NOAA Earth System Research Laboratory

Slides:



Advertisements
Similar presentations
Matthew Hendrickson, and Pascal Storck
Advertisements

WRF Modeling System V2.0 Overview
Statistical post-processing using reforecasts to improve medium- range renewable energy forecasts Tom Hamill and Jeff Whitaker NOAA Earth System Research.
Advanced Research WRF High Resolution Simulations of Hurricanes Katrina, Rita and Wilma (2005) Kristen L. Corbosiero, Wei Wang, Yongsheng Chen, Jimy Dudhia.
Atmospheric Reanalyses Update Mike Bosilovich. ReanalysisHoriz.ResDatesVintageStatus NCEP/NCAR R1T present1995ongoing NCEP-DOE R2T present2001ongoing.
CHOICES FOR HURRICANE REGIONAL ENSEMBLE FORECAST (HREF) SYSTEM Zoltan Toth and Isidora Jankov.
Observing System Simulation Experiments to Evaluate the Potential Impact of Proposed Observing Systems on Hurricane Prediction: R. Atlas, T. Vukicevic,
5/22/201563rd Interdepartmental Hurricane Conference, March 2-5, 2009, St. Petersburg, FL Experiments of Hurricane Initialization with Airborne Doppler.
Instituting Reforecasting at NCEP/EMC Tom Hamill (ESRL) Yuejian Zhu (EMC) Tom Workoff (WPC) Kathryn Gilbert (MDL) Mike Charles (CPC) Hank Herr (OHD) Trevor.
Recent performance statistics for AMPS real-time forecasts Kevin W. Manning – National Center for Atmospheric Research NCAR Earth System Laboratory Mesoscale.
Convection-permitting forecasts initialized with continuously-cycling limited-area 3DVAR, EnKF and “hybrid” data assimilation systems Craig Schwartz and.
AHW Ensemble Data Assimilation and Forecasting System Ryan D. Torn, Univ. Albany, SUNY Chris Davis, Wei Wang, Steven Cavallo, Chris Snyder, James Done,
S4D WorkshopParis, France Polar Meteorology Group, Byrd Polar Research Center, The Ohio State University, Columbus, Ohio A High-Resolution David H. Bromwich.
Assimilating Sounding, Surface and Profiler Observations with a WRF-based EnKF for An MCV Case during BAMEX Zhiyong Meng & Fuqing Zhang Texas A&M University.
Initializing a Hurricane Vortex with an EnKF Yongsheng Chen Chris Snyder MMM / NCAR.
The NCEP operational Climate Forecast System : configuration, products, and plan for the future Hua-Lu Pan Environmental Modeling Center NCEP.
Brian Ancell, Cliff Mass, Gregory J. Hakim University of Washington
Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land.
1 NGGPS Dynamic Core Requirements Workshop NCEP Future Global Model Requirements and Discussion Mark Iredell, Global Modeling and EMC August 4, 2014.
The Relative Contribution of Atmospheric and Oceanic Uncertainty in TC Intensity Forecasts Ryan D. Torn University at Albany, SUNY World Weather Open Science.
1 st UNSTABLE Science Workshop April 2007 Science Question 3: Science Question 3: Numerical Weather Prediction Aspects of Forecasting Alberta Thunderstorms.
Ensemble Post-Processing and it’s Potential Benefits for the Operational Forecaster Michael Erickson and Brian A. Colle School of Marine and Atmospheric.
Impact of the 4D-Var Assimilation of Airborne Doppler Radar Data on Numerical Simulations of the Genesis of Typhoon Nuri (2008) Zhan Li and Zhaoxia Pu.
Lili Lei1,2, David R. Stauffer1 and Aijun Deng1
Configuring, storing, and serving the next-generation global reforecast Tom Hamill NOAA Earth System Research Lab 1 NOAA Earth System Research Laboratory.
UKmet February Hybrid Ensemble-Variational Data Assimilation Development A partnership to develop and implement a hybrid 3D-VAR system –Joint venture.
Henry R. Winterbottom, Eric P. Chassignet, and Carol Anne Clayson A Coupled Atmosphere-Ocean Model System for Tropical Cyclone Studies Motivation Methodology.
Incorporation of TAMDAR into Real-time Local Modeling Tom Hultquist Science & Operations Officer NOAA/National Weather Service Marquette, MI.
Observing Strategy and Observation Targeting for Tropical Cyclones Using Ensemble-Based Sensitivity Analysis and Data Assimilation Chen, Deng-Shun 3 Dec,
Atmospheric Modeling in an Arctic System Model John J. Cassano Cooperative Institute for Research in Environmental Sciences and Department of Atmospheric.
On the Multi-Intensity Changes of Hurricane Earl (2010) Daniel Nelson, Jung Hoon Shin, and Da-Lin Zhang Department of Atmospheric and Oceanic Science University.
Improvements of WRF Simulation Skills of Southeast United States Summer Rainfall: Focus on Physical Parameterization and Horizontal Resolution Laifang.
By: Michael Kevin Hernandez Key JTWC ET onset JTWC Post ET  Fig. 1: JTWC best track data on TC Sinlaku (2008). ECMWF analysis ET completion ECMWF analysis.
MPO 674 Lecture 20 3/26/15. 3d-Var vs 4d-Var.
Comparison of Different Approaches NCAR Earth System Laboratory National Center for Atmospheric Research NCAR is Sponsored by NSF and this work is partially.
In this study, HWRF model simulations for two events were evaluated by analyzing the mean sea level pressure, precipitation, wind fields and hydrometeors.
IMPACTS OF TURBULENCE ON HURRICANES (ONR-BAA ) PI: Yongsheng Chen, York University, Toronto, Ontario, Canada Co-PIs: George H. Bryan and Richard.
Development of an EnKF/Hybrid Data Assimilation System for Mesoscale Application with the Rapid Refresh Ming Hu 1,2, Yujie Pan 3, Kefeng Zhu 3, Xuguang.
Non-hydrostatic Numerical Model Study on Tropical Mesoscale System During SCOUT DARWIN Campaign Wuhu Feng 1 and M.P. Chipperfield 1 IAS, School of Earth.
Earth-Sun System Division National Aeronautics and Space Administration SPoRT SAC Nov 21-22, 2005 Regional Modeling using MODIS SST composites Prepared.
Predictability and dynamics of the rapid intensification of Hurricane Edouard (2014) Erin Munsell and Fuqing Zhang (Penn State) Jason Sippel (EMC/IMSG)
Global Observing System Simulation Experiments (Global OSSEs) How It Works Nature Run 13-month uninterrupted forecast produces alternative atmosphere.
1 An overview of the use of reforecasts for improving probabilistic weather forecasts Tom Hamill NOAA / ESRL, Physical Sciences Div.
Ligia Bernardet, S. Bao, C. Harrop, D. Stark, T. Brown, and L. Carson Technology Transfer in Tropical Cyclone Numerical Modeling – The Role of the DTC.
DATA ASSIMILATION FOR HURRICANE PREDICTION Experimental system and results of semi-operational implementation during the 2010 Atlantic Hurricane Season.
Tropical Transition in the Eastern North Pacific: Sensitivity to Microphysics Alicia M. Bentley ATM May 2012.
Are Numerical Weather Prediction Models Getting Better? Cliff Mass, David Ovens, and Jeff Baars University of Washington.
Research on the HWRF Model: Intensification and Uncertainties in Model Physics Research on the HWRF Model: Intensification and Uncertainties in Model Physics.
Impact of the backscatter kinetic energy on the perturbation of ensemble members for strong convective event Jakub Guzikowski
Application of a Hybrid Dynamical-Statistical Model for Week 3 and 4 Forecast of Atlantic/Pacific Tropical Storm and Hurricane Activity Jae-Kyung E. Schemm.
Ensemble variability in rainfall forecasts of Hurricane Irene (2011) Molly Smith, Ryan Torn, Kristen Corbosiero, and Philip Pegion NWS Focal Points: Steve.
Progress Update of Numerical Simulation for OSSE Project Yongzuo Li 11/18/2008.
Real-Time High-Resolution MM5 and WRF Forecasts during RAINEX John P. Cangialosi 1*, S. S. Chen 1, W. Zhao 1, D. Ortt 1 W. Wang 2 and J. Michalakas 2 1.
Studying impacts of the Saharan Air Layer on hurricane development using WRF-Chem/EnKF Jianyu(Richard) Liang Yongsheng Chen 6th EnKF Workshop York University.
An Examination Of Interesting Properties Regarding A Physics Ensemble 2012 WRF Users’ Workshop Nick P. Bassill June 28 th, 2012.
The Hyperspectral Environmental Suite (HES) and Advanced Baseline Imager (ABI) will be flown on the next generation of NOAA Geostationary Operational Environmental.
Modeling and Evaluation of Antarctic Boundary Layer
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Predicting Hurricanes with Explicit Convection: The Advanced Hurricane-research WRF (AHW) Chris Davis NCAR Earth System Laboratory Mesoscale and Microscale.
Ensemble prediction review for WGNE, 2010 Tom Hamill 1 and Pedro de Silva-Dias 2 1 NOAA/ESRL 2 Laboratório Nacional de Computação Científica
1 Current and planned research with data collected during the IFEX/RAINEX missions Robert Rogers NOAA/AOML/Hurricane Research Division.
WRF-based rapid updating cycling system of BMB(BJ-RUC) and its performance during the Olympic Games 2008 Min Chen, Shui-yong Fan, Jiqin Zhong Institute.
Advisor: Dr. Fuqing Zhang
Jianyu Liang (York U.) Yongsheng Chen (York U.) Zhiquan Liu (NCAR)
Coupled atmosphere-ocean simulation on hurricane forecast
Group meeting: Summary for HFIP 2012
IMPROVING HURRICANE INTENSITY FORECASTS IN A MESOSCALE MODEL VIA MICROPHYSICAL PARAMETERIZATION METHODS By Cerese Albers & Dr. TN Krishnamurti- FSU Dept.
gWRF Workflow and Input Data Requirements
2007 Mei-yu season Chien and Kuo (2009), GPS Solutions
Access and visualization of theTwentieth Century Reanalysis dataset
Presentation transcript:

NOAA Earth System Research Laboratory GEFS reforecasts: a data set suitable for initializing retrospective WRF forecasts Tom Hamill1 and Tom Galarneau2 NOAA ESRL, Physical Sciences Division NCAR, Mesoscale and Microscale Meteorology Division tom.hamill@noaa.gov; tomjr@ucar.edu also: Jeff Whitaker, Gary Bates, Don Murray, Francisco Alvarez, Mike Fiorino, Tom Galarneau

Challenge: realistic LBC’s for WRF Use of reanalysis data rather than global forecast data for LBC’s can result in: Inappropriately small errors in forecast LBC’s, hence results that are unrealistic of real-time applications. Large time interpolation at lateral boundary due to 6-hourly updates common with reanalyses. Possible remedies Nested domains, with very large outer domain. Use a global model forecast data for LBCs…but from where?

Temporal interpolation, 1030 UTC(zoomed in) Forecast, 0900 UTC Forecast, 1200 UTC Example: interpolation errors in Aladin simulation of 1999 Lothar storm temporal interpolation creates two lows from one. Ref: Tudor & Termonia, MWR, July 2010 Forecast, 1030 UTC (zoomed in) Temporal interpolation, 1030 UTC(zoomed in)

Reforecasts (hindcasts) Numerical simulations of the past weather using the same forecast model and assimilation system that is used operationally.

2nd-generation GEFS reforecast: details Past forecasts using NCEP GEFS operational configuration as of February 2012. This version still operational, though data assimilation method was improved in May 2012. Reforecasts produced every day, for 1984120100 to current. Each 00Z, 11-member forecast, 1 control + 10 perturbed. CFSR (NCEP’s Climate Forecast System Reanalysis) initial conditions (3D-Var) + ETR perturbations (cycled with 10 perturbed members). After ~ 22 May 2012, initial conditions from hybrid EnKF/3D-Var. Spatial resolution: T254L42 to day 8, T190L42 from days 7.5 to day 16. Temporal resolution: 3-hourly to +72 h, 6 hourly thereafter. Fast data archive at ESRL of 99 variables, 28 of which stored at original ~1/2-degree resolution during week 1. All stored at 1 degree. Also: mean and spread to be stored. Full model archive at DOE/Lawrence Berkeley Lab, where data set was created under DOE grant.

Status of the reforecast v2 archive. 00Z reforecast data and (since mid-2012) 00Z GEFS real-time forecasts are publicly available from our archive. Download web sites are open to you now: NOAA/ESRL site: fast access, limited data (99 fields). Also there, README & info on how to ftp. http://www.esrl.noaa.gov/psd/forecasts/reforecast2/ US Department of Energy: slow access, but full model states. http://portal.nersc.gov/project/refcst/v2/

Skill of the raw reforecasts

500 hPa Z anomaly correlation (from deterministic control) Lines w/o filled colors for second–generation reforecast (2012, T254) Lines with filled colors for first-generation reforecast (1998, T62). Perhaps a 1.5-2.5 day improvement relative to 1st-generation reforecasts.

Tropical cyclone track errors Less statistical consistency of errors over the period of the reforecasts, as opposed to 500 hPa anomaly correlation, which emphasizes mid-latitude variability.

At this URL, a tape archive of the full forecast model states, suitable for WRF initialization and LBC’s

Some notes running WRF using data from this archive ( from http://www The proper Vtable file must be created prior to preprocessing the GEFS reforecast data. To do this, copy Vtable.GFS to your working directory for preprocessing the GRIB2 GEFS reforecast data. Rename the Vtable.GFS file as Vtable.reforecast, and modify the file as follows. First, add a line for specific humidity on pressure levels and at 2 m. The specifications for specific humidity should be as follows: metgrid Description: Specific Humidity metgrid units: kg kg­1 metgrid Name: SPECHUMD GRIB2 Discp=0, Catgy=1, Param=0, Level=100 GRIB1 Param=52, Level Type=100, From Level1=* metgrid Description: Specific Humidity at 2 m GRIB2 Discp=0, Catgy=1, Param=0, Level=103 GRIB1 Param=52, Level Type=105, From Level1=2 Second, remove the GRIB2 parameter number for relative humidity on pressure levels and at 2m. Note that ungrib.exe and metgrid.exe will calculate relative humidity for you if you have specific humidity. Finally, change the GRIB2 parameter number for PMSL from 1 to 0. No other known modifications to the Vtable are needed. Now that the Vtable.reforecast file is properly created, follow the instructions for running WRF­ARW on the WRF Users’ Page [http://www.mmm.ucar.edu/wrf/users/]. The files downloaded from DOE will have the fields for the different forecast lead times merged into one grib file. It will be your responsibility to break up that into separate grib files for each lead time.

Demo: WRF ARW Regional Reforecast of Hurricane Rita (2005) An example of generating a WRF high-resolution regional reforecast ensemble using GEFS initial and LBCs Will show in this case that regional reforecast WRF ensemble provided value-added guidance to global ensemble forecast.

Details of reforecast with WRF ARW v3 Details of reforecast with WRF ARW v3.4 using GEFS for initial, boundary conditions Nested simulation 36-, 12- and 4-km with 36 vertical levels 12- and 4-km moving nests Time steps: 180, 60, and 20 s Initial and boundary conditions from GFS reforecast ensemble members Tiedtke cumulus scheme on 36 and 12 km; explicit on 4 km YSU PBL scheme HYCOM ocean analysis WSM6 microphysics Noah land surface 2D Smagorinsky turbulence scheme Goddard shortwave radiation RRTM longwave radiation Second order diffusion Positive definite scalar advection Donelan wind-dependent drag formulation Garratt wind-dependent enthalpy surface fluxes outer WRF domain

WRF-ARW reforecast ensemble results Global reforecast ensemble is consistent with NHC forecast; indicating potential impact on Houston Significant left-of-track error and intensity was underestimated Rita vortex intensified in ARW regional reforecast despite terrible initial vortex Similar left-of-track error in ARW; suggests large-scale control on TC motion

Control Maximum reflectivity (dBZ) 50-h ARW Forecast Verifying 02Z/24 Sep ‘05 Control

Control SLP (contours every 4 hPa) 2-m Temperature (shaded in °C) 10-m wind (barbs in knots) 50-h ARW Forecast Verifying 02Z/24 Sep ‘05 Control

Control 10-m wind speed (m/s) 10-m wind (barbs in knots) 50-h ARW Forecast Verifying 02Z/24 Sep ‘05 Control

Ensemble Analysis: 500 hPa Z 24-h ARW Forecast (36-km domain) verifying 0000 UTC 23 Sep 2005 Philippe right members Rita left members 500 hPa Z difference (right minus left; shaded in m), right mean (magenta every 60 m), and left mean (black every 60 m)

Ensemble Analysis: 500 hPa Z 48-h ARW Forecast (36-km domain) verifying 0000 UTC 24 Sep 2005 Philippe right members Rita left members 500 hPa Z difference (right minus left; shaded in m), right mean (magenta every 60 m), and left mean (black every 60 m)

Ensemble Analysis: 500 hPa Z 48-h ARW Forecast (36-km domain) verifying 0000 UTC 24 Sep 2005 Mid-latitude flow pattern more progressive/amplified for right-track members Philippe right members Rita left members 500 hPa Z difference (right minus left; shaded in m), right mean (magenta every 60 m), and left mean (black every 60 m)

Conclusions This new GEFS global reforecast data set may facilitate running retrospective WRF forecasts in a more appropriate manner, with LBC’s from a forecast model, thus more realistic of a real-time configuration. Demonstrated successfully for hurricane Rita. GEFS information readily available, easy to use. An article on the data set and its applications is in press at BAMS, http://journals.ametsoc.org/doi/pdf/10.1175/BAMS-D-12-00014.1

TC Rita (2005) GFS reforecast ensemble 72-h forecast initialized at 00Z 22 Sept P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 P11 OBS 00Z/22 00Z position

TC Rita (2005) ARW ensemble with GFS reforecast ensemble as boundary and initial conditions 72-h forecast initialized at 00Z 22 Sept P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 P11 OBS 00Z/22 00Z position

Data that is readily available on spinning disk from ESRL This is rather coarse vertical resolution for initialization of a regional model, though.

Data that is readily available on spinning disk from ESRL (continued) [Y] indicates that this variable is available at the native ~0.5-degree resolution as well as the 1-degree resolution.

http://esrl.noaa.gov/psd/forecasts/reforecast2/download.html Produces netCDF files. Also: direct ftp access to allow you to download the raw grib files.