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1.
We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor’s skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.  相似文献   

2.
Precipitation changes over South Korea were projected using five regional climate models (RCMs) with a horizontal resolution of 12.5 km for the mid and late 21st century (2026-2050, 2076- 2100) under four Representative Concentration Pathways (RCP) scenarios against present precipitation (1981-2005). The simulation data of the Hadley Centre Global Environmental Model version 2 coupled with the Atmosphere-Ocean (HadGEM2-AO) was used as boundary data of RCMs. In general, the RCMs well simulated the spatial and seasonal variations of present precipitation compared with observation and HadGEM2-AO. Equal Weighted Averaging without Bias Correction (EWA_NBC) significantly reduced the model biases to some extent, but systematic biases in results still remained. However, the Weighted Averaging based on Taylor’s skill score (WEA_Tay) showed a good statistical correction in terms of the spatial and seasonal variations, the magnitude of precipitation amount, and the probability density. In the mid-21st century, the spatial and interannual variabilities of precipitation over South Korea are projected to increase regardless of the RCP scenarios and seasons. However, the changes in area-averaged seasonal precipitation are not significant due to mixed changing patterns depending on locations. Whereas, in the late 21st century, the precipitation is projected to increase proportionally to the changes of net radiative forcing. Under RCP8.5, WEA_Tay projects the precipitation to be increased by about +19.1, +20.5, +33.3% for annual, summer and winter precipitation at 1-5% significance levels, respectively. In addition, the probability of strong precipitation (≥ 15 mm d-1) is also projected to increase significantly, particularly in WEA_Tay under RCP8.5.  相似文献   

3.
This study was targeted at evaluating the performance of six Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX). The evaluation is on the bases of how well the RCMs simulate the seasonal mean climatology, interannual variability and annual cycles of rainfall, maximum and minimum temperature over two catchments in western Ethiopia during the period 1990–2008. Observed data obtained from the Ethiopian National Meteorological Agency was used for performance evaluation of the RCMs outputs. All Regional Climate Models (RCMs) have simulated seasonal mean annual cycles of precipitation with a significant bias shown on individual models; however, the ensemble mean exhibited better the magnitude and seasonal rainfall. Despite the highest biases of RCMs in the wet season, the annual cycle showed the prominent features of precipitation in the two catchments. In many aspects, CRCM5 and RACMO22 T simulate rainfall over most stations better than the other models. The highest biases are associated with the highest error in simulating maximum and minimum temperature with the highest biases in high elevation areas. The rainfall interannual variability is less evident in Finchaa with short rainy season experiencing a larger degree of interannual variability. The differences in performance of the Regional Climate Models in the two catchments show that all the available models are not equally good for particular locations and topographies. In this regard, the right regional climate models have to be used for any climate change impact study for local-scale climate projections.  相似文献   

4.
In this study, the projection of future drought conditions is estimated over South Korea based on the latest and most advanced sets of regional climate model simulations under the Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios, within the context of the national downscaling project of the Republic of Korea. The five Regional Climate Models (RCMs) are used to produce climate-change simulations around the Korean Peninsula and to estimate the uncertainty associated with these simulations. The horizontal resolution of each RCM is 12.5 km and model simulations are available for historical (1981-2010) and future (2021-2100) periods under forcing from the RCP4.5 and RCP8.5 scenarios. To assess the characteristics of drought on multiple time scales in the future, we use Standardized Precipitation Indices for 1-month (SPI- 1), 6-month (SPI-6) and 12-month (SPI-12). The number of drought months in the future is shown to be characterized by strong variability, with both increasing and decreasing trends among the scenarios. In particular, the number of drought months over South Korea is projected to increase (decrease) for the period 2041-2070 in the RCP8.5 (RCP4.5) scenario and increase (decrease) for the period 2071-2100 in the RCP4.5 (RCP8.5) scenario. In addition, the percentage area under any drought condition is overall projected to gradually decrease over South Korea during the entire future period, with the exception of SPI-1 in the RCP4.5 scenario. Particularly, the drought areas for SPI-1 in the RCP4.5 scenario show weakly positive long-term trend. Otherwise, future changes in drought areas for SPI-6 and SPI-12 have a marked downward trend under the two RCP scenarios.  相似文献   

5.
In this study, we investigated the prospect of calibrating probabilistic forecasts of surface air temperature (SAT) over South Korea by using Bayesian model averaging (BMA). We used 63 months of simulation results from four regional climate models (RCMs) with two boundary conditions (NCEP-DOE and ERA-interim) over the CORDEX East Asia. Rank histograms and residual quantile-quantile (R-Q-Q) plots showed that the simulation skills of the RCMs differ according to season and geographic location, but the RCMs show a systematic cold bias irrespective of season and geographic location. As a result, the BMA weights are clearly dependent on geographic location, season, and correlations among the models. The one-month equal weighted ensemble (EWE) outputs for the 59 stations over South Korea were calibrated using the BMA method for 48 monthly time periods based on BMA weights obtained from the previous 15 months of training data. The predictive density function was calibrated using BMA and the individual forecasts were weighted according to their performance. The raw ensemble forecasts were assessed using the flatness of the rank histogram and the R-Q-Q plot. The results showed that BMA improves the calibration of the EWE and the other weighted ensemble forecasts irrespective of season, simulation skill of the RCM, and geographic location. In addition, deterministic-style BMA forecasts usually perform better than the deterministic forecast of the single best member.  相似文献   

6.
This study assesses future climate change over East Asia using the Global/Regional Integrated Model system—Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2 (HG2); the representative concentration pathways (RCP) 4.5 and 8.5 scenarios for the intergovernmental panel on climate change fifth assessment report (AR5). Analyses for the current (1980–2005) climate are performed to evaluate the RMP’s ability to reproduce precipitation and temperature. Two different future (2006–2050) simulations are compared with the current climatology to investigate the climatic change over East Asia centered in Korea. The RMP satisfactorily reproduces the observed seasonal mean and variation of precipitation and temperature. The spatial distribution of the simulated large-scale features and precipitation by the RMP is generally less reflective of current climatic conditions than that is given by the HG2, but their inter-annual variations in East Asia are better captured by the RMP. Furthermore, the RMP shows higher reproducibility of climate extremes including excessive heat wave and precipitation events over South Korea. In the future, strong warming is distinctly coupled with intensified monsoonal precipitation over East Asia. In particular, extreme weather conditions are increased and intensified over South Korea as follows: (1) The frequency of heat wave events with temperature greater than 30 °C is projected to increase by 131 and 111 % in the RCP 8.5 and 4.5 downscaling, relative to the current climate. (2) The RCP 8.5 downscaling shows the frequency and variability of heavy rainfall to increase by 24 and 31.5 %, respectively, while the statistics given by the RCP 4.5 downscaling are similar to those of the current climate.  相似文献   

7.

This study assesses the hydroclimatic response to global warming over East Asia from multi-model ensemble regional projections. Four different regional climate models (RCMs), namely, WRF, HadGEM3-RA, RegCM4, and GRIMs, are used for dynamical downscaling of the Hadley Centre Global Environmental Model version 2–Atmosphere and Ocean (HadGEM2-AO) global projections forced by the representative concentration pathway (RCP4.5 and RCP8.5) scenarios. Annual mean precipitation, hydroclimatic intensity index (HY-INT), and wet and dry extreme indices are analyzed to identify the robust behavior of hydroclimatic change in response to enhanced emission scenarios using high-resolution (12.5 km) and long-term (1981–2100) daily precipitation. Ensemble projections exhibit increased hydroclimatic intensity across the entire domain and under both the RCP scenarios. However, a geographical pattern with predominantly intensified HY-INT does not fully emerge in the mean precipitation change because HY-INT is tied to the changes in the precipitation characteristics rather than to those in the precipitation amount. All projections show an enhancement of high intensity precipitation and a reduction of weak intensity precipitation, which lead to a possible shift in hydroclimatic regime prone to an increase of both wet and dry extremes. In general, projections forced by the RCP8.5 scenario tend to produce a much stronger response than do those by the RCP4.5 scenario. However, the temperature increase under the RCP4.5 scenario is sufficiently large to induce significant changes in hydroclimatic intensity, despite the relatively uncertain change in mean precipitation. Likewise, the forced responses of HY-INT and the two extreme indices are more robust than that of mean precipitation, in terms of the statistical significance and model agreement.

  相似文献   

8.
Climate change is expected to increase temperatures globally, and consequently more frequent, longer, and hotter heat waves are likely to occur. Ambiguity in defining heat waves appropriately makes it difficult to compare changes in heat wave events over time. This study provides a quantitative definition of a heat wave and makes probabilistic heat wave projections for the Korean Peninsula under two global warming scenarios. Changes to heat waves under global warming are investigated using the representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) experiments from 30 coupled models participating in phase five of the Coupled Model Inter-comparison Project. Probabilistic climate projections from multi-model ensembles have been constructed using both simple and weighted averaging. Results from both methods are similar and show that heat waves will be more intense, frequent, and longer lasting. These trends are more apparent under the RCP8.5 scenario as compared to the RCP4.5 scenario. Under the RCP8.5 scenario, typical heat waves are projected to become stronger than any heat wave experienced in the recent measurement record. Furthermore, under this scenario, it cannot be ruled out that Korea will experience heat wave conditions spanning almost an entire summer before the end of the 21st century.  相似文献   

9.
Multi-variable error correction of regional climate models   总被引：2，自引：1，他引：1  
Climate change impact research needs regional climate scenarios of multiple meteorological variables. Those variables are available from regional climate models (RCMs), but affected by considerable biases. We evaluate the application of an empirical-statistical error correction method, quantile mapping (QM), for a small ensemble of RCMs and six meteorological variables. Annual and monthly biases are reduced to close to zero by QM for all variables in most cases. Exceptions are found, if non-stationarity of the model’s error characteristics occur. Even in the worst cases of non-stationarity, QM clearly improves the biases of raw RCMs. In addition, QM successfully adjusts the distributions of the analysed variables. To approach the question whether time series and inter-variable relationships are still plausible after correction, we evaluate the root-mean-square error (RMSE), autocorrelation and inter-variable correlation. We found improvement or no clear effect in RMSE and autocorrelation, and no clear effect on the correlation between meteorological variables. These results demonstrate that QM retains the quality of the temporal structure in time series and the inter-variable dependencies of RCMs. It has to be emphasised that this cannot be interpreted as an improvement and that deficiencies of the RCMs in those features are retained as well. Our results give some indication for the performance of QM applied to future scenarios, since our evaluation relies on independent calibration and evaluation periods, which are affected by climate variability and change. The effect of non-stationarity, however, can be expected to be larger in far future. We demonstrate the retainment of the RCM’s temporal structure and inter-variable dependencies, and large improvements in biases. This qualifies QM as a valuable, though not perfect, method in the interface between climate models and climate change impact research. Nonetheless, in case of no correlation between re-analysis driven RCM and observation, one should consider that QM does not correct this correlation.  相似文献   

10.
Time of Emergence (ToE) is the time at which the signal of climate change emerges from the background noise of natural climate variability, and can provide useful information for climate change impacts and adaptations. This study examines future ToEs for daily maximum and minimum temperatures over the Northeast Asia using five Regional Climate Models (RCMs) simulations driven by single Global Climate Model (GCM) under two Representative Concentration Pathways (RCP) emission scenarios. Noise is defined based on the interannual variability during the present-day period (1981-2010) and warming signals in the future years (2021-2100) are compared against the noise in order to identify ToEs. Results show that ToEs of annual mean temperatures occur between 2030s and 2040s in RCMs, which essentially follow those of the driving GCM. This represents the dominant influence of GCM boundary forcing on RCM results in this region. ToEs of seasonal temperatures exhibit larger ranges from 2030s to 2090s. The seasonality of ToE is found to be determined majorly by noise amplitudes. The earliest ToE appears in autumn when the noise is smallest while the latest ToE occurs in winter when the noise is largest. The RCP4.5 scenario exhibits later emergence years than the RCP8.5 scenario by 5-35 years. The significant delay in ToEs by taking the lower emission scenario provides an important implication for climate change mitigation. Daily minimum temperatures tend to have earlier emergence than daily maximum temperature but with low confidence. It is also found that noise thresholds can strongly affect ToE years, i.e. larger noise threshold induces later emergence, indicating the importance of noise estimation in the ToE assessment.  相似文献   

11.
利用1981—2010年历史气象数据和2031—2060年（RCP2.6和RCP8.5）气候情景数据,根据橡胶寒害等级指标,结合插值分析、提取分析和地图代数等空间分析方法,研究在未来气候情景下我国橡胶树寒害事件的变化特征。结果表明：(1) RCP2.6和RCP8.5气候情景下2031—2060年我国橡胶种植适宜区基本呈现寒害发生降低的趋势,其中次适宜区（III）和局部可植区（IV）的降低幅度较为明显,有向高一等级适宜区转化的趋势。(2)我国橡胶树寒害中心的纬度,由1981—2010年的22.5°~23.5°N向北移动至2031—2060年RCP2.6情景下的24.0°~24.5°N和RCP8.5情景下的23.5°~24.0°N。(3) 2种气候情景下,2031—2060年我国海南、广西、广东、福建等植胶区橡胶树寒害发生概率（较基准时段1981—2010年）主要呈现降低趋势,云南植胶区在2种气候情景下有明显的差异,表现为RCP2.6情景下,轻度和特重寒害呈现降低趋势,中度和重度寒害呈现增加趋势;RCP8.5情景下,轻度和重度寒害呈现降低趋势,中度和特重寒害呈现增加趋势。(4)对比2种气候情景较基准时段的变化情况,RCP2.6情景对橡胶树轻度和特重寒害影响较大,RCP8.5情景对橡胶树中度和重度寒害影响较大。  相似文献   

12.
Realizing the error characteristics of regional climate models (RCMs) and the consequent limitations in their direct utilization in climate change impact research, this study analyzes a quantile-based empirical-statistical error correction method (quantile mapping, QM) for RCMs in the context of climate change. In particular the success of QM in mitigating systematic RCM errors, its ability to generate “new extremes” (values outside the calibration range), and its impact on the climate change signal (CCS) are investigated. In a cross-validation framework based on a RCM control simulation over Europe, QM reduces the bias of daily mean, minimum, and maximum temperature, precipitation amount, and derived indices of extremes by about one order of magnitude and strongly improves the shapes of the related frequency distributions. In addition, a simple extrapolation of the error correction function enables QM to reproduce “new extremes” without deterioration and mostly with improvement of the original RCM quality. QM only moderately modifies the CCS of the corrected parameters. The changes are related to trends in the scenarios and magnitude-dependent error characteristics. Additionally, QM has a large impact on CCSs of non-linearly derived indices of extremes, such as threshold indices.  相似文献   

13.
The current study examines the recently proposed “bias correction and stochastic analogues” (BCSA) statistical spatial downscaling technique and attempts to improve it by conditioning coarse resolution data when generating replicates. While the BCSA method reproduces the statistical features of the observed fine data, this existing model does not replicate the observed coarse spatial pattern, and subsequently, the cross-correlation between the observed coarse data and downscaled fine data with the model cannot be preserved. To address the dissimilarity between the BCSA downscaled data and observed fine data, a new statistical spatial downscaling method, “conditional stochastic simulation with bias correction” (BCCS), which employs the conditional multivariate distribution and principal component analysis, is proposed. Gridded observed climate data of mean daily precipitation (mm/day) covering a month at 1/8° for a fine resolution and at 1° for a coarse resolution over Florida for the current and future periods were used to verify and cross-validate the proposed technique. The observed coarse and fine data cover the 50-year period from 1950 to1999, and the future RCP4.5 and RCP8.5 climate scenarios cover the 100-year period from 2000 to 2099. The verification and cross-validation results show that the proposed BCCS downscaling method serves as an effective alternative means of downscaling monthly precipitation levels to assess climate change effects on hydrological variables. The RCP4.5 and RCP8.5 GCM scenarios are successfully downscaled.  相似文献   

14.
基于CMIP5逐日最低气温的模拟和预估数据,对中国区域性低温事件进行了研究。通过对中国区域性低温事件的历史模拟显示,模式集合的结果低估了中国区域性低温事件的变化趋势,但能够反映出与观测结果相同的减弱趋势,且比单个模式的结果更稳定,其空间分布与观测结果相似度也较高。在此基础上,采用模式集合方案对不同排放情景下（RCP2.6, RCP4.5, RCP8.5）的中国区域性低温事件进行了预估。结果显示,在RCP2.6排放情景下,中国区域性低温事件的减弱趋势较为缓和;在RCP4.5排放情景下,中国区域性低温事件呈现出显著的减弱趋势;在RCP8.5排放情景下,中国区域性低温事件的减弱趋势更明显。温室气体的排放可能主要影响中国区域性低温事件的强度和发生频次,对其空间分布影响较小。  相似文献   

15.
To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.  相似文献   

16.
A modified Thornthwaite Climate Classification is applied to a 32-member ensemble of CMIP5 GCMs in order to 1) evaluate model performance in the historical climate and 2) assess projected climate change at the end of the 21 s t century following two greenhouse gas representative concentration pathways (RCP4.5 and RCP8.5). This classification scheme differs from the well-known Köppen approach as it uses potential evapotranspiration for thermal conditions, a moisture index for moisture conditions, and has even intervals between climate classes. The multi-model ensemble (MME) reproduces the main spatial features of the global climate reasonably well, however, in many regions the climate types are too moist. Extreme climate types, such as those found in polar and desert regions, as well as the cool- and cold-wet types of eastern North America and the warm and cool-moist types found in the southern U.S., eastern South America, central Africa and Europe are reproduced best by the MME. In contrast, the cold-dry and cold-semiarid climate types characterizing much of the high northern latitudes and the warm-wet type found in parts of Indonesia and southeast Asia are poorly represented by the MME. Regionally, most models exhibit the same sign in moisture and thermal biases, varying only in magnitude. Substantial changes in climate types are projected in both the RCP4.5 and RCP8.5 scenarios. Area coverage of torrid climate types expands by 11 % and 19 % in the RCP4.5 and RCP8.5 projections, respectively. Furthermore, a large portion of these areas in the tropics will experience thermal conditions which exceed the range of historical values and fall into a novel super torrid climate class. The greatest growth in moisture types in climate zones is among those with dry climates (moisture index values < 0) with increased areas of more than 8 % projected by the RCP8.5 MME.  相似文献   

17.
Changes in climate are expected to lead to changes in the characteristics extreme rainfall frequency and intensity. In this study, we propose an integrated approach to explore potential changes in intensity-duration-frequency (IDF) relationships. The approach incorporates uncertainties due to both the short simulation periods of regional climate models (RCMs) and the differences in IDF curves derived from multiple RCMs in the North American Regional Climate Change Assessment Program (NARCCAP). The approach combines the likelihood of individual RCMs according to the goodness of fit between the extreme rainfall intensities from the RCMs’ historic runs and those from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data set and Bayesian model averaging (BMA) to assess uncertainty in IDF predictions. We also partition overall uncertainties into within-model uncertainty and among-model uncertainty. Results illustrate that among-model uncertainty is the dominant source of the overall uncertainty in simulating extreme rainfall for multiple locations in the U.S., pointing to the difficulty of predicting future climate, especially extreme rainfall regimes. For all locations a more intense extreme rainfall occurs in future climate; however the rate of increase varies among locations.  相似文献   

18.
This paper proposes a method for multi-model ensemble forecasting based on Bayesian model averaging (BMA), aiming to improve the accuracy of tropical cyclone (TC) intensity forecasts, especially forecasts of minimum surface pressure at the cyclone center (Pmin). The multi-model ensemble comprises three operational forecast models: the Global Forecast System (GFS) of NCEP, the Hurricane Weather Research and Forecasting (HWRF) models of NCEP, and the Integrated Forecasting System (IFS) of ECMWF. The mean of a predictive distribution is taken as the BMA forecast. In this investigation, bias correction of the minimum surface pressure was applied at each forecast lead time, and the distribution (or probability density function, PDF) of Pmin was used and transformed. Based on summer season forecasts for three years, we found that the intensity errors in TC forecast from the three models varied significantly. The HWRF had a much smaller intensity error for short lead-time forecasts. To demonstrate the proposed methodology, cross validation was implemented to ensure more efficient use of the sample data and more reliable testing. Comparative analysis shows that BMA for this three-model ensemble, after bias correction and distribution transformation, provided more accurate forecasts than did the best of the ensemble members (HWRF), with a 5%–7% decrease in root-mean-square error on average. BMA also outperformed the multi-model ensemble, and it produced “predictive variance” that represented the forecast uncertainty of the member models. In a word, the BMA method used in the multi-model ensemble forecasting was successful in TC intensity forecasts, and it has the potential to be applied to routine operational forecasting.  相似文献   

19.
Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1?scale over China from 1990 to 2100 and investigated the temporal evolution of K o¨ppen–Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions(7%–8% of China's land area) by 2010, including rapid replacement of mixed forest(Dwb) by deciduous forest(Dwa) over Northeast China, strong shrinkage of alpine climate type(ET) on the Tibetan Plateau, weak northward expansion of subtropical winterdry climate(Cwa) over Southeast China, and contraction of oceanic climate(Cwb) in Southwest China. Under all future RCP(Representative Concentration Pathway) scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010–30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario(RCP8.5), sub-polar continental winter dry climate over Northeast China would disappear by 2040–50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9%and 50.8% of China's land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China's ecoregions in future decades.  相似文献   

20.
Based on a 10-year simulation of six Regional Climate Models(RCMs) in phase II of the Regional Climate Model Inter-Comparison Project(RMIP) for Asia,the multivariate statistical method of common principal components(CPCs) is used to analyze and compare the spatiotemporal characteristics of temperature and precipitation simulated by multi-RCMs over China,including the mean climate states and their seasonal transition,the spatial distribution of interannual variability,and the interannual variation.CPC is an effective statistical tool for analyzing the results of different models.Compared with traditional statistical methods,CPC analyses provide a more complete statistical picture for observation and simulation results.The results of CPC analyses show that the climatological means and the characteristics of seasonal transition over China can be accurately simulated by RCMs.However,large biases exist in the interannual variation in certain years or for individual models.  相似文献   

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