THE EFFECT OF THE SURFACE CHARACTERISTICS ON THE DICE RESULTS SEEN BY THE MESONH MODEL M. A. Jiménez, P. Le Moigne and J. Cuxart DICE workshop, 14-16 October.

Slides:



Advertisements
Similar presentations
Robin Hogan, Andrew Barrett
Advertisements

DYMECS: Dynamical and Microphysical Evolution of Convective Storms (NERC Standard Grant) University of Reading: Robin Hogan, Bob Plant, Thorwald Stein,
Joint GABLS-GLASS/LoCo workshop, September 2004, De Bilt, Netherlands Interactions of the land-surface with the atmospheric boundary layer: Single.
1D Dice Experiment at Meteo-France and LES preliminary result E. Bazile, I. Beau, F. Couvreux and P. Le Moigne (CNRM/GAME) DICE Workshop Exeter October.
Using Flux Observations to Improve Land-Atmosphere Modelling: A One-Dimensional Field Study Robert Pipunic, Jeffrey Walker & Andrew Western The University.
FOREST FIRE IMPACT ON AIR QUALITY THE LANCON-DE-PROVENCE 2005 CASE S. Strada, C. Mari Laboratoire d'Aérologie, Université de Toulouse, CNRS, Toulouse,
PBL simulated from different PBL Schemes in WRF during DICE
THE EFFECT OF THE SURFACE CHARACTERISTICS ON THE DICE RESULTS SEEN BY THE MESONH MODEL M. A. Jiménez, P. Le Moigne and J. Cuxart DICE workshop, October.
Semi-direct effect of biomass burning on cloud and rainfall over Amazon Yan Zhang, Hongbin Yu, Rong Fu & Robert E. Dickinson School of Earth & Atmospheric.
Development of Alternative Methods For Estimating Dry Deposition Velocity In CMAQ.
Some Approaches and Issues related to ISCCP-based Land Fluxes Eric F Wood Princeton University.
Earth System Data Record (ESDR) for Global Evapotranspiration. Eric Wood Princeton University ©Princeton University.
Toulouse, 23 Avril 2007 Atmophere-Lake Interactions at a reservoir in the South of Portugal Rui Salgado Centro de Geofísica de Évora / Universidade de.
Globally distributed evapotranspiration using remote sensing and CEOP data Eric Wood, Matthew McCabe and Hongbo Su Princeton University.
AMMA-UK Kick-off meeting Jan 2005 WP1 Land surface and atmosphere interactions Chris Taylor Phil Harris.
Hector simulation We found simulation largely depending on: Model initialization scheme Lateral boundary conditions Physical processes represented in the.
Are the results of PILPS or GSWP affected by the lack of land surface- atmosphere feedback? Is the use of offline land surface models in LDAS making optimal.
Basic definitions: Evapotranspiration: all processes by which water in liquid phase at or near the earth’s surface becomes atmospheric water vapor  “Evaporation”
ERS 482/682 Small Watershed Hydrology
Claire Sarrat, Joël Noilhan, Pierre Lacarrère, Sylvie Donier et al. Atmospheric CO 2 modeling at the regional scale: A bottom – up approach applied to.
Evapotranspiration - Rate and amount of ET is the core information needed to design irrigation projects, managing water quality, predicting flow yields,
Chris Birchfield Atmospheric Sciences, Spanish minor.
The representation of stratocumulus with eddy diffusivity closure models Stephan de Roode KNMI.
1. Objectives Impacts of Land Use Changes on California’s Climate Hideki Kanamaru Masao Kanamitsu Experimental Climate Prediction.
Verification and Case Studies for Urban Effects in HIRLAM Numerical Weather Forecasting A. Baklanov, A. Mahura, C. Petersen, N.W. Nielsen, B. Amstrup Danish.
Jonathan Pleim 1, Robert Gilliam 1, and Aijun Xiu 2 1 Atmospheric Sciences Modeling Division, NOAA, Research Triangle Park, NC (In partnership with the.
Coupling of the Common Land Model (CLM) to RegCM in a Simulation over East Asia Allison Steiner, Bill Chameides, Bob Dickinson Georgia Institute of Technology.
Météo-France / CNRM – T. Bergot 1) Introduction 2) The methodology of the inter-comparison 3) Phase 1 : cases study Inter-comparison of numerical models.
DYMECS: Dynamical and Microphysical Evolution of Convective Storms (NERC Standard Grant) University of Reading: Robin Hogan, Bob Plant, Thorwald Stein,
1/26 APPLICATION OF THE URBAN VERSION OF MM5 FOR HOUSTON University Corporation for Atmospheric Research Sylvain Dupont Collaborators: Steve Burian, Jason.
TURBULENT FLUX VARIABILITIES OVER THE ARA WATERSHED Moussa Doukouré, Sandrine Anquetin, Jean-Martial Cohard Laboratoire d’étude des Transferts en Hydrologie.
Seasonal Modeling (NOAA) Jian-Wen Bao Sara Michelson Jim Wilczak Curtis Fleming Emily Piencziak.
Erik Crosman 1, John Horel 1, Chris Foster 1, Erik Neemann 1 1 University of Utah Department of Atmospheric Sciences Toward Improved NWP Simulations of.
Large-Eddy Simulations of the Nocturnal Low-Level Jet M.A. Jiménez Universitat de les Illes Balears 4th Meso-NH user’s meeting, Toulouse April 2007.
Development of a one-dimensional version of the Hirlam-model in Sweden Background: This model has been run operationally for about nine years now. Mainly.
Investigating Land-Atmosphere CO 2 Exchange with a Coupled Biosphere-Atmosphere Model: SiB3-RAMS K.D. Corbin, A.S. Denning, I. Baker, N. Parazoo, A. Schuh,
A Numerical Study of Early Summer Regional Climate and Weather. Zhang, D.-L., W.-Z. Zheng, and Y.-K. Xue, 2003: A Numerical Study of Early Summer Regional.
Toulouse IHOP meeting 15 June 2004 Water vapour variability within the growing convective boundary layer of 14 June 2002 with large eddy simulations and.
Treatment of Small Scale Land Surface Heterogeneity for Atmospheric Modelling (SSSAM) Günther Heinemann (1) and Michael Kerschgens (2) 1 Meteorologisches.
ATM 301 Lecture #11 (sections ) E from water surface and bare soil.
T. Bergot - Météo-France CNRM/GMME 1) Methodology 2) Results for Paris-CdG airport Improved site-specific numerical model of fog and low clouds -dedicated.
Preliminary LES simulations with Méso-NH to investigate water vapor variability during IHOP_2002 F. Couvreux F. Guichard, V.
Evapotranspiration Estimates over Canada based on Observed, GR2 and NARR forcings Korolevich, V., Fernandes, R., Wang, S., Simic, A., Gong, F. Natural.
Results Time Study Site Measured data Alfalfa Numerical Analysis of Water and Heat Transport in Vegetated Soils Using HYDRUS-1D Masaru Sakai 1), Jirka.
Evaluating a tiled land-surface model with multi-site energy flux observations A. Nordbo 1, A. Manrique-Sunen 2, G. Balsamo 2,
MM5 studies at Wageningen University (NL) Title Jordi Vilà (Group 4) NL North sea Radar MM5 NL North sea.
Initial Results from the Diurnal Land/Atmosphere Coupling Experiment (DICE) Weizhong Zheng, Michael Ek, Ruiyu Sun, Jongil Han, Jiarui Dong and Helin Wei.
SiSPAT-Isotope model Better estimates of E and T Jessie Cable Postdoc - IARC.
Basin-scale nocturnal regimes in complex terrain Maria A. Jiménez and Joan Cuxart Universitat de les Illes Balears Palma de Mallorca, Spain 6th MesoNH.
Météo-France / CNRM – T. Bergot 1) Methodology 2) The assimilation procedures at local scale 3) Results for the winter season Improved Site-Specific.
1 Xiaoyan Jiang, Guo-Yue Niu and Zong-Liang Yang The Jackson School of Geosciences The University of Texas at Austin 03/20/2007 Feedback between the atmosphere,
Hydrologic Losses - Evaporation Learning Objectives Be able to calculate Evaporation from a lake or reservoir using the following methods – Energy Balance.
Hydrologic Losses - Evaporation
Soil analysis scheme for AROME within SURFEX
The Cabauw Experimental Site for Atmospheric Research (CESAR): New developments Fred C. Bosveld (KNMI) Content CESAR and its research themes Long term.
Case study of an urban heat island in London, UK: Comparison between observations and a high resolution numerical weather prediction model Siân Lane, Janet.
Coupled atmosphere-ocean simulation on hurricane forecast
Potential Evapotranspiration (PET)
RMetS Atmospheric Science Conference 2018 Lewis Blunn
Weather forecasting in a coupled world
Mark A. Bourassa and Qi Shi
Cathy Hohenegger 1,2 Linda Schlemmer 1,2 Bjorn Stevens 1
Radiation fogs: WRF and LES numerical experiments
Hydrologic Losses - Evaporation
Mire parameterization
MODELING AT NEIGHBORHOOD SCALE Sylvain Dupont and Jason Ching
RegCM3 Lisa C. Sloan, Mark A. Snyder, Travis O’Brien, and Kathleen Hutchison Climate Change and Impacts Laboratory Dept. of Earth and Planetary Sciences.
Colombe Siegenthaler - Le Drian
Kurowski, M .J., K. Suselj, W. W. Grabowski, and J. Teixeira, 2018
Biomass and Soil Moisture simulation and assimilation over Hungary
Presentation transcript:

THE EFFECT OF THE SURFACE CHARACTERISTICS ON THE DICE RESULTS SEEN BY THE MESONH MODEL M. A. Jiménez, P. Le Moigne and J. Cuxart DICE workshop, October 2013, Exeter (UK)

SCM: MesoNH model ( Lafore et al., 1998 ) Turbulence ( Cuxart et al., 2000 ), length scale ( Bougeault and Lacarrere 1989 ) Radiation (ECMWF code called every time-step) Kessler microphysical scheme (vapor, cloud water and rain) Time step (300s for SCM and 20s for coupled runs) Vertical grid ( Cuxart et al., 2007 ): 85 levels (3m resolution at lower levels, gradual stretching) LSM: SURFEX ( Masson et al., 2013 ) ISBA 3 layers Land use: Ecoclimap at 1km resolution (Masson et al., 2003) 50% great plains crops and 50% rockies grassland total vegetation fraction over the pixel = 0.73 root depth = 1.5m and total depth = 2m leaf area index = 1.46 CLAY=0.24, SAND=0.38 from Harmonized World Soil Database (HWSD) at 1km resolution

RN H LE G SURFACE ENERGY BUDGET (W/m2) CPL more humid (e and LWD large) INTTURBINTRAD Steeneveld et al 2006

M10m (m/s) T2m (K) T (10m) – T (2m) TIME SERIES Q2m (kg/kg)

SCM – STAGE 1BSCM + SURFACE – STAGE 2

SCM – STAGE 1BSCM + SURFACE – STAGE 2

VEGETATIONROOT DEPTH default 50% bare 50% vegetated sfc=1cm, root=1.5m, total=2m BARE 100% bare 0 % vegetated sfc=1cm, root=1.5m, total=2m ROOT50% bare 50% vegetated sfc=1cm, root=0.4m, total=0.6m SENSITIVITY TESTS

LATENT HEAT FLUX (W/m2) TESTING THE SURFACE SCHEME SENSIBLE HEAT FLUX (W/m2) RN (W/m2)

TESTING THE SCM model RN LE H

TESTING THE SCM model 10m wind speed (m/s) 2m specific humidity (kg/kg) 2m temperature (K)

SCM CPL CPL (BARE GROUND) CPL (ROOT DEPTH) SENSITIVITY TESTS WIND SPEED (m/s) WIND SPEED (m/s) TKE (m2/s2)

SCM CPL CPL (BARE GROUND) CPL (ROOT DEPTH) SENSITIVITY TESTS POT. TEMPERATURE (K) (Km/s)

SCM CPL CPL (BARE GROUND) CPL (ROOT DEPTH) SENSITIVITY TESTS SPEC. HUMIDITY (kg/kg) (kg m/s)

SENSITIVITY TESTS vertical resolution default: 85 levels (3m at lower levels) test: 60 levels (10m at lower levels)

SENSITIVITY TESTS vertical resolution 60 levels 85 levels (DICE) wind speed (m/s) potential temperature (K)

SUMMARY 1) SCM vs CPL * CPL is giving larger LE and smaller H than SCM * T colder in CPL than in SCM although there are no significant differences on the wind speed * CPL has more specific humidity than SCM 2) reducing the percentage of vegetation * LE and H become closer to observations * As a test case bare ground soil is taken but this is far from the reality... 3) reducing the root depths to a more realistic values * Improve H and LE is closer to observations than CPL or other tests * the humidity is reduced and the T2m is warmer than CPL, departing from obs * the wind speed is not largely affected 4) vertical grid mesh * importance to properly reproduce the surface layer characteristics

QUESTIONS 1) Are there other surface parameters that might be interesting to check if they have realistic values? 2) Differences between models (CPL run) * surface characteristics * SCM parameterizations * which one is playing the most relevant role? 3) running all the models with the same surface parameters? Stage 1b: evaluating SCM Stage 4(?): evaluating LSM 4)...

ACKNOWLEDGEMENTS RESEARCH PROJECT CGL C04-01 JAE-DOC contract