MCIPv3: Using WRF-EM Output with CMAQ

Similar documents
Creating Meteorology for CMAQ

WRF Modeling System Overview

WRF Modeling System Overview

WRF Modeling System Overview

Accuracy and Cost Considerations in Choosing a Chemical Mechanism for Operational Use in AQ Models

WRF Modeling System Overview

Improvement of Meteorological Inputs for Air Quality Study

THE WEATHER RESEARCH AND FORECAST MODEL VERSION 2.0

Supplement of Photochemical grid model implementation and application of VOC, NO x, and O 3 source apportionment

The Meteorology-Chemistry Interface Processor (MCIP) for the CMAQ modeling system: updates through MCIPv3.4.1

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

Preliminary Experiences with the Multi Model Air Quality Forecasting System for New York State

MULTI-MODEL AIR QUALITY FORECASTING OVER NEW YORK STATE FOR SUMMER 2008

WRF Modeling System Overview

APPLICATION OF CMAQ ON HEMISPHERIC SCALES

The Developmental Testbed Center: Update on Data Assimilation System Testing and Community Support

PRELIMINARY EXPERIENCES WITH THE MULTI-MODEL AIR QUALITY FORECASTING SYSTEM FOR NEW YORK STATE

Statement of the Problem

THE ATMOSPHERIC MODEL EVALUATION TOOL: METEOROLOGY MODULE

Air Quality Screening Modeling

Improvements to the NCEP Global and Regional Data Assimilation Systems

User's Guide for the NMM Core of the Weather Research and Forecast (WRF) Modeling System Version 3. Chapter 4: WRF-NMM Initialization

Urban Forest Effects-Dry Deposition (UFORE D) Model Enhancements. Satoshi Hirabayashi

The WRF NMM Core. Zavisa Janjic Talk modified and presented by Matthew Pyle

Methodology for the creation of meteorological datasets for Local Air Quality modelling at airports

AIRQUEST Annual Report and State of the Model

Lateral Boundary Conditions

Canadian Meteorological and Oceanographic Society and American Meteorological Society 21 st Conference on Numerical Weather Prediction 31 May 2012

2012 and changes to the Rapid Refresh and HRRR weather forecast models

Gridded Met. Data Workgroup

Typhoon Relocation in CWB WRF

GSI Data Assimilation System Support and Testing Activities: 2013 Annual Update

CMAQ Modeling of Atmospheric Mercury

Description of. Jimy Dudhia Dave Gill. Bill Skamarock. WPS d1 output. WPS d2 output Real and WRF. real.exe General Functions.

Weather Research and Forecasting Model

Numerical Weather Prediction. Meteorology 311 Fall 2010

WRF Model Simulated Proxy Datasets Used for GOES-R Research Activities

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

Current and Future Impacts of Wildfires on PM 2.5, Health, and Policy in the Rocky Mountains

Status of Atmospheric Winds in Relation to Infrasound. Douglas P. Drob Space Science Division Naval Research Laboratory Washington, DC 20375

Update on the assimilation of GPS RO data at NCEP

ATMOSPHERIC MERCURY SIMULATION WITH CMAQ VERSION 4.5.1

Enhancing Weather Forecasts via Assimilating SMAP Soil Moisture and NRT GVF

HWRF Dynamics The WRF-NMM

Air Quality Simulation of Traffic Related Emissions: Application of Fine-Scaled Dispersion Modelling

Chapter 3 DEVELOPING METEOROLOGICAL FIELDS

JOINT WMO TECHNICAL PROGRESS REPORT ON THE GLOBAL DATA PROCESSING AND FORECASTING SYSTEM AND NUMERICAL WEATHER PREDICTION RESEARCH ACTIVITIES FOR 2016

Numerical Weather Prediction. Meteorology 311 Fall 2016

Radar data assimilation using a modular programming approach with the Ensemble Kalman Filter: preliminary results

RSMC WASHINGTON USER'S INTERPRETATION GUIDELINES ATMOSPHERIC TRANSPORT MODEL OUTPUTS

NOAA Direct Broadcast Data Initiative to Meet NWP Latency Requirements

MATERHORN Field Campaign

Validation of Boundary Layer Winds from WRF Mesoscale Forecasts over Denmark

Global reanalysis: Some lessons learned and future plans

GSI DATA ASSIMILATION SYSTEM: COMMUNITY SUPPORT AND PRELIMINARY TESTING RESULTS

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

Global Change and Air Pollution (EPA-STAR GCAP) Daniel J. Jacob

Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advancedresearch Hurricane WRF (AHW) Model

Bayesian hierarchical modelling for data assimilation of past observations and numerical model forecasts

MxVision WeatherSentry Web Services Content Guide

5.3 TESTING AND EVALUATION OF THE GSI DATA ASSIMILATION SYSTEM

An Overview of Atmospheric Analyses and Reanalyses for Climate

Forecasting of Optical Turbulence in Support of Realtime Optical Imaging and Communication Systems

NOAA-EPA s s U.S. National Air Quality Forecast Capability

AREP GAW. AQ Forecasting

The Impact of Horizontal Resolution and Ensemble Size on Probabilistic Forecasts of Precipitation by the ECMWF EPS

HIGH RESOLUTION CMAQ APPLICATION FOR THE REGIONAL MUNICIPALITY OF PEEL, ONTARIO, CANADA

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

Some Applications of WRF/DART

AERMOD Technical Forum

SPECIAL PROJECT PROGRESS REPORT

Masahiro Kazumori, Takashi Kadowaki Numerical Prediction Division Japan Meteorological Agency

Deliverable D1.2 Technical report with the characteristics of the models. Atmospheric model WRF-ARW

Speedwell High Resolution WRF Forecasts. Application

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

RESEARCH THEME: DERIVATION OF BATTLESPACE PARAMETERS Roger A. Pielke Sr., P.I.

Application of the Weather Research and Forecasting Model for Air Quality Modeling in the San Francisco Bay Area

6.1 WEATHER RESEARCH AND FORECASTING MODEL WIND SENSITIVITY STUDY AT EDWARDS AIR FORCE BASE, CA

Comparing Variational, Ensemble-based and Hybrid Data Assimilations at Regional Scales

11A.6 ON THE ROLE OF ATMOSPHERIC DATA ASSIMILATION AND MODEL RESOLUTION ON MODEL FORECAST ACCURACY FOR THE TORINO WINTER OLYMPICS

Regional Scale Modeling and Numerical Weather Prediction

Incorporating Space-borne Observations to Improve Biogenic Emission Estimates in Texas (Project )

Lecture 10 March 15, 2010, Monday. Atmospheric Pressure & Wind: Part 1

USE OF SURFACE MESONET DATA IN THE NCEP REGIONAL GSI SYSTEM

Thunderstorm-Scale EnKF Analyses Verified with Dual-Polarization, Dual-Doppler Radar Data

Prediction of tropical cyclone induced wind field by using mesoscale model and JMA best track

Overview of U.S. Forecasting/Outreach Methods

An evaluation of wind indices for KVT Meso, MERRA and MERRA2

Polar WRF. Polar Meteorology Group Byrd Polar and Climate Research Center The Ohio State University Columbus Ohio

Introduction to ensemble forecasting. Eric J. Kostelich

GSI Tutorial Background and Observation Errors: Estimation and Tuning. Daryl Kleist NCEP/EMC June 2011 GSI Tutorial

Ozone Transport Commission. Modeling Committee. Editor: Debra Baker MDE. Contributors. Debra Baker MDE. Tom Downs ME DEP.

Francis O. 1, David H. Bromwich 1,2

Assessing Potential Impact of Air Pollutant Observations from the Geostationary Satellite on Air Quality Prediction through OSSEs

Worldwide Data Quality Effects on PBL Short-Range Regulatory Air Dispersion Models

NCEP s UNIFIED POST PROCESSOR (UPP) 2018 HWRF Tutorial

Comparison of Typhoon Track Forecast using Dynamical Initialization Schemeinstalled

18.1 MODELING EXTREMELY COLD STABLE BOUNDARY LAYERS OVER INTERIOR ALASKA USING A WRF FDDA SYSTEM

ASSESMENT OF THE SEVERE WEATHER ENVIROMENT IN NORTH AMERICA SIMULATED BY A GLOBAL CLIMATE MODEL

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

Transcription:

MCIPv3: Using WRF-EM Output with CMAQ Tanya L. Otte* and Jonathan E. Pleim* EPA/ORD/NERL/Atmospheric Modeling Division Research Triangle Park, NC *On assignment from NOAA Air Resources Laboratory Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce s National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.

MCIP Version 3.0 Highlights Process MM5 or WRF fields with same code Optional dry deposition species for Cl (6) and Hg (2) Corrections for Southern Hemisphere domains Optimizations for processing met fields to MCIP arrays Don t need to specify vertical structure if same as met Expanded maximum number of input met files MM5v3 layer heights consistent with NCAR formulae Define MM5 winds on C-grid with less interpolation

MCIP Version 3.0 Highlights (cont.) Use 10-m wind components directly from MM5 or WRF (if available) for output 10-m wind speed and direction Use fractional land use (if available) to derive % urban for new min K z algorithm in CMAQ and for RADMdry I/O API 3: consistency check for params in I/O API Changed meteorology ingest arrays to (x,y,z) Updated compiler options for IBM, PGF90, and Intel Updated script New Frequently Asked Questions List (FAQ)

Transitioning to WRF Will be gradual switch from MM5 to WRF-EM Steep learning curve (programs, data, scripts ) Critical components for AQM under development Four-dimensional data assimilation (FDDA) via nudging Pleim-Xiu land-surface model (PX LSM) Demonstration of WRF capability is mandatory Initial evaluation of WRF simulations is underway Suitability of WRF fields for CMAQ is just starting

Adding WRF Processing to MCIP U. Houston WCIP was incorporated and enhanced Several issues to keep MCIP user-friendly Array convention: (y,x,z kmax 1 ) changed to (x,y,z 1 kmax ) Horizontal grid, vertical structure, state variables Minimize user changes to WRF Registry Allow users to transition to WRF with minimal delay MCIP generalized to support using MM5 and WRF May facilitate new met models in MCIP by users

Differences Between MM5 and WRF Horizontal grid (Arakawa and Lamb, 1978) B j+1 h u,v C j+1 v h u j j j-1 i-1 i i+1 dx j-1 i-1 i i+1 dx MM5 WRF-EM, CMAQ, RAMS

Differences Between MM5 and WRF Vertical: terrain-following, based on different prs MM5: p = reference total prs; WRF: p = dry hydrostatic prs MM5 σ = p - p t WRF η = p - p h ht p * μ p* = p - p s t μ = p - h p s h t

Differences Between MM5 and WRF Meteorology state variables: MM5 U- and V-component wind (dot points) Temperature Water Vapor Mixing Ratio Pressure (reference + perturbation) WRF U- and V-component wind (face points) Potential Temperature Water Vapor Mixing Ratio Density (dry) Geopotential

Differences Between MM5 and WRF CMAQ state variables based on met state equations MM5 Jacobian: J = pr * ρ g r WRF Jacobian: J p * J = ρg = μ g ρ d Density (ρ r ) = Reference total density Reduced Pressure (p r *) = reference total pressure Density (ρ d ) = dry density Reduced Pressure (μ) = time-varying, dry hydro. prs

WRF Data and MCIPv3 Must be WRFv2.0 or greater. MCIPv3 developed from WRFv2.0.3.1 (Dec. 2004) Must be WRF-EM (a.k.a. ARW or NCAR core) WRF namelist variable dyn_opt=2 MCIPv3 does not support WRF-NMM (NCEP core) Must have WRF I/O API formatted output WRF namelist variable io_form_history=2

WRF Data and MCIPv3 (continued) Must use non-hydrostatic dynamics in WRF WRF namelist variable non_hydrostatic=.true. Should have, at most, hourly output in WRF WRF namelist variable history_interval=60. (or less) Need to add 2D variables to output via Registry: Friction velocity (UST) Albedo (ALBEDO) Emissivity (EMISS) Roughness Length (ZNT)

Negative Mixing Ratios in WRF Can occur as a result of the non-positive-definite advection scheme in WRF-EM Will cause problems in CMAQ Can zero out or constrain negative mixing ratios to user-definable minimum value in WRF MCIP sets minimums on mixing ratios 1.0 x 10-14 kg/kg for Q v 1.0 x 10-30 kg/kg for Q c, Q i, Q r, Q s, Q g

Simple Comparison of MM5 and WRF Yes this is apples vs. oranges Run for 12 UTC 19 Jun 00 UTC 19 Aug 2001 Use same domain & RAWINS analyses for both MM5 in 108-h chunks; WRF in 60-h chunks 12-h spin-up period ignored for both sets MM5 w/ FDDA & LSM; WRF w/o FDDA or LSM Other options as appropriate Is WRF qualitatively OK for retrospective AQM?

Sample MM5 and WRF-EM t + 12 h MM5 has nudging and P-X LSM. WRF has no nudging and no LSM. t + 60 h As expected, WRF simulation (as strictly forecast) is less accurate over time than MM5 simulation with the benefit of nudging and LSM. Using WRF as is for AQM today would require much more frequent initialization.

Sample MM5 and WRF-EM MM5 (with nudging and LSM) WRF (with no nudging or LSM) 12-36 h 12-36 h Logarithmic color scale from -10 K to +10 K. Green / yellow / orange = warm bias Blue / purple / red = cool bias 36-60 h 36-60 h Both simulations initialized at 12 UTC 8 Aug 2001.

Sample MM5 and WRF-EM MM5: July 2001 Great Lakes WRF: July 2001 Great Lakes MM5: July 2001 South WRF: July 2001 South

Future Directions Extensive testing and applications with WRF Explore WRF options, model behavior Assess impacts on both meteorology and chemistry Support for WRF options not currently considered Nudging Start with analysis nudging option Extend to obs nudging as it becomes available Pleim-Xiu LSM testing Compare with MM5 runs for similar period Can WRF outperform MM5 for retrospective AQM?

Credits S.-B. Kim and D. Byun (U. Houston) WCIP R. Gilliam (NOAA) Use of AMET G. Sarwar (EPA) Cl dry dep R. Bullock (NOAA) Hg dry dep W. Hutzell (EPA) Dry dep reorg P. Sanhueza (U. Santiago, Chile) and C. Wiedinmyer (NCAR) Southern Hemisphere issues Z. Adelman (UNC) Use all met layers without specifying a priori D. Wong (Lockheed Martin) MCIP optimizations D. Byun (U. Houston) Fractional land use for RADMdry MCIPv3 Beta Testers especially: K. Baker (LADCO) K. Smith (WeatherSmith, LLC) P. Sanhueza (U. Santiago, Chile) Q. Mao and T. Cook (TVA) M. Prodanova (Bulgarian Academy of Sciences, Bulgaria) F. Ngan (U. Houston) Z. Wang (U. California, Riverside)