New Climatic Zones in Iran: A Comparative Study of Different Empirical Methods and Clustering Technique

2021 ◽  
Author(s):  
Faezeh Abbasi ◽  
Saeed Bazgeer ◽  
Parviz Rezazadeh Kalehbasti ◽  
Ebrahim Asadi Oskoue ◽  
Masoud Haghighat ◽  
...  
Keyword(s):  
Zagros Mountains ◽  
Empirical Methods ◽  
Climate Classification ◽  
Climate Type ◽  
Air Masses ◽  
Clustering Technique ◽  
Mountainous Regions ◽  
Synoptic Weather ◽  
Industrial Sectors ◽  
Weather Stations

Abstract It is a scientifically novel insight to classify the climate of a region using empirical methods together with clustering technique for practical usage in agricultural and industrial sectors. The main objective of this study is to compare the empirical approach to climate classification (Thornthwaite and Mather, De Martonne, the Extended De Martonne and the IRIMO (I.R. of Iran Meteorological Organization)) with clustering technique, Ward’s hierarchical agglomerative method over Iran. The maximum and minimum temperatures and precipitation data of 356 weather stations are used from IRIMO databases. 35 synoptic weather stations are selected for detailed inspection based on appropriate geographical distribution and availability of a continuous 50-year data (1966–2015). Compared with the three empirical reference methods of climate classification, the Thornthwaite and Mather method clearly shows the role of water bodies and air masses for determining the climate type in different regions. This factor is identified as the main advantage of this method over the three others. This superiority is the most visible for the highlands/mountainous regions, in the vicinity of the Zagros Mountains, and in the western regions of Iran. As a case in point, while in the De Martonne and the Extended De Martonne methods, the Zagros storm cell is climatically classified similar to patchy areas in Caspian Sea coastal zone, this cell is correctly identified as a separate zone in the Thornthwaite and Mather method. The results revealed that the clusters obtained from Ward’s algorithm are comparable to those of empirical climate classifications, particularly Thornthwaite and Mather method.

scholarly journals A countrywide analysis of 27 solar power plants installed at different climates

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Talat Ozden
Keyword(s):  
Power Plant ◽  
Alternative Energy ◽  
Power Plants ◽  
Solar Power ◽  
Meteorological Data ◽  
Energy Sources ◽  
Climate Classification ◽  
Climate Type ◽  
Monthly Average ◽  
The World

AbstractThe world is still heavily using nonconventional energy sources, which are worryingly based on carbon. The step is now alternative energy sources hoping that they will be more environmentally friendly. One of the important energy conversion forms by using these sources is photovoltaic solar systems. These type of power plants is on the increase in everyday on the world. Before investment a solar power plant in a specified region, a techno-economic analyse is performed for that power plant by using several meteorological data like solar irradiance and ambient temperature. However, this analyses generally lacks evaluation on effects of climatic and geographical conditions. In this work, 5 years of data of 27 grid-connected photovoltaic power plants are investigated, which are installed on seven different climate types in Turkey. Firstly, the power plants are categorized considering the tilt angles and Köppen–Gieger climate classification. The performance evaluations of the plants are mainly conducted using monthly average efficiencies and specific yields. The monthly average efficiencies, which were classified using the tilts and climate types were from 12 to 17%, from 12 to 16% and from 13 to 15% for tilts 30°/10°, 25° and 20°, respectively. The variation in the specific yields decrease with elevation as y(x) =  − 0.068x + 1707.29 (kWh/kWp). As the performances of photovoltaic systems for some locations within the Csb climatic regions may relatively lower than some other regions with same climate type. Thus, techno-economic performance for PVPP located in this climate classification should be carefully treated.

scholarly journals New climatic zones in Iran: a comparative study of different empirical methods and clustering technique

2021 ◽  
Author(s):  
Faezeh Abbasi ◽  
Saeed Bazgeer ◽  
Parviz Rezazadeh Kalehbasti ◽  
Ebrahim Asadi Oskoue ◽  
Masoud Haghighat ◽  
...  
Keyword(s):  
Comparative Study ◽  
Empirical Methods ◽  
Climatic Zones ◽  
Clustering Technique

scholarly journals Evaluation of the Performance of CFSR Reanalysis Data Set for Estimating Potential Evapotranspiration (PET) in Turkey

2021 ◽  
Author(s):  
AHMET IRVEM ◽  
Mustafa OZBULDU
Keyword(s):  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Actual Evapotranspiration ◽  
Observation Data ◽  
Reanalysis Dataset ◽  
Data Set ◽  
Climate Forecast System Reanalysis ◽  
Mountainous Regions ◽  
Weather Stations

Abstract Evapotranspiration is an important parameter for hydrological, meteorological and agricultural studies. However, the calculation of actual evapotranspiration is very challenging and costly. Therefore, Potential Evapotranspiration (PET) is typically calculated using meteorological data to calculate actual evapotranspiration. However, it is very difficult to get complete and accurate data from meteorology stations in, rural and mountainous regions. This study examined the availability of the Climate Forecast System Reanalysis (CFSR) reanalysis data set as an alternative to meteorological observation stations in the computation of potential annual and seasonal evapotranspiration. The PET calculations using the CFSR reanalysis dataset for the period 1987-2017 were compared to data observed at 259 weather stations observed in Turkey. As a result of the assessments, it was determined that the seasons in which the CFSR reanalysis data set had the best prediction performance were the winter (C'= 0.76 and PBias = -3.77) and the autumn (C' = 0.75 and PBias = -12.10). The worst performance was observed for the summer season. The performance of the annual prediction was determined as C'= 0.60 and PBias = -15.27. These findings indicate that the results of the PET calculation using the CFSR reanalysis data set are relatively successful for the study area. However, the data should be evaluated with observation data before being used especially in the summer models.

scholarly journals Global Solar Radiation Models in Minas Gerais, Southeastern Brazil

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Ana Flávia Martins Monteiro ◽  
Fabrina Bolzan Martins
Keyword(s):  
Cluster Analysis ◽  
Solar Radiation ◽  
Sunshine Duration ◽  
Global Solar Radiation ◽  
Minas Gerais ◽  
Southeastern Brazil ◽  
Climate Classification ◽  
Air Temperatures ◽  
Climatic Classification ◽  
Weather Stations

Accurate and complete global solar radiation (Hs) data at a specific region are crucial for regional climate assessment, crop growth modeling, and all operations that use solar energy. However, in the Minas Gerais state, Southeastern Brazil (SEB), the number of weather stations that measure global solar radiation is scarce, and when it is available, it presents gaps in the time series. An attractive alternative to solve the data gap problem is to estimate global solar radiation using empirical models. In this study, thirteen models based on maximum and minimum air temperatures, precipitation, sunshine duration, and extraterrestrial solar radiation were compared in the daily estimation of Hs. Data from 10 weather stations, from 1999 to 2017, located in Minas Gerais were used. Also, cluster analysis was used to group the localities (weather stations) with similar patterns of model performance, climatic classification (Köppen–Geiger and Thornthwaite), and seasonal data variability, considering minimum and maximum air temperatures, precipitation, sunshine duration, and global solar radiation. Although it is apparently simple, studies on this subject are scarce and the few existing ones in Minas Gerais have flaws, which justifies this study. The models were evaluated by root mean square error (RMSE), mean absolute percentage error (MAPE), mean bias error (BIAS), Willmott’s index of agreement (d), and performance index (c-index). Models based on sunshine duration, such as those proposed by Ertekin and Yaldiz and by Newland, showed the best performance (average c-index = 0.71). Models based on temperature and precipitation showed the worst results (average c-index = 0.41). Cluster analysis showed that there is a similar pattern between the performance of the models, climatic classification, and seasonal variability of data among the localities of Minas Gerais. In general, models that presented extremely poor performance were formed with weather stations located in the dry zone, but with different climate classification, and models that presented very good (and good) performance were composed by weather stations located in the humid zone (dry subhumid) with the same climate classification and similar seasonal variability. Furthermore, the models based on temperature have a tendency to overestimate radiation values below 10 MJ·m−2 day−1 and to underestimate values higher than 25 MJ·m−2 day−1. This point is a limitation of the model for estimating global solar radiation below and above these levels, showing the influence of atmospheric systems and atmospheric attenuation mechanisms of global solar radiation.

scholarly journals The influence of precipitation origin on the δ18O–T relationship at Neumayer station, Ekstrmisen, Antarctica

2004 ◽  
Vol 39 ◽  
pp. 41-48 ◽  
Author(s):  
Elisabeth Schlosser ◽  
Carleen Reijmer ◽  
Hans Oerter ◽  
Wolfgang Graf
Keyword(s):  
Air Temperature ◽  
Open Water ◽  
Weddell Sea ◽  
Air Masses ◽  
Ice Coverage ◽  
Synoptic Weather ◽  
Time Period ◽  
The Relationship ◽  
Snow Samples

AbstractThe relationship between δ18O and air temperature at Neumayer station, Ekstrmisen, Antarctica, was investigated using fresh-snow samples from the time period 1981–2000. A trajectory model that calculated 5 day-backward trajectories was used to study the influence of different synoptic weather situations and thus of different moisture sources on this correlation. Generally a high correlation between air temperature and δ18O was found, but the quality of the δ18O–T relationship varied with the different trajectory classes. Additionally, the sea-ice coverage on the travel path of the moist air was considered. The amount of open ocean water underneath the trajectory has a large influence on the δ18O–T relationship. For trajectories that lead completely above open water, no significant correlation between δ18O and T was found, because mixing with air masses containing additionally evaporated water vapour from the ocean influences the isotope ratio of precipitation. A very high correlation, however, was found for transports over the completely ice-covered Weddell Sea.

scholarly journals Source–Receptor Relationships and Cluster Analysis of CO2, CH4, and CO Concentrations in West Africa: The Case of Lamto in Côte d’Ivoire

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 903 ◽  
Author(s):  
Dro Touré Tiemoko ◽  
Fidèle Yoroba ◽  
Jean-Daniel Paris ◽  
Adama Diawara ◽  
Antoine Berchet ◽  
...  
Keyword(s):  
Emission Sources ◽  
Air Masses ◽  
Clustering Technique ◽  
North East ◽  
Range Transport ◽  
Continental Origin ◽  
And Cluster Analysis ◽  
Combustion Processes ◽  
Co Concentrations ◽  
Source Receptor Relationships

The contribution in terms of long-range transport of CO2, CH4, and CO concentrations to measurements at Lamto (5°02′ W–6°13′ N) was analyzed for the 2014–2017 period using the FLEXPART model that calculates the retro-plumes of air masses arriving at the station. The identification of the source-receptor relationships was also studied with a clustering technique applied on those retro-plumes. This clustering technique enabled us to distinguish four categories of air mass transports arriving at Lamto site described as follows: oceanic and maritime origin (≈37% of the retro-plumes), continental origin (≈21%), and two hybrid clusters (≈42%). The results show that continental emission sources contribute significantly to the increases in concentrations of CO2, CH4, and CO and explain ≈40% of their variance. These emission sources are predominantly from north and north-east directions of the measurement point, and where densely populated and economically developed areas are located. In addition, the transport of air masses from these directions lead to the accumulation of CO2, CH4, and CO. Furthermore, the ratios ΔCO/ΔCH4 and ΔCO/ΔCO2 observed in the groups associated with Harmattan flows clearly show an influence of combustion processes on the continent. Thus, the grouping based on FLEXPART footprints shows an advantage compared to the use of simple trajectories for analyzing source–receptor relationships.

scholarly journals Statistical Characteristic of Heavy Rainfall Associated with Typhoons near Taiwan Based on High-Density Automatic Rain Gauge Data

2016 ◽  
Vol 97 (8) ◽  
pp. 1363-1375 ◽  
Author(s):  
Chun-Chieh Wu ◽  
Tzu-Hsiung Yen ◽  
Yi-Hsuan Huang ◽  
Cheng-Ku Yu ◽  
Shin-Gan Chen
Keyword(s):  
Heavy Rainfall ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Statistical Characteristics ◽  
Rain Gauge Data ◽  
Mountainous Regions ◽  
Rain Gauges ◽  
Weather Stations ◽  
Central Weather Bureau

Abstract This study utilizes data compiled over 21 years (1993–2013) from the Central Weather Bureau of Taiwan to investigate the statistical characteristics of typhoon-induced rainfall for 53 typhoons that have impacted Taiwan. In this work the data are grouped into two datasets: one includes 21 selected conventional weather stations (referred to as Con-ST), and the other contains all the available rain gauges (250–500 gauges, mostly automatic ones; referred to as All-ST). The primary aim of this study is to understand the potential impacts of the different gauge distributions between All-ST and Con-ST on the statistical characteristics of typhoon-induced rainfall. The analyses indicate that although the average rainfall amount calculated with Con-ST is statistically similar to that with All-ST, the former cannot identify the precipitation extremes and rainfall distribution appropriately, especially in mountainous areas. Because very few conventional stations are located over the mountainous regions, the cumulative frequency obtained solely from Con-ST is not representative. As compared to the results from All-ST, the extreme rainfall assessed from Con-ST is, on average, underestimated by 23%–44% for typhoons approaching different portions of Taiwan. The uneven distribution of Con-ST, with only three stations located in the mountains higher than 1000 m, is likely to cause significant biases in the interpretation of rainfall patterns. This study illustrates the importance of the increase in the number of available stations in assessing the long-term rainfall characteristic of typhoon-associated heavy rainfall in Taiwan.

scholarly journals Changes in Rainfall and Climate Classification in South Sulawesi

2021 ◽  
Vol 2 (5) ◽  
pp. 37-50
Author(s):  
Ridahwati Ridahwati
Keyword(s):  
Rainfall Intensity ◽  
Geographical Location ◽  
Subtropical Climate ◽  
The Sun ◽  
Q Value ◽  
Climate Classification ◽  
Climate Type ◽  
South Sulawesi ◽  
The Earth

The study discuss about Changes in Rainfall and Climate Classification in South Sulawesi. The climate of the Earth is determined by the location of the sun in relation to the earth's surface. Geographical location influences the categorization of climate on our planet. The results of the study (1) Rainfall in Bone Regency has been classified as high rainfall intensity for the last 10 years; (2) Determination of climate classification can be done by processing rainfall data obtained from data before weighting, after weighting, ranking, and opportunity; (3) The climate classification according to Schmidt-Ferguson for Bone Regency has a B climate type, which is a humid subtropical climate; and (4) The climate classification according This is based on a comparison of the number of dry months (BK) and wet months (BB), from which the Q value is obtained, which is then used to determine the type of climate according to Schmidt-Ferguson; (4) Oldeman's climate classification for Bone Regency has a C1 climate type, which has the characteristics of planting lowland rice once a year and secondary crops twice a year; (5) Oldeman's climate classification for Bone Regency has a This is based on the number of Wet Months (BB) and Dry Months (BK) in a given year

scholarly journals Planetary boundary influence at the Jungfraujoch analyzed by aerosol cycles and synoptic weather types

2011 ◽  
Vol 11 (1) ◽  
pp. 985-1024 ◽  
Author(s):  
M. Collaud Coen ◽  
E. Weingartner ◽  
M. Furger ◽  
S. Nyeki ◽  
A. S. H. Prévôt ◽  
...  
Keyword(s):  
Relative Increase ◽  
Weather Type ◽  
Specific Humidity ◽  
Weather Types ◽  
Annual Cycles ◽  
Air Masses ◽  
Scattering Coefficients ◽  
Diurnal Cycles ◽  
Synoptic Weather ◽  
Time Of Year

Abstract. Fourteen years of meteorological parameters, aerosol variables (absorption and scattering coefficients, aerosol number concentration) and trace gases (CO, NOx, SO2) measured at the Jungfraujoch (JFJ, 3580 m a.s.l.) have been analyzed as a function of different synoptic weather types. The Alpine Weather Statistics (AWS) classification was used to define the synoptic meteorology over the whole Swiss region. The seasonal contribution of each synoptic weather type to the aerosol concentration was deduced from the aerosol annual cycles while the planetary boundary layer (PBL) influence was estimated by means of the diurnal cycles. Since aerosols are scavenged by precipitation, the diurnal cycle of the CO concentration was also used to identify polluted air masses. SO2 and NOx concentrations were used as precursor tracers for new particle formation and growth. This study confirms the consensus view that the JFJ is mainly influenced by the free troposphere during winter and by injection of air parcels from the PBL during summer. A more detailed picture is, however, drawn where the JFJ is completely influenced by free tropospheric air masses in winter during advective weather types and largely influenced by the PBL also during the night in summer during the subsidence weather type. Between these two extreme situations, the PBL influence at the JFJ depends on both the time of year and the synoptic weather type. The fraction of PBL air transported to the JFJ was estimated by the relative increase of the specific humidity and CO.

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