Abstract

The thermodynamic sea ice code in a coupled atmosphere-mixed layer ocean GCM has been altered to allow the presence of open water within an ice pack (leads) and a prescribed turbulent oceanic heat flux at the ice bottom. Two experiments with the GCM are then performed: one with leads included and one without. A comparison between the two model runs is presented, in addition to a comparison between observations and the simulation with leads. Selected sea ice and atmospheric variables in the high-latitude Northern Hemisphere are analyzed to assess the sensitivity of these climatic components to the presence of leads and to identify feedback mechanisms that are introduced by leads.

The inclusion of leads causes Northern Hemispheric sea ice concentration to decrease in every season, with year-round statistically significant reductions at the highest latitude band (81°N). Using the improved sea ice code, the model's simulation of sea ice concentration in the central Arctic is consistent with observations in every season. Simulated summertime sea ice concentration at 81°N averages 93.8%, which agrees well with observations. There is a pronounced longitudinal variation to the lead fraction in summer, with the smallest values (0.01) neat the Canadian Archipelago and the largest (0.25) north of the East Siberian Sea. Consistent with observations, the model produces wintertime turbulent sensible heat fluxes over leads that are one to two orders of magnitude larger than over adjacent sea ice and of the opposite sign. Annual solar radiation absorption by leads in the central Arctic is 1.8 times as large as over adjacent sea ice, resulting in a summertime shortwave energy gain of over 2.5 W m⁻² at 8 1°N compared to the model run without leads.

The inclusion of leads causes thicker sea ice in every season, because the very rapid ice growth rate in the leads is translated into enhanced accretion at the bottom of adjacent sea ice once a prescribed minimum lead fraction is reached. As a result, the weaker conductive heat flux through the thicker ice causes the surface temperature to decrease in winter across the entire Arctic basin. In the lower troposphere, however, this effect is offset by vigorous sensible heat transport through the leads, resulting in warmer temperatures up to 700 mb in winter and spring.

Abstract

A coupled atmosphere–mixed layer ocean GCM (GENESIS2) is forced with altered orbital boundary conditions for paleoclimates warmer than modern (6 kyr BP) and colder than modern (115 kyr BP) in the high-latitude Northern Hemisphere. A pair of experiments is run for each paleoclimate, one with sea-ice dynamics and one without, to determine the climatic effect of ice motion and to estimate the climatic changes at these times. At 6 kyr BP the central Arctic ice pack thins by about 0.5 m and the atmosphere warms by 0.7 K in the experiment with dynamic ice. At 115 kyr BP the central Arctic sea ice in the dynamical version thickens by 2–3 m, accompanied by a 2 K cooling. The magnitude of these mean-annual simulated changes is smaller than that implied by paleoenvironmental evidence, suggesting that changes in other earth system components are needed to produce realistic simulations.

Contrary to previous simulations without atmospheric feedbacks, the sign of the dynamic sea-ice feedback is complicated and depends on the region, the climatic variable, and the sign of the forcing perturbation. Within the central Arctic, sea-ice motion significantly reduces the amount of ice thickening at 115 kyr BP and thinning at 6 kyr BP, thus serving as a strong negative feedback in both pairs of simulations. Ice motion causes the near-surface air to cool in both sets of experiments, however, thus representing a positive feedback at 115 kyr BP and a negative feedback at 6 kyr BP. The excess cooling with ice motion at 115 kyr BP is caused by the enhanced, advective spreading of the ice pack into the North Atlantic dominating over the warming tendency from the thinner central Arctic sea ice. The reduced atmospheric warming due to ice dynamics at 6 kyr BP is caused by sea-ice ridging, a thickening process that partially counteracts the orbitally induced atmospheric warming perturbation.

Abstract

Understanding extreme precipitation events in the current and future climate system is an important aspect of climate change for adaptation and mitigation purposes. The current study investigates extreme precipitation events over Madison, Wisconsin, during the late twentieth and late twenty-first centuries using 18 coupled ocean–atmosphere general circulation models that participated in the Coupled Model Intercomparison Project (CMIP3). An increase of ~10% is found in the multimodel average of annual precipitation received in Madison by the end of the twenty-first century, with the largest increases projected to occur during winter [December–February (DJF)] and spring [March–May (MAM)]. It is also found that the observed seasonal cycle of precipitation in Madison is not accurately captured by the models. The multimodel average shows a strong seasonal peak in May, whereas observations peak during midsummer. Model simulations also do not accurately capture the annual cycle of extreme precipitation events in Madison, which also peak in summer. Instead, the timing of model-simulated extreme events exhibits a bimodal distribution that peaks during spring and fall. However, spatial composites of average daily precipitation simulated by GCMs during Madison’s wettest 1% of precipitation events during the twentieth century strongly resemble the spatial pattern produced in observations. The role of specific humidity and vertically integrated moisture flux convergence (MFC) during extreme precipitation events in Madison is investigated in twentieth- and twenty-first-century simulations. Spatial composites of MFC during the wettest 1% of days during the twentieth-century simulations agree well with results from the North American Regional Reanalysis dataset (NARR), suggesting that synoptic-scale dynamics are vital to extreme precipitation events.

Abstract

This study diagnoses the changes in Arctic clouds simulated by the Community Climate System Model version 3 (CCSM3) in a transient 2 × CO₂ simulation. Four experiments—one fully coupled and three with prescribed SSTs and/or sea ice cover—are used to identify the mechanisms responsible for the projected cloud changes. The target simulation uses a T42 version of the CCSM3, in which the atmosphere is coupled to a dynamical ocean with mobile sea ice. This simulation is approximated by a T42 atmosphere-only integration using CCSM3’s atmospheric component [the Community Atmosphere Model version 3 (CAM3)] forced at its lower boundary with the changes in both SSTs and sea ice concentration from CCSM3’s 2 × CO₂ run. The authors decompose the combined effect of the higher SSTs and reduced sea ice concentration on the Arctic cloud response in this experiment by running two additional CAM3 simulations: one forced with modern SSTs and the projected sea ice cover changes in CCSM3 and the other forced with modern sea ice coverage and the projected changes in SSTs in CCSM3.

The results suggest that future increases in Arctic cloudiness simulated by CCSM3 are mostly attributable to two separate processes. Low cloud gains are primarily initiated locally by enhanced evaporation within the Arctic due to reduced sea ice, whereas cloud increases at middle and high levels are mostly driven remotely via greater meridional moisture transport from lower latitudes in a more humid global atmosphere. The enhanced low cloudiness attributable to sea ice loss causes large increases in cloud radiative forcing during the coldest months and therefore promotes even greater surface warming. Because CCSM3’s Arctic cloud response to greenhouse forcing is similar to other GCMs, the driving mechanisms identified here may be applicable to other models and could help to advance our understanding of likely changes in the vertical structure of polar clouds.

Abstract

This study tests the hypothesis that Arctic amplification (AA) of global warming remotely affects midlatitudes by promoting a weaker, wavier atmospheric circulation conducive to extreme weather. The investigation is based on the late twenty-first century over greater North America (20°–90°N, 50°–160°W) using 40 simulations from the Community Earth System Model Large Ensemble, spanning 1920–2100. AA is found to promote regionally varying ridging aloft (500 hPa) with strong seasonal differences reflecting the location of the strongest surface thermal forcing. During winter, maximum increases in future geopotential heights are centered over the Arctic Ocean, in conjunction with sea ice loss, but minimum height increases (troughing) occur to the south, over the continental United States. During summer the location of maximum height inflation shifts equatorward, forming an annular band across mid-to-high latitudes of the entire Northern Hemisphere. This band spans the continents, whose enhanced surface heating is aided by antecedent snow-cover loss and reduced terrestrial heat capacity. Through the thermal wind relationship, midtropospheric winds weaken on the equatorward flank of both seasonal ridging anomalies—mainly over Canada during winter and even more over the continental United States during summer—but strengthen elsewhere to form a dipole anomaly pattern in each season. Changes in circulation waviness, expressed as sinuosity, are inversely correlated with changes in zonal wind speed at nearly all latitudes, both in the projections and as observed during recent decades. Over the central United States during summer, the weaker and wavier flow promotes drying and enhanced heating, thus favoring more intense summer weather.

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

The Community Atmosphere Model, version 4 (CAM4), was released as part of the Community Climate System Model, version 4 (CCSM4). The finite volume (FV) dynamical core is now the default because of its superior transport and conservation properties. Deep convection parameterization changes include a dilute plume calculation of convective available potential energy (CAPE) and the introduction of convective momentum transport (CMT). An additional cloud fraction calculation is now performed following macrophysical state updates to provide improved thermodynamic consistency. A freeze-drying modification is further made to the cloud fraction calculation in very dry environments (e.g., the Arctic), where cloud fraction and cloud water values were often inconsistent in CAM3. In CAM4 the FV dynamical core further degrades the excessive trade-wind simulation, but reduces zonal stress errors at higher latitudes. Plume dilution alleviates much of the midtropospheric tropical dry biases and reduces the persistent monsoon precipitation biases over the Arabian Peninsula and the southern Indian Ocean. CMT reduces much of the excessive trade-wind biases in eastern ocean basins. CAM4 shows a global reduction in cloud fraction compared to CAM3, primarily as a result of the freeze-drying and improved cloud fraction equilibrium modifications. Regional climate feature improvements include the propagation of stationary waves from the Pacific into midlatitudes and the seasonal frequency of Northern Hemisphere blocking events. A 1° versus 2° horizontal resolution of the FV dynamical core exhibits superior improvements in regional climate features of precipitation and surface stress. Improvements in the fully coupled mean climate between CAM3 and CAM4 are also more substantial than in forced sea surface temperature (SST) simulations.

Abstract

Rising levels of carbon dioxide since the preindustrial era have likely contributed to an observed warming of the global surface, and observations show global greening and an expansion of boreal forests. This study reproduces observed climate and vegetation trends associated with rising CO₂ using a fully coupled atmosphere–ocean–land surface GCM with dynamic vegetation and decomposes the effects into physiological and radiative components. The simulated warming trend, strongest at high latitudes, was dominated by the radiative effect, although the physiological effect of CO₂ on vegetation (CO₂ fertilization) contributed to significant wintertime warming over northern Europe and central and eastern Asia. The net global greening of the model was primarily due to the physiological effect of increasing CO₂, while the radiative and physiological effects combined to produce a poleward expansion of the boreal forests. Observed and simulated trends in tree ring width are consistent with the enhancement of vegetation growth by the physiological effect of rising CO₂.

Abstract

As Earth’s largest collection of freshwater, the Laurentian Great Lakes have enormous ecological and socioeconomic value. Their basin has become a regional hotspot of climatic and limnological change, potentially threatening its vital natural resources. Consequentially, there is a need to assess the current state of climate models regarding their performance across the Great Lakes region and develop the next generation of high-resolution regional climate models to address complex limnological processes and lake–atmosphere interactions. In response to this need, the current paper focuses on the generation and analysis of a 20-member ensemble of 3-km National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) simulations for the 2014/15 cold season. The study aims to identify the model’s strengths and weaknesses; optimal configuration for the region; and the impacts of different physics parameterizations, coupling to a 1D lake model, time-variant lake-surface temperatures, and spectral nudging. Several key biases are identified in the cold-season simulations for the Great Lakes region, including an atmospheric cold bias that is amplified by coupling to a 1D lake model but diminished by applying the Community Atmosphere Model radiation scheme and Morrison microphysics scheme; an excess precipitation bias; anomalously early initiation of fall lake turnover and subsequent cold lake bias; excessive and overly persistent lake ice cover; and insufficient evaporation over Lakes Superior and Huron. The research team is currently addressing these key limitations by coupling NU-WRF to a 3D lake model in support of the next generation of regional climate models for the critical Great Lakes Basin.