Downscaling extreme month-long anomalies in southern South America

We investigate the performance of one stretched-grid atmospheric global model, five different regional climate models and a statistical downscaling technique in simulating 3 months (January 1971, November 1986, July 1996) characterized by anomalous climate conditions in the southern La Plata Basin. Models were driven by reanalysis (ERA-40). The analysis has emphasized on the simulation of the precipitation over land and has provided a quantification of the biases of and scatter between the different regional simulations. Most but not all dynamical models underpredict precipitation amounts in south eastern South America during the three periods. Results suggest that models have regime dependence, performing better for some conditions than others. The models’ ensemble and the statistical technique succeed in reproducing the overall observed frequency of daily precipitation for all periods. But most models tend to underestimate the frequency of dry days and overestimate the amount of light rainfall days. The number of events with strong or heavy precipitation tends to be under simulated by the models.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

Uncertainty analysis of statistical downscaling models using Hadley Centre Coupled Model

Regression-based statistical downscaling is a method broadly used to resolve the coarse spatial resolution of general circulation models. Nevertheless, the assessment of uncertainties linked with climatic variables is essential to climate impact studies. This study presents a procedure to characterize the uncertainty in regression-based statistical downscaling of daily precipitation and temperature over a highly vulnerable area (semiarid catchment) in the west of Iran, based on two downscaling models: a statistical downscaling model (SDSM) and an artificial neural network (ANN) model. Biases in mean, variance, and wet/dry spells are estimated for downscaled data using vigorous statistical tests for 30 years of observed and downscaled daily precipitation and temperature data taken from the National Center for Environmental Prediction reanalysis predictors for the years of 1961 to 1990. In the case of daily temperature, uncertainty is estimated by comparing monthly mean and variance of downscaled and observed daily data at a 95 % confidence level. In daily precipitation, downscaling uncertainties were evaluated from comparing monthly mean dry and wet spell lengths and their confidence intervals, cumulative frequency distributions of monthly mean of daily precipitation, and the distributions of monthly wet and dry days for observed and modeled daily precipitation. Results showed that uncertainty in downscaled precipitation is high, but simulation of daily temperature can reproduce extreme events accurately. Finally, this study shows that the SDSM is the most proficient model at reproducing various statistical characteristics of observed data at a 95 % confidence level, while the ANN model is the least capable in this respect. This study attempts to test uncertainties of regression-based statistical downscaling techniques in a semiarid area and therefore contributes to an improvement of the quality of predictions of climate change impact assessment in regions of this type.     

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.     

Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.     

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.     

Annual precipitation cycle in regional climate models: the influence of horizontal resolution

The influence of increased horizontal resolution on regional climate models simulations of 1961–1990 period was investigated with a focus on precipitation. The main attention was paid to the annual cycle of precipitation described by a special characteristic, precipitation half-time. Two models (RegCM3 and ALADIN-CLIMATE/CZ), both of them in two horizontal resolutions (25 and 10 km), were used. An evaluation of model simulations with 25 km resolution on the European domain is presented as well as a more detailed evaluation of both 25 and 10 km versions on the area of the Czech Republic. Generally, the effects of increased horizontal resolution vary with climate model and evaluated characteristic. For the precipitation amount and the dependence of precipitation amount on altitude, the increase in horizontal resolution decreases the accuracy of results in both models. For the simulation of annual precipitation cycle and the precipitation half-time, RegCM3 results improved with the increased horizontal resolution, whereas ALADIN-CLIMATE/CZ results worsened.     

基于RegCM4模式的中国区域日尺度降水模拟误差订正

气候模式模拟得到的各气候变量与观测相比,总会存在一定的偏差,所得到的气候变化预估结果难以在影响评估模型中直接应用。本文尝试对一个区域气候模式（RegCM4.4）所模拟的中国区域逐日降水,基于概率分布（分位数映射）方法进行统计误差订正。在订正过程中,以模拟时段1991~2010年中的前半段（1991~2000年）作为参照时段,建立传递函数,对后一时段（2001~2010年）进行订正并检验其效果。首先对使用参数和非参数所建立的6种不同传递函数方法进行对比,发现6种方法均可明显减少降水模拟的误差,其中利用非参数转换建立传递函数的RQUANT方法效果更好。随后进一步分析了采用该方法对模式模拟降水所做订正的效果,结果表明,该方法可以明显改善对平均降水,以及降水年际变率和极端事件的模拟结果。     

Temporal statistical downscaling of precipitation and temperature forecasts using a stochastic weather generator

Statistical downscaling is based on the fact that the large-scale climatic state and regional/local physiographic features control the regional climate. In the present paper, a stochastic weather generator is applied to seasonal precipitation and temperature forecasts produced by the International Research Institute for Climate and Society(IRI). In conjunction with the GLM(generalized linear modeling) weather generator, a resampling scheme is used to translate the uncertainty in the seasonal forecasts(the IRI format only specifies probabilities for three categories: below normal, near normal, and above normal) into the corresponding uncertainty for the daily weather statistics. The method is able to generate potentially useful shifts in the probability distributions of seasonally aggregated precipitation and minimum and maximum temperature, as well as more meaningful daily weather statistics for crop yields, such as the number of dry days and the amount of precipitation on wet days. The approach is extended to the case of climate change scenarios, treating a hypothetical return to a previously observed drier regime in the Pampas.     

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.     

European dry spell length distributions, years 1951–2000

Daily precipitation records of 267 European rain gauges are considered to obtain dry spell length (DSL) series along the second half of the twentieth century. A dry spell consists of consecutive days with daily rain amount below a given threshold, R ₀. Four DSL series are obtained for R ₀ values equal to 0.1, 1.0, 5.0, and 10.0 mm/day, and their empirical distributions are properly fitted to different statistical models: Pearson type III (PE3), Weibull (WEI), generalised Pareto, (GPA) and lognormal distributions. The parameters of every model are estimated by L-moments, and the goodness of fit is assessed by quantifying discrepancies between empirical and theoretical distributions in the L-skewness–kurtosis diagrams. The most common best-fitting model is PE3, especially for 0.1 and 1.0 mm/day. Nevertheless, a few stations in southern Europe are better modelled by the WEI distribution. For 5.0 and 10.0 mm/day, the spatial distribution of the best-fitting model is more heterogeneous than for the lowest thresholds. While PE3 is still the preferred model for Western Europe, some DSL series are better fitted to WEI or GPA models. Maps of DSL average and standard deviation and expected lengths for return periods of 2, 5, 10, 25, and 50 years show some common features. Whereas for thresholds of 0.1 and 1.0 mm/day, a N–S gradient is detected, especially in Mediterranean areas; for 5.0 and 10.0 mm/day, a NW–SE gradient is observed in the Iberian Peninsula and a SW–NE gradient in the Scandinavian Peninsula. Then, the vicinity to Atlantic and Arctic Oceans and the Mediterranean Sea, as well as orographic features, are more determining factors than the latitude in patterns associated with the highest R ₀ thresholds. Finally, a regional frequency analysis based on a clustering algorithm is attempted for the four thresholds R ₀, with the PE3 model as the parent distribution for the largest clusters.     

Projected change in East Asian summer monsoon precipitation under RCP scenario

Future changes in East Asian summer monsoon precipitation climatology, frequency, and intensity are analyzed using historical climate simulations and future climate simulations under the RCP4.5 scenario using the World Climate Research Programme’s (WCRP) Coupled Model Intercomparison Project 5 (CMIP5) multi-model dataset. The model reproducibility is evaluated, and well performance in the present-day climate simulation can be obtained by most of the studied models. However, underestimation is obvious over the East Asian region for precipitation climatology and precipitation intensity, and overestimation is observed for precipitation frequency. The overestimation of precipitation frequency is mainly due to the large positive bias of the light precipitation (precipitation <10 mm/day) days, and the underestimation of precipitation intensity is mainly caused by the negative bias of the intense precipitation (precipitation >10 mm/day) intensity. For the future climate simulations, simple multi-model ensemble (MME) averages using all of the models show increases in precipitation and its intensity over almost all of East Asia, while the precipitation frequency is projected to decrease over eastern China and around Japan and increase in other regions. When the weighted MME is considered, no large difference can be observed compared with the simple MME. For the MME using the six best models that have good performance in simulating the present-day climate, the future climate changes over East Asia are very similar to those predicted using all of the models. Further analysis shows that the frequency and intensity of intense precipitation events are also projected to significantly increase over East Asia. Increases in precipitation frequency and intensity are the main contributors to increases in precipitation, and the contribution of frequency increases (contributed by 40.8 % in the near future and by 58.9 % by the end of the twenty-first century) is much larger than that of intensity increases (contributed by 29.9 % in the near future and by 30.1 % by the end of the twenty-first century). This finding also implies an increased risk of intense precipitation events over the East Asian region under global warming scenario. These results regarding future climate simulations show much greater reliability than those using CMIP3 simulations.     

Changes in daily climate extremes in the arid area of northwestern China

There has been a paucity of information on trends in daily climate and climate extremes, especially for the arid region. We analyzed the changes in the indices of climate extremes, on the basis of daily maximum and minimum air temperature and precipitation at 59 meteorological stations in the arid region of northwest China over the period 1960–2003. Twelve indices of extreme temperature and six indices of extreme precipitation are examined. Temperature extremes show a warming trend with a large proportion of stations having statistically significant trends for all temperature indices. The regional occurrence of extreme cool days and nights has decreased by ?0.93 and ?2.36 days/decade, respectively. Over the same period, the occurrence of extreme warm days and nights has increased by 1.25 and 2.10 days/decade, respectively. The number of frost days and ice days shows a statistically significant decrease at the rate of ?3.24 and ?2.75 days/decade, respectively. The extreme temperature indices also show the increasing trend, with larger values for the index describing variations in the lowest minimum temperature. The trends of Min Tmin (Tmax) and Max Tmin (Tmax) are 0.85 (0.61) and 0.32 (0.17)?°C/decade. Most precipitation indices exhibit increasing trends across the region. On average, regional maximum 1-day precipitation, annual total wet-day precipitation, and number of heavy precipitation days and very wet days show insignificant increases. Insignificant decreasing trends are also found for consecutive dry days. The rank-sum statistic value of most temperature indices exhibits consistent or statistically significant trends across the region. The regional medians after 1986 of Min Tmin (Tmax), Max Tmin (Tmax), warm days (nights), and warm spell duration indicator show statistically more larger than medians before 1986, but the frost days, ice days, cool days (nights), and diurnal temperature range reversed. The medians of precipitation indices show insignificant change except for consecutive dry days before and after 1986.     

Projection and possible causes of summer precipitation in eastern China using self-organizing map

Self-organizing map (SOM) is used to simulate summer daily precipitation over the Yangtze–Huaihe river basin in Eastern China, including future projections. SOM shows good behaviors in terms of probability distribution of daily rainfall and spatial distribution of rainfall indices, as well as consistency of multi-model simulations. Under RCP4.5 Scenario, daily rainfall at most sites (63%) is projected to shift towards larger values. For the early 21st century (2016–2035), precipitation in the central basin increases, yet decreases occur over the middle reaches of the Yangtze River as well as a part of its southeast area. For the late 21st century (2081–2100), the mean precipitation and extreme indices experience an overall increase except for a few southeast stations. The total precipitation in the lower reaches of the Yangtze River and in its south area is projected to increase from 7% at 1.5 °C global warming to 11% at 2 °C, while the intensity enhancement is more significant in southern and western sites of the domain. A clustering allows to regroup all SOM nodes into four distinct regimes. Such regional synoptic regimes show remarkable stability for future climate. The overall intensification of precipitation in future climate is linked to the occurrence-frequency rise of a wet regime which brings longitudinally closer the South Asia High (eastward extended) and the Western Pacific Subtropical High (westward extended), as well as the reduction of a dry pattern which makes the two atmospheric centers of action move away from each other.     

Assessing the robustness of projected precipitation changes over central Africa on the basis of a multitude of global and regional climate projections

It is well accepted within the scientific community that a large ensemble of different projections is required to achieve robust climate change information for a specific region. For this purpose we have compiled a state-of-the-art multi-model multi-scenario ensemble of global and regional precipitation projections. This ensemble combines several global projections from the CMIP3 and CMIP5 databases, along with some recently downscaled regional CORDEX-Africa projections. Altogether daily precipitation data from 77 different climate change projections is analysed; separated into 31 projections for a high and 46 for a low emission scenario. We find a robust indication that, independent of the underlying emission scenario, annual total precipitation amounts over the central African region are not likely to change severely in the future. However some robust changes in precipitation characteristics, like the intensification of heavy rainfall events as well as an increase in the number of dry spells during the rainy season are projected for the future. Further analysis shows that over some regions the results of the climate change assessment clearly depend on the size of the analyzed ensemble. This indicates the need of a “large-enough” ensemble of independent climate projections to allow for a reliable climate change assessment.     

Assessing future climate changes and extreme indicators in east and south Asia using the RegCM4 regional climate model

This paper assesses future climate changes over East and South Asia using a regional climate model (RegCM4) with a 50?km spatial resolution. To evaluate the model performance, RegCM4 is driven with ??perfect boundary forcing?? from the reanalysis data during 1970?C1999 to simulate the present day climate. The model performs well in reproducing not only the mean climate and seasonality but also most of the chosen indicators of climate extremes. Future climate changes are evaluated based on two experiments driven with boundary forcing from the European-Hamburg general climate model (ECHAM5), one for the present (1970?C1999) and one for the SRES A1B future scenario (2070?C2099). The model predicts an annual temperature increase of about 3°?C5° (smaller over the ocean and larger over the land), and an increase of annual precipitation over most of China north of 30°N and a decrease or little change in the rest of China, India and Indochina. For temperature-related extreme indicators in the future, the model predicts a generally longer growing season, more hot days in summer, and less frost days in winter. For precipitation-related extremes, the number of days with more than 10?mm of rainfall is predicted to increase north of 30°N and decrease in the south, and the maximum five-day rainfall amount and daily intensity will increase across the whole model domain. In addition, the maximum number of consecutive dry days is predicted to increase over most of the model domain, south of 40°N. Most of the Yangtze River Basin in China stands out as ??hotspots?? of extreme precipitation changes, with the strongest increases of daily rain intensity, maximum five-day rain amount, and the number of consecutive dry days, suggesting increased risks of both floods and droughts.     

Application of physical scaling towards downscaling climate model precipitation data

Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2–4 day), and long (more than 5-day) precipitation events is projected.     

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during1961–2005, the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5), are assessed in terms of spatial distribution and interannual variability. The CMIP6 multi-model ensemble mean(CMIP6-MME) can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature, and minimum ...     

NEX-GDDP降尺度数据对中国极端降水指数模拟能力的评估

利用1986—2005年中国地面气象台站观测的格点化逐日降水数据(CN05.1)评估了NASA高分辨率降尺度逐日数据集NEX-GDDP中21个全球气候模式在0.25?(约25 km×25 km)分辨率下对中国极端降水的模拟能力.选取年最大日降水量(RX1D)、年最大5 d降水量(RX5D)、湿日总降水量(PRCPTOT...     

Climate projections of future extreme events accounting for modelling uncertainties and historical simulation biases

A methodology is presented for providing projections of absolute future values of extreme weather events that takes into account key uncertainties in predicting future climate. This is achieved by characterising both observed and modelled extremes with a single form of non-stationary extreme value (EV) distribution that depends on global mean temperature and which includes terms that account for model bias. Such a distribution allows the prediction of future “observed” extremes for any period in the twenty-first century. Uncertainty in modelling future climate, arising from a wide range of atmospheric, oceanic, sulphur cycle and carbon cycle processes, is accounted for by using probabilistic distributions of future global temperature and EV parameters. These distributions are generated by Bayesian sampling of emulators with samples weighted by their likelihood with respect to a set of observational constraints. The emulators are trained on a large perturbed parameter ensemble of global simulations of the recent past, and the equilibrium response to doubled CO₂. Emulated global EV parameters are converted to the relevant regional scale through downscaling relationships derived from a smaller perturbed parameter regional climate model ensemble. The simultaneous fitting of the EV model to regional model data and observations allows the characterisation of how observed extremes may change in the future irrespective of biases that may be present in the regional models simulation of the recent past climate. The clearest impact of a parameter perturbation in this ensemble was found to be the depth to which plants can access water. Members with shallow soils tend to be biased hot and dry in summer for the observational period. These biases also appear to have an impact on the potential future response for summer temperatures with some members with shallow soils having increases for extremes that reduce with extreme severity. We apply this methodology for London, using the A1B future emissions scenario to obtain projections of the 50 year return values for the 20 year period centred on 2050. We obtain 10th to 90th percentile ranges of 35.9–42.1 °C for summer daily maximum temperature, 35.5–52.4 mm for summer daily rainfall and 79.2, 97.0 mm for autumn 5 day total rainfall, compared to observed estimates for 1961–1990 of 35.7 °C, 42.1 and 78.4 mm respectively.