A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ~0.5 to ~0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate. T he effect of climate change on tropical cyclones has been a controversial scientific issue for a number of years. Advances in our theoretical understanding of the relationship between climate and tropical cyclones have been made, enabling us to understand better the links between the mean climate and the potential intensity (PI; the theoretical maximum intensity of a tropical cyclone for a given climate condition) of tropical cyclones. Improvements in the capabilities of climate models, the main tool used to predict future climate, have enabled them to achieve a considerably improved and more credible simulation of the present-day climatology of tropical cyclones. Finally, the increasing ability of such models to predict the interannual variability of tropical cyclone formation in various regions of the globe indicates that they are capturing some of the essential physical relationships governing the links between climate and tropical cyclones. HURRICANES AND CLIMATEPrevious climate model simulations, however, have suggested some ambiguity in projections of future numbers of tropical cyclones in a warmer world. While many models have projected fewer tropical cyclones globally (Sugi et al. 2002;Bengtsson et al. 2007b; Gualdi et al. 2008; Knutson et al. 2010), other climate models and related downscaling methods have suggested some increase in future numbers (e.g., Broccoli and Manabe 1990;Haarsma et al. 1993; Emanuel 2013a). When future projections for individual basins are made, the issue becomes more serious: for example, for the Atlantic basin there appears to be little consensus on the future number of tropical cyclones or on the relative importance of forcing factors such as aerosols or increases in carbon dioxide (CO 2 ) concentration. One reason could be statistical: annual numbers of tropical cyclones in the Atlantic are relatively small, making the identification of such storms sensitive to the detection method used.Further, there is substantial spread in projected responses of regional tropical cyclone (TC) frequency and intensity over the twenty-first century from downscaling studies (Knutson et al. 2007; Emanuel 2013a). Interpreting the sources of those differences is complicated by different projections of large-scale climate and by differences in the present-day reference period and sea surface temperature (SST) datasets used. A natural question is whether the diversity in responses to projected twenty-firstcentury climate of each of the studies is primarily | a reflection of uncertainty arising from different large-scale forcing (as has been suggested by, e.g., Villarini et al. 2011;Villarini and Vecchi 2012;Knutson et al. 2013) or whether this spread reflects principally different inherent sensitivities across the various downscaling techniques, even including different sensitivity of responses within the same model due to...

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere‐only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050.

Abstract. This paper describes a new open-source software framework for automated pointwise feature tracking that is applicable to a wide array of climate datasets using either structured or unstructured grids. Common climatological pointwise features include tropical cyclones, extratropical cyclones and tropical easterly waves. To enable support for a wide array of detection schemes, a suite of algorithmic kernels have been developed that capture the core functionality of algorithmic tracking routines throughout the literature. A review of efforts related to pointwise feature tracking from the past 3 decades is included. Selected results using both reanalysis datasets and unstructured grid simulations are provided.

It is the purpose of this paper to provide a comprehensive documentation of the new NCAR (National Center for Atmospheric Research) version of the spectral element (SE) dynamical core as part of the Community Earth System Model (CESM2.0) release. This version differs from previous releases of the SE dynamical core in several ways. Most notably the hybrid sigma vertical coordinate is based on dry air mass, the condensates are dynamically active in the thermodynamic and momentum equations (also referred to as condensate loading), and the continuous equations of motion conserve a more comprehensive total energy that includes condensates. Not related to the vertical coordinate change, the hyperviscosity operators and the vertical remapping algorithms have been modified. The code base has been significantly reduced, sped up, and cleaned up as part of integrating SE as a dynamical core in the CAM (Community Atmosphere Model) repository rather than importing the SE dynamical core from High‐Order Methods Modeling environment as an external code.

[1] Black carbon (BC) has an increased forcing per unit mass when it is located above reflective clouds. To explore sensitivity of forcing to aerosol vertical location, we used a column radiative transfer model to produce globally-averaged values of normalized direct radiative forcing (NDRF) for BC over and under different types of clouds. We developed a simple column-weighting scheme based on the mass fractions of BC that are over and under clouds in measured vertical profiles. The resulting NDRF is in good agreement with global 3-D model estimates, supporting the column-weighted model as a tool for exploring uncertainties due to diversity in vertical distribution. BC above low clouds accounts for about 20% of the global burden but 50% of the forcing. We estimate maximumminimum spread in NDRF due to modeled profiles as about 40% and uncertainty as about 25%. Because models overestimate BC in the upper troposphere compared with measurements, modeled NDRF might need to be reduced by about 15%. Redistributing BC within the lowest 4 km of the atmosphere affects modeled NDRF by only about 5% and cannot account for very high forcing estimates.Citation: Zarzycki, C. M., and T. C. Bond (2010), How much can the vertical distribution of black carbon affect its global direct radiative forcing?, Geophys.

Abstract. Climatic effects of short-lived climate forcers (SLCFs) differ from those of long-lived greenhouse gases, because they occur rapidly after emission and because they depend upon the region of emission. The distinctive temporal and spatial nature of these impacts is not captured by measures that rely on global averages or long time integrations. Here, we propose a simple measure, the Specific Forcing Pulse (SFP), to quantify climate warming or cooling by these pollutants, where we define "immediate" as occurring primarily within the first year after emission. SFP is the amount of energy added to or removed from a receptor region in the Earth-atmosphere system by a chemical species, per mass of emission in a source region. We limit the application of SFP to species that remain in the atmosphere for less than one year. Metrics used in policy discussions, such as total forcing or global warming potential, are easily derived from SFP. However, SFP conveys purely physical information without incurring the policy implications of choosing a time horizon for the global warming potential.Using one model (Community Atmosphere Model, or CAM), we calculate values of SFP for black carbon (BC) and organic matter (OM) emitted from 23 source-region combinations. Global SFP for both atmosphere and cryosphere impacts is divided among receptor latitudes. SFP is usually greater for open-burning emissions than for energy-related (fossil-fuel and biofuel) emissions because of the timing of emission. Global SFP for BC varies by about 45% for energy-related emissions from different regions. This variation would be larger except for compensating effects. When emitted aerosol has larger cryosphere forcing, it often has lower atmosphere forcing because of less deep convection and a shorter atmospheric lifetime.Correspondence to: T. C. Bond (yark@illinois.edu) A single model result is insufficient to capture uncertainty. We develop a best estimate and uncertainties for SFP by combining forcing results from 12 additional models. We outline a framework for combining a large number of simple models with a smaller number of enhanced models that have greater complexity. Adjustments for black carbon internal mixing and for regional variability are discussed. Emitting regions with more deep convection have greater model diversity. Our best estimate of global-mean SFP is +1.03 ± 0.52 GJ g −1 for direct atmosphere forcing of black carbon, +1.15 ± 0.53 GJ g −1 for black carbon including direct and cryosphere forcing, and −0.064 (−0.02, −0.13) GJ g −1 for organic matter. These values depend on the region and timing of emission. The lowest OM:BC mass ratio required to produce a neutral effect on top-ofatmosphere direct forcing is 15:1 for any region. Any lower ratio results in positive direct forcing. However, important processes, particularly cloud changes that tend toward cooling, have not been included here.Global-average SFP for energy-related emissions can be converted to a 100-year GWP of about 740 ± 370 for BC without snow forcing, and ...

A variable-resolution option has been added within the spectral element (SE) dynamical core of the U.S. Department of Energy (DOE)-NCAR Community Atmosphere Model (CAM). CAM-SE allows for static refinement via conforming quadrilateral meshes on the cubed sphere. This paper investigates the effect of mesh refinement in a climate model by running variable-resolution (var-res) simulations on an aquaplanet. The variable-resolution grid is a 28 (;222 km) grid with a refined patch of 0.258 (;28 km) resolution centered at the equator. Climatology statistics from these simulations are compared to globally uniform runs of 28 and 0.258. A significant resolution dependence exists when using the CAM version 4 (CAM4) subgrid physical parameterization package across scales. Global cloud fraction decreases and equatorial precipitation increases with finer horizontal resolution, resulting in drastically different climates between the uniform grid runs and a physics-induced grid imprinting in the var-res simulation. Using CAM version 5 (CAM5) physics significantly improves cloud scaling at different grid resolutions. Additional precipitation at the equator in the highresolution mesh results in collocated zonally anomalous divergence in both var-res simulations, although this feature is much weaker in CAM5 than CAM4. The equilibrium solution at each grid spacing within the var-res simulations captures the majority of the resolution signal of the corresponding globally uniform grids. The var-res simulation exhibits good performance with respect to wave propagation, including equatorial regions where waves pass through grid transitions. In addition, the increased frequency of high-precipitation events in the refined 0.258 area within the var-res simulations matches that observed in the global 0.258 simulations.