Metrological Stations Research Articles

Mechanism of “black-water” occurrence in the reservoirs with <i>Eucalyptus</i> plantation, southern China

桉树（Eucalyptus）在我国南方大规模种植，最快两三年成材，经济价值高，但近来却被认为是抽水机、绿色沙漠，甚至传言有毒.特别是近年来桉树人工林区水库出现的泛黑现象——水体呈现黑褐色并伴有涩味，给种植地附近居民造成了很大的恐慌.并且其黑水形成机理、物质来源及触发条件等尚不清楚.基于此，本文选取我国南方桉树人工林区典型水库，开展了水体泛黑现象成因研究：于2015年8月2016年4月对广西南宁市那降水库、天雹水库、百合水库分别进行了4次水体垂直分层采样，测定其理化指标，并结合当地水库管理站提供的水文数据进行综合分析.结果表明，桉树人工林区水库泛黑与特定季节及特殊气候条件有关，水体温度分层结构失稳是黑水物质运移的主要动力因素；夏季水库水温分层结构稳定，限制了底层致黑物质向上迁移，溶解氧等水质指标分层明显，秋冬季节分层消失，水体发生垂直交换，给底层致黑物质提供了上翻的作用力，导致泛黑现象发生.硫化物、单宁酸、铁、锰等物质季节性及空间分异特征与水温季节性分层特性密切相关.桉树林区水库水体铁和锰浓度最高可达2.93和3.46 mg/L，桉树茎、叶在水体中浸出大量单宁酸，在硫化物、单宁酸、铁、锰同时存在的条件下，发生铁、锰与硫化物，硫化物与单宁酸，铁、锰与单宁酸等一系列反应，生成黑色络合物，导致水库泛黑.研究结果可为保障桉树人工林区饮用水源地安全提供指导，并为桉树人工林区水库黑水深入研究奠定基础，引领更多学者进行深入研究.;Eucalyptus can grow into wood in two or three years and has large-scale cultivation in the southern China, with high economic value. Recently it is considered pump, green desert, and even rumoured toxic. The water in the reservoir in Eucalyptus planting area appeared black sporadically. The water was dark brown with a pungent smell, which has caused great panic within local residents. The phenomenon is associated to Eucalyptus trees plantation. To explore the mechanism of blackwater in the reservoir in Eucalyptus plantation, southern China, three typical reservoirs (Najiang, Tianbao, Baihe Reservoirs) were selected in Eucalyptus planting area. Main water quality variables including hydrological and environmental factors were observed 4 times, from August 2015 to April 2016. The physicochemical indexes of water were determined, and then synthetic analysis was performed combined with hydrological data provided by the Nanning Metrological Station. The results indicate that reservoirs in Eucalyptus forest area blackening are associated with a particular season and special climatic conditions. Meanwhile, the instability of water temperature stratification structure is the main driving factor of black materials transport. In summer, hierarchical structure, the water temperature in reservoirs keeping thermal stratification structure stable, results in dissolved oxygen and other water quality indexes were changing with stratification and limits transporting upward. In autumn and winter, stratification disappears, and vertical exchange of water body provides the underlying pollutants with upward force. Finally, pollutants spread the whole body and lead blackwater phenomenon. Seasonality and spatial heterogeneity of sulfide, tannic acid, iron, manganese and other materials is closely related to the seasonal characteristics of water temperature stratification. In the Eucalyptus forest reservoirs, iron and manganese concentrations are up to 2.93 and 3.46 mg/L, respectively. A large amount of tannic acid appeared when Eucalyptus leaves soaked in the water. When sulfide, tannic acid, iron and manganese exist together, a series of reactions such as iron, manganese and sulphur, sulphur and tannic acid, iron, manganese and tannic acid can produce black complex. Our results can provide guidance in guaranteeing the safety of drinking water sources in Eucalyptus planting area and lay the foundation for the further research of black water.

The Influence of Environmental Factors on Employee Comfort Based on an Example of Location Temperature

AbstractWork in unfavorable, changing environmental conditions negatively affects people working on scaffoldings used on construction sites, which may increase the risk of occurrence of dangerous situations. The purpose of this article is to show the scale of temperature changes which workers are exposed to. The paper compares examples of temperature measurements obtained from a metrological station and during tests on scaffoldings located in the Lodz and Warsaw regions. This article also presents the methodology of examining environmental parameters of the surroundings where employees work on scaffoldings. Analysis results show that high temperatures and significant temperature variations frequently occur on the scaffoldings, which leads to a lack of adaptability and consequently to tiredness or decreased alertness. Unfavorable environmental conditions can lead to behaviors which, in turn, can cause accidents.

Assessment of precipitation variability and uncertainty of stream flow in the Hindu Kush Himalayan and Karakoram River basins of Pakistan

The agricultural production system and hydropower production of Pakistan is largely dependent on melting water from the Hindu Kush Himalayan and the Karakoram River basins. Regardless of such significant prominence, a complete evaluation of the prevailing state of hydro-climatic variables is missing. In this context, we examine the precipitation variability and uncertainty of river flows based on diversity indexes and Shannon information entropy theory. The results indicate that the Shannon diversity index presents a clear depiction of precipitation variability on all metrological stations as compared to the Simpson diversity index. The maximum precipitation variability was found at Chilas station as compared to Hunza, Bunji and Gilgit stations. The results also show that the diversity indexes are highly, negatively correlated with standard deviation, and the amount of precipitation is less than 50 mm (dry months). At the decadal scale, the Hunza and Astore stations show higher precipitation evenness as compared to the Skardu, Bunji and Gilgit stations. The uncertainty analysis shows higher entropy value E D = 90% for Indus River gauged at Mangla station. The higher entropy means the greater the chaos of the variables and the lower their certainty. The analysis exhibited that the rivers with high stream flow variability also show low entropy of its distribution and therefore higher stream flow concentration in the annual cycle.

Recognizing Rainfall Pattern for Pakistan using Computational Intelligence

Over the world, rainfall patterns and seasons are shifting in new directions due to global warming. In the case of Pakistan, unusual rainfall events may outcome with droughts, floods and other natural disasters along with disturbance of economy, so the scientific understating of rainfall patterns will be very helpful to water management and for the economy. In this paper, we have attempted to recognize rainfall patterns over selected regions of the Pakistan. All the time series data of metrological stations are taken from the PMD (Pakistan Meteorological Department). Using PCA (Principal Component Analysis), monthly metrological observations of all the stations in Punjab have been analyzed which covers the area of 205,344 km² and includes monsoon-dominated regions. To tackle the problem of inter-annual variations, trend detection, and seasonality, rainfall data of Lahore, the Pakistan is taken that covers the period of 1976-2006. To obtain results, MASH (Moving Average over Shifting Horizon), PCA (Principal Component Analysis) along with other supporting techniques like bi-plots, the Pair-wise correlation has been applied. The results of this study successfully show seasonal patterns, variations and hidden information in complex precipitation data structure.

Integration of Remote Sensing and Hydraulic Models to Identify Flood Prone Areas in Woybo River Catchment, South Western Ethiopia

In line with Climate change rainfall seasonal fluctuation and rainfall amount have major impact on flood and becoming a trait to human life and properties especially on agriculture and different installation. Therefore estimating the runoff and identifying flood prone area at different return period is very essential for effective flood mitigation measure. One of the possible approaches for identifying flood prone area is use of integration of RS with hydraulic models (HECRAS). The present study area is of Woybo River catchment, south western Ethiopia, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), 90 m resolution downloaded from united states geological survey, were used to extract the river geometry. Daily peak rainfall data from tow metrological stations (1990-2013), collected from national metrological agency, were used for estimating design rainfall and runoff for 5, 10, 25, 50, 100 and 200 return period. In HEC-RAS, river geometry, boundary conditions, manning’s n value of different land cover, designed runoff for different return periods were inputted then steady flow analysis was carried out. estimated design rainfall frequency showed expected peak rainfall were 63.2, 70.87, 80.57, 87.77, 94.91 and 102.02 mm and estimated design runoff were 378, 461, 568, 650.5, 733, and 817 m3/se. Steady analysis showed that water surface elevation in the longitudinal profile increase with increasing return period, Inundation area were 1727, 1788, 18560, 1905, 1950 and 1987 ha respectively. The study also suggested that flood prone areas were at the lower reach along the banks of the river extending to 50 m right and left. The finding has been used for planning and decision making in insuring that this areas are protected and limit the risk of damage occurring.

GCMs Derived Projection of Precipitation and Analysis of Spatio-Temporal Variation over N-W Himalayan Region

The ensembles of two Global Climate Models (GCMs) namely, third generation Canadian Coupled Global Climate Model (CGCM3) and Hadley Center Coupled Model, version 3 (HadCM3) are used to project future precipitation in a part of North-Western (N-W) Himalayan region, India. Statistical downscaling method is used to downscale and generate future scenarios of precipitation at station scale from large scale climate variables obtained from GCMs. The observed historical precipitation data has been collected for three metrological stations, namely, Rampur, Sunni and Kasol falling in the basin for further analysis. The future trends and patterns in precipitation under scenarios A2 and A1B for CGCM3 model, and A2 and B2 for HadCM3 model are analyzed for these stations under three different time periods: 2020’s, 2050’s and 2080’s. An overall rise in mean annual precipitation under scenarios A2 and A1B for CGCM3 model have been noticed for future periods: 2020’s, 2050’s and 2080’s. Decrease, in precipitation has been found under A2 and B2 scenarios of HadCM3 model for 2050’s and slight increase for 2080’s periods. Based on the analysis of results, CGCM3 model has been found better for simulation of precipitation in comparison to HadCM3 model.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.1-14

Evaluation of groundwater potential using geospatial techniques

The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas.

ENGLISH

The objective of this study consists to the modeling and prediction of the regime of windin the intention to estimate the potential of wind energy at Douala in Cameroon. The probability densityof windspeed is modeled through an analysis using the Weibull distribution function. The model has been obtained using wind speed data collected from a metrological station at the Airport of Douala. Four methods for calculating the shape and scale parameters of the Weibull wind speed distribution for wind energy analysis are presented: The Maximum likelihood method, the Graphical method, the Empirical method and the proposed Energy pattern factor method. The application of these four methods is effective using a sample wind speed data set. With some statistical analysis, a comparison of the accuracy of each method is also performed. The study helps to determine that Empirical method is the most effective (K= 2.80 and C= 1.97).

Integrated Water Resource Management (IWRM): A Case Study of Durlung Watershed, Bagmati Zone, Nepal

Water in Nepal is a key strategic natural resource, which has the potential to lead the all round development and economic growth of the country. Integrated Water Resource Management (IWRM) is a holistic management approach, integrating land water interaction, socio economic groups, upstream downstream relations, indigenous knowledge, and institutions built up, along the temporal dimensions based on an agreed set of principles. It is a bottom-up decentralized approach for the management of water resources. IWRM is a challenge to conventional practices, attitudes and professional certainties. It confronts entrenched sectoral interest & requires that the water resources are managed holistically for the benefits of all.The broad objective of the multidisciplinary study was to assess the possibilities of Human Dimensions of water resource development and its management. Water resource accounting is done by the collection of water resources data through participatory group formation. Scientific data of hydro and metrological stations was also acquired. Hydrological modeling tools were also used. Feasibility of hydropower plant and potential of power production in the basin was readily estimated.Total daily discharge of the Durlung Watershed was estimated on an average of 157 Million Liters. Rivers of the watershed are turbulent, unsteady & flowing with very high current, which can be utilized by local people for low cost drinking water, tourism, irrigation & hydropower generation. Micro-hydropower production possibilities in Ratan and Deuta rivers have shown multidimensional positive impacts on socio-economic development of the region. Level of community partnership in IWRM and synchronization with the local, district & national level institutional framework for Basin Management was observed to be satisfactory. Participatory research was carried to identify water resource base with school & community partnership. Community motives, their difficulties and gaps in community level organization were identified. For capabilities of community to take over the responsibilities of IWRM concept, there is a lot more need of training and capacity building for now. HYDRO Nepal Journal of Water Energy and EnvironmentVolume- 18, 2016, JanuaryPage -47 to 54

Obtaining Soft X-ray Emission and Absorption Spectra Using SR from the VEPP-4 Storage Ring on the Metrology Station “Cosmos”

The experimental equipment of the metrology station “Cosmos” was adjusted for obtaining soft X-ray emission (XES) and absorption (XANES) spectra of reference samples. In the present work were used two different optical schemes: flat (Bragg-scheme) and cylindrically bent crystals (Johann scheme). Experimental XES and XANES spectra were compared with the spectra obtained on a laboratory X-ray spectrometer and the results of the quantum-chemical calculations.

Analysis of Monthly Rainfall Data Prediction for Change of Economic Environment in Pampadumpara Using Gamma distribution

The Gamma distribution model is well en suite to the monthly and annual rainfall estimate detection. The rainfall gauging station of Pampadumpara, Idukki district metrological station data is being used. This study tests the goodness-of-fit using the Kolmogorov-simirnov (KS) test, and compare these results against gamma distribution which is commonly used during rainfall events. This distribution makes it feasible to estimate the likelihood of rainfall being within the specified range. In this paper, we consider the application of Gamma distribution in modelling intense rainfall. The distribution was applied to the monthly rainfall data from Pampadumpara station with the observation period from January 1978 to December 2013. The figures showed that the annual daily maximum rainfall received at any time ranged between 0.0 mm (Min) to 775.5 mm (Max) indicating a diverse range of fluctuation during the period of study. For this set of figures, Gamma distribution is opted for a better performance. The scientific results clearly established that the analytical procedure devised and tested in this study may be suitably applied for the identification of the best fit probability distribution of weather parameters. The distribution level is very good to predict the maximum monthly rainfall. The results showed that the Gamma distribution is very appropriate for extreme monthly rainfall. These models are used as decision making tools for food security, water management, agriculture, and hydroelectric power providing decision.

Climatic Zones of Sri Lanka under Changing Climate

Climate change is the major phenomenon and fundamental human development challenge of the 21st century. It is well known that all climatic regions in Sri Lanka have been experienced with severe climatic changes. As a result, entire flora and fauna including humans are vulnerable to these adverse consequences. In general, it is believed that nations would mitigate the climate change or adapt to the changing environments. For employment of such measures, it is necessary to understand the macro-climatic region and their behavior under the changing global climate. Based on the annual rainfall received, the country is divided mainly into four climatic zones: wet, intermediate, dry and arid. The climate of the country depends largely on the monsoon wind patterns and series of temperature. Therefore, it is necessary to understand the climatic zones and their behavior to identify each climatic zone‟s minor and major climate changes. The main objective of this study was to study on macro-climatic regions of Sri Lanka under changing climate. Therefore, the present study was carried out on macro-climatic regions of the island to find out the potential variation of temperature and rainfall patterns. Climatic data for the 30 year period were collected from randomly selected metrological stations in each climatic zone and average temperature and rainfall data were analysed using least significant difference (LSD) test. The results showed that average temperature of the country has increased 0.4° C from the year 1869 to 1980. Kandy (intermediate zone) region shows the higher temperature after the year of 1886 named as colonial era which was prevalent for deforestation and tea cultivation. A significantly increasing trend of temperature and decreasing trend of rainfall could be observed entirely within wet zone, dry zone and intermediate zone in 20th century than 19th century. Findings reveal that the wet zone boundary has squeezed in and dry zone boundary has expanded in recent time. Such boundary movements of the zones are significantly important on reclassification of the dry zone and intermediate zone. Therefore, further studies on climate regions of Sri Lanka under changing climate is needed to examine the relationship between the vegetation cover distribution changes within the boundary of the climatic zones. Hence researchers could identify wet and intermediate zones as a “micro-climatic zones” while dry zone could be identified as a “macro-climatic zone” instead of traditionally generalised term in future. Keywords: Changing climate, Climatic zones, Macro-climatic region, Zone boundary movement, Colonial era

ANALYSIS OF RAINFALL DATA TO ESTIMATE RAIN CONTRIBUTION TOWARDS CROP WATER REQUIREMENT USING CROPWAT MODEL

A study was carried out to define the analysis of rainfall data in order to estimate its contribution towards crop water requirements to overcome these problems. Rainfall and climatic data was collected from metrological stations, C.P UAF rain gauge (A), (AARI), (B), (CAA), (C) and (WAPDA), (D), Faisalabad of given region and this data was reserved for cross validation. The test station’s (A) rainfall data was subjected to double mass curve technique to check its consistency with respect to other rainfall stations (B, C and D) in that area. The results derived by double curve technique were accurate for interested gauge station because there was no any break in curve. Then this consistent data was used to determine effective rainfall. The ETo was established by using penman-monteith method in the course of CROPWAT model and its effect with respect to other parameters like sun shine hour, wind speed, maximum & minimum temperature and rainfall humidity were determined. It was founded that the reference evapotranspiration (ETo) is more during April to September due to increase in temperature and low in remaining months. After that data was placed in the model to acquire crop water requirement and irrigation of illustrative crops (wheat & maize) from the district. Through which we estimated that 7.5% rainfall for wheat and 15.5% rainfall for maize can contribute in actual irrigation per year. Through which we determined that 92.5 % and 84.5 % irrigation is required for wheat and maize crop respectively.

A Study on Disastrous Law of Flood in Hubei Province

Using the daily precipitation and disaster census data of 76 metrological stations in Hubei province from 1960 to 2005, the authors studied the temporal-spatial distributions and disastrous laws of flood. The results show that the frequent occurrence area of flood mainly occurred along the river, with the high value center in Tongshan, Chibi and Chongyang. The average annual occurrences of flood disaster showed three different tendency periods from 1960 to 2005, with a decrease of stations of flood after 1996. The flood disaster mainly concentrated in summer. The overall variation trend of flood disaster-causing intensity is quasi periodic oscillation. Both of the damaged areas of agriculture crops and agricultural economic losses reached maximum values in the 1990s, and with a correlation coefficient of 0.80 between the two variables. There was good relationship between the flood-affected population and direct economic losses. The increasing speed of direct economic losses was accelerated with the growth of flood-affected population, while the abilities to prevent flood disaster were also strengthened.

A Basic Wind Speed Map for Oman

The aim of this research was to develop the first basic wind speed map for Oman. Hourly mean wind speed records from 40 metrological stations were used in the calculation. The period of continuous records ranged from 4–37 years. The maximum monthly hourly mean and the maxima annual hourly mean wind speed data were analysed using the Gumbel and Gringorten methods. Both methods gave close results in determining basic wind speeds, with the Gumbel method giving slightly higher values. Due to a lack of long-term records in some regions of Oman, basic wind speeds were extrapolated for some stations with only short-term records, which were defined as those with only 4– 8 years of continuous records; in these cases, monthly maxima were used to predict the long-term basic wind speeds. Accordingly, a basic wind speed map was developed for a 50-year return period. This map was based on basic wind speeds calculated from actual annual maxima records of 29 stations with at least 9 continuous years of records as well as predicted annual maxima wind speeds for 11 short-term record stations. The basic wind speed values ranged from 16 meters/second (m/s) to 31 m/s. The basic wind speed map developed in this research is recommended for use as a guide for structural design in Oman.

Implementation and economical study of HAWT under different wind scenarios

Wind energy has seen a tremendous growth over the past decade and continues to grow into a major player into the renewable energy market. More than 3% of global electricity supply comes from wind power in 2012. The technology continues to mature thereby reducing the deployment cost at a value competing with the least expensive natural gas power plant. Diligent analysis of the wind including average wind speed, wind gust, boundary layer, seasonal and diurnal wind pattern adding to land mortgage, public perception, road and grid accessibility are all key factors for successful and profitable wind turbine implementation. In this work, the implementation of wind energy in Abu Dhabi was considered. In this study the annual wind data recorded every 10min at Masdar metrological station over a period of three years from 2010 to 2012 are analyzed. The probability density distributions are derived from time series data and the distributional parameters are identified. It is followed by fitting the measured wind data with the maximum likelihood Weibull distribution. The power curves of two commercially available horizontal axis wind turbines (HAWTs) a large size 600kW and small size 3.5kW are coupled with the modelled data to account for the annual energy production and capacity factor. Considering the turbine efficiency, economical study that evaluates the cost of wind energy implementation, returns on investment are conducted accounting for capital cost, annuity, depreciation and operation and maintenance.

Spatial interpolation of climatic variables in a predominantly arid region with complex topography

The benefits of accurately interpolating spatial distribution patterns of precipitation and temperature are well recognized. However, precipitation and temperature patterns are difficult to understand in a region that has complex topography and poor meteorological information. In this study, geostatistical and deterministic interpolation methods are used to understand the best modeling approach for mapping precipitation and temperature in a data-scarce arid region of Pakistan, where elevation and climate vary widely within a short distance. Long-term climate data collected from 15 metrological stations distributed over the Balochistan province of Pakistan are used for this purpose. The performances of various deterministic and geostatistical methods are assessed by using root mean squared errors in interpolation. The results show a difference in accuracy among interpolation methods. Incorporation of elevation significantly improves the accuracy of the interpolation of climate variables. The study concluded that the most preferable models for reliable mapping of precipitation and temperature for such region are disjunctive and universal cokriging.

Italian neutron sources

Many research activities, instrumental analysis, studies of radiation damage, etc., require neutron sources. The main neutron sources present in Italy are described in three different sections: nuclear research reactors, accelerator driven, and metrology stations. The nuclear research reactors of LENA (University of Pavia) and ENEA Casaccia are described in terms of irradiation facilities available, neutron flux for each of them and the main activities carried out by each research centre. In the second section, the Frascati Neutron Generator (FNG), the Frascati Beam-Test Facility (BTF) and their main features are reported. In the last section there is a detailed description of the institutional role and the main activities carried out in the field of neutron metrology by the National Institute for Metrology of Ionizing Radiation (INMRI) with a brief description of neutron sources of which the institute is endowed.

English

Weather forecasting is the application of science and technology to predict the state of the atmosphere for a future time at a given location. It is carried out by collecting quantitative data about the current state of the atmosphere and past and/or present experiences. In this study Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multiple linear regression model were used to analyze metrological data sets obtained from the metrological station. The Multiple linear regression model is simple due to the fact that it uses simple mathematical equation using Multiple Linear Regression (MLR) equations that can be easily understood by a medium educated farmer. Adaptive Neuro- Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different kinds of problems.The data covers a five year period (2008-2012) were for the monthly means of minimum and maximum temperature, wind speed, and relative humidity and mean sea level pressure (MSLP). The results showed that both models could be applied to weather prediction problems. The performance evaluation of the two models that was carried out on the basis of root mean square error (RMSE) showed that the ANFIS model yielded better results than the multiple linear regression (MLR) model with a lower prediction error.

A statistical method based on remote sensing for the estimation of air temperature in China

ABSTRACTEnvironmental applications require accurate air temperature (Tair) datasets with different temporal and spatial resolutions. Existing methods generally improve the estimation accuracy ofTairusing environmental variables as auxiliary data to overcome problems related to sparse metrological stations. However, these data are always fixed and do not comprehensively explain the variations inTairvalues at all temporal and spatial scales. Moreover, these methods seldom consider the spatial heterogeneity of relationships betweenTairand auxiliary data. This heterogeneity is often caused by several factors, such as land type, topography, and climate. This study proposes an estimation method to produce maximum, minimum, and meanTair(Tmax,Tmin, andTmean) datasets at different temporal and spatial resolutions using satellite‐derived digital elevation model data and both nighttime and daytime land surface temperature data as auxiliary data. The method is based on the assumption that the relationships betweenTairand the chosen auxiliary data vary spatially. These relationships were further explored using geographically weighted regression with adaptive bi‐square kernel function. The derived relationships were used to construct aTairestimation model. MonthlyTairdata with 5‐km resolution and 8‐dayTairdata with 1‐km resolution were produced for 2010. The results show that the proposed method can accurately represent the variations inTair; theR2values were in the range of 0.95–0.99 for the monthlyTairdata and 0.93–0.99 for the 8‐dayTairdata. The root mean square errors (RMSEs) for the monthly and 8‐dayTmax,Tmin, andTmeandata of the year 2010 were 1.29 and 1.45 °C, 1.24 and 1.29 °C, and 0.8 and 1.2 °C, respectively. These results were compared with those from other estimation methods, specifically the estimation ofTairbased on multiple linear regression (EATMLR) and regression kriging (EATRK). The proposed method was found to produce RMSEs that were 25–26% smaller than EATMLR and 34–42% smaller than EATRK.