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1.
Many researchers use outputs from large-scale global circulation models of the atmosphere to assess hydrological and other impacts associated with climate change. However, these models cannot capture all climate variations since the physical processes are imperfectly understood and are poorly represented at smaller regional scales. This paper statistically compares model outputs from the global circulation model of the Geophysical Fluid Dynamics Laboratory to historical data for the United States' Laurentian Great Lakes and for the Emba and Ural River basins in the Commonwealth of Independent States (C.I.S.). We use maximum entropy spectral analysis to compare model and data time series, allowing us to both assess statistical predictabilities and to describe the time series in both time and frequency domains. This comparison initiates assessments of the model's representation of the real world and suggests areas of model improvement.  相似文献   

2.
Quantification of spatially and temporally resolved water flows and water storage variations for all land areas of the globe is required to assess water resources, water scarcity and flood hazards, and to understand the Earth system. This quantification is done with the help of global hydrological models (GHMs). What are the challenges and prospects in the development and application of GHMs? Seven important challenges are presented. (1) Data scarcity makes quantification of human water use difficult even though significant progress has been achieved in the last decade. (2) Uncertainty of meteorological input data strongly affects model outputs. (3) The reaction of vegetation to changing climate and CO2 concentrations is uncertain and not taken into account in most GHMs that serve to estimate climate change impacts. (4) Reasons for discrepant responses of GHMs to changing climate have yet to be identified. (5) More accurate estimates of monthly time series of water availability and use are needed to provide good indicators of water scarcity. (6) Integration of gradient-based groundwater modelling into GHMs is necessary for a better simulation of groundwater–surface water interactions and capillary rise. (7) Detection and attribution of human interference with freshwater systems by using GHMs are constrained by data of insufficient quality but also GHM uncertainty itself. Regarding prospects for progress, we propose to decrease the uncertainty of GHM output by making better use of in situ and remotely sensed observations of output variables such as river discharge or total water storage variations by multi-criteria validation, calibration or data assimilation. Finally, we present an initiative that works towards the vision of hyperresolution global hydrological modelling where GHM outputs would be provided at a 1-km resolution with reasonable accuracy.  相似文献   

3.
Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.  相似文献   

4.
This work aims to answer if post-processing climate model outputs will improve the accuracy of climate change impact assessment and adaptation evaluation. To achieve this aim, the daily outputs of CSIRO Conformal Cubic Atmospheric Model for periods 1960–1979, 1980–1999 and 2046–2065, and observed daily climate data (1960–1979, 1980–1999) were used by a stochastic weather generator, the Long Ashton Research Station-Weather Generator to construct long time series of local climate scenarios (CSs). The direct outputs of climate models (DOCM) and CSs were then fed into the Agricultural Production System sIMulator—Wheat model to calculate seasonal climate variables and production components at three locations spanning northern, central and southern wheat production areas in New South Wales (NSW), Australia. This study firstly compared the differences in climate variables and production components derived from DOCM and CSs against those from observed climate for period 1960–1979. The impact difference arising from the use of DOCM and CSs for the future period 2046–2065 was then quantified. Simulation results show that (1) both the median/mean and distribution/variation of climate variables and production components associated with CSs were closer to those derived from observed climate when compared to those from DOCM in most of the cases (median/mean, distribution/variation, climate variables, production components and locations); (2) the difference in the mean and distribution of climate variables and production components derived from DOCM and observed climate was significant in most of the cases; (3) longer dry spells in both winter and spring were found from CSs across the three locations considered in comparison with those from DOCM; (4) the median growing season (GS) rainfall total, GS average maximum temperature, GS average solar radiation, GS length and final wheat yield were lower from DOCM than those from CSs and vice versa for GS rainfall frequency and GS average minimum temperature in 2055; (5) the mean and distribution of these climate variables and production components arising from the use of DOCM and CSs are significantly different in most of the cases. This implied that using the direct outputs of spatially downscaled general circulation model without implementing post-processing procedures may lead to significant errors in projected climate impact and the identified effort in tackling climate change risk. It is therefore highly recommended that post-processing procedures be used in developing robust CSs for climate change impact assessment and adaptation evaluation.  相似文献   

5.
Climate change is expected to alter rainfall regimes across most parts of the world. The implications of this could be more severe in arid environments where rainfall is limited and highly variable in space and time. However, lack of good quality data, of sufficient record length and spatial coverage usually restricts model development and performance geared towards assessing the effects of climate change in these areas. This paper presents an analysis of rainfall and climate data in order to determine the time of change in rainfall series and identify possible correlations between rainfall and temperature. In addition, the paper aims to make predictions of future rainfall patterns in Botswana. This is achieved by using historical rainfall and climate data from rainfall stations spread across Botswana from 1965 to 2008. In addition, large scale reanalysis data from NCAR/NCEP and El Nino Southern Oscillation (ENSO) data were used to augment the limited observed spatial climate data series when developing a rainfall model. Temperature and ENSO indices have been used to predict rainfall regimes for the present climate. Based on these, the effects of climate change were quantified using a stochastic generalised linear rainfall model (GLM) driven by outputs of global climate models (GCMs). The results indicate that temperature is a significant rainfall predictor in Botswana compared to ENSO indices.  相似文献   

6.
The aim of this study is to estimate likely changes in flood indices under a future climate and to assess the uncertainty in these estimates for selected catchments in Poland. Precipitation and temperature time series from climate simulations from the EURO-CORDEX initiative for the periods 1971–2000, 2021–2050 and 2071–2100 following the RCP4.5 and RCP8.5 emission scenarios have been used to produce hydrological simulations based on the HBV hydrological model. As the climate model outputs for Poland are highly biased, post processing in the form of bias correction was first performed so that the climate time series could be applied in hydrological simulations at a catchment-scale. The results indicate that bias correction significantly improves flow simulations and estimated flood indices based on comparisons with simulations from observed climate data for the control period. The estimated changes in the mean annual flood and in flood quantiles under a future climate indicate a large spread in the estimates both within and between the catchments. An ANOVA analysis was used to assess the relative contributions of the 2 emission scenarios, the 7 climate models and the 4 bias correction methods to the total spread in the projected changes in extreme river flow indices for each catchment. The analysis indicates that the differences between climate models generally make the largest contribution to the spread in the ensemble of the three factors considered. The results for bias corrected data show small differences between the four bias correction methods considered, and, in contrast with the results for uncorrected simulations, project increases in flood indices for most catchments under a future climate.  相似文献   

7.
This paper presents the results of an investigation into the problems associated with using downscaled meteorological data for hydrological simulations of climate scenarios. The influence of both the hydrological models and the meteorological inputs driving these models on climate scenario simulation studies are investigated. A regression‐based statistical tool (SDSM) is used to downscale the daily precipitation and temperature data based on climate predictors derived from the Canadian global climate model (CGCM1), and two types of hydrological model, namely the physically based watershed model WatFlood and the lumped‐conceptual modelling system HBV‐96, are used to simulate the flow regimes in the major rivers of the Saguenay watershed in Quebec. The models are validated with meteorological inputs from both the historical records and the statistically downscaled outputs. Although the two hydrological models demonstrated satisfactory performances in simulating stream flows in most of the rivers when provided with historic precipitation and temperature records, both performed less well and responded differently when provided with downscaled precipitation and temperature data. By demonstrating the problems in accurately simulating river flows based on downscaled data for the current climate, we discuss the difficulties associated with downscaling and hydrological models used in estimating the possible hydrological impact of climate change scenarios. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

8.
General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.  相似文献   

9.
The Coupled Model Inter-comparison Project Phase 5(CMIP5)contains a group of state-of-the-art climate models and represents the highest level of climate simulation thus far.However,these models significantly overestimated global mean surface temperature(GMST)during 2006-2014.Based on the ensemble empirical mode decomposition(EEMD)method,the long term change of the observed GMST time series of HadCRUT4 records during 1850-2014 was analyzed,then the simulated GMST by 33 CMIP5 climate models was assessed.The possible reason that climate models failed to project the recent global warming hiatus was revealed.Results show that during 1850-2014 the GMST on a centennial timescale rose with fluctuation,dominated by the secular trend and the multi-decadal variability(MDV).The secular trend was relatively steady beginning in the early 20th century,with an average warming rate of 0.0883℃/decade over the last 50 years.While the MDV(with a~65-year cycle)showed2.5 multi-decadal waves during 1850-2014,which deepened and steepened with time,the alarming warming over the last quarter of the 20th century was a result of the concurrence of the secular warming trend and the warming phase of the MDV,both of which accounted one third of the temperature increase during 1975-1998.Recently the slowdown of global warming emerged as the MDV approached its third peak,leading to a reduction in the warming rate.A comparative analysis between the GMST time series derived from HadCRUT4 records and 33 CMIP5 model outputs reveals that the GMSTs during the historical simulation period of 1850-2005 can be reproduced well by models,especially on the accelerated global warming over the last quarter of 20th century.However,the projected GMSTs and their linear trends during 2006-2014 under the RCP4.5 scenario were significantly higher than observed.This is because the CMIP5 models confused the MDV with secular trend underlying the GMST time series,which results in a fast secular trend and an improper MDV with irregular phases and small amplitudes.This implies that the role of atmospheric CO_2 in global warming may be overestimated,while the MDV which is an interior oscillation of the climate system may be underestimated,which should be related to insufficient understanding of key climatic internal dynamic processes.Our study puts forward an important criterion for the new generation of climate models:they should be able to simulate both the secular trend and the MDV of GMST.  相似文献   

10.
The Köppen climate classification was applied to the observed gridded climatological sets and the outputs of four general circulation models (GCMs) over the continents of the Earth. All data had been acquired via the Data Distribution Centre established by the Intergovernmental Panel on Climate Change. The ability of the GCMs to simulate the Köppen climate zones identified in the real data was explored and possible future (global warming) changes in the climate types' distribution for each GCM were assessed. Differences in the area distributions derived from the GCMs' recent climate simulations give evidence about uncertainties generally involved in climate models. As to the global warming simulations, all GCM projections of warming climate (horizon 2050) show that the zones representing tropical rain climates and dry climates become larger, and the zones identified with boreal forest and snow climates together with the polar climates are smaller.  相似文献   

11.
鄱阳湖流域过去1000 a径流模拟以及对气候变化响应研究   总被引：1，自引：1，他引：0  
张小琳  李云良  于革  张奇 《湖泊科学》2016,28(4):887-898
为研究过去千年尺度径流变化及其对气候变化的响应,以长江中游鄱阳湖流域为研究区,运用气候模式CCSM4和ECHAM5模拟过去1000 a气候数据,空间降尺度后驱动水文模型模拟了鄱阳湖流域过去近千年流域径流序列.利用快速傅里叶变换、小波分析等手段,分析流域极端径流变化特征、周期和该流域旱涝事件发生频率.结果表明:2种气候模式均能反映出中世纪暖期及小冰期阶段的干湿交替变化,且小冰期内中干旱状态维持时间较长;径流的丰枯变化与降水量变化具有较好的对应关系.CCSM4和ECHAM5模式下发生旱涝灾害与极大极小降水事件发生频率基本相同,径流丰枯变化与降水变化周期相近,均具有30 a左右的主周期,10~15、7 a左右的子周期.小波系数模平方图中30 a左右显著的能量信号揭示了该周期与北太平洋气候的主要环流机制的太平洋年代际振荡周期相近,因此,大气环流涛动是造成气候-水文变化的主要原因.研究结果拓展了基于近代60 a观测记录的流域水文变化的认识,探讨了千年时间长度下流域干湿变化特征和水文对气候响应的动力机制,有助于全面系统认识长江中游在全球气候暖化背景下旱涝极端水文事件的发生机制与变化规律.  相似文献   

12.
Global atmosphere-ocean general circulation models are the tool by which projections for climate changes due to radiative forcing scenarios have been produced. Further, regional atmospheric downscaling of the global models may be applied in order to evaluate the details in, e.g., temperature and precipitation patterns. Similarly, detailed regional information is needed in order to assess the implications of future climate change for the marine ecosystems. However, regional results for climate change in the ocean are sparse. We present the results for the circulation and hydrography of the Barents Sea from the ocean component of two global models and from a corresponding pair of regional model configurations. The global models used are the GISS AOM and the NCAR CCSM3. The ROMS ocean model is used for the regional downscaling of these results (ROMS-G and ROMS-N configurations, respectively). This investigation was undertaken in order to shed light on two questions that are essential in the context of regional ocean projections: (1) How should a regional model be set up in order to take advantage of the results from global projections; (2) What limits to quality in the results of regional models are imposed by the quality of global models? We approached the first question by initializing the ocean model in the control simulation by a realistic ocean analysis and specifying air-sea fluxes according to the results from the global models. For the projection simulation, the global models’ oceanic anomalies from their control simulation results were added upon initialization. Regarding the second question, the present set of simulations includes regional downscalings of the present-day climate as well as projected climate change. Thus, we study separately how downscaling changes the results in the control climate case, and how scenario results are changed. For the present-day climate, we find that downscaling reduces the differences in the Barents Sea between the original global models. Furthermore, the downscaled results are closer to observations. On the other hand, the downscaled results from the scenario simulations are significantly different: while the heat transport into the Barents Sea and the salinity distribution change modestly from control to scenario with ROMS-G, in ROMS-N the heat transport is much larger in the scenario simulation, and the water masses become much less saline. The lack of robustness in the results from the scenario simulations leads us to conclude that the results for the regional oceanic response to changes in the radiative forcing depend on the choice of AOGCM and is not settled. Consequently, the effect of climate change on the marine ecosystem of the Barents Sea is anything but certain.  相似文献   

13.
Coupled atmosphere–ocean general circulation models are key tools to investigate climate dynamics and the climatic response to external forcings, to predict climate evolution and to generate future climate projections. Current general circulation models are, however, undisputedly affected by substantial systematic errors in their outputs compared to observations. The assessment of these so-called biases, both individually and collectively, is crucial for the models’ evaluation prior to their predictive use. We present a Bayesian hierarchical model for a unified assessment of spatially referenced climate model biases in a multi-model framework. A key feature of our approach is that the model quantifies an overall common bias that is obtained by synthesizing bias across the different climate models in the ensemble, further determining the contribution of each model to the overall bias. Moreover, we determine model-specific individual bias components by characterizing them as non-stationary spatial fields. The approach is illustrated based on the case of near-surface air temperature bias in the tropical Atlantic and bordering regions from a multi-model ensemble of historical simulations from the fifth phase of the Coupled Model Intercomparison Project. The results demonstrate the improved quantification of the bias and interpretative advantages allowed by the posterior distributions derived from the proposed Bayesian hierarchical framework, whose generality favors its broader application within climate model assessment.  相似文献   

14.
Three-dimensional general circulation models (GCMs) are 'state-of-the-art' tools for projecting possible changes in climate. Scenarios constructed for the Czech Republic are based on daily outputs of the ECHAM-GCM in the central European region. Essential findings, derived from validating, procedures are summarized and changes in variables between the control and perturbed experiments are examined. The resulting findings have been used in selecting the most proper methods of generating climate change projections for assessing possible hydrological and agricultural impacts of climate change in selected exposure units. The following weather variables have been studied: Daily extreme temperatures, daily mean temperature, daily sum of global solar radiation, and daily precipitation amounts. Due to some discrepancies revealed, the temperature series for changed climate conditions (2×CO 2 ) have been created with the help of temperature differences between the control and perturbed runs, and the precipitation series have been derived from an incremental scenario based on an intercomparison of the GCMs' precipitation performance in the region. Solar radiation simulated by the ECHAM was not available and, therefore, it was generated using regression techniques relating monthly means of daily extreme temperatures and global radiation sums. The scenarios published in the paper consist of monthly means of all temperatures, their standard deviations, and monthly means of solar radiation and precipitation amounts. Daily weather series, the necessary input to impact models, are created (i) by the additive or multiplicative modification of observed weather daily series or (ii) by generating synthetic time series with the help of a weather generator whose parameters have been modified in accord with the suggested climate change scenarios.  相似文献   

15.
A joint model is proposed for analyzing and predicting the occurrence of extreme heat events in two temperature series, these being daily maximum and minimum temperatures. Extreme heat events are defined using a threshold approach and the suggested model, a non-homogeneous common Poisson shock process, accounts for the mutual dependence between the extreme events in the two series. This model is used to study the time evolution of the occurrence of extreme events and its relationship with temperature predictors. A wide range of tools for validating the model is provided, including influence analysis. The main application of this model is to obtain medium-term local projections of the occurrence of extreme heat events in a climate change scenario. Future temperature trajectories from general circulation models, conveniently downscaled, are used as predictors of the model. These trajectories show a generalized increase in temperatures, which may lead to extrapolation errors when the model is used to obtain projections. Various solutions for dealing with this problem are suggested. The results of the fitted model for the temperature series in Barcelona in 1951–2005 and future projections of extreme heat events for the period 2031–2060 are discussed, using three global circulation model trajectories under the SRES A1B scenario.  相似文献   

16.
Nowadays Regional Climate Models (RCMs) are increasingly used for downscaling of information from the coarse resolution of global climate models (GCMs) and they represent a more and more popular tool for assessment of future climate changes and their impacts at regional scales. In spite of continual progress of RCMs, their outputs still suffer from many uncertainties and biases. Therefore, it is necessary to assess their ability to simulate observed climate characteristics and uncertainties in their outputs before they are applied in subsequent studies. In the present study, the assessment of RCM performance in simulating climate in the reference period of 1961–1990 over the area of Czech Republic is presented. Furthermore, we focused on the intercomparison of the models’ results, mainly on the comparison of the Czech model ALADIN-Climate/CZ with outputs of other RCMs. Simulation of ALADIN-Climate/CZ in 25-km horizontal resolution, and thirteen RCM simulations from the ENSEMBLES project were assessed. Attention was paid especially to comparison of simulated and observed spatial and temporal variability of several climatic variables. The monthly and seasonal values of surface air temperature, precipitation totals and relative humidity were examined for evaluation of temporal variability and 30-year seasonal and monthly values with respect to spatial variability. Climate model performance was evaluated in several ways, namely by boxplots, maps of variability characteristics, skill scores based on mean square error and Taylor diagrams. Model errors detected by model evaluation depend on many factors (e.g. considered variables and their characteristics, area of analysis, time scale of interest and the method of assessment). On the basis of incorporated performance criteria model ALADIN-Climate/CZ belonged to a better group of RCMs in most cases. However, it was definitely the worst in simulating spring monthly means of air temperature and relative humidity in all seasons.  相似文献   

17.
Hydrological response to expected future changes in land use and climate in the Samin catchment (278 km2) in Java, Indonesia, was simulated using the Soil and Water Assessment Tool model. We analysed changes between the baseline period 1983–2005 and the future period 2030–2050 under both land-use change and climate change. We used the outputs of a bias-corrected regional climate model and six global climate models to include climate model uncertainty. The results show that land-use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual streamflow and surface runoff. The findings of this study will be useful for water resource managers to mitigate future risks associated with land-use and climate changes in the study catchment.  相似文献   

18.
Climatic and hydrological changes will likely be intensified in the Upper Blue Nile (UBN) basin by the effects of global warming. The extent of such effects for representative concentration pathways (RCP) climate scenarios is unknown. We evaluated projected changes in rainfall and evapotranspiration and related impacts on water availability in the UBN under the RCP4.5 scenario. We used dynamically downscaled outputs from six global circulation models (GCMs) with unprecedented spatial resolution for the UBN. Systematic errors of these outputs were corrected and followed by runoff modelling by the HBV (Hydrologiska ByrånsVattenbalansavdelning) model, which was successfully validated for 17 catchments. Results show that the UBN annual rainfall amount will change by ?2.8 to 2.7% with a likely increase in annual potential evapotranspiration (in 2041–2070) for the RCP4.5 scenario. These changes are season dependent and will result in a likely decline in streamflow and an increase in soil moisture deficit in the basin.  相似文献   

19.
Initial findings from high-latitude ice-cores implied a relatively unvarying Holocene climate, in contrast to the major climate swings in the preceding late-Pleistocene. However, several climate archives from low latitudes imply a less than equable Holocene climate, as do recent studies on peat bogs in mainland north-west Europe, which indicate an abrupt climate cooling 2800 years ago, with parallels claimed in a range of climate archives elsewhere. A hypothesis that this claimed climate shift was global, and caused by reduced solar activity, has recently been disputed. Until now, no directly comparable data were available from the southern hemisphere to help resolve the dispute. Building on investigations of the vegetation history of an extensive mire in the Valle de Andorra, Tierra del Fuego, we took a further peat core from the bog to generate a high-resolution climate history through the use of determination of peat humification and quantitative leaf-count plant macrofossil analysis. Here, we present the new proxy-climate data from the bog in South America. The data are directly comparable with those in Europe, as they were produced using identical laboratory methods. They show that there was a major climate perturbation at the same time as in northwest European bogs. Its timing, nature and apparent global synchronicity lend support to the notion of solar forcing of past climate change, amplified by oceanic circulation. This finding of a similar response simultaneously in both hemispheres may help validate and improve global climate models. That reduced solar activity might cause a global climatic change suggests that attention be paid also to consideration of any global climate response to increases in solar activity. This has implications for interpreting the relative contribution of climate drivers of recent ‘global warming’.  相似文献   

20.
A regional numerical physico-mathematical model of river runoff formation is used to study the possibility to assess long-term variations of water regime characteristics in the Amur R. in the XXI century. Two methods were used to specify climate projections as boundary conditions in the hydrological model: (1) based on the results of calculations with an ensemble of global climate models of CMI5 project, (2) based on data obtained by linear transformation of series of actual meteorological observations with the use of normal annual climate parameters calculated by climate models. The results of numerical experiments were used to analyze the sensitivity of the anomaly of Amur normal annual runoff to changes in the climate normals of air temperature and precipitation. The anomalies of normal annual runoff were shown to respond similarly (within the accuracy of sensitivity coefficient estimates) to changes in the appropriate climate normals, whatever the way of specifying climate projections.  相似文献   

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