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  1. Abstract Based on 20-day control forecasts by the 9-km Integrated Forecasting System (IFS) at the European Centre for Medium-Range Weather Forecasts (ECMWF) for selected periods of summer and winter events, this study investigates global distributions of gravity wave momentum fluxes resolved by the highest-resolution-ever global operational numerical weather prediction model. Two supplementary datasets, including 18-km ECMWF IFS experiments and the 30-km ERA5, are included for comparison. In the stratosphere, there is a clear dominance of westward momentum fluxes over the winter extratropics with strong baroclinic instability, while eastward momentum fluxes are found in the summer tropics. However, meridional momentum fluxes, locally as important as the above zonal counterpart, show different behaviors of global distribution characteristics, with northward and southward momentum fluxes alternating with each other especially at lower altitudes. Both events illustrate conclusive evidence that stronger stratospheric fluxes are found in the ECMWF forecast with finer resolution, and that ERA5 datasets have the weakest signals in general, regardless of whether regridding is applied. In the troposphere, probability distributions of vertical motion perturbations are highly asymmetric with more strong positive signals especially over latitudes covering heavy rainfall, likely caused by convective forcing. With the aid of precipitation accumulation, a simple filteringmore »method is proposed in an attempt to eliminate those tropospheric asymmetries by convective forcing, before calculating tropospheric wave-induced fluxes. Furthermore, this research demonstrates promising findings that the proposed filtering method could help in reducing the potential uncertainties with respect to estimating tropospheric wave-induced fluxes. Finally, absolute momentum flux distributions with proposed approaches are presented, for further assessment in the future.« less
    Free, publicly-accessible full text available October 1, 2023
  2. Free, publicly-accessible full text available September 1, 2023
  3. Abstract

    Atmospheric rivers (ARs) impacting western North America are analyzed under climate intervention applying stratospheric aerosol injections (SAI) using simulations produced by the Whole Atmosphere Community Climate Model. Sulfur dioxide injections are strategically placed to maintain present-day global, interhemispheric, and equator-to-pole surface temperatures between 2020 and 2100 using a high forcing climate scenario. Three science questions are addressed: (1) How will western North American ARs change by the end of the century with SAI applied, (2) How is this different from 2020 conditions, and (3) How will the results differ with no future climate intervention. Under SAI, ARs are projected to increase by the end of the 21st century for southern California and decrease in the Pacific Northwest and coastal British Columbia, following changes to the low-level wind. Compared to 2020 conditions, the increase in ARs is not significant. The character of AR precipitation changes under geoengineering results in fewer extreme rainfall events and more moderate ones.

  4. Free, publicly-accessible full text available November 16, 2023
  5. Abstract. Simulating the complex aerosol microphysical processes in a comprehensive Earth system model can be very computationally intensive; therefore many models utilize a modal approach, where aerosol size distributions are represented by observation-derived lognormal functions, and internal mixing between different aerosol species within an aerosol mode is often assumed. This approach has been shown to yield satisfactory results across a large array of applications, but there may be cases where the simplification in this approach may produce some shortcomings. In this work we show specific conditions under which the current approximations used in some modal approaches might yield incorrect answers. Using results from the Community Earth System Model v1 (CESM1) Geoengineering Large Ensemble (GLENS) project, we analyze the effects in the troposphere of a continuous increasing load of sulfate aerosols in the stratosphere, with the aim of counteracting the surface warming produced by non-mitigated increasing greenhouse gas (GHG) concentrations between 2020–2100. We show that the simulated results pertaining to the evolution of sea salt and dust aerosols in the upper troposphere are not realistic due to internal mixing assumptions in the modal aerosol treatment, which in this case reduces the size, and thus the settling velocities, of those particles and ultimatelymore »changes their mixing ratio below the tropopause. The unnatural increase of these aerosol species affects, in turn, the simulation of upper tropospheric ice formation, resulting in an increase in ice clouds that is not due to any meaningful physical mechanisms. While we show that this does not significantly affect the overall results of the simulations, we point to some areas where results should be interpreted with care in modeling simulations using similar approximations: in particular, in the evolution of upper tropospheric clouds when large amounts of sulfate are present in the stratosphere, as after a large explosive volcanic eruption or in similar stratospheric aerosol injection cases. Finally, we suggest that this can be avoided if sulfate aerosols in the coarse mode, the predominant species in these situations, are treated separately from other aerosol species in the model.« less
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  7. Abstract There is a growing demand for understanding sources of predictability on subseasonal to seasonal (S2S) time scales. Predictability at subseasonal time scales is believed to come from processes varying slower than the atmosphere such as soil moisture, snowpack, sea ice, and ocean heat content. The stratosphere as well as tropospheric modes of variability can also provide predictability at subseasonal time scales. However, the contributions of the above sources to S2S predictability are not well quantified. Here we evaluate the subseasonal prediction skill of the Community Earth System Model, version 1 (CESM1), in the default version of the model as well as a version with the improved representation of stratospheric variability to assess the role of an improved stratosphere on prediction skill. We demonstrate that the subseasonal skill of CESM1 for surface temperature and precipitation is comparable to that of operational models. We find that a better-resolved stratosphere improves stratospheric but not surface prediction skill for weeks 3–4.