RCM sensitivity to domain size in summer and winter With the collaboration of: Jean-Philippe Morin (simulations) and Mathieu Moretti (diagnostics) By Martin.

Slides:



Advertisements
Similar presentations
The effect of indiscriminate nudging time in regional climate modeling of the Mediterranean basin Tamara Salameh, Philippe Drobinski, Thomas Dubos and.
Advertisements

Where and when should one hope to find added value from dynamical downscaling of GCM data? René Laprise Director, Centre ESCER (Étude et Simulation du.
Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.
The Role of High-value Observations for Forecast Simulations in a Multi- scale Climate Modeling Framework Gabriel J. Kooperman, Michael S. Pritchard, and.
Earth Science & Climate Change
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss The Latent Heat Nudging Scheme of COSMO EWGLAM/SRNWP Meeting,
Explicit Treatment of Model Error Simultaneous State and Parameter Estimation with an Ensemble Kalman Filter Altuğ Aksoy*, Fuqing Zhang, and John W. Nielsen-Gammon.
The transition from mesoscale to submesoscale in the California Current System X. Capet, J. McWilliams, J. Molemaker, A. Shchepetkin (IGPP/UCLA), feb.
© Crown copyright Met Office Atmospheric Blocking and Mean Biases in Climate Models Adam Scaife, Tim Hinton, Tim Woollings, Jeff Knight, Srah Keeley, Gill.
WFM 6311: Climate Risk Management © Dr. Akm Saiful Islam WFM 6311: Climate Change Risk Management Akm Saiful Islam Lecture-4: Module- 3 Regional Climate.
Assessment of Future Change in Temperature and Precipitation over Pakistan (Simulated by PRECIS RCM for A2 Scenario) Siraj Ul Islam, Nadia Rehman.
Simulations of Floods and Droughts in the Western U.S. Under Climate Change L. Ruby Leung Pacific Northwest National Laboratory US CLIVAR/NCAR ASP Researcher.
LAMEPS Development and Plan of ALADIN-LACE Yong Wang et al. Speaker: Harald Seidl ZAMG, Austria Thanks: Météo France, LACE, NCEP.
IPRC Lunch Time Seminar, 12. March 2002 Hans von Storch Inst. Coastal Research GKSS Research Center Geesthacht Germany Issues in regional atmospheric modelling:
Added Value Generated by Regional Climate Models H. von Storch, F. Feser Institute of Coastal Research, Helmholtz Zentrum Geesthacht, Germany 29 May 1.
Regional Climate Modeling in the Source Region of Yellow River with complex topography using the RegCM3: Model validation Pinhong Hui, Jianping Tang School.
The case of polar lows Hans von Storch 13 and Matthias Zahn 2 1. Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Germany. 2. Environmental.
SLEPS First Results from SLEPS A. Walser, M. Arpagaus, C. Appenzeller, J. Quiby MeteoSwiss.
© Crown copyright Met Office Climate Projections for West Africa Andrew Hartley, Met Office: PARCC national workshop on climate information and species.
Strategies for assessing natural variability Hans von Storch Institute for Coastal Research, GKSS Research Center Geesthacht, Germany Lund, ,
Workshop: Aspects of regional modelling – at GKSS Contributions by Hans von Storch, Frauke Feser, Insa Meinke and Burkhardt Rockel Ouranos, Montreal
Köppen, Hadley and Dethloff Zwei Seiten einer Medaille: Vom Globalen und vom Regionalen.
Russ Bullock 11 th Annual CMAS Conference October 17, 2012 Development of Methodology to Downscale Global Climate Fields to 12km Resolution.
Development of a downscaling prediction system Liqiang Sun International Research Institute for Climate and Society (IRI)
Dynamical Downscaling Developing a Model Framework for WRF for Future GCM Downscaling Jared H. Bowden Tanya L. Otte June 25, th Annual Meteorological.
Dynamical Downscaling: Assessment of model system dependent retained and added variability for two different regional climate models Christopher L. Castro.
Keynote 3.2 Strategies and measures for determining the skill of dynamical downscaling Hans von Storch; HZG Lund, 17. June 2014.
Regional Climate Models Add Value to Global Model Data H. von Storch, F. Feser, B. Rockel, R. Weisse Institute of Coastal Research, Helmholtz Zentrum Geesthacht,
1 Climate Ensemble Simulations and Projections for Vietnam using PRECIS Model Presented by Hiep Van Nguyen Main contributors: Mai Van Khiem, Tran Thuc,
Climate Downscaling Using Regional Climate Models Liqiang Sun.
Preliminary Results of Global Climate Simulations With a High- Resolution Atmospheric Model P. B. Duffy, B. Govindasamy, J. Milovich, K. Taylor, S. Thompson,
Comparison of convective boundary layer velocity spectra calculated from large eddy simulation and WRF model data Jeremy A. Gibbs and Evgeni Fedorovich.
“Spatial ensemble characterisation for summer convective cases” S. Dey Supervisors: R. Plant, N. Roberts and S. Migliorini Mesoscale group 03/06/2014.
Tropical Domain Results Downscaling Ability of the NCEP Regional Spectral Model v.97: The Big Brother Experiment Conclusions: Motivation: The Big Brother.
MJO simulations under a dry environment Marcela Ulate M Advisor: Chidong Zhang (… in a Nudging World)
Dynamical downscaling of future climates Steve Hostetler, USGS Jay Alder, OSU/USGS Andrea Schuetz, USGS/OSU Environmental Computing Center, COAS/OSU.
Part I: Representation of the Effects of Sub- grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects.
Simulating Rainfall Extremes in South America: Sensitivity to remote and local forcing Anji Seth and Maisa Rojas International Research Institute for Climate.
Toward a mesoscale flux inversion in the 2005 CarboEurope Regional Experiment T.Lauvaux, C. Sarrat, F. Chevallier, P. Ciais, M. Uliasz, A. S. Denning,
Assimilation of HF radar in the Ligurian Sea Spatial and Temporal scale considerations L. Vandenbulcke, A. Barth, J.-M. Beckers GHER/AGO, Université de.
Downscaling tropical cyclones from global re-analysis and scenarios: Statistics of multi-decadal variability of TC activity in E Asia Hans von Storch,
“Very high resolution global ocean and Arctic ocean-ice models being developed for climate study” by Albert Semtner Extremely high resolution is required.
1) What is the variability in eddy currents and the resulting impact on global climate and weather? Resolving meso-scale and sub- meso-scale ocean dynamics.
Toulouse IHOP meeting 15 June 2004 Water vapour variability within the growing convective boundary layer of 14 June 2002 with large eddy simulations and.
Southern California February 9, 2002 MISR mesoscale climate dynamics in Southern California Sebastien Conil Alex Hall IRI, April 4, 2006.
High-Resolution Simulations with CMAQ for Improved Linkages with Exposure Models Martin Otte CSC Christopher Nolte US EPA Robert Walko Univ. Miami.
Page 1. Page 2 German presentations COLIJN Franciscus, GKSS: COSYNA VON STORCH Jin-Song, MPIM: Wind generated power input into the deep ocean VON STORCH.
© Crown copyright Met Office Downscaling ability of the HadRM3P model over North America Wilfran Moufouma-Okia and Richard Jones.
DRAFT – Page 1 – January 14, 2016 Development of a Convective Scale Ensemble Kalman Filter at Environment Canada Luc Fillion 1, Kao-Shen Chung 1, Monique.
1 First results and methodological approach to parameter perturbations in GEM-LAM simulations PART II Leo Separovic, Ramon de Elia and Rene Laprise.
Evaluation of regional climate simulations with WRF model in conditions of central Europe Jan Karlický, Tomáš Halenka, Michal Belda, (Charles University.
Arctic climate simulations by coupled models - an overview - Annette Rinke and Klaus Dethloff Alfred Wegener Institute for Polar and Marine Research, Research.
1 First results and methodological approach to parameter perturbations in GEM-LAM simulations PART I Leo Separovic, Ramon de Elia and Rene Laprise.
OSEs with HIRLAM and HARMONIE for EUCOS Nils Gustafsson, SMHI Sigurdur Thorsteinsson, IMO John de Vries, KNMI Roger Randriamampianina, met.no.
NOAA Northeast Regional Climate Center Dr. Lee Tryhorn NOAA Climate Literacy Workshop April 2010 NOAA Northeast Regional Climate.
The Assessment of Typhoon Hazards at Regional-Scales in the Pacific Regions with Downscaling Numerical Experiments Tetsuya Takemi Fourth Capacity Building.
Exploring and Validating LM Performances at Very High Resolution M. Didone, D. Lüthi, H.C Davies Institute for Atmospheric and Climate Science, ETH Zürich.
© Crown copyright Met Office Mismatching Perturbations at the Lateral Boundaries in Limited-Area Ensemble Forecasting Jean-François Caron … or why limited-area.
COASTDAT: Regional downscaling re-analysis - concept and utility VON STORCH Hans Institute of Coastal Research, Helmholtz Zentrum Geesthacht, Germany 22.
Does nudging squelch the extremes in regional climate modeling?
Emerging Research Opportunities at the Climate Modeling Laboratory NC State University (Presentation at NIA Meeting: 9/04/03) Fredrick H. M. Semazzi North.
9th Annual Meteorological Users’ Meeting
Overview of Downscaling
Dynamical downscaling of ERA-40 with WRF in complex terrain in Norway – comparison with ENSEMBLES U. Heikkilä, A. D. Sandvik and A.
On HRM3 (a.k.a. HadRM3P, a.k.a. PRECIS) North American simulations
Leo Separovic, Ramón de Elía, René Laprise and Adelina Alexandru
Application of the ensemble technique to CRCM simulations
RegCM3 Lisa C. Sloan, Mark A. Snyder, Travis O’Brien, and Kathleen Hutchison Climate Change and Impacts Laboratory Dept. of Earth and Planetary Sciences.
Influence of large-scale nudging on RCM’s internal variability
Presentation transcript:

RCM sensitivity to domain size in summer and winter With the collaboration of: Jean-Philippe Morin (simulations) and Mathieu Moretti (diagnostics) By Martin Leduc and René Laprise

The Big-Brother experiment « Perfect-model » approach:  driving and nested model are the same.  differences between LB and BB fields are directly attributable to the nesting procedure. Big-BrotherFiltered Big-BrotherLittle-Brother Measuring the RCM sensitivity to various parameters: Spatial resolution and the update frequency of the LBC: Denis et al. (2003), Antic et al. (2004) and Dimitrijevic and Laprise (2005) Errors in the nesting data: Diaconescu et al. (2007) Size of the domain: Leduc and Laprise (2008)

The domain-size issue (1) - LARGE domain - Model is free to develop its own large-scale dynamics, differing from the nesting data. Does spectral nudging is appropriate to solve this ? "If you don't believe in the value of global climate models then there's no point in downscaling them” -Filippo Giorgi Maybe not ! May be good: Small-scale physical processes can affect the large-scale dynamics.  constrain the RCM to follow the “good” large scales  let the RCM free to correct the “wrong” large scales In other words:

LBC exert a strong control on the solution (as for SN). Small-scale features have not enough time/space to develop. The domain-size issue (2) - SMALL domain - Leduc and Laprise (2008) : Effects related to the domain size have been studied for a winter case where the atmospheric flow is :  strong and westerly Need to repeat the experiment with a summer flow.

Experimental framework Simulations: Big-Brother  BB: 196x196 Little-Brothers  LB1: 144x144  LB2: 120x120  LB3: 96x96  LB4: 72x72 Validation area: QC: 38x38 2 Periods:  July 90 to 93  February 90 to 93 Sponge zone: 10 grid points

Summer and winter flows over Québec SUMMERWINTER ANIMATE !

700-hPa wind magnitude (temporal deviation) Small scales Large scales SUMMERWINTER

Small-scale transient eddies of the 700-hPa wind magnitude BB LB1LB2 LB3LB4 (m/s) R* LB1: 79% LB2: 68% LB3: 65% LB4: 78% SUMMER BB LB1LB2 LB3LB4 R* LB1: 56% LB2: 50% LB3: 71% LB4: 44% WINTER (m/s)

Small-scale transient eddies of the 700-hPa relative humidity (%) R* LB1: 61% LB2: 49% LB3: 49% LB4: 50% WINTERSUMMER R* LB1: 90% LB2: 87% LB3: 89% LB4: 90% (%) BB LB1LB2 LB3LB4 BB LB1LB2 LB3LB4

Small-scale transient variance ratio: LB / BB (wind magnitude) WINTERSUMMER (%)

Small-scale transient variance ratio: LB / BB (relative humidity) (%) SUMMERWINTER Did summer really heal our RCM ? 1- Flow characteristics (a high residency time) 2- Intense convective processes 3- Vertical turbulent fluxes

General conclusions - Smaller domain can be used in summer - (for comparable skills) Lateral boundary conditions control :  increases when the domain size is reduced, and is stronger in winter  applied on large scales, it affects similarly the small ones Magnitude of the small-scale features:  spin-up area in winter  homogeneous spin-up in summer

Antic, S., R. Laprise, B. Denis and R. de Elía, 2004: Testing the downscaling ability of a one-way nested regional climate model in regions of complex topography. Climate Dynamics, 23, Denis, B., R. Laprise and D. Caya, 2003: Sensitivity of a regional climate model to the resolution of the lateral boundary conditions. Climate Dynamics, 20, Diaconescu, E. P., R. Laprise and L. Sushama, 2007: The impact of lateral boundary data errors on the simulated climate of a nested regional climate model. Climate Dynamics, 28, Dimitrijevic, M. and R. Laprise, 2005: Validation of the nesting technique in a RCM and sensitivity tests to the resolution of the lateral boundary conditions during summer. Climate Dynamics, 25, Leduc, M. and R. Laprise, 2008: Regional Climate Model sensitivity to domain size. Accepted in Climate Dynamics. References

Taylor diagrams (ls)

Taylor diagrams (ss)

Spectral filters “T30” : 2160 to 1080 km LPF : 2160 to 540 km

Small-scale transient variance ratio: LB / BB (relative vorticity)

700-hPa rvort SUMMERWINTER

Summer and winter flows over Québec SUMMERWINTER