Action De Recherche Petite Echelle Grande Echelle Research Articles

A global observing‐system simulation experiment for the EPS–Sterna microwave constellation

AbstractA constellation of microwave sounders named the EUMETSAT Polar System–Sterna (EPS–Sterna) is under study at the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), with the aim of complementing the backbone orbits of the global observing system in low Earth orbit. The satellites of this constellation would be similar to the Arctic Weather Satellite (AWS), which is being developed by the European Space Agency (ESA). The microwave sounder on board AWS is equipped with temperature sounding channels around the 50‐GHz oxygen absorption band, water‐vapour sounding channels around the 183‐ and 325‐GHz absorption bands, and also window channels at 89 and 165 GHz. An observing‐system simulation experiment (OSSE) has been conducted at the Centre National de Recherches Météorologiques (CNRM) to evaluate the impact of this constellation on numerical weather prediction (NWP) at the global scale with the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) model. Two periods ranging from August–October 2021 and December 2021–February 2022 have been chosen to compute the nature run and to run 4D‐Var data assimilation experiments. As validation of the OSSE framework, the impact of a Metop‐B denial experiment in the OSSE is compared with the impact of a Metop‐B denial with real observations. This comparison shows that the Metop‐B denial impacts are very similar in the OSSE and with real observations, with the OSSE slightly overestimating the impact. Then, the impacts of various scenarios for the EPS–Sterna constellation are assessed by computing forecast errors, fractions skill scores, and moist global energy norms, and comparing these with the results of a baseline experiment without the EPS–Sterna constellation. Significant and positive improvements of the forecasts are found up to 96 h, for every variable tested, with an impact increasing with the number of satellites.

Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates

Abstract. A novel method of comparison between an atmospheric model and satellite probabilistic estimates of relative humidity (RH) in the tropical atmosphere is presented. The method is developed to assess the Météo-France numerical weather forecasting model ARPEGE (Action de Recherche Petite Echelle Grande Echelle) using probability density functions (PDFs) of RH estimated from the SAPHIR (Sondeur Atmosphérique du Profil d'Humidité Intertropicale par Radiométrie) microwave sounder. The satellite RH reference is derived by aggregating footprint-scale probabilistic RH to match the spatial and temporal resolution of ARPEGE over the April–May–June 2018 period. The probabilistic comparison is discussed with respect to a classical deterministic comparison confronting each model RH value to the reference average and using a set confidence interval. This study first documents the significant spatial and temporal variability in the reference distribution spread and shape. We demonstrate the need for a finer assessment at the individual case level to characterize specific situations beyond the classical bulk comparison using determinist “best” reference estimates. The probabilistic comparison allows for a more contrasted assessment than the deterministic one. Specifically, it reveals cases where the ARPEGE-simulated values falling within the deterministic confidence range actually correspond to extreme departures in the reference distribution, highlighting the shortcomings of the too-common Gaussian assumption of the reference, on which most current deterministic comparison methods are based.

Significant additional Antarctic warming in atmospheric bias-corrected ARPEGE projections with respect to control run

Abstract. In this study, we use run-time bias correction to correct for the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) atmospheric model systematic errors on large-scale atmospheric circulation. The bias-correction terms are built using the climatological mean of the adjustment terms on tendency errors in an ARPEGE simulation relaxed towards ERA-Interim reanalyses. The bias reduction with respect to the Atmospheric Model Intercomparison Project (AMIP)-style uncorrected control run for the general atmospheric circulation in the Southern Hemisphere is significant for mean state and daily variability. Comparisons for the Antarctic Ice Sheet with the polar-oriented regional atmospheric models MAR and RACMO2 and in situ observations also suggest substantial bias reduction for near-surface temperature and precipitation in coastal areas. Applying the method to climate projections for the late 21st century (2071–2100) leads to large differences in the projected changes of the atmospheric circulation in the southern high latitudes and of the Antarctic surface climate. The projected poleward shift and strengthening of the southern westerly winds are greatly reduced. These changes result in a significant 0.7 to 0.9 K additional warming and a 6 % to 9 % additional increase in precipitation over the grounded ice sheet. The sensitivity of precipitation increase to temperature increase (+7.7 % K−1 and +9 % K−1) found is also higher than previous estimates. The highest additional warming rates are found over East Antarctica in summer. In winter, there is a dipole of weaker warming and weaker precipitation increase over West Antarctica, contrasted by a stronger warming and a concomitant stronger precipitation increase from Victoria to Adélie Land, associated with a weaker intensification of the Amundsen Sea Low.

Sensitivity of Aeolus HLOS winds to temperature and pressure specification in the L2B processor

Abstract. The retrieval of wind from the first Doppler wind lidar of European Space Agency (ESA) launched in space in August 2018 is based on a series of corrections necessary to provide observations of a quality useful for numerical weather prediction (NWP). In this paper we examine the properties of the Rayleigh–Brillouin correction necessary for the retrieval of horizontal line-of-sight wind (HLOS) from a Fabry–Pérot interferometer. This correction is taking into account the atmospheric stratification, namely temperature and pressure information that are provided by a NWP model as suggested prior to launch. The main goal of the study is to evaluate the impact of errors in simulated atmospheric temperature and pressure information on the HLOS sensitivity by comparing the Integrated Forecast System (IFS) and Action de Recherche Petite Echelle Grande Echelle (ARPEGE) global model temperature and pressure short-term forecasts collocated with the Aeolus orbit. These errors are currently not taken into account in the computation of the HLOS error estimate since its contribution is believed to be small. This study largely confirms this statement to be a valid assumption, although it also shows that model errors could locally (i.e. jet-stream regions, below 700 hPa over both earth poles and in stratosphere) be significant. For future Aeolus follow-on missions this study suggests considering realistic estimations of errors in the HLOS retrieval algorithms, since this will lead to an improved estimation of the Rayleigh–Brillouin sensitivity uncertainty contributing to the HLOS error estimate and better exploitation of space lidar winds in NWP systems.

Energy Demand Forecasting Using Deep Learning: Applications for the French Grid

This paper investigates the use of deep learning techniques in order to perform energy demand forecasting. To this end, the authors propose a mixed architecture consisting of a convolutional neural network (CNN) coupled with an artificial neural network (ANN), with the main objective of taking advantage of the virtues of both structures: the regression capabilities of the artificial neural network and the feature extraction capacities of the convolutional neural network. The proposed structure was trained and then used in a real setting to provide a French energy demand forecast using Action de Recherche Petite Echelle Grande Echelle (ARPEGE) forecasting weather data. The results show that this approach outperforms the reference Réseau de Transport d’Electricité (RTE, French transmission system operator) subscription-based service. Additionally, the proposed solution obtains the highest performance score when compared with other alternatives, including Autoregressive Integrated Moving Average (ARIMA) and traditional ANN models. This opens up the possibility of achieving high-accuracy forecasting using widely accessible deep learning techniques through open-source machine learning platforms.

Homogeneity criteria from AVHRR information within IASI pixels in a numerical weather prediction context

Abstract. This article focuses on the selection of satellite infrared IASI (Infrared Atmospheric Sounding Interferometer) observations in the global numerical weather prediction (NWP) system ARPEGE (Action de Recherche Petite Echelle Grande Echelle). The observation simulation is performed with the sophisticated radiative transfer model RTTOV-CLD, which takes into account the cloud scattering and the multilayer clouds from atmospheric profiles and cloud microphysical profiles (liquid water content, ice content and cloud fraction). The aim of this work is to select homogeneous scenes by using the information of the collocated Advanced Very High Resolution Radiometer (AVHRR) pixels inside each IASI field of view and to retain the most favourable cases for the assimilation of IASI infrared radiances. Two methods to select homogeneous scenes using homogeneity criteria already proposed in the literature were adapted: the criteria derived from Martinet et al. (2013) for cloudy sky selection in the French mesoscale model AROME (Applications of Research to Operations at MEsoscale) and the criteria from Eresmaa (2014) for clear-sky selection in the global model IFS (Integrated Forecasting System). A comparison between these methods reveals considerable differences, in both the method to compute the criteria and the statistical results. From this comparison a revised method representing a kind of compromise between the different tested methods is proposed and it uses the two infrared AVHRR channels to define the homogeneity criteria in the brightness temperature space. This revised method has a positive impact on the observation minus the simulation statistics, while retaining 36 % of observations for the assimilation. It was then tested in the NWP system ARPEGE for the clear-sky assimilation. These criteria were added to the current data selection based on the McNally and Watts (2003) cloud detection scheme. It appears that the impact on analyses and forecasts is rather neutral.

Assimilation of IASI Ozone‐Sensitive Channels in Preparation for an Enhanced Coupling Between Numerical Weather Prediction and Chemistry Transport Models

AbstractIn this study, IASI ozone‐sensitive channels have been assimilated in 1D‐Var data assimilation combined with realistic ozone background coming from a MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle) Chemistry Transport Model (CTM) as a first stage of coupling between Numerical Weather Prediction (NWP) and MOCAGE CTM at Météo‐France for global model ARPEGE (Action de Recherche Petite Echelle Grande Echelle). To evaluate the impact of ozone‐sensitive channels on analyses, databases of 161 temperatures, humidity, and ozone radiosondes across the globe during a 1‐year period have been considered. Ozone forecast from MOCAGE CTM was evaluated with radiosondes and used as input for the Radiative Transfer Model (RTM) RTTOV. Statistics of IASI observations minus simulations show that the use of ozone from MOCAGE CTM allows to better simulate IASI ozone‐sensitive channels. The Desroziers method is used to diagnose observation error covariance matrix and estimate realistic ozone observation standard errors taking into account cross‐correlations between IASI channels. The background error covariance matrix for ozone is estimated using radiosondes. A control run assimilating 123 IASI operational channels is compared to an experiment which assimilates, in addition, 15 IASI ozone‐sensitive channels. Results show potential benefits of IASI ozone‐sensitive channels combined with realistic ozone from MOCAGE CTM to improve temperature, humidity and ozone analyses simultaneously. This work is an encouraging first step for the enhancing of the coupling between the global model ARPEGE and MOCAGE CTM.

Combining an EKF soil analysis with a 3D‐Var upper‐air assimilation in a limited‐area NWP model

In recent years, the Extended Kalman Filter (EKF) has been gaining more attention in the surface data assimilation (DA) community and has already replaced the older Optimal Interpolation (OI) scheme for the vertical component of the land surface DA system in a number of meteorological institutes. An EKF has been developed within the standalone land‐surface modelling platform SURFace Externalisée (SURFEX) for the initialisation of soil temperature and soil water content based on screen‐level temperature and relative humidity. In this article we present a new combination of the EKF with a basic (using conventional observations only) three‐dimensional variational (3D‐Var) upper‐air assimilation for the limited‐area model ALARO coupled to SURFEX. This new combination is compared to an Open Loop experiment where all initial conditions are interpolated from an analysis of the global numerical weather prediction model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and to an experiment where the surface is initialised using the EKF, while the upper‐air initial conditions are interpolated from the ARPEGE analysis. The aim of this article is to examine whether the EKF surface assimilation coupled or not with a basic 3D‐Var upper‐air assimilation has an added value compared to the Open Loop, in which the more advanced upper‐air data assimilation of ARPEGE with more observations used is interpolated onto the limited‐area model grid. All set‐ups are verified during a 1‐year period 2013 against soil measurements, screen‐level observations, radiosoundings and merged radar–rain‐gauge precipitation observations. Results indicate that the EKF surface assimilation has positive effects on humidity scores and is able to produce similar or improved scores compared to the Open Loop. While the upper‐air 3D‐Var DA system of ALARO still needs improvements, the potential benefits of the combination of upper‐air and surface assimilation are demonstrated through soil moisture and screen‐level relative humidity verifications.

A parallel implementation of a 4DEnVar ensemble

The four‐dimensional ensemble variational (4DEnVar) formulation has received considerable attention during recent years, especially at numerical weather prediction centres that are (or were) relying on a 3D/4D‐Var formalism for their data assimilation systems. Since 4DEnVar background‐error covariances are, by construction, given by an ensemble of 4D nonlinear trajectories, an important issue is the way in which to build this ensemble. The use of an ensemble of perturbed 4DEnVar to generate the ensemble is a natural approach, but raises difficulties for the input and storage of 4D trajectories. A parallel implementation of such a 4DEnVar ensemble (En‐4DEnVar) approach is proposed, with distributed input and storage of ensemble perturbations. It has the benefit of an object‐oriented implementation of 4DEnVar, which has recently been developed at Météo‐France. First results obtained with the French global model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) show that such an approach is efficient and suggest that En‐4DEnVar implementations are tractable.

Improving spatial localization in 4DEnVar

The four‐dimensional ensemble‐variational (4DEnVar) formulation is a credible alternative to the 4D‐Var formulation, especially for numerical weather prediction centres that have invested a lot in this latter formulation during the last decades. First implementations of this technique, however, rely on a simplified form for the localization of the 4D covariances inside the assimilation period. It is shown in this article that the use of a unique localization for all cross‐covariances between perturbations at different times can be a crude approximation, especially in areas where the mean flow speed is large. To overcome this problem, a Lagrangian advection of the localization is proposed. It is first tested in the simplified Burgers' model and then introduced in the real‐size system associated with the French global model Action de Recherche Petite Echelle Grande Echelle (ARPEGE). The test of this advection in both environments shows a significant positive impact in regions where the advection is large. The possibility of using such a Lagrangian advection to evolve the static initial covariance matrix in a flow‐dependent way inside the assimilation period, in a hybrid 4DEnVar formulation, is also investigated.

PEARP, the Météo‐France short‐range ensemble prediction system

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.

Investigating the impact of the water‐vapour sounding observations from SAPHIR on board Megha‐Tropiques for the ARPEGE global model

Data assimilation experiments of radiances from the microwave sounder SAPHIR on board the Megha‐Tropiques (MT) satellite were conducted using the global numerical weather prediction (NWP) model ARPEGE (Action de Recherche Petite Echelle Grande Echelle) operational at Météo‐France for the period June to August 2012. The combination of the MT's low‐inclined orbit with the SAPHIR's six channels was found to increase the number of assimilated humidity‐sensitive microwave observations in the Tropics by a factor of 3.8, compared with a control experiment using three existing Advanced Microwave Sounding Unit B and Microwave Humidity Sounder instruments. Impacts of SAPHIR on both analyses through the 4D‐Var system and forecasts are found to be positive with respect to radiosonde data and analyses by the European Centre for Medium‐range Weather Forecasts up to 12 h and neutral to positive up to 72 h. In particular, the improvement of innovation statistics for other humidity‐sensitive satellite observations when SAPHIR is assimilated indicates a positive synergy of the MT satellite with the present observing system. In addition to providing new humidity observations in the Tropics, the SAPHIR data can also be used to define new diagnostics for NWP models. In particular: (i) with the MT's orbit being non‐heliosynchronous, all local times are observed by the same sensor for a given area, which makes diurnal cycle diagnostics straightforward to set up; (ii) with SAPHIR providing more information on the vertical (six channels) than similar sensors, it can be easily used to study water‐vapour vertical structures in NWP models. The first diagnostic applied to the ARPEGE model reveals a good consistency between observed and modelled diurnal cycles in analyses over western Africa, but also reveals a 2–4 h time lag between mean observed and equivalent model brightness temperatures. The second diagnostic highlights a well‐represented vertical correlation of simulated brightness temperatures from the ARPEGE model with respect to SAPHIR over western Africa, but a too‐low vertical correlation over drier regions such as the southern Pacific Ocean during the period June to August 2012.

Estimation and diagnosis of heterogeneous flow-dependent background-error covariances at the convective scale using either large or small ensembles

A 90 member ensemble assimilation experiment is run on a severe weather event for the convective-scale Application de la Recherche a l'Operationnel a Meso-Echelle (model AROME-France), coupled to a global 90 member Action de Recherche Petite Echelle Grande Echelle (ARPEGE) ensemble. Background-error covariances are diagnosed for this period, in order to examine flow-dependent features, sampling noise effects associated with six-member estimates (corresponding to the size of a preliminary research AROME ensemble) and a comparison between AROME and ARPEGE estimates. The dependence of error covariances on the weather situation is illustrated for low-level specific humidity in particular, which is associated, for example, with large variance values over the Mediterranean area. While this large-scale contrast is visible in both AROME and ARPEGE ensembles, differences between the two ensembles are also apparent as expected, for instance due to resolution differences. The effects of sampling noise are investigated by comparing independent six-member and 84 member estimates of variances and correlation length-scales. While the six-member ensemble is able to capture some of the signal of interest, spatial filtering techniques seem to be useful in order to reduce estimation errors.

Extratropical Summertime Response to Tropical Interannual Variability in an Idealized GCM

Abstract A primitive equation model is used to investigate the role of the tropics in generating seasonal-mean anomalies in the extratropics. A nudging technique is applied to guide selected tropical regions toward 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the National Centers for Environmental Prediction (NCEP)/Department of Energy Reanalysis (NCEP-2). The time-independent linear response to these tropical anomalies is calculated for extratropical basic states taken from reanalysis climatologies and also from the climatological states of Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and Laboratoire de Météorologie Dynamique (LMDZ) general circulation model simulations. For summer case studies, time-independent linear solutions show that some seasonal anomalies can be attributed to linear wave propagation from the tropics, especially for lower extratropical latitudes. If nudging is applied to the anomaly part of the tropical flow, the linear response shows little dependence on the basic state. Regional tropical nudging experiments display a global extratropical response. The persistent European summer anomaly in 2003 is partly attributable to a linear response to both Central American and West African monsoon circulations. The African region also triggers a wave train along the Asian subtropical jet. The model is then used in “simple GCM” mode to obtain extratropical responses that include a contribution from transient eddies. Tropical nudging improves the simple GCM's stationary wave climatology, and transient eddy forcing can produce substantial seasonal anomalies at high latitudes with better correspondence to some observed cases, especially in the Western Hemisphere, with stronger communication between the Asian monsoon and North America.

Driftsonde Observations to Evaluate Numerical Weather Prediction of the Late 2006 African Monsoon

AbstractDuring the international African Monsoon Multidisciplinary Analysis (AMMA) project, stratospheric balloons carrying gondolas called driftsondes capable of dropping meteorological sondes were deployed over West Africa and the tropical Atlantic Ocean. The goals of the deployment were to test the technology and to study the African easterly waves, which are often the forerunners of hurricanes. Between 29 August and 22 September 2006, 124 sondes were dropped over the seven easterly waves that moved across Africa into the Atlantic between about 10° and 20°N, where almost no in situ vertical information exists. Conditions included waves that developed into Tropical Storm Florence and Hurricanes Gordon and Helene. In this study, a selection of numerical weather prediction model outputs has been compared with the dropsondes to assess the effect of some developments in data assimilation on the quality of analyses and forecasts. By comparing two different versions of the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) model of Météo-France with the dropsondes, first the benefits of the last data assimilation updates are quantified. Then comparisons are carried out using the ARPEGE model and the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts. It is shown that the two models represent very well the vertical structure of temperature and humidity over both land and sea, and particularly within the Saharan air layer, which displays humidity below 5%–10%. Conversely, the models are less able to represent the vertical structure of the meridional wind. This problem seems to be common to ARPEGE and IFS, and its understanding still requires further investigations.

About the Reliability of Manual Model PV Corrections to Improve Forecasts

Abstract The National Weather Forecast Centre of Météo-France has developed a tool that corrects the state of the atmosphere within the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) operational global model by adjusting the potential vorticity when the initial conditions and available observations disagree. Among observational datasets, geostationary satellite data are the primary source of information. Here, the representation of the coherent structures of the tropopause in the model is assessed with Meteosat ozone and water vapor images. Modifications to the initial conditions of the potential vorticity (PV) in areas where the model fails can be applied using a potential vorticity inversion, thus providing a new balanced distribution of the wind and temperature that will then be used as a new initial state. The purpose of the paper is to investigate the degrees of weakness of the present qualitative approach. To this end, PV modifications to the initial conditions are applied by different experts on the eve of the windstorm Klaus (24 January 2009) that hit southwestern France. The different initial PV fields and the subsequent forecasts show significant differences in terms of wind and mean sea level pressure, while sharing some common features. The human modification process is therefore partially reproducible and skillful since the forecast is improved most of the time.

Tropical transition of a Mediterranean storm by jet crossing

AbstractThe tropical transition of a Mediterranean storm that occurred on 26 September 2006 over southeastern Italy is investigated. The explosive development classified this cyclone as a bomb and its full‐tropospheric warm core as a tropical‐like storm or medicane. Forecasts at different scales were analysed to identify the key mechanisms in the explosive development of the medicane. At 108 h lead time, the European Centre for Medium‐Range Weather Forecasts (ECMWF) failed to predict the medicane and the associated upper‐level trough downstream of the ex‐tropical cyclone Helene during its extratropical transition. At shorter range, forecasts by both ECMWF and Action de Recherche Petite Echelle Grande Echelle (ARPEGE) increasingly improved with decreasing lead times. The depth of the medicane was missed, however, probably because of the too low resolution with respect to the 60 km diameter cyclone. Forecasts at kilometre scale were run using the mesoscale model Meso‐NH and verified against in situ and satellite observations. The Meso‐NH forecasts were found to be very sensitive to the initial conditions. Reduced static stability at the southern tip of the upper‐level trough determined the convective activity around the pre‐existing mesocyclone. The medicane was then formed only if enough vertically developed convection was further enhanced by the jet‐induced upward forcing. Otherwise, no tropical transition of the mesocyclone was predicted. This study shows the role of an upper‐level jet in explosively deepening a mesocyclone into a tropical storm. Copyright © 2011 Royal Meteorological Society

Impact of IASI assimilation at global and convective scales and challenges for the assimilation of cloudy scenes

AbstractSince July 2008, Infrared Atmospheric Sounder Interferometer (IASI) radiances have been assimilated in the French global model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and since April 2010 at high density in the French convective‐scale model Applications of Research to Operations at MEsoscale (AROME).The impact of the assimilation of clear IASI data on forecast skill is found to be positive for both models. As many observed scenes are cloudy, several ways to characterize the clouds within the observed spectra are investigated. Firstly, a simple approach that enables the determination of both the cloud‐top pressure and the effective cloud amount of an equivalent single‐layer cloud is followed using a CO2‐slicing method. The first assimilation trials in overcast conditions lead to a small positive impact on forecast skill. Another approach would be to take advantage of the fact that cloud water variables are described at high resolution in the convective‐scale model AROME. Model cloud fields have to be used in conjunction with a cloudy radiative transfer model. The first simulations using this technique are performed and compared against observations. Copyright © 2011 Royal Meteorological Society

The Impacts of AMMA Radiosonde Data on the French Global Assimilation and Forecast System

Abstract The high vertical density soundings recorded during the 2006 African Monsoon Multidisciplinary Analysis (AMMA) campaign are assimilated into the French numerical weather prediction Action de Recherche Petite Echelle Grande Echelle (ARPEGE) four-dimensional variational data assimilation (4DVAR) system, with and without a bias correction for relative humidity. Four different experiments are carried out to assess the impacts of the added observations. The analyses and forecasts from these different scenarios are evaluated over western Africa. For the full experiment using all data together with a bias correction, the humidity analysis is in better agreement with surface observations and independent GPS observations than it was for the other experiments. AMMA data also improve the African easterly jet (AEJ) on its southeasterly side, and when they are used with an appropriate bias correction, the daily and monthly averaged precipitation results are in relatively good agreement with the satellite-based precipitation estimates. Forecast scores are computed with respect to surface observations, radiosondes, and analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF). The positive impacts of additional radiosonde observations (with a relevant bias correction) are found to propagate downstream with a positive impact over Europe at the 2–3-day forecast range.

Impact of initial condition uncertainties on the predictability of heavy rainfall in the Mediterranean: a case study

AbstractThis study explores the predictability of a heavy rainfall event that struck North Africa on 9 and 10 November 2001. This case is a paradigm of Mediterranean extreme events characterized by the presence of a deep upper‐level trough associated with an intense cyclone which developed over the Western Mediterranean basin. Using the French non‐hydrostatic mesoscale model MESO‐NH, numerical experiments starting from various initial atmospheric states were conducted to assess the impact of initial condition uncertainties on the precipitation and cloud cover forecast. To generate a set of perturbed atmospheric states, a simple date‐shifting initialization method was used. Two sets of simulations were run, using lateral boundaries and initial conditions derived from both the French operational global assimilation system Action de Recherche Petite Echelle Grande Echelle (ARPEGE) and the European Centre for Medium‐Range Weather Forecasts (ECMWF) system. Initial perturbations applied to the upper‐level trough propagated and intensified throughout the simulation, leading to some discrepancy in the forecast of the low‐level cyclone. While it was found that the upper‐level trough and the surface cyclone controlled the location of the overall precipitation pattern, the predictability of smaller‐scale features such as localized heavy rainfall was directly related to specific mesoscale structures. The low‐level jet associated with the surface cyclone and the location and the intensity of the surface‐low both impact upon the triggering and the sustainment of the convective cells. In consequence, small‐scale perturbations of these mesoscale features led to large errors in the precipitation forecast, especially in the Algiers area. Copyright © 2008 Royal Meteorological Society