Generalization and application of the flux-conservative thermodynamic equations in the AROME model of the ALADIN system

General yet compact equations are presented to express the thermodynamic impact of physical parameterizations in a NWP or climate model. By expressing the equations in a flux-conservative formulation, the conservation of mass and energy by the physics parameterizations is a built-in feature of the system. Moreover, the centralization of all thermodynamic calculations guarantees a consistent thermodynamical treatment of the different processes. The generality of this physics-dynamics interface is illustrated by applying it in the AROME NWP model. The physics-dynamics interface of this model currently makes some approximations, which typically consist of neglecting some terms in the total energy budget, such as the transport of heat by falling precipitation, or the effect of diffusive moisture transport. Although these terms are usually quite small, omitting them from the energy budget breaks the constraint of energy conservation. The presented set of equations provides the opportunity to get rid of these approximations, in order to arrive at a consistent and energy-conservative model. A verification in an operational setting shows that the impact on monthly-averaged, domain-wide meteorological scores is quite neutral. However, under specific circumstances, the supposedly small terms may turn out not to be entirely negligible. A detailed study of a case with heavy precipitation shows that the heat transport by precipitation contributes to the formation of a region of relatively cold air near the surface, the so-called cold pool. Given the importance of this cold pool mechanism in the life cycle of convective events, it is advisable not to neglect phenomena that may enhance it

Uncertainty in the Representation of Orography in Weather and Climate Models and Implications for Parameterized Drag

The representation of orographic drag remains a major source of uncertainty for numerical weather prediction (NWP) and climate models. Its accuracy depends on contributions from both the model grid‐scale orography (GSO) and the subgrid‐scale orography (SSO). Different models use different source orography datasets and different methodologies to derive these orography fields. This study presents the first comparison of orography fields across several operational global NWP models. It also investigates the sensitivity of an orographic drag parameterisation to the inter‐model spread in SSO fields and the resulting implications for representing the northern hemisphere winter circulation in a NWP model. The inter‐model spread in both the GSO and the SSO fields is found to be considerable. This is due to differences in the underlying source dataset employed and in the manner in which this dataset is processed (in particular how it is smoothed and interpolated) to generate the model fields. The sensitivity of parameterised orographic drag to the inter‐model variability in SSO fields is shown to be considerable and dominated by the influence of two SSO fields: the standard deviation and the mean gradient of the SSO. NWP model sensitivity experiments demonstrate that the inter‐model spread in these fields is of first‐order importance to the inter‐model spread in parameterised surface stress, and to current known systematic model biases. The revealed importance of the SSO fields supports careful reconsideration of how these fields are generated, guiding future development of orographic drag parameterisations and re‐evaluation of the resolved impacts of orography on the flow

Analyse variationnelle des paramètres de surface

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

L'évolution de la chaine de prévision numérique du temps sur la période 2022-2025

Météo-France est le service météorologique et climatologique national. A ce titre, il est chargé de four-nir aux pouvoirs publics, à l’aéronautique, aux entreprises et au grand public, des services adaptéspour gérer les risques en matière de sécurité des personnes et des biens. La prévision numérique dutemps (PNT) est l’outil privilégié pour l’anticipation du risque météorologique, ainsi que pour les prévi -sions fournies à divers secteurs économiques météo-sensibles (agriculture, production et consomma-tion d’énergie, transports). La PNT couvre une gamme d’échéances allant de quelques heures à plu-sieurs jours (jusqu’à 15 généralement). Météo-France, pour répondre à ses différentes missions, déve-loppe, maintient et opère un système de prévision numérique global, Arpège, qui couvre les échéancesjusqu’à 4 jours, et des systèmes de prévision numérique à haute résolution Arome, sur la métropole etles territoires outre-mer, jusqu’à 2 jours d’échéance. Pour les échéances moyennes (5 jours et au-delà),Météo-France s'appuie sur les prévisions numériques du CEPMMT (Centre européen pour les prévi-sions météorologiques à moyen terme), la France étant l'un de ses pays membres fondateurs. Auxéchéances mensuelles et saisonnières, Météo-France produit des prévisions, exploitées conjointementavec celles d'autres services.Cette note donne un aperçu des caractéristiques de la chaîne opérationnelle de PNT à Météo-Franceet de ses évolutions principales prévues sur la période 2022-2025. Cette période correspond à l’exploi-tation du calculateur Bull-Atos devenu opérationnel en 2021 et dont la justification a été portée par uncertain nombre de progrès attendus de la chaîne de PNT. Météo-France opère aussi des systèmes nu -mériques en aval de la chaîne de PNT (modèles de prévision marine, de qualité de l’air, de nivologie,d’hydrologie et d’agrométéorologie), qui ne sont pas présentés dans cette note

Systematic errors in weather and climate models:Nature, origins, and ways forward

The fifth Workshop on Systematic Errors (WSE) in weather and climate models was hosted by Environment and Climate Change Canada (ECCC) on under the auspices of the Working Group on Numerical Experimentation (WGNE), jointly sponsored by the Commission of Atmospheric Sciences of the World Meteorological Organization (WMO) and the World Climate Research Programme (WCRP). This major event welcomed over 200 scientists from the weather and climate communities. The workshop primary goal was to increase the understanding of the nature and cause of systematic errors in numerical models across timescales. Out of 240 abstracts submitted to the workshop, 48 talks and 132 posters were presented