نشریه پژوهش های اقلیم شناسی
پیاپی 53 (بهار 1402)

General circulation models (GCMs) provide valuable forecasts of world precipitation and temperature (Schepen et al., 2020). Through improved Seasonal forecasting in recent years several climates centers around the world provide operational climate Such as; the Climate Forecast System version 2 (CFSv2) by National Centers for Environmental Prediction (NCEP) (Saha et al., 2010), the European Centre for Medium-Range Weather Forecasts (ECMWF (Johnson et al., 2019), and the Geophysical Fluid Dynamics Laboratory (GFDL) (Delworth et al., 2020). These GCM outputs generally need to downscale to use in regional-scale relevant applications and more actionable end-user-oriented climate services. One way to transfer world predictions from GCMs to regional or local scales is dynamical downscaling with RCMs such as Weather Research and Forecasting model (WRF). The Initial and lateral boundary conditions from General Circulation Models (GCMs) drive these models. The mesoscale circulations, topography, and land use-land cover are displayed better by RCMs, and these models improve the extremes and regional climate variable compared to the coarse resolution GCMs. The WRF has been coupled with numerous parameterizations to resolve processes occurring within a grid box. Some research has indicated convective and planetary boundary layer (PBL) schemes have a significant influence on precipitation simulation (Li et al 2017; Njuki, S.M., et al 2021). The WRF Model version 4 provides more than 11 convective schemes and 13 planetary boundary layer (PBL) schemes. This study has attempted to assess a suitable combination of physics schemes of the Weather Research and Forecasting (WRF) model for seasonal precipitation simulation over the northeast of Iran. Using the CFSV2 as Initial and lateral boundary conditions data, simulation experiments from winter to spring in seven months (from November to May) have been performed for 2019-2020). Three nested domains have applied with the outer domain at 54 km resolution and two interdomains at 18 and 6 km resolution.

The study area is located in the northeast of Iran, and climatologically, most precipitation occurs from winter to spring (November to May). On average, the western part of this region receives approximately 60% of the annual precipitation, while the rest of the areas in the east receive lower precipitation. The real-time forecast data used in this study is the 6-hourly time series from the 9-month runs operational model for seasonal prediction at the NCEP operational CFSv2. The observed precipitation data is extracted from IRIMO. The new Weather Research and Forecasting model (WRF) is applied to determine how varying physical parameterization of PBL scheme configuration processes simulate seasonal (winter and spring) precipitation. For this purpose, four group configurations have been designed.Group1: convective schemes (KFT, BMJ, GF, KF), Yonsei University PBL (YSU) for the plenary boundary layer, surface layer scheme (Revised MM5), the shortwave radiation scheme (Dudhia), the longwave radiation scheme (RRTM) and land surface models (Noah).Group 2 all four convective schemes, PBL Mellor–Yamada–Janjic (MYJ), RRTMG for long –short radiation, 5-layer thermal diffusion, and Eta for land surface and surface layer. GROUP 3; include second-order Mellor-Yamada-Nakanishi-Niino (MYNN3) as PBL scheme, same shortwave and longwave radiation (New Goddard), the surface layer (MYNN), and land surface (RUC). Finally, group4 set by ACM2 for the plenary boundary layer, The surface layer (Pleim-Xiu), the shortwave and longwave radiation schemes (GFDL), the land surface (PX), four convective schemes have been fixed in all groups. For all WRF simulations, we used the WRF single-moment 6-class microphysics scheme. In this way, a total of 20 simulation sets in 4 groups have run, and one configuration set without any cumulus scheme in domain 3 in each group.The following statistics, the correlation (R), the root mean square error (RMSE), the mean absolute error (MAE), and bias and four verification skills are calculated from the total daily precipitation over the six months out of the seven-month integration time with the first month used as spin-up.

The WRF-CFSv2 model performance was evaluated against precipitation observations from Iran's Meteorological organization. The correlation scores between the observed and predicted 6- month and winter precipitation were moderately acceptable (0.3-0.5) however decreased to 0.36 in spring. In terms of bias, group 1 (PBL1,..) configuration have considerably structures than the group4 (PBL7,..), group2 (PBL2,…), and especially group3 (PBL6,..). All configurations showed a wet bias over the study area (-0.8 mm/d, -3.55mm/d) in the 6-month prediction. It is consistent with previous studies using GCMs in this region. The significant MAE of the 6-month precipitations simulated by group 1 and PBL1-CU2، PBL1-CU0, and PBL1-CU1 scenarios were the lowest among the configuration. Meanwhile, this group of configurations showed a similar RMSE score pattern by MAE, and the lowest RMSE showed in group 1 and group 2. In all configurations, the wet bias has been persistent in the study area.The WRF prediction captured the observed precipitation by groups 2 and 3 with MYJ and MYNN3 planetary boundary layer schemes. However, the false alarm (b) in group 1 and the number of missed events (c) in group 2 of configurations were finer low.

In this study, the WRF model performance was evaluated for various physical parameterizations in predicting precipitation for varying planetary boundary layer (PBL) schemes and Cumulus schemes over northeast Iran.Based on the sensitivity analysis, is concluded that the set that performs best for the region is YSU PBL, MM5 SL, Dudhia shortwave radiation, RRTM longwave radiation, and Noah LSM schemes.And using a cumulus scheme for grid resolutions between 3km and 10km is gray, as respects is not clear whether a cumulus scheme should be used or not. So, recommended testing a configuration set of no cumulus scheme mode to determine if using a cumulus scheme is ideal for your particular run.

Production potential refers to the yield of a particular cultivar of a crop in a given environment with sufficient growth sources and free of pests and diseases, which is determined only by solar radiation and the temperature of that environment.Understanding potential production helps direct agricultural research to identify growth-limiting factors and, consequently, promote policy-making and reduce the yield gap (Hackman et al., 2013).Today, several models based on the rate of evaporation of transpiration, radiation and heat are used by researchers to estimate the potential for dry matter production in plants. Among these, we can mention the model of FAO (thermal radiation), Wachningen, Albero, Dust, Episim, Wafest and Aquacrop (Salo et al., 2016). In Iran, from the FAO model to evaluate the potential of cotton production in Qom province (Seyed Jalali, 2004), alfalfa in Qazvin province (Taati et al., 2015), sugar beet in Lorestan and Silakhor plain (Sohrabi and Chegini, 2011), corn It has been used in Shahrekord (Etedali et al., 2012). For Hashtgerd region (Noshabadi et al., 2016) and Dasht-e Moghan (Izadfard et al., 2017), the yield potential of wheat and barley based on radiation and heat of the region has been studied by FAO model.Therefore, the present study aimed to determine the potential yield of winter wheat and barley based on radiation and heat of the study area (Abhar) through plant characteristics of high-yielding cultivars of two major wheat and barley plants under optimal growth conditions.

The study area was 30247 hectares in Abhar city (located in Zanjan province), which is located between the eastern longitude 49̊ 10́ to 49̊ 25́ and between the northern latitude 36̊ and 36̊ 15́. Approximately 3662 hectares of land are not cultivable due to high roughness, steep slopes and industrial structures. According to the climatic information of Khorramdareh synoptic station, the closest station to the study site, this region has a Mediterranean climate with cold and humid winters versus mild and dry summers. The average minimum and maximum annual temperatures are 0.1 and 12.7 degrees Celsius, respectively (average annual temperature is 12.7 degrees Celsius). Total precipitation, effective precipitation (relationship 4 and 5) and potentialtranspiration evaporation per year were 334, 102.8 and 1329.95 mm, respectively.Estimation of crop water requirement, using cropwat software version 8, the crop water requirement in the growth cycle was calculated. In cropwat software, the plant coefficient is calculated daily. Planting date According to the information of local farmers, the harvest date of summer crops and also the date of occurrence of early autumn frosts were selected, based on which, the first half of October 15 was the best time to plant wheat and winter barley. In addition, the length of each of the four stages of growth (initial, plant development, intermediate and final) based on the climate of the region (semi-arid) along with their related plant coefficients was extracted from FAO Journal No. 56 Irrigation and Drainage (Allen et al., 1998). Finally, plant coefficients from the beginning to the end of the growth cycle were estimated through linear interpolation in Krapowat software (Alizadeh, 2011).In the present study, the production potential of high-yielding winter wheat and barley cultivars were estimated using the FAO model and long-term radiation and temperature data of Abhar region. In addition, the water requirement of these crops was assessed using the FAO Cropwat model and climatic data including relative air humidity, wind speed, sun hours, solar radiation, minimum and maximum air temperatures.

Effective rainfall during the growth cycle, water requirement and irrigation of wheat crop with average plant coefficient of 0.79 were estimated to be 93.4, 694.5 and 601.1 mm, respectively. The effective rainfall during the growth cycle, water requirement and irrigation of barley with an average plant coefficient of 0.79 were calculated as 93.4, 615.3 and 522.7 mm, respectively. Biomass dry matter and grain in wheat with 45% harvest index were calculated 16.98 and 7.64 tons per hectare, respectively, which with the calculation of 11% grain moisture, the economic yield potential reaches 8.48 tons per hectare. Biomass dry matter and grain in six-row barley with 45% harvest index were estimated at 15.88 and 7.15 tons per hectare, respectively, which with the calculation of 11% grain moisture, the economic yield potential reached 7.94 tons per hectare.

Yield is a quantitative trait that results from the interaction of a large number of genes and environmental conditions. Therefore, the farmer strives to provide optimal growth conditions as far as possible through agriculture to increase plant production capacity. According to climatic variables (radiation and temperature) and crop characteristics of high-yielding cultivars, it seems that the FAO growth model has a reasonable estimate of production potential.

Inter-basin water transfer (IBT) is widely used to alleviate water scarcity at the cost of compromising water access in water-exporting regions. How efficient are inter-regional water in changing weather conditions and water supply and demand. In this research, we are trying to achieve the correct amount with the help of climate change scenarios. Hydrometric and climatology data of 21 years (1998-2019) were used to investigate the effects of climate change on the water resources of the basin. These changes (temperature and rainfall) were investigated using the data of minimum temperature, maximum temperature and rainfall, and using the LARS-WG model, the climate change of the Tejn basin was simulated using the CMIP5 atmospheric general circulation model and RCP2.6, RCP4.5 and RCP8.5 climate scenarios in 2050-2030. became The evaluation results of the CMIP5 atmospheric general circulation model in the base period have the highest correlation and agreement compared to the synoptic and rain gauge station statistics based on temperature and precipitation components in Naz and Darab stations, respectively. In the period from 2030 to 2050, under the RCP 2.6, RCP 4.5 and RCP 8.5 scenarios, an increase of 2-10 and 2-20 percent of precipitation has occurred in some months in Pol Safid and Tajen stations, respectively. But in most of the months, we have also faced constant or sometimes 2 to 10 percent decrease in rainfall, which has caused a decrease in runoff due to the implementation of water resources development projects in the region. The results of the runoff analysis in the climate model under scenario 4.5 have been that the amount of runoff has decreased in most months, and this percentage difference is very small, but in scenarios 2.6 and 8.5, .

There are many applied experiments that, for unknown reasons, have a disappeared observations. Some of these limitations are: little opportunity to announce the results. not having access to all the units or being disappointed with the result of all the units. These factors cause the researcher may not have access to all the studied data. There are some experiments where have been done sequentially, and only record-breaking data are observed. These types of data have been used in a wide variety of practical experiments, such as oil and mining surveys, quality control, hydrology, sports achievements, seismology, the strength of materials, economics, industry, and climatology. An observation is called an upper record valueif its value exceeds all previous observations. An analogous definition can be given for lower record value. The record ranked set sample (RRSS) scheme, has been formally proposed by Salehi and Ahmadi, 2014 . Among the authors who worked on this scheme, Salehi and Ahmadi (2015) considered the estimation of stress and strength using upper RRSS from the exponential distribution. They also, with the collaborationof Dey (2016), made a comparison between RRSS scheme and the ordinary record statistics in estimating the unknown parameter of the proportional hazard rate model. They showed that the RRSS scheme outperforms the ordinary record statistics in the frequentist/Bayesian point and interval estimation under that family of distributions. Safaryian et al. (2019) proposed some improved estimators, including the preliminary test estimator, as well as a stein-type shrinkage estimator for stress-strength reliability using record ranked set sampling scheme. Recently, Sadeghpour et al. (2020) considered the estimation of stress and strength reliability using a lower record ranked set sampling scheme under the generalized exponential distribution. To introduce lower RRSS scheme, suppose we have n independent random sequences where the ith sequence sampling is stopped whenever the ith lower record is observed. The only observations available for analysis are the last lower record value in each sequence. This process is called lower record ranked set sampling scheme or (RRSS). Among the authors who worked on this scheme, Ahsanullah (1995), Arnold et al. (1998), Paul and Thomas (2017) , Salehi et al (1998) , Nevzorov (2001) and Gulati and Padgett (2003). Nowadays, climatic factors directly affect human life. Therefore, to different planning, the role of the parameters of climatic as an influencing factor in the execution process of the plans is worthwhile. One of the important aims of climatology, is to get an estimate of the unknown parameters of model. In such situations, considering appropriate estimators and sampling schemes, in order to reduce the cost and increase the accuracy based on information from the sample are important. In this research, based on RRSS scheme, the problem of Bayes estimation and maximum likelihood estimation of the parameter of generalized exponential model is studied. The Bayesian approach, as an alternative to the classical approach, is in statistical inference. Its principle is to incorporate the information in the parameters’ history through a prior distribution assuming, a known form of distribution. The parameters of a prior distribution called prior parameters. In the Bayesian inference, the performance of the estimator depends on the prior distribution and also on the loss function used. A symmetric loss as Square error loss function is found in different fields. The symmetric nature of this function gives equal weight to overestimation as well as underestimation, while in the estimation of parameters of lifetime model, overestimation may be more severe than underestimation or vice-versa. An asymmetric loss function, is also useful. For example, in the estimation of reliability and failure rate function, an overestimation is usually much more serious than underestimate .Using a Monte Carlo simulation, for both estimation methods, namely Bayes estimation and maximum likelihood estimation, the risk criterion estimators are computed and evaluated. Finally, the results are checked by analyzing real data of temperature ‎record ‎values‎ related to on a daily time scale from the month of January during the years 2018 to 2021 which were obtained from the meteorological station of Sari city in Mazandaran province. The results demonstrate the Bayes estimates are generally, better than the maximum likelihood estimates, and all estimates improve by increasing record values. It is recommended to use the RRSS scheme if conditions are ready for the RRSS scheme.

Changes in hydrological-climatic series can occur in different ways. Change can occur suddenly or gradually (trend) or in more complex forms. In general, trend analysis is performed to obtain information and study whether a trend or a pattern can be extracted from this information. Information about precipitation trends is important, because precipitation trends are related to water-related problems in the region, environmental and water management goals. This information will be the most valuable when studying climate change and its effects on water resources management. Determining the precipitation trend has been one of the most important activities of hydrologists and meteorologists in advancing climate change studies. In addition, the study of climate change requires information on the trend of various indicators (hydrological and climatic) because climate change is a continuous change. Almost all water and meteorological parameters are affected by climate change phenomenon. Precipitation is one of these variables that strongly affects the environment and the hydrological cycle. The temporal changes of precipitation are important both from scientific and practical point of views, since they strongly affect water resources. Therefore, studying the process of these changes is very important for short-term and long-term management planning. The importance of this study increases when we face time and place limitations of rainfall in an arid and semi-arid region like Iran and especially in Fars province. Therefore, in the present study, the 30-year trend of precipitation was investigated in 27 rain, synoptic and evapotranspiration stations in Fars province. The study of rainfall changes was done at annual and seasonal and at both stational and regional scales. At the first step, monthly precipitation data was gathered from meteorological organization and water resources management company. Then monthly data was converted to seasonal and annual data sets. Mann-Kendall methods, age slope estimator and linear regression analysis were used to conduct at point analysis. In order to study the rainfall trends at regional scale, first, the study area was clustered based on mean seasonal and annual precipitation using the K-mean clustering method. It is worth mentioning that for each season and annual, separate homogenous regions were formed. Then regional Mann-Kendall method was utilized to investigate the trends in each homogenous region. On an annual scale, a decreasing trend of precipitation was observed at all stations. But Arsanjan, Berghan, Tangab Firozabad and Farashband stations are the only points whose rainfall trends are significant at the 95% confidence level. On a seasonal scale, a decreasing trend of precipitation was observed in almost most seasons and most of the stations. Except for the summer season, when we see a very slight increase in the majority of the stations. In spring and summer, respectively, 48% and 67% of the stations witness a decrease in precipitation, but these trends are not significant. In the autumn season, 74% of the stations experienced a negative trend of precipitation, and among these stations, Arsanjan, Berghan, Shiraz, Farashband, Kazeroon, Madersaliman and Zarghan witnessed a significant decreasing trend at the 95% confidence level. At the regional level, on annual and seasonal scales, the entire province has seen a decrease in rainfall, especially in winter and annual rainfall. This decrease in rainfall in the northwest of the province is a little weaker than other parts of the province. In the spring season, decreasing changes were observed, but these changes are not significant. In the summer season, a significant increase was seen in rainfall in the southern part of the province. This may be due to the increased activity of the Indian Monsoon. In the autumn season, a decreasing trend in the whole province was experienced, which is not significant. Similarly, the winter season also a decrease in precipitation was observed, with the difference that this trend is significant at the 95% confidence level. In general, all point and regional analyzes show a decrease in precipitation, especially in the annual and winter scales. On the other hand, there are signs of an increase in rainfall in the summer season. Considering that most of the province's annual rainfall occurs in the winter season, the decrease in rainfall in this season can have irreparable negative effects, which of course it has done so far. Therefore, it is expected that more attention must be paid to the planning of the water management and agriculture. In addition, due to the signs of increased rainfall in the spring and summer seasons, there should be sufficient attention to the problem of flooding in these seasons and the resulted damages, and in general, the comprehensive management of water resources in these changing conditions should be seriously considered so that the minimum losses and maximum benefits could be obtained.

Introduction:

Global warming due to greenhouse gas emissions is leading to changes in the spatial and temporal distribution of water resources on a global scale. On the other hand, as Iran is located in an arid and semi-arid climatic region, about 75% of rainfall in the country is directly returned to the atmosphere through evaporation. Since potential evapotranspiration is one of the most important components of the natural water cycle and is the identification of plant water requirement, its exact estimation plays a key role in the planning related to the type of cultivation and irrigation. Based on the literature, the Mann-Kendall test has been used repeatedly to examine the trend of changes in meteorological components. Considering the importance of determining the trend of evapotranspiration changes in water resources planning, the purpose of this study is its investigation in a monthly timescale using Mann-Kendall test and the Sen’s estimator slope in Iran. In addition, by analyzing the spatial distribution of evapotranspiration using the GIS, the trend of evapotranspiration changes was also examined.

The study area in this research includes 79 appropriately distributed synoptic meteorological stations with acceptable data quality which belong to the Irainan Meteorological Organization. Their common statistical period is 22 years (1995 to 2016). From a geographical point of view, Iran is located in the northern hemisphere between 25 and 40 degrees north latitude and between 44 and 63.5 degrees east longitude. It has a dominant arid and semi-arid climate with low rainfall and high evapotranspiration. After selecting synoptic stations, the required data including geographical coordinates of stations, altitude, daily temperature (minimum, maximum, and average), wind speed, and sunshine hours were collected for the common time period (1995 to 2016). Then, the potential evapotranspiration was calculated using Hargreaves-Samani method and the total monthly evapotranspiration was extracted for the desired time period. By performing the Mann-Kendall test, the trend of evapotranspiration variation has been estimated and the significance of this trend has been analyzed using the Sen’s estimator slope.

The results of this study obtained by the analysis of the evapotranspiration trend during 1995 to 2016 and implementing the Mann-Kendall test and the Sen’s estimator slope on a monthly time scale show that the trend does not follow the same pattern during different months of the year. In terms of time, in spring and summer, significant increasing trends have been seen in most cases where its highest were in June. In July, different climates of Iran have a significant increasing trend. Due to low rainfall in this month and sensitive conditions, this increasing trend of evaporation can raise the demand for water resources and in some cases reduce the yield of agricultural products. In August and September, despite the oppressive heat, in most of central and southern parts of the country, with a hot and dry climate, there was a decreasing trend of evapotranspiration. At the beginning of autumn and in October, the central parts of Iran had a significant downward trend, but in November and December, the existence of significant trends is much less. In winter, there is no trend in most stations. Generally speaking, the most significant increasing trends have occurred in the warm months of the year. Due to the decrease in precipitation oscillations and increase of temperature in these months, increase of evaporation has raised the water needs for agricultural products. Thus, the failure in its management will lead to a shortage of available water and damage to agriculture by the reduction of crop efficiency and yield. From spatial viewpoint, there is a more increasing trend in the cold regions and mountainous areas of the country and a negative trend has appeared in the tropical, central and eastern regions. In general, the percentage of non-trending stations varies from about 68% in summer to about 86% in autumn, and on average, about 78% of stations have a steady state about the evapotranspiration. Of the remaining 22% of stations, most (about 15%) have an increasing trend, and this goes back to the spring and summer seasons. This means that the plants’ water requirement is increasing when there is less rainfall, which is consistent with the conditions created by climate change, which leads to more severe drought events in arid areas.

Nowadays, the issue of thermal comfort has been raised as one of the important factors in the quality of urban spaces along with physical factors, so that not paying attention to it, causes these spaces not to be used and confined so that a space where all physical factors to use It has citizens in it, it is not used due to not considering thermal comfort. In fact, it can be said that observing the thermal comfort of open urban spaces is also important for the use of citizens and should be taken into consideration. On the other hand, due to the impact of various factors and parameters in urban open spaces that affect the thermal comfort of users and the lack of codified principles in this field has made it difficult for designers to identify and meet climatic needs in an urban area. The present study, considering the discussion of thermal comfort in urban sidewalks, investigates climatic and environmental factors in the area in which this study is located in the city of Khorramabad and in the area of ​​the celestial sphere and through the application of energy simulation technique by software. Envy Matt, which is an application software in the design of open urban spaces according to climatic conditions, uses an analytical method to study the thermal comfort index (PMV, average vote prediction), which is one of the important indicators in measuring thermal comfort in spring, and In the end, the results obtained in the simulation, which includes all different parts of the sidewalk, showed that factors such as choosing the direction of the sidewalk, the width of the sidewalk, the presence of trees, shade and water, and walking time in terms of thermal comfort. The sidewalk has been impressive.Optimal public and open urban space can be the bedrock of various positive effects on the city. One of the positive effects that increases people's face-to-face meetings are sidewalks. The consequence of this effect is an increase in social interactions. Accordingly, urban spaces are the arena of human interaction in which the story of collective life is opened, a space in which all people can be present and active (Lang, 1987). Riversides are a type of sidewalks that are necessarily formed on the banks of rivers, and for this reason, their special geographical location and their proximity to the fluid nature of the river, puts riverbanks in the group of sidewalks with special qualities. The presence of citizens in two groups of cavalry and pedestrians and different speeds is another feature of riverside spaces. Flexible nature, gentle breeze, soft stretches, dense vegetation, wide landscape and bright light and various colors all create an energetic atmosphere that is perfected by the presence of different groups of people.Although determining all the factors affecting rivers is a significant task, "climate and environmental comfort" seems to be much more effective. Thermal comfort is the condition in which the comfort of a thermal environment is provided for humans (Hansen, 1990). Cremona mentions comfort as a basic need in public space, noting that without comfort, it is difficult to find how other needs of space can be met (Carmona, 2007). Therefore, the equilibrium relationship between the presence of people and having climatic and environmental comfort to create a public and open urban space can play an effective role because public space that can not provide comfort is less used and even avoided (Lenzholzer). , 2012). Field studies on the Khorramabad River show that factors such as "temperature" and "radiation" are among the climatic factors that increase the spatial quality of the river.The issue of increasing the quality of various urban spaces has always been a significant issue for urban designers. Due to the close interaction between the man-made environment and the pristine nature, the rivers are a suitable place to join these spaces to other functional spaces of the city and the possibility of greater productivity and continuous presence of citizens in this part of the city.The purpose of this study is to investigate the climatic and environmental comfort of sidewalks in Rudkenar in order to find the factors that have the greatest impact between humans and the environment in open urban spaces and ultimately increase the presence in these spaces, which is the purpose of this study. The need for this research is also due to the fact that open urban spaces are a large part of the city that are often used with very practical functions such as sales, access to indoor and semi-open spaces and passenger traffic. The use of urban open spaces as a place for recreation, leisure and relaxation is an approach that, along with other uses, increases the presence of citizens.1-1. Problem definition and research backgroundIn recent decades, several models have been defined to estimate the energy balance of the human body in different environments to assess thermal comfort. Most of these models include meteorological components and environmental reflection (Fanger, 1972). In addition to meteorological components, the models also include the average radiant temperature, which plays an important role in the heat balance of the human body in summer and in urban environments. This temperature shows the effect of radiant energy from the environment on the exchange of radiation between a person and the surrounding environment (Heidarinejad and Delfani, 2009). Among the researches done on thermal comfort in open urban spaces can be a research entitled "Microclimate and thermal comfort in open spaces of sidewalks" by Patvin and Ahmad Omar (Ahmad Amr Patvin, 2007) with the aim of examining different urban spaces in order to evaluate Thermal comfort conditions in Quebec, Canada were performed on three open spaces in Boston, a dense commercial area and a high-rise urban area. In this study, urban morphological characteristics such as height and height, porosity, density

The Intergovernmental Panel on Climate Change (IPCC) has observed that climate variable changes associated with global warming are affecting different sector of human society. Changes in precipitation and temperature are anticipated as direct driving factors because they are the main factors that impact regional hydrological processes.The general circulation models (GCMs) are the most important tool for predicting the future climate change, which can reproduce important processes about global and continental scale atmosphere and project future climate under the different scenarios.The use of climate model simulations is now widespread, but there's still a risk in using these data, given the existing biases as well as the inability of these models to represent regional topography and land-sea contrast properly due to the coarse resolution of GCMs which makes local climate projection a huge challenge. Teutschbein and Seibert (2012) state that simulations of temperature and precipitation using GCMs often show significant biases due to systematic model errors or discretization and spatial averaging within grid cells, which hampers the use of simulated climate data as direct input data for climate change studies. Bias correction procedures are used to minimize the discrepancy between observed and simulated climate variables on a daily time step so that the corrected simulated climate data match simulations using observed climate data reasonably well. Many bias correction methods, ranging from simple scaling techniques to the rather more sophisticated distribution mapping techniques, have been developed to correct biased GCM outputs.This study aims to select the best model and bias correction method based on different statistical metrics to downscale the daily precipitation and Maximum and Minimum temperature (Tax and Thin) outputs of selected CMIP6 models for Mashhad and Goldmkan synoptic stations, which are located in the Kashaf Rroud basin.

For this study, daily observations of precipitation, minimum temperature and maximum temperature during 1989-2019 of two synoptic stations in the Kashaf Roud basin were used. Over the last few years, the Copernicus database has been of great help to researchers in the field of climate change studies for the preparation and aggregation of climate data, observational data, satellite data, etc. This database has enabled researchers to pre-select models as well as specify the desired time and place. The historical CMIP6 data have been download from the Copernicus Climate Data Store (CDS).First, the precipitation and temperature time series were qualified. RHtests-dlyPrcp and RHtestsV4 packages in the R software environment were then used to test the homogeneity of the precipitation and temperature daily time series.CMhyd (Climate Model data for hydrologic modeling) is a software that has been used to extract and bias-correct data obtained from the selected global climate models using three statistical methods e.g., linear scaling (LS), distribution mapping (DM) and delta change (DC). The bias, RMSE, Pearson, Spearman and Kendall correlation coefficients and the Taylor diagram were used to determine the accuracy of the results of each model and to select the best method to downscale the daily and monthly outputs of GCMs. There are two sets of data in the CMIP6 simulations:2-1. Historical data Historical data of CMIP6 covers the period of 1850-2014, which can be used as a reference period to compare and verify the performance of each GCM.2-2. Scenarios dataSSP scenarios provide different pathways for future climate forcing. They typically cover the period 2100-2006.

In this study, daily precipitation and temperature time series from two synoptic stations, Mashhad and Golmakan, located in the Kashaf Roud basin, were first used as primary quality control. Then the homogeneity of these data was tested. Maximum and minimum temperatures and precipitation in Golmakan were homogeneous. Mashhad was homogeneous for precipitation and minimum temperature time series, but for maximum temperature it had a change point on 09/30/1994, which was homogenized in the series and then used. The large-scale data of precipitation and temperature of three models have been scaled down to the level of the stations using three statistical methods and have been corrected for bias. Root-mean-square error (RMSE), correlation coefficients (Pearson, Spearman and Kendall) and bias (RB) were calculated to determine the accuracy and performance of each model and each exponential downscale method. In a further step, the daily time series of these data were converted to monthly data, then all validation process were done for monthly data in order to make a better and more comprehensive decision based on these results.Among downscale results of rainfall and temperature using LS, DM and DC methods; in all models and at both stations for daily and monthly rain; LS method showed better results. However, the DM method gives better results for the maximum and minimum temperature data (except for the minimum temperature in the ACCESS-CM2 model, where the LS method is slightly better for both Mashhad and Golmakan). With a difference of 1.6 mm in the DM method, the largest bias in the monthly precipitation data for Mashhad is observed in the MIROC6 model.

The results of this research show that LS for precipitation and DM for temperature will have higher accuracy in the Kashaf Roud basin. MRI model performed better for precipitation and maximum temperature using LS method, however ACCESS performed better for minimum temperature in these stations. Exponential down scaling using the DM method gives better results for precipitation in Mashhad for the MRI model and in Goldmkan for the ACCESS model. MRI gives better results at Mashhad and MIRO at Goldmkan. The DM method also simulates more accurate results at both stations of the MRI model for the minimum temperature. Therefore, the MRI model is ranked first and ACCESS and MIRO are ranked second and third, respectively, if we want to select a comprehensive model among these three models that has the best simulations of precipitation and temperature.

Beng today, human bioclimatic studies are the basis of urban planning, housing, architecture and more.In all of these studies, attention is paid to the interiors and its influence on the climate of the area in question, so tat the climate in turn influences the design of the building. The research metod in this study is based on Evanz modeling and using data Fifty Years (1966-2010) is the Ahvaz Synoptic Weather Station.And human comfort or lack of comfort in this climate was investigated based on the above modeling. The results show that the city of Ahnaz enjoys very hot to cool conditions throughout the year. It is out of the climate comfort zone during the winter and summer reasons and with the onset of spring and autumn seasons in the transition from cold to heat (April) and heat to cold (November) the climate of Ahvaz is approaching human conditions. Summary, it results that approximately9months of the year during the night without the use of mechanical devices and merely considering the materials appropriate to the climate and olso consider how elements in the city of Ahvaz are comfortable condition.Beng today, human bioclimatic studies are the basis of urban planning, housing, architecture and more.In all of these studies, attention is paid to the interiors and its influence on the climate of the area in question, so tat the climate in turn influences the design of the building. The research metod in this study is based on Evanz modeling and using data Fifty Years (1966-2010) is the Ahvaz Synoptic Weather Station.And human comfort or lack of comfort in this climate was investigated based on the above modeling. The results show that the city of Ahnaz enjoys very hot to cool conditions throughout the year. It is out of the climate comfort zone during the winter and summer reasons and with the onset of spring and autumn seasons in the transition from cold to heat (April) and heat to cold (November) the climate of Ahvaz is approaching human conditions. Summary, it results that approximately9months of the year during the night without the use of mechanical devices and merely considering the materials appropriate to the climate and olso consider how elements in the city of Ahvaz are comfortable condition.Beng today, human bioclimatic studies are the basis of urban planning, housing, architecture and more.In all of these studies, attention is paid to the interiors and its influence on the climate of the area in question, so tat the climate in turn influences the design of the building. The research metod in this study is based on Evanz modeling and using data Fifty Years (1966-2010) is the Ahvaz Synoptic Weather Station.And human comfort or lack of comfort in this climate was investigated based on the above modeling. The results show that the city of Ahnaz enjoys very hot to cool conditions throughout the year. It is out of the climate comfort zone during the winter and summer reasons and with the onset of spring and autumn seasons in the transition from cold to heat (April) and heat to cold (November) the climate of Ahvaz is approaching human conditions. Summary, it results that approximately9months of the year during the night without the use of mechanical devices and merely considering the materials appropriate to the climate and olso consider how elements in the city of Ahvaz are comfortable condition.Beng today, human bioclimatic studies are the basis of urban planning, housing, architecture and more.In all of these studies, attention is paid to the interiors and its influence on the climate of the area in question, so tat the climate in turn influences the design of the building. The research metod in this study is based on Evanz modeling and using data Fifty Years (1966-2010) is the Ahvaz Synoptic Weather Station.And human comfort or lack of comfort in this climate was investigated based on the above modeling. The results show that the city of Ahnaz enjoys very hot to cool conditions throughout the year. It is out of the climate comfort zone during the winter and summer reasons and with the onset of spring and autumn seasons in the transition from cold to heat (April) and heat to cold (November) the climate of Ahvaz is approaching human conditions. Summary, it results that approximately9months of the year during the night without the use of mechanical devices and merely considering the materials appropriate to the climate and olso consider how elements in the city of Ahvaz are comfortable condition.

Dust, one of the most important known atmospheric phenomena and natural disasters, has attracted the attention of many thinkers and researchers in various branches of science, including atmospheric science. The origin and mechanism of formation, transmission, and diffusion, as well as the consequences of this phenomenon, are studied with various techniques and methods. Countries located in the arid and semi-arid belt of the world, including Iran, have always been involved with the phenomenon of dust. The occurrence of successive droughts in recent years and the possible consequences of climate change in the field of desertification have made dust storms the focus of many researchers' attention (Shahkoi and Rahmani, 2018).

For 18 selected stations in the annual time series (1979-2018), first, the statistics of both Mann-Kendall and Sen,s slope non-parametric tests were calculated. After that, the significance of their results was tested at the 95% confidence level. In this research, to evaluate the frequency of days with dust, weather codes 06 and 07 were prepared in the west of the country, and maps of days with dust were drawn. In this way, the mentioned maps were analyzed on the annual and seasonal scale of codes 06 and 07 using the IDW interpolation method in the ArcGIS 10.7 software environment. In addition to that, the trend of changes in the days with the dust of weather codes 06 and 07 during 40 years was analyzed based on the non-parametric Mann-Kendall and Sen,s slope statistical methods, as well as the charts for determining the 40-year jump points of codes 06 and 07 using the method Mann-Kendall was evaluated. Finally, codes 06 and 07 were interpolated annually and seasonally by the IDW method in the ArcGIS 10.7 software environment.

Based on the findings of the present research, the frequency of annual occurrence of codes 06 and 07 (1979-2018) in the west of Iran showed that in code 07, the highest amount of dust phenomenon is related to Sanandaj and Kermanshah stations, and in code 06 stations Sanandaj, Kermanshah, and Abadan are the most abundant. The results of the frequency of seasonal occurrence of code 06 showed that dust covers a larger area in the spring season. In the summer season, there is more dust phenomenon in the northeastern parts of the region. And in the autumn season, a noticeable decrease in the frequency of dust occurrence was observed. Finally, the frequency of dust occurrence has decreased in the winter season as well as in the autumn season. The results of the frequency of seasonal occurrence of code 07 also indicate that the dust phenomenon was the most frequent in the spring of Sanandaj and Saqqez stations. And the lowest frequency of occurrence in spring is assigned to Ramhormoz station. In the summer season, more dust phenomenon occurred in the northeastern parts of the region, i.e. Bijar and Qorveh stations. Significant decreasing trend; In both codes 06 and 07, Dezful and Ramhormoz stations show a decreasing trend. a significant trend of increase; It includes the stations of Abadan, Bandar Mahshahr, Dehlran, Sara Roud, Saqqez, and Sanandaj in code 06. And in code 07, Bijar, Ravansar, Sarpol Zahab, Saqez, Sanandaj, Qorve, and Kangavar stations have a significant increasing trend. The jump graphs of dusty days in code 06 of Abadan and Sanandaj stations showed an increasing trend, and in code 07, the mentioned stations continued to show an increasing trend for most of the years.

The significant increasing trend of the phenomenon of dust showed that the highest frequency of occurrence in the stations of Abadan, Bandar Mahshahr, Dehlran, Sara Roud, Saqez, and Sanandaj in code 06 and code 07 Bijar, Ravansar, Sarpol Zahab, Saqez, Sanandaj, It has been Qorve and Kangavar. A significant decrease trend of codes 06 and 07 have occurred in Dezful and Ramhormoz stations. The results of the annual charts for determining the mutation points of code 06 during the last 40 years in Abadan and Sanandaj showed that the increasing trend has increased in recent years. And in code 07, the mentioned stations have continued to increase in most of the years. According to the distribution of stations with significant trends in western Iran, it can be concluded that the trends are subject to a certain order. In code 07, on an annual scale, the highest amount of dust is related to Sanandaj and Kermanshah stations, and in code 06, Sanandaj, Kermanshah, and Abadan stations have the highest frequency. The reason for the occurrence of more dust in the spring season should be considered to be the combined factors and the exit of the western winds from the country. In the summer, the very dry air dominating the deserts of the neighboring countries causes the instabilities of these regions to turn into dust. In autumn and winter, which coincides with the arrival of external systems with instability and humidity in the country, a decrease in the frequency of dust occurrence is evident in some study stations.

Estimation of plant water requirement under climate change conditions is important for planning in the direction of irrigation principles and water resources management in the agricultural sector. Cotton is one of the most important industrial products in the country. In this study, based on the data of meteorological stations in the base period and the output of total atmospheric circulation models from the next period to 2060, ETo changes and deviations and the water requirement of cotton crop in Khorasan Razavi were investigated. Evaluation of the province based on observational data showed that most of the province's rainfall occurs in the cold period of the year, especially in March or March to late April and mid-May. Examination of the simulated data showed that in the next period up to 2061; the amount of air temperature in the region will increase. Monthly precipitation in the period (2020-2040) decreased compared to the base period, but in the decades (2041-2061) increased compared to previous decades and reached close to normal. In fact, in the near decade 2060, the amount of rainfall will increase slightly compared to the next decades; These conditions can not be stabilized due to the increase in air temperature, a slight increase in precipitation. Studies have shown that the amount of Eto or reference evapotranspiration in the future period will increase compared to the base period and the past due to the increase in air temperature. Based on the increase in reference evapotranspiration, the water requirement of cotton growth stages, including the initial, intermediate and final stages, will also increase. In terms of length of growth period; The highest amount of water requirement will occur in the middle period of cotton growth. In terms of spatial distribution and dispersion; The northern half of the province and the center of the province have the highest amount of reference evapotranspiration and water requirement due to altitude and mountainous conditions (Quchan, Dargaz, Chenaran, Neishabour and Torbat Heydariyeh). The need for serious attention to the optimal management of water resources and planting resistant crops with higher adaptability is important.Estimation of plant water requirement under climate change conditions is important for planning in the direction of irrigation principles and water resources management in the agricultural sector. Cotton is one of the most important industrial products in the country. In this study, based on the data of meteorological stations in the base period and the output of total atmospheric circulation models from the next period to 2060, ETo changes and deviations and the water requirement of cotton crop in Khorasan Razavi were investigated. Evaluation of the province based on observational data showed that most of the province's rainfall occurs in the cold period of the year, especially in March or March to late April and mid-May. Examination of the simulated data showed that in the next period up to 2061; the amount of air temperature in the region will increase. Monthly precipitation in the period (2020-2040) decreased compared to the base period, but in the decades (2041-2061) increased compared to previous decades and reached close to normal. In fact, in the near decade 2060, the amount of rainfall will increase slightly compared to the next decades; These conditions can not be stabilized due to the increase in air temperature, a slight increase in precipitation. Studies have shown that the amount of Eto or reference evapotranspiration in the future period will increase compared to the base period and the past due to the increase in air temperature. Based on the increase in reference evapotranspiration, the water requirement of cotton growth stages, including the initial, intermediate and final stages, will also increase. In terms of length of growth period; The highest amount of water requirement will occur in the middle period of cotton growth. In terms of spatial distribution and dispersion; The northern half of the province and the center of the province have the highest amount of reference evapotranspiration and water requirement due to altitude and mountainous conditions (Quchan, Dargaz, Chenaran, Neishabour and Torbat Heydariyeh). The need for serious attention to the optimal management of water resources and planting resistant crops with higher adaptability is important.Estimation of plant water requirement under climate change conditions is important for planning in the direction of irrigation principles and water resources management in the agricultural sector. Cotton is one of the most important industrial products in the country. In this study, based on the data of meteorological stations in the base period and the output of total atmospheric circulation models from the next period to 2060, ETo changes and deviations and the water requirement of cotton crop in Khorasan Razavi were investigated. Evaluation of the province based on observational data showed that most of the province's rainfall occurs in the cold period of the year, especially in March or March to late April and mid-May. Examination of the simulated data showed that in the next period up to 2061; the amount of air temperature in the region will increase. Monthly precipitation in the period (2020-2040) decreased compared to the base period, but in the decades (2041-2061) increased compared to previous decades and reached close to normal. In fact, in the near decade 2060, the amount of rainfall will increase slightly compared to the next decades; These conditions can not be stabilized due to the increase in air temperature, a slight increase in precipitation. Studies have shown that the amount of Eto or reference evapotranspiration in the future period will increase compared to the base period and the past due to the increase in air temperature. Based on the increase in

Evapotranspiration is one of the crucial parts of the water cycle balance. In Iran, the total annual rainfall is estimated at 413 billion cubic meters. According to an analysis, 296 billion cubic meters, or 72% of this amount, became out of reach due to evapotranspiration. Accurate estimation of evapotranspiration plays a crucial role in studies on the issues such as global climate changes, environmental evolution, and control of water resources. Due to the limited number of meteorological stations and the high costs and time of collecting ground data, using remote sensing techniques and satellite images to have accurate and appropriate outputs can be a suitable tool to determine the actual evapotranspiration rate. One remote sensing algorithm for estmating evapotranspiration is the Surface Energy Balance (SEBAL).

The SEBAL is a model based on image processing that includes twenty-five models for calculating the evapotranspiration (ET) rate as the remainder of the Earth's surface energy balance. This model was introduced by Bastiansen in the Netherlands and also developed for the Idaho Highlands based on measured evapotranspiration at ground level. The SEBAL model uses digital image information captured by the Landsat satellite or other remote sensing sensors capable of recording thermal infrared and visible and near-infrared radiations. The ET value per pixel (e.g., in 30 by 30 square meters of TM and ETM Landsat images) is calculated for the specific moment at which the photo is taken.The ET value will equal the net radiation minus the heat entering the soil minus the heat entering the air. Further details of this model have been provided by Bastiansen et al., but the general equation used by the SEBAL is as follows:LE = Rn – H – GWhere LE is the latent heat flux (Wm-2), which can be easily converted to ET; Rn is the net solar radiation (Wm-2); H is the sensible heat flux (Wm-2), and G is the ground or soil heat flux (Wm-2). From this formula, the formula can be inferred that the radiation that reaches the Earth's surface from the atmosphere is separated into three parts: a part of the Earth or soil is heated, another part of it near the surface of the Earth is heated, and the rest of the remaining energy is evaporated. The SEBAL aims to calculate the latent heat flux (ET), considering the actual ET. It should be noted that the essential accuracy of the results is for the LE or ET. It is affected by the accuracy of the shortwave band as well as the thermal band of the satellite. In the following equation, the net radiation from the surface energy equilibrium equation is calculated as:Rn= (1-α) Rs + (Lin-Lout)Where a is the surface albedo; Rs is the solar radiation (Wm-2); e is the reflection of the Earth's surface (emission), and Lin-Lout is the radiations entering and leaving the Earth in the form of long waves. A value is obtained by mixing spectral reflections from six shortwave bands on the Landsat satellite. Lin-Lout is also considered a function of the surface temperature, which can be extracted from the satellite image. The value of e is obtained by plant indices created from two short-wavelength bands. The potential importance of Rs per pixel with a definite slope can be determined using the precise sky theory curves. The soil heat flux or G can be obtained empirically using Bastiansen's et al. (1998).

According to the results obtained from analyzing the data and output maps captured by the Landsat satellite, and considering the LST map, in which green color indicates a deficiency and red color represents very high, there was an oscillating trend from 2000 to 2008. Still, according to LST maps, since 2010, there has been a sharp incremental trend, the peak of which has been in 2020, and the LST has reached its highest level. Such a trend has also been seen concerning the soil temperature map of Mazandaran province. A remarkable point about the increase in soil temperature is that it was significant and instantaneous in the fifth month of 2010, and the soil surface temperature has increased, just as in the LST, since 2010. Regarding the NDVI map of Mazandaran province, significant and impressive changes have occurred since 2012, and this trend has risen from this year until 2020. According to the maps obtained from the soil moisture in the province, the data show that oscillating changes occurred until 2012, and since the fourth month of 2012, the region's soil moisture has also increased. All the factors mentioned have a direct relationship with evapotranspiration. According to the results obtained and the increasing trends, especially from 2010 to 2020, there is expected to be an increasing trend for evapotranspiration using the SEBAL algorithm. The primary outcome of this research, which studies the changes in the evapotranspiration rates in Mazandaran province, is that: as expected, due to the increase in all the factors affecting the evapotranspiration increase, the results show that since 2010 the evapotranspiration trend has dramatically increased; Of course, due to the geographical location and proximity to the Caspian Sea, the evapotranspiration has always been relatively high, but there have been significant changes and a sharp increase from 2010 to 2020.

Proper temperature forecasting is of significant importance in adapting to climate change at local scales. For this purpose, in this research, feature selection is done using principal component analysis algorithm, then in the post-processing stage of the neural network, the group method of data modeling is improved using the water strider algorithm, so that the temperature prediction can be done optimally. In order to compare, the results show a decrease in mean square error of 0.0469 in the proposed method compared to the feature selection method using mlp.

 The presence of fog reduces the horizontal visibility to less than 1000 meters and disrupts air transport services and can make it impossible for aircraft to land and take off. Climatology of fog can help better diagnosis and prediction of fog. In this study, METAR data from 2005 to 2020 were used to detect fog events at Rasht Airport and according to the classification algorithm of Tardif and Rasmussen (2007), the types of fog events were determined. Then the fog climate was studied during the period. The results showed that in terms of frequency, the most common type of fog at Rasht Airport was radiation fog with 58.84% and Cloud Base Lowering (CBL) fog with 26.74% of all fog occurrences. The rarest type of fog was advection fog with 3.49% of all occurrences at this Airport during 16 years of study. These results are consistent with Tajbakhsh (2015).In terms of the duration of the fog occurrence, due to the long and heavy rains in this station, the radiation fog event was the longest type of fog events. Also, the duration of CBL fog event was shorter than other types of fog events. The second type of fog in terms of duration of occurrence was advection fog, which can be caused by the slow movement of the synoptic system to transfer moist air from the sea to the land (Tardif and Rasmussen, 2007). Advection and radiation fogs had minimum visibility of less than 100 meters for 50% of occurrences. Radiation fog had the lowest concentration so that only 50% of radiation fog events had visibility less than 400 meters.Precipitation fog had the lowest concentration so that only 50% of precipitation fog events had visibility less than 400 meters. The highest incidence of fog during the study years was at 00 GMT. This stems from the fact, the radiative cooling is the strongest in the hours before sunrise. The strong reduction of the temperature increases the relative humidity near to 100%. This trend of changes in the number of hours with fog event during the day and night is consistent with the results of studies by Tajbakhsh (2015) at Rasht Airport, Cséplő, et al. (2019) in Hungary, and Tardif and Rasmussen (2007) in New York. The monthly distribution of radiation fog showed that this type of fog event often occurs in autumn and winter to early spring (October to April). The minimum frequency of radiation fog was also observed in May to September. The maximum monthly frequency of advection fog was seen in early spring (March) and its minimum frequency was seen in April, June to September and November. Previous studies have shown that in early spring, with the increase of air temperature on land, the water temperature is lower than the air temperature on land and the conditions for the formation of advection fog are available (Roach, 1995; Cho, et al., 2000; Taylor, 1917; Klein and Hartmann, 1993). The monthly distribution of CBL fog showed that there was no occurrence of CBL fog in July to September. This type of fog starts in late autumn and continues until mid-spring. Boundary layer cooling is the most important process that causes fog in spring, while winter occurrences can be caused due to large-scale atmospheric systems (Tardif and Rasmussen, 2007). The monthly distribution of precipitation fog showed that the most occurrences are in winter season (January and February). Precipitation fog didn’t occurred in April to October. Since precipitation fog depends on large-scale factors (Tardif and Rasmussen, 2007), this type of fog is more common in autumn and winter. In terms of annual changes in the occurrence of fog, there was no significant trend in the number of fog hours during the studied years. In terms of fog concentration, the number of semi-dense fog events (visibility equal or more than 100 meters and less than 500 meters) at Rasht Airport was higher than fog (visibility equal or more than 500 meters and less than 1000 meters) and dense fog (visibility less than 100 meters) in all months. Also, most fog events had a minimum visibility of 100 meters and then 200 meters .