Occurrence Of Extreme Climate Events Research Articles

Climatic impacts induced by winter wheat irrigation over North China simulated by the nonhydrostatic RegCM4.7

Quantification of the impact of winter wheat irrigation on the climate and the occurrence of extreme climatic events over North China is crucial for regional adaptation planning. Previous related studies mainly focused on the impact on surface processes; however, few focused on the effects of extreme events using high-resolution nonhydrostatic regional climate models. Here, the 9-km-resolution nonhydrostatic RegCM4.7 was coupled with a crop irrigation scheme and an updated winter wheat irrigation dataset to better simulate irrigation effects. Two experiments were conducted with and without winter wheat irrigation to isolate the effects of irrigation. Results showed that irrigation simulation reduces the model biases in temperature, precipitation, latent heat flux, soil moisture, sensitive heat flux, and top-layer soil moisture. Moreover, it also reduces the bias and increases the correlation with observations obtained in irrigated areas, especially in summer, indicating better representation of irrigation schemes. Winter wheat irrigation tends to cause substantial cooling of the local surface maximum, minimum, and mean air temperatures (by −1.68, −0.34, and −0.79 °C, respectively) over irrigated areas of North China, with the largest changes observed in relation to maximum temperature. Additionally, precipitation is found to increase during spring and summer, which is strongly related to water vapor transport in the lower levels of the atmosphere. Further analyses indicated that the number of annual mean hot days decrease (−13.9 d), whereas the number of both comfort days (+10.2 d) and rainy days (days with total precipitation greater than 1 mm: +6.6 d) increase over irrigated areas, demonstrating beneficial feedback to human perception and agriculture. Fortunately, although the heat wave risk increases (number of annual mean heat wave days: +5.8 d), the impact is limited to small areas within irrigated region. Additionally, no notable change was found in terms of heavy rainfall events and precipitation intensity, which might be an undereastimation caused by the less water use in model simulation. Although winter wheat irrigation does not have notable impact on the climate of the surrounding region, it is an important factor for the local-scale climate.

Spatial-Temporal Dynamic Evolution of Land Deformation Driven by Hydrological Signals around Chaohu Lake.

The frequent occurrence of extreme climate events has a significant impact on people's lives. Heavy rainfall can lead to an increase of regional Terrestrial Water Storage (TWS), which will cause land subsidence due to the influence of hydrological load. At present, regional TWS is mostly obtained from Gravity Recovery and Climate Experiment (GRACE) data, but the method has limitations for small areas. This paper used water level and flow data as hydrological signals to study the land subsidence caused by heavy rainfall in the Chaohu Lake area of East China (June 2016-August 2016). Pearson's correlation coefficient was used to study the interconnection between water resource changes and Global Navigation Satellites System (GNSS) vertical displacement. Meanwhile, to address the reliability of the research results, combined with the Coefficient of determination method, the research findings were validated by using different institutional models. The results showed that: (1) During heavy rainfall, the vertical displacement caused by atmospheric load was larger than non-tidal oceanic load, and the influence trends of the two were opposite. (2) The rapidly increasing hydrologic load in the Chaohu Lake area resulted in greater subsidence displacement at the closer CORS station (CHCH station) than the more distant CORS station (LALA station). The Pearson correlation coefficients between the vertical displacement and water level were as high as -0.80 and -0.64, respectively. The phenomenon confirmed the elastic deformation principle of disc load. (3) Although there was a systematic bias between the different environmental load deformation models, the deformation trends were generally consistent with the GNSS monitoring results. The average Coefficients of determination between the different models and the GNSS results were 0.63 and 0.77, respectively. The results demonstrated the effectiveness of GNSS in monitoring short-term hydrological load. This study reveals the spatial-temporal evolution of land deformation during heavy rainfall around Chaohu Lake, which is of reference significance for water resource management and infrastructure maintenance in this area.

Mountain agropastoralism: traditional practices, institutions and pressures in the Indian Trans-Himalaya of Ladakh

Animal husbandry of agropastoral communities in the mountainous region of Leh, Ladakh, has been transformed in response to socio-economic and geo-political changes. This study investigates the current state of agropastoralism in the Trans-Himalaya of Leh, Ladakh, focusing on two objectives: understanding grazing management practices and examining socio-environmental factors affecting traditional pastoral livelihoods. Through a mixed-methods approach, including interviews and focus group discussions, this study explores resource utilisation patterns and decision-making processes within local communities and institutions based on a comparative approach in three pastoral areas of Ladakh. The resource utilisation pattern differs from village to village as a response to meet seasonal fodder demands; accordingly, high-altitude pastures are assessed in winter and/or summer seasons. Key stresses to the perpetuation of traditional pastoral knowledge include livelihood diversification, increasing dependence upon exogenous food production system and diminishing significance of traditional livelihood practices with improved connectivity, higher education aspirations and development of tourism and military services. Broadly, changes could be perceived from the abandonment of regular seasonal migration to pasturelands, in livestock composition and size and the decreasing number of households practising animal herding. Apart from socio-economic and developmental pressures, pastoral practices are simultaneously threatened by wild predators as well as by global warming-induced occurrence of extreme climatic events and pest attacks. While pastoral practices are carried on by a limited number of households in the three detailed study sites, knowledge pertaining to resource management, pastureland system and grazing pattern is still intact considering the resource seasonality and range of social and environmental pressures the region experiences. Ladakh’s agropastoral practices, rooted in local ecological knowledge, face challenges from socio-economic changes, risking climate resilience, ecosystem degradation, cultural loss and food security for agropastoral communities and broader societal contexts. Thus, it becomes vital to safeguard these indigenous livelihood practices and to promote a participatory approach to enhance capacity building for the continuation of the practice, which could contribute to local economies in areas with similar socio-environmental settings.

Impacts of marine cloud brightening scheme on climatic extremes in the Tibetan Plateau

Abstract As an ecologically fragile plateau and major water source in Asia, the Tibetan Plateau (TP) has grown warmer over recent decades, contributing to frequent occurrence of extreme climate events. It is urgently needed to find a suitable option to mitigate climate change impacts in the TP. The marine cloud brightening (MCB) scheme is proposed to mitigate global warming through the increasing cloud droplet number concentration of low marine clouds to reflect some solar radiation back into space. Until now, impacts of MCB scheme on the TP have not been investigated. In this study, we utilized 13 Expert Team on Climate Change Detection and Indices to assess the evolution of climate extremes over the TP with/without MCB implementation. We found that although the MCB is implemented over ocean only, it would cause significant changes on climate extremes in the TP which is very far from oceans and much higher than sea level. During 2030–2059, MCB implementation can decrease warm temperature extremes, leading to a significant decrease in the TXx index by 6–18°C, the TX90p index by 15–45 days, and the TN90p index by 15–50 days. MCB implementation would also have some cooling effects on cold temperature extremes, leading to an increase in the ID index by 30–80 days, the TX10p index by 22–32 days, and the TN10p index by about 12 days and a decrease in the TNn index by 0.5–1.5°C. Although MCB implementation would not have much impacts on precipitation extremes, it would significantly increase the area of the region with <10% drought frequency, and increase the drought intensity in the west of Lhasa city.

Impact of Climate Change on the Major Eco-Hydrological Parameters in the Dongting Lake Basin

Quantifying the impacts of climate change on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin is essential for assessing water scarcity and implementing sustainable development strategies. Premised on actual measurements and remote sensing data from 47 stations, the impact of climate change on eco-hydrological parameters in the Dongting Lake Basin was analyzed in the present study using the BESS model (The Breathing Earth System Simulator), ridge regression analysis, stepwise regression model and time-lag analysis. The results reveal that: (1) the Dongting Lake Basin has been warm and arid over the last four decades, with the frequent occurrence of extreme climate events. Vegetation carbon sequestration capacity exhibited a slightly upward trend with 0.0081 g C m−2 d−1/year from 2000–2017. ET changed with rates of −3.309 mm/year, with possible risk conflicts between water demand and supply in the future. (2) The increasing temperature was the main driver of ET enhancement in the Dongting Lake Basin. Meanwhile, both temperature and precipitation were found to be the dominant drivers of GPP enhancement. The effect of temperature on GPP was found to be greater in the areas covered by crops and tree vegetation, and natural vegetation was more strongly influenced by precipitation than radiation. (3) Extreme temperature events have had a significant impact on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin. Specifically, the cold index in extreme temperature events was found to significantly affect ET, while the heat index in extreme temperature events significantly affected GPP. Additionally, both ET and GPP were found to respond to extreme precipitation events in the region. The results of the study established that vegetation is highly sensitive to temperature, especially temperature extremes, and that precipitation also has a stressful effect. Increasing temperatures and precipitation within a range benefit vegetation productivity. (4) In the Dongting Lake Basin, we found that different climatic factors produced different time lag effects on GPP and ET by time lag analysis. This study highlights the lag effects of climate factors and extreme climate events on eco-hydrological parameters. We suggest incorporating the effects into simulation models of eco-hydrological parameters. This will lead to a better understanding of the variation of eco-hydrological parameters under climate change.

Projected changes in extreme climate events over Africa under 1.5[formula omitted], 2.0[formula omitted] and 3.0[formula omitted] global warming levels based on CMIP6 projections

The ongoing global warming is projected to persist throughout the entire century if effective mitigation measures are not put in place. The warming is associated with occurrence of extreme climate events that are prone over Africa. This study uses model data from 24 CMIP6 modeling centers to investigate future changes in extreme climate events over Africa under 1.5 °C, 2.0 °C and 3.0 °C global warming levels (GWLs). The amplified impact in extreme climate events by additional is computed relative to GWL1.5 °C. The models generally simulate observed climate extremes well, with the ensemble mean minimizing data uncertainties. The entire continent is projected to get warmer with the Sahara, Kalahari and parts of the Mediterranean depicting relatively higher temperatures. Both Rx1day and Rx5day are projected to increase over the continent except for the northern and southern regions of the continent. Rx5day is projected to increase by 4–10% for GWL1.5 and GWL3.0 °C. In comparison, an additional 0.5 °C warming between GWL2.0 °C and GWL1.5 °C will lead to an increase of about 43% impact for the climate extremes. An additional GWL1.5 °C (GWL3.0 °C) could result in about 68% increment in climate extremes. The amplified impact of global warming will result in devastating socioeconomic impacts over Africa. This stresses the need of formulating and implementing more ambitious climate change mitigation measures in effort to limit global warming to 1.5 °C.

Heat waves accelerate the spread of infectious diseases

COVID-19 pandemic appeared summer surge in 2022 worldwide and this contradicts its seasonal fluctuations. Even as high temperature and intense ultraviolet radiation can inhibit viral activity, the number of new cases worldwide has increased to >78% in only 1 month since the summer of 2022 under unchanged virus mutation influence and control policies. Using the attribution analysis based on the theoretical infectious diseases model simulation, we found the mechanism of the severe COVID-19 outbreak in the summer of 2022 and identified the amplification effect of heat wave events on its magnitude. The results suggest that approximately 69.3% of COVID-19 cases this summer could have been avoided if there is no heat waves. The collision between the pandemic and the heatwave is not an accident. Climate change is leading to more frequent extreme climate events and an increasing number of infectious diseases, posing an urgent threat to human health and life. Therefore, public health authorities must quickly develop coordinated management plans to deal with the simultaneous occurrence of extreme climate events and infectious diseases.

An Overview of Extreme Years in Quercus sp. Tree Ring Records from the Northern Moldavian Plateau

In this study, we made use of a regional oak tree-ring network from six stands that cover the northern Moldavian Plateau (eastern Europe) to analyze how different tree ring parameters (i.e., early wood tree-ring width, late wood tree-ring width, and total tree-ring width) of Quercus sp. are influenced by the occurrence of extreme climatic events (e.g., long-lasting drought events). In order to explore the influence of extreme hydroclimatic events on tree ring width, we have selected each of the six most extreme positive and negative years of tree growth and addressed the seasonal cycle of tree growth in comparison with the main climatic parameters, then evaluated both the current and lagged consequences of extreme hydroclimatic events on tree ring width and the capacity of trees to recover. Our results indicate that the variability of oak tree ring width from the Moldavian Plateau is mainly influenced by the availability of water resources, and that an important limiting growth factor for Quercus sp. is the occurrence of long-lasting drought events, e.g., at least two years in a row with severe drought conditions.

Multi-annual predictions of the frequency and intensity of daily temperature and precipitation extremes

The occurrence of extreme climate events in the coming years is modulated by both global warming and internal climate variability. Anticipating changes in frequency and intensity of such events in advance may help minimize the impact on climate-vulnerable sectors and society. Decadal climate predictions have been developed as a source of climate information relevant for decision-making at multi-annual timescales. We evaluate the multi-model forecast quality of the CMIP6 decadal hindcasts in predicting a set of indices measuring different characteristics of temperature and precipitation extremes for the forecast years 1–5. The multi-model ensemble skillfully predicts the temperature extremes over most land regions, while the skill is more limited for precipitation extremes. We further compare the prediction skill for these extreme indices to the skill for mean temperature and precipitation, finding that the extreme indices are predicted with lower skill, particularly those representing the most extreme days. We find only small and region-dependent improvements from model initialization in comparison to historical forcing simulations. This systematic evaluation of decadal hindcasts is essential when providing a climate service based on decadal predictions so that the user is informed on the trustworthiness of the forecasts for each specific region and extreme event.

Herders' adaptation strategies and animal husbandry development under climate change: A panel data analysis

The frequent occurrence of extreme climate events has become an indisputable fact. However, the role of adaptation to extreme climate change in the development of livestock husbandry is still insufficiently understood. This study empirically analyzed the impact of herders' adaptation strategies to extreme drought on livestock husbandry development and aimed to explore the optimal grassland management path under continuous climate change. A panel dataset of surveyed herders from the Xilingol League, a traditional pastoral area in China, was used. The results indicated that the average frequency of extreme drought in the Xilingol League from 1980 to 2020 was 4.94 months/year, and the occurrence of extreme drought showed a slightly upward trend. The average technical efficiency of livestock husbandry was 0.721, which can still be improved. Hay purchases can effectively promote livestock technical efficiency (p<0.01) and is the main adaptation strategy of herders to extreme drought. Further analysis showed that non-farming and pastoral employment has a positive regulatory effect in the impact of purchased hay on livestock technical efficiency. The results of this study deepen the understanding of effective adaptation to extreme weather events in pastoral areas due to climate change and provide useful information to policymakers engaged in grassland management.

Stable background tree mortality in mature and old-growth forests in western Washington (NW USA)

Increasing rates of tree mortality have been observed in recent decades for all major forest types worldwide. Elevated mortality has been linked to drought and high temperatures resulting from human modification of the atmosphere and climate. Older forests in the Pacific Northwest are globally significant as carbon sinks and may serve as refugia in the face of wildfires and climate change. We examined temporal patterns of tree mortality in mature and old-growth forests in national park units in western Washington, U.S.A, over the period 2008 to 2018, to evaluate whether the broader pattern of increasing tree mortality applies there. We also used individual-tree models of mortality to seek links between drought and tree mortality, while considering processes internal to forest stands such as competition. The annualized rate of tree mortality for the entire period generally did not exceed the expected, background rate of 1 %. The mean was ≤ 1.0 % for saplings (2.5 to 12.6 cm dbh) for 60 % of plots, for small trees (12.7 to 76.1 cm dbh) for 66 % of plots, and for large trees (greater than76.1 cm dbh) for 92 % of plots. 95 % confidence intervals wholly exceeded 1.0 % yr−1 only for small size classes in a minority of plots (saplings, 7 % of plots, and small trees, 11 % of plots). Comparing the first and second 5-year segments of the observation period, there were no clear trends of increasing mortality for any of the size classes. We tested generalized linear mixed-effects models based on the Gompit link function, using predictive factors related to drought, tree-to-tree competition, individual tree vigor, and tree species shade tolerance. We found only an index of tree vigor to consistently predict probability of tree mortality. In one model, anomaly of vapor pressure deficit in winter months was significant, but the sign of the effect did not implicate drought (i.e., mortality probability increased with moisture). These results show that, at least up to 2018, healthy trees within old-growth, protected forests in the Pacific Northwest may be resilient to current climatic changes, highlighting the importance of continued conservation and protection of these increasingly rare ecosystems and carbon stores. The occurrence of extreme climatic events following our study period emphasizes the need for continued observation and analysis to facilitate management for protection of refugia and migration corridors.

Climate Change Vulnerability Assessment in Mangrove-Dependent Communities of Manoka Island, Littoral Region of Cameroon.

This study was conducted on Manoka Island (Littoral Region of Cameroon) with the aim of analyzing climate change vulnerability and local adaptation strategies based on the local community's perceptions and biophysical evidence. We used household surveys, focus group discussions, field observation, GIS, and remote sensing to collect data on variables of exposure, sensitivity, and adaptive capacity. Historical changes in rainfall and temperature, mangrove cover, and the occurrence of extreme climatic events were used as indicators of exposure. Property losses and income structure were used as indicators of sensitivity, while human, natural, social, financial, and physical assets represented adaptive capacity. 89 households were interviewed in the nine settlements of the island. Results show that Manoka Island is experiencing irregular rainfall patterns (with average annual values deviating from the mean by −1.9 to +1.8 mm) and increasing temperature (with annual values deviating from the mean by −1.2 to +3.12). The dynamics of the coastline between 1975 and 2017 using EPR show average setbacks of more than ±3 m/year, with erosion levels varying depending on the period and location. The number of households perceiving extreme climatic events like seasonal variability, flood, and rain storm was higher. From respondents' perception, housing and health are the sectors most affected by climate change. The reported high dependence of households on fishing for income, their overall low livelihood diversification, and their poor access to climate information reported by 65% of respondents portray their poor adaptive capacity. Local response initiatives are ineffective and include among others constructing buildings on stilts and using car wheels to counter the advancement of seawater inland. The study concludes that households on Manoka Island are vulnerable to the impacts of climate change. Income diversification, mangrove reforestation, the development of sustainable supply chains for wood fuel, and sustainable fish smoking devices are the main pathways for adaptation planning in this area.

Estimation of Flood Risk on a residential mortgages portfolio

In the context of the rapid changes that have occurred in recent years, characterized by veritable 'black swans' such as the COVID-19 pandemic and extreme weather events that are occurring with increasing frequency, the issue of climate change has come into the focus of banking regulators and supervisors. Therefore banking institutions, if they are subject to the Single Supervisory Mechanism, have been called upon to develop (and, subsequently, to integrate into their business practices) methodologies for the identification, quantification and management of such risks, mainly under the profiles of: - Transition Risk, associated with policies undertaken by governments to foster climate change mitigation and adaptation; - Physical Risk, associated with the occurrence of extreme climatic events and its impact on the bank's assets. This paper analyzes one of the most significant hazards within the Physical Risk domain, which is Flood Risk. The measurement is focused on the prospective evolution of the flood events on a portfolio of mortgages secured by residential properties. The impact of this risk driver is subsequently reflected through the movement of appropriate transmission mechanisms on the LGD and PD parameters relating to the exposures in the scope. Finally, the effect on loan adjustments is provided, by recalculating the expected losses that result from the stressed projections. The flood risk projection is executed on a long-term timeframe, developing over 3 climate scenarios up to 2050. The choice of this hazard is due to its relevance in terms of frequency of events and harmfulness, a relevance that is confirmed by its inclusion in both the top-down climate stress testing exercises carried out by the ECB and in the bottom-up climate stress testing exercise promoted by the ECB itself in 2022 and carried out by the SSM Banks. A comprehensive simulation framework, structured as follows, is then presented: - a macro-climate scenario simulation engine; - the downscaling of these scenarios to obtain localized climate effects on individual properties; - the transmission of these effects into a depreciation formula for the individual property; - the LGD stress associated with the devaluation of the collateral property, and the PD stress that goes along with it, obtained by correlation.

Climatic legacy effects on the drought response of the Amazon rainforest.

Extreme precipitation and drought events are predicted to become more intense and more frequent over the Amazon rainforest. Because changes in forest dynamics could prompt strong feedback loops to the global climate, it is of crucial importance to gain insight into the response of tropical forests to these recurring extreme climatic events. Here, we evaluated the Amazon forest stability (resistance and resilience) to drought in the context of past dry and wet climatic events using MODIS EVI satellite imagery and cumulative water deficit anomalies. We observed large spatial differences in the occurrence of extreme climatic events from 1980 to 2019, with an increase in drought frequency in the central and northern Amazon and drought intensity in the southern Amazon basin. An increasing trend in the occurrence of wet events was found in the western, southern, and eastern Amazon. Furthermore, we found significant legacy effects of previous climatic events on the forest drought response. An extreme drought closely preceding another drought decreased forest resilience, whereas the occurrence of a recent drier-than-usual event also decreased the forest resistance to later droughts. Both wetter-than-usual and extreme wet events preceding an extreme drought increased the resistance of the forest, and with similar effects sizes as dry events, indicating that wet and dry events have similarly sized legacy effects on the drought response of tropical forests. Our results indicate that the predicted increase in drought frequency and intensity can have negative consequences for the functioning of the Amazon forest. However, more frequent wet periods in combination with these droughts could counteract their negative impact. Finally, we also found that more stable forests according to the alternative stable states theory are also more resistant and resilient to individual droughts, showing a positive relationship between the equilibrium and non-equilibrium stability dynamics.

Seasonal forecast of the percentage of days with extreme temperatures in central-northern Argentina: An operational statistical approach

Several socio-economic sectors are sensitive to the occurrence of extreme climate events. The ability to predict these extremes will allow precautionary measures to reduce their impacts. This work aims to disseminate a seasonal statistical forecast of daily temperature extremes in Argentina to the international scientific community. At the local level, this forecast is shared at monthly meetings organized by the Argentine National Meteorological Service and attended by different users. For the temperature extremes modeling, several predictors and statistical techniques were applied. We estimated the probability of each tercile category (above-normal, near-normal, and below-normal) by quantifying the percentage of models that predict each of them. The forecasts were verified by calculating different metrics. In general, we observed that the forecast system has less skill to discriminate the near-normal category in all seasons, and the other categories present a skill highly variable according to the season, region, and extreme index. The verification process revealed that predictability increases for all extreme indices with a previous La Niña phase. This product represents an advance towards an operational seasonal forecast of extreme temperatures in Argentina because it offers predictions based on a detailed study of predictors in the region, the incorporation of multiple statistical methodologies, and the predicted variables are not the most typical ones offered by forecasting centers. Finally, it is highlighted that the accuracy rate obtained with this product exceeds a forecast based on climatology, i.e., despite the uncertainties, our forecasts provide additional information to users for decision making.

Integration of Light and Auxin Signaling in Shade Plants: From Mechanisms to Opportunities in Urban Agriculture.

With intensification of urbanization throughout the world, food security is being threatened by the population surge, frequent occurrence of extreme climate events, limited area of available cultivated land, insufficient utilization of urban space, and other factors. Determining the means by which high-yielding and high-quality crops can be produced in a limited space is an urgent priority for plant scientists. Dense planting, vertical production, and indoor cultivation are effective ways to make full use of space and improve the crop yield. The results of physiological and molecular analyses of the model plant species Arabidopsis thaliana have shown that the plant response to shade is the key to regulating the plant response to changes in light intensity and quality by integrating light and auxin signals. In this study, we have summarized the major molecular mechanisms of shade avoidance and shade tolerance in plants. In addition, the biotechnological strategies of enhancing plant shade tolerance are discussed. More importantly, cultivating crop varieties with strong shade tolerance could provide effective strategies for dense planting, vertical production, and indoor cultivation in urban agriculture in the future.

近60年来印江河流域极端气候演变及其对净初级生产力和归一化植被指数的影响

极端气候事件的发生改变了区域水热条件，并影响着生态环境变化。然而，目前长时间尺度上极端气候的演变规律及其对生态环境的影响尚不明晰。采用Mann-Kendall趋势及突变检验法、连续小波变换和Hurst指数法揭示了喀斯特槽谷印江河流域极端气候的变化趋势、突变时间、周期性特征和未来演变规律，并利用Lindeman-Merenda-Gold模型定量评估了极端气候溶变对生态环境变化的影响。结果表明：（1）印江河流域极端气温显著上升，降雨量增多，呈现湿热多雨的气候特征。未来极端气温事件持续等级将更高，持续强度也更强。（2）同类型极端气候具有潜在的关联性，但不同类型极端气候间的影响较小，且多呈负相关。（3）印江河流域平均净初级生产力（NPP）和归一化植被指数（NDVI）在2000-2015年间呈现相反的变化趋势，NPP平均值为598.53 g C m^-2 a^-1，平均减少速率为-3.32 g C m^-2 a^-1。NDVI平均值为0.59，平均增长速率为0.0013/a。（4）冷持续指数（CSDI）、平均温差（DTR）、系统阈值结冰日数（ID6.4）和生长期长度（GSL）对NPP的贡献较大，贡献率分别12.64%、11.50%、11.05%和7.4%。其中，CSDI、DTR、GSL对NPP变化表现为负贡献，而ID6.4则表现为正贡献。大部分极端气候指数对NPP变化的贡献都不超过5%。ID6.4对NDVI变化的影响最大，暖夜日数（TN90p）、热持续指数（WSDI）和暖昼日数（TX90p）相对次之，贡献率分别为13.67%、13.54%、12.95%和10.02%。总体上看，在2000-2015年间，印江河流域湿热多雨的气候对NDVI增长有促进作用，但是由于气温升高和降雨量增加的原因，对NPP累积产生了较大的负面影响。研究结果可为喀斯特槽谷流域气候预测、水资源管理及生态环境恢复提供参考依据。;The occurrence of extreme climate events has changed the regional hydrothermal conditions and affected the changes of ecological environment. However, at present, the evolution of extreme climate and its impact on ecological environment are unclear. Therefore, the methods of Mann-Kendall test, continuous wavelet transform, and Hurst exponent were applied to analyze the change trend, abrupt time, periodicity and future evolution of extreme climate events in Yinjiang River basin. Then, the Lindeman-Merenda-Gold model was used to quantitatively evaluate the impacts of extreme climate events to ecological environment change. The results were obtained:(1) The extreme temperature events in the Yinjiang River basin increased significantly, and the rainfall also increased, showing a hot and rainy climate. In the future, the level of extreme temperature events will be higher and the intensity will be stronger; (2) The same type of extreme climate had a potential correlation, but the influence of different types of extreme climate was small, and most of them showed negative correlation; (3) The average net primary production (NPP) and normalized difference vegetation index (NDVI) of the Yinjiang River basin showed an opposite trend from 2000 to 2015. The average NPP was 598.53 g C m^-2 a^-1 with the average reduction rate of -3.32 g C m^-2 a^-1 while the average NDVI value was 0.59 with an average growth rate of 0.0013/a; (4) The cold spell duration indicator(CSDI), diurnal temperature range (DTR), icing days defined by system threshold (ID6.4), and growing season length (GSL) contributed significantly to NPP, with contributions of 12.64%, 11.50%, 11.05%, and 7.4%, respectively. Among them, the CSDI, DTR, and GSL showed negative contribution to NPP changes, while ID6.4 showed positive contribution. Most extreme climate indices contributed less than 5% to the NPP changes. ID6.4 had the greatest impact on NDVI, followed by warm nights (TN90p), warm spell duration indicator (WSDI), and warm days (TX90p), with contribution rates of 13.67%, 13.54%, 12.95%, and 10.02%, respectively. On the whole, the study stressed that the hot and rainy climate in the Yinjiang River basin promoted the growth of NDVI during 2000-2015, but caused a significantly negative impact on the accumulation of NPP due to the increase of temperature and rainfall. The results can provide reference for climate prediction, water resources management and ecological environment restoration in a basin of karst trough valley.

陕西省植被覆盖时空变化及其对极端气候的响应

基于2001-2018年MODIS NDVI数据，从生态分区视角分析陕西省归一化植被指数（NDVI）的时空变化特征，并结合该地区31个气象站点日值数据，探讨NDVI对极端气温和极端降水指数的响应特征。结果表明：（1）陕西省及其各生态区的NDVI变化均显著上升，整体呈南高北低的分布特点，其中秦巴山地落叶与阔叶林生态区（IV）NDVI值最高为0.86，陕北北部典型草原生态区（I）NDVI值最低为0.38。（2）年际尺度上，陕西省NDVI与极端气温暖极值（暖夜日数）和极端降水指数总体呈显著正相关（P<0.05），在陕西省北部NDVI变化主要受极端降水的影响，南部则对极端气温的敏感度更高。（3）多年月尺度上，各生态区NDVI对极端气温冷极值（最低气温、日最低气温的极低值和日最高气温的极低值）和极端气温暖极值（最高气温、日最低气温的极高值和日最高气温的极高值）存在明显的滞后性，滞后时间多为3个月；与极端降水指数（单日最大降水量和连续5日最大降水量）的滞后时间为2个月，说明陕西省内NDVI对极端气候的响应具有显著的滞后效应。;Vegetation plays an important role in the terrestrial ecosystem. Under the background of global warming, the response of vegetation cover to climate change has become an important research field. Normalized Difference Vegetation Index (NDVI) is commonly used to study the response of vegetation change to temperature and precipitation on a regional scale. In recent years, the frequent occurrence of extreme climate events has increased the risk and vulnerability of terrestrial ecosystems and endangered ecological security. Shaanxi province is located in the hinterland of China, with a large north-south span and obvious regional differences in hydrothermal conditions and surface ecological environment. Therefore, it is necessary to study the dynamic change of NDVI and its response to extreme climate, which can provide theoretical evidence of ecosystem evolution and ecological environment conservation in Shaanxi Province. Based on MODIS NDVI data from 2001 to 2018, the spatio-temporal variation pattern of NDVI was analyzed from the perspective of different ecological areas in Shaanxi Province. The response characteristics of NDVI to extreme temperature and precipitation indices were also discussed by using the daily meteorological observations from 31 stations in this region. The results showed that (1) the variation of NDVI increased significantly and the spatial difference of NDVI value was obvious in Shaanxi Province and its ecological areas. The high value of NDVI distributed in the south, whereas the low value of NDVI distributed in the north. The decreasing order of the value of NDVI of the different ecological areas was as follows:ecological region of deciduous and broad-leaved forest in Qinba Mountain (IV) > agricultural ecological area of Fenwei Basin (III) > agricultural and grassland ecological region of the Loess Plateau (II) > typical grassland ecological area in northern Shaanxi (I). Meanwhile, the lowest value of NDVI was 0.38 and the highest value was 0.86. (2) The correlation between NDVI and extreme climate indices showed that annual NDVI in each ecological area was significantly positively correlated with TN90p and extreme precipitation indices. However, extreme precipitation had an important impact on vegetation growth in the north of Shaanxi Province, and extreme temperature was the main factor in the south. (3) On the monthly scale, the NDVI had a significant lag time of 3 months with extreme temperature indices, including TMIN_mean, TN_n, TX_n, TMAX_mean, TN_x, and TX_x, while had a lag time of 2 months with extreme precipitation indexes in each ecological area. In general, the results effectively revealed the response of vegetation to climate fluctuations in Shaanxi Province.

Changes of Extreme Agro-Climatic Droughts and Their Impacts on Grain Yields in Rain-Fed Agricultural Regions in China over the Past 50 Years

Climate change and climate extremes and their impacts on agriculture, water resources, and ecosystems have become important issues globally. Agricultural sustainability and food security are facing unprecedented challenges due to the increasing occurrence of extreme climatic events, including, notably, extreme droughts in recent years in China. In this study, a threshold determination model of extreme agro-climatic droughts (EADs) was built based on the cumulative probability distribution functions (CDF) of an agricultural drought index—the consecutive days without available precipitation (CDWAP). The CDWAP was established by combining meteorological data with the characteristics of cropping patterns and the water requirement in different growing periods of crops. The CDF of CDWAP was obtained based on the relationship of CDWAP and its occurrence frequency. Based on the model, the spatial pattern of the thresholds of EADs and the threshold exceedance time series of EADs in 500 meteorological stations were obtained, and then changes in the frequencies and intensities of EADs in China and their impacts on grain yields in rain-fed regions during the past 50 years were analyzed. The results follow: (1) The threshold value of EADs in China gradually increased from southeast to northwest. The stations of the highest value were located in the Northwest China, with the CDWAP more than 60 days, while the lowest value was in the middle reaches of the Yangzi River, with the CDWAP less than 16 days. (2) The frequencies and intensities of the EADs increased mostly in the east areas of the Hu Huanyong line, which was also the main agricultural production region in China. The North China (NC) and Southwest China (SW) regions showed the highest increasing rates of the EADs; their frequencies and intensities were 11.3% and 2.2%, respectively, for the NC region, and 9.3% and 2.7%, respectively, for the SW region. (3) Case studies in the NC, SW, and SE regions indicated that there was a negative correlation between grain yields and EAD frequency and intensity; i.e., the low grain yields often occurred in the year with relatively higher frequency or/and stronger intensity of EADs. The correlation coefficients of grain yield and EAD were generally greater than that of merely extreme climatic droughts; therefore, the study of EAD is necessary when researching the impacts of extreme drought events on grain yield.

The Importance of Monitoring River Water Discharge

River discharge time series, originally recorded to anticipate floods and water scarcity, later became indispensable to design hydroelectric dams. Presently, discharge monitoring aids in detecting climatic and environmental change, because the discharge and quality of river water are functions of many climatic, biological, geological, and topographic variables coexisting in the basin. Climate change is altering the atmospheric precipitation distribution pattern-both, in time and space-as well as the occurrence of extreme climatic events. It is important the global upgrading of river gauging networks to unveil hydrological trends and changing atmospheric patterns. In so doing, discharge monitoring stations–and the resulting time series-may be, as well, invaluable in revealing the role played by significant environmental variables.