Sensitivity of the tropical Pacific seasonal cycle and ENSO to changes in mean state induced by a surface heat flux adjustment in CCSM3

The influence of mean climate on the seasonal cycle and the El Ni?o-Southern Oscillation (ENSO) in the tropical Pacific climate is investigated using the Climate Community System Model Version 3 (CCSM3). An empirical time-independent surface heat flux adjustment over the tropical ocean is applied to the oceanic component of CCSM3. In comparison with the control run, the heat flux-adjusted run simulates a more realistic mean climate not only for the sea surface temperature (SST) but also for wind stress and precipitation. Even though the heat flux adjustment is time-independent, the seasonal cycles of SST, wind stress and precipitation over the equatorial eastern Pacific are more realistic in the flux-adjusted simulation. Improvements in the representation of the ENSO variability in the heat flux-adjusted simulation include that the Nino3.4 SST index is less regular than a strong biennial oscillation in the control run. But some deficiencies also arise. For example, the amplitude of the ENSO variability is reduced in the flux-adjusted run. The impact of the mean climate on ENSO prediction is further examined by performing a series of monthly hindcasts from 1982 to 1998 using CCSM3 with and without the heat flux adjustment. The flux-adjusted hindcasts show slightly higher predictive skill than the unadjusted hindcasts with January initial conditions at lead times of 7?C9?months and July initial conditions at lead times of 9?C11?months. However, their differences during these months are not statistically significant.     

Impact of ocean model resolution on CCSM climate simulations

The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to examine how resolved ocean fronts and eddies impact the simulation of large-scale climate. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5)—the forerunner to CCSM4. Two experiments are reported here. The control experiment is a 155-year present-day climate simulation using a 0.5° atmosphere component (zonal resolution 0.625 meridional resolution 0.5°; land surface component at the same resolution) coupled to ocean and sea-ice components with zonal resolution of 1.2° and meridional resolution varying from 0.27° at the equator to 0.54° in the mid-latitudes. The second simulation uses the same atmospheric and land-surface models coupled to eddy-resolving 0.1° ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming with a global mean surface temperature increase of about 0.2?°C relative to the control. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The sea surface temperature gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the interannual temperature variability is increased with the resolved eddies, and a notable increases in the amplitude of the El Ni?o and the Southern Oscillation is also detected. Changes in global temperature anomaly teleconnections and local air-sea feedbacks are also documented and show large changes in ocean–atmosphere coupling. In particular, local air-sea feedbacks are significantly modified by the increased ocean resolution. In the high-resolution simulation in the extra-tropics there is compelling evidence of stronger forcing of the atmosphere by SST variability arising from ocean dynamics. This coupling is very weak or absent in the low-resolution model.     

GCM response of the mean zonal surface heat and water budgets to a global sea surface temperature anomaly

Two sets of sensitivity experiments are presented. The first set consists of three 100-day integrations with perpetual January conditions: a reference integration, an integration with a uniform +2 K sea surface temperature (SST) anomaly, and an integration with an anomaly of reverse sign. The second set is similar, but with perpetual July conditions. The zonal mean components of the water and heat budgets at the surface are studied over ocean and over land separately.The values of the reference integration are very close to those obtained when the model is run with annual cycle conditions, and reasonably close to observed values over 60° N−40° S ocean. The SST anomalies produce generally a stronger response in July than in January. This response is linear for the averages over ocean, but if we consider the zonal distribution, only the longwave radiation, latent and sensible heat exhibit a linear response. The model response to temperature increase consists of an enhancement of the water cycle over ocean, and a heat transfer from the ocean, through the latent heat, to the continent. In January, we observe also a water transfer from the ocean to the continent. As a consequence of the heat transfer, the land surface temperature increases by the same magnitude as the SST.     

An efficient climate model with a 3D ocean and statistical–dynamical atmosphere*

We describe a coupled climate model of intermediate complexity designed for use in global warming experiments. The atmospheric component is a two-dimensional (zonally averaged) statistical-dynamical model based on the Goddard Institute for Space Study's atmospheric general circulation model (GCM). In contrast with energy-balance models used in some climate models of intermediate complexity, this model includes full representation of the hydrological and momentum cycles. It also has parameterizations of the main physical processes, including a sophisticated radiation code. The ocean component is a coarse resolution ocean GCM with simplified global geometry based on the Geophysical Fluid Dynamics Laboratory modular ocean model. Because of the simplified geometry the resolution in the western boundary layers can be readily increased compared to conventional coarse resolution models, without increasing the model's computational requirements in a significant way. The ocean model's efficiency is also greatly increased by using a moderate degree of asynchronous coupling between the oceanic momentum and tracer fields. We demonstrate that this still allows an accurate simulation of transient behavior, including the seasonal cycle. A 100 years simulation with the model requires less than 8 hours on a state-of the art workstation. The main novelty of the model is therefore a combination of computational efficiency, statistical-dynamical atmosphere and 3D ocean. Long-term present-day climate simulations are carried out using the coupled model with and without flux adjustments, and with either the Gent-McWilliams (GM) parametrization scheme or horizontal diffusion (HD) in the ocean. Deep ocean temperatures systematically decrease in the runs without flux adjustment. We demonstrate that the mismatch between heat transports in the uncoupled states of two models is the main cause for the systematic drift. In addition, changes in the circulation and sea-ice formation also contribute to the drift. Flux adjustments in the freshwater fluxes are shown to have a stabilizing effect on the thermohaline circulation in the model, whereas the adjustments in the heat fluxes tend to weaken the global "conveyor". To evaluate the model's response to transient external forcing global warming simulations are also carried out with the flux-adjusted version of the coupled model. The coupled model reproduces reasonably well the behavior of more sophisticated coupled GCMs for both current climate and for the global warming scenarios.     

Future changes in daily summer temperature variability: driving processes and role for temperature extremes

Anthropogenic greenhouse gas emissions are expected to lead to more frequent and intense summer temperature extremes, not only due to the mean warming itself, but also due to changes in temperature variability. To test this hypothesis, we analyse daily output of ten PRUDENCE regional climate model scenarios over Europe for the 2071–2100 period. The models project more frequent temperature extremes particularly over the Mediterranean and the transitional climate zone (TCZ, between the Mediterranean to the south and the Baltic Sea to the north). The projected warming of the uppermost percentiles of daily summer temperatures is found to be largest over France (in the region of maximum variability increase) rather than the Mediterranean (where the mean warming is largest). The underlying changes in temperature variability may arise from changes in (1) interannual temperature variability, (2) intraseasonal variability, and (3) the seasonal cycle. We present a methodology to decompose the total daily variability into these three components. Over France and depending upon the model, the total daily summer temperature variability is projected to significantly increase by 20–40% as a result of increases in all three components: interannual variability (30–95%), seasonal variability (35–105%), and intraseasonal variability (10–30%). Variability changes in northern and southern Europe are substantially smaller. Over France and parts of the TCZ, the models simulate a progressive warming within the summer season (corresponding to an increase in seasonal variability), with the projected temperature change in August exceeding that in June by 2–3 K. Thus, the most distinct warming is superimposed upon the maximum of the current seasonal cycle, leading to a higher intensity of extremes and an extension of the summer period (enabling extreme temperatures and heat waves even in September). The processes driving the variability changes are different for the three components but generally relate to enhanced land–atmosphere coupling and/or increased variability of surface net radiation, accompanied by a strong reduction of cloudiness, atmospheric circulation changes and a progressive depletion of soil moisture within the summer season. The relative contribution of these processes differs substantially between models.     

Modeling the impact of urbanization on the local and regional climate in Yangtze River Delta, China

The Yangtze River Delta Economic Belt is one of the most active and developed areas in China and has experienced quick urbanization with fast economic development. The weather research and forecasting model (WRF), with a single-layer urban canopy parameterization scheme, is used to simulate the influence of urbanization on climate at local and regional scales in this area. The months January and July, over a 5-year period (2003–2007), were selected to represent the winter and summer climate. Two simulation scenarios were designed to investigate the impacts of urbanization: (1) no urban areas and (2) urban land cover determined by MODIS satellite observations in 2005. Simulated near-surface temperature, wind speed and specific humidity agree well with the corresponding measurements. By comparing the simulations of the two scenarios, differences in near-surface temperature, wind speed and precipitation were quantified. The conversion of rural land (mostly irrigation cropland) to urban land cover results in significant changes to near-surface temperature, humidity, wind speed and precipitation. The mean near-surface temperature in urbanized areas increases on average by 0.45?±?0.43°C in winter and 1.9?±?0.55°C in summer; the diurnal temperature range in urbanized areas decreases on average by 0.13?±?0.73°C in winter and 0.55?±?0.84°C in summer. Precipitation increases about 15% over urban or leeward areas in summer and changes slightly in winter. The urbanization impact in summer is stronger and covers a larger area than that in winter due to the regional east-Asian monsoon climate characterized by warm, wet summers and cool, dry winters.     

Climate model benchmarking with glacial and mid-Holocene climates

Past climates provide a test of models’ ability to predict climate change. We present a comprehensive evaluation of state-of-the-art models against Last Glacial Maximum and mid-Holocene climates, using reconstructions of land and ocean climates and simulations from the Palaeoclimate Modelling and Coupled Modelling Intercomparison Projects. Newer models do not perform better than earlier versions despite higher resolution and complexity. Differences in climate sensitivity only weakly account for differences in model performance. In the glacial, models consistently underestimate land cooling (especially in winter) and overestimate ocean surface cooling (especially in the tropics). In the mid-Holocene, models generally underestimate the precipitation increase in the northern monsoon regions, and overestimate summer warming in central Eurasia. Models generally capture large-scale gradients of climate change but have more limited ability to reproduce spatial patterns. Despite these common biases, some models perform better than others.     

Multiyear hindcast simulations of summer monsoon over South Asia using a nested regional climate model��BCC_RegCM1.0

Multiyear (1983?C2006) hindcast simulation of summer monsoon over South Asia has been carried out using the regional climate model of the Beijing Climate Centre (BCC_RegCM1.0). The regional climate model (hereafter BCC RCM) is nested into the global climate model of the Beijing Climate Centre BCC_CGCM1.0 (here after CGCM). The regional climate model is initialized on 01 May and integrated up to the end of the September for 24?years. Compared to the driving CGCM the BCC RCM reproduces reasonably well the intensity and magnitude of the large-scale features associated with the South Asia summer monsoon such as the upper level anticyclone at 200?hPa, the mid-tropospheric warming over the Tibetan plateau, the surface heat low and the 850?hPa moisture transport from ocean to the land. Both models, i.e., BCC RCM and the driving CGCM overestimates (underestimates) the 850?hPa southwesterly flow over the northern (southern) Arabian Sea. Moreover, both models overestimate the seasonal mean precipitation over much of the South Asia region compared to the observations. However, the precipitation biases are significantly reduced in the BCC RCM simulations. Furthermore, both models simulate reasonably the interannual variability of the summer monsoon over India. The precipitation index simulated by BCC RCM shows significant correlation (0.62) with the observed one. The BCC RCM simulates reasonably well the spatial and temporal variation of the precipitation and surface air temperature compared to the driving CGCM. Further, the temperature biases are significantly reduced (1?C4°C) in the BCC RCM simulations. The simulated vertical structure of the atmosphere show biases above the four sub-regions, however, these biases are significantly reduced in the BCC RCM simulations compared to the driving CGCM. Compared to the driving CGCM, the evolution processes of the onset of summer monsoon, e.g., the meridional temperature gradient and the vertical wind shear are well simulated by the BCC RCM. The 24-year simulations also show that with a little exception the BCC RCM is capable to reproduce the monsoon active and break phases and the intraseasonal precipitation variation over the Indian subcontinent.     

Oceanic Origin of A Recent La Nina-Like Trend in the Tropical Pacific

Global ocean temperature has been rising since the late 1970s at a speed unprecedented during the past century of recordkeeping.This accelerated warming has profound impacts not only on the marine ecosystem and oceanic carbon uptake but also on the global water cycle and climate.During this rapid warming period,the tropical Pacific displays a pronounced La Nin a-like trend,characterized by an intensification of west-east SST gradient and of atmospheric zonal overturning circulation,namely the Walker circulation.This La Nin a-like trend differs from the El Nin o-like trend in warm climate projected by most climate models,and cannot be explained by responses of the global water cycle to warm climate.The results of this study indicate that the intensification of the zonal SST gradient and the Walker circulation are associated with recent strengthening of the upper-ocean meridional overturning circulation.     

A nonlinear impulse response model of the coupled carbon cycle-climate system (NICCS)

 Impulse-response-function (IRF) models are designed for applications requiring a large number of climate change simulations, such as multi-scenario climate impact studies or cost-benefit integrated-assessment studies. The models apply linear response theory to reproduce the characteristics of the climate response to external forcing computed with sophisticated state-of-the-art climate models like general circulation models of the physical ocean-atmosphere system and three-dimensional oceanic-plus-terrestrial carbon cycle models. Although highly computer efficient, IRF models are nonetheless capable of reproducing the full set of climate-change information generated by the complex models against which they are calibrated. While limited in principle to the linear response regime (less than about 3 ^∘C global-mean temperature change), the applicability of the IRF model presented has been extended into the nonlinear domain through explicit treatment of the climate system's dominant nonlinearities: CO₂ chemistry in ocean water, CO₂ fertilization of land biota, and sublinear radiative forcing. The resultant nonlinear impulse-response model of the coupled carbon cycle-climate system (NICCS) computes the temporal evolution of spatial patterns of climate change for four climate variables of particular relevance for climate impact studies: near-surface temperature, cloud cover, precipitation, and sea level. The space-time response characteristics of the model are derived from an EOF analysis of a transient 850-year greenhouse warming simulation with the Hamburg atmosphere-ocean general circulation model ECHAM3-LSG and a similar response experiment with the Hamburg carbon cycle model HAMOCC. The model is applied to two long-term CO₂ emission scenarios, demonstrating that the use of all currently estimated fossil fuel resources would carry the Earth's climate far beyond the range of climate change for which reliable quantitative predictions are possible today, and that even a freezing of emissions to present-day levels would cause a major global warming in the long term. Received: 28 January 2000 / Accepted: 9 March 2001     

Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 2: A diurnally coupled CGCM

Coupled ocean atmosphere general circulation models (GCM) are typically coupled once every 24 h, excluding the diurnal cycle from the upper ocean. Previous studies attempting to examine the role of the diurnal cycle of the upper ocean and particularly of diurnal SST variability have used models unable to resolve the processes of interest. In part 1 of this study a high vertical resolution ocean GCM configuration with modified physics was developed that could resolve the diurnal cycle in the upper ocean. In this study it is coupled every 3 h to atmospheric GCM to examine the sensitivity of the mean climate simulation and aspects of its variability to the inclusion of diurnal ocean-atmosphere coupling. The inclusion of the diurnal cycle leads to a tropics wide increase in mean sea surface temperature (SST), with the strongest signal being across the equatorial Pacific where the warming increases from 0.2°C in the central and western Pacific to over 0.3°C in the eastern equatorial Pacific. Much of this warming is shown to be a direct consequence of the rectification of daily mean SST by the diurnal variability of SST. The warming of the equatorial Pacific leads to a redistribution of precipitation from the Inter tropical convergence zone (ITCZ) toward the equator. In the western Pacific there is an increase in precipitation between Papa new guinea and 170°E of up to 1.2 mm/day, improving the simulation compared to climatology. Pacific sub tropical cells are increased in strength by about 10%, in line with results of part 1 of this study, due to the modification of the exchange of momentum between the equatorially divergent Ekman currents and the geostropic convergence at depth, effectively increasing the dynamical response of the tropical Pacific to zonal wind stresses. During the spring relaxation of the Pacific trade winds, a large diurnal cycle of SST increases the seasonal warming of the equatorial Pacific. When the trade winds then re-intensify, the increase in the dynamical response of the ocean leads to a stronger equatorial upwelling. These two processes both lead to stronger seasonal basin scale feedbacks in the coupled system, increasing the strength of the seasonal cycle of the tropical Pacific sector by around 10%. This means that the diurnal cycle in the upper ocean plays a part in the coupled feedbacks between ocean and atmosphere that maintain the basic state and the timing of the seasonal cycle of SST and trade winds in the tropical Pacific. The Madden–Julian Oscillation (MJO) is examined by use of a large scale MJO index, lag correlations and composites of events. The inclusion of the diurnal cycle leads to a reduction in overall MJO activity. Precipitation composites show that the MJO is stronger and more coherent when the diurnal cycle of coupling is resolved, with the propagation and different phases being far more distinct both locally and to larger lead times across the tropical Indo-Pacific. Part one of this study showed that that diurnal variability of SST is modulated by the MJO and therefore increases the intraseasonal SST response to the different phases of the MJO. Precipitation-based composites of SST variability confirm this increase in the coupled simulations. It is argued that including this has increased the thermodynamical coupling of the ocean and atmosphere on the timescale of the MJO (20–100 days), accounting for the improvement in the MJO strength and coherency seen in composites of precipitation and SST. These results show that the diurnal cycle of ocean–atmosphere interaction has profound impact on a range of up-scale variability in the tropical climate and as such, it is an important feature of the modelled climate system which is currently either neglected or poorly resolved in state of the art coupled models.     

全球变暖背景下中国东部气候变迁及其对物候的影响

鉴于我国东部地区对全球气候变化的高度敏感性,本文应用1960~2014年的CRU和HadISST等全球地表（地球表面的简称,包括陆地和海洋表面,下同）温度再分析资料,采用地理等温线和春、秋季（代表月地表温度）时间的变迁速度等指标,分析了全球和中国东部地区的气候变化速度以及春、秋季物候的变化。结果显示:（1）自1960年以来,全球地表温度呈现十分清晰的上升趋势,其中,北半球（陆地）比南半球（海洋）变暖更显著,地理等温线向两极方向迁移;（2）南、北半球的春（秋）季明显提前（滞后）;（3）中国东部地表温度呈快速上升趋势,陆地升温虽普遍快于海洋,但东部海域升温快于相邻的陆地,地理等温线总体向北迁移,海域的春、秋季物候变化较陆地显著;（4）中国东部生物物候受气候变化影响明显,海域地理等温线的北移受到沿岸地形的抑制,海洋生物适应气候变化的能力受到限制,海洋生态系统及生物多样性将面临气候变化带来的显著风险。     

The seasonal climatic simulation of 9000 years before present by using the IAP atmospheric general circulation model

The seasonal cycle of the climate of 9000 years before present was simulated with the IAP two-level atmospheric general circulation model. The incoming solar radiation was specified from the orbital parameters for 9000 years Ago. The boundary conditions of that time were prescribed to the present value because of the small differences between the two. The change in radiation makes temperature to be higher in summer and lower in winter over large areas of the land; and the increased temperature contrast between the land and the ocean strengthens the summer monsoon circulation and increases the precipitation over there. The asymmetry of temperature change between the Northern Hemisphere and the Southern Hemisphere and between summer and winter still exists, which agrees with that get from the previous perpetual experiments.     

EC-Earth V2.2: description and validation of a new seamless earth system prediction model

EC-Earth, a new Earth system model based on the operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF), is presented. The performance of version 2.2 (V2.2) of the model is compared to observations, reanalysis data and other coupled atmosphere–ocean-sea ice models. The large-scale physical characteristics of the atmosphere, ocean and sea ice are well simulated. When compared to other coupled models with similar complexity, the model performs well in simulating tropospheric fields and dynamic variables, and performs less in simulating surface temperature and fluxes. The surface temperatures are too cold, with the exception of the Southern Ocean region and parts of the Northern Hemisphere extratropics. The main patterns of interannual climate variability are well represented. Experiments with enhanced CO₂ concentrations show well-known responses of Arctic amplification, land-sea contrasts, tropospheric warming and stratospheric cooling. The global climate sensitivity of the current version of EC-Earth is slightly less than 1?K/(W?m^?2). An intensification of the hydrological cycle is found and strong regional changes in precipitation, affecting monsoon characteristics. The results show that a coupled model based on an operational seasonal prediction system can be used for climate studies, supporting emerging seamless prediction strategies.     

Regional simulations to quantify land use change and irrigation impacts on hydroclimate in the California Central Valley

In this study, the influence of land use change and irrigation in the California Central Valley is quantified using the Pennsylvania State University/National Center for Atmospheric Research fifth generation Mesoscale Model (MM5) coupled with the Community Land Model version 3 (CLM3). The simulations were forced with modern-day and presettlement land use types at 30-km spatial resolution for the period 1 October 1995 to 30 September 1996. This study shows that land use change has significantly altered the structure of the planetary boundary layer (PBL) that affects near-surface temperature. In contrast, many land-use change studies indicate that albedo and evapotranspiration variations are the key processes influencing climate at local-to-regional scales. Our modeling results show that modern-day daily maximum near-surface air temperature (Tmax) has decreased due to agricultural expansion since presettlement. This decrease is caused by weaker sensible heat flux resulting from the lower surface roughness lengths associated with modern-day crops. The lower roughness lengths in the Central Valley also result in stronger winds that lead to a higher PBL. The higher PBL produces stronger sensible heat flux, causing nighttime warming. In addition to land use change, cropland irrigation has also affected hydroclimate processes within the California Central Valley. We generated a 10-member MM5-CLM3 ensemble simulation, where each ensemble member was forced by a fixed volumetric soil water content (SWC) between 3% and 30%, at 3% intervals, over the irrigated areas during a spring?Csummer growing season, 1 March to 31 August 1996. The results show that irrigation lowers the modern-day cropland surface temperature. Daytime cooling is produced by irrigation-related evaporation enhancement. This increased evaporation also dominates the nighttime surface cooling process. Surface cooling and the resulting weaker sensible heat flux further lower the near-surface air temperature. Thus, irrigation strengthens the daytime near-surface air temperature reduction that is caused by land use change, and a similar temperature change is seen for observations over irrigated cropland. Based on our modeling results, the nighttime near-surface warming induced by land use change is alleviated by low-intensity irrigation (17%?<?SWC?<?19%), but such warming completely reverses to a cooling effect under high-intensity irrigation (SWC?>?19%). The land use changes discussed in this study are commonly observed in many regions of the world, and the physical processes identified here can be used to better understand temperature variations over other areas with similar land cover changes.     

Variability and trends of sub-continental scale surface climate in the twentieth century. Part II: AOGCM simulations

This work presents an analysis of simulated temperature and precipitation variability and trends throughout the twentieth century over 22 land regions of sub-continental scale in the HADCM3 and HADCM2 (two realizations) coupled models. Regional temperature biases in the HADCM3 and HADCM2 are mostly in the range of -5 K to +3 K for the seasonal averages and -3 K to +2 K for the annual average. Seasonal precipitation biases are mostly in the range of -50% to 75% of present day precipitation, with a tendency in both models to overpredict cold season precipitation. Except for cold season temperature in mid- and high-latitude Northern Hemisphere regions, the average climatology of the HADCM2 and HADCM3 is of comparable quality despite the lack of an ocean flux adjustment in the HADCM3. Both models show warming trends of magnitude in line with observations, although the observed inter-regional patterns of warming trend are not well reproduced. Measures of temperature and precipitation interannual to interdecadal variability in the models are in general agreement with observations except for Northern Hemisphere summer temperature variability, which is overestimated. The models somewhat underestimate the inter-decadal variations in interannual variability measures observed during the century and overestimate the range of anomalies. Both models tend to overpredict the occurrences of short persistences (1-3 years) and underpredict the occurrence and maximum length of long persistences (greater than three years), which is an indication of a deficiency in the simulation of long-lived anomaly regimes. Compared to observations, the models produce a higher magnitude of temporal anomaly correlation across regions and correlation between temperature and precipitation anomalies for a given region. This suggests that local processes that may be effective in decoupling the observed regional anomalies are not captured well. Overall, the variability measures in the HADCM2 and HADCM3 are of similar quality, indicating that the use of a flux correction in the HADCM2 does not strongly affect the regional variability characteristics of the model.     

Attribution of twentieth century temperature change to natural and anthropogenic causes

  We analyse possible causes of twentieth century near-surface temperature change. We use an “optimal detection” methodology to compare seasonal and annual data from the coupled atmosphere-ocean general circulation model HadCM2 with observations averaged over a range of spatial and temporal scales. The results indicate that the increases in temperature observed in the latter half of the century have been caused by warming from anthropogenic increases in greenhouse gases offset by cooling from tropospheric sulfate aerosols rather than natural variability, either internal or externally forced. We also find that greenhouse gases are likely to have contributed significantly to the warming in the first half of the century. In addition, natural effects may have contributed to this warming. Assuming one particular reconstruction of total solar irradiance to be correct implies, when we take the seasonal cycle into account, that solar effects have contributed significantly to the warming observed in the early part of the century, regardless of any relative error in the amplitudes of the anthropogenic forcings prescribed in the model. However, this is not the case with an alternative reconstruction of total solar irradiance, based more on the amplitude than the length of the solar cycle. We also find evidence for volcanic influences on twentieth century near-surface temperatures. The signature of the eruption of Mount Pinatubo is detected using annual-mean data. We also find evidence for a volcanic influence on warming in the first half of the century associated with a reduction in mid-century volcanism. Received: 24 January 2000 / Accepted: 20 April 2000     

Higher precision estimates of regional polar warming by ensemble regression of climate model projections

This study presents projections of twenty-first century wintertime surface temperature changes over the high-latitude regions based on the third Coupled Model Inter-comparison Project (CMIP3) multi-model ensemble. The state-dependence of the climate change response on the present day mean state is captured using a simple yet robust ensemble linear regression model. The ensemble regression approach gives different and more precise estimated mean responses compared to the ensemble mean approach. Over the Arctic in January, ensemble regression gives less warming than the ensemble mean along the boundary between sea ice and open ocean (sea ice edge). Most notably, the results show 3?°C less warming over the Barents Sea (~7?°C compared to ~10?°C). In addition, the ensemble regression method gives projections that are 30?% more precise over the Sea of Okhostk, Bering Sea and Labrador Sea. For the Antarctic in winter (July) the ensemble regression method gives 2?°C more warming over the Southern Ocean close to the Greenwich Meridian (~7?°C compared to ~5?°C). Projection uncertainty was almost half that of the ensemble mean uncertainty over the Southern Ocean between 30° W to 90° E and 30?% less over the northern Antarctic Peninsula. The ensemble regression model avoids the need for explicit ad hoc weighting of models and exploits the whole ensemble to objectively identify overly influential outlier models. Bootstrap resampling shows that maximum precision over the Southern Ocean can be obtained with ensembles having as few as only six climate models.     

Evaluation of water and energy budgets in regional climate models applied over Europe

This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.     

Mechanisms for the land/sea warming contrast exhibited by simulations of climate change

The land/sea warming contrast is a phenomenon of both equilibrium and transient simulations of climate change: large areas of the land surface at most latitudes undergo temperature changes whose amplitude is more than those of the surrounding oceans. Using idealised GCM experiments with perturbed SSTs, we show that the land/sea contrast in equilibrium simulations is associated with local feedbacks and the hydrological cycle over land, rather than with externally imposed radiative forcing. This mechanism also explains a large component of the land/sea contrast in transient simulations as well. We propose a conceptual model with three elements: (1) there is a spatially variable level in the lower troposphere at which temperature change is the same over land and sea; (2) the dependence of lapse rate on moisture and temperature causes different changes in lapse rate upon warming over land and sea, and hence a surface land/sea temperature contrast; (3) moisture convergence over land predominantly takes place at levels significantly colder than the surface; wherever moisture supply over land is limited, the increase of evaporation over land upon warming is limited, reducing the relative humidity in the boundary layer over land, and hence also enhancing the land/sea contrast. The non-linearity of the Clausius–Clapeyron relationship of saturation specific humidity to temperature is critical in (2) and (3). We examine the sensitivity of the land/sea contrast to model representations of different physical processes using a large ensemble of climate model integrations with perturbed parameters, and find that it is most sensitive to representation of large-scale cloud and stomatal closure. We discuss our results in the context of high-resolution and Earth-system modelling of climate change.