Daily precipitation intensity projected for the 21st century: seasonal changes over the Pyrenees

A set of climate parameters (mean precipitation, number of wet days, daily intensity, and number of days with more than 50 mm rainfall) and a quantile-based approach are used to assess the expected changes in daily precipitation characteristics over the Pyrenees predicted for the 21st century using a set of regional climate models (RCMs). The features of the geographic location and topography of the Pyrenees imply that the climate of the region is highly complex. The results point toward an intensification of extremes, with a generalized tendency toward increasing drought periods, an increasing trend in daily intensity, and an increasing contribution of intense events to total precipitation; however, the results are subject to substantial spatial and seasonal variability, mainly related to the Atlantic-Mediterranean gradient and the longitudinal disposition of the main axis of the range.     

Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.     

On the future reduction of snowfall in western and central Europe

Large parts of western and central Europe face a 20–50 % future reduction in snowfall on Hellmann days (days with daily-mean temperatures below freezing). This strong reduction occurs in addition to the expected 75 % decrease of the number of Hellmann days near the end of the twenty first century. The result is insensitive to the exact freezing-level threshold, but is in sharp contrast with the winter daily precipitation, which increases under most global warming scenarios. Not only climate model simulations show this. Observational records also reveal that probabilities for precipitation on Hellmann days have been larger in the past. The future reduction is a consequence of the freezing-level threshold becoming a more extreme quantile of the temperature distribution in the future. Only certain circulation types permit these quantiles to be reached, and it is shown that these have intrinsically low precipitation probability.     

AN ANALYSIS OF THE WINTER EXTREME PRECIPITATION EVENTS ON THE BACKGROUND OF CLIMATE WARMING IN SOUTHERN CHINA

Based on daily precipitation and monthly temperature data in southern China, the winter extreme precipitation changes in southern China have been investigated by using the Mann-Kendall test and the return values of Generalized Pareto Distribution. The results show that a winter climate catastrophe in southern China occurred around 1991, and the intensity of winter extreme precipitation was strengthened after climate warming. The anomalous circulation characteristics before and after the climate warming was further analyzed by using the U.S. National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data. It is found that the tropical winter monsoon over East Asia is negatively correlated with the precipitation in southeastern China. After climate warming the meridionality of the circulations in middle and high latitudes increases, which is favorable for the southward movement of the cold air from the north. In addition, the increase of the temperature over southern China may lead to the decrease of the differential heating between the continent and the ocean. Consequently, the tropical winter monsoon over East Asia is weakened, which is favorable for the transport of the warm and humid air to southeastern China and the formation of the anomalous convergence of the moisture flux, resulting in large precipitation over southeastern China. As a result, the interaction between the anomalous circulations in the middle and high latitudes and lower latitudes after the climate warming plays a major role in the increase of the winter precipitation intensity over southeastern China.     

我国南方冬季气候变暖前后极端降水事件分析

利用我国南方逐日降水资料及逐月温度资料,采用Mann-Kendall突变检验方法,并计算极端降水的GPD(Generalized Pareto Distribution)重现值,讨论了气候变暖前后我国南方冬季极端降水事件的变化。结果表明,我国南方冬季气候变暖的突变发生在1991年前后,且气候变暖后我国南方冬季的极端降水强度普遍有所增加。利用NCEP/NCAR再分析资料进一步分析气候变暖前后的环流场特征,发现东亚热带冬季风异常与我国华南、江南地区降水异常有显著的相关关系。东亚热带冬季风偏强(弱),华南、江南地区降水偏少(多)。气候变暖后中高纬度环流经向度加大,有利于北方的冷空气向南输送。此外,气候变暖后我国南方地面气温升高,海陆热力差异减小,东亚热带冬季风减弱,有利于西太平洋的暖湿气流向我国大陆东南部输送,并在东南部形成异常的水汽通量辐合,有利于形成强降水。气候变暖后,中高纬度与中低纬度异常环流系统的相互作用是我国东南部降水强度增加的主要原因。     

Temporal downscaling: a comparison between artificial neural network and autocorrelation techniques over the Amazon Basin in present and future climate change scenarios

Several studies have been devoted to dynamic and statistical downscaling for both climate variability and climate change. This paper introduces an application of temporal neural networks for downscaling global climate model output and autocorrelation functions. This method is proposed for downscaling daily precipitation time series for a region in the Amazon Basin. The downscaling models were developed and validated using IPCC AR4 model output and observed daily precipitation. In this paper, five AOGCMs for the twentieth century (20C3M; 1970–1999) and three SRES scenarios (A2, A1B, and B1) were used. The performance in downscaling of the temporal neural network was compared to that of an autocorrelation statistical downscaling model with emphasis on its ability to reproduce the observed climate variability and tendency for the period 1970–1999. The model test results indicate that the neural network model significantly outperforms the statistical models for the downscaling of daily precipitation variability.     

Stochastic Modeling of the Effects of Large-Scale Circulation on Daily Weather in the Southeastern U.S.

Statistical methodology is devised to model time series of daily weather at individual locations in the southeastern U.S. conditional on patterns in large-scale atmosphere–ocean circulation. In this way, weather information on an appropriate temporal and spatial scale for input to crop–climate models can be generated, consistent with the relationship between circulation and temporally and/or spatially aggregated climate data (an exercise sometimes termed `downscaling'). The Bermuda High, a subtropical Atlantic circulation feature, is found to have the strongest contemporaneous correlation with seasonal mean temperature and total precipitation in the Southeast (in particular, stronger than for the El Niño–Southern Oscillation phenomenon). Stochastic models for time series of daily minimum and maximum temperature and precipitation amount are fitted conditional on an index indicating the average position of the Bermuda High. For precipitation, a multi-site approach involving a statistical technique known as `borrowing strength' is applied, constraining the relationship between daily precipitation and the Bermuda High index to be spatially the same. In winter (the time of greatest correlation), higher daily maximum and minimum temperature means and higher daily probability of occurrence of precipitation are found when there is an easterly shift in the average position of the Bermuda High. Methods for determining aggregative properties of these stochastic models for daily weather (e.g., variance and spatial correlation of seasonal total precipitation) are also described, so that their performance in representing low frequency variations can be readily evaluated.     

New precipitation and temperature grids for northern Patagonia: Advances in relation to global climate grids

Climate data of mean monthly temperature and total monthly precipitation compiled from different sources in northern Patagonia were interpolated to 20-km resolution grids over the period 1997–2010. This northern Patagonian climate grid (NPCG) improves upon previous gridded products in terms of its spatial resolution and number of contributing stations, since it incorporates 218 and 114 precipitation and temperature records, respectively. A geostatistical method using surface elevation from a Digital Elevation Model (DEM) as the ancillary variable was used to interpolate station data into even spaced points. The maps provided by NPCG are consistent with the broad spatial and temporal patterns of the northern Patagonian climate, showing a comprehensive representation of the latitudinal and altitudinal gradients in temperature and precipitation, as well as their related patterns of seasonality and continentality. We compared the performance of NPCG and various other datasets available to the climate community for northern Patagonia. The grids used for the comparison included those of the Global Precipitation Climatology Project, ERAInterim, Climate Research Unit (University of East Anglia), and University of Delaware. Based on three statistics that quantitatively assess the spatial coherence of gridded data against available observations (bias, MAE, and RMSE), NPCG outperforms other global grids. NPCG represents a useful tool for understanding climate variability in northern Patagonia and a valuable input for regional models of hydrological and ecological processes. Its resolution is optimal for validating data from the general circulation models and working with raster data derived from remote sensing, such as vegetation indices.     

Temporal instability of temperature singularities in a long-term series at Prague-Klementinum

The recent study of meteorological singularities in the Czech Republic—?ezní?ková et al. (Theor Appl Climatol 88:179–192, 2007)—is supplemented with respect to findings concerning temporal stability of air temperature singularities. A long-term daily series at Prague-Klementinum is examined over 1881–2000, adopting the same statistical background for the detection of singularities. A procedure that reduces the dependence of results on the choice of a reference period is proposed. It is shown that nearly all temperature singularities found over the period since 1961 and/or the whole period of 1881–2000 are temporally unstable, and a lot of them should be treated as statistical properties of particular data samples (time periods) reflecting sampling variability rather than stable and recurrent anomalies related to distinct circulation patterns. The most important singularities are identified, occurring on 4 days in year only (around St. Médard’s Day, 8 June), and they are linked to intraseasonal variations in the occurrence of circulation patterns conducive to warm and cold temperature anomalies. A sharp increase (decrease) in the frequency of north (south) circulation types after 8 June leads to the most robust irregularity in the mean annual cycle of temperature.     

Mediterranean climate extremes in synoptic downscaling assessments

The behaviour of precipitation and maximum temperature extremes in the Mediterranean area under climate change conditions is analysed in the present study. In this context, the ability of synoptic downscaling techniques in combination with extreme value statistics for dealing with extremes is investigated. Analyses are based upon a set of long-term station time series in the whole Mediterranean area. At first, a station-specific ensemble approach for model validation was developed which includes (1) the downscaling of daily precipitation and maximum temperature values from the large-scale atmospheric circulation via analogue method and (2) the fitting of extremes by generalized Pareto distribution (GPD). Model uncertainties are quantified as confidence intervals derived from the ensemble distributions of GPD-related return values and described by a new metric called “ratio of overlapping”. Model performance for extreme precipitation is highest in winter, whereas the best models for maximum temperature extremes are set up in autumn. Valid models are applied to a 30-year period at the end of the twenty-first century (2070–2099) by means of ECHAM5/MPI-OM general circulation model data for IPCC SRES B1 scenario. The most distinctive future changes are observed in autumn in terms of a strong reduction of precipitation extremes in Northwest Iberia and the Northern Central Mediterranean area as well as a simultaneous distinct increase of maximum temperature extremes in Southwestern Iberia and the Central and Southeastern Mediterranean regions. These signals are checked for changes in the underlying dynamical processes using extreme-related circulation classifications. The most important finding connected to future changes of precipitation extremes in the Northwestern Mediterranean area is a reduction of southerly displaced deep North Atlantic cyclones in 2070–2099 as associated with a strengthened North Atlantic Oscillation. Thus, the here estimated future changes of extreme precipitation are in line with the discourse about the influence of North Atlantic circulation variability on the changing climate in Europe.     

Evaluation of the twenty-first century RCM simulations driven by multiple GCMs over the Eastern Mediterranean–Black Sea region

In this study, human-induced climate change over the Eastern Mediterranean–Black Sea region has been analyzed for the twenty-first century by performing regional climate model simulations forced with large-scale fields from three different global circulation models (GCMs). Climate projections have been produced with Special Report on Emissions Scenarios A2, A1FI and B1 scenarios, which provide greater diversity in climate information for future period. The gradual increases for temperature are widely apparent during the twenty-first century for each scenario simulation, but ECHAM5-driven simulation generally has a weaker signal for all seasons compared to CCSM3 simulations except for the Fertile Crescent. The contrast in future temperature change between the winter and summer seasons is very strong for CCSM3-A2-driven and HadCM3-A2-driven simulations over Carpathians and Balkans, 4–5 °C. In addition, winter runoff over mountainous region of Turkey, which feeds many river systems including the Euphrates and Tigris, increases in second half of the century since the snowmelt process accelerates where the elevation is higher than 1,500 m. Moreover, analysis of daily temperature outputs reveals that the gradual decrease in daily minimum temperature variability for January during the twenty-first century is apparent over Carpathians and Balkans. Analysis of daily precipitation extremes shows that positive trend is clear during the last two decades of the twenty-first century over Carpathians for both CCSM3-driven and ECHAM5-driven simulations. Multiple-GCM driven regional climate simulations contribute to the quantification of the range of climate change over a region by performing detailed comparisons between the simulations.     

An evaluation of RegCM3_CERES for regional climate modeling in China

A 20-year simulation of regional climate over East Asia by the regional climate model RegCM3_CERES (Regional Climate Model version 3 coupled with the Crop Estimation through Resource and Environment Synthesis) was carried out and compared with observations and the original RegCM3 model to comprehensively evaluate its performance in simulating the regional climate over continental China. The results showed that RegCM3_CERES reproduced the regional climate at a resolution of 60 km over China by using ERA40 data as the boundary conditions, albeit with some limitations. The model captured the basic characteristics of the East Asian circulation, the spatial distribution of mean precipitation and temperature, and the daily characteristics of precipitation and temperature. However, it underestimated both the intensity of the monsoon in the monsoonal area and precipitation in southern China, overestimated precipitation in northern China, and produced a systematic cold temperature bias over most of continental China. Despite these limitations, it was concluded that the RegCM3_CERES model is able to simulate the regional climate over continental China reasonably well.     

Large-scale modes impact on Iraq climate variability

The impact of large-scale modes on Iraq climate is investigated here based on winter and spring fields of temperature and precipitation. The temperature data (1971–2010) was recorded at 8 stations whereas the precipitation fields (1981–2010) were recorded at 18 locations. Empirical orthogonal function analyses were performed in order to characterize the spatial variability of the Iraq climatological parameters. The relationships between the global sea surface temperature, sea level pressure, and geopotential height fields with the dominant modes of Iraq temperature and precipitation were also investigated. Correlation and regression maps emphasize links between Iraq climate and large-scale modes, like the Atlantic Multidecadal Oscillation and the El Niño Southern Oscillation phenomenon.     

Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China

A statistical downscaling method (SDSM) was evaluated by simultaneously downscaling air temperature, evaporation, and precipitation in Haihe River basin, China. The data used for evaluation were large-scale atmospheric data encompassing daily NCEP/NCAR reanalysis data and the daily mean climate model results for scenarios A2 and B2 of the HadCM3 model. Selected as climate variables for downscaling were measured daily mean air temperature, pan evaporation, and precipitation data (1961–2000) from 11 weather stations in the Haihe River basin. The results obtained from SDSM showed that: (1) the pattern of change in and numerical values of the climate variables can be reasonably simulated, with the coefficients of determination between observed and downscaled mean temperature, pan evaporation, and precipitation being 99%, 93%, and 73%, respectively; (2) systematic errors existed in simulating extreme events, but the results were acceptable for practical applications; and (3) the mean air temperature would increase by about 0.7°C during 2011~2040; the total annual precipitation would decrease by about 7% in A2 scenario but increase by about 4% in B2 scenario; and there were no apparent changes in pan evaporation. It was concluded that in the next 30 years, climate would be warmer and drier, extreme events could be more intense, and autumn might be the most distinct season among all the changes.     

Impacts of a nuclear war in South Asia on soybean and maize production in the Midwest United States

Crop production would decline in the Midwestern United States from climate change following a regional nuclear conflict between India and Pakistan. Using Agro-IBIS, a dynamic agroecosystem model, we simulated the response of maize and soybeans to cooler, drier, and darker conditions from war-related smoke. We combined observed climate conditions for the states of Iowa, Illinois, Indiana, and Missouri with output from a general circulation climate model simulation that injected 5 Tg of elemental carbon into the upper troposphere. Both maize and soybeans showed notable yield reductions for a decade after the event. Maize yields declined 10–40 % while soybean yields dropped 2–20 %. Temporal variation in magnitude of yield for both crops generally followed the variation in climatic anomalies, with the greatest decline in the 5 years following the 5 Tg event and then less, but still substantial yield decline, for the rest of the decade. Yield reduction for both crops was linked to changes in growing period duration and, less markedly, to reduced precipitation and altered maximum daily temperature during the growing season. The seasonal average of daily maximum temperature anomalies, combined with precipitation and radiation changes, had a quadratic relationship to yield differences; small (0 °C) and large (?3 °C) maximum temperature anomalies combined with other changes led to increased yield loss, but medium changes (?1 °C) had small to neutral effects on yield. The exact timing of the temperature changes during the various crop growth phases also had an important effect.     

Circulation statistics and climate change in Central Europe: PRUDENCE simulations and observations

PRUDENCE simulations of the climate in Central Europe are analysed with respect to mean temperature, mean precipitation and three monthly mean geostrophic circulation indices. The three global models show important circulation biases in the control climate, in particular in the strength of the west-circulations in winter and summer. The nine regional models inherit much of the circulation biases from their host model, especially in winter. In summer, the regional models show a larger spread in circulation statistics, depending on nesting procedures and other model characteristics. Simulated circulation biases appear to have a significant inluence on simulated temperature and precipitation. The PRUDENCE ensemble appears to be biased towards warmer and wetter than observed circulations in winter, and towards warmer and dryer circulations in summer. A2-scenario simulations show important circulation changes, which have a significant impact on changes in the distributions of monthly mean temperature and precipitation. It is likely that interactions between land–surface processes and atmospheric circulation play an important role in the simulated changes in the summer climate in Central Europe.     

INVESTIGATIONS ON SHORT-TERM CLIMATE PREDICTION BY GCMs IN CHINA

Investigations on the short-term climate predictions by general circulation models(GCMs)inChina have been summarized and reviewed in this paper.The research shows that GCMs have thecapability to predict the seasonal and annual characteristics of atmospheric circulation in theNorthern Hemisphere and the patterns of temperature and precipitation over China.It is inspiringto notice that the GCMs have the ability to predict the summer rainfall over China before twoseasons.Several issues for the short-term climate prediction by the GCMs have been discussed inthis paper.     

Fast responses of Northern Hemisphere winter daily circulation to anthropogenic aerosols

Anthropogenic aerosols (AA) have significantly caused anomalous winter mean atmospheric circulation over the Northern Hemisphere, but the main daily patterns of winter large-scale circulation change are not well understood. Here a self-organizing map analysis is applied to identify the leading patterns in AA-induced winter daily geopotential height (Z) anomaly fields simulated by three atmospheric general circulation models, with a focus on fast adjustments. Two winter daily circulation response patterns with a synoptic time scale are found: one pattern shows concurring Z anomalies over North America and North Asia with the same sign and the Bering Sea seeing the opposite, resembling the Asia–Bering–North American teleconnection; while the other is the Arctic Oscillation-like pattern with similar Z anomalies over North Pacific and North Atlantic and the opposite over the Arctic region. The AA-induced anomalous precipitation over the tropics and anomalous synoptic eddy activities over the extratropical oceans concur to support and maintain these circulation anomaly patterns. The winter-mean climate responses to AA can be understood as a result of these daily anomaly patterns, especially over the higher latitudes. Specifically, the associated changes in surface air temperature (SAT) over the mid-high latitudes are caused by the AA-driven meridional movements of polar (cold and dry) airmass and midlatitude (warm and moist) airmass in the regions, mainly through the relevant surface downward longwave radiation. This study highlights the role of AA in altering daily weather patterns, which is not sufficiently captured by seasonal mean responses.     

Summer weather characteristics and periodicity observed over the period 1888–2013 in the region of Belgrade,Serbia

With the goal of finding summer climate patterns in the region of Belgrade (Serbia) over the period 1888–2013, different techniques of multivariate statistical analysis were used in order to analyze the simultaneous changes of a number of climatologic parameters. An increasing trend of the mean daily minimum temperature was detected. In the recent decades (1960–2013), this increase was much more pronounced. The number of days with the daily minimum temperature greater or equal to 20 °C also increased significantly. Precipitation had no statistically significant trend. Spectral analysis showed a repetitive nature of the climatologic parameters which had periods that roughly can be classified into three groups, with the durations of the following: (1) 6 to 7 years, (2) 10 to 18 years, and (3) 21, 31, and 41 years. The temperature variables mainly had one period of repetitiveness of 5 to 7 years. Among other variables, the correlations of regional fluctuations of the temperature and precipitation and atmospheric circulation indices were analyzed. The North Atlantic oscillation index had the same periodicity as that of the precipitation, and it was not correlated to the temperature variables. Atlantic multidecadal oscillation index correlated well to the summer mean daily minimum and summer mean temperatures. The underlying structure of the data was analyzed by principal component analysis, which detected the following four easily interpreted dimensions: More sunshine-Higher temperature, Precipitation, Extreme heats, and Changeable summer.     

Projected changes in South Asian summer monsoon by multi-model global warming experiments

South Asian summer monsoon (June through September) rainfall simulation and its potential future changes are evaluated in a multi-model ensemble of global coupled climate models outputs under World Climate Research Program Coupled Model Intercomparison Project (WCRP CMIP3) dataset. The response of South Asian summer monsoon to a transient increase in future anthropogenic radiative forcing is investigated for two time slices, middle (2031–2050) and end of the twenty-first century (2081–2100), in the non-mitigated Special Report on Emission Scenarios B1, A1B and A2 .There is large inter-model variability in the simulation of spatial characteristics of seasonal monsoon precipitation. Ten out of the 25 models are able to simulate space–time characteristics of the South Asian monsoon precipitation reasonably well. The response of these selected ten models has been examined for projected changes in seasonal monsoon rainfall. The multi-model ensemble of these ten models projects a significant increase in monsoon precipitation with global warming. The substantial increase in precipitation is observed over western equatorial Indian Ocean and southern parts of India. However, the monsoon circulation weakens significantly under all the three climate change experiments. Possible mechanisms for the projected increase in precipitation and for precipitation–wind paradox have been discussed. The surface temperature over Asian landmass increases in pre-monsoon months due to global warming and heat low over northwest India intensifies. The dipole snow configuration over Eurasian continent strengthens in warmer atmosphere, which is conducive for the enhancement in precipitation over Indian landmass. No notable changes have been projected in the El Niño–Monsoon relationship, which is useful for predicting interannual variations of the monsoon.