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Showing 6 results for Downscaling

Sh. Kouhestani, S, Eslamian, A. Besalatpour,
Volume 21, Issue 1 (6-2017)
Abstract

This study aims to investigate the changes of minimum and maximum temperature variables under the impact of climate change for time period of 2015-2100 in the Zayandeh-Rud River Basin. The outputs of 14 Global Climate Models (GCMs) under three green-house emission scenarios (RCP2.6, RCP4.5, and RCP8.5) are employed from the Fifth Assessment Report (CMIP5) of Intergovernmental Panel on Climate Change (IPCC). A novel statistical downscaling method using a Bayesian Relevance Vector Machine (RVM) is used to project the impact of climate change on the temperature variables at regional scale. The results of the weighting average of the GCMs show that the various models have different accuracy in the projecting the minimum and maximum temperatures in the study area. The results demonstrate that the MIROC5 and CCSM4 are the most reliable models in projecting the maximum and minimum temperatures, respectively. The highest increase for both maximum and minimum temperatures was obtained in winter.
    On the annual basis, the maximum temperature will increase by 0.18-0.76 °C and 0.25-1.67 °C, respectively, in the near and long-term future periods under different emission scenarios. The annual minimum temperature will increase by 0.28 to 0.82 °C and 0.24-1.56 °C, respectively, in the near and long-term future periods. In a general view, changes in maximum temperature will be slightly higher than minimum temperature changes in the future.
 


Dr. S. Akhavan, N. Delavar, Dr. A. M. Mehnatkesh,
Volume 21, Issue 2 (8-2017)
Abstract

The aim of this study was to investigate the climate change impacts on some factors affecting rainfed wheat growth such as effective rainfall, planting date and length of growing season in four stations located in Chaharmahal and Bakhtiari province. Firstly, it is necessary to predict future (2046-2065) climatic conditions. For this purpose, the output of HADCM3 general circulation model was used under three scenarios of A1B, A2 and B1. The data were downscaled by LARS-WG model. After simulating the climatic parameters in mention period, the effective rainfall during the wheat growing season was calculated by Food and Agriculture Organization method. Also, the optimum planting date was defined according to the date of the first rain (at least 10 mm in case of continuing for next days). The wheat's growth stages were determined by Growing Degree Days method. The results indicated a rise in temperature for four stations. On average, it is expected that the annual temperature increase by 1.8°C compared with the baseline period (2010-1990). Total annual precipitation in Shahrekord, Koohrang and Borujen will decrease 2.2, 7.8 and 3.6 per cent respectively. About Lordegan it will increase by 2.7 per cent. Also, the results showed that in three stations of Shahrekord, Koohrang and Borujen, the amount of effective rainfall in November will increase compared to baseline, but in Lordegan it will reduce. So, in the first three stations, in most years, planting date was obtained earlier than baseline, but in Lordegan it was later than baseline. The Length of growing season will reduce in Shahrekord, Borujen and Lordegan stations, 12 days on average and in Koohrang about 13 days.

H. Asakereh, A. Shahbaee Kotenaee, M. Foroumadi,
Volume 23, Issue 1 (6-2019)
Abstract

In the vast majority parts of the Earth, a prospect now visible is the mostly synthetic thinking and fabrication by the human hand. Collision and impact of humans on the natural environment in the short and long-term courses for obvious geographical features have changed a variety of spaces. One of the consequences of human impact on the natural environment during the current period is the phenomenon of climate change. One of the climatic parameters that plays an important role in agriculture, energy, urban, tourism and road transport is the minimum temperature. In this study, an attempt was made using the minimum temperature data from 5 meteorological stations in the West Mazandaran province, as well as HADCM3 model data, to show how to change this parameter in the future periods based on simulation by the SDSM model. Accordingly, after selection of the suitable climate variables and model calibration, the accuracy of the created model in the base period was evaluated; after ensuring the sufficient accuracy of the model according to A2 and B2 scenario, data minimum temperature in 2100 was simulated. Based on the simulation results showed that the values of minimum temperature in the region over the coming years would increase. This parameter was such that the average seasonal periods 2016 to 2039, 2040 to 2069 and 2070 to 2099, as compared to the baseline period would increase, on average, by 1.8, 3.5 and 6 percent. The largest increases in the minimum temperature in the western and southern parts of the region could occur. It was also found that unlike other months of the year, the minimum temperature in January would be a decreasing trend.

M. Farokhi, H. Ansary, A. R. Faridhosseini,
Volume 24, Issue 1 (5-2020)
Abstract

Estimation of soil moisture at various temporal and spatial scales is a key to the strategic management of water resources. Satellite-based microwave observations have coarse spatial resolution despite widespread and continuous of the provision surface soil moisture (SSM). In this study, the SSM data from the Advanced Microwave Scanning Radiometer 2 (AMSR2) 25km resolution were used and these products were downscaled by three parameters retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) to 1km resolution. In the next step, the integration of the SSM downscaling model with SMAR model was used to monitor the root zone soil moisture(RZSM) in the study area (Rafsanjan plain). In order to evaluate the performance of the proposed method, the SSM and the soil profile moisture were measured at 10 points in the Rafsanjan plain. Comparison of AMSR2 25k SSM and downscaled SSM with the field measurement data showed that the mean of total stations for the correlation coefficient(R) was increased from 0.540 to 0.739 and the mean absolute error(MAE) and the root mean square(RMSE) were reduced from 0.039 and 0.040 to 0.018 and 0.020, respectively. Moreover, the results obtained from the validation of the RZSM values showed that the proposed method could estimate the RZSM with high accuracy and indicate the variations.
 


F. Fathian, M. Ghadami, Z. Dehghan,
Volume 26, Issue 4 (3-2023)
Abstract

In this research, the trend of spatial changes in extreme indices of temperature related to the health and agriculture sectors such as the number of frost days, number of summer days, number of icing days, number of tropical nights, growing season length, diurnal temperature range, cold spell duration index, and warm spell duration index were investigated for 54 synoptic stations throughout Iran for observational (1976-2005) and future (2025-2054) periods. Daily maximum and minimum temperature data of three regional climate models namely, CCSM4, MPI-ESM-MR, and NORESM1-ME from the CORDEX project under RCP4.5 and RCP8.5 scenarios were downscaled for each station using a developed multiscale bias correction method. Then, trends and changes of extreme temperature indices were investigated using Mann-Kendall and Sen’s trend line slope methods. The results indicated that the warm indices such as the number of summer days and tropical nights indices have had a positive trend at most stations in both observational and future periods. In contrast, cold indices like the number of frost days have had a decreasing trend in most stations. The results of cold and warm spell duration indices showed that most stations have had no trend for both periods. The growing season length has increased in more than 60% of stations (45% having a significant trend) mainly located in the northern, northwestern, and western regions of the country. Based on the results, it can be concluded that without considering thoughtful climate adaptation measures, some parts of the country may face health risks and limited habitability and agriculture in the future.

M. Naderi, V. Sheikh, A. Bahrehmand, C.b. Komaki, A. Ghangermeh,
Volume 27, Issue 4 (12-2023)
Abstract

Greenhouse gases and the occurrence of climate change have occurred with the development of technology and the industrialization of human societies. long-term forecasting of climate parameters has always been interesting due to the importance of climate change for the earth and its inhabitants. General Circulation Models (GCMs) are one of the most widely used methods for evaluating future climate conditions. In the present study, the results of three general circulation models including the American model of GFDL-CM3, the Canadian model of CanESM2, and the Russian model of inmcm4ncml for the study area were evaluated and the CanESM2 model was selected as the superior model. The RCP scenarios 2.6, 4.5, and RCP 8.5 were used with the CanESM2 model to assess climate change conditions across the Hablehroud River basin for the period 2020-2051. According to the results, the total monthly precipitation shows an increasing trend in the coming decades 2020-2051 period compared to the period 1986-2017. The results of the study of temperature changes in the period 2020-2051 in the Hablehroud River basin also indicate an increase in the monthly average of maximum and minimum temperatures in the coming decades. The consequences of these conditions are of great hydrological importance in the study area, this condition necessitates the adoption of climate change adaptation policies in this watershed.


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