Аннотация:
Downscaling methods for predicting climatic variables such as temperature and precipitation have wide applications in environmental planning and management. In this research, the SDSM downscaling model was used to predict temperature and precipitation variables. The data used includes daily average temperature and precipitation from the Khorramabad synoptic station, NCEP data, and H3A2 data for the base period (1986-2015). Using the 31333 and 822 713 data, results for a 30-year period (2016-2045) were predicted and compared with the base period. The normality of the used data was examined and confirmed using the Shapiro-Wilk test. The aim of this research is to determine the impact of climate change on ecotourism in Khorramabad. Research findings showed that overall, the annual average temperature of the Khorramabad station in the period (2016-2045) increases by 2.12 degrees Celsius. The correlation and regression relationship between the base period data and the predicted period is positive and has significant changes. Considering the data output in the RAYMAN software for 15:30, taking into account the SET index, the comfort coefficient in terms of temperature range is from very cool to warm. Based on the research results, the best time interval for the presence of ecotourists in the city of Khorramabad during the predicted period (2016-2045) is the month of Farvardin, while the months of Mehr, Aban, Azar, Bahman, and Esfand range from warm to very cool. An important point is that based on the prediction made, the months of Aban, Azar, Bahman, and Esfand, which are in the second half of the year, will be suitable for ecotourism activities; this is while in the base period (1986-2015), ecotourism activities had significantly better conditions in the first half of the year. This alone tells of the significant role of climate change in the determining components of ecotourism in the city of Khorramabad, which must be considered by relevant managers and planners.
Автоматическая аннотация:
Rezaei, Maryam, Naitani, Mohammad, Abkar, Alijan, Rezaei, Mahsoomeh, Mirkazahi Rigui, Myri, 2004, Investigation of the efficiency of the Statistical Downscaling Model (SDSM) in predicting temperature parameters in two climates: arid and hyper-arid (Case study: Kerman and B), Watershed Management Research Journal, Year 5, No. 11, pp.
The results show that the highest temperature of the Khorramabad station is from late spring to early The impact of climate change on bioclimatism of Khorramabad city Zand and Hajeri 622 Chart 6: SET thermal sensitivity for the base period 2116-2145 Chart 1 indicates that from January, the Standard Effective Temperature increases from 2 degrees Celsius to 31 degrees Celsius in July, and then decreases from August to December.
The impact of climate change on ecotourism in Khorramabad city Zand and Hajeri 617 (Refer to page image) Chart 2: Comparison of monthly precipitation of observed, downscaled, and predicted data in the 31-year period (2016-2045).
(Refer to page image) Chart 1: Comparison of monthly temperature of observed, downscaled, and predicted data in the 31-year period (2016-2045) The impact of climate change on ecotourism in Khorramabad city Zand and Hajeri 615 In this research, after obtaining data from the (General Directorate of) Meteorology of Lorestan Province, the data were first organized in the Excel software environment, then analyzed and predicted in the SDSM software environment.
(
, 
, 
)
