نشریه پژوهشهای تغییرات آب و هوایی
پیاپی 10 (تابستان 1401)

Increasing global warming is one of the major global issues of the current century. For this reason, it is important for humans to study and evaluate its trend, so simulating this climatic variable can be a way to understand the human future. There are several methods for simulating and predicting heat waves, the most valid of which is the use of the general circulation model of the atmosphere and GCM. One of the most widely used models for GCM data miniaturization is the LARS WG statistical model. In the present study, the efficiency of this model for exponential micro-scale of heat waves in Julfa station was evaluated. To achieve this goal, daily statistical average maximum temperature above 35 ° C in a given statistical period has been used. Also, to predict the heat waves in the coming years, the maximum temperature data of the models (CESM CAM, CMCC CMS, CAN ESM, MPI ESM) under the RCP8.5 scenario for the next period 2011-2016 were performed. The results showed that heat waves in the future period (2011 2065) have a normal distribution compared to the base period. . Therefore, these results show the very good performance of the LARS WG model in simulating heat waves. Jolfa station heat waves in the base periods (1990-2020), with severe irregularity and variability of annual heat wave events, indicate a strong variability of the average annual temperature and a variety of factors affecting the temperature of the region. On the other hand, according to the forecast of MPI ESM, CESM CAM and CMCC CAM climate models, the temperature of the annual heat waves that go towards more heat in the warm period;

To project the minimum and maximum temperatures of cold regions of Iran, the data of 28 synoptic stations of the country and the output of CanESM2 model from CMIP5 model series were used. Downscaling with SDSM statistical model is performed for the historical period (1991-2005) and five future periods (2040-2026, 2041-2055, 2056-2070, 2071-2085 and 2100-2086), under three RCP2.6, RCP4.5, and RCP8.5 scenarios. Four statistics of PCC, RMSE, MBE, and PBIAS were used to evaluate the minimum and maximum temperature of the SDSM model. The evaluation results of the SDSM model showed that this model has a relatively good performance in high latitudes and cold regions. However, due to the availability of only one GCM interface (CanESM2 model), assumptions of stationarity between the large- and small-scale dynamics, and relying solely on statistical relationships between observational data and GCM, are disadvantages of the statistical downscaling with SDSM and the results are associated with high uncertainty, comparing to dynamical or dynamical-statistical methods and ensemble models. The minimum and maximum temperature anomalies are positive in all five projected periods based on three scenarios of radiative forcing for the 21th century. The results of minimum temperature anomaly showed that the minimum of positive anomaly is observed in Yasuj station and the maximum of that is observed in Piranshahr station. Similarly, positive maximum temperature anomalies are observed in Tehran (Geophysical) and Tehran (Shemiran) stations. In general, the minimum and maximum temperatures under the RCP4.5 and RCP8.5 scenarios show a greater increase than the RCP2.6 scenario, especially for the northwestern regions of Iran. This result is important because with the faster melting of snow cover in cold regions, it is a potential threat to arid and semi-arid countries such as Iran due to reduced access to fresh water.

In order to investigate the status of atmospheric synoptic systems during the occurrence of severe rainfall anomalies in eastern Iran, the rainfall statistics of 31 meteorological stations located in the region during the statistical period (from 1990 to 2020) were used. In this regard, precipitation anomaly index (RAI) was used to identify these periods. To explain the structure of the atmosphere at the time of its occurrence by referring to the website of the National Center for Environmental Prediction/Atmospheric Science (NCEP/NCAR) networked data on geopotential height, sea level pressure, vertical velocity component (omega), Relative humidity, orbital components and wind meridian were obtained. Studies have shown that the occurrence of severe rainfall anomalies in eastern Iran is associated with the formation of a strong ridge in the middle of the atmosphere on the east of the Middle East. This causes a recurring current, or high continuity, to dominate the area. On the other hand, the advent of cold weather and the dominance of the north current to the region, the conditions of climbing and instability have been minimized. The location of the region below the upper convergence core of Rudbad is also one of the main reasons for the occurrence and continuation of severe rainfall anomalies in the region. In order to investigate the relationship between the major cyclones for rainfall, the two regions of the Red Sea and the Mediterranean were examined. The results of the study of the correlation between omega indices and the meridional component of wind on the Red Sea and Mediterranean corridors with sea level pressure on the region also showed that with decreasing ascent values in these areas and increasing pressure on eastern Iran, a correlation Positive is established.

This study investigated the performance of the Weather Research and Forecasting (WRF) mesoscale model in the simulation of microphysical parameters of a mesoscale convective system (MCS) event. This case study occurred during 13 April 2016 over the west and southwest of Iran and resulted in a flood in these areas. For all simulations, the WRF model uses a one-way nesting for three meshes of 36, 12, and 4 km horizontal resolution, respectively. In all simulations, the data from NCEP global final analysis (FNL) on 1-degree by 1-degree grids provide initial and boundary conditions. The results obtained from the model simulations are compared with the observations. The distribution of daily precipitation from the second domain of the model outputs showed the Morrison scheme has better performance in the simulation of maximum rainfall and spatial distribution of daily rainfall than the Thompson scheme.Comparison between the simulated daily precipitation in the third domain of all simulations and the observed daily precipitation at 40 synoptic stations in the study area shows that two schemes predict about half of the amount of rainfall in the region close to observational amounts for the mentioned day. Following, the time series of simulated values and station observations plotted for a variety of surface variables such as 2-meter temperature, relative humidity, and sea surface pressure for 13 April 2016 at Ahwaz station; it is possible to verify the model simulations for each of these parameters. The last section investigated several microphysical parameters from the two simulations to better understand the MCS properties. In examining the vertical profile of these microphysical variables, no noticeable difference was observed from the simulation compared with the two schemes. Almost similar concentrations and fall velocities show that the precipitation results from the simulations are comparable and slightly different.

In recent years, the phenomenon of drought has affected many watersheds in Iran and causes many changes in land use and lake area every year. This research tries to investigate the drought situation and its relationship with land use changes in the Abkhiz basin of Maharlo lake in the south of Iran by using the drought remote sensing indicators in the years 2000, 2010 and 2020. In this way, the drought condition was determined using EVI, NDVI, and VCI indicators, then land use maps for the years 2000 and 2020 were prepared using Landsat ETM+8 satellite imagery. In the following, using the regression method, the most important effective drought indicators for land uses were determined. Also, using Markov and Komarkov chains, the state of drought and land use indicators for 2040 was predicted. According to the results of the indicators, it was found that the southern parts are more at risk of drought than other parts. The results of the survey of land use changes showed that in 2020, compared to 2000, more lands were placed in the salty and barren classes. The results showed that according to the regression method, the most important indicators in relation to land use is the NDVI index. The results of Markov and Komarkov chain for predicting indicators showed that this method has acceptable accuracy. Thus, the Kappa coefficient for the VCI index is 0.98, which indicates the high accuracy of the model in predicting drought. Also, the maps predicted by this method showed that in 2040, the values of this index will decrease, which will indicate more drought in the region.

Climate change is one of the biggest challenges facing humanity that affects the sciences related to nature and environment. Changes in factors affecting climate change affect the hydrological responses of watersheds and this phenomenon affects the quantity and quality of water resources such as lakes, reservoirs and dams. Today, the development and progress of computer and computing technologies has had a significant impact on hydrological modeling. In recent years, conceptual and physical models based on the characteristics of watersheds for hydrological systems have attracted the attention of researchers. Due to the emergence of such developments, there will be complications in the process of hydrological modeling. Correct management forecasts in the field of water resources due to the lack of water resources, is one of the topics of interest in the institutions in charge of water resources management, which should use high-precision simulator models for long-term estimates and planning. Considering the crisis and shortage of water resources in Iran, the sub-catchment upstream of Zayandeh Rood Dam was selected as a case study in this research, and the hydrological processes in the sub-basins of Zayandeh Rood Dam were simulated and the inflow to the reservoir of Zayandeh Rood Dam was estimated. For this purpose, the water and soil assessment model SWAT has been used to simulate the rainfall-runoff process and finally to estimate the inflow to the reservoir. Based on the simulated runoff from the three sub-basins of Buin-Damneh, Qala Shahrokh-Chelgerd and Chadegan-Ceshmeh, the model showed acceptable results for the simulation in the three sub-basins mentioned by the model, and it was estimated from the algebraic sum of the three inflows that the mentioned error coefficients are equal to 0.86 has been obtained. This result shows the high accuracy of the models in the simulation