Different Climates Of Iran Research Articles

Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000–2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external analysis of the performance of models at stations with similar climatic conditions denoted the applicability of nearby station' data for estimation of the daily ETo at target station.

Optical and thermal analysis of a parabolic trough solar collector for production of thermal energy in different climates in Iran with comparison between the conventional nanofluids

Optical and thermal analysis of the most well-known solar concentrator system; parabolic trough collector (PTC) are investigated and analyzed. To evaluate performance of the PTC, four cities of Iran with different weather conditions are chosen as case studies. Effective parameters such as concentration ratio, incident angle correction factor, collector mass flow rate are considered. The main objective of this work is evaluation of the solar energy potential using PTC in under consideration cities with different climates. Numerical modeling of the analysis is done using MATLAB software. Simulation results shows that Shiraz, with an average annual thermal efficiency of 13.91% and annual useful energy of 2213 kWh/m2, is the best region to use solar concentrator systems. The impacts of other parameters such as fluid inlet temperature, input fluid flow rate and aperture area of the collector on the output of the system are also investigated. Finally, the effect of using nanofluids as heat transfer fluid on increasing the heat transfer is investigated.

A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model

Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965–2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.

Earth-to-air heat exchangers cooling evaluation for different climates of Iran

Earth-pipe-air heat exchangers (EPAHEs) are viable alternatives or supplements to conventional central heating or cooling systems. In present study, to reduce the cooling load of a sample residential building; usage and potential energy conservation of a four-pipe EPAHE were studied for different climates of Iran. The evaluation of the EPAHE was based on a three-dimensional transient computational model and validated by experimental data of another research. For this purpose four cities of Iran, by different climates (Temperate, Steppe, Desert, and Snow) were selected according to climate classification map of Wladimir Köppen, and the inlet/outlet temperature of working fluid (air) for each pipe, the monthly average energy conservation, and the maximum cooling load of the building with and without the EPAHE for these cities were compared in July.As a result, the average energy conservation by the EPAHE is significantly differentin selected cities with different climates. The energy conservation shows better when the city soil, is silt in comparison with loam and clay. Also in some cases, using of EPAHE shows a negative effect on the air-conditioning of buildings. The model was developed by the FLUENT simulation program.

Effect of Air Temperature on Historical Trend of Long-Term Droughts in Different Climates of Iran

Effective monitoring of drought plays an important role in water resources planning and management, especially under global warming effect. The aim of this paper is to study the effect of air temperature on historical long-term droughts in regions with diverse climates in Iran. To this end, monthly air temperature (T) and precipitation (P) data were gathered from 15 longest record meteorological stations in Iran covering the period 1951–2014. Long-term meteorological droughts behavior was quantified using two different drought indices, i.e. the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Linear and non-linear trends in T, P, SPI and SPEI were evaluated using non-parametric and parametric statistical approaches such as non-modified and modified Mann-Kendall Test, Theil-Sen approach, and simple regression. The results indicated that the significant trends for temperature are approximately all increasing (0.2 °C to 0.5 °C per decade), and for precipitation are mostly decreasing (−7.2 mm to −14.8 mm per decade). It was also indicated that long-term drought intensities monitored by the SPI and SPEI have had significant downward trend (drought intensification with time) at most stations of interest. The observed trends in the SPI series can be worsen if air temperature (in addition to precipitation) participates in drought monitoring as SPEI. In arid and extra arid climates, it was observed that temperature has strong effects on historical drought characteristics when comparing the SPI and SPEI series. Due to the determinative role of temperature in mostly dry regions like Iran, the study suggests using the SPEI rather than SPI for more effective monitoring of droughts.

Uncertainty analysis of radar rainfall estimates over two different climates in Iran

ABSTRACTAccuracy of rainfall quantification is one of the most important concerns in meteorological and hydrological modelling. Satellites and weather radars can provide meteorological information with higher temporal and spatial resolution than ground stations. Rain gauges measure rain rate directly; however, weather radars estimate rain rate by converting radar reflectivity aloft to rain rate at ground level. This conversion with a power law relation between radar reflectivity and rain rate could be altered from place to place or in various precipitation types. This variety may be the source of errors and uncertainty of radar rainfall estimates. One way to assess the uncertainty of radar rainfall is simulation of rainfall fields. In this article, after calibrating two radars located in the south-western and northern parts of Iran, uncertainty of rainfall estimates of these radars has been analysed using the Gaussian Copula model. Reliability of this model was examined for 10% of the rainfall events that were not included in the simulation process. Obtained results of the current research indicate that recalibration of radars can considerably reduce bias and root mean error. In addition, the Copula-based model can generate rainfall fields with similarly spatial structures to those of observed rainfall data.

Evaluation of Some Net Radiation Models for Improving Daily Reference Evapotranspiration Estimation in Iran

AbstractNet radiation (Rn) is one of the effective inputs for controlling soil heat flux, thermal convection, moisture flux exchange, and reference crop evapotranspiration (ET0) rate. In this research, the accuracy of some empirical and semiempirical Rn models is examined for different climates of Iran versus the recommended net radiation model as proposed in the Penman–Monteith Food and Agricultural Organization of the United Nations 56 standard (FAO 56) model for the period 1980–2007. For estimating daily net radiation, various net radiation models [Wright, basic regression model (BRM), Linacre, Berliand, Irmak, and Monteith] were examined. Model evaluations were implemented for four climate types. On regional averages, the linear BRM had the superior performance in generating the most accurate daily ET0. Results showed that for 70% of the study sites, the linear Rn models can be reliable candidates instead of sophisticated nonlinear Rn models, which are proposed in the reference FAO 56 model. For some ...

Cool black roof impacts into the cooling and heating load demand of a residential building in various climates

This paper describes the impacts of different cool black paints on cooling and heating load demand of a residential building in different climates. Cool paints with dark appearance and high reflectance in near infrared portion of sunlight are of great interest by the owners of homes to satisfy both desired visual and energy saving aspects. Three copper oxide (CuO) powders, different in pigment size, and a chromium–iron oxide (Cr2O3–Fe2O3) powder, as a commercial cool black pigment, are used to make the black paints. The samples are made on both conventional black and cool white base coats. The spectral reflectance of all samples in solar range (0.3–2.5µm) and infrared region (2.5–25µm) is measured. The thermal emittance of the samples is estimated using the spectral reflectance measurement and validated by the measurement of infrared camera. A typical residential single-stage single-family home in three different climates of Iran is considered and the impacts of applying the different black paints on cooling and heating load demand are discussed. The results show that the peak and annual cooling load demand decrease by 0.4–1.4kW (6–13%) and 405–2202kWh (6–14%), respectively, depends on the type of pigmented coating and climate conditions.

Thermal analysis of HVAC and solar panels using genetic optimization algorithm

The present study investigates the use of HVAC and solar heating systems inside residential zones using a combination of direct numerical modeling and genetic optimization method in different climates of Iran. The direct numerical modeling is capable of calculating temperature field inside buildings. Then, direct modelling algorithm is used to determine energy consumption rate of the building in the different climates of Iran. The results of direct numerical modelling are checked against those of carrier and energy-plus software. The results show good accordance with those of numerical simulations presented in the open literature.

Effects of Climatic Factors on the Quantity of Essential Oil and Dry Matter Yield of Coriander (<I>Coriandrum sativum L.</I>)

Coriander (Coriandrum sativum L.), is an annual and Mediterranean region species whose oil is widely used in the food, health, cosmetics, soft drinks and chocolate industries in all around of the world. Considering the importance and use of coriander oil, this study was conducted in a completely randomized design to make quantitative comparisons of coriander essential oil and dry matter yield in different climates of Iran. The cultivation of coriander seeds was carried out in pots with four replications in the cities of Maku, Khoy and Urmia with an altitude of 1182 m, 1148 m and 1332 m, respectively. The extraction of volatile oil was performed by water distillation method using Clevenger apparatus. Results of statistical analysis indicated that environmental factors significantly affected the oil content and the dry matter yield of coriander. The maximum oil content was obtained from the fruits, collected from Maku and Khoy. The minimum oil content was obtained from Urmia. With decreasing altitude and precipitation in the cities of Maku and Khoy, the oil content and dry matter yield increased. Our results clearly showed that the essential oil content of coriander fruits, collected from Makou and Khoy, was identical because of the almost identical climate and environmental conditions of these two cities. It can be concluded that among the climate parameters, altitude and precipitation have the most impact on the essential oil content and dry matter yield of coriander. Low altitudes could increase the essential oil content of coriander. Keywords: Altitude, Coriander, Dry Matter, Essential Oil, Precipitation

Applicability of Radiant Heating-Cooling Ceiling Panels in Residential Buildings in Different Climates of Iran

This paper assess the feasibility of using heating-cooling radiant panel in residential buildings in five different climate zones in Iran. This study leverages simulation modeling to evaluate the thermal performance of heating-cooling radiant panels. By defining new indices, applicability limiting factors of the radiant panels, i.e. condensation risk in cooling, and asymmetric radiation discomfort in heating are evaluated and compared in different climatic conditions. The system capacity and setpoints are calculated based on thermal comfort conditions, using PMV index in heating (PMV= -0.5) and cooling (PMV= +0.5) modes. Results of this study indicate that for dryer regions with less risk of condensation the radiant system can help home owners to save around 11.3% on their heating energy and 9.1% on cooling energy use.

Exergy and Economic Evaluation of a Commercially Available PV/T Collector for Different Climates in Iran

Thermal photovoltaic (PV/T) water based collectors are used to convert solar radiation to both thermal energy and electricity simultaneously. Along with energy analysis, exergy analysis is also useful for thermal systems such as PV/T to evaluate the “quality” of energy obtained from the system. Various types of PV/T collectors are available on the market. However, in this paper, a commercialized PV/T system is selected and exergy and economic analysis (exergoeconomics) is performed for a specific collector using known technical parameters and price for three cities in Iran with different insolation level. A MATLAB simulation program is prepared for this purpose, and it is cross validated using a former study on the same collector performed by TRNSYS and good agreement is observed. According to the results, exergy efficiency is obtained to be 9.7%, 9.6%, and 9.6% for the cities of Tabriz, Shiraz, and Esfahan respectively. An economic analysis is also performed using Net Present Value (NPV) method for the mentioned cities, and it concluded that with the specified economic parameters, the system is marginally economically feasible. This is found to be due to high capital investment costs as well as cheap available fossil fuel that is utilized widely in order to supply thermal and electrical energy demand in the studied cities.

Investigating the effective factors on the reduction of energy consumption in residential buildings with green roofs

Heating and cooling of residential and commercial buildings account for approximately 40 percent of world's total energy consumption [1]. This considerable amount of energy consumption have made scientist to search for every possible way to reduce it. Among the most effective approaches is the use of green roof for buildings. Although the positive effects of using such roofs are well proven, the amount of energy reduction which can be achieved by this method is another issue that this paper is trying to investigate. In this study, three different climates of Iran are chosen for the analysis. The results demonstrate that using green roof in Very Hot Dry (Bandar Abbas), Warm Dry (Isfahan), and Mixed Dry (Tabriz) climates causes energy consumption to decrease by approximately 8.5, 9.2 and 6.6 percent, respectively. Considering the reduction of energy consumption as the only desirable benefit of green roof, the payback period would be 25–57 years (depending on the climate).

Adjustment comparison of veranda effect on building shadow area in semi-arid and moderate climates

This research was conducted to assess the performance of horizontal shading device on the building shadow area in two different climates of Iran. The case studies were two holy shrines in Shiraz and Savadkouh (semi arid climate and humid and moderate climate respectively) and were prioritized by Analytical Hierarchy Process weights. The solar angles and shadow area were derived and compared accordingly. The results showed that the shadow on the beneath wall of the lower latitude case study (Shiraz: 29°33′N) was 48.21% in January and 100% in July, and the parallel ratio for Savadkouh was 26.1% in January and 97.22% in July. Through comparison of the monthly shadow area on wall in July with that in January in both climates, the Shiraz and Savadkouh ratios were found to be 2.78 and 4.79, respectively, which indicated that shadow areas in summer were more than those in winter. Therefore, the shadow could cause more outdoor thermal comfort in winter and summer in both climates.

Building Energy Optimization using Sequential Search Approach for Different Climates of Iran

Abstract - In this work the sequential search optimization method applied to a 430 three-floor residential building to find optimal building envelope and solar technology options along the path to zero energy building design. Five different climates of Iran including: Tehran, Tabriz, Esfahan, Bandar Abbas and Shiraz, which are almost good representative of Iran’s climate, are considered. Optimal design options for each climate suggested for different design cases including minimum energy related cost and maximum energy saving design options. It is shown that a proper combination of envelope and solar options can lead to a sustainable design in terms of energy use and environmental effects with an affordable cost. Optimization results showed that at the min-cost design option, it is possible to minimize energy cost up to 23% while energy saving increases up to 15% depending on the considered climate. Maximum energy saving up to 49% is reported while energy cost rises to 25% in comparison to reference building. Depending on each climate, different envelope and solar options are suggested which can be used as a practical guideline for energy management companies and architects in early design stages of building envelope. Investigating the optimization results toward zero energy building design reveals that before using solar technologies to produce a home's energy, it is more cost-effective to first reduce energy usage of building using sustainable envelope parameters which results in a less expensive PV or solar heat water (SHW) system.

Spatial patterns and temporal trends of daily precipitation indices in Iran

Spatial patterns of daily precipitation indices and their temporal trends over Iran are investigated using the APHRODITE gridded daily precipitation dataset for the period 1961–2004. The performance and limitations of the gridded dataset are checked against observations at ten rain-gauge stations that are representative of different climates in Iran. Results suggest that the spatial patterns of the indices reflect the role of orography and sea neighborhoods in differentiating central-southern arid and semi-arid regions from northern and western mountainous humid areas. It is also found that western Iran is impacted by the most extreme daily precipitation events occurring in the country, though the number of rainy days has its maximum in the Caspian Sea region. The time series of precipitation indices is checked for long-term trends using the least squares method and Mann-Kendall test. The maximum daily precipitation per year shows upward trends in most of Iran, though being statistically significant only in western regions. In the same regions, upward trends are also observed in the number of wet days and in the accumulated precipitation and intensity during wet days. Conversely, the contribution of precipitation events below the 75th percentile to the annual total precipitation is decreasing with time, suggesting that extreme events are responsible for the upward trend observed in the total annual precipitation and in the other indices. This tendency towards more severe/extreme precipitation events, if confirmed by other datasets and further analyses with longer records, would require the implementation of adequate water resources management plans in western Iran aimed at mitigating the increasing risk of intense precipitation and associated flash floods and soil erosion.

Drought Monitoring Using the Multivariate Standardized Precipitation Index (MSPI)

One major characteristic of the Standardized Precipitation Index (SPI) is its flexibility to be calculated in a variety of time scales and hence being aware of different types of droughts. However, various time scales may result in confusion of the water resources’ researchers, decision makers and users in identifying and specifying drought periods in a certain region. To solve this problem in this article, a multivariate approach has been utilized having the ability to aggregate a variety of the SPI time series into a new time series called the Multivariate Standardized Precipitation Index (MSPI). The MSPI is based on the principal components analysis (PCA) of the SPI time series in a certain location. Having specified the first principal component’s (PC1’s) scores, the MSPI would be simply attained by dividing PC1’s values by the monthly standard deviation. In this article, MSPI’s capability in depicting the variability of the SPI time series (in five ranges of time scales, including 3–6, 6–12, 3–12, 12–24, and 24–48 months) was studied at four weather stations representing the four different climates in Iran from the driest to the wettest climates. The results showed that the PC1 is able to justify more than 74 % of the variability for the selected sets of the SPI time scales in the studied climates. Also, it became clear that the drought and wet severity classes monitored by MSPIs matched very satisfyingly to those of the five sets of the SPI time scales. Therefore, in cases where the aggregation time scales for calculating the SPI are not previously known, this study recommends the researchers use the MSPI.

A modified distance-weighted approach for filling annual precipitation gaps: application to different climates of Iran

The continuity of precipitation data is critical in climate, hydrological and environmental studies. The main objective of this study is to improve the geographical coordinate (GC) method for filling gaps in annual precipitation observations. The altitude ratio (Ai) and the mean annual precipitation (MAP) were employed through a modification procedure to enhance the efficiency of the GC technique. In this respect, 24 precipitation gauge stations located in six different regions of Iran were taken into consideration in order to investigate the performance of the modified approach. Furthermore, estimates of methods such as the normal ratio (NR), the linear regression (LR) and also the conventional GC were compared with the outcomes obtained from the improved methodology to evaluate whether it has adequate suitability in a broad range of geo-climatic conditions. Average values of model accuracy measures and also results of the priority ranking process indicated that the best method was modified GC and the second priority technique was NR. It was also revealed that the conventional GC occupied no place in the first priority class for all stations, and more interestingly, the modified GC has not been in the lowest priority at all. Hence, the proposed methodology was proven to be a reliable procedure for estimating missing annual precipitation records. In addition to improved performance, the modified approach utilizes input data that are usually available in the most of data-limited areas such as developing countries.

Sizing the prime mover of a residential micro-combined cooling heating and power (CCHP) system by multi-criteria sizing method for different climates

In the present study, a multi-criteria sizing function (MCSF) is proposed for designing the optimum size and operating strategy of the prime mover of a residential micro-combined cooling heating and power (CCHP) system. The CCHP prepares the electrical, thermal, cooling, and domestic hot water demands of the same building in five different climates in Iran. The MCSF integrates fuel energy saving ratio (FESR) and exergy efficiency as the thermodynamical parameters, net present value, internal rate of return and payback period for the economical criteria, and CO2, CO and NOx reduction for the environmental evaluations. Analytical hierarchy process is used to weigh each criterion with respect to others. The engine proposed by MCSF results in considerable fuel saving and pollution reduction and a payback period of about 6 years for the 5 climates. In addition, the best strategy according to the engine size is determined for every climate.

Bulk density, chemical composition and in vitro gas production parameters of Iranian barley grain cultivars grown at different selected climates

Barley grain varieties adapted to grow under different climates of Iran (16 cultivars named Bahman, Makoeei, CB-79-10, Sahand, Reyhan03, Reyhan45, Fajer, Nosrat, Valfajer, Kavir, MB-82-12, AB-23-14, Nimrooz, Jenob, Dasht and Sahra) were provided (10 samples per each cultivars). Samples were assessed for bulk density (BD), chemical composition including organic matter (OM), crude protein (CP), ether extract (EE), acid detergent fiber (ADF), neutral detergent fiber (NDF), and soluble sugar. An in vitro gas production technique was also used to examine the effect of the cultivars evaluated on gas production parameters of the barley grains evaluated. Approximately, 200 mg of each sample was weighed into a 120-ml serum vial (n=4). Gas production was recorded at 2, 4, 6, 8, 12, 24, 36, 48, 72, and 96 h after the incubation. Data of 24 h gas production were also used to estimate the organic matter digestibility and metabolizable energy of the cultivars. Crude protein, soluble sugar, EE, ash, NDF and ADF concentrations of the barley samples investigated was on average of 108, 35, 30, 24, 238.4 and 72 g/kg, respectively; while the difference was significant (P< 0.001) among the cultivars. Dasht had the highest crude protein (CP) and the lowest NDF; while Makooei and Sahra showed the highest NDF and BD, respectively. The average of bulk density was 679 kg/m3 (from 615 to 720); there was a negative correlation between the bulk density and ADF (r = -0.77 and P< 0.001), while the correlation between the bulk density and metabolizable energy was positive (r = 0.69 and P< 0.05). Organic matter digestibility of the samples evaluated ranged from 75 to 81% (mean= 78%) and there was a significant differences (P< 0.01) among the cultivars. Key words: Barley grain, digestibility, metabolizable energy, gas production.