Comparison of univariate and multivariate geographically weighted regression for estimating air temperature over Iran

Station recording air temperature (T_a) has limited spatial coverage, especially in unpopulated areas. Since temperature can change greatly both spatially and temporally, stations data are often inadequate for meteorology and subsequently climatology studies. Time series of moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (T_s) and normalized difference vegetation index (NDVI) products, combined with digital elevation model (DEM), albedo from Era-Interim and meteorological data from 2006 to 2015, were used to estimate daily mean air temperature over Iran. Geographically weighted regression was applied to compare univariate and multivariate model accuracy. In the first model, which only interfered with land surface temperature (LST), the results indicate a weak performance with coefficient of determination up to 91% and RMSE of 1.08 to 2.9 °C. The mean accuracy of a four-variable model (which used LST, elevation, slope, NDVI) slightly increased (6.6% of the univariate model accuracy) when compared to univariate model. RMSE dropped by 19% of the first model. By addition albedo in the third model, the coefficient of determination increased significantly. This increase was 32% of the univariate model and 23.75% of the 4-variable model accuracy. The statistical comparison between the three models revealed that there is significant improvement in air estimation by applying the geographically weighted regression (GWR) method with interfering LST, NDVI, elevation, slope, and albedo with mean absolute RMSE of 0.62 °C and mean absolute R² of 0.99. In order to better illustrate the third model, t values were spatially mapped at 0.05 level.     

Precipitation rate climatology related to different cloud types using satellite imagery over Iran

Cloud types have a substantial influence on precipitation. This paper presents a study of the monthly variations of daytime different cloud types over Iran using data collected from Moderate-resolution Imaging Spectroradiometer (MODIS) aboard Terra during 2001–2015, MODIS aboard Aqua during 2002–2015, International Satellite Cloud Climatology Project (ISCCP) H-series cloud type data during 2001–2009 and precipitation rate associated with different cloud types using Tropical Rainfall Measuring Mission (TRMM) satellite products during 2001–2009. Different cloud types were determined using MODIS cloud optical thickness and cloud top pressure data based on ISCCP algorithm. The results showed that stratocumulus and cumulus clouds have maximum occurrence frequency over marine areas especially southern seas. The maximum frequency of nimbostratus and deep convective occurrence occurred over mountainous regions particularly at the time of Aqua overpass and cirrus and cirrostratus are observed over southeast of Iran during warm months due to monsoon system. Altostratus cloud is extended in each month except January, at the time of Terra overpass while nimbostratus is seen at the time of Aqua overpass during warm months in the study area. Cumulus and altocumulus clouds have shown remarkable frequency in all months especially over marine regions during warm and fall months. The higher value of precipitation rate is related to altostratus with a rate approximately 7 mm/h at the time of Terra overpass during April. Altostratus has the maximum recorded precipitation rate except in Nov., Dec., Sep., and Jan. at the time of Terra overpass, whereas the maximum precipitation rate is linked to nimbostratus cloud activity (up to 5 mm/h) except for March, April, and Sep. at the time of Aqua overpass. Deep convective (up to 1.32 mm/h), cirrostratus (up to 1.11 mm/h), and cirrus (0.02 mm/h) are observed only in warm months. The results were compared with ISCCP cloud types so that precipitation rate classified from low to high and Spearman rank correlation was calculated. The results showed good agreement between these two cloud type data; however, there were few notable difference between them.     

Association between cloudiness and rainfall over Fars province in Iran

Relationship between precipitation sum and cloud properties over Fars province in Iran was analyzed for the cases of light (4 mm), moderate (17 mm), and heavy (62 mm) precipitation. The cloud properties (temperature and pressure at the top, cloud optical thickness and cloud water path) were obtained from satellite data of spectoradiometer MODIS (MODO6). The spatial distribution of rainfall was obtained from the 3-hourly data of TRMM (3B42). The multivariate regression model was developed to predict the spatial distribution of rainfall. A strong significant positive association between the spatial distribution of cloud characteristics and heavy precipitation was found, while no clear correlation was revealed between light precipitation and cloud properties. The developed regression model comprised 64, 47, and 24% of spatial variance of heavy, moderate, and light rainfall, respectively. The influence of cloud water path on the spatial distribution of rainfall dominates.     

The effect of heterogeneity on the character of density-driven natural convection of CO2 overlying a brine layer

The efficiency of mixing in density-driven natural-convection is largely governed by the aquifer permeability, which is heterogeneous in practice. The character (fingering, stable mixing or channeling) of flow-driven mixing processes depends primarily on the permeability heterogeneity character of the aquifer, i.e., on its degree of permeability variance (Dykstra-Parsons coefficient) and the correlation length. Here we follow the ideas of Waggoner et al. (1992) [13] to identify different flow regimes of a density-driven natural convection flow by numerical simulation. Heterogeneous fields are generated with the spectral method of Shinozuka and Jan (1972) [13], because the method allows the use of power-law variograms. In this paper, we extended the classification of Waggoner et al. (1992) [13] for the natural convection phenomenon, which can be used as a tool in selecting optimal fields with maximum transfer rates of CO₂ into water. We observe from our simulations that the rate of mass transfer of CO₂ into water is higher for heterogeneous media.     

Evidence for Mountain Glacier Changes in Semi-arid Environments based on Remote Sensing Data

Countries like Iran, which are geographically situated in a rather arid and warm regions, will suffer more from global warming than countries located in humid and semi-humid regions. In such environments, analyzing the variations of mountain glaciers can reveal several aspects of climate change patterns more efficiently in comparison to the other geo-indicators. The present study reports some evidence of changes for Alamkouh glacier between 1955 and 2010 based on several mediums to high-resolution satellite images. Considering that most part of the Alamkouh glacier is covered by debris and delineating its actual area is not possible, planimetric change analysis was restricted to the clean-ice regions. The object-oriented classification approach was used to estimate the clean ice areas. This technique takes into account the shapes of the features along with their spectral patterns. Results revealed that clean ice regions of Alamkouh glacier shrank since 1955 with an overall area reduction of about 59 %. Although the general observed trend is a clean ice area reduction, some advancement was detected over the period from 2000 to 2010. During 1992–2000, the maximum reduction in the clean ice area was observed (0.08 km².a^?1). However, clean ice area of the case study has partially increased about 0.028 km².a^?1 from 2000 to 2010. Supra-glacial lake change analysis illustrated that at the surface of the glacier, lakes have been enlarged remarkably in the past 55 years (about 4.75 times greater). In addition, clean ice area and the surface area of supra-glacial lakes oscillated in compliance with each other. The findings revealed that the maximum expansion of supra-glacial lake occurred during 1992–2000, which demonstrate the glacier maximum reduction during this period. This shrinkage in the Alamkouh glacier caused an extensive glacial lake outburst flood in Jun 2011. The results of this study agree with documented changes in other mountain glaciers located in arid and semi-arid environments and they also confirm the application of mountain glaciers in climate variations monitoring over such regions.     

Evaluation of thermal comfort conditions in Ourmieh Lake, Iran

Research in developing countries concerning the relationship of weather and climate conditions with tourism shows a high importance not only because of financial aspects but also an important part of the region’s tourism resource base. Monthly mean air temperature, relative humidity, precipitation, vapor pressure, wind velocity, and cloud cover for the period 1985–2005 data collected from four meteorological stations Tabriz, Maragheh, Orumieh, and Khoy were selected. The purpose of this study is to determine the most suitable months for human thermal comfort in Ourmieh Lake, a salt sea in the northwest of Iran. To achieve this, the cooling power and physiologically equivalent temperature (PET) calculated by the RayMan model and the Climate Tourism/Transfer Information Scheme (CTIS) were used. The results based on cooling power indicate that the most favorable period for tourism, sporting, and recreational activities in Ourmieh Lake is between June and October and based on PET between June to September. In addition, the CTIS shows a detailed quantification of the relevant climate–tourism factors.