不同分辨率CCSM4对东亚和中国气候模拟能力分析

本文利用通用气候系统模式CCSM4在三种水平分辨率下的工业化革命前期气候模拟试验,结合观测和再分析资料,比较了各分辨率下模式对中国温度和降水、东亚海平面气压和850 hPa风场的模拟能力,综合评价了模式分辨率对东亚和中国气候模拟的影响.结果表明,三种分辨率对中国温度均具有很好的模拟能力,除春季外,低分辨率(T31,约3.75°×3.75°)对全年温度的模拟能力均要稍好于中(f19,约1.9°×2.5°)、高(f09,约0.9°×1.25°)分辨率;各分辨率对中国降水的模拟能力远不如温度,除冬季外全年都出现的中部地区虚假降水并未因为模式分辨率提高而得到本质改善;对于东亚海平面气压场,低分辨率在冬季模拟能力相对最好,中等分辨率在夏季相对较好,而高分辨率的模拟能力均表现最差;低分辨率对850 hPa东亚冬季风和夏季风的模拟能力均要好于中、高分辨率,而两种较高分辨率的模拟能力则比较接近.总的来说,低分辨率CCSM4在东亚和中国气候模拟中表现出了较大优势,加之其计算代价小,适合进行需要较长时间积分的气候模拟研究.     

Past millennial solar forcing magnitude

A set of global climate model simulations for the last thousand years developed by the Max Planck Institute is compared with paleoclimate proxy data and instrumental data, focusing on surface temperatures for land areas between 30° and 75°N. The proxy data are obtained from six previously published Northern Hemispheric-scale temperature reconstructions, here re-calibrated for consistency, which are compared with the simulations utilizing a newly developed statistical framework for ranking several competing simulations by means of their statistical distance against past climate variations. The climate model simulations are driven by either “low” or “high” solar forcing amplitudes (0.1 and 0.25 % smaller total solar irradiance in the Maunder Minimum period compared to the present) in addition to several other known climate forcings of importance. Our results indicate that the high solar forcing amplitude results in a poorer match with the hemispheric-scale temperature reconstructions and lends stronger statistical support for the low-amplitude solar forcing. However, results are likely conditional upon the sensitivity of the climate model used and strongly dependent on the choice of temperature reconstruction, hence a greater consensus is needed regarding the reconstruction of past temperatures as this currently provides a great source of uncertainty.     

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     

The Warming of the Tibetan Plateau in Response to Transient and Stabilized 2.0°C/1.5°C Global Warming Targets

As "the third pole", the Tibetan Plateau (TP) is sensitive to climate forcing and has experienced rapid warming in recent decades. This study analyzes annual and seasonal near-surface air temperature changes on the TP in response to transient and stabilized 2.0°C/1.5°C global warming targets based on simulations of the Community Earth System Model (CESM). Elevation-dependent warming (EDW) with faster warming at higher elevations is predicted. A surface energy budget analysis is adopted to uncover the mechanisms responsible for the temperature changes. Our results indicate a clear amplified warming on the TP with positive EDW in 2.0°C/1.5°C warmer futures, especially in the cold season. Mean TP warming relative to the reference period (1961–90) is dominated by an enhanced downward longwave radiation flux, while the variations in surface albedo shape the detailed pattern of EDW. For the same global warming level, the temperature changes under transient scenarios are ~0.2°C higher than those under stabilized scenarios, and the characteristics of EDW are broadly similar for both scenarios. These differences can be primarily attributed to the combined effects of differential downward longwave radiation, cloud radiative forcing, and surface sensible and latent heat fluxes. These findings contribute to a more detailed understanding of regional climate on the TP in response to the long-term climate goals of the Paris Agreement and highlight the differences between transient and stabilized warming scenarios.     

Climate sensitivity and response

Results from climate change simulations indicate a reasonably robust proportionality between global mean radiative forcing and global mean surface air temperature response. The "constant" of proportionality is a measure of the overall strength of climate feedback processes and hence of global climate sensitivity. Geographically, however, temperature response patterns are generally not proportional to, nor do they resemble, their parent forcing patterns. Temperature response patterns, nevertheless, exhibit a remarkable additivity whereby the sum of response patterns for different forcings closely resembles the response pattern for the sum of the forcings. The geographical distribution of contributions to the climate sensitivity/feedback are obtained diagnostically from simulations with the Canadian Centre for Climate Modelling and Analysis (CCCma) coupled global climate model (GCM). There is positive feedback over high-latitude oceans, over northern land areas, and over the equatorial Pacific. The remaining regions over oceans and tropical land areas exhibit negative feedback. The feedback results are decomposed into components associated with short-and longwave radiative processes and in terms of cloud-free atmosphere/surface and cloud feedbacks. While the geographic pattern of the feedbacks may generally be linked to local processes, all feedback processes display regions of both positive and negative values (except for the solar atmosphere/surface feedback associated with the retreat of ice and snow which is positive) and all vary from place to place so that there is no simple physical picture that operates everywhere. The stable geographical pattern of the feedback is a consequence of the balance between local physical processes rather than the dominance of a particular process. The feedback results indicate that, to first order, temperature response patterns are determined by the geographical pattern of local feedback processes. The feedback processes act to localize forcing changes and to generate temperature response patterns which depend firstly on the pattern of feedbacks and only secondarily on the pattern of the forcing. The geographical distribution of feedback processes can be regarded as a feature of the climate model (and by inference of the climate system) and not (or only comparatively weak) functions of forcing and climate state. An illustrative model is able to reproduce qualitatively the kinds of forcing/temperature response behavior seen in the CCCma GCM including the quasi-independence of forcing and response patterns, the additivity of temperature response patterns, and the resulting "non-constancy" of the global climate sensitivity.     

气候模式分辨率对气溶胶气候效应模拟结果的影响

气候模式分辨率作为影响模式模拟结果的重要因素,其对气溶胶与云相互作用的影响尚未全面认识。利用公共大气模型CAM5.3在3种分辨率（2°、1°、0.5°）下,分别采用2000年和1850年气溶胶排放情景进行试验,检验提高分辨率是否能改进气候模式的模拟能力,分析不同分辨率下气溶胶气候效应的异同,探索模式分辨率对气溶胶气候效应数值模拟结果的影响。通过观测资料与模式结果对比发现,提高分辨率可以明显改进模式对总云量、云短波辐射强迫的模拟能力,0.5°分辨率下模拟结果与观测更接近,其他变量并无明显改善。在不同分辨率下,全球平均的气溶胶气候效应较为一致,总云量、云水路径均增加,云短波和长波辐射强迫均加强,而云顶的云滴有效半径和降水均减小,地面气温降低。不同分辨率下,气溶胶增加引起的气溶胶光学厚度、云水路径、地面温度、云短波和长波辐射强迫变化的纬向平均分布相似但大小存在差异;而降水和云量变化的纬向分布与大小均存在较大差异,在区域尺度上还存在较大的不确定性。全球平均而言, 0.5°分辨率下气溶胶的间接辐射强迫相比1°分辨率下的结果降低了2.5%,相比2°分辨率下的结果降低了6.4%。提高模式分辨率可以部分改进模式模拟能力,同时,气溶胶的间接效应随着模式分辨率的提高而减弱。但气溶胶引起的云量、降水的变化在不同分辨率下差异较大,存在较大的不确定性。      

Probabilistic projections of transient climate change

This paper describes a Bayesian methodology for prediction of multivariate probability distribution functions (PDFs) for transient regional climate change. The approach is based upon PDFs for the equilibrium response to doubled carbon dioxide, derived from a comprehensive sampling of uncertainties in modelling of surface and atmospheric processes, and constrained by multiannual mean observations of recent climate. These PDFs are sampled and scaled by global mean temperature predicted by a Simple Climate Model (SCM), in order to emulate corresponding transient responses. The sampled projections are then reweighted, based upon the likelihood that they correctly replicate observed historical changes in surface temperature, and combined to provide PDFs for 20 year averages of regional temperature and precipitation changes to the end of the twenty-first century, for the A1B emissions scenario. The PDFs also account for modelling uncertainties associated with aerosol forcing, ocean heat uptake and the terrestrial carbon cycle, sampled using SCM configurations calibrated to the response of perturbed physics ensembles generated using the Hadley Centre climate model HadCM3, and other international climate model simulations. Weighting the projections using observational metrics of recent mean climate is found to be as effective at constraining the future transient response as metrics based on historical trends. The spread in global temperature response due to modelling uncertainty in the carbon cycle feedbacks is determined to be about 65–80 % of the spread arising from uncertainties in modelling atmospheric, oceanic and aerosol processes of the climate system. Early twenty-first century aerosol forcing is found to be extremely unlikely to be less than ?1.7 W m^?2. Our technique provides a rigorous and formal method of combining several lines of evidence used in the previous IPCC expert assessment of the Transient Climate Response. The 10th, 50th and 90th percentiles of our observationally constrained PDF for the Transient Climate Response are 1.6, 2.0 and 2.4 °C respectively, compared with the 10–90 % range of 1.0–3.0 °C assessed by the IPCC.     

Modelling Sea Surface Temperature (SST) in the Hudson Bay Complex Using Bulk Heat Flux Parameterization: Sensitivity to Atmospheric Forcing,and Model Resolution

ABSTRACT

Sea surface temperature (SST) from four Nucleus for European Modelling of the Ocean (NEMO) model simulations is analyzed to study the bulk flux parameterization to compute SST over the Hudson Bay Complex (HBC) for the summer months (August and September) from 2002 to 2009. The NEMO simulation was forced with two atmospheric forcing sets with different resolutions: the Coordinated Ocean-ice Reference Experiment, version 2 (COREv2), as the lower resolution and the Canadian Meteorological Centre’s Global Deterministic Prediction System Reforecasts (CGRF) as the higher resolution. The CGRF forcing is also implemented in the third and fourth runs using different runoff data and different NEMO resolutions (1/12° versus 1/4°). Results show that all four modelled SSTs followed observed SST patterns, with regional differences in SST bias between simulations with different atmospheric forcing. The SST differences are small between simulations forced with the same atmospheric forcing but with different model resolution or runoff. This implies that the model resolution and runoff have a small effect on the simulated SST in the HBC. Moreover, to better capture the effect of near-surface temperature (T_air) on simulated SST, we conducted three analyses using the Haney flux linearization formula. Results from these assessments did not indicate any direct influence on the model-simulated SSTs by T_air. Looking at the heat flux as a signature for SST showed that both averaged spatial distribution and time series of net heat flux produced by the three CGRF forcing simulations were higher than the net heat flux generated by the CORE 2 simulation. This was generally true for all four components of the total heat flux (sensible, latent, shortwave, and longwave) individually as well. Total heat flux in summer is governed by the shortwave heat flux, with values up to 120?W?m^?2 in August, and the longwave heat flux is the main contributor to the total heat flux differences. These heat flux differences lead to corresponding colder model SSTs for the CGRF runs and warmer SSTs for the CORE 2 simulations.     

The modification of greenhouse gas warming by the direct effect of sulphate aerosols

 The Canadian Centre for Climate Modelling and Analysis (CCCma) second generation climate model (GCMII) consists of an atmospheric GCM coupled to mixed layer ocean. It is used to investigate the climate response to a doubling of the CO₂ concentration together with the direct effect of scattering by sulphate aerosols. As expected, the aerosols offset some of the greenhouse gas (GHG) warming; the global annual mean screen temperature change due to doubled CO₂ is 3.4 °C in this model and this is reduced to 2.7 °C when an estimate of the direct effect of anthropogenic sulphate aerosols is included. The pattern of climate response to the comparatively localized aerosol forcing is not itself localized, and it bears a striking resemblance to the response pattern that arises from the globally distributed change in GHG forcing. This “non-local” response to “localized” forcing indicates that the pattern of climate response is determined, to first order, by the overall magnitude of the change in forcing rather than its detailed nature or structure. Feedback processes operating in the system apparently determine this pattern by locally amplifying and suppressing the response to the magnitude of the change in forcing. The influence of the location of the change in forcing is relatively small. These “non-local” and “local” effects of aerosol forcing are characterized and displayed and some of their consequences discussed. Effects on the moisture budget and on the energetics of the global climate are also examined. Received: 10 June 1997 / Accepted: 8 January 1998     

Long-term climate response to stabilized and overshoot anthropogenic forcings beyond the twenty-first century

From multi-ensembles of climate simulations using the Community Climate System Model version 3, global climate changes have been investigated focusing on long-term responses to stabilized anthropogenic forcings. In addition to the standard forcing scenarios for the current international assessment, an overshoot scenario, where radiative forcings are decreased from one stabilized level to another, is also considered. The globally-averaged annual surface air temperature increases during the twenty-first century by 2.58 and 1.56°C for increased forcings under two future scenarios denoted by A1B and B1, respectively. These changes continue but at much slower rates in later centuries under forcings stabilized at year 2100. The overshoot scenario provides a different pathway to the lower B1 level by way of the greater A1B level. This scenario results in a surface climate similar to that in the B1 scenario within 100 years after the forcing reaches the B1 level. Contrasting to the surface changes, responses in the ocean are significantly delayed. It is estimated from the linear response theory that temperature changes under stabilized forcings to a final equilibrium state in the A1B (B1) scenario are factors of 0.3–0.4, 0.9, and 17 (0.3, 0.6, and 11) to changes during the twenty-first century, respectively, for three ocean layers of the surface to 100, 100–500, and 500 m to the bottom. Although responses in the lower ocean layers imply a nonlinear behavior, the ocean temperatures in the overshoot and B1 scenarios are likely to converge in their final equilibrium states.     

Time-dependent response of a zonally averaged ocean–atmosphere–sea ice model to Milankovitch forcing

An ocean–atmosphere–sea ice model is developed to explore the time-dependent response of climate to Milankovitch forcing for the time interval 5–3 Myr BP. The ocean component is a zonally averaged model of the circulation in five basins (Arctic, Atlantic, Indian, Pacific, and Southern Oceans). The atmospheric component is a one-dimensional (latitudinal) energy balance model, and the sea-ice component is a thermodynamic model. Two numerical experiments are conducted. The first experiment does not include sea ice and the Arctic Ocean; the second experiment does. Results from the two experiments are used to investigate (1) the response of annual mean surface air and ocean temperatures to Milankovitch forcing, and (2) the role of sea ice in this response. In both experiments, the response of air temperature is dominated by obliquity cycles at most latitudes. On the other hand, the response of ocean temperature varies with latitude and depth. Deep water formed between 45°N and 65°N in the Atlantic Ocean mainly responds to precession. In contrast, deep water formed south of 60°S responds to obliquity when sea ice is not included. Sea ice acts as a time-integrator of summer insolation changes such that annual mean sea-ice conditions mainly respond to obliquity. Thus, in the presence of sea ice, air temperature changes over the sea ice are amplified, and temperature changes in deep water of southern origin are suppressed since water below sea ice is kept near the freezing point.     

A fractal climate response function can simulate global average temperature trends of the modern era and the past millennium

A climate response function is introduced that consists of six exponential (low-pass) filters with weights depending as a power law on their e-folding times. The response of this two-parameter function to the combined forcings of solar irradiance, greenhouse gases, and SO₂-related aerosols is fitted simultaneously to reconstructed temperatures of the past millennium, the response to solar cycles, the response to the 1991 Pinatubo volcanic eruption, and the modern 1850–2010 temperature trend. Assuming strong long-term modulation of solar irradiance, the quite adequate fit produces a climate response function with a millennium-scale response to doubled CO₂ concentration of 2.0 ± 0.3 °C (mean ± standard error), of which about 50 % is realized with e-folding times of 0.5 and 2 years, about 30 % with e-folding times of 8 and 32 years, and about 20 % with e-folding times of 128 and 512 years. The transient climate response (response after 70 years of 1 % yearly rise of CO₂ concentration) is 1.5 ± 0.2 °C. The temperature rise from 1820 to 1950 can be attributed for about 70 % to increased solar irradiance, while the temperature changes after 1950 are almost completely produced by the interplay of anthropogenic greenhouse gases and aerosols. The SO₂-related forcing produces a small temperature drop in the years 1950–1970 and an inflection of the temperature curve around the year 2000. Fitting with a tenfold smaller modulation of solar irradiance produces a less adequate fit with millennium-scale and transient climate responses of 2.5 ± 0.4 and 1.9 ± 0.3 °C, respectively.     

Past and future polar amplification of climate change: climate model intercomparisons and ice-core constraints

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO₂ concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. An erratum to this article can be found at     

A transient climate change simulation with greenhouse gas and aerosol forcing: projected climate to the twenty-first century

 The potential climatic consequences of increasing atmospheric greenhouse gas (GHG) concentration and sulfate aerosol loading are investigated for the years 1900 to 2100 based on five simulations with the CCCma coupled climate model. The five simulations comprise a control experiment without change in GHG or aerosol amount, three independent simulations with increasing GHG and aerosol forcing, and a simulation with increasing GHG forcing only. Climate warming accelerates from the present with global mean temperatures simulated to increase by 1.7 °C to the year 2050 and by a further 2.7 °C by the year 2100. The warming is non-uniform as to hemisphere, season, and underlying surface. Changes in interannual variability of temperature show considerable structure and seasonal dependence. The effect of the comparatively localized negative radiative forcing associated with the aerosol is to retard and reduce the warming by about 0.9 °C at 2050 and 1.2 °C at 2100. Its primary effect on temperature is to counteract the global pattern of GHG-induced warming and only secondarily to affect local temperatures suggesting that the first order transient climate response of the system is determined by feedback processes and only secondarily by the local pattern of radiative forcing. The warming is accompanied by a more active hydrological cycle with increases in precipitation and evaporation rates that are delayed by comparison with temperature increases. There is an “El Nino-like” shift in precipitation and an overall increase in the interannual variability of precipitation. The effect of the aerosol forcing is again primarily to delay and counteract the GHG-induced increase. Decreases in soil moisture are common but regionally dependent and interannual variability changes show considerable structure. Snow cover and sea-ice retreat. A PNA-like anomaly in mean sea-level pressure with an enhanced Aleutian low in northern winter is associated with the tropical shift in precipitation regime. The interannual variability of mean sea-level pressure generally decreases with largest decreases in the tropical Indian ocean region. Changes to the ocean thermal structure are associated with a spin-down of the Atlantic thermohaline circulation together with a decrease in its variability. The effect of aerosol forcing, although modest, differs from that for most other quantities in that it does not act primarily to counteract the GHG forcing effect. The barotropic stream function in the ocean exhibits modest change in the north Pacific but accelerating changes in much of the Southern Ocean and particularly in the north Atlantic where the gyre spins down in conjunction with the decrease in the thermohaline circulation. The results differ in non-trivial ways from earlier equilibrium 2 × CO₂ results with the CCCma model as a consequence of the coupling to a fully three-dimensional ocean model and the evolving nature of the forcing. Received: 24 September 1998 / Accepted: 8 October 1999     

Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections

A fast simple climate modelling approach is developed for predicting and helping to understand general circulation model (GCM) simulations. We show that the simple model reproduces the GCM results accurately, for global mean surface air temperature change and global-mean heat uptake projections from 9 GCMs in the fifth coupled model inter-comparison project (CMIP5). This implies that understanding gained from idealised CO₂ step experiments is applicable to policy-relevant scenario projections. Our approach is conceptually simple. It works by using the climate response to a CO₂ step change taken directly from a GCM experiment. With radiative forcing from non-CO₂ constituents obtained by adapting the Forster and Taylor method, we use our method to estimate results for CMIP5 representative concentration pathway (RCP) experiments for cases not run by the GCMs. We estimate differences between pairs of RCPs rather than RCP anomalies relative to the pre-industrial state. This gives better results because it makes greater use of available GCM projections. The GCMs exhibit differences in radiative forcing, which we incorporate in the simple model. We analyse the thus-completed ensemble of RCP projections. The ensemble mean changes between 1986–2005 and 2080–2099 for global temperature (heat uptake) are, for RCP8.5: 3.8 K (2.3 × 10²⁴ J); for RCP6.0: 2.3 K (1.6 × 10²⁴ J); for RCP4.5: 2.0 K (1.6 × 10²⁴ J); for RCP2.6: 1.1 K (1.3 × 10²⁴ J). The relative spread (standard deviation/ensemble mean) for these scenarios is around 0.2 and 0.15 for temperature and heat uptake respectively. We quantify the relative effect of mitigation action, through reduced emissions, via the time-dependent ratios (change in RCPx)/(change in RCP8.5), using changes with respect to pre-industrial conditions. We find that the effects of mitigation on global-mean temperature change and heat uptake are very similar across these different GCMs.     

On the role of domain size and resolution in the simulations with the HIRHAM region climate model

We investigate the simulated temperature and precipitation of the HIRHAM regional climate model using systematic variations in domain size, resolution and detailed location in a total of eight simulations. HIRHAM was forced by ERA-Interim boundary data and the simulations focused on higher resolutions in the range of 5.5–12 km. HIRHAM outputs of seasonal precipitation and temperature were assessed by calculating distributed model errors against a higher resolution data set covering Denmark and a 0.25° resolution data set covering Europe. Furthermore the simulations were statistically tested against the Danish data set using bootstrap statistics. The results from the distributed validation of precipitation showed lower errors for the winter (DJF) season compared to the spring (MAM), fall (SON) and, in particular, summer (JJA) seasons for both validation data sets. For temperature, the pattern was in the opposite direction, with the lowest errors occurring for the JJA season. These seasonal patterns between precipitation and temperature are seen in the bootstrap analysis. It also showed that using a 4,000 × 2,800 km simulation with an 11 km resolution produced the highest significance levels. Also, the temperature errors were more highly significant than precipitation. In similarly sized domains, 12 of 16 combinations of variables, observation validation data and seasons showed better results for the highest resolution domain, but generally the most significant improvements were seen when varying the domain size.     

Modeling of a severe winter drought in eastern China using different initial and lateral boundary forcing datasets

To highlight the compatibility of climate model simulation and proxy reconstruction at different timescales, a timescale separation merging method combining proxy records and climate model simulations is presented. Annual mean surface temperature anomalies for the last millennium (851–2005 AD) at various scales over the land of the Northern Hemisphere were reconstructed with 2° × 2° spatial resolution, using an optimal interpolation (OI) algorithm. All target series were decomposed using an ensemble empirical mode decomposition method followed by power spectral analysis. Four typical components were obtained at inter-annual, decadal, multidecadal, and centennial timescales. A total of 323 temperature-sensitive proxy chronologies were incorporated after screening for each component. By scaling the proxy components using variance matching and applying a localized OI algorithm to all four components point by point, we obtained merged surface temperatures. Independent validation indicates that the most significant improvement was for components at the inter-annual scale, but this became less evident with increasing timescales. In mid-latitude land areas, 10–30% of grids were significantly corrected at the inter-annual scale. By assimilating the proxy records, the merged results reduced the gap in response to volcanic forcing between a pure reconstruction and simulation. Difficulty remained in verifying the centennial information and quantifying corresponding uncertainties, so additional effort should be devoted to this aspect in future research.     

A Comparison Study of Tropical Pacific Ocean State Estimation： Low-Resolution Assimilation vs. High-Resolution Simulation

A comparison study is performed to contrast the improvements in the tropical Pacific oceanic state of a low-resolution model respectively via data assimilation and by an increase in horizontal resolution.A low resolution model (LR) (1°lat by 2°lon) and a high-resolution model (HR) (0.5°lat by 0.5°lon) are employed for the comparison. The authors perform 20-yr numerical experiments and analyze the annual mean fields of temperature and salinity. The results indicate that the low-resolution model with data assimilation behaves better than the high-resolution model in the estimation of ocean large-scale features.From 1990 to 2000, the average of HR's RMSE (root-mean-square error) relative to independent Tropical Atmosphere Ocean project (TAO) mooring data at randomly selected points is 0.97℃ compared to a RMSE of 0.56℃ for LR with temperature assimilation. Moreover, the LR with data assimilation is more frugal in computation. Although there is room to improve the high-resolution model, the low-resolution model with data assimilation may be an advisable choice in achieving a more realistic large-scale state of the ocean at the limited level of information provided by the current observational system.     

Signal analysis of the atmospheric mean 500/1000 hPa temperature north of 55°N between 1949 and 1994

 The lower tropospheric mean temperature 500/1000 hPa is examined in the Northern Hemisphere high-latitude region north of 55°N with regard to a climate change signal due to anthropogenic climate forcing as a supplement to previous studies which concentrated on near surface temperatures. An observational data set of the German Weather Service is compared with several model simulations including different scenarios of greenhouse gas and sulfate aerosol forcing derived from the two recent versions of the coupled climate model in Hamburg, ECHAM-3/LSG and ECHAM-4/OPYC. The signal analysis is based on the optimal fingerprint method, which supplies a detection variable with optimal signal-to-noise ratio. The natural variability measures are derived from the corresponding long-term control experiments. From 1970 onward, we find high trend pattern analogies between the observational data and the greenhouse-gas induced model simulations. The fingerprint of this common temperature signal consists of a predominate warming with maximum over Siberia and a weak cooling over the North Atlantic reaching an estimated significance level of about 1%. A non-optimized approach has also been examined, leading to even closer trend pattern correlations. The additional forcing by sulfate aerosols decreases the correlation of this climate change simulation with the observations. The natural variability constitutes about 50% of the conforming trend patterns. The signal-to-noise ratio is best over the oceans while the tropospheric temperatures over the land masses are contaminated by strong noise. The trend pattern correlations look the same for both model versions and several ensemble members with different noise realizations. Received: 4 January 1999 / Accepted: 11 April 2001     

A simple model perturbed physics study of the simulated climate sensitivity uncertainty and its relation to control climate biases

In this study the relationship between climate model biases in the control climate and the simulated climate sensitivity are discussed on the basis of perturbed physics ensemble simulations with a globally resolved energy balance (GREB) model. It is illustrated that the uncertainties in the simulated climate sensitivity (estimated by the transient response to CO₂ forcing scenarios in the twenty first century or idealized 2 × CO₂ forcing experiments) can be conceptually split into two parts: a direct effect of the perturbed physics on the climate sensitivity independent of the control mean climate and an indirect effect of the perturbed physics by changing the control mean climate, which in turn changes the climate sensitivity, as the climate sensitivity itself is depending on the control climate. Biases in the control climate are negatively correlated with the climate sensitivity (colder climates have larger sensitivities), if no physics are perturbed. Perturbed physics that lead to warmer control climate, would in average also lead to larger climate sensitivities, if the control climate is held at the observed reference climate by flux corrections. Thus the effects of control biases and perturbed physics are opposing each other and are partially cancelling each other out. In the GREB model the biases in the control climate are the more important effect for the regional climate sensitivity uncertainties, but for the global mean climate sensitivity both, the biases in the control climate and the perturbed physics, are equally important.