series of storm properties (storm duration, intensity, total precipitation, and inter-storm period), stream discharge, lake stage, and groundwater head values observed in the Lake Tuscaloosa watershed, Alabama, USA. To quantify the potentially non-stationary statistics of hydrological extremes, the time-scale local Hurst exponent (TSLHE) was also calculated for the time series data recording both the surface and subsurface hydrological processes. First, results showed that storm duration was most closely related to groundwater recharge compared to the other storm properties, while intensity also had a close relationship with recharge. These relationships were likely due to the effects of oversaturation and overland flow in extreme total precipitation storms. Second, the surface water and groundwater series were persistent according to the TSLHE values, because they were relatively slow evolving systems, while storm properties were anti-persistent since they were rapidly evolving in time. Third, the stretched Gaussian distribution was the most effective PDF to capture the distribution of surface and subsurface hydrological extremes, since this distribution can capture the broad transition from a Gaussian distribution to a power-law one.

Urban Heat Island and Future Climate Change-Implications for Delhi's Heat

UrbClim, the urban climate model, is used for short- and long-term projections of climate for Delhi. The projections are performed for RCP8.5 using an ensemble of 11 GCM model outputs. Various heat stress indices were employed to understand the role of urban heat island (UHI) in influencing the present and future urban climate of the city. UHI intensity based on 5% warmest nights (TNp95) was 4.1 °C and exhibits negligible change over time. However, the impact of UHI on other heat stress indices is very strong. Combined hot days and tropical nights (CHT) that influenced 58-70% of the reference time frame are expected to rise to 68-77% in near-future and to 91-97% in far-future time periods. For reference time period, urban areas experience 2.3 more number of heat wave days (NHWD) than rural areas per summer season. This difference increases to 7.1 in short-term and 13.8 in long-term projections. Similar to this trend, frequency of heat waves (FHW) for urban areas is also expected to increase from 0.8 each summer season in reference time frame to 2.1 and 5.1 in short- and long-term projections. The urban-rural difference for duration of heat waves (DHW) appears to increase from 1.7 days in past to 2.3 and 2.2 days in future, illustrating that DHW for cities will be higher than non-urban areas at least by 2 days. The intensity of heat wave (IHW) for urban land uses increases from 40 °C in reference time frame to 45 °C in short-term projection to 49 °C in far future. These values for non-urban land use were 33 °C during the baseline time period and are expected to increase to 42 °C and 46 °C in near- and far-future time frames. The results clearly indicate the contribution of UHI effects in intensifying the impacts of extreme heat and heat stress in the city.

Carbon balance and source-sink metabolic changes in winter wheat exposed to high night-time temperature

Carbon loss under high night-time temperature (HNT) leads to significant reduction in wheat yield. Growth chamber studies were carried out using six winter wheat genotypes, to unravel postheading HNT (23°C)-induced alterations in carbon balance, source-sink metabolic changes, yield, and yield-related traits compared with control (15°C) conditions. Four of the six tested genotypes recorded a significant increase in night respiration after 4 days of HNT exposure, with all the cultivars regulating carbon loss and demonstrating different degree of acclimation to extended HNT exposure. Metabolite profiling indicated carbohydrate metabolism in spikes and activation of the TriCarboxylic Acid (TCA) cycle in leaves as important pathways operating under HNT exposure. A significant increase in sugars, sugar-alcohols, and phosphate in spikes of the tolerant genotype (Tascosa) indicated osmolytes and membrane protective mechanisms acting against HNT damage. Enhanced night respiration under HNT resulted in higher accumulation of TCA cycle intermediates like isocitrate and fumarate in leaves of the susceptible genotype (TX86A5606). Lower grain number due to lesser productive spikes and reduced grain weight due to shorter grain-filling duration determined HNT-induced yield loss in winter wheat. Traits and mechanisms identified will help catalyze the development of physiological and metabolic markers for breeding HNT-tolerant wheat.

A downscaling-disaggregation approach for developing IDF curves in arid regions

Over the past decades, urbanization in Arabian Gulf region expands in flood-prone areas at an unprecedented rate. Chronic water stress and potential changes in extreme rainfall attributed to climate change therefore pose unique challenges in planning and designing water management infrastructures. The objective of this study is to develop a framework to integrate climate change variations into intensity-duration-frequency (IDF) curves in Oman. A two-stage downscaling-disaggregation method was applied with rainfall at Tawi-Atair station in Dhofar region. Potential variations of extreme rainfall in future were examined by eight scenarios composed with two general circulation models (GCMs), two representative concentration pathways (RCPs), and two future periods (2040-2059 and 2080-2099). A stochastic weather generator model was used to downscale rainfall output from GCM grid scale to local scale. Downscaled daily data were then disaggregated to hourly and 5-min series by using K-nearest neighbor (K-NN) technique. Annual maximum rainfall extracted from eight future scenarios and also from present climate (baseline period) was used to develop rainfall intensity-frequency relationships for eight durations range from 5 min to 24 h. Results of the K-NN analysis indicate that the optimum window size of 57 days and 181 h is suitable for hourly and 5-min disaggregation models, respectively. Results also predict that the effects of climate change on the rainfall intensity will be more significant on storms with shorter durations and higher return periods. Moving towards the end of the twenty-first century, the return period of extreme rainfall events is likely to decrease due to intensified rainfall events.

Evaluating the influence of climate change on the fate and transport of fecal coliform bacteria using the modified SWAT model

Fecal coliform bacteria (FCB) contamination of natural waters is a serious public health issue. Therefore, understanding and anticipating the fate and transport of FCB are important for reducing the risk of contracting diseases. The objective of this study was to analyze the impacts of climate change on the fate and transport of FCB. We modified both the soil and the in-stream bacteria modules in the soil and water assessment tool (SWAT) model and verified the prediction accuracy of seasonal variability of FCB loads using observations. Forty bias-correcting GCM-RCM projections were applied in the modified SWAT model to examine various future climate conditions at the end of this century (2076-2100). Lastly, we also compared the variability of FCB loads under current and future weather conditions using multi-model ensemble simulations (MMES). The modified SWAT model yielded a satisfactory performance with regard to the seasonal variability of FCB amounts in the soil and FCB loading to water bodies. The modified SWAT model presented substantial proliferation of FCB in the soil (30.1%-147.5%) due to an increase in temperature (25.1%). Also, increase in precipitation (53.3%) led to an increase in FCB loads (96.0%-115.5%) from the soil to water body. In the in-stream environment, resuspension from the stream bed was the dominant process affecting the amount of FCB in stream. Therefore, the final FCB loads increased by 71.2% because of the growing peak channel velocity and volume of water used due to an increase in precipitation. Based on the results of MMES, we concluded that the level of FCB would increase simultaneously in the soil as well as in stream by the end of this century. This study will aid in understanding the future variability of FCB loads as well as in preparing an effective management plan for FCB levels in natural waters.

A High-Resolution Global Gridded Historical Dataset of Climate Extreme Indices

Climate extreme indices (CEIs) are important metrics that not only assist in the analysis of regional and global extremes in meteorological events, but also aid climate modellers and policymakers in the assessment of sectoral impacts. Global high-spatial-resolution CEI datasets derived from quality-controlled historical observations, or reanalysis data products are scarce. This study introduces a new high-resolution global gridded dataset of CEIs based on sub-daily temperature and precipitation data from the Global Land Data Assimilation System (GLDAS). The dataset called “CEI_0p25_1970_2016” includes 71 annual (and in some cases monthly) CEIs at 0.25 ∘ × 0.25 ∘ gridded resolution, covering 47 years over the period 1970–2016. The data of individual indices are publicly available for download in the commonly used Network Common Data Form 4 (NetCDF4) format. Potential applications of CEI_0p25_1970_2016 presented here include the assessment of sectoral impacts (e.g., Agriculture, Health, Energy, and Hydrology), as well as the identification of hot spots (clusters) showing similar historical spatial patterns of high/low temperature and precipitation extremes. CEI_0p25_1970_2016 fills gaps in existing CEI datasets by encompassing not only more indices, but also by being the only comprehensive global gridded CEI data available at high spatial resolution.

Study on the Functional Improvement of Economic Damage Assessment for the Integrated Assessment Model

The economic damage function of the integrated assessment model (IAM) is used to quantify the economic loss caused by climate change, and it is quite important for coupling the economic system and natural system in a model. However, there are many shortcomings of the damage function in the current IAM. The most important shortcoming is that the only climatic factor in the damage function is the global annual mean temperature rise, which would result in the estimation deviating from reality. We improved the damage function by introducing extreme climate change events. Additionally, the improved damage function is applicable to the regional characteristics by using regional climate change data. The extreme climate event information is extracted with the categories of the disasters. The damage function is set up by using the Ordinary Least Square (OLS) method based on the climate data and economic loss data. The results show that the improved IAM damage function can better reflect the actual climate change economic loss in China, making it more reasonable. This paper provides an important method and technical solution for the realization of an effective connection between the disaster damage function of the integrated assessment model and the climate elements of the Earth system model.

Spatial and Temporal Variations of Compound Droughts and Hot Extremes in China

Droughts and hot extremes may lead to tremendous impacts on the ecosystem and different sectors of the society. A variety of studies have been conducted on the variability of the individual drought or hot extreme in China. However, the evaluation of compound droughts and hot extremes, which may induce even larger impacts than the individual drought or hot extreme, is still lacking. The aim of this study is to investigate changes in the frequency and spatial extent of compound droughts and hot extremes during summer in China using monthly precipitation and daily temperature data from 1953 to 2012. Results show that a high frequency of compound droughts and hot extremes mostly occur in the regions stretching from northeast to southwest of China. There is an overall increase in the frequency of co-occurrence of droughts and hot extremes across most parts of China with distinct regional patterns. In addition, an increasing trend in the areas covered by compound extremes has been observed, especially after the 1990s. At regional scales, the increase of the frequency and spatial extent of compound extremes has been shown to be most profound in North China (NC), South China (SC), and Southwest China (SWC), while the decrease of compound extremes was found in Central China (CC). These results show the variability of compound droughts and hot extremes and could provide useful insights into the mitigation efforts of extreme events in China.

Assessing Hydrological Ecosystem Services in a Rubber-Dominated Watershed under Scenarios of Land Use and Climate Change

Land use and climate change exert pressure on ecosystems and threaten the sustainable supply of ecosystem services (ESS). In Southeast-Asia, the shift from swidden farming to permanent cash crop systems has led to a wide range of impacts on ESS. Our study area, the Nabanhe Reserve in Yunnan province (PR China), saw the loss of extensive forest areas and the expansion of rubber (Hevea brasiliensis Müll. Arg.) plantations. In this study, we model water yield and sediment export for a rubber-dominated watershed under multiple scenarios of land use and climate change in order to assess how both drivers influence the supply of these ESS. For this we use three stakeholder-validated land use scenarios, varying in their degree of rubber expansion and land management rules. As projected climate change varies remarkably between different climate models, we combined the land use scenarios with datasets of temperature and precipitation changes, derived from nine General Circulation Models (GCMs) of the Fifth Assessment Report of the IPCC (Intergovernmental Panel on Climate Change) in order to model water yield and sediment export with InVEST (Integrated Valuation of Ecosystem Services and Trade-offs). Simulation results show that the effect of land use and land management decisions on water yield in Nabanhe Reserve are relatively minor (4% difference in water yield between land use scenarios), when compared to the effects that future climate change will exert on water yield (up to 15% increase or 13% decrease in water yield compared to the baseline climate). Changes in sediment export were more sensitive to land use change (15% increase or 64% decrease) in comparison to the effects of climate change (up to 10% increase). We conclude that in the future, particularly dry years may have a more pronounced effect on the water balance as the higher potential evapotranspiration increases the probability for periods of water scarcity, especially in the dry season. The method we applied can easily be transferred to regions facing comparable land use situations, as InVEST and the IPCC data are freely available.

Development of Damage Prediction Formula for Natural Disasters Considering Economic Indicators

Damage caused by natural disasters produces the difference of damage size not only according to damage volume or size, but a national economic level. In addition, budgets and aids should be constantly acquired for disaster management since natural disasters sporadically or irregularly occur. This study proposed disaster management methods by countries considering natural disaster damage documents and economic indicators from 1900 to 2017 among 187 countries in the world. It developed a damage prediction formula considering damage documents of previous natural disasters, economic indicators by countries, and basic indicators as disaster management methods by countries. Independent variables of the damage prediction formula include GDP, population, and area. It applied multiple regression analysis and calculated average human losses due to death, human losses affected, and damage costs by countries. Regarding the adjusted R² of the natural disaster damage prediction formula, the human losses from deaths mean was 0.893, the human losses affected mean was 0.915, and the damage costs mean was 0.946, which had higher explanatory powers. Therefore, results from this study are considered to calculate quantitative damage sizes considering uncertain damage sizes of natural disasters, economic indicators by countries, and are used as indicators for disaster management.

Impact of a severe flood on large-scale contamination of arable soils by potentially toxic elements (Serbia)

Extreme flooding in May, 2014 affected the sub-catchments of six major rivers in Serbia. The goal of the study was to evaluate the contents of potentially toxic elements (PTEs) As, Cd, Pb, Cr, Ni, Cu, and Zn in flood sediments and arable soils within the affected sub-catchments using regulatory guidelines and background levels. The sub-catchment of West Morava was selected to assess the degree of sediments and soils contamination and environmental risk [using the Pollution index (P_i), Enrichment factor, Geo-accumulation index, and Potential ecological risk index (PERI)] as well as to identify main PTEs sources by Principal component (PCA) and cluster analysis. Contents of Ni, Cr, As, Pb, and Cu above both guidelines and background levels, and of Zn and Cd above background levels were detected in the sediments and soils from all the sub-catchments. P_i indicted that about 95% of the soils and sediments were extremely polluted by Ni and about 65% slightly polluted by Cr, whereas about 90% were not polluted by As, Cd, Pb, Cu, or Zn. E_f indicated minor to moderate enrichment of the soils and sediments by Ni, and Cr. PCA differentiated a geogenic origin of Ni, Cr, As, and Pb, a mixed origin of Cd and Zn, and a predominantly anthropogenic origin of Cu. PERI of the soils and sediments suggested a low overall multi-element ecological risk. The ecological risk of the individual elements (E _r ⁱ ) for soils was Zn < Cr < Pb < Ni < Cu < As < Cd.

Spatial and temporal variability in extreme temperature and precipitation events in Inner Mongolia (China) during 1960-2017

Due to global warming, extreme climate events have become an important issue, and different geographical regions have different sensitivities to climate change. Therefore, temporal and spatial variations in extreme temperature and precipitation events in Inner Mongolia were analyzed based on the daily maximum temperature, minimum temperature, and precipitation data during the period of 1960-2017. The results showed that warm extreme indices, such as SU25, TX90p, TN90p, and WSDI, significantly increased, whereas the cold extreme indices, such as FD0, TX10p, TN10p, and CSDI, significantly decreased; all indices have obvious abrupt changes based on the Mann-Kendall test; nighttime warming was higher than daytime warming. Extreme precipitation indices slightly decreased overall. All of the extreme temperature and precipitation indices had long-range correlations based on detrended fluctuation analysis (a > 0.5), thereby indicating that the extreme climate indices will maintain their current trend directions in the future. ENSO, AO, and IOD had a strong positive influence on warm extremes and a strong negative influence on cold extremes in Inner Mongolia. NCEP/NCAR and ERA-20CM reanalysis showed that strengthening anticyclone circulation, increasing geopotential height, decreasing daytime cloudiness and increasing nightime cloudiness contributed to changes in climate extremes in Inner Mongolia.

The Multi-Scale Temporal Variability of Extreme Precipitation in the Source Region of the Yellow River

Changes in extreme precipitation are critical to assess the potential impacts of climate change on human and natural systems. This paper provides a comprehensive investigation on the multi-scale temporal variability of extreme precipitation in the Source Region of the Yellow River (SRYR). The statistical analysis explores multi-scale extreme precipitation variability ranging from short to long term, including seasonal, annual, and inter-annual variations at different locations in the SRYR. The results suggest that seasonal patterns of extreme precipitation do not always follow the seasonal pattern of total precipitation. Heavy precipitation mostly happens during the period from May and October with July as the peak, while dry conditions are mostly seen in winter seasons. However, there are no significant annual trends for most indices at most locations. The extreme heavy precipitation presents an increasing trend at high elevation and decreasing trend at low elevation. The extreme dry condition presents more consistently decreasing trends at nearly all locations. Long-term analyses indicate that most of the selected indices except average daily intensity display multi-year bands ranging from 2 to 8 years which is probably due to the effects of El Niño–Southern Oscillation (ENSO). A further evaluation on how the ENSO events would impact extreme precipitation shows that eastern Pacific warming (EPW) and central Pacific warming (CPW) would bring less extreme heavy precipitation compared to normal years. These results can provide a beneficial reference to understand the temporal variability of extreme precipitation in the SRYR.

Extreme temperature and mortality: evidence from China

The frequency, intensity, and duration of extreme temperature events are expected to rise in the future and increase the related health risks of human beings. Using a novel, nationwide dataset that links extreme temperature and mortality, we estimated the short-term and long-term effects of extreme temperature on mortality in China during 2002-2013. Both extreme hot and extreme cold had immediate and long-term effects on all-cause mortality. Annual deaths per 100,000 people due to extreme hot and cold in the long term were considerably larger compared to the short term. The change in cold spell duration indicator exhibited the greatest effects on annual deaths per 100,000 people among a set of extreme weather indicators. Furthermore, cities with low economic development levels were more vulnerable to extreme temperature, compared to cities with high economic development levels. Our results offer important policy implications for developing a regional-specific extreme weather plan to handle extreme temperature events in China.

Regional Temporal and Spatial Trends in Drought and Flood Disasters in China and Assessment of Economic Losses in Recent Years

Understanding the temporal and spatial distribution in disasters plays an important role in disaster risk management. The present study aims to explore the long-term trends in drought and floods over China and estimate the economic losses they cause. A peak-over-threshold approach is used to identify flood peaks, and the relationship between the disasters and climate indices is investigated using Poisson regression. The major results are as follows: (1) the northeastern part of China was severely affected by drought disasters (average damaged area was 6.44 million hectares); (2) the northern part of East China and Central China upstream of the Yangtze River were severely affected by flood disasters (average damaged area was 3.97 million hectares); (3) in the Yangtze River Basin, there are increasing trends in terms of drought and extreme precipitation, especially upstream of the Yangtze River, accompanied by severe disaster losses; and (4) by combining the trends in drought and extreme precipitation days with the spatial distribution of damaged areas, the study indicates that the increasing trend in droughts has shifted gradually from north to south, and the increasing trend in extreme precipitation gradually has shifted from south to north.

An in vivo model to assess the thermoregulatory response of lactating Holsteins to an acute heat stress event occurring after a pharmacologically-induced LH surge

Hyperthermia occurring 10-12 h after LH surge reduces quality of maturing oocyte, thereby reducing fertility. Objective was to examine consequences of an acute heat stress and the influence of certain hormones on the thermoregulatory responses of lactating cows during this critical period. Between the months of February through May, cows were transported to a facility and maintained at a temperature-humidity index (THI) of 65.9 ± 0.2 (thermoneutral) or exposed to changes in THI to simulate what may occur during an acute heat stress event (71-86 THI; heat stress); cows were rapidly cooled thereafter. Mixed model regressions with repeated measures were used to test respiration rates (RR) and rectal temperature (RT). Within 40 and 110 min of increasing THI, RR increased in a quadratic fashion (P < 0.001); RT increased by 0.04 ± 0.1 °C (P < 0.001) per unit THI. Changes in RR lagged THI and preceded rises in RT. Average THI 3-days before treatment (prior THI) influenced RR (P = 0.050) and RT (P < 0.001) changes. Increased RR was more noticeable in heat-stressed cows when prior THI was in the 40 s. Rectal temperature of heat-stressed cows was 0.8 ± 0.02 °C lower when prior THI was in the 40 s versus low 60 s. Levels of progesterone and luteinizing hormone before treatment were predictive of thermoregulatory response in heat-stressed cows. Rapid cooling decreased RR by 0.6 ± 0.1 bpm (P < 0.001) and RT by 0.02 ± 0.002 °C per min (P < 0.002). Speed and magnitude of thermoregulatory changes to an acute heat stress and after sudden cooling emphasizes importance of strategic cooling before ovulation. Efforts to do so when prior THI approaches levels expected to induce mild stress are especially important. Respiration rate is a useful indicator of the degree of hyperthermia a lactating cow is experiencing.

Observed Trends and Changes in Temperature and Precipitation Extreme Indices over Myanmar

Projected increase in frequency and severity of extreme events are important threat brought by climate change. Thus, there is a need to understand the dynamics and magnitude of climate extreme at local and regional level. This study examines the patterns of annual trends and changes of extreme daily temperature and precipitation in Myanmar for the period of 1981 to 2015 using the RClimDex 1.1 software. The trends of maximum and minimum temperature show significant warming trends (p < 0.001) across Myanmar. From 2009 to 2015, the maximum temperature anomaly has continuously increased by 0.5 °C for all years except 2011. The larger rise in both maximum and minimum temperature observed after 2000 suggests that, overall, days and nights are becoming hotter for the entirety of Myanmar over this recent period. Furthermore, our works also show that the temperature extreme indices of warm days and warm nights have increased, whereas the frequency of cool days and cool nights have decreased. Our analysis also reveals that increasing trends in precipitation anomaly were not significant during 1981–2015. On the contrary, slight increasing trends towards wetter conditions were observed with a rate of 76.52 mm/decade during the study period. The other precipitation extreme indicators—namely, annual total precipitation (PRCPTOT), heavy precipitation days (R20mm), extreme wet days precipitation (R99p), and consecutive wet days (CWD)—are consistent with warming trends. Additionally, the relationship between inter-annual variability in the climate extremes indices and Oceanic Niño Index (ONI) patterns was also examined with a focus on the influence of the El Niño-Southern Oscillation (ENSO) phenomenon.

Analysis of Precipitation Extremes in the Source Region of the Yangtze River during 1960–2016

The source region of the Yangtze River (SRYR) on the central Tibetan Plateau has seen one of the most significant increases in temperature in the world. Climate warming has altered the temporal and spatial characteristics of precipitation in the SRYR. In this study, we analyzed the temporal trends and spatial distributions of extreme precipitation in the SRYR during 1960–2016 using 11 extreme precipitation indices (EPIs) derived from daily precipitation data collected at five meteorological stations in the region. The trends in the EPIs were estimated using the linear least squares method, and their statistical significance was assessed using the Mann–Kendall test. The results show the following. Temporally, the majority of SRYR EPIs (including the simple daily intensity index, annual maximum 1-day precipitation (RX1day), annual maximum 5-day precipitation (RX5day), very wet day precipitation, extremely wet day precipitation, number of heavy precipitation days, number of very heavy precipitation days, and number of consecutive wet days) exhibited statistically nonsignificant increasing trends during the study period, while annual total wet-day precipitation (PRCPTOT) and the number of wet days exhibited statistically significant increasing trends. In addition, the number of consecutive dry days (CDD) exhibited a statistically significant decreasing trend. For the seasonal EPIs, the PRCPTOT, RX1day, and RX5day all exhibited nonsignificant increasing trends during the wet season, and significant increasing trends during the dry season. Spatially, changes in the annual and wet season EPIs in the study area both exhibited significant differences in their spatial distribution. By contrast, changes in dry season PRCPTOT, RX1day, and RX5day exhibited notable spatial consistency. These three indices exhibited increasing trends at each station. Moreover, there was a statistically significant positive correlation between the annual PRCPTOT and each of the other EPIs (except CDD). However, the contribution of extreme precipitation to annual PRCPTOT exhibited a nonsignificant decreasing trend.

Spatio-Temporal Trend Analysis of Rainfall and Temperature Extremes in the Vea Catchment, Ghana

This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash–Sutcliff efficiency (0.98) and percentage bias (4.4% and −8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.

GHWR, a multi-method global heatwave and warm-spell record and toolbox

Heatwaves are extended periods of unusually high temperatures with significant societal and environmental impacts. Despite their significance, there is not a generalized definition for heatwaves. In this paper, we introduce a multi-method global heatwave and warm-spell data record and analysis toolbox (named GHWR). In addition to a comprehensive long-term global data record of heatwaves, GHWR allows processing and extracting heatwave records for any location efficiently. We use traditional constant temperature threshold methods, as well as spatially and temporally localized threshold approaches to identify heatwaves. GHWR includes binary (0/1) occurrence records of heatwaves/warm-spells, and annual summary files with detailed information on their frequency, duration, magnitude and amplitude. GHWR also introduces the standardized heat index (SHI) as a generalized statistical metric to identify heatwave/warm-spells. SHI has direct association with the probability distribution function of long-term daily temperatures for any given calendar day and spatial grid. Finally, GHWR offers a unique opportunity for users to select the type of heatwave/warm-spell information from a plethora of methods based on their needs and applications.

The First Comparisons of IMERG and the Downscaled Results Based on IMERG in Hydrological Utility over the Ganjiang River Basin

Rainfall information is a prerequisite to and plays a vital role in driving hydrological models. However, limited by the observation methods, the obtained precipitation data, at present, are still too coarse. In this study, a new downscaling method was proposed to obtain high spatial resolution (~1 km/hourly) precipitation estimates based on Integrated Multi-satellitE Retrievals for GPM (IMERG) data at hourly scale. Compared with original IMERG data, the downscaled precipitation results showed the similar spatial patterns with those of original IMERG data, but with finer spatial resolution. In addition, the downscaled precipitation estimates were further analyzed to quantify their improvements using the Coupled Routing and Excess STorage (CREST) model across Ganjiang River basin. Compared with the observed streamflow, the downscaled precipitation results showed satisfying hydrological performance, with Nash-Sutcliffe Coefficient of Efficiency (NSCE), Root Mean Square Error (RMSE), Relative Bias (BIAS), and Correlation Coefficient (CC). The improvement in terms of four statistic metrics in terms of streamflow simulation also indicated great potential of hydrological utility for the downscaled precipitation results.

Threshold Values of Extreme Hydrometeorological Events on the Polish Baltic Coast

The main aim of this study is to determine the threshold values for extreme sea and weather events on the Polish Baltic coast. The study is based on daily hydrometeorological data on the sea level; air temperature and atmospheric precipitation collected between 1965–2014 from six coastal sites (Świnoujście; Kołobrzeg, Ustka, Łeba, Hel, and Gdynia/Gdańsk). Threshold values for the occurrence of extreme events (with a probability of 10% and 95%, and a return rate of once every 10 years) and exceptionally extreme events (with a probability of 1% and 99%, and a return rate of once every 100 years) were determined using probability distribution and quantile analysis. Hydrometeorological absolute extremes were also determined. The methodology used to determine these extreme events and the time-space analysis of hydrometeorological extremes reveal significant geohazards for the functioning of the Baltic coastal zone, including the erosion of coastal dunes and cliffs and the destruction of technical infrastructure.

Projected Changes in Hydrological Extremes in the Yangtze River Basin with an Ensemble of Regional Climate Simulations

This paper estimates the likely impacts of future climate change on streamflow, especially the hydrological extremes over the Yangtze River basin. The future climate was projected by the Coordinated Regional Climate Downscaling Experiment in East Asia (CORDEX-EA) initiative for the periods 2020–2049 under two representative concentration pathways (RCP) 4.5 and 8.5 emission scenarios. The bias corrected outputs from five regional climate models (RCMs) were used in conjunction with the variable infiltration capacity (VIC) macroscale hydrological model to produce hydrological projections. For the future climate of the Yangtze River basin, outputs from an ensemble of RCMs indicate that the annual mean temperature will increase for 2020–2049 by 1.81 °C for RCP4.5 and by 2.26 °C for RCP8.5. The annual mean precipitation is projected to increase by 3.62% under RCP4.5 and 7.65% under RCP8.5. Overall, increases in precipitation are amplified in streamflow, and the change in streamflow also shows significant temporal and spatial variations and large divergence between regional climate models. At the same time, the maximum streamflow in different durations are also projected to increase at three mainstream gauging stations based on flood frequency analysis. In particular, larger increases in maximum 1-day streamflow (+14.24% on average) compared to 5-day and 15-day water volumes (+12.79% and +10.24%) indicate that this projected extreme streamflow increase would be primarily due to intense short-period rainfall events. It is necessary to consider the impacts of climate change in future water resource management.

Dynamic amplification of extreme precipitation sensitivity

Changes in precipitation extremes under climate change are subject to substantial uncertainty. Atmospheric moisture increases alone would make extreme rain events heavier at a well-understood rate of ∼7% K−1, but a component associated with storm dynamics is much less well-understood and can either amplify or reduce that moisture-driven intensification. This paper uses an idealized modeling framework to understand the coupling of these two components, simulating one actual heavy rain event in both the present climate and hypothetical perturbed climates. The increased heating due to increased moisture drives a dynamical increase in large-scale ascent, amplifying the moisture-driven response by as much as a factor of two for warmer climates.

A useful starting hypothesis for predictions of changes in precipitation extremes with climate is that those extremes increase at the same rate as atmospheric moisture does, which is ∼7% K−1 following the Clausius–Clapeyron (CC) relation. This hypothesis, however, neglects potential changes in the strengths of atmospheric circulations associated with precipitation extremes. As increased moisture leads to increased precipitation, the increased latent heating may lead to stronger large-scale ascent and thus, additional increase in precipitation, leading to a super-CC scaling. This study investigates this possibility in the context of the 2015 Texas extreme precipitation event using the Column Quasi-Geostrophic (CQG) method. Analogs to this event are simulated in different climatic conditions with varying surface temperature (Ts) given the same adiabatic quasigeostrophic forcing. Precipitation in these events exhibits super-CC scaling due to the dynamic contribution associated with increasing ascent due to increased latent heating, an increase with importance that increases with Ts. The thermodynamic contribution (attributable to increasing water vapor; assuming no change in vertical motion) approximately follows CC as expected, while vertical structure changes of moisture and diabatic heating lead to negative but secondary contributions to the sensitivity, reducing the rate of increase.

Canola Responses to Drought, Heat, and Combined Stress: Shared and Specific Effects on Carbon Assimilation, Seed Yield, and Oil Composition

Photosynthetic assimilation is remarkably altered by heat and drought, and this depends on the individual or combined occurrence of stressors and their respective intensities and durations. Abiotic stressors may also alter the nutritional quality and economic value of crops. In this controlled greenhouse study, we evaluated the response of Brassica napus L., from flowering to seed development, to two temperature and water treatments and a combination of these treatments. The diffusional limitations of stomatal conductance and mesophyll conductance on photosynthesis, as well as resource-use efficiency (particularly water and nitrogen), were assessed. In addition, the effects of stressors on the seed fatty acid content and composition and the total protein content were examined. The results showed that the reduction in the net photosynthetic assimilation rate was caused by combinations of heat and drought (heat + drought) treatments, by drought alone, and, to a lesser extent, by heat alone. The stomatal conductance decreased under drought and heat + drought treatments but not under heat. Conversely, the mesophyll conductance was reduced significantly in the plants exposed to heat and heat + drought but not in the plants exposed to drought alone. The carboxylation efficiency rate and the electron transport rate were reduced under the heat treatment. The seed yield was reduced by 85.3% under the heat treatment and, to a lesser extent, under the drought treatment (31%). This emphasizes the devastating effects of hotter weather on seed formation and development. Seed oil content decreased by 52% in the plants exposed to heat, the protein content increased under all the stress treatments. Heat treatment had a more deleterious effect than drought on the seed oil composition, leading to enhanced levels of saturated fatty oils and, consequently, desaturation efficiency, a measure of oil frying ability. Overall, this study showed that except for the photosynthetic assimilation rate and stomatal conductance, heat, rather than drought, negatively affected the photosynthetic capacity, yield, and oil quality attributes when imposed during the flowering and silique-filling stages. This result highlights the necessity for a better understanding of heat tolerance mechanisms in crops to help to create germplasms that are adapted to rapid climate warming.

Effects of Northern Hemisphere Atmospheric Blocking on Arctic Sea Ice Decline in Winter at Weekly Time Scales

In this study, the effects of the Northern Hemisphere atmospheric blocking circulation on Arctic sea ice decline at weekly time scales are examined by defining four key regions based on observational data analysis. Given the regression analysis, the frequently occurring atmospheric patterns related to the sea ice decline in four key sea regions (Baffin Bay, Barents-Kara Seas, Okhotsk Sea and Bering Sea) are found to be Greenland blocking (GB), Ural blocking (UB), western Pacific blocking (PB-W) and eastern Pacific blocking (PB-E), respectively. The results show that the regional blocking frequency is higher (lower) in lower (higher) sea ice winters for each key region. Moreover, composite analysis indicates that blocking evolution is usually accompanied by significant sea ice decline at weekly time scales during the blocking life cycle for each key region. In addition, the intensified surface downward infrared radiation (IR) anomaly and the precipitable water for the entire atmosphere (PWA) in each key region are found to make significant contributions to the positive surface air temperature (SAT) anomaly, which is beneficial for the reduction in sea ice. The approximate quantitative analysis of different surface energy fluxes induced by blocking is also applied. Further analysis shows that the blocking event and the associated changes in SAT and radiation anomalies for each key region lead the sea ice decline by approximately 3~6 days. This result indicates that regional blocking can contribute to regional sea ice decline at weekly time scales through surface warming associated with enhanced water vapor and associated IR variations. Further quantitative estimates indicate that regional blocking can reduce regional sea ice cover (SIC) by 49.6%, 49.4%, 52.2% and 49.5% for Baffin Bay, Barents-Kara Seas, Okhotsk Sea and Bering Sea, respectively, during the blocking life cycle. Finally, a physical process diagrammatic sketch is given to illustrate how blocking affects SIC decline.

Monthly and annual temperature extremes and their changes on the Tibetan Plateau and its surroundings during 1963-2015

In this study, the spatiotemporal distributions of monthly and annual temperature minima (T_min) and maxima (T_max), extreme T_min and T_max, the highest (lowest) T_min (T_max), frost day (FD), icing day (ID), summer day (SD) and tropical night (TR) at 112 stations and over the ten large river basins on the Tibetan Plateau and its surroundings (TPS) during 1963–2015 are examined. Mann-Kendall test is applied for the trends. The analyses show: the northwest experiences the hottest summer while the central TPS has the coldest winter and most frequent frost and icing days. The northwest (southeast) features the highest (lowest) monthly extreme temperature ranges. The northwest has the most frequent hot summer days, whereas the southeast has the least frequent frost and icing days. The entire TPS displays few tropical nights. Most stations show positive trends for all monthly and annual T_min and T_max variables. February displays the most positive trends for both monthly T_min and T_max variables while April shows the highest number of stations with decreasing trends in monthly T_max. The trends of FD and ID are negative, whereas the trends of SU and TR are positive. Over river basins, the trends of monthly T_min are all positive and statistically significant and the trends of monthly T_max are all positive except for one negative trend and around 1/3 of the positive trends are statistically significant. Relatively larger increases in monthly T_min and T_max are noted for the cold season than the warm. The monthly and annual T_min variables increase more than T_max variables.

Projected climate and agronomic implications for corn production in the Northeastern United States

Corn has been a pillar of American agriculture for decades and continues to receive much attention from the scientific community for its potential to meet the food, feed and fuel needs of a growing human population in a changing climate. By midcentury, global temperature increase is expected to exceed 2°C where local effects on heat, cold and precipitation extremes will vary. The Northeast United States is a major dairy producer, corn consumer, and is cited as the fastest warming region in the contiguous U.S. It is important to understand how key agronomic climate variables affect corn growth and development so that adaptation strategies can be tailored to local climate changes. We analyzed potential local effects of climate change on corn growth and development at three major dairy locations in the Northeast (Syracuse, New York; State College, Pennsylvania and Landisville, Pennsylvania) using downscaled projected climate data (2000-2100) from nine Global Climate Models under two emission pathways (Representative Concentration Pathways (RCP) 4.5 and 8.5). Our analysis indicates that corn near the end of the 21st century will experience fewer spring and fall freezes, faster rate of growing degree day accumulation with a reduction in time required to reach maturity, greater frequencies of daily high temperature ≥35°C during key growth stages such as silking-anthesis and greater water deficit during reproductive (R1-R6) stages. These agronomic anomalies differ between the three locations, illustrating varying impacts of climate change in the more northern regions vs. the southern regions of the Northeast. Management strategies such as shifting the planting dates based on last spring freeze and irrigation during the greatest water deficit stages (R1-R6) will partially offset the projected increase in heat and drought stress. Future research should focus on understanding the effects of global warming at local levels and determining adaptation strategies that meet local needs.

Climate change impact assessment on the hydrological regime of the Kaligandaki Basin, Nepal

The Hindu Kush-Himalayan region is an important global freshwater resource. The hydrological regime of the region is vulnerable to climatic variations, especially precipitation and temperature. In our study, we modelled the impact of climate change on the water balance and hydrological regime of the snow dominated Kaligandaki Basin. The Soil and Water Assessment Tool (SWAT) was used for a future projection of changes in the hydrological regime of the Kaligandaki basin based on Representative Concentration Pathways Scenarios (RCP 4.5 and RCP 8.5) of ensemble downscaled Coupled Model Intercomparison Project's (CMIP5) General Circulation Model (GCM) outputs. It is predicted to be a rise in the average annual temperature of over 4°C, and an increase in the average annual precipitation of over 26% by the end of the 21st century under RCP 8.5 scenario. Modeling results show these will lead to significant changes in the basin's water balance and hydrological regime. In particular, a 50% increase in discharge is expected at the outlet of the basin. Snowmelt contribution will largely be affected by climate change, and it is projected to increase by 90% by 2090.Water availability in the basin is not likely to decrease during the 21st century. The study demonstrates that the important water balance components of snowmelt, evapotranspiration, and water yield at higher elevations in the upper and middle sub-basins of the Kaligandaki Basin will be most affected by the increasing temperatures and precipitation.