CLIMATE VARIABILITY empowers critical consequences on sustainability of soil and water resources. In this paper the trend of annual and seasonal time scale of temperature (minimum, maximum, average), relative humidity (minimum, maximum, average), precipitation, wind speed, extreme events, cloudiness, reference evapotranspiration employing Mann- kendall and least square errors were studied. These parameters showed direct or indirect effect on CLIMATE VARIABILITY in northeast of Iran. The results, for example in Mashhad station, showed an increasing trend in temperature, decreasing trend in humidity and no trend in precipitation. In addition, there were an increasing trend in the number of clear days (no cloud) and a decreasing trend in number of cloudy days across all study stations but Mashhad.

BACKGROUND AND OBJECTIVES: CLIMATE change has a greater influence on agriculture through local CLIMATE VARIABILITY than global CLIMATE patterns. The impact of CLIMATE change on agricultural productivity and shifts in crop patterns varies significantly across regions. Its impact is closely tied to the technical abilities of farmers in managing their cocoa farming businesses. Technical skills encompass the proficiency of farmers in adopting adaptive cocoa cultivation techniques for planting, maintaining cocoa plants, as well as handling harvest and postharvest processes. The technical capability is interconnected with factors such as crop dependency on rainfall patterns, availability of infrastructure for quality inputs, soil degradation and fertility, nutrient levels, limited farmers’ resources, and technology penetration. Given the significant impact of CLIMATE change on cocoa farmers, it becomes crucial to enhance their adaptive capacity to address these challenges. Therefore, this study aimed to analyze the relationship between the characteristics of farmers and their adaptive capacity in responding to the impact of CLIMATE change.METHODS: Data were collected from 960 populations from two regencies, 4 districts, and 8 villages using the stratified sampling technique through interviews with 282 respondents. The sample size was determined using the Slovin formula through in-depth interviews with five key informants. The data collected were descriptively and statistically analyzed using the Excel program, which involved generating frequency distribution tables. Furthermore, the Mann-Whitney test, utilizing Statistical Product and Service Solution version 24, was employed to conduct a comparative analysis.FINDINGS: This result showed that the characteristics of farmers in the two areas were relatively the same in terms of age, non-formal education, number of family dependents, and perceptions of the CLIMATE. In terms of age, most farmers fell within the mature group of 36-48 years, with an average age of 44.63, considering in low category. The low productive age of farmers (44.63), along with their non-formal education, including training in CLIMATE field schools and integrated pest management field schools, as well as the number of dependents and their perceptions of CLIMATE change, emerged as significant parameters impacting farmers'''' decision-making processes. These factors also influenced their ability to cope, adapt, and seek new approaches to manage and mitigate the effects of CLIMATE change on their farming operations.CONCLUSION: The relationship between farmers’ characteristics and adaptive capacity showed that the larger the land owned by farmers, the higher the managerial adaptability of farmers with lower technical ability.

The research examined effect of CLIMATE VARIABILITY on yieldof the two dominant cool weather cereals (wheat andbarley) in central highland and Arssi grain plough farmingsystems of Ethiopia using eight round unbalanced panel data(1994-2014). The stochastic frontier model result revealed thatproduction inputs for producing wheat and barley in the twofarming system had significant effect. Crop season rainfall incrementhad negative and significant effect on technicalefficiency of smallholders to produce wheat as to the modelresult. Technical efficiency of two crops responded differentlyfor cropping season rainfall VARIABILITY, in which wheat hadnegative and significant interaction with it while barley hadpositive. Given this, cropping season temperature had significantand positive effect on technical efficiency of both wheat andbarley. Having this into account, yield of the two cropsresponded similarly for changes in production inputs likeworking capital, human labor and fertilizer. In general, rainfallinconsistency at the different stages of the production periodhad strong effect on yield of the two crops. Given this, thestudy forwarded an assignment to plant scientists in order tohave further investigation on how the two crops responded differentlyto temperature VARIABILITY.

Observations show that the global surface air temperature has risen by 0.6 during th 20th century. Global warming causes extreme events and bad weather in the near term. The loss of seasonal distinctions, larger fluctuation in intra-day temperature and large fluctuations in precipitations, and increasing of frequency and magnitude of the extreme events may be due to global warming. World Meteorological Organization (WMO), Intergovernmental Panel of CLIMATE Change (IPCC) and the other responsible groups began to develop guidelines related to detection of CLIMATE change by applying statistical methods.The purpose of this paper is to present a few simple and complex statistical models staking into account the effects of climatic change. In addition, the result of a few related projects which evaluated CLIMATE VARIABILITY by statistical methods in the country has been presented. It has been shown, there are a number of changes including trend, jump, unusual fluctuation, changes in distribution of elements and also changes in extreme indices including heat waves, diurnal temperature range, growing length season, ext.