Solar irradiance modelling over Belgium using WRF-ARW :

Similar documents
Assessment of the Noah LSM with Multi-parameterization Options (Noah-MP) within WRF

Development and Testing of Polar WRF *

Wind conditions based on coupling between a mesoscale and microscale model

Simulating roll clouds associated with low-level convergence in WRF

Water Balance in the Murray-Darling Basin and the recent drought as modelled with WRF

Influences of PBL Parameterizations on Warm-Season Convection-Permitting Regional Climate Simulations

WRF SOLAR FORECASTING

Supplementary Material

Sensitivity of precipitation forecasts to cumulus parameterizations in Catalonia (NE Spain)

ANNUAL WRF SIMULATIONS FOR THE UTAH BUREAU OF LAND MANAGEMENT S AIR RESOURCE MANAGEMENT STRATEGY (ARMS) AIR QUALITY MODELING

Testing and Improving Pacific NW PBL forecasts

Accuracy comparison of mesoscale model simulated offshore wind speeds between Japanese and German coastal waters

Variable-Resoluiton Global Atmospheric Modeling Spanning Convective to Planetary Scales

Sensitivity of tropical cyclone Jal simulations to physics parameterizations

Analysis and accuracy of the Weather Research and Forecasting Model (WRF) for Climate Change Prediction in Thailand

D.Carvalho, A, Rocha, at 2014 Applied Energy. Report person:zhang Jiarong. Date:

FINAL PROJECT REPORT YEAR: 2013 WTFRC Project Number: TR Project Title: High resolution weather forecasting for freeze prediction in WA

Simulation studies for Lake Taihu effect on local meteorological environment. Ren Xia

Upsidence wave during VOCALS. David A. Rahn and René Garreaud Department of Geophysics Universidad de Chile

Upsidence wave during VOCALS. David A. Rahn and René Garreaud Department of Geophysics Universidad de Chile

National Center for Atmospheric Research Research Applications Laboratory Renewable Energy

WRF-RTFDDA Optimization and Wind Farm Data Assimilation

Jordan G. Powers Kevin W. Manning. Mesoscale and Microscale Meteorology Laboratory National Center for Atmospheric Research Boulder, Colorado, USA

HWRF sensitivity to cumulus schemes

Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

VALIDATION OF BOUNDARY-LAYER WINDS FROM WRF MESOSCALE FORECASTS WITH APPLICATIONS TO WIND ENERGY FORECASTING

Forecasting the Diabatic Offshore Wind Profile at FINO1 with the WRF Mesoscale Model

LARGE-SCALE WRF-SIMULATED PROXY ATMOSPHERIC PROFILE DATASETS USED TO SUPPORT GOES-R RESEARCH ACTIVITIES

Preliminary results. Leonardo Calvetti, Rafael Toshio, Flávio Deppe and Cesar Beneti. Technological Institute SIMEPAR, Curitiba, Paraná, Brazil

COSMIC GPS Radio Occultation and

EVALUATION OF THE PRESAXIO AIR QUALITY FORECASTING SYSTEM: PBL SCHEMES WRF COMPARISON AND AIR QUALITY MODELING VALIDATION

Lightning Data Assimilation using an Ensemble Kalman Filter

Application of the Ems-Wrf Model in Dekadal Rainfall Prediction over the Gha Region Franklin J. Opijah 1, Joseph N. Mutemi 1, Laban A.

2012 AHW Stream 1.5 Retrospective Results

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height

Tue 2/16/2016. Wrap-up on some WRF PBL options Paper presentations (Hans, Pat, Dylan, Masih, Xia, James) Begin convective parameterization (if time)

Investigation of surface layer parameterization in WRF model & its impact on modeled nocturnal wind biases

Incorporation of 3D Shortwave Radiative Effects within the Weather Research and Forecasting Model

Improved rainfall and cloud-radiation interaction with Betts-Miller-Janjic cumulus scheme in the tropics

A comparative study on the genesis of North Indian Ocean cyclone Madi (2013) and Atlantic Ocean cyclone Florence (2006)

P Hurricane Danielle Tropical Cyclogenesis Forecasting Study Using the NCAR Advanced Research WRF Model

Observations and WRF simulations of fog events Engineering at the Spanish Northern Plateau

608 SENSITIVITY OF TYPHOON PARMA TO VARIOUS WRF MODEL CONFIGURATIONS

Assessing WRF PBL Schemes for Wind Energy Applications

Regional Climate Simulations with WRF Model

Weather Research and Forecasting Model. Melissa Goering Glen Sampson ATMO 595E November 18, 2004

Numerical Prediction of Tropical Cyclones (PAGASA Experience)

P1.2 SENSITIVITY OF WRF MODEL FORECASTS TO DIFFERENT PHYSICAL PARAMETERIZATIONS IN THE BEAUFORT SEA REGION

Challenges of convection-permitting regional climate simulations for future climate projection in Japan

Development and Validation of Polar WRF

Comparison of Typhoon Track Forecast using Dynamical Initialization Schemeinstalled

Track sensitivity to microphysics and radiation

Development of a Coupled Atmosphere-Ocean-Land General Circulation Model (GCM) at the Frontier Research Center for Global Change

Improved Representation of Boundary Layer Clouds over the Southeast Pacific in ARW-WRF Using a Modified Tiedtke Cumulus Parameterization Scheme*

Dynamic Ensemble Model Evaluation of Elevated Thunderstorms sampled by PRECIP

PERFORMANCE OF THE WRF-ARW IN THE COMPLEX TERRAIN OF SALT LAKE CITY

Importance of Numerical Weather Prediction in Variable Renewable Energy Forecast

Variational data assimilation of lightning with WRFDA system using nonlinear observation operators

High resolution rainfall projections for the Greater Sydney Region

Arctic System Reanalysis Provides Highresolution Accuracy for Arctic Studies

CAPS Storm-Scale Ensemble Forecasting (SSEF) System

A New Ocean Mixed-Layer Model Coupled into WRF

Importance of minor treatments in parameterizations in GCMs for the cloud representations and the cloud feedbacks

Jordan G. Powers Kevin W. Manning. Mesoscale and Microscale Meteorology Laboratory National Center for Atmospheric Research Boulder, CO

Toward improved initial conditions for NCAR s real-time convection-allowing ensemble. Ryan Sobash, Glen Romine, Craig Schwartz, and Kate Fossell

QUANTITATIVE VERIFICATION STATISTICS OF WRF PREDICTIONS OVER THE MEDITERRANEAN REGION

NCEP s "NAM" (North American Mesoscale) model WRF-NMM. NCEP =National Centers for Environmental Prediction

A GSI-based convection-allowing EnKF and ensemble forecast system for PECAN

Toshi Matsui, Taka Iguchi, and Wei-Kuo Tao NASA GSFC Code 612 ESSIC UMD

Advanced Hurricane WRF (AHW) Physics

An analysis of Wintertime Cold-Air Pool in Armenia Using Climatological Observations and WRF Model Data

Logistics. Goof up P? R? Can you log in? Requests for: Teragrid yes? NCSA no? Anders Colberg Syrowski Curtis Rastogi Yang Chiu

Arctic System Reanalysis

Causes of WRF surface energy fluxes biases in a stratocumulus region

The Fifth-Generation NCAR / Penn State Mesoscale Model (MM5) Mark Decker Feiqin Xie ATMO 595E November 23, 2004 Department of Atmospheric Science

Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO 2 mole fractions in the US Midwest

IMPROVING CLOUD PREDICTION IN WRF THROUGH THE USE OF GOES SATELLITE ASSIMILATION

Analysis of different wind gust forecast approaches

Overview of HFIP FY10 activities and results

Numerical Weather Prediction: Data assimilation. Steven Cavallo

Aaron Johnson* and Xuguang Wang. University of Oklahoma School of Meteorology and Center for Analysis and Prediction of Storms (CAPS), Norman, OK

Field Experiment on the Effects of a Nearby Asphalt Road on Temperature Measurement

Assimilating MTSAT-Derived Humidity in Nowcasting Sea Fog over the Yellow Sea

Intercomparison of 7 Planetary Boundary- Layer/Surface-Layer Physics Schemes over Complex Terrain for Battlefield Situational Awareness

Air Quality Modeling from the Offshore Energy Sector in the Gulf of Mexico: An Overview for the Oil and Gas Industry

P1M.4 COUPLED ATMOSPHERE, LAND-SURFACE, HYDROLOGY, OCEAN-WAVE, AND OCEAN-CURRENT MODELS FOR MESOSCALE WATER AND ENERGY CIRCULATIONS

UNIVERSITY OF CALIFORNIA

VERIFICATION OF HIGH RESOLUTION WRF-RTFDDA SURFACE FORECASTS OVER MOUNTAINS AND PLAINS

Predicting Wind Power Generation

Creating Meteorology for CMAQ

An Integrated Approach to the Prediction of Weather, Renewable Energy Generation and Energy Demand in Vermont

Warm weather s a comin!

Evaluation of WRF Model Output for Severe Weather Forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment

Downscaling and Probability

Evaluation of High-Resolution WRF Model Simulations of Surface Wind over the West Coast of India

Egyptian Meteorological Authority Cairo Numerical Weather prediction centre

Comprehensive Analysis of Annual 2005/2008 Simulation of WRF/CMAQ over Southeast of England

State of the art of wind forecasting and planned improvements for NWP Helmut Frank (DWD), Malte Mülller (met.no), Clive Wilson (UKMO)

Wind turbines in icing conditions: performance and prediction

Meteorological Modeling using Penn State/NCAR 5 th Generation Mesoscale Model (MM5)

Transcription:

Solar irradiance modelling over Belgium Sensitivity analysis of Mellor-Yamada- Nakanishi-Niino (MYNN) boundary layer scheme parameters Beaumet J., Fettweis X., Doutreloup S. & Erpicum M. Meteoclim, PhD Symposium Antwerpen, 06/06/2014

Overview Context Simulation set-up Results Focus : modelling of different weather/clouds types - Low clouds (St, Sc) - Convective clouds (Cu) - Clear skies and thermal inversions A Modèle Atmosphérique Régional (MAR) / WRF-ARW comparison Conclusions 2 J.Beaumet (ULg)

I. Context PREMASOL project : - Photovoltaic production day-ahead Solar Incident Irradiances (SWD) forecasting (+ 2m Wind and T ) using WRF-ARW forced by GFS - Global and diffuse irradiance measurement at Centre Spatial de Liège (CSL) PhD : Regional Climate Model version calibrated for solar irradiance, wind and temperature modelling over Belgium forecasting and future changes 3 J.Beaumet (ULg)

II. Simulations set-up WRF-ARW v3.6 (released April 2014) Surface schemes : 6 microphysic schemes : 16 Short-wave schemes : 7 boundary layer schemes : 10 Cumulus schemes : 9 surface layer schemes : 7 Inner domain : 5 km Time-scale : 15 minutes Observations : SWD measured at Liège (Sart-Tilman) Validation : Two periods November December 2013 March April 2014 Relative BIAS and RMSE (in %) 4 J.Beaumet (ULg)

III. Results Huge number of possible set-ups Lot of them tested at our laboratory NO SIGNIFICANT CHANGES In spring : significant positive (dry) BIAS (+20%) and RMSE ~ 40 % In winter : slight negative BIAS (-10%) but very large relative RMSE (~70%) Get inside scheme codes for further calibration Surface scheme : Noah lsm Microphysics scheme : Thompson SW scheme : Dudhia Surface layer scheme : Monin-Obukhov Cumulus scheme : Kain-Fritsch Boundary layer scheme : MYNN 2.5 5 J.Beaumet (ULg)

III. Solar irradiance modelling over Belgium Results Over a «long» period : no significant changes/improvements But for some days, changes can be important November December 2013 March April 2014 rbias(%) rrmse(%) rbias(%) rrmse(%) Alp5 = 0.5-9,4 76,3 Alp5 = 1.0-11,8 77 Alp5 = 5.0-5,8 68,9 Alp5 = 10.0 0 71,6 Alp5 = 0.5 22,7 41,4 Alp5 = 1.0 22,2 41,5 Alp5 = 5.0 23 42,2 Alp5 = 10.0 21,1 42,6 Relative (in %) BIAS and RMSE for the modelling of solar irradiance (SWD) using different WRF versions at Liège (Sart-Tilman) Alp5 : in winter reduced negative BIAS for increasing values increase mixing length fastest cloud clearance 6 J.Beaumet (ULg)

IV. Focus : modelling of low clouds (St, Sc) Modelled vs Observed SWD at Liège (Sart-Tilman) 7 J.Beaumet (ULg) WRF versions : alp5 = 0.5,1,5,10

IV. Focus : modelling of low clouds (St, Sc) Modelled cloud water content over Liège (Sart-Tilman) 8 J.Beaumet (ULg) WRF versions : alp5 = 1,5

IV. Focus : modelling of low clouds (St, Sc) Modelled cloud water content over Liège (Sart-Tilman) Obs: Am. 5,6/8 St Pm. 8/8 Sc 9 J.Beaumet (ULg) WRF versions : alp5 = 1,5

IV. Focus : modelling of convective clouds (Cu) Modelled vs Observed SWD at Liège (Sart-Tilman) 10 J.Beaumet (ULg) WRF versions : alp5 = 0.5,1,5,10

IV. Focus : modelling of convective clouds (Cu) Modelled cloud water content over Liège (Sart-Tilman) 11 J.Beaumet (ULg) WRF versions : alp5 = 1,5

IV. Focus : clear skies and pollution peak? Modelled vs Observed SWD at Liège (Sart-Tilman) 12 J.Beaumet (ULg)

V. MAR (ULg) / WRF comparison (2013) Modelled vs Observed SWD at Liège (Sart-Tilman) 13 J.Beaumet (ULg)

VI. Conclusions I. Boundary layer scheme parameters modifications : - No significant improvement considering long periods - Lack of convective clouds in WRF simulations unchanged - Possible strategy for ensembles forecasts II. Encouraging results for MAR model 14 J.Beaumet (ULg)

Reference Nakanishi M. and Niino H., 2004. An improved Mellor Yamada Level-3 model with Condensation physics : its design and verification. Boundary-Layer Meteorology, 112, 1-31. Mellor G. and Yamada T., 1982. Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20/4, 851-875. Kitamura Y., 2010. Modifications of the Mellor-Yamada-Nakanishi-Niino (MYNN) model for the stable stratification case. Journal of the Meteorological Society of Japan, 88-5, 857-864. Lopez-Coto I., Bosch J., Mathiensen P. and Kleissl J., 2012. Comparison between several parameterization schemes in WRF for solar forecasting in coastal zones. UCAR technical notes. Questions? 15 J.Beaumet (ULg)