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At present, air conditioning (AC) is the most effective means for the cooling of indoor space. However, its increased global use is problematic for various reasons. This paper explores the challenges linked to increased AC use and discusses more sustainable alternatives. A literature review was conducted applying a transdisciplinary approach. It was further complemented by examples from cities in hot climates. To analyse the findings, an analytical framework was developed which considers four societal levels—individual, community, city, and national. The main challenges identified from the literature review are as follows: environmental, organisational, socio-economical, biophysical and behavioural. The paper also identifies several measures that could be taken to reduce the fast growth of AC use. However, due to the complex nature of the problem, there is no single solution to provide sustainable cooling. Alternative solutions were categorised in three broad categories: climate-sensitive urban planning and building design, alternative cooling technologies, and climate-sensitive attitudes and behaviour. The main findings concern the problems arising from leaving the responsibility to come up with cooling solutions entirely to the individual, and how different societal levels can work towards more sustainable cooling options. It is concluded that there is a need for a more holistic view both when it comes to combining various solutions as well as involving various levels in society. [ABSTRACT FROM AUTHOR]

Significant changes in climate variables in the last decades resulted in changes of perceived climate conditions. However, there are only few studies discussing long-lasting changes in bioclimatic conditions. Thus, the purpose of this paper is to present the temporal and spatial distribution of hazardous heat and cold stress conditions in different regions of Poland. Its focus is on long-lasting changes in such conditions in the period 1951–2018. To assess changes in hazardous thermal stress conditions, the Universal Thermal Climate Index (UTCI) was used. UTCI values at 12 UTC hour (respectively 1 pm winter time, 2 pm summer time) were calculated daily based on air temperature, relative humidity, total cloud cover and wind speed at 24 stations representing the whole area of Poland. We found that the greatest changes were observed in minimum (1.33 °C/10 years) and average (0.52 °C/10 years) UTCI values as well as in cold stress frequency (− 4.00 days per 10 years). The changes vary seasonally and regionally. The greatest increase in UTCImin and decrease in cold stress days were noted from November to March and had the highest values in north-east and east Poland, and also in the foothills of the Carpathian Mountains. The trends in maximum UTCI are much smaller and not always positive. The spatially averaged trend in UTCImax for Poland as a whole was 0.35 °C/10 years and the increase in heat stress days was 0.80 days/10 years. The highest increases in UTCImax and heat stress days were noted in eastern and south-eastern Poland. [ABSTRACT FROM AUTHOR]

Various human heat stress indices have been developed to relate atmospheric measures of extreme heat to human health impacts, but the usefulness of different indices across various health impacts and in different populations is poorly understood. This paper determines which heat stress indices best fit hospital admissions for sets of cardiovascular, respiratory, and renal diseases across five Australian cities. We hypothesized that the best indices would be largely dependent on location. We fit parent models to these counts in the summers (November-March) between 2001 and 2013 using negative binomial regression. We then added 15 heat stress indices to these models, ranking their goodness of fit using the Akaike information criterion. Admissions for each health outcome were nearly always higher in hot or humid conditions. Contrary to our hypothesis that location would determine the best-fitting heat stress index, we found that the best indices were related largely by health outcome of interest, rather than location as hypothesized. In particular, heatwave and temperature indices had the best fit to cardiovascular admissions, humidity indices had the best fit to respiratory admissions, and combined heat-humidity indices had the best fit to renal admissions. With a few exceptions, the results were similar across all five cities. The best-fitting heat stress indices appear to be useful across several Australian cities with differing climates, but they may have varying usefulness depending on the outcome of interest. These findings suggest that future research on heat and health impacts, and in particular hospital demand modeling, could better reflect reality if it avoided “all-cause” health outcomes and used heat stress indices appropriate to specific diseases and disease groups. [ABSTRACT FROM AUTHOR]

Based on the daily data of relative humidity from 23 meteorological stations in the Tarim River Basin of northwest China during the period from 1961 to 2010, this paper analyzed the multifractal and long memory property of humidity process. Main findings are as follows: (1) The processes present scaling and multifractal property. (2) The left-skewed multifractal spectrum f( α) indicates that the time series of relative humidity is predominated by small fluctuations. (3) There exists long memory with the δ ∈ (0, 0.5) in the processes, except for Kalpin and Aksu's exhibiting non-stationary long memory with the parameter δ being 0.67 and 0.69 respectively. (4) We found that on the whole, the degree of multifractality exhibits a strengthening trend with the longitude and latitude increasing, but decreasing trend with elevation rising; For length of long memory, we investigated that on the whole, the δ values increased with the longitude and latitude increasing, which indicates that the bigger the longitude and latitude is, the longer the memory of humidity process is, but the higher the elevation is, the shorter the memory of humidity process is. [ABSTRACT FROM AUTHOR]

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean values as surrogates of the instantaneous ones in several studies that aimed to assess the impact of global warming on fire. In this paper we test the sensitivity of FWI values to both instantaneous and daily mean values, analyzing their effect on mean seasonal fire danger (seasonal severity rating, SSR) and extreme fire danger conditions (90th percentile, FWI90, and FWI>30, FOT30), with a special focus on its influence in climate change impact studies. To this aim, we analyzed reanalysis and regional climate model (RCM) simulations, and compared the resulting instantaneous and daily mean versions both in the present climate and in a future scenario. In particular, we were interested in determining the effect of these datasets on the projected changes obtained for the mean and extreme seasonal fire danger conditions in future climate scenarios, as given by a RCM. Overall, our results warn against the use of daily mean data for the computation of present and future fire danger conditions. Daily mean data lead to systematic negative biases of fire danger calculations. Although the mean seasonal fire danger indices might be corrected to compensate for this bias, fire danger extremes (FWI90 and specially FOT30) cannot be reliably transformed to accommodate the spatial pattern and magnitude of their respective instantaneous versions, leading to inconsistent results when projected into the future. As a result, we advocate caution when using daily mean data and strongly recommend the application of the standard definition for its calculation as closely as possible. Threshold-dependent indices derived from FWI are not reliably represented by the daily mean version and thus can neither be applied for the estimation of future fire danger season length and severity, nor for the estimation of future extreme events. [ABSTRACT FROM AUTHOR]

We analyzed trends of air temperature across the Cévennes National Park in Southern France, a mid-altitude coastal mountain experiencing a rapid spread of forests at the expense of rangelands and submitted to Mediterranean Sea influences and so, impacted by local and regional processes of climate change. Since 1980, April to June warming trend reached a maximum temperature increase of + 0.124 °C year−1 and uniform whatever the altitude. Minimum temperature increased by + 0.058 °C year−1 at 500 m altitude and + 0.089 °C year−1 at 1500 m. Concomitantly, forest cover is increasing by + 0.51% year−1. Using an intrinsic biophysical mechanism model, we demonstrated that, at monthly scale, the forest surface is 1.7–3.1 °C cooler than that of nearby grasslands. As a result, the decrease in albedo corresponding to the conversion from grasslands to dense forests, translates into a cooling of maximum air temperatures of 0.023 °C year−1 which contributes to slow down the warming rate enhancement. Spring warming trends co-varied with negative WeMO phases associated with a low in the Gulf of Cádiz and an anticyclone in Central Europe. An east to west pressure gradient increases atmospheric humidity leading to a strong water vapor feedback, enhancing the forcing of thermal long wave radiations and hence the rise in temperature. [ABSTRACT FROM AUTHOR]

Brown eye spot (Cercospora coffeicola) is one of the main fungal diseases of coffee, leading to a significant drop in crop productivity and beverage quality in Brazil. The identification of potential risk areas for the development of the disease provides promising information for the management of the pathogen. This study aimed to elaborate an agroclimatic zoning for the incidence of brown eye spot on coffee under climate change scenarios, as suggested by IPCC (IPCC-AR5), in the main coffee-growing regions. Climate data of air temperature, precipitation, and relative humidity were collected from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources (NASA/POWER) platform from 1989 to 2020 for 46 municipalities in the states of Paraná, São Paulo, Minas Gerais, Espírito Santo, Goiás, and Bahia. The ideal climate for brown eye spot occurrence consists of an air temperature (Tmean) between 18 and 30 °C, relative humidity (RHmean) > 90%, and leaf wetness duration (LWD) > 9 h. The number of hours of leaf wetness was determined by the sum of hours with relative humidity > 90%. Relative humidity was estimated for each hour of the day using air temperature and estimated data of mean dew point temperature, maximum relative humidity, and minimum relative humidity. Climate change scenarios were designed based on sets of climate simulations for the twenty-first century. Scenario S1 is the current scenario without changes, while scenarios S2 and S3 show Tmean + 1.5 °C and 3.0 °C, respectively, with RHmean without changes. Scenarios S4 and S5 present RHmean varying from − 30% to + 30%, respectively, with Tmean unchanged. In the current scenario (S1), Minas Gerais presented a predominance of 100% for low climate risk to brown eye spot in September. Paraná presented a medium risk in 76.15% of the state in April. Scenarios S2 and S3 showed significant changes, increasing the average fitness class in the study region, mainly in the states of São Paulo, Minas Gerais, Rio de Janeiro, and Paraná. Scenario S4 showed 100% predominance of the low-risk class. In contrast, S5 showed the occurrence of the high-risk class for the study region with a + 30% increase in relative humidity. Minas Gerais presented a predominance of the high-risk class for the development of C. coffeicola in 76%, 100%, 97.83%, 89.30%, 93.46%, 80.64%, and 57.77% from November to May, respectively. The presence of high relative humidity represents the main factor for the expansion of the high-risk class for the development of C. coffeicola. Producers knowing the months of the year and the places in Brazil with the highest incidence of brown eye spot will be able to prevent the disease in a more sustainable way, using more ecological products, such as the early application of copper. [ABSTRACT FROM AUTHOR]

The latitudinal position of mid-latitude storm tracks has large climate impacts affecting the distribution of precipitation, temperature, humidity, and winds over the extratropics. By the end of this century, climate models project a poleward shift of summer mid-latitude storm tracks in the Southern Hemisphere. Most previous mechanisms for the poleward shift of the storm tracks focused on the role of atmospheric temperature changes. However, the relative roles of other climate system components in the projected storm tracks' shift have not been examined to date. Here it is shown that thermodynamic ocean coupling is responsible for the future poleward shift of the storm tracks as it overcomes the effect of dynamic ocean coupling to shift the storm tracks equatorward. These results stress the importance of using full-physics ocean models to investigate the future shift of the storm tracks, and of better monitoring ocean coupling processes to improve our preparedness for future climate changes. Mid-latitude storm tracks control most of the weather and climate variability in the extratropics. Here the authors show that, in the Southern Hemisphere, ocean processes will act to shift the summer storm tracks poleward in coming decades. [ABSTRACT FROM AUTHOR]

The frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman's formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1–2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman. [ABSTRACT FROM AUTHOR]

Unprecedented hot and dry spells occurred all over Israel for six days, from May 16 to May 21, 2020. Maximal air temperature reached 46.5 °C and minimal relative humidity reached 10%. The total number of hours with temperature of ≥40 °C was 45 and 41 in the coastal plain and the Judean mountains foothills, respectively. The downy mildew pathogens of cucumber and grapevine survived this extreme event, showing a rapid revival in nature soon after the heat wave. The current isolates of these oomycetes seem to be more tolerant to heat compared to the isolates of the previous century. [ABSTRACT FROM AUTHOR]

Energy exchanges between atmosphere and glacier surface control the net energy available for snow and ice melt. Based on the meteorological records in Urumqi River Glacier No.1 (URGN1) in the Chinese Tien Shan during the period of 2012–2015, an energy-mass balance model was run to assess the sensitivity of glacier mass balance to air temperature (T), precipitation (P), incoming shortwave radiation (Sin), relative humidity (RH), and wind speed (u) in the URGN1, respectively. The results showed that the glacier melting was mainly controlled by the net shortwave radiation. The glacier mass balance was very sensitivity to albedo for snow and the time scale determining how long the snow albedo approaches the albedo for firn after a snowfall. The net annual mass balance of URGN1 was decreased by 0.44 m w.e. when increased by 1 K in air temperature, while it was increased 0.30 m w.e. when decreased by 1 K. The net total mass balance increased by 0.55 m w.e. when increased precipitation by 10%, while it was decreased by 0.61 m w.e. when decreased precipitation by 10%. We also found that the change in glacier mass balance was non-linear when increased or decreased input condition of climate change. The sensitivity of mass balance to increase in Sin, u, and RH were at −0.015 m w.e.%−1, −0.020 m w.e.%−1, and −0.018 m w.e.%−1, respectively, while they were at 0.012 m w.e.%−1, 0.027 m w.e.%−1, and 0.017 m w.e.%−1 when decreasing in those conditions, respectively. In addition, the simulations of coupled perturbation for temperature and precipitation indicated that the precipitation needed to increase by 23% could justly compensate to the additional mass loss due to increase by 1 K in air temperature. We also found that the sensitivities of glacier mass balance in response to climate change were different in different mountain ranges, which were mainly resulted from the discrepancies in the ratio of snowfall to precipitation during the ablation season, the amount of melt energy during the ablation season, and precipitation seasonality in the different local regions. [ABSTRACT FROM AUTHOR]

A clear rise in seasonal and annual temperatures, a gradual increase of total radiation, and a relative trend of change in seasonal precipitation have been observed for the last four decades in Brussels (Belgium). These local modifications may have a direct and indirect public health impact by altering the timing and intensity of allergenic pollen seasons. In this study, we assessed the statistical correlations (Spearman’s test) between pollen concentration and meteorological conditions by using long-term daily datasets of 11 pollen types (8 trees and 3 herbaceous plants) and 10 meteorological parameters observed in Brussels between 1982 and 2015. Furthermore, we analyzed the rate of change in the annual cycle of the same selected pollen types by the Mann-Kendall test. We revealed an overall trend of increase in daily airborne tree pollen (except for the European beech tree) and an overall trend of decrease in daily airborne pollen from herbaceous plants (except for Urticaceae). These results revealed an earlier onset of the flowering period for birch, oak, ash, plane, grasses, and Urticaceae. Finally, the rates of change in pollen annual cycles were shown to be associated with the rates of change in the annual cycles of several meteorological parameters such as temperature, radiation, humidity, and rainfall. [ABSTRACT FROM AUTHOR]

This study examined the climate variability of heat wave (HW) according to air temperature and relative humidity to determine trends of variation and stress threshold in three major cities of Taiwan, Taipei (TP), Taichung (TC), and Kaohsiung (KH), in the past four decades (1971-2010). According to the data availability, the wet-bulb globe temperature (WBGT) heat stress for the three studied cities was also calculated for the past (2003-2012) and simulated under the future warming scenario for the end of this century (2075-2099) using ECHAM5/MPIOM-WRF (ECW) dynamic downscaling 5-km resolution. Analysis showed that past decade (2001-2010) saw increase not only in the number of HW days in all three cities but also in the duration of each HW event in TP and KH. Simulation results revealed that ECW well captures the characteristics of data distribution in these three cities during 2003-2012. Under the A1B projection, ECW yielded higher WBGT in all three cities for 2075-2099. The WBGT in TP indicated that the heat stress for 50% of the days in July and August by 2075-2099 will be at danger level (WBGT ≥ 31 °C). Even the median of WBGT in TC and KH (30.91 and 30.88 °C, respectively) are close to 31 °C. Hence, the heat stress in all three cities will either exceed or approach the danger level by the end of this century. Such projection under the global warming trend would necessitate adaptation and mitigation, and the huge impact of dangerous heat stress on public health merits urgent attention for Taiwan. [ABSTRACT FROM AUTHOR]

To predict future spatio-temporal patterns of climate change, we should fully understand the spatio-temporal patterns of climate change during the past millennium. But, we are not yet able to delineate the patterns because the qualities of the retrieved proxy records and the spatial coverage of those records are not adequate. Northern Xinjiang of China is one of such areas where the records are not adequate. Here, we present a 500-yr land-surface moisture sequence from Heiyangpo Peat (48.34°N, 87.18°E, 1353 m a.s.l) in the southern Altai Mountains within northern Xinjiang. Specifically, peat carbon isotope value of cellulose (δC) was used to estimate the warm-season moisture variations and the degree of humification was used to constrain the δC-based hydrological interpretation. The climatic attributions of the interpreted hydrological variations were based on the warm-season temperature reconstructed from Belukha ice core and the warm-season precipitation inferred from the reconstructed Atlantic Multidecadal Oscillations (AMO). The results show that humification decreased and the δC-suggested moisture decreased from ~1510 to ~1775 AD, implying that a constant drying condition may have inhibited peat decay. Our comparison with reconstructed climatic parameters suggests that the moisture-level decline was most likely resulted from a constant decline of precipitation. The results also show that humification kept a stable level and the δC-suggested moisture also decreased from ~1775 to ~2013 AD, implying that peat decay in the acrotelm primarily did not depend on the water availability or an aerobic environment. Again, our comparison with reconstructed climatic parameters suggests that the land-surface moisturelevel decline was most likely resulted from a steady warming of growing-season temperature. [ABSTRACT FROM AUTHOR]

Evapotranspiration estimation is of crucial importance in arid and hyper-arid regions, which suffer from water shortage, increasing dryness and heat. A modeling study is reported here to cross-station assessment between hyper-arid and humid conditions. The derived equations estimate ET values based on temperature-, radiation-, and mass transfer-based configurations. Using data from two meteorological stations in a hyper-arid region of Iran and two meteorological stations in a humid region of Spain, different local and cross-station approaches are applied for developing and validating the derived equations. The comparison of the gene expression programming (GEP)-based-derived equations with corresponding empirical-semi empirical ET estimation equations reveals the superiority of new formulas in comparison with the corresponding empirical equations. Therefore, the derived models can be successfully applied in these hyper-arid and humid regions as well as similar climatic contexts especially in data-lack situations. The results also show that when relying on proper input configurations, cross-station might be a promising alternative for locally trained models for the stations with data scarcity. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) represents the evaporative demand of the atmosphere and depends on climatic parameters such as radiation, air temperature, humidity, and wind speed. Relative role of climatic parameter of ET0 varies from one climate to another and within the climate, and depends on the location and time. Sensitivity analysis was conducted and sensitivity coefficients were determined to evaluate the impact of principal climatic parameters on ET0 in Karnal district of India. Mean monthly ET0 and yearly ET0 from 1981 to 2011 were estimated from FAO-56 Penman-Monteith equation using the daily climate data collected from Central Soil Salinity Research Institute, Karnal. Results showed that seasonal and annual ET0 were most sensitive to maximum temperature followed by sunshine hours. However, wind speed, relative humidity, and minimum temperature had varying effect on mean ET0. After maximum temperature and sunshine hours, ET0 was more sensitive to wind speed followed by relative humidity and minimum temperature in summer. In monsoon, after maximum temperature and sunshine hours, ET0 was more sensitive to minimum temperature followed by relative humidity and wind speed. However, in winter, after maximum temperature and sunshine hours, ET0 was more sensitive to relative humidity followed by wind speed and minimum temperature. The study suggests that the climate variability would affect reference ET0; however, its impact on ET0 would be different for different parameters. [ABSTRACT FROM AUTHOR]

Described is the impact of the Aral Sea desiccation on the local climate and the impact of its numerical prediction in the region. Presented is the analysis of two series of numerical experiments with the WRF-ARW model (numerical prediction and weather research) with the spatial resolution of 5 km and 28 σ-surfaces along the vertical up to the level of 50 hPa for the Aral Sea region. In the first series of forecasts for January and July 2009, underlying surface parameters from the MODIS database are used. In these series the sea surface mask corresponds to the Aral Sea configuration in the 1970s. In another group of experiments, the characteristics of the underlying surface of the Aral Sea area are replaced by the respective characteristics of the surrounding land. To study the effects of variations of surface properties, air temperature, humidity, cloudiness, precipitation, and wind are analyzed. It is demonstrated that if the Aral Sea is assumed to be absent in the model, this results in the significant strengthening of the continentality of regional climate and in the increase in the forecast skill scores. The supposition is made that the regular (at least each 3-5 years) update of global databases with the description of underlying surface properties due to the climate change can result in the considerable increase in the accuracy of numerical prediction and climate change modeling. [ABSTRACT FROM AUTHOR]

The structure parameters of temperature and humidity are important in scintillometry as they determine the structure parameter of the refractive index of air, the primary atmospheric variable obtained with scintillometers. In this study, we investigate the variability of the logarithm of the Monin-Obukhov-scaled structure parameters (denoted as $$\log ({\widetilde{C_{s}^2}_{\mathrm {}}})$$ ) of temperature and humidity. We use observations from eddy-covariance systems operated at three heights (2.5, 50, and 90 m) within the atmospheric surface layer under unstable conditions. The variability of $$\log ({\widetilde{C_{s}^2}_{\mathrm {}}})$$ depends on instability and on the size of the averaging window over which $$\log ({\widetilde{C_{s}^2}_{\mathrm {}}})$$ is calculated. If instability increases, differences in $$\log ({\widetilde{C_{s}^2}_{\mathrm {}}})$$ between upward motions (large $$C_{s}^2$$ ) and downward motions (small $$C_{s}^2$$ ) increase. The differences are, however, not sufficiently large to result in a bimodal probability density function. If the averaging window size increases, the variances of $$\log ({\widetilde{C_{s}^2}_{\mathrm {}}})$$ decrease. A linear regression of the variances of $$\log ({\widetilde{C_{s}^2}_{\mathrm {}}})$$ versus the averaging window size for various stability classes shows an increase of both the offset and slope (in absolute sense) with increasing instability. For temperature, data from the three heights show comparable results. For humidity, in contrast, the offset and slope are larger at 50 and 90 m than at 2.5 m. In the end we discuss how these findings could be used to assess whether observed differences in $$C_{s}^2$$ along a scintillometer path or aircraft flight leg are just within the range of local variability in $$C_{s}^2$$ or could be attributed to surface heterogeneity. This is important for the interpretation of data measured above a heterogeneous surface. [ABSTRACT FROM AUTHOR]

A novel embedded sensor network records changes in key climatic-environmental variables over a range of altitude in the BaekduDaegan Mountain (BDM) of Gangwon Province in Korea, a protected mountain region with unique biodiversity undergoing climate change research. The investigated area is subdivided into three horizontal north-south study areas. Three variables, temperature (T, °C), relative humidity (RH, %), and light intensity (LI, lumens m, or lux, lx), have been continuously measured at hourly intervals from June, 2010 to September, 2011 using HOBO H8 devices at 10 fixed study sites. These hourly observations are aggregated to monthly, seasonal and annual mean values, and results are summarized to inaugurate a long-term climate change investigation. A region wide T difference in accordance with altitude, or lapse rate, over the interval is calculated as 0.4°C 100 m. T lapse rates change seasonally, with winter lapse rates being greater than those of summer. RH is elevated in summer compared to other seasons. LI within forestland is lower during summer and higher during other seasons. The obtained results could closely relate to the vegetation type and structure and the terrain state since data loggers were located in forestland. [ABSTRACT FROM AUTHOR]

Long-term trend and abrupt changes of major climate variables in the Taihu Basin were investigated based on the mean, maximum and minimum air temperature, diurnal temperature range (DTR), precipitation, relative humidity and sunshine duration at six meteorological stations from 1954 to 2006. Results showed that the long-term trend for annual precipitation was not statistically significant during the past 53 years, but a wetter tendency was detected and the increasing centre for annual precipitation was located in the southeast of the study area. Mean air temperature has increased by 1.43°C, similar trends were also identified for maximum and minimum air temperature, which have increased by 1.06 and 1.54°C, respectively, while DTR exhibited a slight decreasing trend with a rate of about −0.09°C/(10 year). The annual mean relative humidity and sunshine duration exhibited a decreasing trend, with Kendall slope values of −0.99%/10 year and −7.797 h/10 year, respectively. Examination of long-range dependence showed that all climate variables exhibited strong persistence at annual scale except minimum air temperature. Detection of abrupt changes using nonparametric Mann-Kendall and Pettitt methods showed different results. Abrupt changes occurred in the 1980s and 2000s for annual precipitation using the nonparametric Mann-Kendall method, while no abrupt changes were detected using the Pettitt method. Abrupt changes of temperature and relative humidity took place in the early 1990s using the nonparametric Mann-Kendall method, which occurred in the late and mid 1980s using the Pettitt method, while abrupt changes of sunshine duration and DTR detected by two methods occurred in the similar period. The result will be helpful for local flood control and drought relief in urban planning and construction under future global climate change. [ABSTRACT FROM AUTHOR]

Monthly scenarios of relative humidity ( R) were obtained for the Malaprabha river basin in India using a statistical downscaling technique. Large-scale atmospheric variables (air temperature and specific humidity at 925 mb, surface air temperature and latent heat flux) were chosen as predictors. The predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis dataset for the period 1978-2000, and (2) simulations of the third generation Canadian Coupled Global Climate Model for the period 1978-2100. The objective of this study was to investigate the uncertainties in regional scenarios developed for R due to the choice of emission scenarios (A1B, A2, B1 and COMMIT) and the predictors selected. Multi-linear regression with stepwise screening is the downscaling technique used in this study. To study the uncertainty in the regional scenarios of R, due to the selected predictors, eight sets of predictors were chosen and a downscaling model was developed for each set. Performance of the downscaling models in the baseline period (1978-2000) was studied using three measures (1) Nash-Sutcliffe error estimate ( E), (2) mean absolute error (MAE), and (3) product moment correlation ( P). Results show that the performances vary between 0.59 and 0.68, 0.42 and 0.50 and 0.77 and 0.82 for E, MAE and P. Cumulative distribution functions were prepared from the regional scenarios of R developed for combinations of predictors and emission scenarios. Results show a variation of 1 to 6% R in the scenarios developed for combination of predictor sets for baseline period. For a future period (2001-2100), a variation of 6 to 15% R was observed for the combination of emission scenarios and predictors. The variation was highest for A2 scenario and least for COMMIT and B1 scenario. [ABSTRACT FROM AUTHOR]