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Alpine wetlands in western Sichuan plateau (WSCP) are located on the eastern edge of the Qinghai-Tibet Plateau (QTP), where the ecological environment is very sensitive to global climate change. Being naturally driven coupled with unreasonable human development activities, alpine wetlands have experienced serious ecological and environmental issues such as drought, inversion, and desertification. However, due to the limitations of data sources and calculation models, it is impossible for us to deeply understand the change mechanism and spatial difference of the ecological environment of the alpine wetland (EEAW) in previous studies. In view of this, an innovative approach for monitoring the EEAW change has been proposed in this paper. We employ the approach to perform the EEAW change trend analysis, and some meaningful characteristics were founded. Specifically, it includes the fol1owing aspects. The air temperature increase is relatively significant, while the precipitation change has obvious spatial differentiation, and even some region's precipitation experienced a decrease especially in plot1. In Haizishan, Lugu Lake, and Bari Lake, we explored an interesting phenomenon that the precipitation increases first and then decrease, and the turning point occurred around 1999. Increases in air temperature and evaporation have aggravated the drought in high-latitude areas. The drought situation has been alleviated in high-altitude areas due to the acceleration of snow melt water. Wetland vegetation and biomass presented an overall increasing trend, but the degradation also occurs in some area, including Zoige and Lugu Lake area. The human activity disturbances of wetland degradation mainly include the settlements expansion, agricultural development, and the ecotourism prosperity. Among them, targeted poverty alleviation projects have accelerated the urbanization in WSCP, and the development of agriculture and tourism has increased the interference of wetlands. Additionally, we have used Landsat images and national wetland survey data (1999, 2013, and 2020 year) from the past two decades to verify the EEAW trend and confirm the reliability of the analysis results using this approach. [ABSTRACT FROM AUTHOR]

This paper shows the effects of changes in the spatial-temporal behavior and phase shift of climate variables on rainfed agriculture in the Lerma-Chapala-Santiago Basin in central Mexico. Specifically, changes in rainfall (R), maximum temperature (Tmax), and minimum temperature (Tmin) were analyzed over two 25-year periods (1960 to 1985 and 1986 to 2010). Climate surfaces were generated by interpolation using the thin-plate smoothing spline algorithm in the software ANUSPLIN. Climate data were Fourier-transformed and fitted to a sinusoidal curve model, and changes in amplitude (increase) and phase were analyzed. The temporal behavior (1960–2010) indicated that rainfall was the most stable variable at the monthly level and presented no significant changes. However, Tmax increased by 2°C in the final period, and Tmin increased by 0.7°C at the end of the final period. The basin was discretized into ten rainfed crop areas (RCAs) according to the extent of changes in the amplitude and phase of the climate variables. The central and southern portions (55% of the area) presented more significant changes in amplitude, mainly in Tmin and Tmax. The remaining RCAs were smaller (14.6%) but presented greater variation: the amplitude of the Tmin decreased in addition to showing a phase shift, whereas Tmax increased in addition to showing a phase shift. These results translate into a delay in the characteristic temperatures of the spring and summer seasons, which can impact the rainfed crop cycle. Additionally, rainfall showed an annual decrease of approximately 50 mm in all RCAs, which can affect the phenological development of crops during critical stages (emergence through flowering). These changes represent a significant threat to the regional economy and food security of Mexico. [ABSTRACT FROM AUTHOR]

Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events. [ABSTRACT FROM AUTHOR]

This paper examines the impact that climate change may have on the lodging of oats in the Republic of Ireland and the UK. Through the consideration of a novel lodging model representing the motion of an oat plant due to the interaction of wind and rain and integrating future predictions of wind and rainfall due to climate change, appropriate conclusions have been made. In order to provide meteorological data for the lodging model, wind and rainfall inputs are analysed using 30 years' time series corresponding to peak lodging months (June and July) from 38 meteorological stations in the United Kingdom and the Irish Republic, which enables the relevant probability density functions (PDFs) to be established. Moreover, climate data for the next six decades in the British Isles produced by UK climate change projections (UKCP18) are analysed, and future wind and rainfall PDFs are obtained. It is observed that the predicted changes likely to occur during the key growing period (June to July) in the next 30 years are in keeping with variations, which can occur due to different husbandry treatments/plant varieties. In addition, the utility of a double exponential function for representing the rainfall probability has been observed with appropriate values for the constants given. [ABSTRACT FROM AUTHOR]

Utilising climate funds properly to reduce the impact of potential risks of climate change at the local level is essential for successful adaptation to climate change. Climate change has been disrupting the lives of millions of households along the coastal region of Bangladesh. The country has allocated support from its national funds and accessed international funds for the implementation of adaptation interventions. With the focus of the scientific community on climate finance mechanisms and governance at the global and the national level, there is a lacuna in empirical evidence of how climate finance affects risk appraisal and engagement in adaptation measures at the local level. This paper aims to examine how the support from climate finance affects risk appraisal in terms of the perceived probability and severity and the factors which influence risk appraisal. A field survey was conducted on 240 climate finance recipient households (CF HHs) and 120 nonclimate finance recipient households (non-CF HHs) in Galachipa Upazila of Patuakhali District in coastal Bangladesh. The results indicate that both CF and non-CF HHs experience a high probability of facing climatic events in the future; however, CF HHs anticipated a higher severity of impacts of climatic events on different dimensions of their households. With higher income and social capital, the overall risk appraisal decreases for CF HHs. CF HHs have higher engagement in adaptation measures and social groups and maintain alternative sources of income. Climate finance played a critical role in supporting households in understanding the risks that they were facing, assisting them in exploring as well as enhancing their engagement in adaptation options. [ABSTRACT FROM AUTHOR]

Accurate remote-sensed precipitation data are crucial to the effective monitoring and analysis of floods and climate change. The Global Precipitation Measurement (GPM) satellite product offers new options for the global study of precipitation. This paper evaluates the applicability of GPM IMERG products at different time resolutions in comparison to ground-measured data. Based on precipitation data from 107 meteorological stations in the Beijing-Tianjin-Hebei region, GPM products were analysed at three timescales: half-hourly (GPM-HH), daily (GPM-D), and monthly (GPM-M). We use a cumulative distribution function (CDF) model to correct GPM-D and GPM-M products to analyse temporal and spatial distributions of precipitation. We came to the following conclusions: (1) The GPM-M product is strongly correlated with ground station data. Based on five evaluation indexes, NRMSE (Normalized Root Mean Square Error), NSE (Nash-Sutcliffe), FAR (False Alarm Ratio), UR (Underreporting Rate), and CSI (Critical Success Index), the monthly GPM products showed the best performance, better than GPM-HH products and GPM-D products. (2) The performance of GPM products in summer and autumn was better than in winter and spring. However, the GPM satellite's precision in undulating terrain was poor, which could easily lead to serious errors. (3) CDF models were successfully used to modify GPM-D and GPM-M products and improve their accuracy. (4) The range of 0–100 mm precipitation could be corrected best, but the GPM-M products were underestimated. Corrected GPM-M data in the range >100 mm were overestimated. According to this analysis, the GPM IMERG Final Run products at daily and monthly timescales have good detection ability and can provide data support for long-time series analyses in the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

The climate continentality or oceanity is one of the main characteristics of the local climatic conditions, which varies with global and regional climate change. This paper analyzes indexes of continentality and oceanity, as well as their variations in the middle and high latitudes of the Northern Hemisphere in the period 1950–2015. Climatology and changes in continentality and oceanity are examined using Conrad’s Continentality Index (CCI) and Kerner’s Oceanity Index (KOI). The impact of Northern Hemisphere teleconnection patterns on continentality/oceanity conditions was also evaluated. According to CCI, continentality is more significant in Northeast Siberia and lower along the Pacific coast of North America as well as in coastal areas in the northern part of the Atlantic Ocean. However, according to KOI, areas of high continentality do not precisely correspond with those of low oceanity, appearing to the south and west of those identified by CCI. The spatial patterns of changes in continentality thus seem to be different. According to CCI, a statistically significant increase in continentality has only been found in Northeast Siberia. In contrast, in the western part of North America and the majority of Asia, continentality has weakened. According to KOI, the climate has become increasingly continental in Northern Europe and the majority of North America and East Asia. Oceanity has increased in the Canadian Arctic Archipelago and in some parts of the Mediterranean region. Changes in continentality were primarily related to the increased temperature of the coldest month as a consequence of changes in atmospheric circulation: the positive phase of North Atlantic Oscillation (NAO) and East Atlantic (EA) patterns has dominated in winter in recent decades. Trends in oceanity may be connected with the diminishing extent of seasonal sea ice and an associated increase in sea surface temperature. [ABSTRACT FROM AUTHOR]

Atmospheric aerosols are considered to be an important constituent of Earth’s atmosphere because of their climatic, environmental, and health effects. Therefore, while studying the global climate change, investigation of aerosol concentrations and properties is essential both at local and regional levels. In this paper, we have used relatively long-term Aerosol Robotic Network (AERONET) data during September 2006–August 2014 to analyze aerosol properties such as aerosol optical depth at 500 nm (AOD), Ångström exponent (440–870 nm) (AE), refractive index (RI), and asymmetry parameter over Karachi, a coastal megacity of Pakistan. The average annual values of AOD and AE were found to be 0.48 ± 0.20 and 0.59 ± 0.29, respectively. The peak (0.88 ± 0.31) AOD was recorded in July with corresponding AE of 0.30 ± 0.22 representing reasonably higher concentration of coarse size particles over Karachi. The cluster analysis using the scatter plot between absorption AE and extinction AE revealed that desert dust prevailed in the atmosphere of Karachi in spring and summer, while biomass burning aerosols dominate in autumn and winter. The peak values of volume concentrations of coarse and fine-mode particulate matter were found in summer and autumn, respectively. Also, we found significant growing trend in single-scattering albedo with wavelength, indicating the domination of dust particles during summer and spring. The peak value of the real part of the RI was observed in spring (1.53) and modest in winter (1.50). On the contrary, the peak value of the imaginary part of the RI was observed to be constantly elevated in winter and lesser in spring. [ABSTRACT FROM AUTHOR]

This paper conducts the assimilating experiments and simulating experiments on typhoon "Aere" (No. 0418), by use of bogus data assimilation (BDA) method combined with advanced microwave sounding unit-A (AMSU-A) data assimilation method in the fifth-generation National Center for Atmospheric Research (NCAR)/Penn State Mesoscale Model Version-3 (MM5V3), the Radiative Transfer for TIROS-N Operational Vertical Sounder Version-7 (RTTOV) model, and their adjoint models. The Bogus data constructed with BDA technique are mainly located at sea level, while the peak energy contribution levels of the sounder channels selected in AMSU-A data assimilation technique are mainly located at upper troposphere. The two types of data can reconstruct the meso-scale information and improve the typhoon initial fields under themodel dynamic forcing effect, respectively from the low level and the upper level of atmosphere during the assimilating process. Numerical results show that with four-dimensional variational data assimilation (4DVAR) technique the circulation of initial fields is improved, the "warm core" of typhoon is enhanced, the "cloud water" phenomenon that occurs in the optimal initial fields and the numerical model is changed into "warm start" from "cold start". [ABSTRACT FROM AUTHOR]

This paper tries to identify one of the reasons for the poor land skin temperature simulated by a climate model over Greenland. It first compares ICEsat surface height measurements over Greenland with those used by the model and reveals that the surface height of Greenland prescribed in the National Center for Atmospheric Research (NCAR) Community Climate System Model/Community Land Model version 3 (CCSM/CLM3) differs greatly from the satellite measurements from National Aeronautics and Space Administration (NASA) ICEsat at edges and central glacier regions. This deficiency, in part, leads to underestimated skin temperatures at coastal regions-the areas where significant ice sheet melt is observed. Furthermore, sensitivity studies reveal that surface skin temperature simulations of Greenland would be significantly improved if the more accurate surface height is used. The problem of the height used in current global climate model is mainly due to the fact that the model has to use coarse grid size, and within one grid, land surface height has high heterogeneity. How to assign a proper surface height for each model grid and meanwhile adequately present the high heterogeneity of land surface is a great challenge in current model development. [ABSTRACT FROM AUTHOR]

The years 2014 and 2015 turned out to be quite catastrophic for the Asia-Pacific region which took a major toll on the socioeconomic stature of all the entities of the region. The agricultural sector which is one of the most contributing factors to the economy of the region has been highly sensitive to the global climatic changes. Hence this endeavor shall greatly help in an efficient prediction of monsoon cycles, thus enabling the hapless farmers to be better informed and avoid major losses of any kind. The paper focuses on the climatology of air temperature and MSLP with the variation pattern in precipitation over the Asia-Pacific region. The NCEP-NCAR reanalysis data is used for air temperature and MSLP along with high-resolution precipitation dataset for Asia-Pacific monsoon region obtained from GPCP. The temperature datasets are analyzed up to the level 500 hPa. Monte Carlo method of correlation and Bootstrapping method of confidence interval are used to analyze the relation of GPCP with MSLP and temperature at all defined levels. So, in this paper authors attempt to assess the nature and relationship of temperature and MSLP to precipitation over the Asia-Pacific region with the recent 10-year changes which are quantified in detail. [ABSTRACT FROM AUTHOR]

Climate change is one of the defining challenges facing the planet. Voluntary forest carbon offset project which has the potential to boost forest carbon storage and mitigate global warming has aroused the global concern. The objective of this paper is to model the game situation and analyze the game behaviors of stakeholders of voluntary forest carbon offset projects in China. A stakeholder model and a Power-Benefit Matrix are constructed to analyze the roles, behaviors, and conflicts of stakeholders including farmers, planting entities, communities, government, and China Green Carbon Foundation. The empirical analysis results show that although the stakeholders have diverse interests and different goals, a win-win solution is still possible through their joint participation and compromise in the voluntary forest carbon offset project. A wide governance structure laying emphasis on benefit balance, equality, and information exchanges and being regulated by all stakeholders has been constructed. It facilitates the agreement among the stakeholders with conflicting or different interests. The joint participation of stakeholders in voluntary forest carbon offset projects might change the government-dominated afforestation/reforestation into a market, where all participators including government are encouraged to cooperate with each other to improve the condition of fund shortage and low efficiency. [ABSTRACT FROM AUTHOR]

Global changes are driving ecosystem alterations, and the effects are becoming more and more obvious. Ecosystem management clarifies the fundamental supporting functions of ecosystems for human survival and sustainable development. Integrated ecosystem monitoring and assessment has become a popular topic of ecology study. However, many scientific questions need to be addressed, including what assessment contents and methods are optimal for temporal and spatial measurements. Therefore, the development of a scientific evaluation framework that includes certain core contents and indicators is very important. This paper proposes a regional integrated ecosystem assessment framework involving comprehensive monitoring. Satellite images are the main data source for different ecosystem and ecological parameters, and these need to be supplemented with the help of surveys or field observation data. A healthy ecosystem is the basis of human survival and sustainable development, and ecological service should be taken as the core of integrated ecosystem assessment. This is decided by the spatial distribution, classification, and patterns of regional ecosystems. That is to say, ecological service, together with ecosystems distribution and pattern, ecological problem indicators, and ecological stress, needs to be integrated analyzed and evaluated. [ABSTRACT FROM AUTHOR]

Global land use and land cover pattern has greatly changed in the past 50 years, which exerts direct or indirect influence on the climate change remarkably at both regional and global scales. Therefore, observing and estimating the land use impacts on surface climate is essential and has been continuously promoted by researchers. This paper explores the advancement in the models, data, and application for observing and estimating the land use impacts on surface climate and points out further research needs and priorities, which hopefully will provide some references for related studies. [ABSTRACT FROM AUTHOR]

There have been tremendous changes in the global land use pattern in the past 50 years, which has directly or indirectly exerted significant influence on the global climate change. Quantitative analysis for the impacts of land use and land cover changes (LUCC) on surface climate is one of the core scientific issues to quantitatively analyze the impacts of LUCC on the climate so as to scientifically understand the influence of human activities on the climate change. This paper comprehensively analyzed the primary scientific issues about the impacts of LUCC on the regional climate and reviewed the progress in relevant researches. Firstly, it introduced the influence mechanism of LUCC on the regional climate and reviewed the progress in the researches on the biogeophysical process and biogeochemical process. Then the model simulation of effects of LUCC on the regional climate was introduced, and the development from the global climate model to the regional climate model and the integration of the improved land surface model and the regional climate model were reviewed in detail. Finally, this paper discussed the application of the regional climate models in the development and management of agricultural land and urban land. [ABSTRACT FROM AUTHOR]

Effective Strength Index (ESI) is the relative strength of NAOand SO. ESI tendency is the algebraic difference between April-ESI and January-ESI and it represents the simultaneous evolution of NAO and SO from winter to spring. During positive (negative) phase of ESI tendency, NAO restores positive (negative) phase and SO restores negative (positive) phase before the beginning of summer season. Thus during contrasting phases (positive and negative) of ESI tendency, the evolution of NAO and SOis out of phase. In this paper we have studied the spatial and temporal variability of winter-time temperature field over Europe, Arabian Sea and Bay of Bengal during contrasting phases of ESI tendency. The study reveals that during positive (negative) ESI tendency, smaller (larger) region of Europe is showing significant winter-time cooling (warming) at surface. The relationship between winter-time surface temperature over above regions and Indian summer monsoon rainfall (ISMR) also shows spatial and temporal variability. The probable explanation for this change in the relationship is discussed in the paper. Two sets of temperature parameters for two different phases of ESI tendency are found out. Multiple regression equations are developed for the prediction of ISMR in each phase of ESI tendency. The performance of these equations is also discussed in this paper. [ABSTRACT FROM AUTHOR]

The detection of possible changes in extreme climate events, in terms of the frequency, intensity as well as duration assumes profound importance on the local, regional, and national scales, due to the associated critical socioeconomic consequences. Therefore, an attempt ismade in this paper to evaluate various aspects of future projections of precipitation extremes over India, as projected by a state-of-art regional climatemodeling system, known as PRECIS (Providing REgional Climates for Impacts Studies) towards the end of the 21st century (that is, 2071-2100) using standardized indices. Study reveals that PRECIS simulations under scenarios of increasing greenhouse gas concentration and sulphate aerosols indicate marked increase in precipitation towards the end of the 21st century and is expected to increase throughout the year. However the changes in daily precipitation and the precipitation extremes during summer monsoon (June through September) season are prominent than during the rest of year. PRECIS simulations under both A2 and B2 scenarios indicate increase in frequency of heavy precipitation events and also enhancement in their intensity towards the end of the 21st century. Both A2 and B2 scenarios show similar patterns of projected changes in the precipitation extremes towards the end of the 21st century. However, the magnitudes of changes in B2 scenario are on the lower side. [ABSTRACT FROM AUTHOR]

The severe heatwaves and hot spells in Vietnam were observed more frequently in intensity and duration due to global warming and climate change impacts. The hot days and extreme summer events make the weather harsh and significantly affect human health and the environment. This study presents the spatiotemporal distribution of the number of hot days (NHDs) in Vietnam. The variability of NHD in seven climate subregions is also examined in association with the large-scale drivers. The European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5) data for the period 1981–2020 are used. Principal component analysis is also applied to the observed monthly NHD to obtain spatial patterns and time series. The results show that the NHD in the Highland and South subregions from March to May is linked with the subtropical high associated with decreased 500hPa-level vertical velocity (VV500). From May to June, the North and Central subregions seem related to deepening the Asiatic low and enhancement of southwest flows across the Indochina Peninsula. Finally, both increased southwest flows and decreased VV500 can partly contribute to the intensification of NHD in the North and Central subregions during July and August. The long trends of NHD are also examined. The results reveal that the increasing trends in NHD occur in most subregions, except for the Central Highland, and changing trends of NHD in June greatly contribute to the annual trend of NHD. Finally, the examinations with the El Niño-Southern Oscillation events show that NHD is significantly higher in El Niño events than in La Niña events in March and April for the Northwest, South Central, Central Highlands, and South, in May and June for all subregions, and in July and August for only the Red River Delta subregion. This suggests that ENSO can provide the potential for improving seasonal climate forecasts and mitigating natural disaster risks for the community. [ABSTRACT FROM AUTHOR]

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources. [ABSTRACT FROM AUTHOR]

This paper reported a comprehensive analysis on the diurnal variation of the Atmospheric Boundary Layer (ABL) in summer of Badain Jaran Desert and discussed deeply the effect of surface thermal to ABL, including the Difference in Surface-Air Temperature (DSAT), net radiation, and sensible heat, based on limited GPS radiosonde and surface observation data during two intense observation periods of experiments. The results showed that (1) affected by topography of the Tibetan Plateau, the climate provided favorable external conditions for the development of Convective Boundary Layer (CBL), (2) deep CBL showed a diurnal variation of three- to five-layer structure in clear days and five-layer ABL structure often occurred about sunset or sunrise, (3) the diurnal variation of DSAT influenced thickness of ABL through changes of turbulent heat flux, (4) integral value of sensible heat which rapidly converted by surface net radiation had a significant influence on the growth of CBL throughout daytime. The cumulative effect of thick RML dominated the role after CBL got through SBL in the development stage, especially in late summer, and (5) the development of CBL was promoted and accelerated by the variation of wind field and distribution of warm advection in high and low altitude. [ABSTRACT FROM AUTHOR]

In the context of global climate change, the extent of snow cover in Siberia has significantly decreased since the 1970s, especially in spring. The changes of snow cover at middle and high latitudes have significant impacts on the meteorological and hydrological processes because the snow cover can affect the surface energy, water balance, and the development of the atmospheric boundary layer. In this paper, the temporal and spatial changes in snow cover were firstly estimated based on a long time series of remote sensing snow cover data, both showing a decreased trend. Based on this, we estimated the radiative forcing caused by the snow cover changes from the 1970s to the 2010s and compared it with the radiative forcing caused by the vegetation cover changes over the same time period in Siberia, indicating that the snow cover changes in Siberia can accelerate climate warming and the vegetation cover changes here have the opposite effect. Furthermore, the snow cover changes may play a more important role than the vegetation cover changes in regulating the surface radiation balance in Siberia on the regional scale. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

The purpose of this work is to present phenology as a valid indicator and methodology for monitoring and assessing the impact of climate change on plant-based tourist activities. Fruit-picking has become a popular rural tourism activity worldwide. However, fruit maturity dates (FMD) have been affected by climate change (CC), which has in turn profoundly affected fruit-picking tourism activities (FPTA). In this paper, phenological data on the FMD for 45 types of plants in 1980–2012, dates for more than 200 fruit-picking festivals, and data on monthly average air temperature in 1980–2013 were used to assess the impact of CC on FPTA by wavelet and correlation analyses. The findings indicated that the study area had been significantly affected by CC. Prevailing temperatures at one or three months prior have a decisive influence on FMD. Among the 11 plants directly related to FPTA, the FMD of four were significantly advanced, while 6-7 were significantly delayed owning to increased temperature. Of the 11 FPTA, only two had realized the impact of CC and had adjusted festival opening dates based on dynamic changes. However, a considerable number of festival activities remained fixed or scheduled on the weekends. [ABSTRACT FROM AUTHOR]

Global warming increases global average precipitation and evaporation, causing extreme climate and hydrological events to occur frequently. Future changes in temperature, precipitation, and runoff from 2021 to 2050 in the upper reaches of the Minjiang River were analyzed using a distributed hydrological model, the SWAT (Soil and Water Assessment Tool), under a future climate scenario. Simultaneously, future variation characteristics of extreme climate hydrological elements in the upper reaches of the Minjiang River were analyzed using extreme climate and runoff indicators. The research shows that the frequency and intensity of the extreme temperature warming index will increase, while those of the extreme temperature cooling index will increase and then weaken in the upper reaches of the Minjiang River under a future climate scenario. The duration of precipitation, the intensity of continuous heavy precipitation, and the frequency of heavy precipitation will increase, whereas the intensity of short-term heavy precipitation and the frequency of heavy precipitation will decrease. However, spatial distribution of flood in the upper reaches is different, and thus flood risk in the upstream source area will still tend to increase. Particular attention should be given to the increase in autumn flood risk in the upper reaches of the Minjiang River. [ABSTRACT FROM AUTHOR]

Climate change is a terrible global concern and one of the greatest future threats to societal development as a whole. The accelerating pace of climate change is becoming a major challenge for agricultural production and food security everywhere. The present study uses the midcentury climate derived from the ensemble of 29 general circulation models (GCMs) on a spatial grid to quantify the anticipated climate change impacts on rice, maize, black gram, and red gram productivity over Tamil Nadu state in India under RCP 4.5 and RCP 8.5 scenarios. The future climate projections show an unequivocal increase of annual maximum temperature varying from 0.9 to 2.2°C for RCP 4.5 and 1.4 to 2.7°C in RCP 8.5 scenario by midcentury, centered around 2055 compared to baseline (1981–2020). The projected rise in minimum temperature ranges from 1.0 to 2.2°C with RCP 4.5 and 1.8 to 2.7°C under RCP 8.5 scenario. Among the monsoons, the southwest monsoon (SWM) is expected to be warmer than the northeast monsoon (NEM). Annual rainfall is predicted to increase up to 20% under RCP 4.5 scenario in two-third of the area over Tamil Nadu. Similarly, RCP 8.5 scenario indicates the possibility of an increase in rainfall in the midcentury with higher magnitude than RCP 4.5. Both SWM and NEM seasons are expected to receive higher rainfall during midcentury under RCP 4.5 and RCP 8.5 than the baseline. In the midcentury, climate change is likely to pose a negative impact on the productivity of rice, maize, black gram, and red gram with both RCP 4.5 and RCP 8.5 scenarios in most places of Tamil Nadu. The magnitude of the decline in yield of all four crops would be more with RCP 8.5 over RCP 4.5 scenario in Tamil Nadu. Future climate projections made through multi-climate model ensemble could increase the plausibility of future climate change impact assessment on crop productivity. The adverse effects of climate change on cereal and legume crop productivity entail the potential adaptation options to ensure food security. [ABSTRACT FROM AUTHOR]

This paper aims to detect climate change points and compare the extreme temperature changes with the average-value changes in the Amur River basin. The daily air temperatures of 44 stations in the Amur River basin were collected from April 1, 1954, to March 31, 2013. The change points for annual mean and extreme temperature in 44 individual stations and their average were detected by the Mann-Kendall test, respectively. The annual mean temperature changed during 1980s in terms of increased mean value and relative stable standard deviation. The annual maximum temperature from 31 stations mostly located in the central and northwest basin changed significantly, and their change points occurred mainly in 1990s. For the annual minimum temperature, 32 stations mainly located in the central basin had significant changes. The generalized extreme value distribution was fitted to the postchange point subseries of annual extreme temperature and the parameters were estimated by the maximum likelihood method. The 10/50/100-year return levels were estimated by the method of profile likelihood. For the areas in the central and Northwestern basin, the probability of occurrence of hot extremes increased, while the occurrence probability of cold extremes was decreased in the central basin under climate change. [ABSTRACT FROM AUTHOR]

The frequent occurrence of geophysical disasters under climate change has drawn Chinese scholars to pay their attention to disaster relations. If the occurrence sequence of disasters could be identified, long-term disaster forecast could be realized. Based on the Earth Degassing Effect (EDE) which is valid, this paper took the magnitude, epicenter, and occurrence time of the earthquake, as well as the epicenter and occurrence time of the rainstorm floods as basic factors to establish an integrated model to study the correlation between rainstorm floods and earthquakes. 2461 severe earthquakes occurred in China or within 3000 km from China and the 169 heavy rainstorm floods occurred in China over the past 200+ years as the input data of the model. The computational results showed that although most of the rainstorm floods have nothing to do with the severe earthquakes from a statistical perspective, some floods might relate to earthquakes. This is especially true when the earthquakes happen in the vapor transmission zone where rainstorms lead to abundant water vapors. In this regard, earthquakes are more likely to cause big rainstorm floods. However, many cases of rainstorm floods could be found after severe earthquakes with a large extent of uncertainty. [ABSTRACT FROM AUTHOR]

Coastal flood regimes have been irreversibly altered by both climate change and human activities. This paper aims to quantify the impacts of multiple factors on delta flood. The Pearl River Delta (PRD), with dense river network and population, is one of the most developed coastal areas in China. The recorded extreme water level (m.s.l.) in flood season has been heavily interfered with by varied income flood flow, sea-level rise, and dredged riverbeds. A methodology, composed of a numerical model and the index R, has been developed to quantify the impacts of these driving factors in the the PRD. Results show that the flood level varied 4.29%–53.49% from the change of fluvial discharge, 3.35%–38.73% from riverbed dredging, and 0.12%–16.81% from sea-level rise. The variation of flood flow apparently takes the most effect and sea-level rise the least. In particular, dense river network intensifies the impact of income flood change and sea-level rise. Findings from this study help understand the causes of the the PRD flood regimes and provide theoretical support for flood protection in the delta region. [ABSTRACT FROM AUTHOR]

As the water source area for the middle route of China’s South-to-North Water Diversion Project, the upper Hanjiang basin is of central concern for future management of the country’s water resources. The upper Hanjiang is also one of the most flood-prone rivers in China. This paper explores the process of extreme floods by using multivariate analysis to characterize flood and precipitation event data in combination, for historical data and simulated data from global climate models. The results suggested that the generalized extreme value and Gamma models better simulated the extreme precipitation and flood volume sequence than the generalized Pareto model for the annual maximum series, while the generalized Pareto distribution model was the best-fit model for peaks over threshold series. For the two-dimensional joint distributions of precipitation and flood volume, the Frank Copula was preferred in simulation of the annual maximum flood series whereas the Gumbel Copula was the most appropriate function to simulate the points over threshold flood series. We concluded that, compared with the traditional univariate approach, multivariate statistical analysis produced flood estimates that were more physically based and statistically sound and carried lower risk for flood design purposes. [ABSTRACT FROM AUTHOR]

Meteorological observation plays a critical role in climatic study, and in situ measurements are the foundation of meteorological observation, especially in the Tibetan Plateau, the surface of which is fairly complex. Several field stations in the Northern Tibetan Plateau, which features relatively homogeneous surface, were selected as the study area. A detailed description on the significance of site observation for climate prediction was given in this paper. Data from weather stations can be used to verify satellite data and provide parameters for initial mode field in the study of weather and climate changes. The field observation data in the Northern Tibetan Plateau from 2001 to 2013 is analyzed. The results show that in El Nino year, values of land surface temperature (Ts), air temperature (Ta) and wind speed are all greater than their mean values and that soil moisture values are lower than the averaged, while the opposite is the case in La Nina year. The warming rate in the Northern Tibetan Plateau is greater than that in global areas. The diurnal variations of Ts and Ta are various in different seasons and underlying surfaces, with the diurnal variations greater in spring, and less in summer and autumn. Furthermore, the diurnal variation in the area with drier underlying surface is more obvious than that in area with moist surface. [ABSTRACT FROM AUTHOR]

Climate changes significantly cause the precipitation deficiency and in turn reduce the inflow amount in reservoir affecting hydroelectric power generation. The primary objective of this study was to evaluate hydropower generation and reservoir operation under climate change from Kesem reservoir. Recent Representative Pathway (RCP) scenarios were used to evaluate the impact of climate change on power generation. Power transformation equation and variance scaling approach were amalgamated to adjust the bias correction of precipitation and temperature, respectively. Bias, root mean square error, and coefficient of variation were used to check the accuracy of projected rainfall. The base and future precipitation, temperature, and evaporation trend was analysed using the Mann–Kendall test. The flow calibration and validation were carried out by the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS), and hydropower generation was evaluated with reservoir simulation model (MODSIM 8.1) under climate scenarios. The performance of the model was found good with Nash–Sutcliffe coefficient (NSE) of 0.72 and coefficient of determination (R2) of 0.73 for calibration and NSE of 0.74 and R2 of 0.75 for validation. Projected future climate scenarios predicted increasing and decreasing trend of temperature and precipitation, respectively. For RCP4.5 climate scenario, the average energy generation is likely to decrease by 0.64% and 0.82% in both short-term (2021–2050) and long-term (2051–2080), respectively. In case of RCP8.5 climate scenario, the average energy generation will be decreased by 1.06% and 1.35% for short-term and long-term, respectively. Remarkable reduction of energy generation was revealed in RCP8.5 with relation to RCP4.5 scenario. This indicates that there will be high energy fluctuation and decreasing trend in the future energy generation. The research finding is crucial for decision-makers, power authorities, governmental and nongovernmental organizations, and watershed management agencies to take care for sustainability in the future hydropower generation in the Kesem reservoir. [ABSTRACT FROM AUTHOR]

Indian monsoon is an important climatic phenomenon and a global climatic marker. Both statistical and numerical prediction schemes for Indian monsoon have been widely studied in literature. Statistical schemes are mainly based on regression or neural networks. However, the variability of monsoon is significant over the years and a single model is often inadequate. Meteorologists revise their models on different years based on prevailing global climatic incidents like El-Niño. These indices often have degree of severity associated with them. In this paper, we cluster the monsoon years based on their fuzzy degree of associativity to these climatic event patterns. Next, we develop individual prediction models for the year clusters. A weighted ensemble of these individual models is used to obtain the final forecast. The proposed method performs competitively with existing forecast models. [ABSTRACT FROM AUTHOR]

Ecosystem services are the benefit human populations derive directly and indirectly from the natural environment. They suffer from both the human intervention, like land use zoning change, and natural intervention, like the climate change. Under the background of climate change, regulation services of ecosystem could be strengthened under proper land use zoning policy to mitigate the climate change. In this paper, a case study was conducted in the middle reaches of the Heihe River Basin to assess the ecosystem services conservation zoning under the change of land use associated with climate variations. The research results show the spatial impact of land use zoning on ecosystem services in the study area which are significant reference for the spatial optimization of land use zoning in preserving the key ecosystem services to mitigate the climate change. The research contributes to the growing literature in finely characterizing the ecosystem services zones altered by land use change to alleviate the impact of climate change, as there is no such systematic ecosystem zoning method before. [ABSTRACT FROM AUTHOR]

Decadal prediction experiments are conducted by using the coupled global climate model FGOALS-s2, following the CMIP 5 protocol. The paper documents the initialization procedures for the decadal prediction experiments and summarizes the predictive skills of the experiments, which are assessed through indicators adopted by the IPCC AR5. The observational anomalies of surface and subsurface ocean temperature and salinity are assimilated through a modified incremental analysis update (IAU) scheme. Three sets of 10-year-long hindcast and forecast runs were started every five years in the period of 1960–2005, with the initial conditions taken from the assimilation runs. The decadal prediction experiment by FGOALS-s2 shows significant high predictive skills in the Indian Ocean, tropical western Pacific, and Atlantic, similar to the results of the CMIP5 multimodel ensemble. The predictive skills in the Indian Ocean and tropical western Pacific are primarily attributed to the model response to the external radiative forcing associated with the change of atmospheric compositions. In contrast, the high skills in the Atlantic are attributed, at least partly, to the improvements in the prediction of the Atlantic multidecadal variability coming from the initialization. [ABSTRACT FROM AUTHOR]

Land degradation is a complex process which involves both the natural ecosystem and the socioeconomic system, among which climate and land use changes are the two predominant driving factors. To comprehensively and quantitatively analyze the land degradation process, this paper employed the Normalized Difference Vegetation Index (NDVI) as a proxy to assess land degradation and further applied the binary panel logit regression model to analyze the impacts of the driving factors on land degradation in the North China Plain. The results revealed that an increase in rainfall and temperature would significantly and positively contribute to the land improvement, and conversion from cultivated land to grassland and forest land showed positive relationship with land improvement, while conversion to built-up area will lead to land degradation. Besides, human agricultural intensification represented by fertilizer utilization will help to improve the land quality. The economic development may exert positive impacts on land quality to alleviate land degradation, although the rural economic development and agricultural production will exert negative impacts on the land and lead to land degradation. Infrastructure construction would modify the land surface and further resulted in land degradation. The findings of the research will provide scientific information for sustainable land management. [ABSTRACT FROM AUTHOR]

Both the “urban minus rural” (UMR) and the “observation minus reanalysis” (OMR) methods were used to quantify the potential impacts of urbanization on regional temperature changes in the Beijing-Tianjin-Hebei metropolitan area in China. DMSP/OLS nighttime light imagery and population census data were used to classify stations into four classes: rural, small city, medium city, and large city groups. The regional average annual mean temperature was estimated to increase by 0.12°C decade−1 derived from urban warming, accounting for 40% of total climate warming from 1960 to 2009 using the UMR method. The OMR method also indicates that rapid urbanization has a significant influence on surface warming trend although the urban warming intensity is dependent on reanalysis dataset. The seasonal cycle patterns from all three datasets are consistent with each other, which is contrary to the UMR result owing to the cooling effect of agriculture activity in the rural stations confusing the UMR result. So in this paper we found a deficiency of the UMR method where it would underestimate the effects of urbanization in summer. In this regard, the results from the OMR method are relatively more convincing although we admit it still has many other problems. [ABSTRACT FROM AUTHOR]

In ecologically fragile areas with arid climate, such as the Heihe River Basin in northwestern China, sustainable social and economic development depends largely on the availability and sustainable uses of water resource. However, there is more and more serious water resource shortage and decrease of water productivity in Heihe River Basin under the influence of climate change and human activities. This paper attempts to identify the severe water scarcity under climate change and presents possible solutions for sustainable development in Heihe River Basin. Three problems that intervened land use changes, water resource, the relevant policies and institutions in Heihe River basin were identified, including (1) water scarcity along with serious contradiction between water supply and demand, (2) irrational water consumption structure along with low efficiency, and (3) deficient systems and institutions of water resource management along with unreasonable water allocation scheme. In this sense, we focused on reviewing the state of knowledge, institutions, and successful practices to cope with water scarcity at a regional extent. Possible solutions for dealing with water scarcity are explored and presented from three perspectives: (1) scientific researches needed by scientists, (2) management and institution formulation needed by governments, and (3) water resource optimal allocation by the manager at all administrative levels. [ABSTRACT FROM AUTHOR]

This study focuses on extreme precipitation changes in Xinjiang Province of Northwest China, which has experienced an increase in climate disasters in recent years. This paper investigates extreme precipitation events in Xinjiang, using 54 stations with daily precipitation records from the period 1961–2008. Different statistical tests and approaches were used to check the significance of trends of single and Xinjiang regionally aggregated precipitation series for intensity and in frequency. There were predominantly positive trends in annual maximum precipitation and a remarkable increment in the frequency of extreme precipitation over certain thresholds (from 10 to 40 mm). Although the series of frequencies exceeding thresholds had positive trends, only a minority were statistically significant. This lack of significance is because of the high variability of extreme precipitation in space and time. Thus, significant trends were evident when we assessed the extreme precipitation indicators of intensity and frequency at the regional level, both in intensity and frequency over thresholds, with a clearer signal in Xinjiang. [ABSTRACT FROM AUTHOR]

When compared to the wide range of atmospheric sensing techniques, global navigation satellite system (GNSS) offers the advantage of operating under all weather conditions, is continuous, with high temporal and spatial resolution and high accuracy, and has long-term stability. The utilisation of GNSS ground networks of continuous stations for operational weather and climate services is already in place in many nations in Europe, Asia, and America under different initiatives and organisations. In Africa, the situation appears to be different. The focus of this paper is to assess the conditions of the existing and anticipated GNSS reference network in the African region for meteorological applications. The technical issues related to the implementation of near-real-time (NRT) GNSS meteorology are also discussed, including the data and network requirements for meteorological and climate applications. We conclude from this study that the African GNSS network is sparse in the north and central regions of the continent, with a dense network in the south and fairly dense network in the west and east regions of the continent. Most stations lack collocated meteorological sensors and other geodetic observing systems as called for by the GCOS Reference Upper Air Network (GRUAN) GNSS Precipitable Water Task Team and the World Meteorological Organization (WMO). Preliminary results of calculated zenith tropospheric delay (ZTD) from the African GNSS indicate spatial variability and diurnal dependence of ZTD. To improve the density and geometry of the existing network, countries are urged to contribute more stations to the African Geodetic Reference Frame (AFREF) program and a collaborative scheme between different organisations maintaining different GNSS stations on the continent is recommended. The benefit of using spaced based GNSS radio occultation (RO) data for atmospheric sounding is highlighted and filling of geographical gaps from the station-based observation network with GNSS RO is also proposed. [ABSTRACT FROM AUTHOR]

Hydropower is sustainable and environmentally friendly source of energy worldwide. Driven by streamflow, it is vulnerable to climate change and land use change. The hydropower production from the two existing run-of-river hydropower projects on the Sondu Miriu River is vulnerable to rainfall variability and requires strategies for building resilience for the local communities. The objective of this study was to identify appropriate and sustainable strategies for integrating climate change adaptation into hydropower development within the Sondu Miriu River Basin. The methodology involved review of existing climate change adaptation strategies to identify appropriate strategies for integrating climate change adaptation in hydropower developments within the Sondu Miriu River Basin. The results indicate that no clear climate change adaptation strategies are being implemented within the basin. A framework is needed to implement appropriate climate change adaptation strategies within the basin. Climate Change act of 2016 created linkage with other existing policies for effective support of integration of climate change adaptation into hydropower development in Sondu Miriu River Basin. Strengthening community resilience to climate change impacts is one of the benefits to be derived from the hydropower projects by supporting appropriate adaptation strategies. [ABSTRACT FROM AUTHOR]

The aviation industry has a global economic impact of $2.7 trillion (including direct, indirect, induced, and tourism catalytic effects) and contributes 3.6 percent of global GDP. Weather is one of the most essential elements impacting how an aircraft runs and how safely it can fly. The correlation coefficient is the most significant index explaining the relationship between variables and can result in teleconnection patterns of climate indices. El Nino-Southern Oscillation (ENSO) and India Ocean Dipole (IOD) were used in this study based on the ERA5 reanalysis dataset for 30 years (1991–2020). Myanmar's Yangon International Airport has recorded more than 119874 times of observation data from 2009 to 2019. The mean percentage of occurrences of weather elements is calculated for each month and each season. Analysis of flight delay and accident data was obtained statistically from the Aviation Safety Network (ASN). According to the monthly delay index, July, August, and March are the maximum delay index months, and the correlation value between aircraft movement and delays is maximum in July and August and minimum in January and February. After examining numerous characteristics of Yangon International Airport, we identified which elements had a big impact on operations through vital interviews with operators, the accident case study section, and climatology analysis. As a result, we identified two meteorological occurrences: thunderstorm rain (TSRA) and fog (FG) are of high frequency and TSRA poses a larger risk than FG for aviation operation. The maximum frequency (%) of thunderstorm occurrences was 22% in July and the minimum was 1% in January. Annual frequency analysis revealed that TSRA days are becoming more common year after year as a result of global climate change. According to a spatial gridded analysis by ERA5 reanalysis data (1991–2020), the annual convective available potential energy (CAPE) values over local airport regions, the Bay of Bengal (BOB), the western equatorial Pacific, and the South China Sea show a positive correlation with convective rainfall. In contrast, negative convective inhibition (CIN) anomalies have been observed over the same areas as above, except for the western part of BOB along the Indian Coast. The primary innovation is that we look at the effects of thunderstorms on airport operations before determining their link with ENSO and the IOD individually and then combining them during their full phases. This raises a new question and a new possibility for viewing climatology from a new perspective. [ABSTRACT FROM AUTHOR]

In recent decades, global climate change, especially human activities, has led to profound changes in the hydrological cycle and hydrological processes in watersheds. Taking the Yue River watershed in the Qinling Mountains in China as the study area, the Mann–Kendall test and Pettitt mutation test method were used to analyze the various characteristics of hydrological and climatic elements from 1960 to 2018. Then, the elastic coefficient method based on the Budyko framework was used to estimate the elastic coefficient of runoff change on each influencing factor. The results showed that the annual runoff decreased at a rate of 0.038 × 108 m3/a (P > 0.05), and a significant abrupt change occurred in 1990. The annual precipitation and potential evapotranspiration (ET0) increased and decreased, with change rates of 0.614 mm/a and −0.811 mm/a (P > 0.05), respectively. The elasticity coefficients of precipitation, ET0, and the underlying surface were 1.95, −0.95, and −0.85, respectively, indicating that annual runoff was most sensitive to the change in precipitation, followed by the change in ET0, and had the lowest sensitivity to the change in the underlying surface. Underlying surface change is the main factor of runoff decrease; the contribution is 89.07%. The total contribution of climate change to runoff change is 10.93%, in which the contributions of precipitation and ET0 are 17.59% and −6.66%, respectively. The NDVI reflecting underlying surface change has been increasing since 1990, which is an important reason for the runoff decrease. [ABSTRACT FROM AUTHOR]

It is commonly acknowledged that land use changes (LUC) and climate changes have exerted significant effects on ecosystem services which are essential and vital to human well-being. Among all the services provided by ecosystem, climate regulation services are relatively sensitive to LUC and climate changes. This study aims to comprehensively review studies on the complex effects of LUC and climate changes on climate regulation services and further integrates the effects on climate regulation services into impact assessment for human well-being. In this study, we firstly introduced research efforts in which the drivers of and their corresponding effects on climate regulation services are briefly identified. Then, we explicitly reviewed the researches on the effects of LUC and climate changes on climate regulation services, especially focused on the certain methods and models used to quantify the effects on the major drivers of climate regulation services. After that, the effects of LUC and climate changes on human wellbeing via climate regulation services were revisited and commented accordingly. Finally, this paper discussed the current research gaps and proposed some research prospects in future studies. [ABSTRACT FROM AUTHOR]

Tropical deforestation could destabilize regional climate changes. This paper aimed to model the potential climatological variability caused by future forest vulnerability in the Brazilian Amazon over the 21th century. The underlying land surface changes between 2005 and 2100 are first projected based on the respectable output produced by Hurtt et al. Then the weather research and forecasting (WRF) model is applied to assess the impacts of future deforestation on regional climate during 2090-2100. The study results show that the forests in the Brazilian Amazon will primarily be converted into dryland cropland and pasture in the northwest part and into cropland/woodland mosaic in the southeast part, with 5.12% and 13.11%, respectively. These land surface changes will therefore lead to the significant reduction of the sum of sensible heat flux and latent heat flux and precipitation and the increase of the surface temperature. Furthermore, the variability of surface temperature is observed with close link to the deforested areas. [ABSTRACT FROM AUTHOR]

Taking the Yarkand River as an example, this paper conducted an integrative approach combining the Durbin-Watson statistic test (DWST), multiple linear regression (MLR), wavelet analysis (WA), coefficient of determination (CD), and Akaike information criterion (AIC) to analyze the climatic-hydrological process of inland river, Northwest China from a multitime scale perspective. The main findings are as follows. (1) The hydrologic and climatic variables, that is, annual runoff (AR), annual average temperature, (AAT) and annual precipitation (AP), are stochastic and, no significant autocorrelation. (2) The variation patterns of runoff, temperature, and precipitation were scale dependent in time. AR, AAT, and AP basically present linear trends at 16-year and 32-year scales, but they show nonlinear fluctuations at 2-year and 4-year scales. (3) The relationship between AR with AAT and AP was simulated by the multiple linear regression equation (MLRE) based on wavelet analysis at each time scale. But the simulated effect at a larger time scale is better than that at a smaller time scale. [ABSTRACT FROM AUTHOR]

Urban land expansion plays an important role in climate change. It is significant to select a reasonable urban expansion pattern to mitigate the impact of urban land expansion on the regional climate in the rapid urbanization process. In this paper, taking Wuhan metropolitan as the case study area, and three urbanization patterns scenarios are designed to simulate spatial patterns of urban land expansion in the future using the Partitioned and Asynchronous Cellular Automata Model. Then, simulation results of land use are adjusted and inputted into WRF (Weather Research and Forecast) model to simulate regional climate change. The results show that: (1) warming effect is strongest under centralized urbanization while it is on the opposite under decentralized scenario; (2) the warming effect is stronger and wider in centralized urbanization scenario than in decentralized urbanization scenario; (3) the impact trends of urban land use expansion on precipitation are basically the same under different scenarios; (4) and spatial distribution of rainfall was more concentrated under centralized urbanization scenario, and there is a rainfall center of wider scope, greater intensity. Accordingly, it can be concluded that decentralized urbanization is a reasonable urbanization pattern to mitigate climate change in rapid urbanization period. [ABSTRACT FROM AUTHOR]

Climate change caused by land use/cover change (LUCC) is becoming a hot topic in current global change, especially the changes caused by the grassland degradation. In this paper, based on the baseline underlying surface data of 1993, the predicted underlying surface data which can be derived through overlaying the grassland degradation information to the map of baseline underlying surface, and the atmospheric forcing data of RCP 6.0 from CMIP5, climatological changes caused by future grassland changes for the years 2010-2020 and 2040-2050 with the Weather Research Forecast model (WRF) are simulated. The model-based analysis shows that future grassland degradation will significantly result in regional climate change. The grassland degradation in future could lead to an increasing trend of temperature in most areas and corresponding change range of the annual average temperature of -0.1°C- 0.4°C, and it will cause a decreasing trend of precipitation and corresponding change range of the annual average precipitation of 10 mm-50 mm. This study identifies lines of evidence for effects of future grassland degradation on regional climate in Mongolia which provides meaningful decision-making information for the development and strategy plan making in Mongolia. [ABSTRACT FROM AUTHOR]