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Joël Stein

Abstract

The different airflow regimes for prototype orographic problems are controlled by a reduced set of nondimensional numbers. A regime diagram is deduced for the Long problem from a set of numerical simulations made with a primitive equation hydrostatic model. Two transitions separating the quasi-linear regime, the high-drag state and the blocked state, are recovered. The first critical inverse Froude number F = Nh/U (corresponding to the onset of wave breaking) depends smoothly on S = NU/g, which quantifies the wave amplification, in contrast with the second critical inverse Froude number (corresponding to the onset of blocking), which is quasi-independent of S. The dimensional drag in function of F is found in F 2 for the quasi-linear regime, in F ≥2 for the high-drag regime, and in F 1.3 for the blocked regime. The study of the blocked configuration shows that the depth of the blocked region and the top of the turbulent region increase linearly with F.

The regime diagram for the case where a critical layer (U = 0) is inserted in the basic flow is also established. Our study reproduces the main conclusion of the hydraulic theory: a discrete spectrum with a period equal to the vertical wavelength for the critical-level heights leads to a high-drag configuration, and the values of this spectrum are dependent on the mountain height. A global conclusion of this study is that the hydrostatic model has the capacity to reproduce all of the transitions due to the effects of the nonlinearities, provided that the mountain half-width is large enough.

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Joël Stein and Fabien Stoop

Abstract

Some specific scores use a neighborhood strategy in order to reduce double penalty effects, which penalize high-resolution models, compared to large-scale models. Contingency tables based on this strategy have already been proposed, but can sometimes display undesirable behavior. A new method of populating contingency tables is proposed: pairs of missed events and false alarms located in the same local neighborhood compensate in order to give pairs of hits and correct rejections. Local tables are summed up so as to provide the final table for the whole verification domain. It keeps track of the bias of the forecast when neighborhoods are taken into account. Moreover, the scores computed from this table depend on the distance between forecast and observed patterns. This method is applied to binary and multicategorical events in a simplified framework so as to present the method and to compare the new tables with previous neighborhood-based contingency tables. The new tables are then used for the verification of two models operational at Météo-France: AROME, a high-resolution model, and ARPEGE, a large-scale global model. The comparison of several contingency scores shows that the importance of the double penalty decreases more for AROME than for ARPEGE when the neighboring size increases. Scores designed for rare events are also applied to these neighborhood-based contingency tables.

Open access
Stéphane Bélair, Pierre Lacarrère, Joël Noilhan, Valéry Masson, and Joël Stein

Abstract

The newly developed nonhydrostatic model MESO-NH, in which the surface scheme Interactions Soil–Biosphere–Atmosphere has been incorporated, is used in this study to assess the impact of increasing the horizontal resolution from 10 km to 1 km on the simulation of surface and turbulent fluxes for the 16 June 1986 case of HAPEX-MOBILHY, a field experiment that took place in southwestern France.

Except for a slight deterioration over the cultivated areas surrounding the Landes forest (caused by an inconsistency between the soil texture fields at 10 and 1 km), the simulation of the surface fluxes of sensible and latent heat is generally improved by the increase of horizontal resolution. The contrast of the sensible heat fluxes between the Landes forest and the surrounding cultures is well captured in both 10-km and 1-km runs, but the spatial variability of these fluxes is better represented in the high-resolution results. An oasis-type effect over the larger clearings of the Landes forest is even produced by the model, as was observed.

For the 1-km simulation, the comparison of the turbulent fluxes against observations has to include both the grid-scale fluxes resulting from resolved larger eddies within the well-mixed layer, as well as subgrid-scale (i.e., parameterized) fluxes. (At 10-km resolution, all turbulent fluxes are parameterized.) The greater contributions of the grid-scale component are found over the forest, where the larger eddies are more vigorous due to stronger sensible heat fluxes at the surface. For sensible and latent heat fluxes, the grid-scale component is particularly important in the middle of the mixed layer, whereas for turbulent kinetic energy this component is greater near the bottom and top of the mixed layer. In general, the increase of horizontal resolution does not improve significantly the simulation of the turbulent fluxes. Thus, the use of such an intermediate horizontal resolution (i.e., 1 km), lying between that typically used in large-eddy simulation models (<200 m) and that of mesoscale models (>few kilometers), is questionable, even though this resolution is probably optimal for simulating surface fluxes, since it is roughly the same as the resolution of the soil and vegetation databases.

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Michaël Zamo, Liliane Bel, Olivier Mestre, and Joël Stein

Abstract

Numerical weather forecast errors are routinely corrected through statistical postprocessing by several national weather services. These statistical postprocessing methods build a regression function called model output statistics (MOS) between observations and forecasts that is based on an archive of past forecasts and associated observations. Because of limited spatial coverage of most near-surface parameter measurements, MOS have been historically produced only at meteorological station locations. Nevertheless, forecasters and forecast users increasingly ask for improved gridded forecasts. The present work aims at building improved hourly wind speed forecasts over the grid of a numerical weather prediction model. First, a new observational analysis, which performs better in terms of statistical scores than those operationally used at Météo-France, is described as gridded pseudo-observations. This analysis, which is obtained by using an interpolation strategy that was selected among other alternative strategies after an intercomparison study conducted internally at Météo-France, is very parsimonious since it requires only two additive components, and it requires little computational resources. Then, several scalar regression methods are built and compared, using the new analysis as the observation. The most efficient MOS is based on random forests trained on blocks of nearby grid points. This method greatly improves forecasts compared with raw output of numerical weather prediction models. Furthermore, building each random forest on blocks and limiting those forests to shallow trees does not impair performance compared with unpruned and pointwise random forests. This alleviates the storage burden of the objects and speeds up operations.

Open access