Differences and sensitivities in potential hydrologic impact of climate change to regional-scale Athabasca and Fraser River basins of the leeward and windward sides of the Canadian Rocky Mountains respectively

Sensitivities to the potential impact of Climate Change on the water resources of the Athabasca River Basin (ARB) and Fraser River Basin (FRB) were investigated. The Special Report on Emissions Scenarios (SRES) of IPCC projected by seven general circulation models (GCM), namely, Japan’s CCSRNIES, Canada’s CGCM2, Australia’s CSIROMk2b, Germany’s ECHAM4, the USA’s GFDLR30, the UK’s HadCM3, and the USA’s NCARPCM, driven under four SRES climate scenarios (A1FI, A2, B1, and B2) over three 30-year time periods (2010–2039, 2040–2069, 2070–2100) were used in these studies. The change fields over these three 30-year time periods are assessed with respect to the 1961–1990, 30-year climate normal and based on the 1961–1990 European Community Mid-Weather Forecast (ECMWF) re-analysis data (ERA-40), which were adjusted with respect to the higher resolution GEM forecast archive of Environment Canada, and used to drive the Modified ISBA (MISBA) of Kerkhoven and Gan (Adv Water Resour 29(6):808–826, 2006). In the ARB, the shortened snowfall season and increased sublimation together lead to a decline in the spring snowpack, and mean annual flows are expected to decline with the runoff coefficient dropping by about 8% per °C rise in temperature. Although the wettest scenarios predict mild increases in annual runoff in the first half of the century, all GCM and emission combinations predict large declines by the end of the twenty-first century with an average change in the annual runoff, mean maximum annual flow and mean minimum annual flow of −21%, −4.4%, and −41%, respectively. The climate scenarios in the FRB present a less clear picture of streamflows in the twenty-first century. All 18 GCM projections suggest mean annual flows in the FRB should change by ±10% with eight projections suggesting increases and 10 projecting decreases in the mean annual flow. This stark contrast with the ARB results is due to the FRB’s much milder climate. Therefore under SRES scenarios, much of the FRB is projected to become warmer than 0°C for most of the calendar year, resulting in a decline in FRB’s characteristic snow fed annual hydrograph response, which also results in a large decline in the average maximum flow rate. Generalized equations relating mean annual runoff, mean annual minimum flows, and mean annual maximum flows to changes in rainfall, snowfall, winter temperature, and summer temperature show that flow rates in both basins are more sensitive to changes in winter than summer temperature.     

Baltic Sea climate in the late twenty-first century: a dynamical downscaling approach using two global models and two emission scenarios

A regional ocean circulation model was used to project Baltic Sea climate at the end of the twenty-first century. A set of four scenario simulations was performed utilizing two global models and two forcing scenarios. To reduce model biases and to spin up future salinity the so-called Δ-change approach was applied. Using a regional coupled atmosphere–ocean model 30-year climatological monthly mean changes of atmospheric surface data and river discharge into the Baltic Sea were calculated from previously conducted time slice experiments. These changes were added to reconstructed atmospheric surface fields and runoff for the period 1903–1998. The total freshwater supply (runoff and net precipitation) is projected to increase between 0 and 21%. Due to increased westerlies in winter the annual mean wind speed will be between 2 and 13% larger compared to present climate. Both changes will cause a reduction of the average salinity of the Baltic Sea between 8 and 50%. Although salinity in the entire Baltic might be significantly lower at the end of the twenty-first century, deep water ventilation will very likely only slightly change. The largest change is projected for the secondary maximum of sea water age within the halocline. Further, the average temperature will increase between 1.9 and 3.2°C. The temperature response to atmospheric changes lags several months. Future annual maximum sea ice extent will decrease between 46 and 77% in accordance to earlier studies. However, in contrast to earlier results in the warmest scenario simulation one ice-free winter out of 96 seasons was found. Although wind speed changes are uniform, extreme sea levels may increase more than the mean sea level. In two out of four projections significant changes of 100-year surge heights were found.     

Testing a GCM land surface scheme against catchment-scale runoff data

A GCM land surface scheme was used, in off-line mode, to simulate the runoff, latent and sensible heat fluxes for two distinct Australian catchments using observed atmospheric forcing. The tropical Jardine River catchment is 2500 km² and has an annual rainfall of 1700 mm y^–1 while the Canning River catchment is 540 km², has a Mediterranean climate (annual rainfall of 800 mm y^–1) and is ephemeral for half the year. It was found that the standard version of a land surface scheme developed for a GCM, and initialised as for incorporation into a GCM, simulated similar latent and sensible heat fluxes compared to a basin-scale hydrological model (MODHYDROLOG) which was calibrated for each catchment. However, the standard version of the land surface scheme grossly overestimated the observed peak runoff in the wet Jardine River catchment at the expense of runoff later in the season. Increasing the soil water storage permitted the land surface scheme to simulate observed runoff quite well, but led to a different simulation of latent and sensible heat compared to MODHYDROLOG. It is concluded that this 2-layer land surface scheme was unable to simulate both catchments realistically. The land surface scheme was then extended to a three-layer model. In terms of runoff, the resulting control simulations with soil depths chosen as for the GCM were better than the best simulations obtained with the two-layer model. The three-layer model simulated similar latent and sensible heat for both catchments compared to MODHYDROLOG. Unfortunately, for the ephemeral Canning River catchment, the land surface scheme was unable to time the observed runoff peak correctly. A tentative conclusion would be that this GCM land surface scheme may be able to simulate the present day state of some larger and wetter catchments but not catchments with peaky hydrographs and zero flows for part of the year. This conclusion requires examination with a range of GCM land surface schemes against a range of catchments. Received: 9 June 1995 / Accepted: 4 April 1996     

The role of terrestrial snow cover in the climate system

Snow cover is known to exert a strong influence on climate, but quantifying its impact is difficult. This study investigates the global impact of terrestrial snow cover through a pair of GCM simulations run with prognostic snow cover and with all snow cover on land eliminated (NOSNOWCOVER). In this experiment all snowfall over land was converted into its liquid–water equivalent upon reaching the surface. Compared with the control run, NOSNOWCOVER produces mean-annual surface air temperatures up to 5 K higher over northern North America and Eurasia and 8–10 K greater during winter. The globally averaged warming of 0.8 K is one-third as large as the model’s response to 2 × CO₂ forcing. The pronounced surface heating propagates throughout the troposphere, causing changes in surface and upper-air circulation patterns. Despite the large atmospheric warming, the absence of an insulating snow pack causes soil temperatures in NOSNOWCOVER to fall throughout northern Asia and Canada, including extreme wintertime cooling of over 20 K in Siberia and a 70% increase in permafrost area. The absence of snow melt water also affects extratropical surface hydrology, causing significantly drier upper-layer soils and dramatic changes in the annual cycle of runoff. Removing snow cover also drastically affects extreme weather. Extreme cold-air outbreaks (CAOs)—defined relative to the control climatology—essentially disappear in NOSNOWCOVER. The loss of CAOs appears to stem from both the local effects of eliminating snow cover in mid-latitudes and a remote effect over source regions in the Arctic, where −40°C air masses are no longer able to form.     

Potential impact of climate change on the water availability of South Saskatchewan River Basin

The potential hydrologic impact of climatic change on three sub-basins of the South Saskatchewan River Basin (SSRB) within Alberta, namely, Oldman, Bow and Red Deer River basins was investigated using the Modified Interactions Soil-Biosphere-Atmosphere (MISBA) land surface scheme of Kerkhoven and Gan (Advances in Water Resources 29:808–826 2006). The European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40) climate data, Digital Elevation Model of the National Water Research Institute, land cover data and a priori soil parameters from the Ecoclimap global data set were used to drive MISBA to simulate the runoff of SSRB. Four SRES scenarios (A21, A1FI, B21 and B11) of four General Circulation Models (CCSRNIES, CGCM2, ECHAM4 and HadCM3) of IPCC were used to adjust climate data of the 1961–1990 base period (climate normal) to study the effect of climate change on SSRB over three 30-year time periods (2010–2039, 2040–2069, 2070–2099). The model results of MISBA forced under various climate change projections of the four GCMs with respect to the 1961–1990 normal show that SSRB is expected to experience a decrease in future streamflow and snow water equivalent, and an earlier onset of spring runoff despite of projected increasing trends in precipitation over the 21st century. Apparently the projected increase in evaporation loss due to a warmer climate over the 21st century will offset the projected precipitation increase, leading to an overall decreasing trend in the basin runoff of SSRB. Finally, a Gamma probability distribution function was fitted to the mean annual maximum flow and mean annual mean flow data simulated for the Oldman, Bow and Red Deer River Basins by MISBA to statistically quantify the possible range of uncertainties associated with SRES climate scenarios projected by the four GCMs selected for this study.     

Improved regional scale processes reflected in projected hydrological changes over large European catchments

For the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC), the recent version of the coupled atmosphere/ocean general circulation model (GCM) of the Max Planck Institute for Meteorology has been used to conduct an ensemble of transient climate simulations These simulations comprise three control simulations for the past century covering the period 1860–2000, and nine simulations for the future climate (2001–2100) using greenhouse gas (GHG) and aerosol concentrations according to the three IPCC scenarios B1, A1B and A2. For each scenario three simulations were performed. The global simulations were dynamically downscaled over Europe using the regional climate model (RCM) REMO at 0.44° horizontal resolution (about 50 km), whereas the physics packages of the GCM and RCM largely agree. The regional simulations comprise the three control simulations (1950–2000), the three A1B simulations and one simulation for B1 as well as for A2 (2001–2100). In our study we concentrate on the climate change signals in the hydrological cycle and the 2 m temperature by comparing the mean projected climate at the end of the twenty-first century (2071–2100) to a control period representing current climate (1961–1990). The robustness of the climate change signal projected by the GCM and RCM is analysed focussing on the large European catchments of Baltic Sea (land only), Danube and Rhine. In this respect, a robust climate change signal designates a projected change that sticks out of the noise of natural climate variability. Catchments and seasons are identified where the climate change signal in the components of the hydrological cycle is robust, and where this signal has a larger uncertainty. Notable differences in the robustness of the climate change signals between the GCM and RCM simulations are related to a stronger warming projected by the GCM in the winter over the Baltic Sea catchment and in the summer over the Danube and Rhine catchments. Our results indicate that the main explanation for these differences is that the finer resolution of the RCM leads to a better representation of local scale processes at the surface that feed back to the atmosphere, i.e. an improved representation of the land sea contrast and related moisture transport processes over the Baltic Sea catchment, and an improved representation of soil moisture feedbacks to the atmosphere over the Danube and Rhine catchments.     

The effect of climate change on hydrological regimes in Europe: a continental perspective

This paper outlines the effects of climate change by the 2050s on hydrological regimes at the continental scale in Europe, at a spatial resolution of 0.5×0.5°. Hydrological regimes are simulated using a macro-scale hydrological model, operating at a daily time step, and four climate change scenarios are used. There are differences between the four scenarios, but each indicates a general reduction in annual runoff in southern Europe (south of around 50°N), and an increase in the north. In maritime areas there is little difference in the timing of flows, but the range through the year tends to increase with lower flows during summer. The most significant changes in flow regime, however, occur where snowfall becomes less important due to higher temperatures, and therefore both winter runoff increases and spring flow decreases: these changes occur across a large part of eastern Europe. In western maritime Europe low flows reduce, but further east minimum flows will increase as flows during the present low flow season – winter – rise. “Drought” was indexed as the maximum total deficit volume below the flow exceeded 95% of the time: this was found to increase in intensity across most of western Europe, but decrease in the east and north. The study attempted to quantify several sources of uncertainty, and showed that the effects of model uncertainty on the estimated change in runoff were generally small compared to the differences between scenarios and the assumed change in global temperature by 2050.     

Temperature scenarios for Norway: from regional to local scale

Scenarios with daily time resolution are frequently used in research on the impacts of climate change. These are traditionally developed by regional climate models (RCMs). The spatial resolution, however, is usually too coarse for local climate change analysis, especially in regions with complex topography, such as Norway. The RCM used, HIRHAM, is run with lateral boundary forcing provided from two global medium resolution models; the ECHAM4/OPYC3 from MPI and the HadAM3H from the Hadley centre. The first is run with IPCC SRES emission scenario B2, the latter is run with IPCC SRES emission scenarios A2 and B2. All three scenarios represent the future time period 2071–2100. Both models have a control run, representing the present climate (1961–1990). Daily temperature scenarios are interpolated from HIRHAM to Norwegian temperature stations. The at-site HIRHAM-temperatures, both for the control and scenario runs, are adjusted to be locally representative. Mean monthly values and standard deviations based on daily values of the adjusted HIRHAM-temperatures, as well as the cumulative distribution curve of daily seasonal temperatures, are conclusive with observations for the control period. Residual kriging are used on the adjusted daily HIRHAM-temperatures to obtain high spatial temperature scenarios. Mean seasonal temperature grids are obtained. By adjusting the control runs and scenarios and improving the spatial resolution of the scenarios, the absolute temperature values are representative at a local scale. The scenarios indicate larger warming in winter than in summer in the Scandinavian regions. A marked west–east and south–north gradient is projected for Norway, where the largest increase is in eastern and northern regions. The temperature of the coldest winter days is projected to increase more than the warmer temperatures.     

水文模式DHSVM与区域气候模式RegCM2/China嵌套模拟试验

本研究在改进水文 -土壤 -植被模式DHSVM ,用气候观测资料驱动DHSVM进行模拟试验的基础上 ,建立了区域气候模式RegCM2 /China与水文模式DHSVM的嵌套系统 ,将区域气候模式对中国和东亚地区控制试验 (目前气候情景 )和敏感性试验 (未来 2×CO2 气候情景 )结果用双线性插值方法降尺度 (downscaling)到滦河、桑干河流域的 8个气象站点 ,然后再用数字高程模式DEM插值到DHSVM的细网格点 ,驱动水文模式进行嵌套模拟试验。试验结果表明 ,滦河、桑干河流域在未来大气中CO2 浓度加倍情况下 ,地面气温呈一致的增加趋势 ,年平均气温增加2 .8℃ ;两流域未来降水也呈增加趋势 ,滦河、桑干河流域年降水量分别增加 6mm和 4 6mm ;两流域未来蒸发量有所增加 ,年均蒸发量增加 2 9mm ;未来滦河流域年径流深减少 2 7mm ,流量减少 14 .72× 10 8m3 ,桑干河流域径流深增加 2 6mm ,流量增加 12 .2 2× 10 8m3 ,两流域合计 ,流量减少 2 .5× 10 8m3 ;未来滦河、桑干河流域径流深趋向一致 ,分别为 74和 71mm ,约为全国目前平均径流深 2 84mm的 1/ 4。可见 ,两流域未来总体上仍呈现暖干化趋势。本研究发展的嵌套模式系统具有一定的预测能力 ,而且通过参数移植 ,可应用于中国其他流域     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Trend and Correlation Analysis of k-Day Extreme Precipitationover Belgium

Summary k-day extreme precipitation depths (k=1,2,3, … 30) for the climatological network of Belgium (165 stations) are analysed to detect a possible evolution in the occurrence of extreme rainfall events during the 1951–1995 reference period. The calendar year and the hydrological summer and winter are considered separately. Spearman’s rank correlation coefficient shows a strong spatial correlation between extreme k-day precipitation events, depending on the time of the year (lower during summer than during winter) and increasing with k. In some cases the distances of de-correlation exceed 200 km which is comparable to the size of the country. Due to this correlation, tests for trends have been carried out on the leading principal components (PC) derived from the covariance matrix. Various PC selection rules have been applied to identify the number of components to analyse. The number of components needed to reproduce a given proportion of the total variance varies, with larger values for summer than for winter and a decrease with growing k. The Fisher test is used as a global test. It combines the individual Mann-Kendall trend tests carried out on the selected PC scores. Significant trends have been found in extreme winter k-day precipitation for all the values of k and none in extreme summer precipitation. The results for the annual k-day precipitation depths are between those for the two seasons: no trend for small k because summer events dominate and a significant trend for k larger than 7 due to the winter events. Analysis of a few stations with long-term series shows no significant trend for the period 1910–1995, these series also reproduce almost the same trends as those found for the shorter 1951–1995 period. Received April 23, 1999 Revised December 6, 1999     

A comparison of explicit and implicit spatial downscaling of GCM output for soil erosion and crop production assessments

Spatial downscaling of climate change scenarios can be a significant source of uncertainty in simulating climatic impacts on soil erosion, hydrology, and crop production. The objective of this study is to compare responses of simulated soil erosion, surface hydrology, and wheat and maize yields to two (implicit and explicit) spatial downscaling methods used to downscale the A2a, B2a, and GGa1 climate change scenarios projected by the Hadley Centre’s global climate model (HadCM3). The explicit method, in contrast to the implicit method, explicitly considers spatial differences of climate scenarios and variability during downscaling. Monthly projections of precipitation and temperature during 1950–2039 were used in the implicit and explicit spatial downscaling. A stochastic weather generator (CLIGEN) was then used to disaggregate monthly values to daily weather series following the spatial downscaling. The Water Erosion Prediction Project (WEPP) model was run for a wheat–wheat–maize rotation under conventional tillage at the 8.7 and 17.6% slopes in southern Loess Plateau of China. Both explicit and implicit methods projected general increases in annual precipitation and temperature during 2010–2039 at the Changwu station. However, relative climate changes downscaled by the explicit method, as compared to the implicit method, appeared more dynamic or variable. Consequently, the responses to climate change, simulated with the explicit method, seemed more dynamic and sensitive. For a 1% increase in precipitation, percent increases in average annual runoff (soil loss) were 3–6 (4–10) times greater with the explicit method than those with the implicit method. Differences in grain yield were also found between the two methods. These contrasting results between the two methods indicate that spatial downscaling of climate change scenarios can be a significant source of uncertainty, and further underscore the importance of proper spatial treatments of climate change scenarios, and especially climate variability, prior to impact simulation. The implicit method, which applies aggregated climate changes at the GCM grid scale directly to a target station, is more appropriate for simulating a first-order regional response of nature resources to climate change. But for the site-specific impact assessments, especially for entities that are heavily influenced by local conditions such as soil loss and crop yield, the explicit method must be used.     

Potential climate change impact on wind energy resources in northern Europe: analyses using a regional climate model

There is considerable interest in the potential impact of climate change on the feasibility and predictability of renewable energy sources including wind energy. This paper presents dynamically downscaled near-surface wind fields and examines the impact of climate change on near-surface flow and hence wind energy density across northern Europe. It is shown that: Simulated wind fields from the Rossby Centre coupled Regional Climate Model (RCM) (RCAO) with boundary conditions derived from ECHAM4/OPYC3 AOGCM and the HadAM3H atmosphere-only GCM exhibit reasonable and realistic features as documented in reanalysis data products during the control period (1961–1990). The near-surface wind speeds calculated for a climate change projection period of 2071–2100 are higher than during the control run for two IPCC emission scenarios (A2, B2) for simulations conducted using boundary conditions from ECHAM4/OPYC3. The RCAO simulations conducted using boundary conditions from ECHAM4/OPYC3 indicate evidence for a small increase in the annual wind energy resource over northern Europe between the control run and climate change projection period and for more substantial increases in energy density during the winter season. However, the differences between the RCAO simulations for the climate projection period and the control run are of similar magnitude to differences between the RCAO fields in the control period and the NCEP/NCAR reanalysis data. Additionally, the simulations show a high degree of sensitivity to the boundary conditions, and simulations conducted using boundary conditions from HadAM3H exhibit evidence of slight declines or no change in wind speed and energy density between 1961–1990 and 2071–2100. Hence, the uncertainty of the projected wind changes is relatively high.     

General Characteristics of the Atmospheric Boundary Layer Over a Flaw Lead Polynya Region in Winter and Spring

A time series of microwave radiometric profiles over Arctic Canada’s Cape Bathurst (70°N, 124.5°W) flaw lead polynya region from 1 January to 30 June, 2008 was examined to determine the general characteristics of the atmospheric boundary layer in winter and spring. A surface based or elevated inversion was present on 97% of winter (January–March) days, and on 77% of spring (April–June) days. The inversion was the deepest in the first week of March (≈1100 m), and the shallowest in June (≈250 m). The mean temperature and absolute humidity from the surface to the top of the inversion averaged 250.1 K (−23.1°C), and 0.56 × 10⁻³ kg m⁻³ in winter, and in spring averaged 267.5 K (−5.6°C), and 2.77 × 10⁻³ kg m⁻³. The median winter atmospheric boundary-layer (ABL) potential temperature profile provided evidence of a shallow, weakly stable internal boundary layer (surface to 350 m) topped by an inversion (350–1,000 m). The median spring profile showed a shallow, near-neutral internal boundary layer (surface to 350 m) under an elevated inversion (600–800 m). The median ABL absolute humidity profiles were weakly positive in winter and negative in spring. Estimates of the convergence of sensible heat and water vapour from the surface that could have produced the turbulent internal boundary layers of the median profiles were 0.67 MJ m⁻² and 13.1 × 10⁻³ kg m⁻² for the winter season, and 0.66 MJ m⁻² and 33.4 × 10⁻³ kg m⁻² for the spring season. With fetches of 10–100 km, these accumulations may have resulted from a surface sensible heat flux of 15–185 W m⁻², plus a surface moisture flux of 0.001–0.013 mm h⁻¹ (or a latent heat flux of 0.7–8.8 W m⁻²) in winter, and 0.003–0.033 mm h⁻¹ (or a latent heat flux of 2–22 W m⁻²) in spring.     

Simulating the hydrological response to predicted climate change on a watershed in southern Alberta, Canada

The current body of research in western North America indicates that water resources in southern Alberta are vulnerable to climate change impacts. The objective of this research was to parameterize and verify the ACRU agro-hydrological modeling system for a small watershed in southern Alberta and subsequently simulate the change in future hydrological responses over 30-year simulation periods. The ACRU model successfully simulated monthly streamflow volumes (r ²?=?0.78), based on daily simulations over 27 years. The delta downscaling technique was used to perturb the 1961?C1990 baseline climate record from a range of global climate model (GCM) projections to provide the input for future hydrological simulations. Five future hydrological regimes were compared to the 1961?C1990 baseline conditions to determine the average net effect of change scenarios on the hydrological regime of the Beaver Creek watershed over three 30-year time periods (starting in 2010, 2040 and 2070). The annual projections of a warmer and mostly wetter climate in this region resulted in a shift of the seasonal streamflow distribution with an increase in winter and spring streamflow volumes and a reduction of summer and fall streamflow volumes over all time periods, relative to the baseline conditions (1961?C1990), for four of the five scenarios. Simulations of actual evapotranspiration and mean annual runoff showed a slight increase, which was attributed to warmer winters, resulting in more winter runoff and snowmelt events.     

RegCM3 regional climatologies for South America using reanalysis and ECHAM global model driving fields

To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.     

Biases in AMIP model simulations of the east China monsoon system

 AMIP model simulations of the east China (5–50°N; 105–122°E) monsoon system are analyzed to study coherent relationships between rainfall and wind annual cycle biases. A comparison with observed interannual variability patterns is carried out to identify the physical processes that explain the biases. The analyses show that poleward displacement of the simulated east Asian jet stream causes the ascending branch of the jet-induced transverse circulation to move north and, as a consequence, produces negative (positive) rainfall biases occur in central (northeast) China. The model simulations show decreased southwesterly flow and ITCZ rainfall over the South China Sea when weaker (versus observations) summer Hadley and Walker circulations are present. This results from diminished model tropical disturbance activity, and highlights the importance of air-sea interactions. In addition, during October–January, intensified model low-level easterlies enhance moisture transport and produce positive local rainfall biases over central and northeast China. Biases in the east China monsoon system are concurrently reflected in the planetary circulation. Enhanced northeast China rainfall results from increased surface pressure over the North Pacific and an amplified zonal pressure gradient along the east China coast. This bias pattern is associated with differences in model representations of topography. On the other hand, the South China Sea experiences an extensive elongated meridional rainfall bias dipole structure that straddles the equator. This is accompanied by a baroclinic vertical pattern over the tropics as well as a barotropic wave train that extends from Australia to the Antarctic, where the teleconnection is likely a direct atmospheric response to tropical convective heating. Received: 20 June 2000 / Accepted: 17 September 2000     

The relative influence of soil moisture and SST in climate predictability explored within ensembles of AMIP type experiments

Three ensembles of AMIP-type simulations using the Arpege-climat coupled land–atmosphere model have been designed to assess the relative influence of SST and soil moisture (SM) on climate variability and predictability. The study takes advantage of the GSWP2 land surface reanalysis covering the 1986–1995 period. The GSWP2 forcings have been used to derive a global SM climatology that is fully consistent with the model used in this study. One ensemble of ten simulations has been forced by climatological SST and the simulated SM is relaxed toward the GSWP2 reanalysis. Another ensemble has been forced by observed SST and SM is evolving freely. The last ensemble combines the observed SST forcing and the relaxation toward GSWP2. Two complementary aspects of the predictability have been explored, the potential predictability (analysis of variance) and the effective predictability (skill score). An analysis of variance has revealed the effects of the SST and SM boundary forcings on the variability and potential predictability of near-surface temperature, precipitation and surface evaporation. While in the tropics SST anomalies clearly maintain a potentially predictable variability throughout the annual cycle, in the mid-latitudes the SST forced variability is only dominant in winter and SM plays a leading role in summer. In a similar fashion, the annual cycle of the hindcast skill (evaluated as the anomalous correlation coefficient of the three ensemble means with respect to the “observations”) indicates that the SST forcing is the dominant contributor over the tropical continents and in the winter mid-latitudes but that SM is supporting a significant part of the skill in the summer mid-latitudes. Focusing on boreal summer, we have then investigated different aspects of the SM and SST contribution to climate variations in terms of spatial distribution and time-evolution. Our experiments suggest that SM is potentially an additional source of climate predictability. A realistic initialization of SM and a proper representation of the land–atmosphere feedbacks seem necessary to improve state-of-the-art dynamical seasonal predictions, but will be actually efficient only in the areas where SM anomalies are themselves predictable at the monthly to seasonal timescale (since remote effects of SM are probably much more limited than SST teleconnections).     

不同气候情景下华北平原蒸发与径流时空变化分析

基于中国气象局国家气候中心生成的IPCC第四次评估报告中23种气候模式的情景集成数据,采用Schreiber公式和Thornthwaite方法计算实际蒸发和径流,分析了2001-2060年SRES A1B、A2和 B1这3种情景下,华北平原气温、降水、蒸发与径流的时空变化。结果表明：未来华北平原气温呈升高趋势,且冬半年升温幅度大于夏半年;降水亦呈增加趋势,而冬半年降水增加幅度小于夏半年;与此相应,华北平原蒸发和年径流呈增加趋势,增幅和空间差异随时间推移而增大,到2041-2060年蒸发将上升7.1%～9.4%,径流将增加8.7%～10.7%。