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Yalin Fan, Isaac M. Held, Shian-Jiann Lin, and Xiaolan L. Wang

Abstract

Surface wind (U 10) and significant wave height (Hs) response to global warming are investigated using a coupled atmosphere–wave model by perturbing the sea surface temperatures (SSTs) with anomalies generated by the Working Group on Coupled Modeling (WGCM) phase 3 of the Coupled Model Intercomparison Project (CMIP3) coupled models that use the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4)/Special Report on Emissions Scenarios A1B (SRES A1B) scenario late in the twenty-first century.

Several consistent changes were observed across all four realizations for the seasonal means: robust increase of U 10 and Hs in the Southern Ocean for both the austral summer and winter due to the poleward shift of the jet stream; a dipole pattern of the U 10 and Hs with increases in the northeast sector and decreases at the midlatitude during boreal winter in the North Atlantic due to the more frequent occurrence of the positive phases of the North Atlantic Oscillation (NAO); and strong decrease of U 10 and Hs in the tropical western Pacific Ocean during austral summer, which might be caused by the joint effect of the weakening of the Walker circulation and the large hurricane frequency decrease in the South Pacific.

Changes of the 99th percentile U 10 and Hs are twice as strong as changes in the seasonal means, and the maximum changes are mainly dominated by the changes in hurricanes. Robust strong decreases of U 10 and Hs in the South Pacific are obtained because of the large hurricane frequency decrease, while the results in the Northern Hemisphere basins differ among the models. An additional sensitivity experiment suggests that the qualitative response of U 10 and Hs is not affected by using SST anomalies only and maintaining the radiative forcing unchanged (using 1980 values), as in this study.

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Isaac M. Held, Michael Winton, Ken Takahashi, Thomas Delworth, Fanrong Zeng, and Geoffrey K. Vallis

Abstract

The fast and slow components of global warming in a comprehensive climate model are isolated by examining the response to an instantaneous return to preindustrial forcing. The response is characterized by an initial fast exponential decay with an e-folding time smaller than 5 yr, leaving behind a remnant that evolves more slowly. The slow component is estimated to be small at present, as measured by the global mean near-surface air temperature, and, in the model examined, grows to 0.4°C by 2100 in the A1B scenario from the Special Report on Emissions Scenarios (SRES), and then to 1.4°C by 2300 if one holds radiative forcing fixed after 2100. The dominance of the fast component at present is supported by examining the response to an instantaneous doubling of CO2 and by the excellent fit to the model’s ensemble mean twentieth-century evolution with a simple one-box model with no long times scales.

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Yalin Fan, Shian-Jiann Lin, Isaac M. Held, Zhitao Yu, and Hendrik L. Tolman

Abstract

This study describes a 29-yr (1981–2009) global ocean surface gravity wave simulation generated by a coupled atmosphere–wave model using NOAA/GFDL’s High-Resolution Atmosphere Model (HiRAM) and the WAVEWATCH III surface wave model developed and used operationally at NOAA/NCEP. Extensive evaluation of monthly mean significant wave height (SWH) against in situ buoys, satellite altimeter measurements, and the 40-yr ECMWF Re-Analysis (ERA-40) show very good agreements in terms of magnitude, spatial distribution, and scatter. The comparisons with satellite altimeter measurements indicate that the SWH low bias in ERA-40 reanalysis has been improved in these model simulations. The model fields show a strong response to the North Atlantic Oscillation (NAO) in the North Atlantic and the Southern Oscillation index (SOI) in the Pacific Ocean that are well connected with the atmospheric responses. For the NAO in winter, the strongest subpolar wave responses are found near the northern Europe coast and the coast of Labrador rather than in the central-northern Atlantic where the wind response is strongest. Similarly, for the SOI in the Pacific Ocean, the wave responses are strongest in the northern Bering Sea and the Antarctic coast.

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Xianan Jiang, Ngar-Cheung Lau, Isaac M. Held, and Jeffrey J. Ploshay

Abstract

A model diagnosis has been performed on the nocturnal Great Plains low-level jet (LLJ), which is one of the key elements of the warm season regional climate over North America. The horizontal–vertical structure, diurnal phase, and amplitude of the LLJ are well simulated by an atmospheric general circulation model (AGCM), thus justifying a reevaluation of the physical mechanisms for the formation of the LLJ based on output from this model. A diagnosis of the AGCM data confirms that two planetary boundary layer (PBL) processes, the diurnal oscillation of the pressure gradient force and of vertical diffusion, are of comparable importance in regulating the inertial oscillation of the winds, which leads to the occurrence of maximum LLJ strength during nighttime. These two processes are highlighted in the theories for the LLJ proposed by Holton (1967) and Blackadar (1957). A simple model is constructed in order to study the relative roles of these two mechanisms. This model incorporates the diurnal variation of the pressure gradient force and vertical diffusion coefficients as obtained from the AGCM simulation. The results reveal that the observed diurnal phase and amplitude of the LLJ can be attributed to the combination of these two mechanisms. The LLJ generated by either Holton’s or Blackadar’s mechanism alone is characterized by an unrealistic meridional phase shift and weaker amplitude.

It is also shown that the diurnal phase of the LLJ exhibits vertical variations in the PBL, more clearly at higher latitudes, with the upper PBL wind attaining a southerly peak several hours earlier than the lower PBL. The simple model demonstrates that this phase tilt is due mainly to sequential triggering of the inertial oscillation from upper to lower PBL when surface cooling commences after sunset. At lower latitudes, due to the change of orientation of prevailing mean wind vectors and the longer inertial period, the inertial oscillation in the lower PBL tends to be interrupted by strong vertical mixing in the following day, whereas in the upper PBL, the inertial oscillation can proceed in a low-friction environment for a relatively longer duration. Thus, the vertical phase tilt initiated at sunset is less evident at lower latitudes.

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Gabriel A. Vecchi, Stephan Fueglistaler, Isaac M. Held, Thomas R. Knutson, and Ming Zhao

Abstract

Impacts of tropical temperature changes in the upper troposphere (UT) and the tropical tropopause layer (TTL) on tropical cyclone (TC) activity are explored. UT and lower TTL cooling both lead to an overall increase in potential intensity (PI), while temperature changes at 70 hPa and higher have negligible effect. Idealized experiments with a high-resolution global model show that lower temperatures in the UT are associated with increases in global and North Atlantic TC frequency, but modeled TC frequency changes are not significantly affected by TTL temperature changes nor do they scale directly with PI.

Future projections of hurricane activity have been made with models that simulate the recent upward Atlantic TC trends while assuming or simulating very different tropical temperature trends. Recent Atlantic TC trends have been simulated by (i) high-resolution global models with nearly moist-adiabatic warming profiles and (ii) regional TC downscaling systems that impose the very strong UT and TTL trends of the NCEP–NCAR reanalysis, an outlier among observational estimates. The impact of these differences in temperature trends on TC activity is comparable to observed TC changes, affecting assessments of the connection between hurricanes and climate. Therefore, understanding the character of and mechanisms behind changes in UT and TTL temperature is important to understanding past and projecting future TC activity changes. The UT and TTL temperature trends in the NCEP–NCAR reanalysis are unlikely to be accurate and likely drive spuriously positive TC and PI trends and an inflated connection between absolute surface temperature warming and TC activity increases.

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Thomas R. Knutson, Joseph J. Sirutis, Stephen T. Garner, Isaac M. Held, and Robert E. Tuleya

In this study, a new modeling framework for simulating Atlantic hurricane activity is introduced. The model is an 18-km-grid nonhydrostatic regional model, run over observed specified SSTs and nudged toward observed time-varying large-scale atmospheric conditions (Atlantic domain wavenumbers 0–2) derived from the National Centers for Environmental Prediction (NCEP) reanalyses. Using this “perfect large-scale model” approach for 27 recent August–October seasons (1980–2006), it is found that the model successfully reproduces the observed multidecadal increase in numbers of Atlantic hurricanes and several other tropical cyclone (TC) indices over this period. The correlation of simulated versus observed hurricane activity by year varies from 0.87 for basinwide hurricane counts to 0.41 for U.S. landfalling hurricanes. For tropical storm count, accumulated cyclone energy, and TC power dissipation indices the correlation is ~0.75, for major hurricanes the correlation is 0.69, and for U.S. landfalling tropical storms, the correlation is 0.57. The model occasionally simulates hurricanes intensities of up to category 4 (~942 mb) in terms of central pressure, although the surface winds (< 47 m s−1) do not exceed category-2 intensity. On interannual time scales, the model reproduces the observed ENSO-Atlantic hurricane covariation reasonably well. Some notable aspects of the highly contrasting 2005 and 2006 seasons are well reproduced, although the simulated activity during the 2006 core season was excessive. The authors conclude that the model appears to be a useful tool for exploring mechanisms of hurricane variability in the Atlantic (e.g., shear versus potential intensity contributions). The model may be capable of making useful simulations/projections of pre-1980 or twentieth-century Atlantic hurricane activity. However, the reliability of these projections will depend on obtaining reliable large-scale atmospheric and SST conditions from sources external to the model.

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Brian J. Soden, Isaac M. Held, Robert Colman, Karen M. Shell, Jeffrey T. Kiehl, and Christine A. Shields

Abstract

The extent to which the climate will change due to an external forcing depends largely on radiative feedbacks, which act to amplify or damp the surface temperature response. There are a variety of issues that complicate the analysis of radiative feedbacks in global climate models, resulting in some confusion regarding their strengths and distributions. In this paper, the authors present a method for quantifying climate feedbacks based on “radiative kernels” that describe the differential response of the top-of-atmosphere radiative fluxes to incremental changes in the feedback variables. The use of radiative kernels enables one to decompose the feedback into one factor that depends on the radiative transfer algorithm and the unperturbed climate state and a second factor that arises from the climate response of the feedback variables. Such decomposition facilitates an understanding of the spatial characteristics of the feedbacks and the causes of intermodel differences. This technique provides a simple and accurate way to compare feedbacks across different models using a consistent methodology. Cloud feedbacks cannot be evaluated directly from a cloud radiative kernel because of strong nonlinearities, but they can be estimated from the change in cloud forcing and the difference between the full-sky and clear-sky kernels. The authors construct maps to illustrate the regional structure of the feedbacks and compare results obtained using three different model kernels to demonstrate the robustness of the methodology. The results confirm that models typically generate globally averaged cloud feedbacks that are substantially positive or near neutral, unlike the change in cloud forcing itself, which is as often negative as positive.

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Gabriel A. Vecchi, Ming Zhao, Hui Wang, Gabriele Villarini, Anthony Rosati, Arun Kumar, Isaac M. Held, and Richard Gudgel

Abstract

Skillfully predicting North Atlantic hurricane activity months in advance is of potential societal significance and a useful test of our understanding of the factors controlling hurricane activity. In this paper, a statistical–dynamical hurricane forecasting system, based on a statistical hurricane model, with explicit uncertainty estimates, and built from a suite of high-resolution global atmospheric dynamical model integrations spanning a broad range of climate states is described. The statistical model uses two climate predictors: the sea surface temperature (SST) in the tropical North Atlantic and SST averaged over the global tropics. The choice of predictors is motivated by physical considerations, as well as the results of high-resolution hurricane modeling and statistical modeling of the observed record. The statistical hurricane model is applied to a suite of initialized dynamical global climate model forecasts of SST to predict North Atlantic hurricane frequency, which peaks during the August–October season, from different starting dates. Retrospective forecasts of the 1982–2009 period indicate that skillful predictions can be made from as early as November of the previous year; that is, skillful forecasts for the coming North Atlantic hurricane season could be made as the current one is closing. Based on forecasts initialized between November 2009 and March 2010, the model system predicts that the upcoming 2010 North Atlantic hurricane season will likely be more active than the 1982–2009 climatology, with the forecasts initialized in March 2010 predicting an expected hurricane count of eight and a 50% probability of counts between six (the 1966–2009 median) and nine.

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Brian Medeiros, Bjorn Stevens, Isaac M. Held, Ming Zhao, David L. Williamson, Jerry G. Olson, and Christopher S. Bretherton

Abstract

Cloud effects have repeatedly been pointed out as the leading source of uncertainty in projections of future climate, yet clouds remain poorly understood and simulated in climate models. Aquaplanets provide a simplified framework for comparing and understanding cloud effects, and how they are partitioned as a function of regime, in large-scale models. This work uses two climate models to demonstrate that aquaplanets can successfully predict a climate model’s sensitivity to an idealized climate change. For both models, aquaplanet climate sensitivity is similar to that of the realistic configuration. Tropical low clouds appear to play a leading role in determining the sensitivity. Regions of large-scale subsidence, which cover much of the tropics, are most directly responsible for the differences between the models. Although cloud effects and climate sensitivity are similar for aquaplanets and realistic configurations, the aquaplanets lack persistent stratocumulus in the tropical atmosphere. This, and an additional analysis of the cloud response in the realistically configured simulations, suggests the representation of shallow (trade wind) cumulus convection, which is ubiquitous in the tropics, is largely responsible for differences in the simulated climate sensitivity of these two models.

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Thomas R. Knutson, Joseph J. Sirutis, Gabriel A. Vecchi, Stephen Garner, Ming Zhao, Hyeong-Seog Kim, Morris Bender, Robert E. Tuleya, Isaac M. Held, and Gabriele Villarini

Abstract

Twenty-first-century projections of Atlantic climate change are downscaled to explore the robustness of potential changes in hurricane activity. Multimodel ensembles using the phase 3 of the Coupled Model Intercomparison Project (CMIP3)/Special Report on Emissions Scenarios A1B (SRES A1B; late-twenty-first century) and phase 5 of the Coupled Model Intercomparison Project (CMIP5)/representative concentration pathway 4.5 (RCP4.5; early- and late-twenty-first century) scenarios are examined. Ten individual CMIP3 models are downscaled to assess the spread of results among the CMIP3 (but not the CMIP5) models. Downscaling simulations are compared for 18-km grid regional and 50-km grid global models. Storm cases from the regional model are further downscaled into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model (9-km inner grid spacing, with ocean coupling) to simulate intense hurricanes at a finer resolution.

A significant reduction in tropical storm frequency is projected for the CMIP3 (−27%), CMIP5-early (−20%) and CMIP5-late (−23%) ensembles and for 5 of the 10 individual CMIP3 models. Lifetime maximum hurricane intensity increases significantly in the high-resolution experiments—by 4%–6% for CMIP3 and CMIP5 ensembles. A significant increase (+87%) in the frequency of very intense (categories 4 and 5) hurricanes (winds ≥ 59 m s−1) is projected using CMIP3, but smaller, only marginally significant increases are projected (+45% and +39%) for the CMIP5-early and CMIP5-late scenarios. Hurricane rainfall rates increase robustly for the CMIP3 and CMIP5 scenarios. For the late-twenty-first century, this increase amounts to +20% to +30% in the model hurricane’s inner core, with a smaller increase (~10%) for averaging radii of 200 km or larger. The fractional increase in precipitation at large radii (200–400 km) approximates that expected from environmental water vapor content scaling, while increases for the inner core exceed this level.

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