INSTYTUT METEOROLOGII I GOSPODARKI WODNEJ INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT TITLE : IMPLEMENTATION OF MOSAIC APPROACH IN COSMO AT IMWM AUTHORS:

Slides:



Advertisements
Similar presentations
COSMO Workpackage No First Results on Verification of LMK Test Runs Basing on SYNOP Data Lenz, Claus-Jürgen; Damrath, Ulrich
Advertisements

Meteorologisches Institut der Universität München
Fog Forecasting at Roissy Airport (Paris) with 1D model Thierry Bergot and Joël Noilhan Météo-France 1) Methodology Cobel : 1D model of boundary layer.
Indirect Determination of Surface Heat Fluxes in the Northern Adriatic Sea via the Heat Budget R. P. Signell, A. Russo, J. W. Book, S. Carniel, J. Chiggiato,
Hector simulation We found simulation largely depending on: Model initialization scheme Lateral boundary conditions Physical processes represented in the.
Results of an Adaptive Radiative Transfer Parameterisation for the Lokal-Modell LM-User-Seminar 5 th – 7 th March 2007, Langen Annika Schomburg 1), Victor.
Spectral microphysics in weather forecast models with special emphasis on cloud droplet nucleation Verena Grützun, Oswald Knoth, Martin Simmel, Ralf Wolke.
Peak Performance Technical Environment FMI NWP Activities.
Institute of Meteorology and Water Management – NRI Extensive tests of lower-boundary-variation-based COSMO EPS COTEKINO Priority Project -
COSMO General Meeting Zurich, 2005 Institute of Meteorology and Water Management Warsaw, Poland- 1 - Verification of the LM at IMGW Katarzyna Starosta,
The National Environmental Agency of Georgia L. Megrelidze, N. Kutaladze, Kh. Kokosadze NWP Local Area Models’ Failure in Simulation of Eastern Invasion.
Earth Science Division National Aeronautics and Space Administration 18 January 2007 Paper 5A.4: Slide 1 American Meteorological Society 21 st Conference.
Introducing the Lokal-Modell LME at the German Weather Service Jan-Peter Schulz Deutscher Wetterdienst 27 th EWGLAM and 12 th SRNWP Meeting 2005.
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.
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Conditional verification of all COSMO countries: first.
Tropical Domain Results Downscaling Ability of the NCEP Regional Spectral Model v.97: The Big Brother Experiment Conclusions: Motivation: The Big Brother.
Météo-France / CNRM – T. Bergot 1) Introduction 2) The methodology of the inter-comparison 3) Phase 1 : cases study Inter-comparison of numerical models.
Budgets of second order moments for cloudy boundary layers 1 Systematische Untersuchung höherer statistischer Momente und ihrer Bilanzen 1 LES der atmosphärischen.
Accounting for Uncertainties in NWPs using the Ensemble Approach for Inputs to ATD Models Dave Stauffer The Pennsylvania State University Office of the.
Sensitivity Analysis of Mesoscale Forecasts from Large Ensembles of Randomly and Non-Randomly Perturbed Model Runs William Martin November 10, 2005.
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
Sensitivity experiments with the Runge Kutta time integration scheme Lucio TORRISI CNMCA – Pratica di Mare (Rome)
HNMS contribution to CONSENS Petroula Louka & Flora Gofa Hellenic National Meteorological Service
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.
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.
10 th COSMO General Meeting, Krakow, September 2008 Recent work on pressure bias problem Lucio TORRISI Italian Met. Service CNMCA – Pratica di Mare.
An evaluation of satellite derived air-sea fluxes through use in ocean general circulation model Vijay K Agarwal, Rashmi Sharma, Neeraj Agarwal Meteorology.
1 Rachel Capon 04/2004 © Crown copyright Met Office Unified Model NIMROD Nowcasting Rachel Capon Met Office JCMM.
Assimilating satellite cloud information with an Ensemble Kalman Filter at the convective scale Annika Schomburg, Christoph Schraff, Hendrik Reich, Roland.
Application of an adaptive radiative transfer parameterisation in a mesoscale numerical weather prediction model DWD Extramural research Annika Schomburg.
Bogdan Rosa 1, Marcin Kurowski 1 and Michał Ziemiański 1 1. Institute of Meteorology and Water Management (IMGW), Warsaw Podleśna, 61
Deutscher Wetterdienst COSMO-ICON Physics Current Status and Plans Ulrich Schättler Source Code Administrator COSMO-Model.
The correction of initial values of temperature at low model levels Blinov D. Revokatova A. Rivin G. Rozinkina I. Sapuncova E.
10 th COSMO General Meeting, Krakow, September 2008 Recent work on pressure bias problem Lucio TORRISI Italian Met. Service CNMCA – Pratica di Mare.
One-year re-forecast ensembles with CCSM3.0 using initial states for 1 January and 1 July in Model: CCSM3 is a coupled climate model with state-of-the-art.
INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT Hydrological applications of COSMO model Andrzej Mazur Institute of Meteorology and Water Management Centre.
General Meeting Moscow, 6-10 September 2010 High-Resolution verification for Temperature ( in northern Italy) Maria Stefania Tesini COSMO General Meeting.
COSMO General Meeting Zurich, 2005 Institute of Meteorology and Water Management Warsaw, Poland- 1 - Simple Kalman filter – a “smoking gun” of shortages.
Joint SRNWP/COST-717 WG-3 session, Lisbon Stefan Klink Data Assimilation Section Early results with rainfall assimilation.
Snow modelling using Surfex with the Crocus snow scheme for Norway Dagrun Vikhamar-Schuler 1 and Karsten Müller 2 1 MET.NO, 2 NVE.
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Component testing of the COSMO model’s turbulent diffusion.
Vincent N. Sakwa RSMC, Nairobi
Simulations of MAP IOPs with Lokal Modell: impact of nudging on forecast precipitation Francesco Boccanera, Andrea Montani ARPA – Servizio Idro-Meteorologico.
INSTYTUT METEOROLOGII I GOSPODARKI WODNEJ INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT TITLE : Experiments with TILES and MOSAIC at IMWM AUTHORS: Grzegorz.
A physical initialization algorithm for non-hydrostatic NWP models using radar derived rain rates Günther Haase Meteorological Institute, University of.
Evaluation of cloudy convective boundary layer forecast by ARPEGE and IFS Comparisons with observations from Cabauw, Chilbolton, and Palaiseau  Comparisons.
Météo-France / CNRM – T. Bergot 1) Methodology 2) The assimilation procedures at local scale 3) Results for the winter season Improved Site-Specific.
Parameterization of the Planetary Boundary Layer -NWP guidance Thor Erik Nordeng and Morten Køltzow NOMEK 2010 Oslo 19. – 23. April 2010.
Representation of low clouds/stratus in Aladin/AUT: Ongoing work and Outlook.
COSMO model simulations for COPS IOP 8b, 15 July 2007 Jörg Trentmann, Björn Brötz, Heini Wernli Institute for Atmospheric Physics, Johannes Gutenberg-University.
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Experiments at MeteoSwiss : TERRA / aerosols Flake Jean-Marie.
Eidgenössisches Departement des Innern EDI Bundesamt für Meteorologie und Klimatologie MeteoSchweiz Ensemble activites and plans at MeteoSwiss André Walser.
Mesoscale Assimilation of Rain-Affected Observations Clark Amerault National Research Council Postdoctoral Associate - Naval Research Laboratory, Monterey,
Limitations of ’column physics’ for radiation computations in atmospheric models Bent H Sass Danish Meteorological Institute 1 May 2009 As the horizontal.
INSTYTUT METEOROLOGII I GOSPODARKI WODNEJ INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT TITLE: IMGW in COSMO AUTHOR: Michał Ziemiański DATA:
Matt Vaughan Class Project ATM 621
Introducing the Lokal-Modell LME at the German Weather Service
Operational COSMO of MeteoSwiss
MM5- and WRF-Simulated Cloud and Moisture Fields
Bogdan Rosa, Damian K. Wójcik, Michał Z. Ziemiański
aLMo from GME and IFS boundary conditions: A comparison
A. Topographic radiation correction in COSMO: gridscale or subgridscale? B. COSMO-2: convection resolving or convection inhibiting model? Matteo Buzzi.
Results of semi realistic and realistic simulations performed
INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT
Mire parameterization
INSTYTUT METEOROLOGII I GOSPODARKI WODNEJ
INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT
Preliminary validation results of the prognostic 3d-TKE-scheme
transport equations for the scalar variances
Presentation transcript:

INSTYTUT METEOROLOGII I GOSPODARKI WODNEJ INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT TITLE : IMPLEMENTATION OF MOSAIC APPROACH IN COSMO AT IMWM AUTHORS: Grzegorz Duniec, Andrzej Mazur DATE:

2 1.Validation of SUBS – done for ver. 4.8 of COSMO MODEL 2.Estimation of the influence of SUBS on model results for different parameterization of physics and numerics Studies IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

3 Numerical schemes Leapfrog: 3–timelevel HE-VI (Horizontally Explicit – Vertically Implicit) Integration Leapfrog: 3–timelevel semi–implicit Runge – Kutta: 2–timelevel HE–VI Integration with irunge_kutta=1 (3-order standard scheme) Runge – Kutta: 2–timelevel HE–VI Integration with irunge_kutta=2 (variant scheme with Total Variation Diminishing ) Convection schemes Kain – Fritsch (1992) Tiedtke (1989) Modified Tiedtke scheme for shallow convection Tests setup IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

4 Domain (113x101 grid points, 40 levels, resolution 7km, forecast time horizon 3 hours) Tests setup (cntd.) IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

5 Orig – original COSMO ver. 4.8 Ctrl – control (subs-modified code of COSMO ver 4.8 with no account for subs: nsubs=0) Twins – subs modified COSMO ver. 4.8 with nsubs=4, low resolution input data only (nsubs=4, identical subpixels) Subs – modified COSMO ver. 4.8, nsubs=4, high–resolution data included Explanation of abbreviations IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

6 T2m – air temperature at 2m above groud level TD – dew point temperature TSO – soil temperature at 0 cm down (surface temp.) U10m – zonal wind component, 10m above ground level V10m – meridional wind component, 10m above ground level Water+ice content of soil layers 1cm down Resulting fields (selected) IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

Dates chosen for tests IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Six different synoptic situations chosen for tests (domain marked with black frame in next six slides)  2009.II.01 (00UTC) low temperature, ground was frozen solid  2009.IV.22 (12 UTC) sunny/fair day  2009.X.16 (00 UTC, 06 UTC) ground covered with snow  2009.XI.04 (12 UTC) windy day with intensive precipitation  2009.XI.21 (06 UTC) dense fog and data for previous case with correct formula for derivation of mean qvs to mimic flux averaging  2006.VIII.01 (12 UTC)

8 low temperature, ground was frozen solid Synoptic situation – 01 II 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

9 sunny/fair day Synoptic situation – 22 IV 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

10 ground covered with snow Synoptic situation – 16 X 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

11 windy day with intensive precipitation Synoptic sytuation – 04 XI 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

12 dense fog Synoptic sytuation – 21 XI 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM

Methodology IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Comparison (for all combinations of convection and numerical schemes) orig vs ctrl orig vs subs orig vs twins twins vs ctrl subs vs ctrl twins vs subs Statistics (for all combinations of convection and numerical schemes) correlation standard deviation covariance variance

The ”best” configurations and results IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM The „best” configuration (concerning correlation coefficient) was obtained for all combinations – results for water in soil (WSO) for 01 II, 22 IV, 16 X, 21 XI (with and without shallow convection). correlation coefficient – WSO leapdef l eapdef1leapsemi l eapsemi1Runge K utta1Runge K utta2 orig-twins orig-subs orig-ctrl ctrl-twins ctrl-subs subs-twins111111

The ”best” configurations and results IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM One of the „best” configuration (concerning correlation coefficient) was obtained for zonal wind component (U10) for 22 IV 2009 (without shallow convection). correlation coefficient – U10 (without shallow convection) leapdef l eapdef1leapsemi l eapsemi1Runge K utta1Runge K utta2 orig-twins orig-subs0,9990,9980,9920,9910,999 orig-ctrl ctrl-twins ctrl-subs0,999 0,9920,9910,999 subs-twins0,999 0,9920,9910,999

The ”best” configurations and results IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM The „best” configuration (concerning correlation coefficient) was obtained for dew point temperature (TD) for 01 II 2009 (with shallow convection). correlation coefficient – TD (with shallow convection) leapdefleapsemiRunge K utta1Runge K utta2 orig-twins1111 orig-subs0,9990,9980,999 orig-ctrl1111 ctrl-twins1111 ctrl-subs0,9990,9980,999 subs-twins0,9990,9980,999

The ”worst” configurations and results IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM One of the „worst” configuration (concerning correlation coefficient) was obtained for orig vs. twins, ctrl vs. twins, subs vs. twins for air temperature for 04 XI 2009: correlation coefficient – T 2M (without shallow convection) leapdefleapsemiRunge K utta1Runge K utta2 orig-twins0,0260,0490,026 orig-subs0,9990,9920,9991 orig-ctrl1111 ctrl-twins0,0260,0490,026 ctrl-subs0,9990,99311 subs-twins0,0260,0570,0270,028

The ”worst” configurations and results IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM One of the „worst” configuration (concerning correlation coefficient) was obtained for orig vs. twins, ctrl vs. twins, subs vs. twins for air temperature for 04 XI 2009: correlation coefficient – T 2M (with shallow convection) leapdefleapsemiRunge K utta1Runge K utta2 orig-twins0,0200,0370,024 orig-subs10,99711 orig-ctrl1111 ctrl-twins0,0200,0370,024 ctrl-subs10,99711 subs-twins0,0200,0440,026

The ”worst” configurations and results IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM The „worst” configuration (concerning correlation coefficient) was obtained for leapsemi – orig, ctrl and subs vs. twins – results for soil temperature for 16 X 2009: correlation coefficient – TSO (without shallow convection) leapdef l eapdef1leapsemi l eapsemi1Runge K utta1Runge K utta2 orig-twins110,85111 orig-subs0,998 0,997 0,998 orig-ctrl ctrl-twins110,85111 ctrl-subs0,998 0,9970,9960,998 subs-twins0,9970,9980,850,9960,998

Two bugs in cosmo-subs detected (Corrected by Annika Schomburg) IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM 1. The major bug is in the computation of the effective qv_s (specific humidity at the surface): wrong formula correct formula 2. The second error is not important for the model run itself, only for some of the output variables. In the module near_surface.f90 there is a loop over ns=1:nsubs1, which, by mistake, includes some of the output variables like rain_con, which are summed up too many times due to this loop. To correct this bug one can just exchange the single large loop by smaller loops only for those variables where necessary.

Results with wrong formula for 1 VIII 2006 (example) IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM correlation coefficient – zonal wind component leapdefleapsemi l eapsemi1Runge-Kutta1Runge-Kutta1.1Runge K utta2RungeKutta2.1 orig-twins0,89 0,920,980,910,880,91 orig-subs0,880,850,880,410,920,420,92 subs-twins0,990,970,980,210,990,210,99

Results with correct formula for 1 VIII 2006 (example) IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM correlation coefficient – zonal wind component leapdefleapsemi l eapsemi1RungeKutta1RungeKutta1.1Runge K utta2RungeKutta2.1 orig-twins orig-subs0,9940,9790,9800,9950,9960,9950,996 subs-twins0,9940,9790,9800,9950,9960,9950,996

The ”worst” configurations and results – 16 X 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Soil temperature at 0 cm down (surface temp.) CORRELATION: 0,85 DIFFERENCE BETWEEN ORIG AND TWINS (K)

The ”worst” configurations and results – 16 X 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Soil temperature at 0 cm down (surface temp.) CORRELATION: 0,85 DIFFERENCE BETWEEN SUBS AND TWINS (K)

The ”worst” configurations and results – 16 X 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Soil temperature at 0 cm down (surface temp.) CORRELATION: 0,85 DIFFERENCE BETWEEN CTRL AND TWINS (K)

The ”best” configurations and results – 22 IV 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Zonal component wind (U10) without shallow convection CORRELATION: 0,991 DIFFERENCE BETWEEN SUBS AND TWINS (K)

The ”best” configurations and results – 01 II 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Dew point temperature (TD) (with shallow convection) CORRELATION: 0,998 DIFFERENCE BETWEEN SUBS AND TWINS (K)

The ”worst” configurations and results – 04 XI 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Air temperature at 2 m (T2M) (without shallow convection) CORRELATION: 0,026 DIFFERENCE BETWEEN SUBS AND TWINS (K)

The ”worst” configurations and results – 04 XI 2009 IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Air temperature at 2 m (T2M) (with shallow convection) CORRELATION: 0,020 DIFFERENCE BETWEEN CTRL AND TWINS (K)

Results for 1 VIII 2006 with wrong formula IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Zonal wind component (U10) CORRELATION: 0,21 DIFFERENCE BETWEEN SUBS AND TWINS (K)

Results for 1 VIII 2006 with correct formula IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Zonal wind component (U10) CORRELATION: 0,995 DIFFERENCE BETWEEN SUBS AND TWINS (K)

Summary IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM Extended tests of MOSAIC4COSMO implentation was performed. Miscellaneous combinations of various numerical schemes and physical parameterizations were tested for six different synoptic situations Except for November 4th, 2009, correlation between results for selected meteorological fields is quite good (from 0.85 to ~1) Numerical errors (esp. in data preparation) seem to be a reason for poor correlation for November 4th, 2009

Plans IMPLEMENTATION OF TILE APPROACH IN COSMO AT IMWM 1.We want to test two new data sets with very interesting meteorological situation(s): -15 VIII 2008 –very strong thunderstorm, -May 2010 – very intensive precipitation. 2. We intend to check an influence of subs and twins on: -moisture flux, -heat flux, -microstructure of Stratus- and Stratocumulus clouds (e.g. liquid water content or ice content, esp. in winter), -cloud cover with Stratus- or Stratocumulus clouds, -precipitation intensity, -height of cloud base for Stratus- and Stratocumulus clouds, -microstructure of fog layers, -structure of boundary layer… 3. If there will be an interest to – maybe to go for tile approach…

THANK YOU FOR YOUR ATTENTION AUTHORS:Grzegorz Duniec Warszawa, ul.: Podleśna 61 phone: +48 (22) Andrzej Mazur Warszawa, ul.: Podleśna 61 phone: +48 (22)