Abstract

Simulation of key features of the Arctic atmosphere in the Community Climate System Model, version 4 (CCSM4) is evaluated against observational and reanalysis datasets for the present-day (1981–2005). Surface air temperature, sea level pressure, cloud cover and phase, precipitation and evaporation, the atmospheric energy budget, and lower-tropospheric stability are evaluated. Simulated surface air temperatures are found to be slightly too cold when compared with the 40-yr ECMWF Re-Analysis (ERA-40). Spatial patterns and temporal variability are well simulated. Evaluation of the sea level pressure demonstrates some large biases, most noticeably an under simulation of the Beaufort High during spring and autumn. Monthly Arctic-wide biases of up to 13 mb are reported. Cloud cover is underpredicted for all but summer months, and cloud phase is demonstrated to be different from observations. Despite low cloud cover, simulated all-sky liquid water paths are too high, while ice water path was generally too low. Precipitation is found to be excessive over much of the Arctic compared to ERA-40 and the Global Precipitation Climatology Project (GPCP) estimates. With some exceptions, evaporation is well captured by CCSM4, resulting in P − E estimates that are too high. CCSM4 energy budget terms show promising agreement with estimates from several sources. The most noticeable exception to this is the top of the atmosphere (TOA) fluxes that are found to be too low while surface fluxes are found to be too high during summer months. Finally, the lower troposphere is found to be too stable when compared to ERA-40 during all times of year but particularly during spring and summer months.

Abstract

This study presents an overview of the El Niño–Southern Oscillation (ENSO) phenomenon and Pacific decadal variability (PDV) simulated in a multicentury preindustrial control integration of the NCAR Community Climate System Model version 4 (CCSM4) at nominal 1° latitude–longitude resolution. Several aspects of ENSO are improved in CCSM4 compared to its predecessor CCSM3, including the lengthened period (3–6 yr), the larger range of amplitude and frequency of events, and the longer duration of La Niña compared to El Niño. However, the overall magnitude of ENSO in CCSM4 is overestimated by ~30%. The simulated ENSO exhibits characteristics consistent with the delayed/recharge oscillator paradigm, including correspondence between the lengthened period and increased latitudinal width of the anomalous equatorial zonal wind stress. Global seasonal atmospheric teleconnections with accompanying impacts on precipitation and temperature are generally well simulated, although the wintertime deepening of the Aleutian low erroneously persists into spring. The vertical structure of the upper-ocean temperature response to ENSO in the north and south Pacific displays a realistic seasonal evolution, with notable asymmetries between warm and cold events. The model shows evidence of atmospheric circulation precursors over the North Pacific associated with the “seasonal footprinting mechanism,” similar to observations. Simulated PDV exhibits a significant spectral peak around 15 yr, with generally realistic spatial pattern and magnitude. However, PDV linkages between the tropics and extratropics are weaker than observed.

Abstract

The simulation characteristics of the Asian–Australian monsoon are documented for the Community Climate System Model, version 4 (CCSM4). This is the first part of a two part series examining monsoon regimes in the global tropics in the CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 [Community Atmosphere Model, version 4, (CAM4)] to deduce differences in the monsoon simulations run with observed sea surface temperatures (SSTs) and with ocean–atmosphere coupling. These simulations are also compared to a previous version of the model (CCSM3) to evaluate progress. In general, monsoon rainfall is too heavy in the uncoupled AMIP run with CAM4, and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Most aspects of the Asian–Australian monsoon simulations are improved in CCSM4 compared to CCSM3. There is a reduction of the systematic error of rainfall over the tropical Indian Ocean for the South Asian monsoon, and well-simulated connections between SSTs in the Bay of Bengal and regional South Asian monsoon precipitation. The pattern of rainfall in the Australian monsoon is closer to observations in part because of contributions from the improvements of the Indonesian Throughflow and diapycnal diffusion in CCSM4. Intraseasonal variability of the Asian–Australian monsoon is much improved in CCSM4 compared to CCSM3 both in terms of eastward and northward propagation characteristics, though it is still somewhat weaker than observed. An improved simulation of El Niño in CCSM4 contributes to more realistic connections between the Asian–Australian monsoon and El Niño–Southern Oscillation (ENSO), though there is considerable decadal and century time scale variability of the strength of the monsoon–ENSO connection.

Abstract

This is the second part of a two part series studying simulation characteristics of the Community Climate System Model, version 4 (CCSM4) for various monsoon regimes around the global tropics. Here, the West African, East African, North American, and South American monsoons are documented in CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 (CAM4), to deduce differences in the monsoon simulations run with observed SSTs and with ocean–atmosphere coupling. These simulations are also compared to a previous version of the coupled model (CCSM3) to evaluate progress. In most, but not all instances, monsoon rainfall is too heavy in the uncoupled AMIP run with the Community Atmosphere Model, version 4 (CAM4), and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Some aspects of the monsoon simulations are improved in CCSM4 compared to CCSM3. Early-season rainfall in the West African monsoon is better simulated in CAM4 than in CCSM4 presumably because of the specification of SSTs in the Gulf of Guinea, but the Sahel rainfall season is captured better in CCSM4 as are the African easterly jet and the tropical easterly jet. Improvements in the simulation of the Sahel rainy season (July, August, and September) in CCSM4 compared with CCSM3 are significant, but problems remain in the simulation of the early season (May and June) in association with the misrepresentation of eastern Atlantic (Gulf of Guinea) SSTs. Precipitation distributions and the southwesterly low-level inflow in the North American monsoon are improved in CCSM4 compared to CCSM3. Both CAM4 and CCSM4 reproduce the seasonal evolution of rainfall over the South American monsoon region, but the location of maximum rainfall is misplaced to the northeast in both models.

Abstract

The new Community Climate System Model, version 4 (CCSM4), provides a powerful tool to understand and predict the earth’s climate system. Several aspects of the Southern Ocean in the CCSM4 are explored, including the surface climatology and interannual variability, simulation of key climate water masses (Antarctic Bottom Water, Subantarctic Mode Water, and Antarctic Intermediate Water), the transport and structure of the Antarctic Circumpolar Current, and interbasin exchange via the Agulhas and Tasman leakages and at the Brazil–Malvinas Confluence. It is found that the CCSM4 has varying degrees of accuracy in the simulation of the climate of the Southern Ocean when compared with observations. This study has identified aspects of the model that warrant further analysis that will result in a more comprehensive understanding of ocean–atmosphere–ice dynamics and interactions that control the earth’s climate and its variability.

Abstract

The authors summarize the twenty-first-century Arctic climate simulated by NCAR’s Community Climate System Model, version 4 (CCSM4). Under a strong radiative forcing scenario, the model simulates a much warmer, wetter, cloudier, and stormier Arctic climate with considerably less sea ice and a fresher Arctic Ocean. The high correlation among the variables composing these changes—temperature, precipitation, cloudiness, sea level pressure (SLP), and ice concentration—suggests that their close coupling collectively represents a fingerprint of Arctic climate change. Although the projected changes in CCSM4 are generally consistent with those in other GCMs, several noteworthy features are identified. Despite more global warming in CCSM4, Arctic changes are generally less than under comparable greenhouse forcing in CCSM3, as represented by Arctic amplification (16% weaker) and the date of a seasonally ice-free Arctic Ocean (20 years later). Autumn is the season of the most pronounced Arctic climate change among all the primary variables. The changes are very similar across the five ensemble members, although SLP displays the largest internal variability. The SLP response exhibits a significant trend toward stronger extreme Arctic cyclones, implying greater wave activity that would promote coastal erosion. Based on a commonly used definition of the Arctic (the area encompassing the 10°C July air temperature isotherm), the region shrinks by about 40% during the twenty-first century, in conjunction with a nearly 10-K warming trend poleward of 70°N. Despite this pronounced long-term warming, CCSM4 simulates a hiatus in the secular Arctic climate trends during a decade-long stretch in the 2040s and to a lesser extent in the 2090s. These pauses occur despite averaging over five ensemble members and are remarkable because they happen under the most extreme greenhouse-forcing scenario and in the most climatically sensitive region of the world.

Abstract

This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels.

Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia.

New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m⁻² for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.

Abstract

The representation of permafrost and seasonally frozen ground and their projected twenty-first century trends is assessed in the Community Climate System Model, version 4 (CCSM4) and the Community Land Model version 4 (CLM4). The combined impact of advances in CLM and a better Arctic climate simulation, especially for air temperature, improve the permafrost simulation in CCSM4 compared to CCSM3. Present-day continuous plus discontinuous permafrost extent is comparable to that observed [12.5 × 10⁶ versus (11.8–14.6) × 10⁶ km²], but active-layer thickness (ALT) is generally too thick and deep ground (>15 m) temperatures are too warm in CCSM4. Present-day seasonally frozen ground area is well simulated (47.5 × 10⁶ versus 48.1 × 10⁶ km²). ALT and deep ground temperatures are much better simulated in offline CLM4 (i.e., forced with observed climate), which indicates that the remaining climate biases, particularly excessive high-latitude snowfall biases, degrade the CCSM4 permafrost simulation.

Near-surface permafrost (NSP) and seasonally frozen ground (SFG) area are projected to decline substantially during the twenty-first century [representative concentration projections (RCPs); RCP8.5: NSP by 9.0 × 10⁶ km², 72%, SFG by 7.1 × 10⁶, 15%; RCP2.6: NSP by 4.1 × 10⁶, 33%, SFG by 2.1 × 10⁶, 4%]. The permafrost degradation rate is slower (2000–50) than in CCSM3 by ~35% because of the improved soil physics. Under the low RCP2.6 emissions pathway, permafrost state stabilizes by 2100, suggesting that permafrost related feedbacks could be minimized if greenhouse emissions could be reduced. The trajectory of permafrost degradation is affected by CCSM4 climate biases. In simulations with this climate bias ameliorated, permafrost degradation in RCP8.5 is lower by ~29%. Further reductions of Arctic climate biases will increase the reliability of permafrost projections and feedback studies in earth system models.

Abstract

The equilibrium solution of a fully coupled general circulation model with present-day orbital forcing is compared to the solution of the same model with the orbital forcing from 115 000 years ago. The difference in snow accumulation between these two simulations has a pattern and a magnitude comparable to the ones inferred from reconstructions for the last glacial inception. This is a major improvement over previous similar studies, and the increased realism is attributed to the higher spatial resolution in the atmospheric model, which allows for a more accurate representation of the orography of northern Canada and Siberia. The analysis of the atmospheric heat budget reveals that, as postulated by Milankovitch’s hypothesis, the only necessary positive feedback is the snow–albedo feedback, which is initiated by reduced melting of snow and sea ice in the summer. However, this positive feedback is almost fully compensated by an increased meridional heat transport in the atmosphere and a reduced concentration of low Arctic clouds. In contrast to similar previous studies, the ocean heat transport remains largely unchanged. This stability of the northern North Atlantic circulation is explained by the regulating effect of the freshwater import through the Nares Strait and Northwest Passage and the spiciness import by the North Atlantic Current.

Abstract

The El Niño–Southern Oscillation (ENSO) response to anthropogenic climate change is assessed in the following 1° nominal resolution Community Climate System Model, version 4 (CCSM4) Coupled Model Intercomparison Project phase 5 (CMIP5) simulations: twentieth-century ensemble, preindustrial control, twenty-first-century projections, and stabilized 2100–2300 “extension runs.” ENSO variability weakens slightly with CO₂; however, various significance tests reveal that changes are insignificant at all but the highest CO₂ levels. Comparison with the 1850 control simulation suggests that ENSO changes may become significant on centennial time scales; the lack of signal in the twentieth- versus twenty-first-century ensembles is due to their limited duration. Changes to the mean state are consistent with previous studies: a weakening of the subtropical wind stress curl, an eastward shift of the tropical convective cells, a reduction in the zonal SST gradient, and an increase in vertical thermal stratification take place as CO₂ increases. The extratropical thermocline deepens throughout the twenty-first century, with the tropical thermocline changing slowly in response. The adjustment time scale is set by the relevant ocean dynamics, and the delay in its effect on ENSO variability is not diminished by increasing ensemble size. The CCSM4 results imply that twenty-first-century simulations may simply be too short for identification of significant tropical variability response to climate change. An examination of atmospheric teleconnections, in contrast, shows that the remote influences of ENSO do respond rapidly to climate change in some regions, particularly during boreal winter. This suggests that changes to ENSO impacts may take place well before changes to oceanic tropical variability itself become significant.