Predict changes in climate parameters Lorestan Province in 50 years by using HADCM3
Abstract:
Introduction
The indiscriminate use of fossil fuels, changes in land use and population growth and increased industrial activities cause some changes in the Earth's climate events that increased climate extremes such as floods, storms, heat waves, droughts. It is the most important. Today, these variations are a major concern climatologists and atmospheric scientists has become.General circulation models of the atmosphere, can be used on a smaller scale are not, therefore, need to downscaling. Statistical downscaling models, the output of general circulation climate models using statistical methods to establish statistical correlation between atmospheric general circulation models output data period in the past with climate models stations in the network somehow, nearly as downscaling is very similar to the observed data at scale station. Statistical downscaling model studies made it possible to estimate the climate fluctuations that can weather data at appropriate spatial and temporal scale production. This feature helps to study climate variability at local and regional scale. Using the manufacturer of weather can be fine-scale atmospheric general circulation models to be output. One of the most common and the most appropriate method for assessing future climate, using general circulation models of the atmosphere. The main objective of these models, three-dimensional climate index is specified in the network. These models, the right tools and the ability to study and assess the risks of climate change such as occurrence of dry periods, storms and torrential rains and more. It also approved the use of scenarios Intergovernmental Panel on Climate Change, to be able to create long-term time series of temperature, minimum temperature, maximum temperature, radiation and evapotranspiration in the daily scale.
Materials and Methods
In this study, data for downscaling of general circulation models HADCM3 LARS-WG5 model, which is one of the most famous models are weather-generating random data is used. The model for daily precipitation amounts, minimum temperature, maximum temperature and radiation or sundial at one station and the next base can be used under all environmental conditions. In general, the data produced by LARS-WG model in three stages that include calibration data, evaluation and production of meteorological data for future periods. And remnant stations removed. After processing and sorting data and preparation of input files, the model was run for the base period. In the next stage using statistical coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE), which follows their relationship, to evaluate the data generated by the model and the actual data ( observed) were included in the base period. Then Normal monthly averaged model output and climate parameters in the 50-year period under study was based on climate change scenarios listed. The normal distribution for the series of wet and dry season, between monitored data and simulated using the Kolmogorov-Smirnof test was calculated.
In this study the performance of LARS-WG to produce data daily rainfall, maximum and minimum temperature and sunshine hours in the province were evaluated using changes in climate parameters were evaluated in the future. In the first model was implemented for the period 1961-2005 and average monthly climate observations and products mentioned parameters were compared. Correlation values using T-STUDENT test showed that the 99% difference between the actual data and data from the model does not exist. Mean monthly observation and meteorological variables produced using statistical parameters R2, RMSE, MAE also were compared and proved to be an efficient model for its daily production data. In the next step after ensuring efficiency in the simulation model meteorological parameters, data three scenarios A1B (middle scenario), A2 (maximum scenario) and B1 (minimum scenario) in the period 2005 to 2055 HADCM3 model with statistical model LARS-WG It was small scale.
Conclusion
The results showed that according to estimates of LARS-WG for the scenarios examined in future periods, the average maximum temperature of about 9.0 to 03/1 degrees, increase the amount of sunshine about 6/0 reduction in rainfall is about 12.4 percent will. The maximum temperature also changes less than the minimum temperature, increasing average air temperature during this period is expected. According to the results of climate Lorestan province in the next 50 years will be a significant difference with the current situation and long-term planning and strategic management of these conditions is necessary.
Language:
Persian
Published:
Journal of of Geographical Data (SEPEHR), Volume:26 Issue: 101, 2017
Page:
143
magiran.com/p1699024  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 990,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
دسترسی سراسری کاربران دانشگاه پیام نور!
اعضای هیئت علمی و دانشجویان دانشگاه پیام نور در سراسر کشور، در صورت ثبت نام با ایمیل دانشگاهی، تا پایان فروردین ماه 1403 به مقالات سایت دسترسی خواهند داشت!
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 50 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!