Cross-evaluation of modelled and remotely sensed surface soil moisture with in situ data in southwestern France

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

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

The ALADIN system and its canonical model configurations AROME CY41T1 and ALARO CY40T1

The ALADIN System is a numerical weather prediction (NWP) system developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Meteo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the ALADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here

The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of Earth surface variables and fluxes

CC Attribution 3.0 License.Final revised paper also available at http://www.geosci-model-dev.net/6/929/2013/gmd-6-929-2013.pdfInternational audienceSURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surface: nature, town, inland water and ocean. It can be run either coupled or in offline mode. It is mostly based on pre-existing, well validated scientific models. It can be used in offline mode (from point scale to global runs) or fully coupled with an atmospheric model. SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. It also includes a data assimilation module. The main principles of the organization of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally the main applications of the code are summarized. The current applications are extremely diverse, ranging from surface monitoring and hydrology to numerical weather prediction and global climate simulations. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage

Identification of error sources in convective planetary boundary layer cloud forecasts using SIRTA observations

International audienceIn this study, errors in cloud base height predicted by two numerical weather prediction models is evaluated using observations from the French instrumented site SIRTA. Results show that a significant portion of the error is due to errors in predicted surface relative humidity. These errors are in turn thought to be caused by the convection schemes

From near-surface to root-zone soil moisture using different assimilation techniques

International audienceRoot-zone soil moisture constitutes an important variable for hydrological and weather forecast models. Microwave radiometers like the L-band instrument on board the European Space Agency's (ESA) future Soil Moisture and Ocean Salinity (SMOS) mission are being designed to provide estimates of near surface soil moisture (0-5 cm). This quantity is physically related to root-zone soil moisture through diffusion processes, and both surface and root-zone soil layers are commonly simulated by land surface models (LSMs). Observed time series of surface soil moisture may be used to analyze the root-zone soil moisture using data assimilation systems. In this paper, various assimilation techniques derived from Kalman filters (KFs) and variational methods (VAR) are implemented and tested. The objective is to correct the modeled root-zone soil moisture deficiencies of the newest version of the Interaction between Soil, Biosphere, and Atmosphere scheme (ISBA) LSM, using the observations of the surface soil moisture of the Surface Monitoring of the Soil Reservoir Experiment (SMOSREX) over a 4-yr period (2001-04). This time period includes contrasting climatic conditions. Among the different algorithms, the ensemble Kalman filter (EnKF) and a simplified one-dimensional variational data assimilation (1DVAR) show the best performances. The lower computational cost of the 1DVAR is an advantage for operational root-zone soil moisture analysis based on remotely sensed surface soil moisture observations at a global scale

Three-dimensional dust aerosol distribution and extinction climatology over northern Africa simulated with the ALADIN numerical prediction model from 2006 to 2010

International audienceThe seasonal cycle and optical properties of mineral dust aerosols in northern Africa were simulated for the period from 2006 to 2010 using the numerical atmospheric model ALADIN (Aire Limitée Adaptation dy-namique Développement InterNational) coupled to the surface scheme SURFEX (SURFace EXternalisée). The partic-ularity of the simulations is that the major physical processes responsible for dust emission and transport, as well as ra-diative effects, are taken into account on short timescales and at mesoscale resolution. The aim of these simulations is to quantify the dust emission and deposition, locate the major areas of dust emission and establish a climatology of aerosol optical properties in northern Africa. The mean monthly aerosol optical thickness (AOT) simulated by AL-ADIN is compared with the AOTs derived from the standard Dark Target (DT) and Deep Blue (DB) algorithms of the Aqua-MODIS (MODerate resolution Imaging Spectro-radiometer) products over northern Africa and with a set of sun photometer measurements located at Banizoumbou, Cin-zana, Soroa, Mbour and Cape Verde. The vertical distribution of dust aerosol represented by extinction profiles is also analysed using CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations. The annual dust emission simulated by ALADIN over northern Africa is 878 Tg year −1. The Bodélé Depression appears to be the main area of dust emission in northern Africa, with an average estimate of about 21.6 Tg year −1. The simulated AOTs are in good agreement with satellite and sun photometer observations. The positions of the maxima of the modelled AOTs over northern Africa match the observed positions, and the ALADIN simulations satisfactorily reproduce the various dust events over the 2006–2010 period. The AOT climatology proposed in this paper provides a solid database of optical properties and consolidates the existing climatology over this region derived from satellites, the AERONET network and regional climate models. Moreover, the 3-D distribution of the simulated AOTs also provides information about the vertical structure of the dust aerosol extinction