Météo‐France has implemented a short‐range ensemble prediction system known as Prévision d'Ensemble ARPEGE (PEARP). This system is a global ensemble performing forecasts up to 4.5 days. It uses the ...operational global numerical weather prediction model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and benefits from variable horizontal resolution, so that it is comparable to some limited‐area mesoscale systems over France. Perturbations to the initial conditions are computed by combining an ensemble data assimilation system with singular vectors. Model uncertainties are represented through a ‘multiphysics’ approach with ten different physical parametrization sets. The article describes the set‐up of the system and provides an assessment of the approaches used to represent initial conditions and model uncertainties. The positive impact of the variable horizontal resolution of PEARP is also illustrated. As a global ensemble forecast system (EFS), PEARP is also used to forecast cyclone tracks. It is shown that it has correctly predicted the landfall of hurricane Sandy. The performance of PEARP as run operationally with these features in 2014 is assessed objectively and compared with that of four operational global EFSs using classical probabilistic scores. This comparison is based on The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data. This is one of the first evaluations of EFSs for short‐range forecasts. The reliability and global skill of the five EFSs are evaluated over a three‐month period with scores computed against observations. PEARP shows skill comparable to or better than the other EFSs.
Land surface spinup for episodic modeling Angevine, W. M; Bazile, E; Legain, D ...
Atmospheric chemistry and physics,
08/2014, Letnik:
14, Številka:
15
Journal Article, Publication
Recenzirano
Odprti dostop
Soil moisture strongly controls the surface fluxes in mesoscale numerical models, and thereby influences the boundary layer structure. Proper initialization of soil moisture is therefore critical for ...faithful simulations. In many applications, such as air quality or process studies, the model is run for short, discrete periods (a day to a month). This paper describes one method for soil initialization in these cases – self-spinup. In self-spinup, the model is initialized with a coarse-resolution operational model or reanalysis output, and run for a month, cycling its own soil variables. This allows the soil variables to develop appropriate spatial variability, and may improve the actual values. The month (or other period) can be run more than once if needed. The case shown is for the Boundary Layer Late Afternoon and Sunset Turbulence experiment, conducted in France in 2011. Self-spinup adds spatial variability, which improves the representation of soil moisture patterns around the experiment location, which is quite near the Pyrenees Mountains. The self-spinup also corrects a wet bias in the large-scale analysis. The overall result is a much-improved simulation of boundary layer structure, evaluated by comparison with soundings from the field site. Self-spinup is not recommended as a substitute for multi-year spinup with an offline land data assimilation system in circumstances where the data sets required for such spinup are available at the required resolution. Self-spinup may fail if the modeled precipitation is poorly simulated. It is an expedient for cases when resources are not available to allow a better method to be used.
The SMOSMANIA soil moisture network in Southwestern France is used to evaluate modelled and remotely sensed soil moisture products. The surface soil moisture (SSM) measured in situ at 5 cm permits to ...evaluate SSM from the SIM operational hydrometeorological model of Météo-France and to perform a cross-evaluation of the normalised SSM estimates derived from coarse-resolution (25 km) active microwave observations from the ASCAT scatterometer instrument (C-band, onboard METOP), issued by EUMETSAT and resampled to the Discrete Global Grid (DGG, 12.5 km gridspacing) by TU-Wien (Vienna University of Technology) over a two year period (2007–2008). A downscaled ASCAT product at one kilometre scale is evaluated as well, together with operational soil moisture products of two meteorological services, namely the ALADIN numerical weather prediction model (NWP) and the Integrated Forecasting System (IFS) analysis of Météo-France and ECMWF, respectively. In addition to the operational SSM analysis of ECMWF, a second analysis using a simplified extended Kalman filter and assimilating the ASCAT SSM estimates is tested. The ECMWF SSM estimates correlate better with the in situ observations than the Météo-France products. This may be due to the higher ability of the multi-layer land surface model used at ECMWF to represent the soil moisture profile. However, the SSM derived from SIM corresponds to a thin soil surface layer and presents good correlations with ASCAT SSM estimates for the very first centimetres of soil. At ECMWF, the use of a new data assimilation technique, which is able to use the ASCAT SSM, improves the SSM and the root-zone soil moisture analyses.
We test a recently developed engineering turbulence model, a so-called explicit algebraic Reynolds-stress (EARS) model, in the context of the atmospheric boundary layer. First of all, we consider a ...stable boundary layer used as the well-known first test case from the Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study (GABLS1). The model is shown to agree well with data from large-eddy simulations (LES), and this agreement is significantly better than for a standard operational scheme with a prognostic equation for turbulent kinetic energy. Furthermore, we apply the model to a case with a (idealized) diurnal cycle and make a qualitative comparison with a simpler first-order model. Some interesting features of the model are highlighted, pertaining to its stronger foundation on physical principles. In particular, the use of more prognostic equations in the model is shown to give a more realistic dynamical behaviour. This qualitative study is the first step towards a more detailed comparison, for which additional LES data are needed.
The parameterization of the stably stratified atmospheric boundary layer is a difficult issue, having a significant impact on medium-range weather forecasts and climate integrations. To pursue this ...further, a moderately stratified Arctic case is simulated by nineteen single-column turbulence schemes. Statistics from a large-eddy simulation intercomparison made for the same case by eleven different models are used as a guiding reference. The single-column parameterizations include research and operational schemes from major forecast and climate research centres. Results from first-order schemes, a large number of turbulence kinetic energy closures, and other models were used. There is a large spread in the results; in general, the operational schemes mix over a deeper layer than the research schemes, and the turbulence kinetic energy and other higher-order closures give results closer to the statistics obtained from the large-eddy simulations. The sensitivities of the schemes to the parameters of their turbulence closures are partially explored.PUBLICATION ABSTRACT
Social media, which functions as a transmitter of sociocultural ideals defining constructs such as beauty and thinness, has been shown to negatively impact the body image of girls and young women. ...Because there has been a lack of research on whether this impact extends beyond young populations, this convergent mixed methods study investigated the impact of social media use on the body image of midlife women and older women. The results of this study indicated that social media use negatively impacts the body image of midlife and older women and demonstrated the complexity of age as a mediating factor for body image concerns in older women. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: journal abstract)
...as a check at the local scale, the daily forecasts from both the parallel and the operational suites were compared to observations from the Monitoring the Usable Soil Reservoir Experimentally ...(MUREX) field experiment (Calvet et al. 1998) for the two intensive validation periods. ...the forecast of latent heat fluxes is improved, with an average of 48 W m22 over 24 h for the parallel suite, to be compared to 45 W m22 for observations and 73 W m22 for the operational suite.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Results are presented of the GASS/EUCLIPSE single‐column model intercomparison study on the subtropical marine low‐level cloud transition. A central goal is to establish the performance of ...state‐of‐the‐art boundary‐layer schemes for weather and climate models for this cloud regime, using large‐eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North‐Eastern Pacific, while one reflects conditions in the North‐Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low‐level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well‐known “too few too bright” problem. The boundary‐layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization.
Key Points
SCM simulations of low‐level cloud transitions are confronted with LES results
Longstanding problems are identified along with encouraging progress
The model‐ensemble median outperforms the individual models
Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface ...radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stations near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in‐depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud‐related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.
Key Points
Surface temperature biases in SGP are associated with large shortwave and longwave radiation biases in NWP and climate models
Convective clouds contribute most to the radiation biases, although most models experience contributions from the surface albedo as well
Models rain too much and too often in the afternoon, yet have convective clouds that are too transparent to SW radiation
We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen temperature biases over ...the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from nine institutes, perform a series of 5 day hindcasts, each initialized from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally, a strong diurnal cycle in the screen temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.
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