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Downscaling of atmospheric forcing for ROMS for the period 1958-2008 : Application to the Peru-Chile system

Downscaling of atmospheric forcing for ROMS for the period 1958-2008 : Application to the Peru-Chile system. Gildas Cambon IRD, LEGOS, France . ROMS_AGRIF development team:. Cambon, G . (a) , Marchesiello, P. (a) ; Debreu L. (b) ; Penven P. (c)

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Downscaling of atmospheric forcing for ROMS for the period 1958-2008 : Application to the Peru-Chile system

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  1. Downscaling of atmospheric forcing for ROMS for the period 1958-2008 :Application to the Peru-Chile system Gildas Cambon IRD, LEGOS, France

  2. ROMS_AGRIF development team: Cambon, G. (a), Marchesiello, P. (a) ; Debreu L. (b) ; Penven P. (c) (a): IRD/LEGOS, France ; (b): INRIA/LJK, France ; (c) : IRD/LPO, France Application Humbolt : PEPS project (ANR) Gildas Cambon(a) , Boris Dewitte (a,c,d), Katerina Goubanova (a,d), Vincent Echevin (a), Christophe Hourdin (b), Ali Belmadani (b), Timothée Brochier (b), Colas Francois (e) (a): IRD/LEGOS, France ; (b): IRD/LOCEAN, France ; (c): IGP, Peru ; (d) : IMARPE, Peru ; (e) : IGPP, UCLA, USA

  3. ROMS_AGRIF is a branch of ROMS developed in France by IRD and INRIA and based at LEGOS, Toulouse. Its main particularity is the AGRIF online nesting capability (Debreu et al, 2005, 2010) : http://roms.mpl.ird.fr This French branch of ROMS is developed to respond to the objectives of IRD in terms of support to developing countries. In this community experiment, the model code is developed in parallel with a powerful pre- and post- processing set of tools: the ROMSTOOLS matlab toolbox(Penven et al, 2008). ROMS_AGRIF general context

  4. ROMS_AGRIF general context A world-wide community of users : Today, the ROMS_AGRIF community well spread developed around the world, with more than 1100 registered users. A more restricted community of about 40 beta testers exist also and is referenced on our SVN development website at INRIA: http://gforge.inria.fr/projects/romsagrif. Here we present an application of ROMS_AGRIF for the Peru-Chile current system conducted in collaboration with Peruvian partners.

  5. Outlines • Introduction & Issues • The statistical atmospheric model • The interannual ROMS simulation • Impact of the stat. downscaling • Perspectives • Summary & Conclusions

  6. Introduction & Issues Scientific context& main objectives Humboldt Current system (HSC) is the most productive eastern boundary current system with permanent upwelling. Its fisheries represent about 20% of world wide marine fish catch. There is a need for evaluating the impact of regional climate variability on the Peru-Chile upwelling system In this context: • Use of global model simulations of the recent past (1958-present) • ROMS is use for oceanic downscaling • Downscaling methods for atmospheric forcing are needed.

  7. Introduction & Issues Strategy • Interannual regional configuration of ROMS_AGRIF at 1/6° from 1958 to 2008 period. • For the moment, hind casts over a test period 1992-2005 to evaluate the realism of the solution and 98 El Nino event. • Set up of atmospheric downscaling methods Atmopheric downscaling strategy : AOGCM model needed for these long periods : NCEP, ERA …but large errors are found in coastal areas. • Dynamical downscaling using WRF : experienced in our group in New Caledonia (Lefevre et al., 2010, Jourdain et al., 2001) and over the Central Chile region (Renault et al 2009, see poster) • Statistical downscaling approach, (Goubanova et al , 2010, Clim. Dyn., revised) In this study, statistical approach have been choose in reason of his low computational cost but others are also evaluating (not presented)

  8. Outlines • Introduction & Issues • The statistical atmospheric model • The interannual ROMS simulation • Impact of the stat. downscaling • Perspectives • Summary & Conclusions

  9. Statistical downscaling of NCEP reanalysis Description 10m wind speed from QuikSCAT 10m wind speed from NCEP 1. Find a statistical relationship F between large-scale predictors X and regional variables Y for the observed period F – Multiple linear regression Y – 10 m wind/stress from QSCAT, 0.5x0.5° X – 10 m wind + SLP from NCEP, 2.5°x2.5° 2. In order to derive regional variables Y for a period of interest apply the relationship F to corresponding large-scale predictors X QuikSCAT is a good product to reproduce upwelling processes (Capet et al, 2004) but we only have it for recent years (2000 – 2008) Goubanova et al 2010

  10. Statistical downscaling of NCEP reanalysis Improvements on spatial structure In coastal area with NCEP_DS : • Wind curl is more realistic, which leads to better estimates of along shore currents. (PCC closer to the coast) • Wind stronger near the coast : upwelling intensity intensified and more realistic

  11. Statistical downscaling of NCEP reanalysis Improvements on interannual variability Differences in wind amplitude between the warm phase and the cold phase of the 1997/1998 El Niño-La Niña. satellite data products outputs Data were 6-month low-pass filtered and the warm (cold) phase corresponds to September 1997 (December 1998). Stat downscaling induces a better representation of wind interannual variability near the coast.

  12. Statistical downscaling of NCEP reanalysis Improvements on interannual variability The statistical downscaling was applied to both the NCEP (top) and ERA40 (bottom) ERA40 and NCEP reanalysis have a very different pattern near the coast. The downscaling allows correcting the interannual biases between reanalyses products. . For these reasons, use of these downscaled NCEP wind stress in an interannual Peru-Chile regional ROMS simulation

  13. Outlines • Introduction & Issues • The statistical atmospheric model • The interannual ROMS simulation • Impact of the stat. downscaling • Perspectives • Summary & Conclusions

  14. The interannual ROMS experiment : Set-up Numerical Set-Up • Ocean model : ROMS_AGRIFhttp://roms.mpl.ird.fr • Resolution : 1/6° • Test Period : 1992 - 2005 • Bathymetry : Etopo 2 • Atmospheric forcing: • NCEP heat fluxes (2.5° x 2.5°) • NCEP_Downscalled wind stress (0.5°x0.5°) • Bulk formulation (Fairall et al.) for latent and sensible heat fluxes • Lateral forcing : SODA model (Carton & Giese), 0.5°x0.5°, 5-days T, S, u, v, U2d, V2d,  imposed at the open boundaries • OBC : active open boundaries conditions (Marchesiello et al, 2001)

  15. The interannual ROMS experiment : Validations NECC SEC PCC POC PCC Oceanic circulation scheme for the eastern Tropical Pacific (figure from Montes et al., 2010, JGR) Annual mean SST from Pathfinder satellite observation Annual mean SST and Surface currents ROMS Surface currents in agreement with the obs. and literature : PCC, SEC and POC Mean SST well reproduced

  16. The interannual ROMS experiment : Validations Currents vertical structures across Eq. and across 12.S 86° W Zonal velocity in m/s 12°S Meridional velocity in m/s Coastal jet SEC PCC NECC PCUC EUC pSSCC sSSCC U V Along coast poleward current PCUC: main source for coastal upwelling (Peru–North Chile) Quite well reproduced, consistent with previous studies description. Surface equatorial currents SEC and NECC ok Equatorwards subsurface currents EUC, p-SSCC, s-SSCC: good amplitude and position. This simulation compared well to the obs. It reproduce well the mean state circulation and thermohaline structure

  17. Outlines • Introduction & Issues • The statistical atmospheric model • The interannual ROMS simulation • Impact of the atmospheric downscaling • Perspectives • Conclusions

  18. The interannual ROMS experiment : Stat. downscaling impact On EKE from SSH and SSH variability ROMS – NCEP TOPEX/ERS ROMS NCEP_DS Irrealistic offshore shift of EKE max NCEP_DS NCEP Annual mean EKE from SSH in cm2/s2 ROMS with NCEP_DS wind stress compared very well to the observations • Mesoscale variability well represented in NCEP_DS run. • Mean current baroclinic instability much better represented in NCEP_DS run • Significative improves compared to the run using original NCEP wind stress

  19. The interannual ROMS experiment: Stat. downscaling impact SST Pathfinder On the upwelling intensity With NCEP_DS stress : Near coast wind are more realistic and stronger  upwelling better represented. The statistical downscaling methodology employed to downscale the NCEP wind stresses in the region clearly improves the ROMS simulation near the coast : upwelling and eddy activity !

  20. Outlines • Introduction & Issues • The statistical atmospheric model • The interannual ROMS simulation • Impact of the stat. downscaling • Perspectives • Summary & Conclusions

  21. Perspectives With our statistical downscaling approach, we improve the realism of the simulation: investigation of the vertical along shore currents structure and its reverse during El Nino events (as complementary works of Colas et al, 2008) During El Nino event : • Collapse of the upwelling • Strong modifications of the subsurface poleward PCUC, intensified, uplifted to the surface and moved offshore extensions • Intensifications of currents and quasi-reverse of currents ay coast

  22. Perspectives • Dynamical atmospheric downscaling using WRF : • Experienced successfully in our group with ROMS_AGRIF and WRF in Nouméa by Marchesiello’s group (Lefevre et al, Jourdain et al). • Applied for shorter periods by Renault et al over the Central Chile region :to reproduce the specific wind burst event called ‘Coastal Jet’ and his associated oceanic response. (98-2000) Renault et al., 2010, in preparation and see poster Atmospheric model: WRF two nested grids : 30km and 10km Oceanic model: ROMS :spatial resolution : 10km Recover in a dynamically consistent way the energy spectra of atmospheric circulation at the mesoscale range (absent in the NCEP data) Figure from Marchesiello et al

  23. Perspectives • Ocean downscaling using online AGRIF 2 -way procedure capability of ROMS_AGRIF (Debreu et al 2010, submitted)to improve the ocean downscaling performance : there is an update on 2D and 3D time stepping for the parent grid. Example of 4 grid nested simulation with the 2-way AGRIF procedure (coarser grid not shown): Menkes C. & Marchesiello P., Debreu L., 2010 Left : vertical velocity, right : vorticity

  24. Conclusions (1) • Interannual ROMS_AGRIF simulation of the Peru-Chile region using the SODA OGCM interannual boundary conditionsand outputs andadapted NCEP atmospheric forcing. • Statistical downscaling based on the QuikSCAT (2000 -2008) periods applied on the NCEP wind-stress (soon the heat fluxes) to improve near shore winds over long periods. • Important improvements for the interannual simulation near the coast, on the PCC equatorwards current drive by the wind stress curl. • Large improve on the upwelling structure and intensity due to stronger and more realistic wind intensity . • Flexible method and an efficient alternative to the costly dynamical downscaling that improves the results.

  25. Observational programs related Filamentos and VOCALS-Rex coastal cruises (2008) + PAITA + CHICAMA + CHIMBOTE + HUACHO + CALLAO + PISCO + SAN JUAN + ATICO + ILO Tracks Filamentos and VOCALS Peru cruises Long-term cross-shelf sections Coastal stations (SST, SSS, Winds) Filamentos, VOCALS-Rex.

  26. Thank you Picture: Paracas, South of Pisco, Peru

  27. Conclusions (2) Perspectives : • WRF atmospheric modeling for long periods. • 2-way AGRIF nesting to have a high quality ocean embedding. • Investigate of the alongshore vertical structure of PCUC and especially its reverses during El Nino events with this simulation.

  28. The interannual ROMS experiment: Validations Eq. Some validations to WOA Annual Mean 92-2004 12° S 20°S ROMS WOA • Maximum biases of 2°C in surface: • Roms colder near the equator :  equatorial. upwelling • Warmer southern in upper layer • Colder near the coast  coastal upwelling. Eq. 12.S This simulation compared quite well to the obs. It reproduce well the mean state circulation and thermohaline structure 20.S

  29. The interannual ROMS experiment : Stat. downscaling impact On EKE from SSHand SSH variability ROMS AVISO ROMS ROMS with NCEP_DS wind stress compared well observation: • Mean state pattern well represented. • As well, significative impact of the statistical downscaling of NCEP stresses, especially near the equator NCEP_DS NCEP SSH variability in cm AVISO ROMS ROMS Annual mean EKE from SSH in cm2/s2 ROMS with NCEP_DS wind stress compared well observation: • Mesoscale variability well represented in NCEP_DS run. • Significative improves compared to the run the original NCEP wind stress NCEP_DS NCEP NCEP

  30. Scientific perspectives Scientific perspectives: • Evaluation of the pathways from the EUC towards the Peru-Chile undercurrent (PCUC) at interannual time scale: as complementary works of Montes et al., JGR, 2010 • Impact of equatorial Kelvin waves on the PCUC during the 1997 El Niño as complementary works of Colas et al, 2008, PIO. Dec 97 Mature El Nino, EK m=1,2 Equatorial Kelvin wave along the equator in SODA (baroclinic modes 1 and 2) (in cm) June 97 Starting El Nino, EK m=1 Out El Nino Mars 97

  31. The interannual ROMS experiment : El Nino signature On the SST @12S P2 El Nino 97-98 • The upwelled water ~[15-18°C] near shore( upwelling of PCUC waters mainly) • Offshore ~[21-25°C] • During El Nino, shift of + 5°C near shore and 2-3°C offshore P1 Relax • Different phases in El Nino (Colas et al, 2008) : P1, Relax, P2 • Can be linked to the different modes of Kelvin waves arrivals

  32. Scientific perspectives • Evaluation of the pathways from the EUC towards the Peru-Chile undercurrent (PCUC) at interannual time scale: as complementary works of Montes et al., JGR, 2010 • ~60% of EUC alimented by subsurface equatorial flows (EUC, p-SSCC & s-SSCC): Lagrangian studies did for climatological runs. Interest to take in account the interannual variability of large scale currents, in particular the ENSO modulation. • Contribution of the different vertical mode of equatorial Kelvin waves on the PCUC during the 1997 El Niño as complementary works of Colas et al, 2008, PIO.

  33. Outlines • Introduction & Issues • The statistical atmospheric model • Description • Improvements • The interannual ROMS simulation • Numerical set up • Validations • Impact of the stat. downscaling • El Nino signature • Scientific perspectives • Modeling perspectives • Conclusions

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