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Coordination: Modeling activities


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Météo-France products

Various operational NWP model output will be available to help the decision during the field campaign as well as the interpretation of measures. At Météo-France, the new operational assimilation system at mesoscale  (3D Var Aladin with a 10 km resolution, run every 6 hours) will be in operation during the field campaign. The radiososonde soundings taken during the Intense Observing Periods (IOPs) at synoptic hours will enter the 3D Var system in real time. The objective is here to improve the mesoscale weather analysis which could be used as initial and lateral conditions for high-resolution mesoscale modelling (e.g. with Meso-NH model).

Forecast products from ECMWF, Arpege and Aladin will be of course available at the headquarter of the campaign, as well as plots of back- and direct Aladin-forecasted trajectories (up to 2-day forecast), routinely computed for CaroboEurope every 6 hours at the sites of Biscarrosse, Marmande and Toulouse (i.e. at the entrance, middle and exit parts of the domain) at 500 and 2000m  altitude, to help the decision to start an IOP and  choice the aircraft flight plans. Among the Arpege/Aladin output, a large-scale map will be available once a day from the actual up to three days in advance, to illustrate the synoptic winds, surface fronts, and rainfall (see an example below).

figure IV.2-a : Values of surface atmospheric pressure, ground track of atmopsheric fronts, synoptic wind and rainfall at 12 UTC

At regional scale, the horizontal wind fields will be available at 500 and 1500m altitude, at 09, 12 and 15h UTC the day after, together with the forecasted “radiosonde” profiles above the “La Cape Sud” (CS) site, as illustrated below.

figure IV.1.2-b : Example of horizontal wind fields at 500 (bottom) and 1500m (top), and “adiosonde” profiles, forecasted by Aladin for the day after

Max-Plank Institute (Jena) products

MPG-BGC will provide forecasts of the airmass history for a number of receptors in the experiment region. For this it is planned during the IOP to implement an operational system. This system will enable to plan airborne sampling in a way that can optimally constrain the exchange between biosphere and atmosphere. Such a system has been successfully used for the COBRA experiments [Lin et al., 2004], see also <http://www.deas.harvard.edu/cobra/Fltplan/>. A recent update was made for the COBRA-Maine experiment in summer 2004, and this version has been transferred to workstations at the MPI-BGC. It will run on a newly purchased Workstation (4 processors, 8 GB RAM).

The forecasting system involves the Stochastic Time-Inverted Lagrangian Transport model (STILT), that is driven by forecasted meteorological fields, and that represents airmasses as individual Lagrangian particles. These particles are released at a given receptor location, and are moved backward in time by mean and turbulent winds [Lin et al., 2003], [Gerbig et al., 2003]. The density of these particles at a given time and location then describe the influence of that location to mixing ratios at the receptor location. That way measurements at different times can be located such that they observe the same airmass, i.e. they are made in a Lagrangian (airmass following) way. The system also suggests flight paths to characterize airmasses at a given time, and picks out nearby airports for missed approaches (missed approaches are “fake” landings at small airports, that allow to profile down to very low altitudes unreachable over other areas).

Modifications to this system will include adaptation of meteorological forecast fields not used before. The only met fields currently used that covering the intensive operational area, are generated by the gobal NCEP (US National Centers for Environmental Prediction) AVN model (now called GFS model). It is planned to add forecasted fields from the ECMWF model at 50 km resolution, and a file converter/pre-processor is currently being written. It is further planned to use high-resolution output from Aladin, a mesoscale operational forecasting system by Météo-France. Further modifications of the forecasting system involve extension of the airport database to Europe, so that the detailed planning of flights can be done in a nearly automated way.

It is planned to have the forecasting system operational and web-accessible to project partners well before start of the IOP, to ensure a high quality during the campaign, but also to allow for a period of getting used to using the information.

 

Gerbig, C., J.C. Lin, S.C. Wofsy, B.C. Daube, A.E. Andrews, B.B. Stephens, P.S. Bakwin, and C.A. Grainger, Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented framework, Journal of Geophysical Research-Atmospheres, 108 (D24), 4757, doi:10.1029/2003JD003770, 2003.

Lin, J.C., C. Gerbig, S.C. Wofsy, A.E. Andrews, B.C. Daube, K.J. Davis, and C.A. Grainger, A near-field tool for simulating the upstream influence of atmospheric observations: The Stochastic Time-Inverted Lagrangian Transport (STILT) model, Journal of Geophysical Research-Atmospheres, 108 (D16), 4493, doi:10.1029/2002JD003161, 2003.

Lin, J.C., C. Gerbig, S.C. Wofsy, A.E. Andrews, B.C. Daube, C.A. Grainger, B.B. Stephens, P.S. Bakwin, and D.Y. Hollinger, Measuring fluxes of trace gases at regional scales by Lagrangian observations: Application to the CO2 Budget and Rectification Airborne (COBRA) study, Journal of Geophysical Research-Atmospheres, 109, D15304, doi:10.1029/2004JD004754, 2004.

An example of the graphical product generated by the flight planning tool. The receptor is Howland, Maine, which is the center of the downwind (0-hr) cross-section from where particles are simulated backward in time in STILT.  The release time is on May 28th, 1300UT, and in this example the STILT particles are driven with meteorological fields from the AVN model updated on May 25th, 0600UT. The different components of the figure are tagged with numbers that are linked to explanations on the side


figure IV.1.2-c: AVN model

 

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