| 1. |
- Bardakov, Roman, et al.
(author)
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A Novel Framework to Study Trace Gas Transport in Deep Convective Clouds
- 2020
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In: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:5
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Journal article (peer-reviewed)abstract
- Deep convective clouds reach the upper troposphere (8-15 km height). In addition to moisture and aerosol particles, they can bring aerosol precursor gases and other reactive trace gases from the planetary boundary layer to the cloud top. In this paper, we present a method to estimate trace gas transport based on the analysis of individual air parcel trajectories. Large eddy simulation of an idealized deep convective cloud was used to provide realistic environmental input to a parcel model. For a buoyant parcel, we found that the trace gas transport approximately follows one out of three scenarios, determined by a combination of the equilibrium vapor pressure (containing information about water-solubility and pure component saturation vapor pressure) and the enthalpy of vaporization. In one extreme, the trace gas will eventually be completely removed by precipitation. In the other extreme, there is almost no vapor condensation on hydrometeors and most of the gas is transported to the top of the cloud. The scenario in between these two extremes is also characterized by strong gas condensation, but a small fraction of the trace gas may still be transported aloft. This approach confirms previously suggested patterns of inert trace gas behavior in deep convective clouds, agrees with observational data, and allows estimating transport in analytically simple and computationally efficient way compared to explicit cloud-resolving model calculations.
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| 2. |
- de Lavergne, C., et al.
(author)
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A Parameterization of Local and Remote Tidal Mixing
- 2020
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In: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:5
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Journal article (peer-reviewed)abstract
- Vertical mixing is often regarded as the Achilles' heel of ocean models. In particular, few models include a comprehensive and energy-constrained parameterization of mixing by internal ocean tides. Here, we present an energy-conserving mixing scheme which accounts for the local breaking of high-mode internal tides and the distant dissipation of low-mode internal tides. The scheme relies on four static two-dimensional maps of internal tide dissipation, constructed using mode-by-mode Lagrangian tracking of energy beams from sources to sinks. Each map is associated with a distinct dissipative process and a corresponding vertical structure. Applied to an observational climatology of stratification, the scheme produces a global three-dimensional map of dissipation which compares well with available microstructure observations and with upper-ocean finestructure mixing estimates. This relative agreement, both in magnitude and spatial structure across ocean basins, suggests that internal tides underpin most of observed dissipation in the ocean interior at the global scale. The proposed parameterization is therefore expected to improve understanding, mapping, and modeling of ocean mixing. ©2020. The Authors.
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| 3. |
- Mauritsen, Thorsten, et al.
(author)
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Tuning the MPI-ESM1.2 Global Climate Model to Improve the Match With Instrumental Record Warming by Lowering Its Climate Sensitivity
- 2020
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In: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:5
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Journal article (peer-reviewed)abstract
- A climate model's ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons it cannot be considered a purely empirical result of the modeling efforts because the desired result is known in advance and so is a potential target of tuning. Here we report how the latest edition of the Max Planck Institute for Meteorology Earth System Models (MPI-ESM1.2) atmospheric component (ECHAM6.3) had its sensitivity systematically tuned in order to improve the modeled match with the instrumental record. In practice, this was done by targeting an equilibrium climate sensitivity of about 3 K, slightly lower than in the previous model generation (MPI-ESM), which warmed more than observed, and in particular by addressing a climate sensitivity of about 7 K in an intermediate version of the model. In the process we identified several controls on cloud feedback, some of which confirm recently proposed hypotheses. We find the model exhibits excellent fidelity with the observed centennial global warming. We further find that an alternative approach with high climate sensitivity compensated by strong aerosol cooling instead would yield colder than observed results in the second half of the twentieth century.
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| 4. |
- Rasp, Stephan, et al.
(author)
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WeatherBench : A Benchmark Data Set for Data-Driven Weather Forecasting
- 2020
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In: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:11
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Journal article (peer-reviewed)abstract
- Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could also be used to predict global weather patterns days in advance. First studies show promise but the lack of a common data set and evaluation metrics make intercomparison between studies difficult. Here we present a benchmark data set for data-driven medium-range weather forecasting (specifically 3-5 days), a topic of high scientific interest for atmospheric and computer scientists alike. We provide data derived from the ERA5 archive that has been processed to facilitate the use in machine learning models. We propose simple and clear evaluation metrics which will enable a direct comparison between different methods. Further, we provide baseline scores from simple linear regression techniques, deep learning models, as well as purely physical forecasting models. The data set is publicly available at and the companion code is reproducible with tutorials for getting started. We hope that this data set will accelerate research in data-driven weather forecasting.
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