Study of the Jacobian of an extended Kalman filter for soil analysis in SURFEXv5

An externalised surface scheme like SURFEX allows computationally cheap offline runs. This is a major advantage for surface assimilation techniques such as the extended Kalman filter (EKF), where the offline runs allow a cheaper numerical estimation of the observation operator Jacobian. In the recent past an EKF has been developed within SURFEX for the initialisation of soil water content and soil temperature based on screen-level temperature and relative humidity observations. In this paper we make a comparison of the Jacobian calculated with offline SURFEX runs and with runs coupled to the atmospheric ALARO model. Comparisons are made with respect to spatial structure and average value of the Jacobian, gain values and increments. We determine the optimal perturbation size of the Jacobian for the offline and coupled approaches and compare the linearity of the Jacobian for these cases. Results show that the offline Jacobian approach gives similar results to the coupled approach and that it allows for smaller perturbation sizes that better approximate this linearity assumption. We document a new case of non-linearities that can hamper this linearity assumption and cause spurious 2 delta t oscillations in small parts of the domain for the coupled as well as offline runs. While these oscillations do not have a detrimental effect on the model run, they can introduce some noise in the Jacobian at the affected locations. The oscillations influence both the surface fluxes and the screen-level variables. The oscillations occur in the late afternoon in summer when a stable boundary layer starts to form near the surface. We propose a filter to remove the oscillations and show that this filter works accordingly

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 Externalisee (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

Land surface albedo from MSG/SEVIRI: retrieval method, validation, and application for weather forecast

The European Meteorological Satellite Organization (EUMETSAT) maintains a number of decentralized processing centers dedicated to different scientific themes. The Portuguese Meteorological Institute hosts the Satellite Application Facility on Land Surface Analysis (LSA-SAF). The primary objective of the LSA-SAF is to provide added-value products for the meteorological and environmental science communities with main applications in the fields of climate modeling, environmental management, natural hazards management, and climate change detection. Since 2005 data from Meteosat Second Generation satellite are routinely processed in near real time by the LSA-SAF operational system in Lisbon. Presently, the delivered operational products comprise land surface albedo and temperature, shortwave and long-wave downwelling radiation fluxes, vegetation parameters and snow cover. After more than ten years (1999-2010) of research, development, and progressive operational activities, a summary of the surface albedo product characteristics and performances is presented. The relevance of LSA-SAF albedo product is analyzed through a weather forecast model (ALADIN) in order to account for the inter-annual spatial and temporal variability. Results clearly show a positive impact on the 12-hour forecast of 2m temperatures

The Necrotic Signal Induced by Mycophenolic Acid Overcomes Apoptosis-Resistance in Tumor Cells

The amount of inosine monophosphate dehydrogenase (IMPDH), a pivotal enzyme for the biosynthesis of the guanosine tri-phosphate (GTP), is frequently increased in tumor cells. The anti-viral agent ribavirin and the immunosuppressant mycophenolic acid (MPA) are potent inhibitors of IMPDH. We recently showed that IMPDH inhibition led to a necrotic signal requiring the activation of Cdc42.Herein, we strengthened the essential role played by this small GTPase in the necrotic signal by silencing Cdc42 and by the ectopic expression of a constitutive active mutant of Cdc42. Since resistance to apoptosis is an essential step for the tumorigenesis process, we next examined the effect of the MPA–mediated necrotic signal on different tumor cells demonstrating various mechanisms of resistance to apoptosis (Bcl2-, HSP70-, Lyn-, BCR-ABL–overexpressing cells). All tested cells remained sensitive to MPA–mediated necrotic signal. Furthermore, inhibition of IMPDH activity in Chronic Lymphocytic Leukemia cells was significantly more efficient at eliminating malignant cells than apoptotic inducers.These findings indicate that necrosis and apoptosis are split signals that share few if any common hub of signaling. In addition, the necrotic signaling pathway induced by depletion of the cellular amount of GTP/GDP would be of great interest to eliminate apoptotic-resistant tumor cells

Satellite and in situ observations for advancing global Earth surface modelling: a review

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort

Analyse variationnelle des paramètres de surface

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Modélisation de cisaillements de vent et assimilation de données dans la couche limite atmosphérique

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Definition of the Moist-Air Exergy Norm: A Comparison with Existing “Moist Energy Norms”

International audienceThis 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 which 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 middle troposphere, respectively

Bayesian Selection of Atmospheric Profiles from an Ensemble Data Assimilation System using Infrasonic Observations of May 2016 Mount Etna Eruptions

International audienceAbstract Observed infrasound arrivals are considered as a way to provide additional knowledge of the middle atmosphere for numerical weather prediction (NWP) models. To do so, a Bayesian approach, based on the discrepancies between predicted and observed infrasound arrival characteristics, is adopted for selecting the most likely atmospheric states, in terms of temperature and wind velocity profiles, among an ensemble of NWP model analyses. The predicted characteristics, in terms of trace velocity and the back azimuth angle, are computed using a three‐dimensional ray‐tracing model and atmospheric profiles extracted once a day from ensemble of analyses produced by the Météo‐France global NWP model. The performance of the method is demonstrated using a set of thousands of volcanic eruptions that correspond to an upsurge in volcanic activity of Mount Etna (Sicily) during May 2016. It is shown that the Bayesian approach allows the identification of the most likely members and hence provides additional knowledge on the atmosphere truly probed by the infrasound. When the atmospheric temperature and wind profiles are reasonably meeting the effective sound speed assumption requirements, the members retrieved are similar in terms of effective sound speed but not in terms of wind and temperature. For improving both temperature and wind velocity profile selection, additional infrasound arrival characteristics are then required (e.g., travel time, amplitude, etc.). The confidence on the retrieved profiles is also sensitive to the time of validity of the meteorological analyses and on the definition of the surface conditions involved in the estimation of the predicted trace velocities