A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments

Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.

Predicting Groundwater Level Using Climate Change Scenarios in the Southern Part of Mali

Groundwater is mainly demanded in all the activities for the population of the southern part especially in the Koda catchment, the studied area. These resources are affected by various factors especially climate change. Therefore, knowing the impact of projected climate change on groundwater recharge is an important issue for water resources management, especially for those responsible for the Koda catchment. In this work, the impact of climate change on groundwater resources in the study area in Mali, West Africa is investigated. The Hydrogeological modeling was performed using the Gardenia model, and the monthly precipitation and temperature data were used as the Baseline. These data considered the past 30-year period (1987-2016) and the projections for the next 30 years (2021-2050). Projected precipitation and air temperatures, extracted from the Rossby Centre regional Atmospheric climate model (RCA 4) statistically downscaled from the GCM-IHEC-EC-EARTH and the GCM-MPI-M-MPI-ESM-LR under the Representative Concentration Pathways RCP 4.5 and RCP 8.5 and corrected with the Multiscale Quantile Mapping bias correction method, were used as input data to the gardenia model. Potential evapotranspiration (PET) values estimated from Blaney Criddle method and groundwater levels measured in three piezometers were used to calibrate the Gardenia model. The outputs display the reduction of groundwater level in the three piezometers in the Koda catchment for all the two Regional Climate Models (RCMs) during the periods of rainy season from July to October. From the results of GCM IHEC-EC-EARTH, the projected decline in GWL reaches 1.09 m for the RCP 4.5 and it up to 1.26 m for the RCP 8.5 in the study area while the GCM MPI-M-MPI-ESM-LR presentes the decline in groundwater level (GWL) during winter season from about 0.62 m for the RCP 4.5 up to 1.93 m for the RCP 8:5. Both RCMs project a reduction trend of groundwater recharge over time. It is noticeable that this decline is greater in RCP8.5 for all the three piezometers. The results also show that the average groundwater recharge (90 mm) in the future (2021-2050) is lower (180 mm) than that of the current drought (1987-2016), which could lead to severe drought events. The projected impacts of climate change would have a significant impact on groundwater in the period of 2029-2039;this situation could have a negative impact the socioeconomic activities especially on agriculture, which depends on water resources. The results will help also to take some adaptation measures to climate change, the famers could have a possibility to know the period of groundwater recharge where they have more water infiltration therefore, where to seek crops that need less or more water. The study area presents numerous potential of groundwater, the results could be a tool for groundwater management and to determine the favorable sites to implant new boreholes.

Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.

Impact of climate change and variability on water resources in Heihe River Basin

Studies indicate that the climate has experienced a dramatic change in the Heihe River Basin with scope of temperature rise reaching 0.5-1.1 o C in the 1990s compared to the mean value of the period 1960-1990, precipitation increased 18.5 mm in the 1990s compared to the 1950s, and 6.5 mm in the 1990s compared to the mean value of the period 1960-1990, water resources decreased 2.6×10 8 m 3 in the 1990s compared to the 1950s, and 0.4×10 8 m 3 in the 1990s compared to the mean value of the period 1960-1990. These changes have exerted a greater effect on the local environment and socio-economy, and also made the condition worsening in water resources utilizations in the Heihe Rver Basin.

Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia

Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment.Although there are enough historical evidence to support the theory that climate change is a natural phenomenon,many research scientists are widely in agreement that the increase in temperature in the 20 th century is anthropologically related.The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally.In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness.This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia.The comparison of decadal variation of precipitation and temperature anomalies before the 1970 s found general increases which were mostly varying.But beyond the 1970 s,global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period.There are frequent changes and a shift westward of the Indian summer monsoon.Although precipitation is observed to be 70%below normal levels,in some areas the topography affects the intensity of rainfall.These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future.The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human,financial,infrastructure and food security of the region.

Climate Change and Variability in Southeast Zimbabwe: Scenarios and Societal Opportunities

A lot of researches have been done on the negative impacts and challenges caused by extreme weather conditions due to climate change and variability. Not many researches have been focused on the positive side in form of opportunities presented due to climate change. The study aimed to show the climate change scenarios and explore possible opportunities that could be derived from such scenarios in the southeastern region of Zimbabwe. The research used climate data records from three Zimbabwe Meteorological Services Department run weather stations in the region. The time series data were analyzed to show trends of rainfall and temperature over time. A questionnaire survey was also carried out to enquire from the farmers if they perceived climate change to have any opportunities. The rainfall trend analysis showed that rainfall amounts have declined at two of the three stations used. Rainfall total was also shown to be variable from year to year at all the stations. Ambient temperatures at all the stations were shown to have increased for both winter and summer. Opportunities that could be derived from climate change in the region were identified as the hydrological, agricultural and industrial. The research concludes that taking advantages of opportunities offered by climate change and variability provides the quickest way of embracing climate change adaptation.

Influences of Climate Change and Its Interannual Variability on Surface Energy Fluxes from 1948 to 2000

Understanding changes in land surface processes over the past several decades requires knowledge of trends and interannual variability in surface energy fluxes in response to climate change. In our study, the Community Land Model version 3.5 （CLM3.5）, driven by the latest updated hybrid reanalysis-observational surface climate data from Princeton University, is used to obtain global distributions of surface energy fluxes during 1948 to 2000. Based on the climate data and simulation results, long-term trends and interannual variability （IAV） of both climatic variables and surface energy fluxes for this span of 50＋ years are derived and analyzed. Regions with strong long-term trends and large IAV for both climatic variables and surface energy fluxes are identified. These analyses reveal seasonal variations in the spatial patterns of climate and surface fluxes; however, spatial patterns in trends and IAV for surface energy fluxes over the past ～50 years do not fully correspond to those for climatic variables, indicating complex responses of land surfaces to changes in the climatic forcings.

Implications of future climate change on crop and irrigation water requirements in a semi-arid river basin using CMIP6 GCMs

Agriculture faces risks due to increasing stress from climate change,particularly in semi-arid regions.Lack of understanding of crop water requirement(CWR)and irrigation water requirement(IWR)in a changing climate may result in crop failure and socioeconomic problems that can become detrimental to agriculture-based economies in emerging nations worldwide.Previous research in CWR and IWR has largely focused on large river basins and scenarios from the Coupled Model Intercomparison Project Phase 3(CMIP3)and Coupled Model Intercomparison Project Phase 5(CMIP5)to account for the impacts of climate change on crops.Smaller basins,however,are more susceptible to regional climate change,with more significant impacts on crops.This study estimates CWRs and IWRs for five crops(sugarcane,wheat,cotton,sorghum,and soybean)in the Pravara River Basin(area of 6537 km^(2))of India using outputs from the most recent Coupled Model Intercomparison Project Phase 6(CMIP6)General Circulation Models(GCMs)under Shared Socio-economic Pathway(SSP)245 and SSP585 scenarios.An increase in mean annual rainfall is projected under both scenarios in the 2050s and 2080s using ten selected CMIP6 GCMs.CWRs for all crops may decline in almost all of the CMIP6 GCMs in the 2050s and 2080s(with the exceptions of ACCESS-CM-2 and ACCESS-ESM-1.5)under SSP245 and SSP585 scenarios.The availability of increasing soil moisture in the root zone due to increasing rainfall and a decrease in the projected maximum temperature may be responsible for this decline in CWR.Similarly,except for soybean and cotton,the projected IWRs for all other three crops under SSP245 and SSP585 scenarios show a decrease or a small increase in the 2050s and 2080s in most CMIP6 GCMs.These findings are important for agricultural researchers and water resource managers to implement long-term crop planning techniques and to reduce the negative impacts of climate change and associated rainfall variability to avert crop failure and agricultural losses.

Preface to the Special Issue “Unified Perspective of Climate Variability and Change”

Forty years ago, Klaus Wyrtki （1975） of University of Hawaii discovered that E1 Nifio warming off South America is not a result of local wind change but a response to the relaxed equatorial trade winds some 10 000 km away near the international dateline. The Kelvin wave mechanism was quickly verified from wind-forced ocean model simulations. Consequent develop- ments show that the dance between the fast-reacting atmosphere and slow-evolving ocean sets the pace of E1 Nifio-Southern Oscillation （ENSO; Philander, 1990）. The concept of ocean-atmosphere interaction has revolutionized our view of the climate system and led to operational climate prediction.

Comparative Evaluation of Farmers’ Perception and Adaptation Strategies to Climate Change and Variability in Bako Tibe, Ethiopia and Abeokuta, Nigeria

Comparing the perception of farmers to climate change and variability in Bako Tibe, Ethiopia and Abeokuta, Nigeria is important in promoting sustainable agriculture and in understanding the impact of climate change and variability on agriculture in Africa. A total of 153 farmers were interviewed in both study areas using well structure questionnaire. The study describes the socioeconomic characteristics of farmers using descriptive statistics and thereafter the perception of Bako Tibe and Abeokuta farmers to climate change and variability was examined using Likert type scale. The binary logistics regression was later used to ascertain the effect of socioeconomic characteristics on perception of the farmers in both study areas. The farmers in both study areas believed that there have been changes in the amount of rainfall and temperature in the past thirty years. The farmers in Bako agreed that there have been increased temperature and decreased rainfall, contrary to the farmer’s perception in Abeokuta. The binary logistic regression results showed that socioeconomic characteristics of farmers in Bako Tibe, have no effect on the perception of farmers on climate change and variability. However, in Abeokuta, age, land ownership, and distance to market had an effect on the perception on the farmers on climate change and variability. The adaptation strategies to climate change and variability commonly used by Bako Tibe farmers was, improved seed (drought resistance) adaptation method, while most farmers in Abeokuta used soil moisture conservation adaptation method. The study recommends that government and Non-Governmental Organization of both countries should promote more adaptation and mitigation practices to climate change and variability through policy interventions to help curb the impact of climate change and variability to agriculture.

Magnitudes of Climate Variability and Changes over the Arid and Semi-Arid Lands of Kenya between 1961 and 2013 Period

The magnitude and trend of temperature and rainfall extremes as indicators of climate variability and change were investigated in the Arid and Semi-Arid Lands (ASALs) of Kenya using in-situ measurements and gridded climate proxy datasets, and analysed using the Gaussian-Kernel analysis and the Mann-Kendall statistics. The results show that the maximum and minimum temperatures have been increasing, with warmer temperatures being experienced mostly at night time. The average change in the mean maximum and minimum seasonal surface air temperature for the region were 0.74°C and 0.60°C, respectively between the 1961-1990 and 1991-2013 periods. Decreasing but statistically insignificant trends in the seasonal rainfall were noted in the area, but with mixed patterns in variability. The March-April-May rainfall season indicated the highest decrease in the seasonal rainfall amounts. The southern parts of the region had a decreasing trend in rainfall that was greater than that of the northern areas. The results of this study are expected to support sustainable pastoralism system prevalent with the local communities in the ASALs.

Implications of Land Use Land Cover Change and Climate Variability on Future Prospects of Beef Cattle Production in the Lake Victoria Basin

This paper presents the lessons learnt from a research project titled “Improving Beef Cattle Productivity for Enhanced Food Security and Efficient Utilization of Natural Resources in the Lake Victoria Basin” which includes Tanzania, Uganda and Rwanda. The key focus is on the implications of land use land cover change and climate variability on the future prospects of beef cattle production in this region. The study utilizes information and data from natural resources and climate components to deduce the impact of land use and land cover changes on climate variability. Additional analysis is conducted to summarize the land use and land cover data to carry out analysis on climate data using the Mann-Kendal test, linear regression and moving averages to reveal patterns of change and trends in annual and seasonal rainfall and temperature. The findings reveal that the study areas of Rwanda, Uganda and Tanzania in the Lake Victoria Basin (LVB) have changed over time following land cover manipulations and land use change, coupled with climate variability. The grazing land has been converted to agriculture and settlements, thereby reducing cattle grazing land which is the cheapest and major feed source for ruminant livestock production. Although the cattle population has been on the increase in the same period, it has been largely attributed to the fact that the carrying capacity of available grazing areas had not been attained. The current stocking rates in the LVB reveal that the rangelands are greatly overstocked and overgrazed with land degradation already evidenced in some areas. Climate variability coupled with a decrease in grazing resources is driving unprecedented forage scarcity which is now a major limiting factor to cattle production. Crop cultivation and settlement expansion are major land use types overtaking grazing lands;therefore the incorporation of crop residues into ruminant feeding systems could be a feasible way to curtail rangeland degradation and increase beef cattle production.

Perception of Fogera Cattle Farmers on Climate Change and Variability in Awi Zone, Ethiopia

This study aimed at assessing perception of Fogera cattle farmers on climate change and variability in selected districts of Awi zone. The zone was classified as lowland (<1500), midland (1500 - 2500), and highland (>2500 m.a.s.l) based on altitudinal variation from which a total of three districts one per cluster were selected through random sampling. 150 households were selected through systematic random sampling targeting Fogera cattle owners for primary data collection. Over 36 years (from 1983-2019) of meteorological data were taken from the National Meteorological Agency. Meteorological data result confirmed that climate was changing across all the agro-ecological zones. Both the mean annual maximum and minimum temperature was considerably increasing for all agro-ecological zones whereas the mean annual rainfall was decreasing which is consistent with the farmers’ perception. Meteorological data result also showed that the short rainy and dry season rainfall indicated high interannual variability at all agro-ecological zones. Survey result revealed that 97.13% of the farmers recognized climate change and variability impact in all agro-ecological zones. About 80.91% of Fogera cattle farmers reported the incidence of negative impacts of climate change and variability on cattle. Chi-square test values of survey results show that in all agro-ecological zones frequency of drought, duration of dry spell, wind, and floods were ever-increasing (p < 0.001). Moreover, about 84.48%, 65.3%, and 60.47% of farmers owning Fogera cattle in the lowland, midland, and highland, respectively perceived the prevalence of increasing (p < 0.001) cattle mortality. In response to climate change and variability, farmers were reducing number of livestock, diversification of livestock species, and replacing Fogera cattle with small ruminants as adaptation strategies. Thus, regular prediction of climate change and variability and designing pertinent response strategies is essential to reduce the adverse impacts of climate change for enhancing resilience capacity of the Fogera cattle farmers in the study areas.

Identifying Possible Climate Change Signals Using Meteorological Parameters in Short-Term Fire Weather Variability for Russian Boreal Forest in the Republic of Sakha (Yakutia)

The Boreal forest is a terrestrial ecosystem highly vulnerable to the impacts of short-term climate and weather variabilities. Detecting abrupt, rapid climate-induced changes in fire weather and related changes in fire seasonality can provide important insights to assessing impacts of climate change on forestry. This paper, taking the Sakha Republic of Russia as study area, aims to suggest an approach for detecting signals indicating climate-induced changes in fire weather to express recent fire weather variability by using short-term ranks of major meteorological parameters such as air temperature and atmospheric precipitation. Climate data from the “Global Summary of the Day Product” of NOAA (the United States National Oceanic and Atmospheric Administration) for 1996 to 2018 were used to investigate meteorological parameters that drive fire activity. The detection of the climate change signals is made through a 4-step analysis. First, we used descriptive statistics to grasp monthly, annual, seasonal and peak fire period characteristics of fire weather. Then we computed historical normals for WMO reference period, 1961-1990, and the most recent 30-year period for comparison with the current means. The variability of fire weather is analyzed using standard deviation, coefficient of variation, percentage departures from historical normals, percentage departures from the mean, and precipitation concentration index. Inconsistency and abrupt changes in the evolution of fire weather are assessed using homogeneity analysis whilst a Mann-Kendall test is used to detect significant trends in the time series. The results indicate a significant increase of temperature during spring and fall months, which extends the fire season and potentially contributes to increase of burned areas. We again detected a significant rainfall shortage in September which extended the fire season. Furthermore, this study suggests a new approach in statistical methods appropriate for the detection of climate change signals on fire weather variability using short-term climate ranks and evaluation of its impact on fire seasonality and activity.

Spatial Rainfall Variability and an Increasing Threat of Drought, According to Climate Change in Uttaradit Province, Thailand

This study presents the work commenced in northern Thailand on spatial and temporal variability of rainfall. Thirty years (1988-2017) rainfall data of eight meteorological stations were used for assessing temporal variability and trend analysis. The results showed decreasing trend in rainfall from its first half of the observed study period (1988-2002) to last half of the time period (2003-2017) in total average annual as well as monsoonal average rainfall by 14.92% and 15.50% respectively. It was predicted from linear regression results that by 2030 the average annual and monsoonal rainfall will drop by 35% and 34.10% respectively. All stations showed negative trend except Fakara met-station in annual rainfall. In the seasonal trend analysis, the results showed decreasing trend almost in all met-stations. Mann-Kendall trend test was applied to assess the trend. All met-stations show significant negative trend. To assess drought in the study area, Standardized Precipitation Index (SPI) was applied to 12-month temporal time period. The results predicted meteorological drought in the near future. The spatial distribution of rainfall presented changing phenomena in average annual, monsoonal, winter, and summer seasons in both analyzed periods.

Simulating hydrological responses to climate change using dynamic and statistical downscaling methods: a case study in the Kaidu River Basin, Xinjiang, China

Climate change may affect water resources by altering various processes in natural ecosystems. Dynamic and statistical downscaling methods are commonly used to assess the impacts of climate change on water resources. Objectively, both methods have their own advantages and disadvantages. In the present study, we assessed the impacts of climate change on water resources during the future periods (2020–2029 and 2040–2049) in the upper reaches of the Kaidu River Basin, Xinjiang, China, and discussed the uncertainties in the research processes by integrating dynamic and statistical downscaling methods (regional climate models (RCMs) and general circulation modes (GCMs)) and utilizing these outputs. The reference period for this study is 1990–1999. The climate change trend is represented by three bias-corrected RCMs (i.e., Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA), Regional Climate Model version 4 (RegCM4), and Seoul National University Meso-scale Model version 5 (SUN-MM5)) and an ensemble of GCMs on the basis of delta change method under two future scenarios (RCP4.5 and RCP8.5). We applied the hydrological SWAT (Soil and Water Assessment Tool) model which uses the RCMs/GCMs outputs as input to analyze the impacts of climate change on the stream flow and peak flow of the upper reaches of the Kaidu River Basin. The simulation of climate factors under future scenarios indicates that both temperature and precipitation in the study area will increase in the future compared with the reference period, with the largest increase of annual mean temperature and largest percentage increase of mean annual precipitation being of 2.4°C and 38.4%, respectively. Based on the results from bias correction of climate model outputs, we conclude that the accuracy of RCM (regional climate model) simulation is much better for temperature than for precipitation. The percentage increase in precipitation simulated by the three RCMs is generally higher than that simulated by the ensemble of GCMs. As for the changes in seasonal precipitation, RCMs exhibit a large percentage increase in seasonal precipitation in the wet season, while the ensemble of GCMs shows a large percentage increase in the dry season. Most of the hydrological simulations indicate that the total stream flow will decrease in the future due to the increase of evaporation, and the maximum percentage decrease can reach up to 22.3%. The possibility of peak flow increasing in the future is expected to higher than 99%. These results indicate that less water is likely to be available in the upper reaches of the Kaidu River Basin in the future, and that the temporal distribution of flow may become more concentrated.

Climate change trend and its effects on reference evapotranspiration at Linhe Station, Hetao Irrigation District

Linhe National Meteorological Station, a representative weather station in the Hetao Irrigation District of China, was selected as the research site for the present study. Changes in climatic variables and reference evapotranspiration （ET0 ） （estimated by the Penman-Monteith method） were detected using Mann-Kendall tests and Sen＇s slope estimator, respectively. The authors analyzed the relationship between the ET0 change and each climatic variable＇s change. From 1954 to 2012, the air temperature showed a significant increasing trend, whereas relative humidity and wind speed decreased dramatically. These changes resulted in a slight increase in ETo. The radiative component of total ET0 increased from 50% to 57%, indicating that this component made a greater contribution to the increase in total ETo than the aerodynamic component, especially during the crop growing season （from April to October）. The sensitivity analysis showed that ETo in Hetao is most sensitive to mean daily air temperature （11.8%）, followed by wind speed （-7.3%） and relative humidity （4.8%）. Changes in sunshine duration had only a minor effect on ET0 over the past 59 years.