FVM 1.0: a nonhydrostatic finite-volume dynamical core for the IFS

We present a nonhydrostatic finite-volume global atmospheric model formulation for numerical weather prediction with the Integrated Forecasting System (IFS) at ECMWF and compare it to the established operational spectral-transform formulation. The novel Finite-Volume Module of the IFS (henceforth IFS-FVM) integrates the fully compressible equations using semi-implicit time stepping and non-oscillatory forward-in-time (NFT) Eulerian advection, whereas the spectral-transform IFS solves the hydrostatic primitive equations (optionally the fully compressible equations) using a semi-implicit semi-Lagrangian scheme. The IFS-FVM complements the spectral-transform counterpart by means of the finite-volume discretization with a local low-volume communication footprint, fully conservative and monotone advective transport, all-scale deep-atmosphere fully compressible equations in a generalized height-based vertical coordinate, and flexible horizontal meshes. Nevertheless, both the finite-volume and spectral-transform formulations can share the same quasi-uniform horizontal grid with co-located arrangement of variables, geospherical longitude–latitude coordinates, and physics parameterizations, thereby facilitating their comparison, coexistence, and combination in the IFS. We highlight the advanced semi-implicit NFT finite-volume integration of the fully compressible equations of IFS-FVM considering comprehensive moist-precipitating dynamics with coupling to the IFS cloud parameterization by means of a generic interface. These developments – including a new horizontal–vertical split NFT MPDATA advective transport scheme, variable time stepping, effective preconditioning of the elliptic Helmholtz solver in the semi-implicit scheme, and a computationally efficient implementation of the median-dual finite-volume approach – provide a basis for the efficacy of IFS-FVM and its application in global numerical weather prediction. Here, numerical experiments focus on relevant dry and moist-precipitating baroclinic instability at various resolutions. We show that the presented semi-implicit NFT finite-volume integration scheme on co-located meshes of IFS-FVM can provide highly competitive solution quality and computational performance to the proven semi-implicit semi-Lagrangian integration scheme of the spectral-transform IFS.</p

Physics–Dynamics Coupling in weather, climate and Earth system models: Challenges and recent progress

This is the final version. Available from American Meteorological Society via the DOI in this record.Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions.Natural Environment Research Council (NERC)National Science FoundationDepartment of Energy Office of Biological and Environmental ResearchPacific Northwest National Laboratory (PNNL)DOE Office of Scienc

Coherent evolution of potential vorticity anomalies associated with deep moist convection

Potential Vorticity (PV) elegantly describes synoptic- and planetary-scale dynamics, but it has received less attention on smaller scales. On the convective scale PV is characterised by dipoles associated with convective cells. We show that the PV dipoles are consistent and associated with statistically significant flow anomalies. Our hypothesis is that there is a coherent evolution of the PV dipoles. This hypothesis is tested by tracking convective cells in the nonhydrostatic COSMO-DE Numerical Weather Prediction (NWP) model during nine severe weather events. The 3135 convective cells used in this study are representative of deep moist convection over western Europe in the COSMO-DE model. Composites of the evolution of convective cells are made, and differences between “normal” and intense cells are discussed. Even when averaging over 3135 cells during nine cases, a clear horizontal PV dipole pattern can be seen with associated flow anomalies. Compared to normal cells, intense cells (identified using PV, precipitation rate or vertical velocity) have a more monopole morphology, which resembles supercells. The consistency of the PV dipoles implies that PV is also a useful diagnostic on the convective-weather scale

The “Grey Zone” cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations

A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation “Grey Zone” project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity

Evaluation of a mesoscale coupled ocean‐atmosphere configuration for tropical cyclone forecasting in the South West Indian Ocean basin

The performance in term of tropical cyclone track and intensity prediction of the new coupled ocean-atmosphere system based on the operational atmospheric model AROME-Indian Ocean and the ocean model NEMO is assessed against that of the current operational configuration in the case of seven recent tropical cyclones. Five different configurations of the forecast system are evaluated: two with the coupled system, two with an ocean mixed layer parameterization and one with a constant sea surface temperature. For each ocean-atmosphere coupling option, one is initialized directly with the MERCATOR-Ocean PSY4 product as in the current operational configuration and the other with the ocean state that is cycled in the AROME-NEMO coupled suite since a few days before the cyclone intensification. The results show that the coupling with NEMO generally improves the intensity of cyclones in AROME-IO, reducing the mean intensity bias of the 72 h forecast of about 10 hPa. However, the impact is especially significant when the TCs encounter a slow propagation phase. For short-term forecasts (less than 36 hours), the presence of a cooling in the initial state that has been triggered by the AROME high-resolution cyclonic winds in a previous coupled forecast already improves the tropical cyclone intensity bias of 2-3 hPa for both coupled or uncoupled configurations. Key Points AROME/NEMO improves the forecast of tropical cyclone compared to the operational configuration with a 1D ocean mixed layer parameterization The improvement mostly comes from quasi-stationary or very slow moving intense cyclones The tropical cyclone forecasts are sensitive to the ocean initial conditions Plain Language Summary The ocean provides a large part of the energy for the intensification of tropical cyclones through warm sea surface temperature and sea-air heat and moisture exchanges. However, the ocean-atmosphere interactions also trigger processes which cools the sea surface temperature beneath the tropical cyclone and thus generates a negative feedback on the TC intensification. The numerical forecasts of the regional numerical weather prediction model AROME-IO are valuable guidance for the Regional Specialized Meteorological Centre for Tropical Cyclones, La Réunion. The objective of our study is to evaluate the possibility of replacing the current ocean mixed layer parameterization by a more realistic ocean able to represent more complex processes such as the explicit transport by the currents. Overall, we found that the new coupling improves the cyclone intensity in AROME-IO both in terms of bias and standard deviation. These improvements come almost entirely from tropical cyclones that encounter a slow propagation phase. For short-term forecasts, the presence of a cooling that is triggered by AROME high-resolution cyclonic winds in the initial state of the ocean already improves the TC intensity forecast, even when the ocean mixed layer parameterization is used

Vers une amélioration du schéma statistique de nuages de méso-échelle dans les modèles AROME et Méso-NH

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Projected changes in the Southern Indian Ocean cyclone activity assessed from high-resolution experiments and CMIP5 models

International audienceThe evolution of tropical cyclone activity under climate change remains a crucial scientific issue. Physical theory of cyclogenesis is limited, observational datasets suffer from heterogeneities in space and time, and state-of-the-art climate models used for future projections are still too coarse (;100 km of resolution) to simulate realistic systems. Two approaches can nevertheless be considered: 1) perform dedicated highresolution (typically ,50 km) experiments in which tropical cyclones can be tracked and 2) assess cyclone activity from existing low-resolution multimodel climate projections using large-scale indices as proxies. Here we explore these two approaches with a particular focus on the southern Indian Ocean. We first compute highresolution experiments using the rotated-stretched configuration of our climate model (CNRM-CM6-1), which is able to simulate realistic tropical cyclones. In a 2-K warmer world, the model projects a 20% decrease in the frequency of tropical cyclones, together with an increase in their maximum lifetime intensity, a slight poleward shift of their trajectories, and a substantial delay (about 1 month) in the cyclone season onset. Largescale indices applied to these high-resolution experiments fail to capture the overall decrease in cyclone frequency, but are able to partially represent projected changes in the spatiotemporal distribution of cyclone activity. Last, we apply large-scale indices to multimodel CMIP5 projections and find that the seasonal redistribution of cyclone activity is consistent across models