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Catherine M. Naud, Jeyavinoth Jeyaratnam, James F. Booth, Ming Zhao, and Andrew Gettelman

ABSTRACT

Using a high-spatial- and high-temporal-resolution precipitation dataset, Integrated Multi-satellite Retrievals for GPM (IMERG), extratropical cyclone precipitation is evaluated in two reanalyses and two climate models. Based on cyclone-centered composites, all four models overestimate precipitation in the western subsiding and dry side of the cyclones, and underestimate the precipitation in the eastern ascending and moist side. By decomposing the composites into frequency of occurrence and intensity (mean precipitation rate when precipitating), the analysis reveals a tendency for all four models to overestimate frequency and underestimate intensity, with the former issue dominating in the western half and the latter in the eastern half of the cyclones. Differences in frequency are strongly dependent on cyclone environmental moisture, while the differences in intensity are strongly impacted by the strength of ascent within the cyclone. There are some uncertainties associated with the observations: IMERG might underreport frozen precipitation and possibly exaggerate rates in vigorously ascending regions. Nevertheless, the analysis suggests that all models produce extratropical cyclone precipitation too often and too lightly. These biases have consequences when evaluating the changes in precipitation characteristics with changes in cyclone properties: the models disagree on the magnitude of the change in precipitation intensity with a change in environmental moisture and in precipitation frequency with a change in cyclone strength. This complicates accurate predictions of precipitation changes in a changing climate.

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Shaohua Chen, Haikun Zhao, Graciela B. Raga, and Philip J. Klotzbach

Abstract

This study highlights the distinct modulation of May–October tropical cyclones (TCs) in the western North Pacific (WNP), eastern North Pacific (ENP), and North Atlantic (NATL) Ocean basins by tropical transbasin variability (TBV) and ENSO. The pure TBV significantly modulates total TC counts in all three basins, with more TCs in the WNP and ENP and fewer TCs in the NATL during warm TBV years and fewer TCs in the WNP and ENP and more TCs in the NATL during cold TBV years. By contrast, the pure ENSO signal shows no impact on total TC count over any of the three basins. These results are consistent with changes in large-scale factors associated with TBV and ENSO. Low-level relative vorticity (VOR) is an important driver of WNP TC genesis frequency, with broad agreement between the observed spatial distribution of TC genesis and TBV/ENSO-associated VOR anomalies. TBV significantly affects ENP TC frequency as a result of changes in basinwide vertical wind shear and sea surface temperatures, whereas the modulation in TC frequency by ENSO is primarily caused by a north–south dipole modulation of large-scale atmospheric and oceanic factors. The pure TBV-related low-level VOR changes appear to be the most important factor modulating NATL TC frequency. Changes in large-scale factors compare well with the budget of synoptic-scale eddy kinetic energy. Possible physical processes associated with pure TBV and pure ENSO that modulate TC frequency are further discussed. This study contributes to the understanding of TC interannual variability and could thus be helpful for seasonal TC forecasting.

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Xianan Jiang, Ángel F. Adames, Ming Zhao, Duane Waliser, and Eric Maloney

Abstract

The Madden–Julian oscillation (MJO) exhibits pronounced seasonality. While it is largely characterized by equatorially eastward propagation during the boreal winter, MJO convection undergoes marked poleward movement over the Asian monsoon region during summer, producing a significant modulation of monsoon rainfall. In classical MJO theories that seek to interpret the distinct seasonality in MJO propagation features, the role of equatorial wave dynamics has been emphasized for its eastward propagation, whereas coupling between MJO convection and the mean monsoon flow is considered essential for its northward propagation. In this study, a unified physical framework based on the moisture mode theory, is offered to explain the seasonality in MJO propagation. Moistening and drying caused by horizontal advection of the lower-tropospheric mean moisture by MJO winds, which was recently found to be critical for the eastward propagation of the winter MJO, is also shown to play a dominant role in operating the northward propagation of the summer MJO. The seasonal variations in the mean moisture pattern largely shape the distinct MJO propagation in different seasons. The critical role of the seasonally varying climatological distribution of moisture for the MJO propagation is further supported by the close association between model skill in representing the MJO propagation and skill at producing the lower-tropospheric mean moisture pattern. This study thus pinpoints an important direction for climate model development for improved MJO representation during all seasons.

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Catherine M. Naud, James F. Booth, Jeyavinoth Jeyaratnam, Leo J. Donner, Charles J. Seman, Ming Zhao, Huan Guo, and Yi Ming

Abstract

The clouds in Southern Hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat, and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of “AM4,” a model GFDL that will utilize for CMIP6, and the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low levels (again by differing amounts), especially in the post–cold frontal (PCF) region, when compared with observations. In focusing only on the models, it is seen that their differences in high and midlevel clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud-parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting that other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

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Gabriele Villarini, David A. Lavers, Enrico Scoccimarro, Ming Zhao, Michael F. Wehner, Gabriel A. Vecchi, Thomas R. Knutson, and Kevin A. Reed

Abstract

Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socioeconomic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date and still represents a major challenge. The capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group activity is used to examine TC response to idealized global-scale perturbations: the doubling of CO2, uniform 2-K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO2 scenario (on the order of 5% globally) and an increase in TC rainfall rates associated with a uniform increase of 2 K in SST (both alone and in combination with CO2 doubling; on the order of 10%–20% globally).

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Allison A. Wing, Suzana J. Camargo, Adam H. Sobel, Daehyun Kim, Yumin Moon, Hiroyuki Murakami, Kevin A. Reed, Gabriel A. Vecchi, Michael F. Wehner, Colin Zarzycki, and Ming Zhao

Abstract

Tropical cyclone intensification processes are explored in six high-resolution climate models. The analysis framework employs process-oriented diagnostics that focus on how convection, moisture, clouds, and related processes are coupled. These diagnostics include budgets of column moist static energy and the spatial variance of column moist static energy, where the column integral is performed between fixed pressure levels. The latter allows for the quantification of the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclone spinup, including surface flux feedbacks and cloud-radiative feedbacks. Tropical cyclones (TCs) are tracked in the climate model simulations and the analysis is applied along the individual tracks and composited over many TCs. Two methods of compositing are employed: a composite over all TC snapshots in a given intensity range, and a composite over all TC snapshots at the same stage in the TC life cycle (same time relative to the time of lifetime maximum intensity for each storm). The radiative feedback contributes to TC development in all models, especially in storms of weaker intensity or earlier stages of development. Notably, the surface flux feedback is stronger in models that simulate more intense TCs. This indicates that the representation of the interaction between spatially varying surface fluxes and the developing TC is responsible for at least part of the intermodel spread in TC simulation.

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Yumin Moon, Daehyun Kim, Suzana J. Camargo, Allison A. Wing, Adam H. Sobel, Hiroyuki Murakami, Kevin A. Reed, Enrico Scoccimarro, Gabriel A. Vecchi, Michael F. Wehner, Colin M. Zarzycki, and Ming Zhao

Abstract

Characteristics of tropical cyclones (TCs) in global climate models (GCMs) are known to be influenced by details of the model configurations, including horizontal resolution and parameterization schemes. Understanding model-to-model differences in TC characteristics is a prerequisite for reducing uncertainty in future TC activity projections by GCMs. This study performs a process-level examination of TC structures in eight GCM simulations that span a range of horizontal resolutions from 1° to 0.25°. A recently developed set of process-oriented diagnostics is used to examine the azimuthally averaged wind and thermodynamic structures of the GCM-simulated TCs. Results indicate that the inner-core wind structures of simulated TCs are more strongly constrained by the horizontal resolutions of the models than are the thermodynamic structures of those TCs. As expected, the structures of TC circulations become more realistic with smaller horizontal grid spacing, such that the radii of maximum wind (RMW) become smaller, and the maximum vertical velocities occur off the center. However, the RMWs are still too large, especially at higher intensities, and there are rising motions occurring at the storm centers, inconsistently with observations. The distributions of precipitation, moisture, and radiative and surface turbulent heat fluxes around TCs are diverse, even across models with similar horizontal resolutions. At the same horizontal resolution, models that produce greater rainfall in the inner-core regions tend to simulate stronger TCs. When TCs are weak, the radial gradient of net column radiative flux convergence is comparable to that of surface turbulent heat fluxes, emphasizing the importance of cloud–radiative feedbacks during the early developmental phases of TCs.

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Suzana J. Camargo, Claudia F. Giulivi, Adam H. Sobel, Allison A. Wing, Daehyun Kim, Yumin Moon, Jeffrey D. O. Strong, Anthony D. Del Genio, Maxwell Kelley, Hiroyuki Murakami, Kevin A. Reed, Enrico Scoccimarro, Gabriel A. Vecchi, Michael F. Wehner, Colin Zarzycki, and Ming Zhao

Abstract

Here we explore the relationship between the global climatological characteristics of tropical cyclones (TCs) in climate models and the modeled large-scale environment across a large number of models. We consider the climatology of TCs in 30 climate models with a wide range of horizontal resolutions. We examine if there is a systematic relationship between the climatological diagnostics for the TC activity [number of tropical cyclones (NTC) and accumulated cyclone energy (ACE)] by hemisphere in the models and the environmental fields usually associated with TC activity, when examined across a large number of models. For low-resolution models, there is no association between a conducive environment and TC activity, when integrated over space (tropical hemisphere) and time (all years of the simulation). As the model resolution increases, for a couple of variables, in particular vertical wind shear, there is a statistically significant relationship in between the models’ TC characteristics and the environmental characteristics, but in most cases the relationship is either nonexistent or the opposite of what is expected based on observations. It is important to stress that these results do not imply that there is no relationship between individual models’ environmental fields and their TC activity by basin with respect to intraseasonal or interannual variability or due to climate change. However, it is clear that when examined across many models, the models’ mean state does not have a consistent relationship with the models’ mean TC activity. Therefore, other processes associated with the model physics, dynamical core, and resolution determine the climatological TC activity in climate models.

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J. Teixeira, S. Cardoso, M. Bonazzola, J. Cole, A. DelGenio, C. DeMott, C. Franklin, C. Hannay, C. Jakob, Y. Jiao, J. Karlsson, H. Kitagawa, M. Köhler, A. Kuwano-Yoshida, C. LeDrian, J. Li, A. Lock, M. J. Miller, P. Marquet, J. Martins, C. R. Mechoso, E. v. Meijgaard, I. Meinke, P. M. A. Miranda, D. Mironov, R. Neggers, H. L. Pan, D. A. Randall, P. J. Rasch, B. Rockel, W. B. Rossow, B. Ritter, A. P. Siebesma, P. M. M. Soares, F. J. Turk, P. A. Vaillancourt, A. Von Engeln, and M. Zhao

Abstract

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

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Leo J. Donner, Bruce L. Wyman, Richard S. Hemler, Larry W. Horowitz, Yi Ming, Ming Zhao, Jean-Christophe Golaz, Paul Ginoux, S.-J. Lin, M. Daniel Schwarzkopf, John Austin, Ghassan Alaka, William F. Cooke, Thomas L. Delworth, Stuart M. Freidenreich, C. T. Gordon, Stephen M. Griffies, Isaac M. Held, William J. Hurlin, Stephen A. Klein, Thomas R. Knutson, Amy R. Langenhorst, Hyun-Chul Lee, Yanluan Lin, Brian I. Magi, Sergey L. Malyshev, P. C. D. Milly, Vaishali Naik, Mary J. Nath, Robert Pincus, Jeffrey J. Ploshay, V. Ramaswamy, Charles J. Seman, Elena Shevliakova, Joseph J. Sirutis, William F. Stern, Ronald J. Stouffer, R. John Wilson, Michael Winton, Andrew T. Wittenberg, and Fanrong Zeng

Abstract

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.

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