CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959-2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s^(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.

Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.

Assessment of the Spatio-Temporal Trends of Annual Extreme Temperature Indices over Tanzania during the Period of 1982-2022

Extreme weather and climatic phenomena, such as heatwaves, cold waves, floods and droughts, are expected to become more common and have a significant impact on ecosystems, biodiversity, and society. Devastating disasters are mostly caused by record-breaking extreme events, which are becoming more frequent throughout the world, including Tanzania. A clear global signal of an increase in warm days and nights and a decrease in cold days and nights has been observed. The present study assessed the trends of annual extreme temperature indices during the period of 1982 to 2022 from 29 meteorological stations in which the daily minimum and maximum data were obtained from NASA/POWER. The Mann-Kendall and Sen slope estimator were employed for trend analysis calculation over the study area. The analyzed data have indicated for the most parts, the country has an increase in warm days and nights, extreme warm days and nights and a decrease in cold days and nights, extreme cold days and nights. It has been disclosed that the number of warm nights and days is on the rise, with the number of warm nights trending significantly faster than the number of warm days. The percentile-based extreme temperature indices exhibited more noticeable changes than the absolute extreme temperature indices. Specifically, 66% and 97% of stations demonstrated positive increasing trends in warm days (TX90p) and nights (TN90p), respectively. Conversely, the cold indices demonstrated 41% and 97% negative decreasing trends in TX10p and TN10p, respectively. The results are seemingly consistent with the observed temperature extreme trends in various parts of the world as indicated in IPCC reports.

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5),are assessed in terms of spatial distribution and interannual variability.The CMIP6 multi-model ensemble mean(CMIP6-MME)can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature,and minimum daily minimum temperature.However,CMIP6-MME has difficulties in reproducing cold nights and warm days,and has large cold biases over the Tibetan Plateau.Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices.Compared to CMIP5,CMIP6 models show improvements in the simulation of climate indices over China.This is particularly true for precipitation indices for both the climatological pattern and the interannual variation,except for the consecutive dry days.The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME)to 79%(CMIP6-MME).The most striking feature is that the dry biases in southern China,very persistent and general in CMIP5-MME,are largely reduced in CMIP6-MME.Stronger ascent together with more abundant moisture can explain this reduction in dry biases.Wet biases for total precipitation,heavy precipitation,and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME,but smaller,compared to CMIP5-MME.

2021:A Year of Unprecedented Climate Extremes in Eastern Asia,North America,and Europe

The year 2021 was recorded as the 6th warmest since 1880.In addition to large-scale warming,2021 will be remembered for its unprecedented climate extremes.Here,a review of selected high-impact climate extremes in 2021,with a focus on China,along with an extension to extreme events in North America and Europe is presented.Nine extreme events that occurred in 2021 in China are highlighted,including a rapid transition from cold to warm extremes and sandstorms in spring,consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year,extremely heavy rainfall over Henan Province and Hubei Province during summer,as well as heatwaves,persistent heavy rainfall,and a cold surge during fall.Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here,providing insights to understand climate extremes from a global perspective.This serves as a reference for climate event attribution,process understanding,and high-resolution modeling of extreme events.

The Extremely Hot and Dry Climatic Events and Potash Enrichment in Salt Lakes of the Jiangling Depression, Jianghan Basin

Objective A total of 820 million tons of potash reserves are predicted to exist in the Palaeocene–Eocene of the Jianghan Basin.However,the basin history is still unclear concerning the potash enriching conditions and mechanism.The Well SKD1 is the first exploration well drilled in the Paleogene of Jianghan Basin with continuous coring,which was implemented in the

The Effect of Extreme Climatic Events on Extreme Runoff in the Past 50 Years in the Manas River Basin, Xinjiang, China

To analyze extreme climatic change features and effects on runoff in the Manas River basin, Xinjiang, data were collected including daily mean temperature, daily highest and lowest temperatures, and daily precipitation from six meteorological stations in the Manas River basin as well as daily runoff data from the Kensiwate hydrologic stations during 1960-2010. By adopting the threshold value of extreme climatic events defined by ET ALDDMI and with the aid of nonparametric statistical tests, Pearson III methods, and others, the effect of extreme climatic events on extreme runoff in the past 50 years in the Manas River basin, Xinjiang, was analyzed. The results showed that in the past 50 years, 1) extreme warming events (annual extreme maximum temperature, warm-day and warm-night index) have risen significantly (P < 0.05). Among these the warm-day and warm-night indices decreased abruptly in 2001 and 1996, respectively. With respect to extreme cold events (annual extreme minimum temperature, cold-day and cold-night indices), the extreme minimum temperature was high after 1976, and the cold-day index weakened significantly, similar to the cold-night index. 2) Except for the continuous drought days (CDD), the other five indices of extreme precipitation events appeared to trend upward, with an abrupt change around 1993. 3) Flood events in 1990, mostly in summer, accounted for 42.9% of the total number of floods since 1960. Floods increased mainly because extremely high summer temperatures increased snowmelt, increasing inflow to the rivers, which combined with more precipitation to cause the increase in summer peak flood discharge.

Assessing Change of Lamto Reserve Area Based on the MODIS Time Series Data and Bioclimatic Factors Using BFAST Algorithms

Lamto Reserve area is a savannah landscape threatened by periodic drought, and anthropogenic activities leading to natural ecological imbalance. The ecological support services of the landscape had been significantly impacted by the grassland ecosystem. The Breaks for Additive Season and Trend Algorithms have been implemented in R to analyze the land cover/land use dynamic in relation to the climatic driver of Lamto forest from 2000 to 2020. We examine the vegetation state breaks using vegetation phenological patterns, and several time series including the Normalized Difference Vegetation Index and the Enhanced Vegetation Index, were studied utilizing Breaks for Additive Season and Trend. The findings indicate that the phenological changes in the vegetation in 2020 resulted from an increased temperature from (27.7°C) to (32.17°C), and a decrease in precipitation (71.75 millimeters). The analysis of variance ANOVA of the non-parametric Mann-Kendall test reveals a strong correlation between Precipitation/Evapotranspiration Grass (p mperature/Evapotranspiration Grass (p < 0.311), and Temperature/Normalized Difference Vegetation Index (p in vegetation detected by the Breaks for Additive Season and Trend Algorithms were caused by temperature extremes and reduced rainfall.

Assessment of Spatial Distribution and Temporal Trends of Precipitation and Its Extremes over Nigeria

This study analyzed the spatial distribution and temporal trends of precipitation and its extremes over Nigeria from 1979-2013 using climate indices, in order to assess climatic extremes in the country. Daily precipitation data used in this study were obtained from Nigeria Meteorological Agency (NIMET), Lagos. The study used climate indices developed by the Expert Team on Climate Change Detection (ETCCDI) for assessing extreme precipitation. Sen’s slope estimator and Mann-Kendall trend test were employed in data analysis. Results revealed that precipitation and its extremes varied spatially across Nigeria. Significant negative trends were observed in most of the precipitation indices for the period under study. Furthermore, significant downward trends were observed in the CWD (Consecutive Wet Day) while the CDD (Consecutive Dry Day) showed significant upward trends in all the regions. These spatial and temporal changes indicate that Nigeria’s climate is trending towards a warmer and drier condition, which could be attributed to global warming-induced climate change;which altered historical rainfall patterns thereby leading to extreme events. The findings of this study have provided useful information in understanding the extreme events that are assumed by the general populace to be normal recurrent events in Nigeria. The results of the analysis of yearly and decadal changes in precipitation totals and extreme values for the last 35 years (1979-2013) suggest the likelihood of severe impacts on water resources, agriculture, and water-sensitive economic activities

Climate Extremes along the Mining Chain over the Eastern Amazon: Projections to 2050

The mineral industry is of great importance for the economy and for the development of Brazil. However, climate change further accentuates the impacts caused by extreme weather and climate events on the logistics and operation processes of the mineral production chain (from the mine to the port). In order to reduce these effects, it is essential to have information about the future climate that will help this economic sector to carry out better long-term planning of its activities. However, the current scientific literature still lacks studies with this approach applied to the mineral industry. Therefore, the purpose of this study was to evaluate the future seasonal patterns of climate extremes in eastern Amazonia, exploring their impacts on the mineral production chain in the near future (2019-2050). To categorize the dry and rainy climate extremes, the Standard Precipitation Index (SPI) was calculated for the precipitation data series of Climate Prediction Center (CPC) observations and the PRECIS regional modeling system, considering the IPCC RCP4.5. The 1981-2005 period was defined as the present climate and used to assess the performance of the modeling system in reproducing the extremes. The analyses were based on the relative frequency of the categories of dry and rainy extremes. The performance evaluation of PRECIS showed that it had better accuracy in representing seasonal extremes of drought than extremes of rain. Along the mineral chain in eastern Amazonia, its accuracy was better over the port region, except for the dry extremes experienced from June to August (JJA), and from December to February (DJF) and March to May (MAM) for rainy extremes. The analysis of the frequency of occurrence of these events for the future indicates a greater probability of rain extremes along the mineral chain compared to another category of extremes. In addition, JJA will be the most suitable period to optimize operational processes in eastern Amazonia, as extremes are less likely to occur. On the other hand, the greater probability of extreme rain events from September through to November (SON) and MAM make these two periods less suitable for activity in the mining regions and areas north of the railway. The results of this study suggest an increasing risk to the processes of the mineral chain until 2050 associated with the occurrence of climate extremes, since it is susceptible to adverse weather conditions.

Ice storm damage to oak forests in subtropical China

Ice storms,as important sources of frequent and injurious disturbances,drive forest dynamics in the Northern Hemisphere.However,stand-level differential vulnerability to ice storms and the associated factors that predispose forest stands remain unclear.This is particularly concerning in the subtropics where the frequency of ice storms is predicted to increase with global warming.Here we assessed how the impact on three forest stands(early and late secondary-growth forests,and old-growth forests)differed after an extreme ice storm during 20–21 March 2022,and identified the abiotic and biotic factors that determine the damage intensity in the Shennongjia World Natural Heritage Site,a biodiversity conservation hotspot in central China.We found a stand-specific‘middomain effect’where the late secondary-growth forest sustained the most severe damage,the early secondarygrowth forest sustained the least,and the old-growth forest suffered an intermediate amount.‘Crown broken’was the most severe damage type across all three forest stands,although the proportion of‘branch broken’was also high in the old-growth forest.Topography played a significant role in determining the vulnerability of the early secondary-growth forest to severe ice storms whereas the forest structure and composition were important factors in explaining the damage rates in the old-growth forest,although they differed among the damage categories.In contrast,topography,forest structure and composition generally explain the intensity of damage in the late secondary-growth forests.Our results highlight that,in subtropical forests,the intensity of damage caused by severe ice storms and related determining factors are stand-level dependent.We also suggest exploring potential management strategies(e.g.,slow-growing hardwood species that can resist storms should be the main species for reforestation in early secondary-growth forests)to mitigate the risk of future severe ice storms,as well as other wind-related climatic extremes.

The Warm Arctic-Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

An enhanced Warm Arctic-Cold Eurasia(WACE)pattern has been a notable feature in recent winters of the Northern Hemisphere.However,divergent results between model and observational studies of the WACE still remain.This study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the WACE pattern in winter of 1980-2014 and explores the key factors causing the differences in the simulation capability among the models.The results show that the multimodel ensemble(MME)can better simulate the spatial distribution of the WACE pattern than most single models.Models that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well,especially the latter,usually can/cannot simulate the WACE pattern well.This mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea-Kara seas(BKS)region.Further analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking(UB),which can transport heat to the BKS region,causing the warm Arctic,and strengthen the westerly trough downstream,cooling central Eurasia.Therefore,simulation of UB is key and significantly affects the model’s performance in simulating the WACE.

Spatiotemporal variation of ecological environment quality and extreme climate drivers on the Qinghai-Tibetan Plateau

Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological environment of the QTP.However,there are few studies that explored the effects of climate extremes on ecological environment quality of the QTP,and few researchers have made quantitative analysis.Hereby,this paper proposed the Ecological Environmental Quality Index(EEQI)for analyzing the spatial and temporal variation of ecological environment quality on the QTP from 2000 to 2020,and explored the effects of climate extremes on EEQI based on Geographically and Temporally Weighted Regression(GTWR)model.The results showed that the ecological environment quality in QTP was poor in the west,but good in the east.Between 2000 and 2020,the area of EEQI variation was large(34.61%of the total area),but the intensity of EEQI variation was relatively low and occurred mainly by a slightly increasing level(EEQI change range of 0.05-0.1).The overall ecological environment quality of the QTP exhibited spatial and temporal fluctuations,which may be attributed to climate extremes.Significant spatial heterogeneity was observed in the effects of the climate extremes on ecological environment quality.Specifically,the effects of daily temperature range(DTR),number of frost days(FD0),maximum 5-day precipitation(RX5day),and moderate precipitation days(R10)on ecological environment quality were positive in most regions.Furthermore,there were significant temporal differences in the effects of consecutive dry days(CDD),consecutive wet days(CWD),R10,and FD0 on ecological environment quality.These differences may be attributed to variances in ecological environment quality,climate extremes,and vegetation types across different regions.In conclusion,the impact of climate extremes on ecological environment quality exhibits complex patterns.These findings will assist managers in identifying changes in the ecological environment quality of the QTP and addressing the effects of climate extremes.

Habitat heterogeneity and biotic interactions mediate climate influences on seedling survival in a temperate forest

Seedling stage has long been recognized as the bottleneck of forest regeneration,and the biotic and abiotic processes that dominate at seedling stage largely affect the dynamics of forest.Seedlings might be particularly vulnerable to climate stress,so elucidating the role of interannual climate variation in fostering community dynamics is crucial to understanding the response of forest to climate change.Using seedling survival data of 69 woody species collected for five consecutive years from a 25-ha permanent plot in a temperate deciduous forest,we identified the effects of biotic interactions and habitat factors on seedling survival,and examined how those effects changed over time.We found that interannual climate variations,followed by biotic interactions and habitat conditions,were the most significant predictors of seedling survival.Understory light showed a positive impact on seedling mortality,and seedling survival responded differently to soil and air temperature.Effects of conspecific neighbor density were significantly strengthened with the increase of maximum air temperature and vapor pressure deficits in the growing season,but were weakened by increased maximum soil temperature and precipitation in the non-growing season.Surprisingly,seedling survival was strongly correlated with interannual climate variability at all life stages,and the strength of the correlation increased with seedling age.In addition,the importance of biotic and abiotic factors on seedling survival differed significantly among species-trait groups.Thus,the neighborhood-mediated effects on mortality might be significantly contributing or even inverting the direct effects of varying abiotic conditions on seedling survival,and density-dependent effects could not be the only important factor influencing seedling survival at an early stage.

Overview of China Polar Climate Change Annual Report(2022)

The China Meteorological Administration recently released China Polar Climate Change Annual Report(2022)in Chinese,with the following main conclusions.Using the China Reanalysis-40 dataset(CRA-40),rapid warming has been observed in the Antarctic Peninsula and West Antarctica since 1979,with some parts of East Antarctica also experiencing warming.In 2022,the regional average temperature in Antarctica based on observational data was close to the long-term average(1991-2020).The Arctic,on the other hand,has experienced a warming trend at a rate of 0.63℃per decade from 1979 to 2022 based on CRA-40,which is 3.7 times the global mean during the same period(0.17℃per decade).In 2022,the overall temperature in the Arctic,using station data,was 1.10℃above the long-term average(1991-2020).In recent years,both the Antarctic and Arctic regions have witnessed an increase in the frequency and intensity of extreme weather events.In 2022,based on the sea ice extent from National Snow and Ice Data Center,USA,Antarctic sea ice reached its lowest extent on record since 1979,and on 18 March,the most rapid surface warming event ever recorded on Earth occurred in the Antarctic,with a temperature increase of 49℃within 3 d.This report has been integrated into China's National Climate Change Bulletin system,to contribute to raising public awareness of polar climate change and providing valuable scientific references to address climate change.

2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.

Observed Frequent Occurrences of Marine Heatwaves in Most Ocean Regions during the Last Two Decades

Marine heatwaves(MHWs)are prolonged high-temperature extreme events in the ocean that can be devastating to marine life and seriously impact climate systems and economies.This paper describes the accessibility,content,characteristics,and potential applications of an MHW dataset to facilitate its use in scientific research.Daily intensities of global MHWs from 1982 to 2020 were analyzed using gridded SST data sourced from the National Oceanic and Atmospheric Administration(NOAA)Optimum Interpolation(OI)SST V2 high-resolution(0.25°)dataset.The analysis shows a linear increase in the frequency of MHWs in most ocean regions of the world as well as significant interdecadal changes.This data product can be used as a basic dataset to study the seasonal to decadal changes in extreme ocean events and explore the effects of global warming on the surface layers of oceans during the last 40 years.

The 2020 Summer Floods and 2020/21 Winter Extreme Cold Surges in China and the 2020 Typhoon Season in the Western North Pacific

China experienced significant flooding in the summer of 2020 and multiple extreme cold surges during the winter of 2020/21.Additionally,the 2020 typhoon season had below average activity with especially quiet activity during the first half of the season in the western North Pacific(WNP).Sea surface temperature changes in the Pacific,Indian,and Atlantic Oceans all contributed to the heavy rainfall in China,but the Atlantic and Indian Oceans seem to have played dominant roles.Enhancement and movement of the Siberian High caused a wavier pattern in the jet stream that allowed cold polar air to reach southward,inducing cold surges in China.Large vertical wind shear and low humidity in the WNP were responsible for fewer typhoons in the first half of the typhoon season.Although it is known that global warming can increase the frequency of extreme weather and climate events,its influences on individual events still need to be quantified.Additionally,the extreme cold surge during 16–18 February 2021 in the United States shares similar mechanisms with the winter 2020/21 extreme cold surges in China.

Spatial and Temporal Variations of Extreme Climate Events in Xinjiang, China during 1961-2010

Daily maximum/minimum temperature and precipitation data from 35 weather stations in Xinjiang during 1961-2010 were examined using kriging spatial analysis, linear tendency estimation, and correlation analysis. Temporal trends and spatial distribution patterns of extreme temperature and precipitation in this area were then analyzed using 12 extreme temperature and 7 extreme precipitation indices. The following results were obtained. 1) Over the past 50 years, extreme cold indices, excepting the monthly maximum temperature minimum value and monthly extreme minimum temperature, showed slight decreasing trends. These indices include the maximum number of consecutive frost days, icy days, cold-nighttime days, and cold-daytime days. 2) Extreme warm events generally showed significant increasing trends (P < 0.01), including the indices of summertime days, warm-nighttime days, warm-daytime days, monthly extreme maximum temperature, and monthly minimum temperature maximum value. 3) The spatial distributions of threshold values of extreme warm and cold events showed notable regional differences. A reducing trend of extreme cold events and an increase in extreme warm events has occurred mainly in northern Xinjiang. 4) For the past 50 years, six extreme precipitation indices, aside from consecutive dry days, showed significant increasing trends in Xinjiang (P < 0.05) and notable differences in spatial distribution. The increase in extreme precipitation events was more rapid at northern than at southern sites. Extreme precipitation intensity was greater in mountainous areas, and precipitation frequency increased in the plain region. 5) Factor analysis revealed good correlations among extreme temperature indices, excepting extreme temperature days.

Trends of Extreme Temperature and Rainfall Indices for Arid and Semi-Arid Lands of South Eastern Kenya

Extreme climate events have profound impacts on economies and livelihoods of many regions of the world. In Kenya, the extreme climate events often have strong impacts on agriculture production systems in the Arid and Semi-Arid Lands (ASALs). A small change in the mean climate condition can cause large changes in these production systems. There is a paucity of information on trends in climate and climate extremes in the country. However, a joint World Meteorological Commission for Climatology/World Climate Research Programme (WCPRP) project on climate Variability and Predictability (WMO CCl/CLIVAR) Expert Team (ET) on Climate Change Detection, Monitoring and Indices has defined 27 core climate indices mainly focusing on extreme events which can be derived through the use of RClimDex Software. In this study, therefore, the RClimDex software has been used to derive climate extreme indices for five stations in the ASALs of South-Eastern Kenya based on climate data for the period 1961 to 2009. The objective was to examine trends in these extremes to aid agricultural planning and practice. These indices have shown decreasing trends in annual rainfall, rainfall intensity and consecutive wet days but increasing trends in consecutive dry days. Steady warming patterns were evident in both the maximum and minimum temperature indices. This paper concludes that indeed significant changes in climate extremes are apparent in the ASALs of the country and recommends a re-thinking of planning and practice of rain-fed agriculture in the ASALs of South-Eastern Kenya.