Search Results

You are looking at 1 - 10 of 24 items for

  • Author or Editor: Jean-François Mahfouf x
  • Refine by Access: All Content x
Clear All Modify Search
Jean-François Mahfouf

Abstract

The main purpose of this paper is to demonstrate that it is possible to estimate soil moisture from the evolution of atmospheric parameters near the surface (temperature and relative humidity) if a realistic surface transfer model is available. Two methods to initialize soil moisture in meteorological models are then proposed: a variational method where the optimal soil moisture minimizes a penality function and a sequential method consisting of a set of predictions and static corrections of soil moisture. The algorithms are examined with a one-dimensional model including a detailed land-surface parameterization. A feasibility study is undertaken using the HAPEX-MOBILHY dataset where soil moisture has been measured together with atmospheric parameters. It is demonstrated that for three 48-h clear-sky periods the two methods are able to converge rapidly toward a realistic soil moisture content starting from arbitrary values.

Full access
Jean-François Mahfouf

Abstract

A simple Kuo-type convection scheme with an improved closure based on moist enthalpy accession (Kuo symmetric) has been linearized for the tangent-linear (TL) and adjoint (AD) versions of the Global Environmental Multiscale (GEM) model. The nonlinear scheme exhibits a reasonable behavior in terms of heating and moistening rates when evaluated in stand-alone mode over a set of deep convective profiles. A preliminary evaluation of a straightforward linearization in the global TL model has revealed the existence of noise that leads to an unacceptable solution after 12 h of integration. By neglecting several terms in the linearization (detrainment rate and cloud properties), the temporal evolution of humidity analysis increments is improved by including this simplified linearized convection scheme in the TL model. The behavior of the linearized scheme has also been compared favorably to the linearized version of the European Centre for Medium-Range Weather Forecasts (ECMWF) mass-flux convection scheme. When examining the validity of the TL approximation for surface precipitation, it appears that linearization errors are large for both stratiform and convective rainfall (rms errors are about twice the mean absolute perturbed precipitation). These errors are not reduced when considering accumulated rain rates instead of instantaneous quantities. However, the occurrence of “on–off” processes is reduced by a temporal integration of rain. This could make the variational assimilation of accumulated precipitation rates easier. Finally, errors coming from internal nonlinearities are slightly larger than those produced by discontinuities. This confirms the interest for improving the linearity of nonlinear convection schemes for applications in variational contexts.

Full access
Jean-François Mahfouf and Bruno Jacquemin

Abstract

Rainfall interception by vegetation canopies is studied using a parameterization of land surface Processes for mesoscale meteorological models. The interception scheme allows for a single vegetation canopy, and manages interception through a prognostic variable representing the amount of liquid water retained by the foliage.

A set of 24 h simulation fully interactive with the boundary layer, is carried out with a one-dimensional model in order to examine the sensitivity of the interception scheme to vegetation properties. The evaporation from the interception reservoir is strongly enhanced by high values of the roughness length. The leaf area index, acting on the maximum storm capacity, modifies the drying time of the foliage.

As a first stage of validation, the interception scheme is compared with other models developed for hydrological purposes. It appears that the scheme is not very different from the single-layer Rutter model, which has been well tested and validated. Only minor differences are noticed between the results of the two models. The scheme is also compared with a multilayer model that provides a more physical description of the rainfall interception. The main departure concerns the drying time of the canopy, which is almost independent of the rainfall rate in the single-layer model.

Finally, a validation of the interception scheme is made using micrometeorological data from the HAPEX-MOBILHY experiment. Six simulations lasting 24 h indicate that the parameterization reproduces quite well the daily evolution of the components of the surface energy balance for various surface conditions and various rainfall distributions.

Full access
Virginie Marécal and Jean-François Mahfouf

Abstract

This paper studies the impact of assimilating rain-derived information in the European Centre for Medium-Range Weather Forecasts (ECMWF) four-dimensional variational (4DVAR) system. The approach is based on a one-dimensional variational (1DVAR) method. First, model temperature and humidity profiles are adjusted by assimilating observed surface rain rates in 1DVAR. Second, 1DVAR total column water vapor (TCWV) estimates are assimilated in 4DVAR. Observations used are Tropical Rainfall Measuring Mission (TRMM) surface rain-rate estimates from the TRMM Microwave Imager.

Two assimilation experiments making use of 1DVAR TCWV were run for a 15-day period. The “Rain-1” experiment only assimilates 1DVAR retrievals where the observed rain rate is nonzero while the “Rain-2” experiment assimilates all 1DVAR TCWV estimates. The period selected includes Hurricane Bonnie, which was well sampled by TRMM (late August 1998).

Results show a positive impact on the humidity analysis of assimilating 1DVAR TCWV in 4DVAR. The model rain rates at the analysis time are closer to the TRMM observations showing a posteriori the consistency of the two-step approach chosen to assimilate rain-rate information in 4DVAR. The modification of the humidity analysis induces changes in the wind and pressure analysis. In particular the analysis of the track of Hurricane Bonnie is noticeably improved for the early stage of the storm development for both the Rain-1 and Rain-2 experiments. When Bonnie is in a mature stage the influence of the 1DVAR TCWV assimilation is to intensify the hurricane. Comparison with Clouds and the Earth's Radiant Energy System (CERES) measurements also show a neutral impact on the radiative fluxes at the top-of-the atmosphere when using 1DVAR TCWV estimates.

The impact on the forecasts is a slight reduction of the model precipitation spindown over tropical oceans. Objective scores for the Tropics are improved, particularly for wind and for upper-tropospheric temperature.

Analysis and forecast results are generally better for the Rain-2 experiment compared to Rain-1, implying that the 1DVAR TCWV estimates retrieved where no rain is observed provide useful information to 4DVAR.

Full access
Jean-François Mahfouf and Bernard Bilodeau

Abstract

The adjoint version of the Global Environmental Multiscale model including a comprehensive package of simplified and linearized physical processes (large-scale condensation, deep moist convection, vertical diffusion, and subgrid-scale orographic effects) is used to evaluate the sensitivity of surface precipitation to initial conditions for up to 24 h for two meteorological systems: a midlatitude front and a tropical cyclone. Such diagnostics are useful to improve the understanding on variational assimilation of precipitation data. In agreement with a similar study, the largest sensitivity is found with respect to the temperature field for both stratiform and convective precipitation. Close to the observation time and for stratiform precipitation, the sensitivity with respect to specific humidity is rather large, which corroborates conclusions from previous one-dimensional variational data assimilation experimentations. The sensitivity is then reduced significantly after the observation time. The sensitivities of surface precipitation to the wind components and to specific humidity are comparable and are at a maximum at the observation time. The sensitivity to the surface pressure is always much smaller than the sensitivity to the other variables. In general, sensitivities are largest at the observation time and then decrease. However, for the midlatitude perturbation, the sensitivity is enhanced after 12 h for stratiform precipitation and also for convective precipitation using a scheme based on the moisture convergence closure. This results from a dynamical coupling upstream of the area of interest through baroclinic instability as evidenced by vertically backward-tilted sensitivities. Such enhancement is not observed for the tropical case. The tangent-linear approximation remains acceptable for accumulated precipitation up to 24 h but is rather poor for instantaneous rain rates. The variational assimilation of accumulated precipitation should thus be favored.

Full access
Luc Fillion and Jean-François Mahfouf

Abstract

Some problems posed by the coupling of moist-convective and stratiform precipitation processes for variational assimilation of precipitation-rate data are examined in a 1D-Var framework. Background-error statistics and vertical resolution are chosen to be representative of current operational practice. Three advanced parameterization schemes for moist-convection are studied: the relaxed Arakawa–Schubert (RAS) scheme, Tiedtke’s mass-flux scheme (operational at the European Centre for Medium-Range Weather Forecasts), and the Betts–Miller scheme. Both fractional-stepping and process-splitting approaches for combining physical processes are examined. The behavior of the variational adjustment for background profiles of temperature and specific humidity in the neighborhood of saturation is of particular interest.

In the 1D-Var context examined here, it is demonstrated that the introduction of the stratiform precipitation process can have a negative impact on the minimization in the sense that, even when only slight supersaturation occurs, the minimization is controlled by the stratiform precipitation process at the expense of convective precipitation. This is generally true in process-splitting mode and conditionally true in fractional-stepping mode. The net result in such cases is an adjustment to the wrong type of precipitation over convective regions. In some of the cases examined (1D-Var with the RAS scheme, for instance), it is preferable to deactivate the stratiform precipitation process and to explicitly control the degree of supersaturation during the adjustment of convection. Evaporation of precipitation in subsaturated layers also appears as an important factor influencing the partition of precipitation. The method of fractional stepping appears less problematical compared to the process-splitting approach.

These results also indicate the need for a detailed examination of the partition of precipitation between convective and stratiform type in more sophisticated 3D/4D-Var data assimilation systems, and for a better combined parameterization of the two physical processes.

Full access
Virginie Marécal and Jean-François Mahfouf

Abstract

This paper examines the performance of a one-dimensional variational (1DVAR) assimilation of Tropical Rainfall Measuring Mission satellite-derived surface rainfall rates from the Microwave Imager TMI. Temperature and specific humidity profiles are retrieved that are consistent with both observed and model short-range forecast rain rates.

Two atmospheric situations are examined from ECMWF short-range forecasts at TL319L31 resolution. They encompass tropical cyclones, frontal bands, and mesoscale convective systems. Results show that 1DVAR is generally able to find modified profiles within the range of forecast errors (specified from the operational ECMWF statistics) that provide a precipitation field close to observations. Increments of temperature with respect to the background state are small indicating that 1DVAR essentially adjusts specific humidity to modify precipitation amounts. Consistency checks have been defined in order to discard profiles producing too large departures from the observed rainfall rates or having too little sensitivity of model rain rates to changes in temperature and humidity. Moreover, the current 1DVAR approach is unable to modify profiles when the model rain rate is zero and the observed rain rate is nonzero.

Sensitivity experiments are performed to the specification of observation errors. Observation errors are increased from 25% of the observed value to 50%. It is shown that 1DVAR is still able to assimilate some information from observations. To decrease the computational cost of 1DVAR, two simplifications are explored:a reduction of the control vector by not including temperature profiles and the use of one background field and one observation field instead of seven for each assimilation window. These two approaches will be further evaluated when 1DVAR products are assimilated in the ECMWF four-dimensional variational system.

Full access
Luc Fillion and Jean-François Mahfouf

Abstract

A detailed examination of the Jacobian matrix of sensitivities of the prognostic cloud scheme operational at the European Centre for Medium-Range Weather Forecasts (ECMWF) is presented. These Jacobians exhibit sensitivities of output variables (e.g., cloud condensate) to small input perturbations on temperature and moisture. The coupling of the cloud scheme with the ECMWF convective mass-flux scheme is considered. The sensitivity of the cloud scheme is split into all its contributing parts in order to extract the dominant terms. A selection of contrasted convective cases normally present in a regular operational forecast is considered. Some comparisons are made with a simpler diagnostic cloud scheme.

It is shown that the main contributing terms to the sensitivity in cloud condensate l are the following for cases of deep convection: detrainment from moist convection, evaporation processes, and conversion of cloud water into rain. The structure of the Jacobians in terms of temperature and moisture perturbations in such cases is strongly dominated by the structure of the Jacobians of the convective mass flux at cloud base. Because of this dominance, the Jacobians from a simpler diagnostic cloud scheme have similarities in shape with those produced by the prognostic scheme. For shallow convection cases, the same terms as for deep convective cases are important (convective effects still dominate), but now erosion of clouds becomes significant. Jacobians of integrated l produced by the diagnostic and prognostic cloud schemes here are also similar, still because of the dominance of convective effects. When moist convection plays a negligible role, the dominant terms are the condensation/evaporation effects and the conversion of cloud water into rain. Larger differences are found then between the Jacobians of the prognostic and diagnostic cloud schemes. In such situations, the sensitivity of l with respect to vertical motion plays an equally important role compared to temperature and humidity.

Full access
Frédéric Chevallier and Jean-François Mahfouf

Abstract

In this paper, linearized versions of fast infrared radiative transfer schemes for variational data assimilation are studied. A neural network–based infrared broadband radiation model (NeuroFlux) is compared with the European Centre for Medium-Range Weather Forecasts operational radiation model. Also, the Radiative Transfer for Television and Infrared Observation Satellite Operational Vertical Sounder (RTTOV) scheme for satellite brightness temperature computation is compared with a more physically based scheme: the narrowband Synsatrad model developed at the European Organization for the Exploitation of Meteorological Satellites. The Jacobians are examined. They are converted into flux perturbations with the tangent-linear approximation and into atmospheric variable increments with a one-dimensional variational assimilation system. For NeuroFlux and RTTOV, despite accurate flux and radiance computation, the sensitivity with respect to water vapor needs to be improved. However, the random structure of the neural network derivative error allows the use of NeuroFlux with a single mean Jacobian in the variational context. Also, further improvements to RTTOV are expected from ongoing work on the regression dataset and on the choice of the regression predictors.

Full access
Pascal Marquet, Jean-François Mahfouf, and Daniel Holdaway

Abstract

This study presents a new formulation for the norms and scalar products used in tangent linear or adjoint models to determine forecast errors and sensitivity to observations and to calculate singular vectors. The new norm is derived from the concept of moist-air available enthalpy, which is one of the availability functions referred to as exergy in general thermodynamics. It is shown that the sum of the kinetic energy and the moist-air available enthalpy can be used to define a new moist-air squared norm that is quadratic in 1) wind components, 2) temperature, 3) surface pressure, and 4) water vapor content. Preliminary numerical applications are performed to show that the new weighting factors for temperature and water vapor are significantly different from those used in observation impact studies, and are in better agreement with observed analysis increments. These numerical applications confirm that the weighting factors for water vapor and temperature exhibit a large increase with height (by several orders of magnitude) and a minimum in the midtroposphere, respectively.

Free access