Regional climate changes as the factors of impact on the objects of construction and infrastructure

Considered are the changes in the climate impact on the objects of construction and infrastructure on the territory of Russia. The focus is on the changes in the characteristics of daily air temperature and precipitation expected by the middle of the 21st century, which are of high importance in terms of the building design. The assessment of expected changes is based on the results of ensemble computations using the MGO gobal climate model and the embedded regional model (MGO RCM) with the horizontal resolution of 25 km. Along with the ensemble-averaged estimates of changes in applied climate parameters, an uncertainty of estimates associated with the natural climate variability is analyzed using the data of numerical experiments. The attention is drawn to the most significant effects of climate changes which should be taken into account when developing the measures for adapting the construction sector in Russia.     

Climate simulation of the twenty-first century with interactive land-use changes

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean–atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.     

Variation of surface temperature during the last millennium in a simulation with the FGOALS-gl climate system model

A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model (FGOALS-gl) developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). The model presents a reasonable performance in comparison with reconstructions of surface temperature. Differentiated from significant changes in the 20th century at the global scale, changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere. Seasonally, modeled significant changes are more pronounced during the wintertime at higher latitudes. This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback. The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period, especially at decadal timescales. Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability. The model response to specified external forcings is modulated by cloud radiative forcing (CRF). The CRF acts against the fluctuations of external forcings. Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period, but mainly in longwave radiation by a decrease in cloud amount in the anthropogenic-forcing-dominant period.     

Optimal detection and attribution of climate change: sensitivity of results to climate model differences

Fingerprint techniques for the detection of anthropogenic climate change aim to distinguish the climate response to anthropogenic forcing from responses to other external influences and from internal climate variability. All these responses and the characteristics of internal variability are typically estimated from climate model data. We evaluate the sensitivity of detection and attribution results to the use of response and variability estimates from two different coupled ocean atmosphere general circulation models (HadCM2, developed at the Hadley Centre, and ECHAM3/LSG from the MPI für Meteorologie and Deutsches Klimarechenzentrum). The models differ in their response to greenhouse gas and direct sulfate aerosol forcing and also in the structure of their internal variability. This leads to differences in the estimated amplitude and the significance level of anthropogenic signals in observed 50-year summer (June, July, August) surface temperature trends. While the detection of anthropogenic influence on climate is robust to intermodel differences, our ability to discriminate between the greenhouse gas and the sulfate aerosol signals is not. An analysis of the recent warming, and the warming that occurred in the first half of the twentieth century, suggests that simulations forced with combined changes in natural (solar and volcanic) and anthropogenic (greenhouse gas and sulfate aerosol) forcings agree best with the observations.     

The impact of natural and anthropogenic forcings on climate and hydrology since 1550

A climate simulation of an ocean/atmosphere general circulation model driven with natural forcings alone (constant “pre-industrial” land-cover and well-mixed greenhouse gases, changing orbital, solar and volcanic forcing) has been carried out from 1492 to 2000. Another simulation driven with natural and anthropogenic forcings (changes in greenhouse gases, ozone, the direct and first indirect effect of anthropogenic sulphate aerosol and land-cover) from 1750 to 2000 has also been carried out. These simulations suggest that since 1550, in the absence of anthropogenic forcings, climate would have warmed by about 0.1 K. Simulated response is not in equilibrium with the external forcings suggesting that both climate sensitivity and the rate at which the ocean takes up heat determine the magnitude of the response to forcings since 1550. In the simulation with natural forcings climate sensitivity is similar to other simulations of HadCM3 driven with CO₂ alone. Climate sensitivity increases when anthropogenic forcings are included. The natural forcing used in our experiment increases decadal–centennial time-scale and large spatial scale climate variability, relative to internal variability, as diagnosed from a control simulation. Mean conditions in the natural simulation are cooler than in our control simulation reflecting the reduction in forcing. However, over certain regions there is significant warming, relative to control, due to an increase in forest cover. Comparing the simulation driven by anthropogenic and natural forcings with the natural-only simulation suggests that anthropogenic forcings have had a significant impact on, particularly tropical, climate since the early nineteenth century. Thus the entire instrumental temperature record may be “contaminated” by anthropogenic influences. Both the hydrological cycle and cryosphere are also affected by anthropogenic forcings. Changes in tree-cover appear to be responsible for some of the local and hydrological changes as well as an increase in northern hemisphere spring snow cover.

---

European temperature records of the past five centuries based on documentary/instrumental information compared to climate simulations

Two European temperature reconstructions for the past half-millennium, January-to-April air temperature for Stockholm (Sweden) and seasonal temperature for a Central European region, both derived from the analysis of documentary sources and long instrumental records, are compared with the output of climate simulations with the model ECHO-G. The analysis is complemented by comparisons with the long (early)-instrumental record of Central England Temperature (CET). Both approaches to study past climates (simulations and reconstructions) are burdened with uncertainties. The main objective of this comparative analysis is to identify robust features and weaknesses in each method which may help to improve models and reconstruction methods. The results indicate a general agreement between simulations obtained with temporally changing external forcings and the reconstructed Stockholm and CET records for the multi-centennial temperature trend over the recent centuries, which is not reproduced in a control simulation. This trend is likely due to the long-term change in external forcing. Additionally, the Stockholm reconstruction and the CET record also show a clear multi-decadal warm episode peaking around AD 1730, which is absent in the simulations. Neither the reconstruction uncertainties nor the model internal climate variability can easily explain this difference. Regarding the interannual variability, the Stockholm series displays, in some periods, higher amplitudes than the simulations but these differences are within the statistical uncertainty and further decrease if output from a regional model driven by the global model is used. The long-term trend of the CET series agrees less well with the simulations. The reconstructed temperature displays, for all seasons, a smaller difference between the present climate and past centuries than is seen in the simulations. Possible reasons for these differences may be related to a limitation of the traditional ‘indexing’ technique for converting documentary evidence to temperature values to capture long-term climate changes, because the documents often reflect temperatures relative to the contemporary authors’ own perception of what constituted ‘normal’ conditions. By contrast, the amplitude of the simulated and reconstructed inter-annual variability agrees rather well.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

Natural variability of summer rainfall over China in HadCM3

Summer rainfall over China has shown decadal variability in the past half century, which has resulted in major north–south shifts in rainfall with important implications for flooding and water resource management. This study has demonstrated how multi-century climate model simulations can be used to explore interdecadal natural variability in the climate system in order to address important questions around recent changes in Chinese summer rainfall, and whether or not anthropogenic climate change is playing a role. Using a 1,000-year simulation of HadCM3 with constant pre-industrial external forcing, the dominant modes of total and interdecadal natural variability in Chinese summer rainfall have been analysed. It has been shown that these modes are comparable in magnitude and in temporal and spatial characteristics to those observed in the latter part of the twentieth century. However, despite 1,000 years of model simulation it has not been possible to demonstrate that these modes are related to similar variations in the global circulation and surface temperature forcing occurring during the latter half of the twentieth century. This may be in part due to model biases. Consequently, recent changes in the spatial distribution of Chinese summer rainfall cannot be attributed solely to natural variability, nor has it been possible to eliminate the likelihood that anthropogenic climate change has been the driving factor. It is more likely that both play a role.     

Indicators of Climate Change for the Russian Federation

Observed climate changes over the Russian Federation (RF) territory are considered. Several indicators based on monthly mean temperature and precipitation station data are used to quantify regional climate changes. Some of these are the components of two aggregated indices of climate change, suggested by Karl et al. (1996): the Climate Extremes Index (CEI) and the Greenhouse Climate Response Index (GCRI). For the RF territory as a whole, and for its western part, the "Russian Permafrost Free (RPF) territory" in particular, changes in surface air temperature are investigated, together with changes in precipitation and drought indices, and also the fraction of the Russian territory experiencing climatic anomalies below and/or above certain specified percentiles. Composite indices CEI-3 and GCRI-3 based on three parameters (air temperature, precipitation and drought indices) are examined, as well as the Climate Anomaly Index (CAI), known in Russia as Bagrov's coefficient of "anomality".It is shown, that over the area of the RPF as a whole, air temperature and the occurrence of drought has increased somewhat during the 20th century, while precipitation has decreased; these changes were non-uniform in space. The linear trend accounts for only a small fraction of the total variability, but the role of climate variations on decadal scales seems more substantial. The CEI, determined as the percentage of the area experiencing extreme anomalies (with a 10% or less frequency of occurrence) of either sign, increased for mean annual temperature, decreased for total precipitation and increased slightly for the occurrence of drought conditions; the aggregated index based on all three of these quantities increased slightly. There was also an increase in the GCRI-3 index, which is indicative of an agreement between the observed climate changes and the changes owing to the greenhouse effect as predicted by climatic models.The observed climate changes are too small to enable us confidently to reject a hypothesis that they are a reflection of the natural variability of climatic parameters within the context of a stationary climate. However, there is no doubt about the reality and importance of the observed changes.     

Estimation of critical levels of climate change influence on the natural terrestrial ecosystems on the territory of Russia

Developed are the axiomatics and criteria for estimating the critical levels of climate change influence on the natural terrestrial ecosystems based on the revelation of key climate-dependent environmental elements and model analysis of their variations. Developed is an empirical statistical vegetation model for the territory of Russia considering 15 vegetation zones including five ones in the permafrost zone. The model was used to estimate the proximity of the climate impact on the natural terrestrial ecosystems to the critical level for several climate projections.     

Climate of Russia in the 21st century. Part 3. Future climate changes calculated with an ensemble of coupled atmosphere-ocean general circulation CMIP3 models

Probable climate changes in Russia in the 21st century are considered based on the results of global climate simulations with an ensemble of coupled atmosphere-ocean CMIP3 models. The future changes in the surface air temperature, atmospheric pressure, cloud amount, atmospheric precipitation, snow cover, soil water content, and annual runoff in Russia and some of its regions in the early, middle, and late 21st century are analyzed using the A2 scenario of the greenhouse gas and aerosol emission. Future changes in the yearly highest and lowest surface air temperatures and in summer precipitation of high intensity are estimated for Russia. Possible oscillations of the Caspian Sea level associated with the expected global climate warming are estimated. In addition to the estimates of the ensemble mean changes in climatic characteristics, the information about standard deviations and statistical significance of the corresponding climate changes is given.     

Natural and anthropogenic climate change: incorporating historical land cover change,vegetation dynamics and the global carbon cycle

This study explores natural and anthropogenic influences on the climate system, with an emphasis on the biogeophysical and biogeochemical effects of historical land cover change. The biogeophysical effect of land cover change is first subjected to a detailed sensitivity analysis in the context of the UVic Earth System Climate Model, a global climate model of intermediate complexity. Results show a global cooling in the range of –0.06 to –0.22 °C, though this effect is not found to be detectable in observed temperature trends. We then include the effects of natural forcings (volcanic aerosols, solar insolation variability and orbital changes) and other anthropogenic forcings (greenhouse gases and sulfate aerosols). Transient model runs from the year 1700 to 2000 are presented for each forcing individually as well as for combinations of forcings. We find that the UVic Model reproduces well the global temperature data when all forcings are included. These transient experiments are repeated using a dynamic vegetation model coupled interactively to the UVic Model. We find that dynamic vegetation acts as a positive feedback in the climate system for both the all-forcings and land cover change only model runs. Finally, the biogeochemical effect of land cover change is explored using a dynamically coupled inorganic ocean and terrestrial carbon cycle model. The carbon emissions from land cover change are found to enhance global temperatures by an amount that exceeds the biogeophysical cooling. The net effect of historical land cover change over this period is to increase global temperature by 0.15 °C.     

Multidecadal-to-centennial SST variability in the MPI-ESM simulation ensemble for the last millennium

We assess the responses of North Atlantic, North Pacific, and tropical Indian Ocean Sea Surface Temperatures (SSTs) to natural forcing and their linkage to simulated global surface temperature (GST) variability in the MPI-Earth System Model simulation ensemble for the last millennium. In the simulations, North Atlantic and tropical Indian Ocean SSTs show a strong sensitivity to external forcing and a strong connection to GST. The leading mode of extra-tropical North Pacific SSTs is, on the other hand, rather resilient to natural external perturbations. Strong tropical volcanic eruptions and, to a lesser extent, variability in solar activity emerge as potentially relevant sources for multidecadal SST modes’ phase modulations, possibly through induced changes in the atmospheric teleconnection between North Atlantic and North Pacific that can persist over decadal and multidecadal timescales. Linkages among low-frequency regional modes of SST variability, and among them and GST, can remarkably vary over the integration time. No coherent or constant phasing is found between North Pacific and North Atlantic SST modes over time and among the ensemble members. Based on our assessments of how multidecadal transitions in simulated North Atlantic SSTs compare to reconstructions and of how they contribute characterizing simulated multidecadal regional climate anomalies, past regional climate multidecadal fluctuations seem to be reproducible as simulated ensemble-mean responses only for temporal intervals dominated by major external forcings.     

Scenary forecasts of air temperature variations for the regions of the Russian Federation up to 2030 using the empirical stochastic climate models

It is demonstrated that the results of the climate modeling cannot be directly used to forecast the regional climate changes on the territory of the Russian Federation for one-three decades due to the strong influence of the natural long-period climatic variability associated with the processes in the ocean-atmosphere system in the North Atlantic. A model is proposed of the temperature variations in the regions of the Russian Federation including the variations of the global temperature and North Atlantic Oscillation (NAO) index. An empirical dynamic-stochastic model with external radiation impacts is used for the global temperature. Different scenarios of concentration variations of the radiation-active atmospheric components and NAO are considered. It is demonstrated that depending on the accepted hypothesis concerning the type of the expected NAO variations (natural fluctuations or the result of anthropogenic impacts) and on the scenario of concentration variations of the sulfate aerosols and methane, the average annual temperature variations on the territory of the Russian Federation between 2007 and 2030 may amount from 0.81 to 1.90°C. The estimates of temperature variations for the main physiographic regions of the Russian Federation are obtained.     

Mitigating the Effects of Climate Change on the Water Resources of the Columbia River Basin

The potential effects of climate change on the hydrology and water resources of the Columbia River Basin (CRB) were evaluated using simulations from the U.S. Department of Energy and National Center for Atmospheric Research Parallel Climate Model (DOE/NCAR PCM). This study focuses on three climate projections for the 21st century based on a `business as usual' (BAU) global emissions scenario, evaluated with respect to a control climate scenario based on static 1995 emissions. Time-varying monthly PCM temperature and precipitation changes were statistically downscaled and temporally disaggregated to produce daily forcings that drove a macro-scale hydrologic simulation model of the Columbia River basin at 1/4-degree spatial resolution. For comparison with the direct statistical downscaling approach, a dynamical downscaling approach using a regional climate model (RCM) was also used to derive hydrologic model forcings for 20-year subsets from the PCM control climate (1995–2015) scenario and from the three BAU climate(2040–2060) projections. The statistically downscaled PCM scenario results were assessed for three analysis periods (denoted Periods 1–3: 2010–2039,2040–2069, 2070–2098) in which changes in annual average temperature were +0.5,+1.3 and +2.1 °C, respectively, while critical winter season precipitation changes were –3, +5 and +1 percent. For RCM, the predicted temperature change for the 2040–2060 period was +1.2 °C and the average winter precipitation change was –3 percent, relative to the RCM controlclimate. Due to the modest changes in winter precipitation, temperature changes dominated the simulated hydrologic effects by reducing winter snow accumulation, thus shifting summer streamflow to the winter. The hydrologic changes caused increased competition for reservoir storage between firm hydropower and instream flow targets developed pursuant to the Endangered Species Act listing of Columbia River salmonids. We examined several alternative reservoir operating policies designed to mitigate reservoir system performance losses. In general, the combination of earlier reservoir refill with greater storage allocations for instream flow targets mitigated some of the negative impacts to flow, but only with significant losses in firm hydropower production (ranging from –9 percent in Period1 to –35 percent for RCM). Simulated hydropower revenue changes were lessthan 5 percent for all scenarios, however, primarily due to small changes inannual runoff.     

The contribution of anthropogenic forcings to regional changes in temperature during the last decade

Regional distributions of the mean annual temperature in the 2000s are computed with and without the effect of anthropogenic influences on the climate in several sub-continental regions. Simulated global patterns of the temperature response to external forcings are regressed against observations using optimal fingerprinting. The global analysis provides constraints which are then used to construct the regional temperature distributions. A similar approach was also employed in previous work, but here the methodology is extended to examine changes in any region, including areas with a poor observational coverage that were omitted in the earlier study. Two different General Circulation Models (GCMs) are used in the analysis. Anthropogenic forcings are found to have at least quadrupled the likelihood of occurrence of a year warmer than the warmest year since 1900 in 23 out of the 24 regions. The temperature distributions computed with the two models are very similar. While a more detailed assessment of model dependencies remains to be made once additional suitable GCM simulations become available, the present study introduces the statistical methodology and demonstrates its first application. The derived information concerning the effect of human influences on the regional climate is useful for adaptation planning. Moreover, by pre-computing the change in the likelihood of exceeding a temperature threshold over a range of thresholds, this kind of analysis enables a near real-time assessment of the anthropogenic impact on the observed regional temperatures.     

Climate simulations for 1880–2003 with GISS modelE

We carry out climate simulations for 1880–2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880–2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model

The results are analyzed of the ensemble forecast of temperature and precipitation extremes on the territory of Siberia by the middle of the 21st century based on the regional climate model of the Main Geophysical Observatory (MGO) with the resolution of 25 km. The results of computation of oceanic components of CMIP3 coupled models are used as the boundary conditions on the sea surface. It is demonstrated that the high resolution of the regional model enables to simulate the observed climate variability in a more realistic way as compared to the low-resolution models. The analysis of the signal-to-noise ratio for future climate changes made it possible to determine to which degree its internal variability for various time scales (from interannual to interdecennial one) bounds the potential of the ensemble to compute the statistically significant anthropogenic changes of extremes. A comparative analysis of variations of extreme and average seasonal characteristics of the Siberian climate is carried out.     

Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change

 A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95% confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis, the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal. The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent with greenhouse gas or solar forcing alone. Received: 28 April 1996 / Accepted: 27 January 1997     

Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900–2099

Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5 °C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.