Search

An increase in energy demand and consumption is one of the significant challenges of the world community. Global climate change and temperature rise can significantly affect energy demand, especially in the building sector. Green passive design strategies (GPDS) such as green roof and green wall are considered a passive energy-saving technology which can deal with further climate change in near future. This paper compares the energy demand and CO2 emissions of a building with different structural scenarios during the current (2000–2019) and future climatic conditions (the 2050s) in two hot-dry (Kerman) and hot-humid (BandarAbbas) climate samples in Iran. The base case, green roof, and green wall modeling of the selected building have been developed by DesignBuilder software. Results revealed that 61% of the annual energy consumption of Kerman is related to the heating sector, while it will be changed to 47% under the effect of climate change and based on RCP2.6. However, 99% of the annual energy consumption of BandarAbbas belongs to cooling demand and it will not change by 2050s. Also, the maximum heating and cooling energy demand were calculated for the base building. Based on the results, green wall has more efficiency in optimizing total energy consumption compared to green roof in both climate types. On the other hand, GPDS are more efficient to optimize heating energy demand in comparison with cooling energy demand. Furthermore, the green wall strategy has better performance in reducing CO2 emissions as well. Accordingly, CO2 emissions reduce in Kerman by 2.73% and 2.93% by the implementation of the green wall during the observation period and 2050s, respectively. Meanwhile, this strategy can reduce CO2 emissions by only 1% per year in BandarAbbas during all studied periods. [ABSTRACT FROM AUTHOR]

Meteorological and oceanographic data from ships of opportunity are the largest contributor to the world’s ocean surface database and thus are extensively used to estimate the change in climatic properties over the world’s oceans during the previous 150 years. The importance of these data for climate change studies underscores the need to fully understand the error associated with averages of these data. The sampling error problem is especially acute for ship data due to the fact that ships are moving platforms and, thus, report observations from constantly varying locations with time. This paper develops a theoretical framework for assessing the averaged sampling error associated with monthly, 1°×1° latitude-longitude box averaged ship data. It should be noted that the time-space distribution of ships within the averaging domain strongly affects the sampling error. This is shown in our derivation. The framework developed here can be used to improve upon existing methods for estimating the sampling error associated with three-dimensional box averages of meteorological and oceanographic data obtained from ship records. The framework is complimentary to existing methods of assessing biases and random error due to instrumentation, recording, etc. It is demonstrated mathematically that the uncertainty due to incomplete sampling is primarily a trade off between of the number of observations and their relative locations within the box as well as the inherent time-space correlation structure of the variable of interest. This work differs from other studies in that the three-dimensional interdependence of data is taken into account in deriving an expression for the sampling error. [ABSTRACT FROM AUTHOR]

The analysis of large data sets in meteorological and air quality studies is often made though the examination of specific case studies, especially when time-consuming computational models are employed. This paper presents the development of a tool to identify specific case studies, termed as representative days, that would subsequently be modelled. The success of such tools should be judged on the discrimination between the specified cases: and the degree to which they capture and recreate historical characteristics of the original data set. The developed approach utilises a principal component algorithm with varimax rotation (r-PCA) and the subtractive clustering algorithm coupled with a cluster validity criterion. In this paper, the developed tool is applied to a data set from the North Sea, utilizing two years worth of data from the DNMI operational forecasting model. The results will be subsequently used in photochemical and radiative forcing modelling tools as part of the EC funded project AEOLOS, with the ultimate goal to estimate the global warming potential of non-radioactive tracing substances such as SF6 and PFCs, which are heavily used in the oil industry. [ABSTRACT FROM AUTHOR]

The Northeast China is one of typical regions experiencing intensive human activities within short time worldwide. Particularly, as the significant changes of agriculture land and forest, typical characteristics of pattern and process of agroforestry ecotone change formed in recent decades. The intensive land use change of agroforestry ecotone has made significant change for regional land cover, which had significant impact on the regional climate system elements and the interactions among them. This paper took agroforestry ecotone of Nenjiang River Basin in China as study region and simulated temperature change based on land cover change from 1950s to 1978 and from 1978 to 2010. The analysis of temperature difference sensitivity to land cover change based on Weather Research and Forecasting (WRF) model showed that the land cover change from 1950s to 1978 induced warming effect over all the study area, including the change of grassland to agriculture land, grassland to deciduous broad-leaved forest, and deciduous broad-leaved forest to shrub land. The land cover change from 1978 to 2010 induced cooling effect over all the study area, including the change of deciduous broad-leaved forest to agriculture land, grassland to agriculture land, shrub land to agriculture land, and deciduous broad-leaved forest to grassland. In addition, the warming and cooling effect of land cover change was more significant in the region scale than specific land cover change area. [ABSTRACT FROM AUTHOR]

During the Indian monsoon season, organized convection in the form of inter-tropical convergence zone (ITCZ) originates from the equatorial trough (ET) region over the equatorial Indian Ocean, propagates northward towards the heated Indian landmass at intraseasonal timescales (30-60 days). In this paper, the long-term changes in rainfall over the ET region during the northern summer season has been investigated for a 34-year (1979-2012) period using gauge-adjusted multisatellite Global Precipitation Climatology Project (GPCP) rainfall data set. Rainfall over this region shows a pronounced seasonality and the eastern ET (EET) receives higher rainfall than the western ET (WET) during the northern summer season. Moreover, the northern summer rainfall over the WET and EET are not significantly correlated with each other. Linear trend analysis of domain-mean seasonal rainfall shows a statistically significant increasing trend of 0.4 mm day decade during the northern summer over the WET, whereas no significant trend is observed over the EET. The long-term changes in the associated variables linked through the moisture budget equation are also examined over both regions of ET for the study period. Even though evaporation over both WET and EET shows statistically significant increasing trend associated with an increase in sea surface temperature and near-surface wind, the vertically integrated moisture convergence shows no significant change over the WET whereas it shows a decrease over the EET during the study period. These might be the possible reasons behind a significant increase in rainfall over the WET with an insignificant change in rainfall over the EET. [ABSTRACT FROM AUTHOR]

Recent air temperature changes in the high Arctic (HA) have been investigated based on mean seasonal and annual data calculated for the period 1951–2015 and for two sub-periods 1976–2015 and 1996–2015. Two kinds of air temperature data (observational and reanalysis) have been used in the research. The observational data were compared with data taken from six reanalysis products (20CRv2c, CERA-20C, ERA-Int, MERRA-2, NCEP-CFSRR, JRA-55). The scale of the HA warming for the period 1996–2015 relative to the reference period 1951–1990 reached 1.6 °C for annual mean and was greatest in autumn (1.9 °C) and in winter (1.7 °C), while it was smallest in summer (0.9 °C). Evidently, the greatest warming was observed in the Atlantic and Siberian climatic regions, while in the rest of the HA, the rate of warming was usually weaker than trends calculated for the period 1976–2015. Air temperature tendencies in all study periods 1951–2015, 1976–2015 and 1996–2015 showed a predominance of positive trends that were statistically significant at the level of 0.05. In the two latter periods, the rate of warming was on average 2–3 times faster than for the entire study period. In the HA, there has not been a slowdown in the rate of warming ("hiatus") in the last two decades (in contrast to that which was noted for the Northern Hemisphere). Our results reveal that, in most cases, the closest fit to observations was obtained for two reanalysis products (the ERA-Interim and JRA-55, since 1979) and the six reanalysis average. Two new polar amplification (PA) metrics based on scaled and standardised values of surface air temperature (SAT) reveal the non-existence of this phenomenon in the period 1951–2015. One of the metrics shows very small PA in the periods 1976–2015 and 1996–2015. [ABSTRACT FROM AUTHOR]

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31–162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann–Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878–1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970–2000 and 1989–2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the role that horizontal resolution plays in the simulation of East Asia precipitation. Two sets of numerical experiments are performed using the Regional Climate Model (RegCM2) nested in one-way mode within the CSIRO global coupled atmosphere-ocean model. In the first set we use the actual RegCM2 topography at the selected model resolutions, which are 45, 60, 90, 120, 180, 240 and 360 km. In the second set of the experiments, the same coarse CSIRO model topography is used in all simulations using the different resolutions of the first set. The results demonstrate that the simulation of East Asian precipitation improves as the horizontal resolution is increased. Moreover, it is shown that the simulations using a higher resolution along with the coarse CSIRO topography perform better than the simulations using a coarser model resolution with corresponding model topography. This suggests that over East Asia adequate spatial resolution to resolve the physical and dynamical processes is more important than topography. Lastly, the results indicate that model resolutions of 60 km or higher are needed to accurately simulate the distribution of precipitation over China and East Asia. [ABSTRACT FROM AUTHOR]

This paper deals with variability in the air temperature field of an urban area during thermal advection, associated with frontal zones, and its interaction with an urban heat island (UHI). Thermal changes experienced in Wrocław, Poland form the basis of this case study analysis. The discussion also contributes to questions concerning the definition of the UHI and ways to select UHI episodes from existing data sets. It is shown that changes in temperature generated during periods of advection are of short duration, only a few hours at most, but thermal contrasts between various parts of a city at such times are sometimes large, reaching an intensity of 5–6 K, even as large as 9 K. Thus, their intensity is comparable with that of the UHI occurring on cloudless and windless nights. The thermal influence of advection is often greater than that due to urban factors; it is only on occasions with less dynamic advection, that a concentric temperature field is formed due to the modified physical properties of the city. In the majority of cases, the thermal field is non-concentric and this is linked with the location of a frontal zone at any given time. The thermal effects of advection recorded in a data set might easily be viewed as episodes of UHI existence, especially if analysis is conducted based on the data derived from just two stations – one urban the other rural. On occasions when such ‘quasi-UHI’ occur the role of the location of the rural, reference station is also evaluated. Precise definition of the urban heat island can be of significance when conducting comparative studies of the UHI in cities located in different geographical zones and when making an urban climate synthesis. [ABSTRACT FROM AUTHOR]

Summary ¶The paper deals with the computation of solar energy available in a specific location. First, a new formula describing the relation between global solar irradiation and the duration of bright sunshine is established. The analysis of its use shows that global solar clear sky irradiance models are essential tools for daily computation of global irradiation. An integrated spectral atmospheric transmittance model is presented, it can be used to compute beam and diffuse clear sky irradiance for all applications where broadband solar energy input is needed. Since it is desirable to use simplified estimation methods for many applications, a parametric global solar irradiance model, derived from the spectral model, is also presented. This model needs only surface meteorological data as input. The influence of the averaging method used for the input parameters on the model accuracy is evaluated. Comparison of model results with the measurements shows an acceptable level of accuracy with the new model. Finally, an application of daily global solar energy computation is presented. [ABSTRACT FROM AUTHOR]

Summary ¶Trends and low frequency fluctuations relying on 14 observed temperature and precipitation series 1901?1998 from Hungarian sites are presented. The statistical significances of systematic changes are calculated by the t-test for the linear trends and the Mann-Kendall test. Characteristics of long-term fluctuations are investigated by spectrum analysis (Fisher-test), fitting optimum-ranked polynomials as well as illustrated by smoothed curves of 15-point Gauss-filter application. While the increase of mean temperature in Hungary during the 20 th century is not significant, the annual precipitation totals have substantially decreased. In the first half of the century mainly the precipitation totals in the transitional seasons decreased. By the second half of the century the seasonal structure of the precipitation trends has altered significantly: there was practically no systematic change in the transitional seasons, but winter precipitation decreased dramatically. The paper makes some comparisons with the same type climatic characteristics of the surrounding geographical regions, the temperature changes of the Northern Hemisphere, as well as discusses the relationship between winter precipitation in Hungary and the North Atlantic oscillation. A significant 50-year oscillation was found in the summer mean temperatures and the annual sums of extreme positive daily temperature anomalies in Hungary. This oscillation seems to be in tune with other processes over the Euro-Atlantic region. A cycle of 3.6 years in the annual precipitation totals was found to be significant at the 0.10 level. [ABSTRACT FROM AUTHOR]

The agricultural sector in Poland is of considerable social and economic importance for the nation. Climate variability and change are of primary relevance to this largely climate-dependent sector. Changes in seven temperature-related agroclimatic indices (lengths of the growing season and of the frost-free season, days of occurrence of the last spring frost and of the first autumn frost; and annual sums of growing degree-days for three values of temperature threshold) in Poland in 1951-2010 are examined. As expected, they generally correspond to the overwhelming and ubiquitous warming. Many, but not all, detected trends are statistically significant. However, for some indices, strong natural variability overshadows eventual trends. Projections of temperature-related agroclimatic indices for the future, based on regional climate models, are also discussed. [ABSTRACT FROM AUTHOR]

Spatial and temporal changes of prolonged dry episodes, defined by the 90th percentile of consecutive no-rain days (<1 mm/day) in both the wet (May to September) and dry seasons (October to April), were investigated using daily precipitation data of 72 meteorological stations over Northeast China from 1961 to 2012. Increasing trends are detected for the prolonged dry episode duration at 94.4 % of the stations in the wet season, and 26.5 % of these increasing trends are statistically significant at the 5 % level. In the dry season, 77.8 % of the stations show decreasing trends, and 32.1 % of these decreasing trends are significant at the 5 % level. The drought trend in the wet season detected by the prolonged dry episode duration is more prominent than that detected by the total number of no-rain days or the Standard Precipitation Index. The ratio between the prolonged dry episode duration and total number of no-rain days exhibits a significant (at the 5 % level) increase of 8.3 %/52 years in the wet season and a significant decrease (at the 5 % level) of nearly 11 %/52 years. An overall dry (before 1980), wet (during the 1980s), and dry (after 1990) tendency in the wet season is detected at the regional average level. Inter-annual variations of the prolonged dry episode duration at individual stations show four patterns. The most predominant pattern is similar to the regional average condition but with larger amplitude and mainly occurring over the northern part of Northeast China. Our study provides a more in-depth case to monitor droughts caused by extremely long dry spells and supports studies over other regions. [ABSTRACT FROM AUTHOR]

Summary A paper recently published in “Nature” finds that there is sufficient evidence to identify the effects of human activity on global temperature. The study is based on northern and southern hemispheres’ time series temperature from 1865 to 1994 and the econometric technique applied is Granger causality analysis. In this note, we make some critical remarks on the conclusions of this study which seem to be rather inconsistent from a methodological point of view. It is shown that a more accurate application of Granger causality analysis to this problem may not allow the same strong and unambiguous conclusions. [ABSTRACT FROM AUTHOR]

In this note we observe that a problem of linear approach to Granger causality testing between CO and global temperature is that such tests can have low power. The probability to reject the null hypothesis of non-causality when it is false is low. Regarding non-linear Granger causality, based on multi-layer feed-forward neural network, the analysis provides evidence of significant unidirectional Granger causality from CO to global temperature. [ABSTRACT FROM AUTHOR]

Previous studies indicate that the temperature changes from a day to the following day are not normally distributed either in winter or in summer. However, this study is the first to investigate the causes of the asymmetry in these temperature changes. We hypothesised that the asymmetries are driven by the passages of atmospheric fronts and by the radiative processes during anticyclonic circulation conditions. We used the maximum and minimum temperatures observed at the Praha-Karlov station, the records of front passages, and 7 different catalogues of circulation types over central Europe. We demonstrated that the asymmetries in the large temperature changes (5 °C and larger) were related to the passages of all three front types in winter and to the passages of cold fronts in summer. The asymmetries in the slight temperature changes (up to 3 °C) were mainly caused by cold advection from the north and the northeast in winter and by warm advection from the south, the southeast, and the east in summer. We suppose that our results can be generalized; that is, the passages of atmospheric fronts and cold/warm advection are the likely causes of the asymmetries of the day-to-day temperature changes elsewhere in Europe. The presented findings can be applied as a tool for the validation of climate model outputs. [ABSTRACT FROM AUTHOR]

Three large ocean currents are represented by proxy time series: the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI), and the Pacific Decadal Oscillation (PDO). We here show how proxies for the currents interact with each other and with the global temperature anomaly (GTA). Our results are obtained by a novel method, which identifies running average leading–lagging (LL) relations, between paired series. We find common cycle times for a paired series of 6–7 and 25–28 years and identify years when the LL relations switch. Switching occurs with 18.4 ± 14.3-year intervals for the short 6–7-year cycles and with 27 ± 15-year intervals for the 25–28-year cycles. During the period 1940–1950, the LL relations for the long cycles were circular (nomenclature x leads y: x → y): GTA → NAO → SOI → PDO → GTA. However, after 1960, the LL relations become more complex and there are indications that GTA leads to both NAO and PDO. The switching years are related to ocean current tie points and reversals reported in the literature. [ABSTRACT FROM AUTHOR]

Using multiple datasets, including three grid datasets (ERA-Interim, WFDEI, and SURF) and one station dataset, we analyzed the climatological distributions and trends of daily maximum air temperature (DMAT) and number of heat days (NHD) over China from 1979 to 2012. In general, all the three grid datasets show the highest climatological DMAT and NHD values in Xinjiang and southeast China, and increasing trends of DMAT and NHD in most of China. Nevertheless, both the climatological condition and trend exhibit differences in detail among the three grid datasets. Using the observed grid dataset (SURF) as a reference, the results show that the WFDEI dataset is closer to SURF than ERA-Interim in characterizing climatological features of DMAT and NHD, and the values from ERA-Interim dataset are lower than the SURF in most part of China. Since the trends of NHD in WFDEI are smaller than those in the other two grid datasets, especially in the middle and lower beaches of the Yangtze River, ERA-Interim is better than WFDEI in representing the trends of NHD. In four regions: Chuanyu, Huanghuai, Xinjiang, and Southeast where the NHD occurs frequently and increases rapidly, the WFDEI is more reliable than ERA-Interim due to the fact that the changes of regional NHD in WFDEI are more consistent with those in observed datasets. Because there exist biases in the records of DMAT between the ERA-interim and WFDEI, it is better to adopt percentile index than absolute threshold to study the changes of China extreme air temperature when using reanalysis datasets. [ABSTRACT FROM AUTHOR]

Observationally constrained values of the global radiative response coefficient are pivotal to assess the reliability of modeled climate feedbacks. A widely used approach is to measure transient global radiative imbalance related to surface temperature changes. However, in this approach, a potential error in the estimate of radiative response coefficients may arise from surface inhomogeneity in the climate system. We examined this issue theoretically using a simple two-zone energy balance model. Here, we dealt with the potential error by subtracting the prescribed radiative response coefficient from those calculated within the two-zone framework. Each zone was characterized by the different magnitude of the radiative response coefficient and the surface heat capacity, and the dynamical heat transport in the atmosphere between the zones was parameterized as a linear function of the temperature difference between the zones. Then, the model system was forced by randomly generated monthly varying forcing mimicking time-varying forcing like an observation. The repeated simulations showed that inhomogeneous surface heat capacity causes considerable miscalculation (down to -1.4Wm-2 K-1 equivalent to 31.3% of the prescribed value) in the global radiative response coefficient. Also, the dynamical heat transport reduced this miscalculation driven by inhomogeneity of surface heat capacity. Therefore, the estimation of radiative response coefficients using the surface temperature-radiation relation is appropriate for homogeneous surface areas least affected by the exterior. [ABSTRACT FROM AUTHOR]

Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (T) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50), and the greatest warming for daily minimum air temperature (T) occurred with very strong trends exceeding 4 °C/50. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in T. More than half part of the frequency distribution show negative trends less than −0.5 °C/50 in 1961-1985, while showing trends less than 2.5 °C/50 in 1986-2010. [ABSTRACT FROM AUTHOR]

Increasing global temperatures during the last century have had their own effects on other climatic conditions, particularly on precipitation characteristics. This study was meant to investigate the spatial and temporal monthly trends of precipitation using the least square error (LSE) approach for the northwest of Iran (NWI). To this end, a database was obtained from 250 measuring stations uniformly scattered all over NWI from 1961 to 2010. The spatial average of annual precipitation in NWI during the period of study was approximately 220.9-726.7 mm. The annual precipitation decreased from southwest to northeast, while the large amount of precipitation was concentrated in the south-west and in the mountainous areas. All over NWI, the maximum and minimum precipitation records occurred from March to May and July to September, respectively. The coefficient of variation (CV) is greater than 44 % in all of NWI and may reach over 76 % in many places. The greatest range of CV, for instance, occurred during July. The spatial variability of precipitation was consistent with a tempo-spatial pattern of precipitation trends. There was a considerable difference between the amounts of change during the months, and the negative trends were mainly attributed to areas concentrated in eastern and southern parts of NWI far from the western mountain ranges. Moreover, limited areas with positive precipitation trends can be found in very small and isolated regions. This is observable particularly in the eastern half of NWI, which is mostly located far from Westerlies. On the other hand, seasonal precipitation trends indicated a slight decrease during winter and spring and a slight increase during summer and autumn. Consequently, there were major changes in average precipitation that occurred negatively in the area under study during the observation period. This finding is in agreement with those findings by recent studies which revealed a decreasing trend of around 2 mm/year over NWI during 1966-2005. [ABSTRACT FROM AUTHOR]

The persistent temperature and precipitation extremes may bring damage to the economy and human due to their intensity, duration and areal coverage. Understanding the quality of reanalysis datasets in descripting these extreme events is important for detection, attribution and model evaluation. In this study, the performances of two reanalysis datasets [the twentieth century reanalysis (20CR) and Interim ECMWF reanalysis (ERA-Interim)] in reproducing the persistent temperature and precipitation extremes in China are evaluated. For the persistent temperature extremes, the two datasets can better capture the intensity indices than the frequency indices. The increasing/decreasing trend of persistent warm/cold extremes has been reasonably detected by the two datasets, particularly in the northern part of China. The ERA-Interim better reproduces the climatology and tendency of persistent warm extremes, while the 20CR has better skill to depict the persistent cold extremes. For the persistent precipitation extremes, the two datasets have the ability to reproduce the maximum consecutive 5-day precipitation. The two datasets largely underestimate the maximum consecutive dry days over the northern part of China, while overestimate the maximum consecutive wet days over the southern part of China. For the response of the precipitation extremes against the temperature variations, the ERA-Interim has good ability to depict the relationship among persistent precipitation extremes, local persistent temperature extremes, and global temperature variations over specific regions. [ABSTRACT FROM AUTHOR]

Among several variables affecting climate change and climate variability, temperature plays a crucial role in the process because its variations in monthly and extreme values can impact on the global hydrologic cycle and energy balance through thermal forcing. In this study, an analysis of temperature data has been performed over 22 series observed in New Zealand. In particular, to detect possible trends in the time series, the Mann-Kendall non-parametric test was first applied at monthly scale and then to several indices of extreme daily temperatures computed since 1951. The results showed a positive trend in both the maximum and the minimum temperatures, in particular, in the autumn-winter period. This increase has been evaluated faster in maximum temperature than in minimum one. The trend analysis of the temperature indices suggests that there has been an increase in the frequency and intensity of hot extremes, while most of the cold extremes showed a downward tendency. [ABSTRACT FROM AUTHOR]

The multiple downscaled scenario products allow us to assess the uncertainty of the variations of precipitation and temperature in the current and future periods. Probabilistic assessments of both climatic variables help better understand the interdependence of the two and thus, in turn, help in assessing the future with confidence. In the present study, we use ensemble of statistically downscaled precipitation and temperature from various models. The dataset used is multi-model ensemble of 10 global climate models (GCMs) downscaled product from CMIP5 daily dataset using the Bias Correction and Spatial Downscaling (BCSD) technique, generated at Portland State University. The multi-model ensemble of both precipitation and temperature is evaluated for dry and wet periods for 10 sub-basins across Columbia River Basin (CRB). Thereafter, copula is applied to establish the joint distribution of two variables on multi-model ensemble data. The joint distribution is then used to estimate the change in trends of said variables in future, along with estimation of the probabilities of the given change. The joint distribution trends vary, but certainly positive, for dry and wet periods in sub-basins of CRB. Dry season, generally, is indicating a higher positive change in precipitation than temperature (as compared to historical) across sub-basins with wet season inferring otherwise. Probabilities of changes in future, as estimated from the joint distribution, indicate varied degrees and forms during dry season whereas the wet season is rather constant across all the sub-basins. [ABSTRACT FROM AUTHOR]

We apply a novel method based upon 'before' and 'after' relationships to investigate and quantify interconnections between global temperature anomaly (GTA), as response variable, and greenhouse gases (CO) and total solar irradiance (TSI) as candidate causal variables for the period 1880 to 2010. The most likely interpretations of our results for the 6 to 8 years cyclic components of the variables are that during the period 1929 to 1936, CO significantly leads GTA. However, during the period 1960-2003, GTA apparently leads CO, that is, the peaks (and troughs) in GTA are in front of, and close to, the peaks (and troughs) in CO For time windows outside these periods, we did not find significant before or after-relations. An alternative interpretation is that there is a shift between short (≈1.5 year) and long (≈5 years) durations between cause and effect. Relationships between GTA and TSI suggest that 'inertia' of the global sea, land, and atmosphere system leads to delays longer than half their common cycle length of about 10 years. Based on the interaction patterns between the variables GTA, CO, and TSI, we suggest the possibility that a new regime for how the variables interact started around 1960. From trend forms, and not considering physical mechanisms, we found that the trend in CO contributes ≈ 90 %, and the trend in TSI ≈ 10 %, to the trend in GTA during the last 130 years. [ABSTRACT FROM AUTHOR]

Using three models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we compare the direct and other effects of anthropogenic aerosols on observed and simulated annual, winter, and summer temperature changes. Three regions, namely, arid-semiarid area, humid-semiarid area, and the whole of China, are studied. The temperature changes caused by other effects of anthropogenic aerosol (OE) are calculated from the difference between the anthropogenic aerosol forcing run (AA) and the anthropogenic aerosol direct effect forcing run (DE). When the combined effects are considered, a significant area-averaged cooling rate varies in the range of −0.86 to −0.76 °C per century throughout China. Meanwhile, the isolated direct and other effects lower the temperature nationwide by −0.66 to −0.55 °C per century, and −0.31 to −0.11 °C per century, respectively. From a nonlinear perspective, the aerosol-induced temperature experiences a cooling trend, with AA having the largest cooling trend changes both annually and in the summer, while DE has the greatest reduction in the winter. Additionally, the influence of OE cannot be detected in observed annual changes over the arid-semiarid area and the whole of China, while the others are clearly detectable in all cases. AA (DE, OE) reduces the observational temperature mainly over the humid-semihumid region, where the contribution to the observed warming ranges from −515.2 % (−298.7 %, −198.9 %) to −173.6 % (−130.3 %, −66.4 %). [ABSTRACT FROM AUTHOR]

The present study provides an evaluation of the regional differences over China in surface energy budget components as simulated by a selection of models from phase five of the Coupled Model Intercomparison Project (CMIP5), covering the period 1960-2005. Similarities and differences exist among the models in terms of both spatial and magnitude patterns. For climatology, the CMIP5 models show quite different spatial distributions of shortwave radiation and sensible heat flux. In terms of seasonal variation, the surface energy budgets are remarkably different between western and eastern China. The discrepancies in the seasonal variation of sensible heat flux are mainly attributable to temperature differences and wind speed, while those of shortwave radiation are caused by the seasonal variation in total cloud cover. Cloudiness is one of the most crucial parameters in estimating the surface energy budget. In addition, the study also reveals that the magnitudes of the various components show larger (more than two-fold) differences between western and eastern parts of China, especially in net longwave and upward shortwave radiation, as well as latent and sensible heat fluxes. The results for surface soil heat flux show that there is more incoming energy during spring and summer and more outgoing energy during fall and winter in both western and eastern China. Furthermore, compared to NCEP2 data, the ERA-40 reanalysis product produces results more similar to the multi-model ensemble mean for most components. [ABSTRACT FROM AUTHOR]

On the basis of the daily minimum ( T), mean ( T), and maximum ( T) temperature records of 25 meteorological stations in Northeast China (NEC) and 10 weather stations in Hokkaido, Japan (HKD), from 1951 to 2011, we comparatively analyzed the change in extreme temperature events and the relationship of these events with the mean value. Results showed that for the extreme lowest temperature (ELT) frequency, approximately 96 % of the stations exhibited decreasing trends ranging from −0.63 to 0 days/decade in NEC, whereas all the stations in HKD showed decreasing trends ranging from −0.4 to 0 days/decade. However, the average decrease in amplitude of 0.24 days/decade in HKD was significantly less than the 0.27 days/decade average in NEC. The extreme highest temperature (EHT) frequency trends in the two regions showed insignificant increases. Notable decreasing trends for the ELT intensity were found at −0.9 to 0 %/decade in 92 % of the stations in NEC and −1.1 to 0 %/decade in 90 % of the stations in HKD. Inversely, increasing trends in EHT intensity were observed in 80 % of the stations over HKD, ranging from 0.06 to 0.32 %/decade, and the majority of the stations (64 %) showed increasing trends in NEC. T and T had strong negative correlations with the ELT intensity in NEC, whereas T and T had strong significant negative correlations with the ELT frequency in HKD. T, T, and T between NEC and HKD exhibited strong significant positive correlations. The frequency and intensity of the ELT in both regions showed significant positive correlations. [ABSTRACT FROM AUTHOR]

Potential changes in Köppen-Geiger climate zones over southern Africa (Africa south of 22 °S) under future climate change are investigated using an ensemble of high-resolution projections of a regional climate model. The projections are performed under the A2 scenario of the Special Report on Emission Scenarios (SRES), and changes are presented for those times in the future when the increase in global average surface temperature reaches thresholds of 1, 2, and 3 °C, relative to the present-day baseline climatology. Widespread shifts in climate regimes are projected, of which the southern and eastern expansion of the hot desert and hot steppe zones is the most prominent. From occupying 33.1 and 19.4 % of southern Africa under present-day climate, these regions are projected to occupy between 47.3 and 59.7 % (hot desert zone) and 24.9 and 29.9 % (hot steppe zone) of the region in a future world where the global temperature has increased by 3 °C. The cold desert and cold steppe zones are projected to decrease correspondingly. The temperate regions of eastern South Africa, the Cape south coast, and winter rainfall region of the southwestern Cape are also projected to contract. An expansion of the hot steppe zone into the cold steppe and temperate zones may favor the intrusion of trees (and therefore the savanna biome) into the most pristine grasslands of southern Africa. However, the correlative climate-vegetation approach of using projected changes in Köppen-Geiger zones to infer future vegetation patterns is of limited value in the savanna complex of southern Africa, where complex feedbacks occur between carbon dioxide (CO) concentrations, trees, C grasses, fire, and climate. The present-day temperate Cape Fynbos regime may come under increasing pressure as the encompassing temperate zone is invaded mainly from the east by the hot steppe climate regime under climate change, with the incidence of Fynbos fires also becoming more likely in a generally warmer and drier climate. [ABSTRACT FROM AUTHOR]

Monthly seasonally adjusted surface temperature patterns in Southeast Asia from 1909 to 2008 were studied. The area comprised 40 regions of 10° × 10° grid boxes in latitudes 25°S to 25°N and longitudes 75°E to 160°E. Temperatures were studied for three overlapping 36-year periods, the first period 1909-1944, the second period 1941-1976 and the third period 1973-2008. The data of each 36-year period were fitted to reduce autocorrelations at lags 1 and 2 months. Factor analysis was used to account for spatial correlation between grid boxes giving six contiguous layer regions. Simple linear regression models were fitted to data within these larger regions. Temperatures were found to have increased in five from six regions over the first period with the increases ranging from 0.005 to 0.148 °C per decade, in only three regions over the second period with the increases ranging from 0.008 to 0.150 °C per decade and in six regions over the third period with the increases ranging from 0.082 to 0.222 °C per decade. [ABSTRACT FROM AUTHOR]

Temperatures were examined at 118 stations located in the Arctic and compared to observations at 50 European stations whose records averaged 200 years and in a few cases extend to the early 1700s. Nearly all stations exhibited warming trends. For each station, the temperature relative to the average value during 1961-1990 was found. The resulting temperature change averaged over the Arctic stations was plotted. For the period 1820-2014, trends were found for the January, July and annual temperatures of 1.0, 0.0 and 0.7 °C per century, respectively. Decadal variations are evident and much of the temperature increase occurred during the 1990s. Over the past century, Siberia, Alaska and Western Canada have experienced somewhat greater warming than Eastern Canada, Greenland and Northern Europe. The temperature change experienced by the Arctic stations during the last two centuries closely tracks that found for the European stations. [ABSTRACT FROM AUTHOR]

Based on daily air temperature data from 745 stations in China, the present study investigates the regional characteristics of temperature trend and the dependence of temperature changes on the altitude during the period of 1963-2012. There is a consistent warming trend throughout the country except for the southwest China where a cooling trend is identified. Moreover, significant warming trend exists in highland areas such as the Northeast, Inner Mongol, and the Tibet region. Compared with other seasons, the warming trend is most pronounced in highland regions in winter. In summer, the temperature has no obvious increasing trend in north China, while the cooling trend is found in south China. The relationship between altitude and temperature trend is further investigated by dividing China into three subregions according to the altitude-below 200, 200-2,000, and above 2,000 m. Although there is no simple linear relationship between elevation and warming trend on national scale, the temperature trend-altitude relation is different among the three regions. The temperature trend decreases with altitude below 200 m while increases from 200 to 2,000 m, and a weak positive temperature trend-altitude relation is found over 2,000 m. The strongest temperature trend-altitude relations are found in the subtropical regions, especially pronounced south of 36°N in China. The magnitudes of decreases from 200 to 2,000 m are one order lower than the increases below 200 m. Low-altitude stations appear to be influenced more by anthropogenic aerosols. High-altitude stations are mostly located in flat terrain and sparsely populated region. Therefore, temperature trends change with elevations. [ABSTRACT FROM AUTHOR]

We have recently suggested 'long-term memory' or internal long-range correlation within the time-series of land-surface air temperature (LSAT) anomalies in both hemispheres. For example, an increasing trend in the LSAT anomalies is followed by another one at a different time in a power-law fashion. However, our previous research was mainly focused on the overall long-term persistence, while in the present study, the upward and downward scaling dynamics of the LSAT anomalies are analysed, separately. Our results show that no significant fluctuation differences were found between the increments and decrements in LSAT anomalies, over the whole Earth and over each hemisphere, individually. On the contrary, the combination of land-surface air and sea-surface water temperature anomalies seemed to cause a departure from symmetry and the increments in the land and sea surface temperature anomalies appear to be more persistent than the decrements. [ABSTRACT FROM AUTHOR]

The global monthly temperature anomaly time series for the period 1850-2012 has been investigated in terms of multifractal detrended fluctuation analysis (MF-DFA). Various multifractal observables, such as the generalized Hurst exponent, the multifractal exponent, and the singularity spectrum, are extracted and are fitted to a generalized binomial multifractal model consists of only two free parameters. The results of this analysis give a clear indication of the presence of long-term memory in the global temperature anomaly time series which causes multifractal pattern in the data. We investigate the possible other source(s) of multifractality in the series by random shuffling as well as by surrogating the original series and find that the probability density function also contributes to the observed multifractal pattern along with the long-memory effect. Surprisingly, the temperature anomaly time series are well described by the two-parameter multifractal binomial model. [ABSTRACT FROM AUTHOR]

The average January, July and annual temperatures were examined at 27 stations located in the Canadian Arctic. Some of these stations have temperature records extending as far back as 1895. Nearly all stations exhibited warming trends. For each station, the difference between the temperatures relative to the average value found during 1961-1990 was found. The resulting temperature change averaged over the 27 stations was then plotted to give a time series covering the period 1895-2014. Trends were found for the January, July and annual temperatures of 3.1, 1.6 and 1.9 °C per century, respectively. Similar trends were found in the western and eastern Arctic. The warming occurred primarily in the first and last decades of the twentieth century. For the period 1915-1995, the annual temperature trend was only 0.4 °C per century. [ABSTRACT FROM AUTHOR]

Availability of high-resolution satellite rainfall products provides a great opportunity to monitor precipitation frequently over large and remote areas. However, the accuracies of these products need thorough assessment before they can be widely used. The objective of this study is to evaluate the accuracies of Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis 3B42 products (TMPA V6 and TMPA V7) using a network of 75 rain gauges over Southwestern China. The study region has a complex terrain, which makes it challenging for TMPA rainfall products to give reliable estimates. The results show that the TMPA products tend to underestimate the occurrences of rainfall events. Furthermore, TMPA V6 always underestimates the precipitation, while V7 generally overestimates rainfall in wet season and underestimates it in dry season. Under- and overestimation of rainfall by the two products can be mainly attributed to false alarm events. The overall accuracies of the two products depend heavily on the time scale. At the daily scale, these products may not be reliable; however, the overall accuracies are improved substantially when the time scale is extended from daily to monthly and seasonal scales. Reliability of the TMPA precipitation estimates is also dependent on the climate zones and elevation to some extent and shows clear seasonal variations. In the wet months from May to September, the estimates for TMPA 3B42 V6 and V7 tend to be more accurate. In comparison, the accuracy of V7 is improved slightly over V6. However, V7 still has some major limitations in reproducing precipitation in dry seasons and in high-elevation regions with complex terrains, suggesting that further improvements in TMPA precipitation retrieval algorithms are still needed for this type of regions. [ABSTRACT FROM AUTHOR]

Impacts of climate change on crop yield can be divided into long-term and year-to-year impacts. The goal of this study is to evaluate whether the long-term and the year-to-year impacts are different using historical datasets. Data on corn yields for 1961-2005 in Jilin and Anhui, located in northeastern and Mideastern China, respectively, are combined with datasets on temperature to build the statistical regression models for evaluation of the impacts of long-term and year-to-year temperature change on corn yield. Over half of the yield trends result from non-climatic factors, such as management and technology. Corn yields could increase threefold (measured by method 1) or twofold (method 2) as long-term temperature increased per degree centigrade. And agriculture in northeastern China has benefitted from climate warming. But the year-to-year temperature change could only result in 12 % yield increase, almost 20 times less than the impacts of long-term temperature change. We conclude that the impacts of long-term and year-to-year temperature change on crop yield are quite different. So, the models derived from year-to-year variations cannot be applied to assess the impacts of long-term climate change. [ABSTRACT FROM AUTHOR]

We investigate here recent (1980-2009) climate variability in the upper Karakoram, Northern Pakistan, of particular interest given the peculiar glacier behavior during the last two decades. Differently from other glacierized regions in the Hindu Kush-Karakoram-Himalaya region, glaciers in the Karakoram display limited ice thinning, and in some cases advancing has been detected. Climate analysis is required to describe recent (i.e., last three decades) variability, to aid highlighting of the factors driving glacier evolution. Starting from monthly data, we analyze seasonal values of total precipitation, number of wet days, maximum ( max) and minimum ( min) air temperature, max precipitation in 24 h, and cloud cover for 17 weather stations in the upper Karakoram, clustered within three climatic regions as per use of principal components analysis. We detect possible nonstationarity in each of these regions by way of (1) linear regression, (2) moving window average, and (3) Mann-Kendall test, also in progressive form, to detect the onset date of possible trends. We then evaluate linear correlation coefficients between Northern Atlantic Oscillation (NAO) index and climate variables to assess effectiveness of teleconnections, claimed recently to affect climate in this area. Also, we compare temperature within the investigated zone against global temperature anomalies, to evidence enhanced warming within this area. We found mostly nonsignificant changes of total precipitation, unless for few stations displaying increase in Chitral-Hindu Kush region and Northwest Karakoram, or Gilgit area, and decrease in Western Himalaya, Kotli region. Max precipitation is mostly unchanged, unless for slight increase in Chitral and Gilgit areas, and slight decrease in Kotli region. Number of wet days is mostly increasing in Gilgit area, and decreasing in Chitral area, with no clear signal in Kotli region. Min temperatures increase always but during Summer, when decreasing values are detected, especially for Gilgit and Chitral regions. Max temperatures are found to increase everywhere. Cloud cover is significantly increasing in Gilgit area, but decreasing otherwise, especially in Kotli region. Max temperature regime is significantly positively correlated against global thermal anomaly, while min temperature regime is nonsignificantly negatively correlated. Max and min temperatures seem mostly negatively correlated to NAO. Some dependence of trend intensity for the considered variables against altitude is found, different for each region, suggesting that investigation of weather variables at the highest altitudes is warranted to discriminate further climate variability in the area. [ABSTRACT FROM AUTHOR]

The direct effects of sulfate aerosol, dust aerosol, carbonaceous aerosol, and total combined aerosols on the tropopause height are simulated with the Community Atmospheric Model version 3.1 (CAM3.1). A decrease of global mean tropopause height induced by sulfate, carbonaceous aerosol, and total combined aerosols is found, and a tropopause height increase is induced by dust aerosol. Sulfate aerosol decreases the tropospheric temperature and increases the stratospheric temperature. These effects cause a decrease in the height of the tropopause. In contrast, carbonaceous and total combined aerosols increase both the tropospheric and the stratospheric temperatures, and they also cause a decrease in the height of the tropopause. The changes in the tropopause height show highly statistically significant correlations with the changes in the tropospheric and stratospheric temperatures. The changes in the tropospheric and stratospheric temperatures are related to the changes in the radiative heat rate, cloud cover, and latent heat, but none of these factors absolutely dominate the temperature change. [ABSTRACT FROM AUTHOR]

Chennai is the fourth largest metropolitan city in India, and it is one of India's chief industrial and economic growth centers. The temperature change in Chennai is studied in this research by analyzing the mean maximum temperature (MMaxT), mean minimum temperature (MMinT), and mean annual temperature (MAT) from 1951 to 2010. Data are analyzed in three parts by running linear regression and by taking anomalies of all time periods: (a) the whole period from 1951 to 2010; (b) phase 1, 1951-1980; and (c) phase 2, 1981-2010. The trends have been evaluated by Student's t statistics and supported by Mann Kendall rank statistics. The observed change in temperature is positive, which has been clear increasing trends in MMaxT, MMinT, and MAT. MAT has increased 1.3°C since the last 60 years. MMaxT has increased up to 1.6°C, in which the second phase accounts for 75 % of the total change during the last 60 years. MMinT over Chennai has increased 1.0°C. There is a high rise in temperature during winter season. [ABSTRACT FROM AUTHOR]

Based on composite analysis using categories of solar inactivity and activity, the responses of surface temperature to different categorized solar activity and a plausible mechanism have been discussed. The results show the increasing solar sunspot activity during solar cycles 13 to 24 (1880-2010) and it seemed to make a positive contribution to rising global temperature. However, the sunspots were fewer in number, if we focused on the most recent 60 years (1950-2010), and the decreasing solar activity did not contribute to a cooler Earth. This result indicates that the connection between sunspots and the Earth's climate is sensitive to the study period. An extreme analysis was performed in an attempt to gain a better understanding of solar impacts. The extreme top 10 composite analysis demonstrated that the surface temperature response to solar activity is spatially different and is highly sensitive to El Niño-Southern Oscillation (ENSO) events. The most sensitive areas in the Pacific sector revealed a significant difference between including and excluding ENSO years. During the solar inactive years, the tropical eastern Pacific was observed as a weak El Niño-like (strong La Niña-like) pattern in the composite including (excluding) ENSO events. Another interesting feature is the strong similarity in the composites which include or exclude ENSO events during the sunspot active years, but it differs from the La Niña-like pattern observed in previous studies. The bottom-up mechanism associated with the response of the surface dynamical circulation and the heat balance when compared to the total solar irradiance forcing partially explains the connection. [ABSTRACT FROM AUTHOR]

In mountain environments, local factors such as topography or exposure to the sun influence the spatial distribution of temperatures. It is therefore difficult to characterise the global evolution of temperatures over several decades. Such local effects can either accentuate or attenuate thermal contrasts between neighbouring areas. The present study uses two regional thermal indicators-thermal gradients and temperatures reduced to sea level-to monitor the monthly evolution of minimum and maximum temperatures in the French Northern Alps. Measures were calculated for the period extending from 1960 to 2007 based on data from 92 measuring stations. Temperature gradients were computed and further used to monitor the altitudinal evolution of temperatures. A characteristic regional temperature was determined for the whole of the French Northern Alps based on temperatures reduced to sea level, and changes in temperatures since 1960 were assessed. Multiple linear regression models made it possible to extend measurements over a longer period and to make enhanced calculations of temperature changes in the mountains since 1885. This is the first study to examine temperature changes in the French Northern Alps over such an extended period. Gradient data suggest that over the last 50 years, temperatures have changed at all altitudes. In addition, the evaluation of the temperature rise over 100 years reveals that minimal and maximal monthly temperatures trends are only significant a few months of the year. [ABSTRACT FROM AUTHOR]

Temperature variability in Moosonee, Thunder Bay, and Toronto, Ontario, Canada is examined through a day-to-day variability framework. Statistical measures used in this study include standard deviation (SD), day-to-day temperature variability (DTD), DTD/SD ratio ( G), change in day-to-day variability (ΔDTD), and threshold measures of 5°C and 10°C. ΔDTD is the difference between day-to-day change in temperature maximum (DTDtmax) and day-to-day change in temperature minimum (DTDtmin). A distinct seasonal trend is reflected in DTD in Moosonee, Thunder Bay, and Toronto, where ΔDTD is greatest during spring. Monthly ΔDTD averages in Toronto, Thunder Bay, and Moosonee are affected by seasonal variation, the lake effect, and the freeze-up of nearby waterbodies. Yearly averages of ΔDTD have significantly increased over the past recent years in Moosonee and Thunder Bay; a continual increase in climate variability may be detrimental to the subsistence lifestyle of those living in these areas. [ABSTRACT FROM AUTHOR]

This study aims to examine how future climate, temperature and precipitation specifically, are expected to change under the A2, A1B, and B1 emission scenarios over the six states that make up the Southern Climate Impacts Planning Program (SCIPP): Oklahoma, Texas, Arkansas, Louisiana, Tennessee, and Mississippi. SCIPP is a member of the National Oceanic and Atmospheric Administration-funded Regional Integrated Sciences and Assessments network, a program which aims to better connect climate-related scientific research with in-the-field decision-making processes. The results of the study found that the average temperature over the study area is anticipated to increase by 1.7°C to 2.4°C in the twenty-first century based on the different emission scenarios with a rate of change that is more pronounced during the second half of the century. Summer and fall seasons are projected to have more significant temperature increases, while the northwestern portions of the region are projected to experience more significant increases than the Gulf coast region. Precipitation projections, conversely, do not exhibit a discernible upward or downward trend. Late twenty-first century exhibits slightly more precipitation than the early century, based on the A1B and B1 scenario, and fall and winter are projected to become wetter than the late twentieth century as a whole. Climate changes on the city level show that greater warming will happened in inland cities such as Oklahoma City and El Paso, and heavier precipitation in Nashville. These changes have profound implications for local water resources management as well as broader regional decision making. These results represent an initial phase of a broader study that is being undertaken to assist SCIPP regional and local water planning efforts in an effort to more closely link climate modeling to longer-term water resources management and to continue assessing climate change impacts on regional hazards management in the South. [ABSTRACT FROM AUTHOR]

This study analyzes the mean maximum and minimum temperature trends on a monthly, seasonal, and annual timescale by applying various statistical tools to data from 476 Spanish weather stations during the period between 1961 and 2006. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the nonparametric Mann-Kendall test was used to determine the statistical significance of the trends. Temperature significantly increased in over 60% of the country in March, June, spring, and summer in the case of maximum temperatures and in March, May, June, August, spring, and summer for minimum temperatures. At the annual resolution, temperatures significantly increased in over 90% of Spain with a rise of around 0.3°C/decade. The maximum temperature increased at a higher rate than the minimum temperature from midsummer to early winter as well as in winter, spring, and summer and also on an annual basis. [ABSTRACT FROM AUTHOR]

The objective of the present study is to apply a wide range of efficient trend estimation methods for understanding how temperature extremes are locally changing. Temporal patterns of changes in extreme daily maximum or minimum temperature at homogeneous climate stations located in Belgium and their associations with changes in climate means are examined for the period 1952/1953 until present. A considerable amount of work is devoted to the formulation of extreme value models in the presence of non-stationarity. The covariate process is considered to be linear in time or/and in the North Atlantic Oscillation index as well. Additional insights on historical changes in frequency and amplitude of temperature extremes are obtained with the non-parametric quantile-perturbation approach. [ABSTRACT FROM AUTHOR]

High-resolution regional climate change simulations have proven to offer an added value compared to available global climate model simulations. However, over many regions of the globe, long-term high-resolution climate change projections are rather sparse. We present a transient high-resolution climate change projection with the regional climate model with the regional climate model REMO over the southern African region, following the SRES A1B emission scenario. The simulation was conducted at 18 km grid spacing for the period from 1960 to 2100, making it to the longest available climate change projection at such a high resolution for the region. In the first part of the study, we focus on the impact of the model setup on the simulated rainfall over the southern African region. In the standard setup, we used the output of the global climate model ECHAM5/MPIOM directly to force REMO. This setup led to a very strong wet bias over the region. Changing it to the double-nesting setup significantly reduced this bias, but a substantial wet bias still persists. The remaining bias could partly be attributed to a warm bias in the SST forcing over the southern Atlantic Ocean. Thus, we applied an SST correction based on the anomaly approach to the data, which led to a further improvement of the rainfall simulation. As the SST bias in the southern Atlantic is a common feature of all global climate models assessed by the IPCC, we recommend the chosen model setup, including the SST correction, as general procedure for dynamical downscaling studies over the southern African region. In the second part, we present the projected spatial and temporal changes of temperature and precipitation, including several rainfall characteristics, over the southern African region. Herby we compare the projections of the high-resolution REMO simulation to those of the forcing regional and global models. We generally find that for temperature the magnitude of the projected changes of the regional model only slightly differs from the GCM projection; however, the spatial patterns are much better resolved in the RCM projections. For precipitation, REMO shows a more intense drying toward the end of the twenty-first century than it is simulated by the global model. This can have a major influence when investigating the impacts of future climate change on a regional or even local scale. In combination with the improved spatial patterns, the application of high-resolution climate change information could therefore improve the results of such applications. [ABSTRACT FROM AUTHOR]

Many dimensions of the global temperature pattern have been explored intensely over the past few decades. In this investigation, we explore the underlying spatial autoregressiveness of annual tropospheric temperature anomalies measured by polar-orbiting satellites. We found that the percent of the Earth covered by areas of significantly high local autocorrelation ranged from 11.92% to 25.90% over the 1979 to 2008 study period. We gathered 13 different teleconnection indices that have been linked to regional to global temperatures and found two (Polar/Eurasia pattern and North Atlantic Oscillation) that were positively correlated to the percent area with high local spatial autocorrelation. The magnitude but not the sign of the El Niño Southern Oscillation is also an important factor in the variation of spatial autocorrelation. The physical mechanism driving high local spatial autocorrelation is thought to be zonal and hemispheric flow governed by the subtropical and polar jet streams. [ABSTRACT FROM AUTHOR]

In this study, the ability of a regional climate model, based on MM5, to simulate the climate of the Middle East at the beginning of the twenty-first century is assessed. The model is then used to simulate the changes due to global warming over the twenty-first century. The regional climate model displays a negative bias in temperature throughout the year and over most of the domain. It does a good job of simulating the precipitation for most of the domain, though it performs relatively poorly over the southeast Black Sea and southwest Caspian Sea. Using boundary conditions obtained from CCSM3, the model was run for the first and last 5 years of the twenty-first century. The results show widespread warming, with a maximum of ~10 K in interior Iran during summer. It also found some cooling in the southeast Black Sea region during spring and summer that is related to increases in snowfall in the region, a longer snowmelt season, and generally higher soil moisture and latent heating through the summer. The results also show widespread decreases in precipitation over the eastern Mediterranean and Turkey. Precipitation increases were found over the southeast Black Sea, southwest Caspian Sea, and Zagros mountain regions during all seasons except summer, while the Saudi desert region receives increases during summer and autumn. Changes in the dominant precipitation-triggering mechanisms were also investigated. The general trend in the dominant mechanism reflects a change away from the direct dependence on storm tracks and towards greater precipitation triggering by upslope flow of moist air masses. The increase in precipitation in the Saudi desert region is triggered by changes in atmospheric stability brought about by the intrusion of the intertropical convergence zone into the southernmost portion of the domain. [ABSTRACT FROM AUTHOR]

Based on two observational data sets in China from 1956 to 2004, wind speed changes are analyzed. The annual mean wind speed (MWS), days of strong wind (SWDs), and maximum wind (MW) all show declining trends over broad areas of China. Only in the southeastern Tibetan Plateau and the regions from the Great Bend of the Yellow River southward to Yunnan and Guangxi Provinces wind speeds are not significantly reduced, but rather, in partial, these regions’ winds speeds are slightly increased. The regions with declining trends match the areas with relatively strong observed winds and the regions without significant declining trends match the areas with light observed winds. In the meantime, the regions with relatively strong winds correspond to areas of reduced days of SWDs. Trends for both increasing intensities and for the number of days of light winds both impact the installation of wind energy facilities. These may be advantageous to the development of wind energy in different regions. Urbanization, the change of anemometers, or relocation of stations are factors that are mildly responsible for the decreasing trend of MWS. The main reason for the decreasing trend is that under the background of global warming, the contrasts of the sea level pressure, and near-surface temperature between the Asian continent and the Pacific Ocean have become significantly smaller, and the east Asian trough has shifted eastward and northward, and has weakened as well. Both East Asian winter and summer monsoons are decreasing, and all of these impacts have resulted in declines of MWS in China. [ABSTRACT FROM AUTHOR]