Long-term variations of surface air temperature at major industrial cities of India

Local temperature is one of the major climatic elements to record the changes in the atmospheric environment brought about by industrialization and urbanization. Long-term variations of seasonal and annual surface air temperature at six major industrial cities of India (Calcutta, Bombay, Madras, Bangalore, Pune and Delhi) have been studied, using data for the past 86 to 112 yr. Comparative analysis of the temperature data of six nonindustrial stations has also been done. The long-term change in the temperature has been evaluated by linear trend. Calcutta, Bombay and Bangalore have shown significant warning trend, while Delhi has shown a cooling trend. The trends at Madras and Pune are not significant. The nonindustrial stations did not show significant trends. In general, there was either a cooling tendency or cessation of warming, after the late 1950s at most of the industrial cities.     

Trend analysis for rainfall in Delhi and Mumbai, India

Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951–1980 and 1981–2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Ni?o- Southern Oscillation and East Atlantic Pattern.     

2009/2010年北半球冬季异常低温分析

分析了2009/2010年冬季(2009年12月1日至2010年2月28日,简称09/10年冬季)北半球地面气温异常特征及同期的水平与垂直环流场的异常结构。结果表明地面气温的异常呈现出带状的分布,表现为在低纬度为正异常、中纬度负异常及高纬度正异常的"正负正"的分布特征,最大的降温区在欧亚大陆和美国东部,其中局部的降温超过了-4℃。09/10年冬季北半球中纬度的地面气温相比过去15年冬季的平均值下降了近1℃,而在欧亚大陆的局部地区降温超过了-8℃。水平环流场的异常特征为:海平面气压和位势高度均表现为高纬度正异常而中纬度负异常的"北高南低"的分布特征,与此同时,中纬度出现气旋式的异常环流而高纬出现反气旋式的异常环流,这种分布形势在高低层表现得较为一致。经圈环流异常特征为:费雷尔环流减弱,中纬度出现异常的上升运动而高纬度出现异常的下沉运动,与此同时,中纬度对流层气温降低,而低纬度和高纬度的对流层气温升高,副热带急流增强,而极地急流减弱。09/10年冬季北半球环流的异常特征与北半球环状模(NAM)负位相时的极为相似。对多年冬季北半球地面气温和NAM指数进行合成和相关分析,结果表明当NAM处于正(负)位相时,北半球中纬度地面气温出现正(负)异常带,并且在欧亚大陆和美国东部最为显著,局部升温(降温)的幅度达到2℃。在热带外地区,经向温度平流是控制温度局地变化的关键因子。NAM影响北半球地面气温的物理机制分析表明,NAM主要是通过影响经向温度平流来影响北半球中纬度气温的。当NAM为正位相时,北半球费雷尔环流加强,中纬度带和高纬度带发生大气质量的交换,海平面气压场表现为中纬度异常高压而高纬度异常低压的"南高北低"的分布特征,中纬度地表出现异常的南风,进而经向暖平流加强,最终导致中纬度地面气温升高,NAM负位相年时与之相反。这个结果揭示了NAM作为自然变率对中纬度地面气温的调控作用。     

Climate-induced changes in river water temperature in North Iberian Peninsula

With the surface air temperature (SAT) data at 37 stations on Central Yunnan Plateau (CYP) for 1961–2010 and the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, the temporal-spatial patterns of the SAT trends are detected using Sen’s Nonparametric Estimator of Slope approach and MK test, and the impact of urbanization on surface warming is analyzed by comparing the differences between the air temperature change trends of urban stations and their corresponding rural stations. Results indicated that annual mean air temperature showed a significant warming trend, which is equivalent to a rate of 0.17 °C/decade during the past 50 years. Seasonal mean air temperature presents a rising trend, and the trend was more significant in winter (0.31 °C/decade) than in other seasons. Annual/seasonal mean air temperature tends to increase in most areas, and higher warming trend appeared in urban areas, notably in Kunming city. The regional mean air temperature series was significantly impacted by urban warming, and the urbanization-induced warming contributed to approximately 32.3–62.9 % of the total regional warming during the past 50 years. Meantime, the urbanization-induced warming trend in winter and spring was more significant than that in summer and autumn. Since 1985, the urban heat island (UHI) intensity has gradually increased. And the urban temperatures always rise faster than rural temperatures on the CYP.     

Detecting climate change signals in Saudi Arabia using mean annual surface air temperatures

Climate change signals in Saudi Arabia are investigated using the surface air temperature (SAT) data of 19 meteorological stations, well distributed across the country. Analyses are performed using cumulative sum, cumulative annual mean, and the Mann–Kendall rank statistical test for the period of 1978–2010. A notable change in SAT for the majority of stations is found around 1997. The results show a negative temperature trend (cooling) for all stations during the first period (1978–1997), followed by a positive trend (warming) in the second period (1998–2010) with reference to the entire period of analysis. The Mann–Kendall test confirms that there is no abrupt cooling at any station during the analysis period, reflecting the warming trend across the country. The warming trend is found to be 0.06 °C/year, while the cooling trend is 0.03 °C/year, which are statistically significant.     

Assessment of urban heat island effect for different land use–land cover from micrometeorological measurements and remote sensing data for megacity Delhi

Urban heat island intensities (UHI) have been assessed based on in situ measurements and satellite-derived observations for the megacity Delhi during a selected period in March 2010. A network of micrometeorological observational stations was set up across the city. Site selection for stations was based on dominant land use–land cover (LULC) classification. Observed UHI intensities could be classified into high, medium and low categories which overall correlated well with the LULC categories viz. dense built-up, medium dense built-up and green/open areas, respectively. Dense urban areas and highly commercial areas were observed to have highest UHI with maximum hourly magnitude peaking up to 10.7 °C and average daily maximum UHI reaching 8.3 °C. UHI obtained in the study was also compared with satellite-derived land surface temperatures (LST). UHI based on in situ ambient temperatures and satellite-derived land surface temperatures show reasonable comparison during nighttime in terms of UHI magnitude and hotspots. However, the relation was found to be poor during daytime. Further, MODIS-derived LSTs showed overestimation during daytime and underestimation during nighttime when compared with in situ skin temperature measurements. Impact of LULC was also reflected in the difference between ambient temperature and skin temperature at the observation stations as built-up canopies reported largest gradient between air and skin temperature. Also, a comparison of intra-city spatial temperature variations based UHI vis-à-vis a reference rural site temperature-based UHI indicated that UHI can be computed with respect to the station measuring lowest temperature within the urban area in the absence of a reference station in the rural area close to the study area. Comparison with maximum and average UHI of other cities of the world revealed that UHI in Delhi is comparable to other major cities of the world such as London, Tokyo and Beijing and calls for mitigation action plans.     

站网均匀化订正对中国夏季气温EOF分析的改进

本文对中国160站站网上1960～2010年夏季(6～8月)气温距平场序列进行了站网均匀化订正,对订正前、后的气温距平场序列作了EOF分析.结果表明:(1)订正后的前3个典型场高绝对值区均衡分布在三北(东北、华北、西北)地区、青藏高原和长江中下游地区,与夏季气温均方差场高值区位置基本一致;订正前的前3个特征向量高绝对值...     

Principal component analysis and neurocomputing-based models for total ozone concentration over different urban regions of India

The present study deals with daily total ozone concentration time series over four metro cities of India namely Kolkata, Mumbai, Chennai, and New Delhi in the multivariate environment. Using the Kaiser–Meyer–Olkin measure, it is established that the data set under consideration are suitable for principal component analysis. Subsequently, by introducing rotated component matrix for the principal components, the predictors suitable for generating artificial neural network (ANN) for daily total ozone prediction are identified. The multicollinearity is removed in this way. Models of ANN in the form of multilayer perceptron trained through backpropagation learning are generated for all of the study zones, and the model outcomes are assessed statistically. Measuring various statistics like Pearson correlation coefficients, Willmott’s indices, percentage errors of prediction, and mean absolute errors, it is observed that for Mumbai and Kolkata the proposed ANN model generates very good predictions. The results are supported by the linearly distributed coordinates in the scatterplots.     

Determining optimum tilt angles of solar surfaces in Sakarya,Turkey

Climate change constitutes a major challenge for high productivity in wheat, the most widely grown crop in Germany. Extreme weather events including dry spells and heat waves, which negatively affect wheat yields, are expected to aggravate in the future. It is crucial to improve the understanding of the spatiotemporal development of such extreme weather events and the respective crop-climate relationships in Germany. Thus, the present study is a first attempt to evaluate the historic development of relevant drought and heat-related extreme weather events from 1901 to 2010 on county level (NUTS-3) in Germany. Three simple drought indices and two simple heat stress indices were used in the analysis. A continuous increase in dry spells over time was observed over the investigated periods from 1901–1930, 1931–1960, 1961–1990 to 2001–2010. Short and medium dry spells, i.e., precipitation-free periods longer than 5 and 8 days, respectively, increased more strongly compared to longer dry spells (longer than 11 days). The heat-related stress indices with maximum temperatures above 25 and 28 °C during critical wheat growth phases showed no significant increase over the first three periods but an especially sharp increase in the final 1991–2010 period with the increases being particularly pronounced in parts of Southwestern Germany. Trend analysis over the entire 110-year period using Mann-Kendall test revealed a significant positive trend for all investigated indices except for heat stress above 25 °C during flowering period. The analysis of county-level yield data from 1981 to 2010 revealed declining spatial yield variability and rather constant temporal yield variability over the three investigated (1981–1990, 1991–2000, and 2001–2010) decades. A clear spatial gradient manifested over time with variability in the West being much smaller than in the east of Germany. Correlating yield variability with the previously analyzed extreme weather indices revealed strong spatiotemporal fluctuations in explanatory power of the different indices over all German counties and the three time periods. Over the 30 years, yield deviations were increasingly well correlated with heat and drought-related indices, with the number of days with maximum temperature above 25 °C during anthesis showing a sharp increase in explanatory power over entire Germany in the final 2001–2010 period.     

Spatial and temporal changes in aridity index in northwest China: 1960 to 2010

Northwest China is the driest region in China and the regional climate fluctuated dramatically during the last century. Aridity index, as the ratio between potential evapotranspiration and precipitation, is a good indicator to represent regional climate character. In this study, the change and attribution of the aridity index was investigated in northwest China using the observed climate data from 80 national meteorological stations during 1960–2010. The spatial and temporal variabilities of the aridity index shows that the annual aridity index decreased significantly (P?<?0.05) by 0.048 year^?1, indicating that northwest China became wetter from 1960 to 2010. A differentiation equation method was used to attribute the change in aridity index to climate variables. The results indicate that the aridity index was most sensitive to the change in precipitation, followed by vapor pressure, solar radiation, wind speed, and air temperature. Increase in air temperature should have led to an increase in aridity index, but this effect had been offset by the increase in precipitation and vapor pressure and the decrease in wind speed. Increasing precipitation, which contributed 91.7 % of the decrease in the aridity index, was the dominant factor to the decrease in the aridity index in northwest China from 1960 to 2010.     

Sensitivity analysis of climate on streamflow in north China

The economics and crowded cities of north China play important roles in China’s overall economic development. Streamflow is a hot issue in ecohydrological studies, and research into changes in streamflow in north China is of great significance. In this study, the sensitivities of streamflow to the aridity index, precipitation, and potential evapotranspiration are evaluated to assess the impact of climatic variation in streamflow in north China. The results show that the average coefficient of sensitivity of streamflow to aridity index is ?2.24, and streamflow would decrease by 22.4 % with a 10 % increase in the aridity index. The average coefficients of sensitivity of streamflow to precipitation and potential evapotranspiration are 3.21 and ?2.21, respectively. A 10 % increase in precipitation or potential evapotranspiration would induce a 32.1 % increase or a 22.1 % decrease of streamflow, respectively. Basins with low streamflows would be more sensitive to climatic variation than basins with high streamflows.     

An Approach to Quantify the Heat Wave Strength and Price a Heat Derivative for Risk Hedging

Mitigating the heat stress via a derivative policy is a vital financial option for agricultural producers and other business sectors to strategically adapt to the climate change scenario. This study has provided an approach to identifying heat stress events and pricing the heat stress weather derivative due to persistent days of high surface air temperature (SAT). Cooling degree days (CDD) are used as the weather index for trade. In this study, a call-option model was used as an example for calculating the price of the index. Two heat stress indices were developed to describe the severity and physical impact of heat waves. The daily Global Historical Climatology Network (GHCN-D) SAT data from 1901 to 2007 from the southern California, USA, were used. A major California heat wave that occurred 20-25 October 1965 was studied. The derivative price was calculated based on the call-option model for both long-term station data and the interpolated grid point data at a regular 0.1 ×0.1 latitude-longitude grid. The resulting comparison indicates that (a) the interpolated data can be used as reliable proxy to price the CDD and (b) a normal distribution model cannot always be used to reliably calculate the CDD price. In conclusion, the data, models, and procedures described in this study have potential application in hedging agricultural and other risks.     

Urbanization effects on the air temperature rise in Saudi Arabia

We study the possible effects of urbanization on the rise of air temperature in Saudi Arabia for the period 1981–2010. The effects of variations in elevation and marine temperature on the air temperature trend are also investigated. Surface air temperature data are analyzed for 24 sites which are mostly located at the airports across the country. The population data for the current (2010) and earlier (2004 and 1992) censuses are used for the nearest cities where the observation sites are located. A national average is calculated using two different approaches (simple averaging and weighted according to area for 1985–2010 when all stations are available) which gives trends of 0.60 and 0.51 °C/decade respectively, both significant at the 99 % level. We find no link between the temperature increase and population increase nor with elevation at the 24 sites which are mostly located in the urban effected area but not at the city centers. This suggests that the rise in air temperature is not likely due to urbanization changes resulting from the population increases.     

Changes in extreme daily rainfall for São Paulo, Brazil

Significant positive trends are found in the evolution of daily rainfall extremes in the city of São Paulo (Brazil) from 1933 to 2010. Climatic indices including ENSO, PDO, NAO and the sea surface temperature at the coast near São Paulo explain 85 % of the increasing frequency of extremes during the dry season. During the wet season the climatic indices and the local sea surface temperature explain a smaller fraction of the total variance when compared to the dry season indicating that other factors such as the growth of the urban heat island and the role of air pollution in cloud microphysics need to be taken into account to explain the observed trends over the almost eight decades.     

Long-term variability in the date of monsoon onset over western India

The date of onset of the southwest monsoon in western India is critical for farmers as it influences the timing of crop plantation and the duration of the summer rainy season. Identifying long-term variability in the date of monsoon onset is difficult, however, as onset dates derived from the reanalysis of instrumental rainfall data are only available for the region from 1879. This study uses documentary evidence and newly uncovered instrumental data to reconstruct annual monsoon onset dates for western India for the period 1781–1878, extending the existing record by 97 years. The mean date of monsoon onset over the Mumbai (Bombay) area during the reconstruction period was 10 June with a standard deviation of 6.9 days. This is similar to the mean and standard deviation of the date of monsoon onset derived from instrumental data for the twentieth century. The earliest identified onset date was 23 May (in 1802 and 1839) and the latest 22 June (in 1825). The longer-term perspective provided by this study suggests that the climatic regime that governs monsoon advance over western India did not change substantially from 1781 to 1955. Monsoon onset over Mumbai has occurred at a generally later date since this time. Our results indicate that this change is unprecedented during the last 230 years. Following a discussion of the results, the nature of the relationship between the date of monsoon onset and the El Niño-Southern Oscillation is discussed. This relationship is shown to have been stable since 1781.     

Impact of surface observations on simulation of rainfall over NCR Delhi using regional background error statistics in WRF-3DVAR model

In this study, efforts are made to improve the simulation of heavy rainfall events over National Capital Region (NCR) Delhi during 2010 summer monsoon, using additional observations from automatic weather stations (AWS). Two case studies have been carried out to simulate the relative humidity, wind speed and precipitation over NCR Delhi in 48-h model integrations; one from 00UTC, August 20, 2010, and the other from 00UTC, September 12, 2010. Several AWS installed over NCR Delhi in the recent past provide valuable surface observations, which are assimilated into state-of-the-art weather research and forecasting (WRF) model using the three-dimensional variational data assimilation (3DVAR). The quality of background error statistics (BES) is a key component in successful 3DVAR data assimilation in a mesoscale model. In this study, the domain-dependent regional background error statistics (RBS) are estimated using National Meteorological Center method in the months of August and September 2010 and then compared with the global background error statistics (GBS) in the WRF model. The model simulations are analyzed and validated against AWS and radiosonde observations to quantify the impact of RBS. The root mean square differences in the spatial distributions of precipitation, relative humidity and wind speed at the surface showed significant differences between both the global and regional BES. Similar differences are also observed in the vertical distributions along the latitudinal cross section at 28.5°N. Model-simulated fields are analyzed at five different surface stations and one upper air station located in NCR Delhi. It is found that in 24-h model simulation, the RBS significantly improves the model simulations in case of precipitation, relative humidity and wind speed as compared to GBS.     

Trend analysis of precipitation in Jharkhand State,India

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901–2011) from 18 meteorological stations. Autocorrelation and Mann–Kendall/modified Mann–Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt–Mann–Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901–2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901–1949, which was reversed during the subsequent period (1950–2011).     

Quantitative evaluation of climatic variability and risks for wheat yield in India

This study comprises (1) an analysis of recent climate trends at two sites in north-west India (Ludhiana in Punjab and Delhi) and (2) an impact and risk assessment for wheat yields associated with climatic variability. North-west Indian agriculture is dominated by rice-wheat rotation in which the wheat season (‘rabi’, November to March) is characterized by predominantly dry conditions—superimposed by very high inter-annual variability of rainfall (17 to 260 mm in Ludhiana and <1 to 155 mm in Delhi). While rainfall remained without discernable trend over the last three decades, minimum and average temperatures showed increasing trends of 0.06 and 0.03°C year^???1, respectively, at Ludhiana. The site in (metropolitan) Delhi was apparently influenced by city-effects, which was noticeable from the decrease in solar radiation of 0.09 MJ m^???2 day^???1 year^???1. The CERES-wheat model was used to calculate yields of rainfed wheat that were at both locations highly correlated with seasonal rainfall. An assessment framework was developed to quantify yield impacts due to rainfall variability in three steps: (1) data from different years were aggregated into four classes, i.e., years with scarce, low, moderate, and high rainfall, (2) yield records of each rainfall class were ranked according to yield to facilitate (3) a comparison of yields with identical rank, i.e. among the best yield of each class, the second-best, etc. The class with moderate rainfall was taken as baseline yield to compute yield impacts of other rainfall scenarios. Years with scarce rainfall resulted in only 34% (Ludhiana) and 35% (Delhi) of the baseline yield. The yields in years with low rainfall accounted for 61% (Delhi) and 49% (Ludhiana) of the baseline yields. In Ludhiana, high rainfall years resulted in 200% yield as compared to the baseline yield, whereas they reached only 105% in Delhi. Low-intensity (1× and 3×) irrigation decreased the relative yield losses, but entailed a higher vulnerability in terms of absolute yield losses. Only high-intensity (4×) irrigation buffered wheat yields against adverse rainfall years. Early sowing was beneficial for wheat yields under all rainfall scenarios. The framework could be a valuable decision-support tool at the farm level where seasonal rainfall variability is high.     

Climate Change: A Case Study Over India

Summary A brief account of various causes of climate change in recent decades and climate change trends in the Indian region is presented. It is of great importance to determine the influence of human activities on the likely climate change during recent decades. Local temperature is one of the major climatic elements to record the changes in the atmospheric environment caused by industrialization and urbanization. It is mentioned in the literature that there is either a cooling tendency or cessation of warming after the late 1950s at most of the Indian industrial cities. A case study of Nagpur, a centrally located city in India, is done to understand and the possible cause of cooling. Nagpur is the only city in India for which a long-term record of temperature, for urban (Mayo Hospital) and relatively suburban (Sonegaon Airport) area, is available. The study of the diurnal asymmetry in maximum and minimum temperatures indicates that the role of suspended particulate matter dominates over that of increasing greenhouse gases. Received April 15, 1998     

Seasonal and annual trends of carbonaceous species of PM<Subscript>10</Subscript> over a megacity Delhi,India during 2010–2017

PM₁₀ samples were collected to characterize the seasonal and annual trends of carbonaceous content in PM₁₀ at an urban site of megacity Delhi, India from January 2010 to December 2017. Organic carbon (OC) and elemental carbon (EC) concentrations were quantified by thermal-optical transmission (TOT) method of PM₁₀ samples collected at Delhi. The average concentrations of PM₁₀, OC, EC and TCA (total carbonaceous aerosol) were 222?±?87 (range: 48.2–583.8 μg m^?3), 25.6?±?14.0 (range: 4.2–82.5 μg m^?3), 8.7?±?5.8 (range: 0.8–35.6 μg m^?3) and 54.7?±?30.6 μg m^?3 (range: 8.4–175.2 μg m^?3), respectively during entire sampling period. The average secondary organic carbon (SOC) concentration ranged from 2.5–9.1 μg m^?3 in PM₁₀, accounting from 14 to 28% of total OC mass concentration of PM₁₀. Significant seasonal variations were recorded in concentrations of PM₁₀, OC, EC and TCA with maxima during winter and minima during monsoon seasons. In the present study, the positive linear trend between OC and EC were recorded during winter (R²?=?0.53), summer (R²?=?0.59) and monsoon (R²?=?0.78) seasons. This behaviour suggests the contribution of similar sources and common atmospheric processes in both the fractions. OC/EC weight ratio suggested that vehicular emissions, fossil fuel combustion and biomass burning could be the major sources of carbonaceous aerosols of PM₁₀ at the megacity Delhi, India. Trajectory analysis indicates that the air mass approches to the sampling site is mainly from Indo Gangetic plain (IGP) region (Uttar Pradesh, Haryana and Punjab etc.), Thar desert, Afghanistan, Pakistan and surrounding areas.