JOURNAL OF CLIMATE RESEARCH
Year:2018 | Volume:8 | Issue:31-32 |Papers Count:8

The temperature humidity index (THI) is one of the measures which describe the climatic discomfort as a result of combined effects of temperature and humidity. This index provides a rapid and accurate evaluation of heat stress effect on animal’ s health and productions. Considering the sequences of global warming and climate change, it is expected that THI values would vary due to changes in temperature and humidity in coming decades. As the soft computing skills increased in recent decades, more number of climate models has been developed for weather and climate predictions which have significantly improved the quality and resolution of projections. This remarkable increase in number of climate models has enabled the scientists to estimate a wide range of main climate variables such as humidity and temperature in fine temporal and spatial resolution. Upon release of new scenarios based on Radiative Forcing which are known as Representative Concentration Pathway scenarios (RCP scenarios), by Intergovernmental panel on climate change (IPCC) in fifth assessment report (AR5), a new set of climate models (GCMs) have been proposed for future climate projections. The main aim of this study is to investigate the temporal and spatial variations of THI values in selected weather stations across Iran as a result of climate change under RCP climatic scenarios proposed in fifth assessment report (AR5) of IPCC.

Satellite images show that WRF/CHEM model has simulated emission, source, diffusion as well as the extent of the areas covered with dust very well. Comparing PM10 concentration of the model outputs with Environment Organization data, show that WRF/CHEM model forecast daily changes very well. But model underestimate significantly in quantity of concentration. These errors may be are due to a model considering only dust quantity but other pollutants have affects on visibility. EURAD model has wrong prediction in dust storm sources and it simulates it in central of our country. In general, it can be said that in this event, dust concentration has been underestimated by WRF/CHEM model especially in maximum amount of PM10 concentration and EURAD model does not simulate dust concentration correctly in amounts and dispersion patterns.

In this study, using the theoretical basis, an algorithm was designed to identify southern system for the period of 1986-2015 which led to identification of 158 southern low pressure systems. Then two of them were selected for synoptic and dynamic analysis. According to the results, the designed algorithm has ability to identify southern systems. The results showed that formation and structure of southern low pressure systems were very similar to mid-latitude weather systems and differed from thermal low pressure systems. Strong baroclinicity, strong temperature advection in low levels, cold pool in mid-levels and cyclonic circulation in air columns are the most important characteristics of southern low pressure systems that are basically different from thermal low pressure systems.

Introduction: In the next decades, climate change is likely to have become a serious challenge that will alter flow regimes such as torrential flows (floods), low flows as well as the existing water resources. Climate change impact is increasingly becoming a subject matter for researchers, but the effect of this phenomena on the low flow is still not widely understood. The consequences of climate change have led the international community to further studies, which will affect the changes in the natural resources, ecosystems, and the population. Global climate cycle has been found to be intensified due to climate change, as well as it has led frequent, severe, long-term, and stable droughts in many regions. Changes in the precipitation and temperature as two major variables in the hydrological cycle will unbalance the rainfall. Also, climate change in the future decades will be very effective on high flows and low flows so that it will have a significant impact on the results of the intensity and recurrence Interval of low flows. The aim of this study is to evaluate the effects of climate change on the low flows using HEC-HMS model, as well as changes in the flow regime such as low flow frequency, the probability, and the recurrence Interval of low flow in the future period (2040-2069). Also, the uncertainties related to the downscaling methods are considered by using two statistical methods (SDSM model) and the change factor as well as it has utilized the outputs of the General Circulation Models, which are resulted from the fifth report of the IPCC. Material and methods: The Gharesou Sub-basin is located in the northwest of Karkheh basin. It covers an area of 5354 km2and its maximum and minimum height is 3364 and 1180 m, respectively. The average annual precipitation varies between 300 and 800 mm. Three major rivers of Merck, Gharesou, and Razavar are flowing into this basin. This study has measured the project of climate change in the Gharesou basin with CANESN2 and RCP scenarios and by using SDSM downscaling model as well as using change factor downscaling. Also, the indices of low flow frequency and FL method on the flows of the future period were analyzed. GCMs are the first tool for understanding past climate variations and predicting the projection for future climate conditions. GCMs demonstrate the atmosphere and ocean in a grid of 1 to 4 latitude degrees and in a longitude from 10 to more than 200 layers vertical in each fluid. Because of the spatial and temporal scale mismatch between the GCMs’ ability and the need of hydrological modelers, the outputs of these models cannot be explicitly used in climate change studies. Various methods of downscaling are used to overcome the problem, which dynamic, statistical, and change factor are three types of downscaling. The low flow selection is done by two different methods that are 7Q10 and FL methods. In fact, FL method is one of the five groups, which has been used in low flows and/or management balances of St. Johns River in Florida. Minimum Flows and/or Levels are low flows or levels that are needed to avoid serious damages to water resources caused by water withdrawals and they are divided into five following groups of flows. The first step in selecting the low flow is done by providing long-term flow data using FL method and then drawing the FDC curve. A low flow is obtained by drawing an FDC curve. FL method was chosen in order to select the low flows on the basis of the following reasons: 1. 7Q10 method for the extreme conditions of low flow, which is appropriate between 95 to 99% of the flow duration curve time. This condition usually occurs during a short-term severe drought and a very high recurrence Interval. 2. FL method is within the low flow selection domain and FL groups are clearly determined the effects of low flow on the floodplain, animal and plant life and ecosystems. Results and Discussion: The results of statistical method showed that basin flow has been reduced in all of the scenarios during the dry season, including July, August, and September. In addition, the results of the change factor suggested an increase in flow in the November, December, January and February and its decrease in the spring and summer. It is critical to note that both of downscaling methods indicated flow reduction in the low flow period. The value of the 7Q10 index in the statistical method and change factor has reached respectively, about 0. 008 m3/s and zero in the future period while this value in the corresponding historic period was respectively 0. 724 and 1. 429 m3/s. Also, the Q80 index has reached the value between 0. 1 and 0. 3 m3/s using both of downscaling methods. Generally, the results indicate a severe low flow condition in the future period.

In this article for two case studies mean sea level pressure data, height and wind at standard pressure levels were extracted from NCEP/NCAR archives relatedto a regular network, on the next step divergence quantities, vertical motion, upper levels vertical wind shear and thermal winds in different days were calculated by means of formulated equtions. The results of analysis of upper level vertical wind shear and thermal wind indicated that the maximum values of these two quantities coincide with jet stream axis. This result expresses the direct correlation between these two quantities and all energy producing interactions within the atmosphere. Moreover, this study showed that the maximum values of upper levels vertical wind shear were located between the trough line and the ridge line mid level altitude and their values at high latitudes were fewer than those of low latitudes.

In recent years, by intensified desertification in Iraq, Saudi Arabia and Syria, dust storms have affected different aspects of people's lives over the West and southwest of Iran. Atmospheric aerosols affect public health, air quality, energy balance of the Earth and the hydrological cycle. Thus, knowledge of the spatio-temporal dust storm's distribution characteristics is extremely important to quantify these effects. By increasing in dust storms in the West and southwest of Iran much discussion about the various causes of this phenomenon has been increasing. Materials and methods Aerosol optical depth (AOD) is an important remote sensing parameter that serves as a columnar proxy variable representing aerosol abundance. In this study, monthly mean AOD from Moderate Resolution Imaging Spectroradiometer (MODIS) are used to investigate the spatio-temporal distribution of dust storms in these affected areas for the period between 2000 and 2015. Monthly AOD data from the MOD08 Level 3 product (http: //ladsweb. nascom. nasa. gov/data) at a resolution of 1° × 1° are used. This study focuses on AOD at 550 nm over land, as this is close to the peak of the solar spectrum and is, therefore, associated with major radiative effects. Synoptic data are examined to identify how well geopotential height, temperature, and wind field at various levels (i. e., sea level, /500/250 hPa isobaric levels) are related to AOD and to dust activity. Meteorological data from the ECMWF archived operational initialized analyses at a resolution of 2. 5° × 2. 5° (Bou Karam et al. 2010; http: //apps. ecmwf. int/datasets/data/interim-full-moda/levtype=sfc) is used. Results, discussion MODIS monthly mean AOD validation results using the Pearson correlation test to determine the correlation between monthly mean AOD and monthly visibility data indicated high efficiency of AOD products in the dust storm intensity study. To distinguish between the Rub’ al Khali and the influence of factors such as dams in other areas, the study domain is divided in two sections consisting of desert areas in (i) Saudi Arabia and (ii) Iraq-Syria. AOD plot of the provinces of the west and southwestern of Iran showed provinces of Khuzestan, Ilam, Kermanshah and Kohgiluyeh in order have experienced the highest dust storms from 2000 to 2015. As the dust storms in all months of the year are not active, to evaluate the spatial distribution of mean AOD per year, the average for the months in which the dust storms are active evaluated (named as annual AOD). Annual and monthly average plots showed that the trend of the amount of AOD in many cases in the deserts of Iraq and Syria desert was similar to deserts of Saudi Arabia. Considering the wide range of climatic conditions affecting the occurrence of dusty storms, the best way to find out the effect of circulation on the formation of dusty storms is to compare the synoptic state of a special month in two active and inactive periods. To achieve this goal, the monthly anomaly maps (monthly average of 30 years (1981-2010)) were extracted at surface level, 250 and 500 Hp. Two months as representative the active and passive dust storm period was selected to study atmospheric circulation associated with dust. To investigate the impact of synoptic systems on factors influencing dust in the study region, precipitation, temperature a case study analysis of July 2009 and July 2014 was conducted. Also analysis the map of the average annual distribution of dust in each region shows that the trend of AOD value in many cases in the deserts of the Saudi Arabian desert was similar to Iraq and Syria desert, but AOD value in which years the dust in deserts of Iraq and Syria were still down is high in East and South East Arabian Peninsula. Conclusion In this study, changes in the behavior of dust storms in the west and southwest of Iran were investigated using quantitative monthly and annual AOD data from 2000 to 2015. The result of the Pearson correlation test with the aim of determining the correlation between the monthly average visibility and mean monthly AOD and indicates the high ability of the AOD monthly data to study dust storms. Trends of AOD show that from 2006 to 2012 there was increasing trend in February, March, April, May, June and July with a significant slope. The gradient of the monthly AOD slope of Kermanshah province was similar to Iraq and Syrian deserts and also Khuzestan province comply Saudi desert or desert of Iraq-Syria in different cases. These differences can only be caused by differences in atmospheric circulation in different dates. By comparing the synoptic maps of active and passive anomaly, it seems at sea level pressure existence of Pakistan's low pressure center and increasing pressure on the Mediterranean Sea exacerbated atmospheric turbulence and wind speed in the Middle East play an important role on the intensification of dust storm activities. At the middle and upper levels of the atmosphere, the sovereignty of the subtropical high pressure over the Arabian Peninsula, south of Iraq, the Persian Gulf and the southern part of Iran, also increasing the activity of the Mediterranean waves, increasing the mean wind speed at the upper levels of the atmosphere, as well as the flow of jet stream core has led to an intensification of dust storms in July 2009. That's why limited dust storms have been created in central and eastern regions of the Arabian Peninsula.

Introduction Annual precipitation is a major meteorological variable. The occurrence of this variable follows a particular law. This rule of law is precisely defined that All rain events occur during the climatic period. But This is impossible. Usually a small sample of this variable is available. Matching several competing laws to data fit and the best with statistical tests of choice, which is an approximate successor to real law. Increasing the sample size increases the accuracy of the test and closer to the actual law. This is more prominent in arid and semi-arid regions such as Iran. The acceptable statistical period for arid and semi-arid regions (such as Mashhad) is at least 70 years old. If this length is more than 100 years old then statistical analysis of the data can be assured relative. Also, if the return period is a phenomenon more than one-fifth of the length of the data, then the estimation of this phenomenon is not accurate. Statistical analysis of precipitation is one of the important requirements of meteorology, climatology, hydrology, drought forecasting and so on. The Sample size is important in results of the statistical analysis of rainfall. The duration of rainfall stations in Iran are often short and the maximum durations of a few stations are 61 years. This study analyzes the frequency of data after collecting and repairing the long-term data of Mashhad. Comparison of the effect of sample size variation on the results of statistical analysis is necessary in order to evaluate the trust of existing data.

The main objective of Climate Zoning is to obtain a simple and also comprehensive framework of climatic elements in a region. Classic or traditional methods that have been pervasive in the past decades are not able to explain the reality of the climate of a geographic area. With the advancement of science and appearance of computer on the field of science studies, as well as the emergence of geographic information systems, applying multivariate methods (factor analysis, principal component analysis, cluster analysis, etc. ) has been rampantly used on the zoning of climatic regions in the last two decades. These methods are comprehensive and more accurate than classical methods and also are easily applicable. After reviewing the principal components analysis on 48 climatic elements, five components that have the most significant role in Kohgiluyeh and Boyer-Ahmad Province, had been identified. These factors, in order of importance, are: temperature component, cloud-wind component, moisture component, wind component, and dust component. Between all the climate elements, temperature and cloud-wind factors, with 61% and 19% of total variance respectively, have the major role in determining the climate diversity of the province. So that in the western half of the province, due to lower elevation and proximity to the hot deserts and lack of rainfall, the role of temperature is highlighted. While by moving to the eastern half of the province, the rainfall is increasing significantly. Regional classification of province’ s climate from two to eight climate zones, can be considered and help in development decisions.