High-resolution simulations of global climate, part 2: effects of increased greenhouse cases

We report results from the highest-resolution simulations of global warming yet performed with an atmospheric general circulation model. We compare the climatic response to increased greenhouse gases of the National Center for Atmospheric Research (NCAR) climate model, CCM3, at T42 and T170 resolutions (horizontal grid spacing of 300 and 75 km respectively). All simulations use prescribed sea surface temperatures (SST). Simulations of the climate of 2100 ad use SSTs based on those from NCAR coupled model, Climate System Model (CSM). We find that the global climate sensitivity and large-scale patterns of climate change are similar at T42 and T170. However, there are important regional scale differences that arise due to better representation of topography and other factors at high resolution. Caution should be exercised in interpreting specific features in our results both because we have performed climate simulations using a single atmospheric general circulation model and because we used with prescribed sea surface temperatures rather than interactive ocean and sea-ice models.     

Changes in frost, snow and Baltic sea ice by the end of the twenty-first century based on climate model projections for Europe

Changes in indices related to frost and snow in Europe by the end of the twenty-first century were analyzed based on experiments performed with seven regional climate models (RCMs). All the RCMs regionalized information from the same general circulation model (GCM), applying the IPCC-SRES A2 radiative forcing scenario. In addition, some simulations used SRES B2 radiative forcing and/or boundary conditions provided by an alternative GCM. Ice cover over the Baltic Sea was examined using a statistical model that related the annual maximum extent of ice to wintertime coastal temperatures. Fewer days with frost and snow, shorter frost seasons, a smaller liquid water equivalent of snow, and milder sea ice conditions were produced by all model simulations, irrespective of the forcing scenario and the driving GCM. The projected changes have implications across a diverse range of human activities. Details of the projections were subject to differences in RCM design, deviations between the boundary conditions of the driving GCMs, uncertainties in future emissions and random effects due to internal climate variability. A larger number of GCMs as drivers of the RCMs would most likely have resulted in somewhat wider ranges in the frost, snow and sea ice estimates than those presented in this paper.     

Potential future changes in the Indian summer monsoon due to greenhouse warming: analysis of mechanisms in a global time-slice experiment

In this study the potential impact of the anticipated increase in the greenhouse gas concentrations on different aspects of the Indian summer monsoon is investigated, focusing on the role of the mechanisms leading to these changes. Both changes in the mean aspects of the Indian summer monsoon and changes in its interannual variability are considered. This is done on the basis of a global time-slice experiment being performed with the ECHAM4 AGCM at a high horizontal resolution of T106. The experiment consists of two 30-year simulations, one representing the present-day climate (period: 1970–1999) and one representing the future climate (period: 2060–2089). The time-slice experiment predicts an intensification of the mean rainfall associated with the Indian summer monsoon due to the general warming, while the future changes in the large-scale flow indicate a weakening of the monsoon circulation in the upper troposphere and only little change in the lower troposphere. The intensification of the monsoon rainfall in the Indian region is related to an intensification of the atmospheric moisture transport into this region. The weakening of the monsoon flow is caused by a pronounced warming of the sea surface temperatures in the central and eastern tropical Pacific and the associated alterations of the Walker circulation. A future increase of the temperature difference between the Indian Ocean and central India as well as a future reduction of the Eurasian snow cover in spring would, by themselves, lead to a strengthening of the monsoon flow in the future. These two mechanisms compensate for the weakening of the low-level monsoon flow induced by the warming of the tropical Pacific. The time-slice experiment also predicts a future increase of the interannual variability of both the rainfall associated with the Indian summer monsoon and of the large-scale flow. A major part of this increase is accounted for by enhanced interannual variability of the sea surface temperatures in the central and eastern tropical Pacific.     

Interpreting observed northern hemisphere snow trends with large ensembles of climate simulations

Simulated variability and trends in Northern Hemisphere seasonal snow cover are analyzed in large ensembles of climate integrations of the National Center for Atmospheric Research’s Community Earth System Model. Two 40-member ensembles driven by historical radiative forcings are generated, one coupled to a dynamical ocean and the other driven by observed sea surface temperatures (SSTs) over the period 1981–2010. The simulations reproduce many aspects of the observed climatology and variability of snow cover extent as characterized by the NOAA snow chart climate data record. Major features of the simulated snow water equivalent (SWE) also agree with observations (GlobSnow Northern Hemisphere SWE data record), although with a lesser degree of fidelity. Ensemble spread in the climate response quantifies the impact of natural climate variability in the presence and absence of coupling to the ocean. Both coupled and uncoupled ensembles indicate an overall decrease in springtime snow cover that is consistent with observations, although springtime trends in most climate realizations are weaker than observed. In the coupled ensemble, a tendency towards excessive warming in wintertime leads to a strong wintertime snow cover loss that is not found in observations. The wintertime warming bias and snow cover reduction trends are reduced in the uncoupled ensemble with observed SSTs. Natural climate variability generates widely different regional patterns of snow trends across realizations; these patterns are related in an intuitive way to temperature, precipitation and circulation trends in individual realizations. In particular, regional snow loss over North America in individual realizations is strongly influenced by North Pacific SST trends (manifested as Pacific Decadal Oscillation variability) and by sea level pressure trends in the North Pacific/North Atlantic sectors.     

Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data

Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.     

Influence of the Eurasian snow cover on the Indian summer monsoon variability in observed climatologies and CMIP3 simulations

The present study is aimed at revisiting the possible influence of the winter/spring Eurasian snow cover on the subsequent Indian summer precipitation using several statistical tools including a maximum covariance analysis. The snow–monsoon relationship is explored using both satellite observations of snow cover and in situ measurements of snow depth, but also a subset of global coupled ocean–atmosphere simulations from the phase 3 of the Coupled Model Intercomparison Project (CMIP3) database. In keeping with former studies, the observations suggest a link between an east–west snow dipole over Eurasia and the Indian summer monsoon precipitation. However, our results indicate that this relationship is neither statistically significant nor stationary over the last 40 years. Moreover, the strongest signal appears over eastern Eurasia and is not consistent with the Blanford hypothesis whereby more snow should lead to a weaker monsoon. The twentieth century CMIP3 simulations provide longer timeseries to look for robust snow–monsoon relationships. The maximum covariance analysis indicates that some models do show an apparent influence of the Eurasian snow cover on the Indian summer monsoon precipitation, but the patterns are not the same as in the observations. Moreover, the apparent snow–monsoon relationship generally denotes a too strong El Niño-Southern Oscillation teleconnection with both winter snow cover and summer monsoon rainfall rather than a direct influence of the Eurasian snow cover on the Indian monsoon.     

CMIP5/AMIP GCM simulations of East Asian summer monsoon

The East Asian summer monsoon （EASM） is a distinctive component of the Asian climate system and critically influences the economy and society of the region.To understand the ability of AGCMs in capturing the major features of EASM,10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project （CMIP5/AMIP）,which used observational SST and sea ice to drive AGCMs during the period 1979-2008,were evaluated by comparing with observations and AMIP Ⅱ simulations.The results indicated that the multi-model ensemble （MME） of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation,and shows the best skill in EASM simulation,better than the AMIP Ⅱ MME.As for the Meiyu/Changma/Baiyu rainbelt,the intensity of rainfall is underestimated in all the models.The biases are caused by a weak western Pacific subtropical high （WPSH） and accompanying eastward southwesterly winds in group Ⅰ models,and by a too strong and west-extended WPSH as well as westerly winds in group Ⅱ models.Considerable systematic errors exist in the simulated seasonal migration of rainfall,and the notable northward jumps and rainfall persistence remain a challenge for all the models.However,the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index （WNPMI）.     

Climate model sensitivity to sea ice albedo parameterization

Summary Three one-year experimental simulations with the National Center for Atmospheric Research Community Climate Model (NCAR CCM) were performed with three sea ice albedo parameterizations and compared with control run results to examine their impact on polar surface temperature, planetary albedo and clouds. The first integration utilized sea ice albedos of the Arctic Basin for the spring and summer of 1977 derived from defence Meteorological Satellite Imagery (DMSP). The second simulation employed prescribed lead and melt pond fractions and an albedo weighting scheme. The third simulation involved the coupling of an interactive sea ice/snow albedo parameterization made a function of surface state.Results show that prescribed, and assumed true satellite sea ice albedos produced higher planetary albedos than those calculated with the standard CCM sea ice albedo scheme in the control run. As a result, lower temperatures (up to 0.5 K) and increased cloudiness are generated for the Arctic region. The standard CCM sea ice albedo scheme is used as an adjustment to maintain normal temperatures for the polar oceans. The radiative impact of leads and melt ponds warmed sea ice regions only for short time periods. The third scheme generated markedly lower planetary albedos (reductions of 0.07 to 0.17) and higher surface temperatures (up to 2.0 K) than control values.The CCM simulates a gradual decrease in spring and summer Arctic cloud cover whereas observations show a sharp spring increase. Examination of the CCM code, particularly the cloud parameterization, is required to address this problem.With 12 Figures     

Arctic sea ice decay simulated for a CO2-induced temperature rise

A large scale numerical time-dependent model of sea ice that takes into account the heat fluxes in and out of the ice, the seasonal occurrence of snow, and ice motions has been used in an experiment to determine the response of the Arctic Ocean ice pack to a warming of the atmosphere. The degree of warming specified is that expected for a doubling of atmospheric carbon dioxide with its associated greenhouse effect, a condition that could occur before the middle of the next century. The results of three 5-year simulations with a warmer atmosphere and varied boundary conditions were: (1) that in the face of a 5 K surface atmospheric temperature increase the ice pack disappeared completely in August and September but reformed in the central Arctic Ocean in mid fall; (2) that the simulations were moderately dependent on assumptions concerning cloud cover; and (3) that even when atmospheric temperature increases of 6–9 K were combined with an order-of-magnitude increase in the upward heat flux from the ocean, the ice still reappeared in winter. It should be noted that a year-round ice-free Arctic Ocean has apparently not existed for a million years or more.Currently on leave, working for the World Meteorological Organization in Geneva, Switzerland, on the World Climate Programme.The calculations for this work were carried out while both authors were at the National Center for Atmospheric Research (NCAR), which is sponsored by the National Science Foundation.     

Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3

Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice?Cocean?Cterrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1?year. In all regimes, ice thickness has high potential predictability for at least 2?years.     

Simulating the diurnal cycle of rainfall in global climate models: resolution versus parameterization

The effects of horizontal resolution and the treatment of convection on simulation of the diurnal cycle of precipitation during boreal summer are analyzed in several innovative weather and climate model integrations. The simulations include: season-long integrations of the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with explicit clouds and convection; year-long integrations of the operational Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts at three resolutions (125, 39 and 16 km); seasonal simulations of the same model at 10 km resolution; and seasonal simulations of the National Center for Atmospheric Research (NCAR) low-resolution climate model with and without an embedded two-dimensional cloud-resolving model in each grid box. NICAM with explicit convection simulates best the phase of the diurnal cycle, as well as many regional features such as rainfall triggered by advancing sea breezes or high topography. However, NICAM greatly overestimates mean rainfall and the magnitude of the diurnal cycle. Introduction of an embedded cloud model within the NCAR model significantly improves global statistics of the seasonal mean and diurnal cycle of rainfall, as well as many regional features. However, errors often remain larger than for the other higher-resolution models. Increasing resolution alone has little impact on the timing of daily rainfall in IFS with parameterized convection, yet the amplitude of the diurnal cycle does improve along with the representation of mean rainfall. Variations during the day in atmospheric prognostic fields appear quite similar among models, suggesting that the distinctive treatments of model physics account for the differences in representing the diurnal cycle of precipitation.     

Radiative effect of black carbon aerosol on seasonal variation in snow depth in the Northern-Hemisphere

In this research, we studied the effects of black carbon (BC) aerosol radiative forcing on seasonal variation in the Northern Hemisphere (NH) using numerical simulations with the NASA finite-volume General Circulation Model (fvGCM) forced with monthly varying three-dimensional aerosol distributions from the Goddard Ozone Chemistry Aerosol Radiation and Transport Model (GOCART). The results show that atmospheric warming due to black carbon aerosols subsequently warm the atmosphere and land surfaces, especially those over Eurasia. As a result, the snow depth in Eurasia was greatly reduced in late winter and spring, and the reduction in snow cover decreased the surface albedo. Our surface energy balance analysis shows that the surface warming due to aerosol absorption causes early snow melting and further increases surface-atmosphere warming through snow/ice albedo feedback. Therefore, BC aerosol forcing may be an important factor affecting the snow/ice albedo in the NH.     

Test of a simple two-layer parameterisation to simulate the energy balance and temperature of a snow pack

Summary  Reasonably simple yet realistic modelling schemes simulating the heat and mass balance within a snow pack are required to provide the necessary boundary conditions for meteorological and hydrological models. An improvement to a one-layer snow energy balance model (UEB, Tarboton etal., 1995) is proposed to better simulate snow surface and snow pack temperatures and, as a result, snowmelt. The modified scheme is assessed against measured snow data from the WINTEX field campaign during spring 1997 in northern Finland, and compared with results from a complex multi-layer snow energy balance scheme. The results show that separation of a one-layer representation into two snow layers and a soil layer enables a more realistic simulation of soil and snow temperatures as well as of the snow surface temperature. The two-layer and the multi-layer snow schemes yielded comparable results for internal processes in the snow whenever the simulation was carried out under similar boundary forcing. The modified scheme is proposed for use as a sub-scheme in meteorological or hydrological models, or as a tool for simulating spatially-variable snowmelt and the surface energy balance during seasonal snow cover. Received November 18, 1999 Revised June 17, 2000     

Local and remote responses to opposite Ross Sea ice anomalies: a numerical experiment with the CPTEC/INPE AGCM

This work examines the near-surface responses, in the Southern Hemisphere atmosphere, to a reduction and an excess of sea ice cover in the Ross Sea. Large ensembles (60 members) of the Atmospheric General Circulation Model of the Center for Weather Forecast and Climate Studies (AGCM-CPTEC) are used for this purpose. Locally, when the sea ice cover decreases (increases), heat fluxes, temperature, and pressure increase (decreases). A principal component analysis of temperature and geopotential height identifies the potential remote connections. We have found three main results: first, an association between the sea ice cover in the Ross Sea and a wave train that resembles the Pacific South American (PSA) pattern; second, a relationship between temperatures in the Ross Sea and in the southern South America; and third, an apparent correspondence between reduced sea ice cover in the Ross Sea and the subtropical jet over Australia.     

Global 60?km simulations with CCAM: evaluation over the tropics

A six-member ensemble of 60?km resolution global atmospheric simulations has been performed for studying future climate scenarios of Pacific island nations. The simulations were performed using the CSIRO Conformal Cubic Atmospheric Model (CCAM), driven by bias-corrected sea surface temperatures (SSTs) provided by six Coupled Model Intercomparison Project phase 3 global climate models (GCMs) from the Intergovernmental Panel on Climate Change Fourth Assessment Report for the period 1971–2100. This paper focuses on results for the representation of the current climate in the tropical region, a region where the “cold tongue” problem is apparent in all host GCMs. The SST bias-correction and the fine horizontal resolution employed in the CCAM simulations produce a significant improvement over the host GCMs in the rainfall patterns for the transient seasons March–April–May and September–October–November, and a moderate improvement for December–January–February and June–July–August. CCAM also simulates improved rainfall patterns over the South Pacific Convergence Zone. The performance of other tropical features, such as El Ni?o Southern Oscillation and the Walker circulation, is also evaluated.     

Simulations of Eurasian Winter Temperature Trends in Coupled and Uncoupled CFSv2

Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled(atmosphere-only) and coupled(ocean–atmosphere) simulations by the Climate Forecast System, version 2(CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project(AMIP) runs forced with mean seasonal cycles of sea surface temperature(SST)and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually,and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time.The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.     

Simulation of sea ice in FGOALS-g2: Climatology and late 20th century changes

Sea ice is an important component in the Earth’s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projection of future changes. This paper evaluates the simulation of sea ice by the Flexible Global Ocean-Atmosphere-Land System model Grid-point Version 2 (FGOALS-g2), in the fifth phase of the Coupled Model Inter-comparison Project (CMIP5), with a focus on historical experiments and late 20th century simulation. Through analysis, we find that FGOALS-g2 produces reasonable Arctic and Antarctic sea ice climatology and variability. Sea ice spatial distribution and seasonal change characteristics are well captured. The decrease of Arctic sea ice extent in the late 20th century is reproduced in simulations, although the decrease trend is lower compared with observations. Simulated Antarctic sea ice shows a reasonable distribution and seasonal cycle with high accordance to the amplitude of winter-summer changes. Large improvement is achieved as compared with FGOALS-g1.0 in CMIP3. Diagnosis of atmospheric and oceanic forcing on sea ice reveals several shortcomings and major aspects to improve upon in the future: (1) ocean model improvements to remove the artificial island at the North Pole; (2) higher resolution of the atmosphere model for better simulation of important features such as, among others, the Icelandic Low and westerly wind over the Southern Ocean; and (3) ocean model improvements to accurately receive freshwater input from land, and higher resolution for resolving major water channels in the Canadian Arctic Archipelago.     

Ice and climate modeling: An editorial essay

The growth and decay of ice sheets are driven by forces affecting the seasonal cycles of snowfall and snowmelt. The external forces are likely to be variations in the earth's orbit which cause differences in the solar radiation received. Radiational control of snowmelt is modulated by the seasonal cycles of snow albedo and cloud cover. The effects of orbital changes can be magnified by feedbacks involving atmospheric CO₂ content, ocean temperatures and desert areas. Climate modeling of the causes of the Pleistocene ice ages involves modeling the interactions of all components of the climate system; snow, sea ice, glacier ice, the ocean, the atmosphere, and the solid earth. Such modeling is also necessary for interpreting oxygen isotope records from ice and ocean as paleoclimatic evidence.     

Some features of sea ice formation in Antarctic coastal waters

Considered are the peculiarities of fast ice formation in the Antarctic coastal waters. It is noted that the fine-crystalline ice with the chaotic orientation of crystals is mainly developed in the surface layers of the ice cover as well as the ice formed due to the infiltration of the sea water and its subsequent freezing in the lower layers of the snow cover. It is demonstrated that under the conditions of coastal Antarctic, the lamination of the structure during the period of ice cover formation and its subsequent development is the result of heavy precipitation in the form of snow and the formation of the large amount of snow sludge and crystals of intrawater ice (frazil ice) on the open water. The main distinctive feature of the Antarctic sea ice is its seasonal stratification with the formation of the surface layer of recrystallized ice and underlying destructive layers including the water interlayer in the ice column. The provision of the safety of overice movement of machinery requires the development of methods of continuous remote control of the snow-ice stratum of the fast ice.     

Snow contribution to springtime atmospheric predictability over the second half of the twentieth century

A set of global atmospheric simulations has been performed with the ARPEGE-Climat model in order to quantify the contribution of realistic snow conditions to seasonal atmospheric predictability in addition to that of a perfect sea surface temperature (SST) forcing. The focus is on the springtime boreal hemisphere where the combination of a significant snow cover variability and an increasing solar radiation favour the potential snow influence on the surface energy budget. The study covers the whole 1950?C2000 period through the use of an original snow mass reanalysis based on an off-line land surface model and possibly constrained by satellite snow cover observations. Two ensembles of 10-member AMIP-type experiments have been first performed with relaxed versus free snow boundary conditions. The nudging towards the monthly snow mass reanalysis significantly improves both potential and actual predictability of springtime surface air temperature over Central Europe and North America. Yet, the impact is confined to the lower troposphere and there is no clear improvement in the predictability of the large-scale atmospheric circulation. Further constraining the prescribed snow boundary conditions with satellite observations does not change much the results. Finally, using the snow reanalysis only for initializing the model on March 1st also leads to a positive impact on predicted low-level temperatures but with a weaker amplitude and persistence. A conditional skill approach as well as some selected case studies provide some guidelines for interpreting these results and suggest that an underestimated snow cover variability and a misrepresentation of ENSO teleconnections may hamper the benefit of an improved snow initialization in the ARPEGE-Climat model.