Extended Abstract
 
Introduction
Many human civilizations have collapsed due to the climate. Historical and geographical evidence demonstrates that the majority of significant and stable civilizations were established in specific geographical-climatic areas with suitable biological conditions. Human civilizations have faced serious damages and collapses due to unfavorable climatic conditions. The existence of most human civilizations can be attributed to climatic conditions, with historical and geographic evidence, especially the special environmental condition of the world in the current situation. Countries that deal with biological, economic, social, and even political issues may not give special importance to this issue. The climate conditions around the world are constantly changing, and there will be severe problems in different dimensions in the not-too-distant future. Their existence could even be threatened by economic problems they will face. The world's population increase and energy demand in today's industrial world also result in damage to the planet's climate and atmosphere, as well as the effects of natural disasters. The human burden has not been spared and has been affected by many fundamental changes, of which the phenomenon of climate change is one of the clear examples. The most important indicators of climate change are temperature and precipitation. The change of each of these factors causes climate variability, which also has consequences on people's lives. The increase in greenhouse gases and suspended particles in the atmosphere, along with variations in the earth's surface, are among the most apparent consequences, and the damage caused by the world's industrial activities and human societies in the past two centuries. Different economic sectors, such as agriculture, industry, tourism, water, and health, are affected by this phenomenon. Based on what has been stated, it can be concluded that climate change will definitely occur in Iran. The agricultural sector will face significant challenges due to the occurrence of such things, given the climatic situation, hydrological characteristics, and limitations of the country's agricultural sector. It has created a unique climatic situation in Iran due to its location. The high-pressure rule in the subtropical zone causes the total amount of precipitation in Iran to be low.
 
Material and Methods
The LARS-WG model is a model that is utilized for exponential micro-scale GCM models. This model is a great choice for generating random weather data, which can be used to generate rainfall, radiation, and maximum and minimum daily temperatures at a station for both current and future climate. In order to model meteorological variables, the LARS-WG model uses a complex statistical distribution. Modeling is based on the length of dry and wet periods, daily precipitation and radiation series, and semi-empirical distribution. Climatic parameters such as minimum temperature, maximum temperature, precipitation, and solar radiation are inputs for the LARS-WG model, which are all in the daily time frame. In this model, temperature is not taken into account when modeling radiation, and the sundial can be utilized instead. From the semi-empirical distribution of the rainfall for the month in question, and without taking into account the wet series or the amount of precipitation from the previous day, the amount of precipitation for one day is calculated. In this model, the temperature is estimated using Fourier series. The daily minimum and maximum temperatures are modeled as random processes using the average and standard deviation of the daily standards, which depend on whether the day is wet or dry. The mean and standard deviation of the seasonal temperature are simulated using the third-order Fourier series. Residue values are determined by subtracting the average values from the observed values, and the minimum and maximum data are utilized in time autocorrelation analysis. Minimum temperature, maximum temperature, precipitation, and radiation are the outputs of this model. LARS-WG model data generation involves three stages: calibrating, evaluating, and creating meteorological data. In the next step, using LARS-WG models under RCP 2.6, 4.5, and 8.5 scenarios and the micro-scale exponential LARS-WG generating model of Jiroft City climate changes during the planting period of each crop in the periods of 2011-2045, 2065-2046, 2066-2079 and 2080-2099. In the final stage, a positive mathematical programming model was utilized to investigate the impact of climate change scenarios on Jiroft City's planting patterns using predicted climate change results. The cultivation pattern of Jiroft city today and the predicted effects of climate change parameters during the periods 2011-2045, 2046-2065, 2066-2079, and 2080-2099 are examined in this section. The current cultivation pattern will be discussed in the previous step. A positive mathematical programming model and GAMS25 software have been employed in this regard. Separate information about the area under cultivation, production, and performance of selected agricultural products, as well as the consumption of inputs, for the agricultural year 2021-2022 is presented in the table.
 
Results and Discussion
The results indicate that the performance of selected products is significantly affected by the climatic parameters of temperature and precipitation. Also, by applying the forecast of climate variability in the cultivation pattern model of all selected crops in the periods 2011-2045, 2046-2065, 2066-2079 and 2080-2099 based on the noses of the HadCM3 model are affected by different climate scenarios. The improvement of agricultural productivity and climate change are both negative effects of this phenomenon. The findings of this investigation can be advantageous for agricultural planning and economic development in Hamadan province.