Représentation des processus de transport et de lessivage pour la modélisation de la composition chimique de l'atmosphère à l'échelle planétaire

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Use of variable ozone in a radiative transfer model for the global Météo‐France 4D‐Var system.

International audienceNowadays, the assimilation of satellite observations, particularly radiances from infrared sounders, into numerical weather prediction (NWP) models plays a dominant role in improving weather forecasts. One of the keys to make optimal use of radiances is to simulate them with a radiative transfer model (RTM). At Météo-France, the RTTOV RTM is used for NWP models. Currently, simulations are carried out taking into account single chemical profiles. However, neglecting the spatial and temporal variability of these gases can affect the accuracy of the simulations and thus the quality of the subsequent analyses and forecasts

Interpol-IAGOS: a new method for assessing long-term chemistry–climate simulations in the UTLS based on IAGOS data, and its application to the MOCAGE CCMI REF-C1SD simulation

International audienceAbstract. A wide variety of observation data sets are used to assess long-term simulations provided by chemistry–climate models (CCMs) and chemistry-transport models (CTMs). However, the upper troposphere–lower stratosphere (UTLS) has hardly been assessed in these modelling exercises yet. Observations performed in the framework of IAGOS (In-service Aircraft for a Global Observing System) combine the advantages of in situ airborne measurements in the UTLS with an almost-global-scale sampling, a ∼20-year monitoring period and a high frequency. Even though a few model assessments have been made using the IAGOS database, none of them took advantage of the dense and high-resolution cruise data in their whole ensemble yet. The present study proposes a method to compare this large IAGOS data set to long-term simulations used for chemistry–climate studies. As a first application, the REF-C1SD reference simulation generated by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) CTM in the framework of Chemistry-Climate Model Initiative (CCMI) phase I has been evaluated during the 1994–2013 period for ozone (O3) and the 2002–2013 period for carbon monoxide (CO). The concept of the new comparison software proposed here (so-called Interpol-IAGOS) is to project all IAGOS data onto the 3-D grid of the model with a monthly resolution, since generally the 3-D outputs provided by chemistry–climate models for multi-model comparisons on multi-decadal timescales are archived as monthly means. This provides a new IAGOS data set (IAGOS-DM) mapped onto the model's grid and time resolution. To get a model data set consistent with IAGOS-DM for the comparison, a subset of the model's outputs is created (MOCAGE-M) by applying a mask that retains only the model data at the available IAGOS-DM grid points. Climatologies are derived from the IAGOS-DM product, and good correlations are reported between with the MOCAGE-M spatial distributions. As an attempt to analyse MOCAGE-M behaviour in the upper troposphere (UT) and the lower stratosphere (LS) separately, UT and LS data in IAGOS-DM were sorted according to potential vorticity. From this, we derived O3 and CO seasonal cycles in eight regions well sampled by IAGOS flights in the northern midlatitudes. They are remarkably well reproduced by the model for lower-stratospheric O3 and also good for upper-tropospheric CO. Along this model evaluation, we also assess the differences caused by the use of a weighting function in the method when projecting the IAGOS data onto the model grid compared to the scores derived in a simplified way. We conclude that the data projection onto the model's grid allows us to filter out biases arising from either spatial or temporal resolution, and the use of a weighting function yields different results, here by enhancing the assessment scores. Beyond the MOCAGE REF-C1SD evaluation presented in this paper, the method could be used by CCMI models for individual assessments in the UTLS and for model intercomparisons with respect to the IAGOS data set

The impact of biomass burning on upper tropospheric carbon monoxide: a study using MOCAGE global model and IAGOS airborne data

International audienceIn this paper, the fate of biomass burning emissions of carbon monoxide is studied with the global chemistry-transport model MOCAGE (MOdélisation de Chimie Atmosphérique à Grande Échelle) and IAGOS (In-Service Aircraft for a Global Observing System) airborne measurements for the year 2013. The objectives are firstly to improve their representation within the model and secondly to analyse their contribution to carbon monoxide concentrations in the upper troposphere. At first, a new implementation of biomass burning injection is developed for MOCAGE, using the latest products available in Global Fire Assimilation System (GFAS) biomass burning inventory on plume altitude and injection height. This method is validated against IAGOS observations of CO made in fire plumes, identified thanks to the SOFT-IO source attribution data. The use of these GFAS products leads to improved MOCAGE skill to simulate fire plumes originating from boreal forest wildfires. It is also shown that this new biomass burning injection method modifies the distribution of carbon monoxide in the free and upper troposphere, mostly at northern boreal latitudes. Then, MOCAGE performance is evaluated in general in the upper troposphere and lower stratosphere in comparison to the IA-GOS observations and is shown to be very good, with very low bias and good correlations between the model and the observations. Finally, we analyse the contribution of biomass burning to upper tropospheric carbon monoxide concentrations. This is done by comparing simulations where biomass are toggled on and off in different source regions of the world to assess their individual influence. The two regions contributing the most to upper tropospheric CO are found to be the boreal forests and equatorial Africa, in accordance with the quantities of CO they emit each year and the fact that they undergo fast vertical transport: deep convection in the tropics and pyroconvection at high latitudes. It is also found that biomass burning contributes more than 11 % on average to the CO concentrations in the upper troposphere and up to 50 % at high latitudes during the wildfire season

Update of Infrared Atmospheric Sounding Interferometer (IASI) channel selection with correlated observation errors for numerical weather prediction (NWP)

International audienceThe Infrared Atmospheric Sounding Interferome-ter (IASI) is an essential instrument for numerical weather prediction (NWP). It measures radiances at the top of the atmosphere using 8461 channels. The huge amount of observations provided by IASI has led the community to develop techniques to reduce observations while conserving as much information as possible. Thus, a selection of the 300 most informative channels was made for NWP based on the concept of information theory. One of the main limitations of this method was to neglect the covariances between the observation errors of the different channels. However, many centres have shown a significant benefit for weather forecasting to use them. Currently, the observation-error covariances are only estimated on the current IASI channel selection, but no studies to make a new selection of IASI channels taking into account the observation-error covariances have yet been carried out. The objective of this paper was therefore to perform a new selection of IASI channels by taking into account the observation-error covariances. The results show that with an equivalent number of channels, accounting for the observation-error covariances, a new selection of IASI channels can reduce the analysis error on average in temperature by 3 %, humidity by 1.8 % and ozone by 0.9 % compared to the current selection. Finally, we go one step further by proposing a robust new selection of 400 IASI channels to further reduce the analysis error for NWP

Operational Response to Volcanic Ash Risks Using HOTVOLC Satellite-Based System and MOCAGE-Accident Model at the Toulouse VAAC

In 2010, the Eyjafjallajökull volcano erupted, generating an ash cloud causing unprecedented disruption of European airspace. Despite an exceptional situation, both the London and Toulouse Volcanic Ash Advisory Centres (VAAC) provided critical information on the location of the cloud and on the concentration of ash, thus contributing to the crisis management. Since then, substantial efforts have been carried out by the scientific community in order to improve remote sensing techniques and numerical modeling. Satellite instruments have proven to be particularly relevant for the characterization of ash cloud properties and a great help in the operational management of volcanic risk. In this study, we present the satellite-based system HOTVOLC developed at the Observatoire de Physique du Globe de Clermont-Ferrand (OPGC) using Meteosat geostationary satellite and designed for real-time monitoring of active volcanoes. After a brief presentation of the system we provide details on newly developed satellite products dedicated to the ash cloud characterization. This includes, in particular, ash cloud altitude and vertical column densities (VCD). Then, from the Stromboli 2018 paroxysm, we show how HOTVOLC can be used in a timely manner to assist the Toulouse VAAC in the operational management of the eruptive crisis. In the second part of the study, we provide parametric tests of the MOCAGE-Accident model run by the Toulouse VAAC from the April 17 Eyjafjallajökull eruption. For this purpose, we tested a range of eruption source parameters including the Total Grain Size Distribution (TGSD), the eruptive column profile, the top plume height and mass eruption rate (MER), as well as the fine ash partitioning. Finally, we make a comparison on this case study between HOTVOLC and MOCAGE-Accident VCD

High-Resolution air quality forecasts with MOCAGE chemistry transport model

MOCAGE is the 3D global off-line chemistry transport model (CTM) run at Météo-France since 2005 for air quality operational forecasts. Three nested domains are used, with decreasing resolutions (globe, Europe, and France), and 47 vertical levels (from the surface to 5 hPa). For the global and the European domain, input meteorological forcing fields are Météo-France ARPEGE forecasts. For France, and for the first day of forecast, MOCAGE uses the operational outputs of Météo-France non-hydrostatic AROME model. This high-resolution (2.5 km) meteorological model is supposed to better represent urban processes (e.g., the urban heat island), which are of strong interest for air quality applications. The purpose of this study is to test the increase of resolution of the CTM MOCAGE over France from 0.1° to 0.025° (i.e. the native resolution of the input meteorological fields)

ASIS v1.0: an adaptive solver for the simulation of atmospheric chemistry

International audienceThis article reports on the development and tests of the adaptive semi-implicit scheme (ASIS) solver for the simulation of atmospheric chemistry. To solve the ordinary differential equation systems associated with the time evolution of the species concentrations, ASIS adopts a one-step linearized implicit scheme with specific treatments of the Ja-cobian of the chemical fluxes. It conserves mass and has a time-stepping module to control the accuracy of the numerical solution. In idealized box-model simulations, ASIS gives results similar to the higher-order implicit schemes derived from the Rosenbrock's and Gear's methods and requires less computation and run time at the moderate precision required for atmospheric applications. When implemented in the MOCAGE chemical transport model and the Laboratoire de Météorologie Dynamique Mars general circulation model, the ASIS solver performs well and reveals weaknesses and limitations of the original semi-implicit solvers used by these two models. ASIS can be easily adapted to various chemical schemes and further developments are foreseen to increase its computational efficiency, and to include the computation of the concentrations of the species in aqueous-phase in addition to gas-phase chemistry