P.1 QPF verif scores for NCEP and International Models ● 2013 ETS/bias scores for 00-24h and 24-48h forecasts (the two forecast ranges that all datasets.

Slides:



Advertisements
Similar presentations
Adaptive Estimation and Tuning of Satellite Observation Error in Assimilation Cycle with GRAPES Hua ZHANG, Dehui CHEN, Xueshun SHEN, Jishan XUE, Wei HAN.
Advertisements

1 NCEP Operational Regional Hurricane Modeling Strategy for 2014 and beyond Environmental Modeling Center, NCEP/NOAA/NWS, NCWCP, College Park, MD National.
The THORPEX Interactive Grand Global Ensemble (TIGGE) Richard Swinbank, Zoltan Toth and Philippe Bougeault, with thanks to the GIFS-TIGGE working group.
Storm Prediction Center Highlights NCEP Production Suite Review December 3, 2013 Steven Weiss, Israel Jirak, Chris Melick, Andy Dean, Patrick Marsh, and.
Hybrid variational-ensemble data assimilation for the NCEP GFS Tom Hamill, for Jeff Whitaker NOAA Earth System Research Lab, Boulder, CO, USA
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Upcoming Changes in Winter Weather Operations at the Weather Prediction Center (WPC) Great Lakes Operational Meteorological Workshop Dan Petersen, Wallace.
1 00/XXXX © Crown copyright Use of radar data in modelling at the Met Office (UK) Bruce Macpherson Mesoscale Assimilation, NWP Met Office EWGLAM / COST-717.
Transitioning unique NASA data and research technologies to the NWS 1 Radiance Assimilation Activities at SPoRT Will McCarty SPoRT SAC Wednesday June 13,
The 2014 Warn-on-Forecast and High-Impact Weather Workshop
Eidgenössisches Departement des Innern EDI Bundesamt für Meteorologie und Klimatologie MeteoSchweiz Institut für Physik der Atmosphäre On the Value of.
Convection-permitting forecasts initialized with continuously-cycling limited-area 3DVAR, EnKF and “hybrid” data assimilation systems Craig Schwartz and.
National Centers for Environmental Prediction (NCEP) Hydrometeorlogical Prediction Center (HPC) Forecast Operations Branch Winter Weather Desk Dan Petersen.
Brian Ancell, Cliff Mass, Gregory J. Hakim University of Washington
Huang et al: MTG-IRS OSSEMMT, June MTG-IRS OSSE on regional scales Xiang-Yu Huang, Hongli Wang, Yongsheng Chen and Xin Zhang National Center.
GFS (left), ECMWF (right) 500 mb Height, Winds, and Temp 00 hr forecast valid 12z 24 Dec 2010.
IS WRF REALLY IMPROVING? A COMPREHENSIVE VERIFICATION OVER THE PACIFIC NORTHWEST Cliff Mass and David Ovens University of Washington.
Presented by: Mark Iredell based on work done by Global Climate and Weather Modeling Branch 2014 NCEP Production Suite Review GLOBAL MODELING 1.
Global Forecast System (GFS) Model Previous called the Aviation (AVN) and Medium Range Forecast (MRF) models. Global model and 64 levels Relatively primitive.
Operational Drought Information System Kingtse Mo Climate Prediction Center NCEP/ NWS/NOAA Operation--- real time, on time and all the time 1.
UMAC data callpage 1 of 16Global Ensemble Forecast System - GEFS Global Ensemble Forecast System Yuejian Zhu Ensemble Team Leader, Environmental Modeling.
Jamie Wolff Jeff Beck, Laurie Carson, Michelle Harrold, Tracy Hertneky 15 April 2015 Assessment of two microphysics schemes in the NOAA Environmental Modeling.
Evaluation of Potential Impacts of Doppler Lidar Wind Measurements on High-impact Weather Forecasting: A Regional OSSE Study Zhaoxia Pu and Lei Zhang University.
Warn on Forecast Briefing September 2014 Warn on Forecast Brief for NCEP planning NSSL and GSD September 2014.
Development of an Hourly- Updated NAM Forecast System: Current Efforts and Future Plans Jacob Carley ab, Eric Rogers b, Shun Liu ab, Xiaoyan Zhang bc,
Forecast Skill and Major Forecast Failures over the Northeastern Pacific and Western North America Lynn McMurdie and Cliff Mass University of Washington.
Fly - Fight - Win 16 th Weather Squadron Evan Kuchera Fine Scale Models and Ensemble 16WS/WXN Template: 28 Feb 06 Air Force Weather Ensembles.
ATM 401/501 Status of Forecasting: Spring Forecasting at NCEP Environmental Modeling Center Ocean Prediction Center.
1 Soil Moisture Assimilation in NCEP Global Forecast System Weizhong Zheng 1, Jerry Zhan 2, Jiarui Dong 1, Michael Ek 1 1 Environmental Modeling Center,
Data assimilation and observing systems strategies Pierre Gauthier Data Assimilation and Satellite Meteorology Division Meteorological Service of Canada.
AMB Verification and Quality Control monitoring Efforts involving RAOB, Profiler, Mesonets, Aircraft Bill Moninger, Xue Wei, Susan Sahm, Brian Jamison.
1 Rolf Langland Naval Research Laboratory – Monterey, CA Uncertainty in Operational Atmospheric Analyses.
Modification of GFS Land Surface Model Parameters to Mitigate the Near- Surface Cold and Wet Bias in the Midwest CONUS: Analysis of Parallel Test Results.
P1.85 DEVELOPMENT OF SIMULATED GOES PRODUCTS FOR GFS AND NAM Hui-Ya Chuang and Brad Ferrier Environmental Modeling Center, NCEP, Washington DC Introduction.
Verification of Global Ensemble Forecasts Fanglin Yang Yuejian Zhu, Glenn White, John Derber Environmental Modeling Center National Centers for Environmental.
Short-Range Ensemble Prediction System at INM José A. García-Moya SMNT – INM 27th EWGLAM & 12th SRNWP Meetings Ljubljana, October 2005.
LAPS / STMAS Verification Activities Steve Albers, Isidora Jankov ESRL / GSD Verification Summit September 2011 Updated Sep 7, 2011.
Interoperability at INM Experience with the SREPS system J. A. García-Moya NWP – Spanish Met Service INM SRNWP Interoperability Workshop ECMWF –
1 Results from Winter Storm Reconnaissance Program 2008 Yucheng SongIMSG/EMC/NCEP Zoltan TothEMC/NCEP/NWS Sharan MajumdarUniv. of Miami Mark ShirleyNCO/NCEP/NWS.
Stage IV Multi-sensor Mosaic Development, production and Application at NCEP/EMC Ying Lin NOAA/NWS/NCEP/EMC Jan 2011.
2006(-07)TAMDAR aircraft impact experiments for RUC humidity, temperature and wind forecasts Stan Benjamin, Bill Moninger, Tracy Lorraine Smith, Brian.
Hurricane Forecast Improvement Project (HFIP): Where do we stand after 3 years? Bob Gall – HFIP Development Manager Fred Toepfer—HFIP Project manager Frank.
Evaluation of impact of satellite radiance data within the hybrid variational/EnKF Rapid Refresh data assimilation system Haidao Lin Steve Weygandt Ming.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Are Numerical Weather Prediction Models Getting Better? Cliff Mass, David Ovens, and Jeff Baars University of Washington.
Page 1© Crown copyright 2004 SRNWP Lead Centre Report on Data Assimilation 2005 for EWGLAM/SRNWP Annual Meeting October 2005, Ljubljana, Slovenia.
Three real case simulations by Meso-NH validated against satellite observations J.-P. Chaboureau and J.-P. Pinty Laboratoire d’Aérologie, Toulouse 1.Elbe.
Munehiko Yamaguchi, Sharanya J. Majumdar (RSMAS/U. Miami) and multiple collaborators 3 rd THORPEX International Science Symposium 14 Sep Coordinated.
MMET Team Michelle Harrold Tracy Hertneky Jamie Wolff Demonstrating the utility of the Mesoscale Model Evaluation Testbed (MMET)
Yuqing Wang Department of Meteorology, University of Hawaii The 65 th IHC, February 28-March 3, 2011.
Verification of ensemble precipitation forecasts using the TIGGE dataset Laurence J. Wilson Environment Canada Anna Ghelli ECMWF GIFS-TIGGE Meeting, Feb.
Module 17 MM5: Climate Simulation BREAK. Regional Climate Simulation for the Pan-Arctic using MM5 William J. Gutowski, Jr., Helin Wei, Charles Vörösmarty,
1 INM’s contribution to ELDAS project E. Rodríguez and B. Navascués INM.
MOS and Evolving NWP Models Developer’s Dilemma: Frequent changes to NWP models… Make need for reliable statistical guidance more critical Helps forecasters.
MPO 674 Lecture 2 1/20/15. Timeline (continued from Class 1) 1960s: Lorenz papers: finite limit of predictability? 1966: First primitive equations model.
Vincent N. Sakwa RSMC, Nairobi
10th COSMO General Meeting, Cracow, Poland Verification of COSMOGR Over Greece 10 th COSMO General Meeting Cracow, Poland.
Overview of SPC Efforts in Objective Verification of Convection-Allowing Models and Ensembles Israel Jirak, Chris Melick, Patrick Marsh, Andy Dean and.
Variability of Arctic Cloudiness from Satellite and Surface Data Sets University of Washington Applied Physics Laboratory Polar Science Center Axel J.
OSEs with HIRLAM and HARMONIE for EUCOS Nils Gustafsson, SMHI Sigurdur Thorsteinsson, IMO John de Vries, KNMI Roger Randriamampianina, met.no.
Notes for Interpretation
Xuexing Qiu and Fuqing Dec. 2014
Tadashi Fujita (NPD JMA)
Update on the Northwest Regional Modeling System 2013
Global Forecast System (GFS) Model
AGREPS – ACCESS Global and Regional Ensemble Prediction System
MODIS Polar Winds Forecast Impact (3DVAR) Northern Hemisphere
Global Forecast System (GFS) Model
Observational Data Source Impacts In The NCEP GDAS
Status of the Regional OSSE for Space-Based LIDAR Winds – Feb01
Presentation transcript:

P.1 QPF verif scores for NCEP and International Models ● 2013 ETS/bias scores for 00-24h and 24-48h forecasts (the two forecast ranges that all datasets have in common) verified over ConUS. ● Models being verified are NCEP's NAM and GFS; Canadian global and regional (CMCGLB/CMC); DWD, ECMWF, JMA, Meteo France (METFR), UKMO. For ease of viewing, the 9 models are divided into two groups, with GFS in common in both (P2) ● Upcoming NAM upgrade: summary of changes/upper-air verif stats (P3, from Eric Rogers); ETS/bias for 2013; quarterly time series comparisons (p4); NAM/NAMX FSS comparisons (p5) ● NAM and GFS quarterly FSS time series, (P6-7) Courtesy Ying Lin, NCEP/EMC

P.2 QPF Skill Scores over ConUS, Jan – Dec 2013, 1 &2 day fcsts Eq. Threat Bias GFS,NAM,CMCGLB,CMC,JMA GFS,DWD,ECMWF,METFR,UKMO 1.0

P.3 NAM vs. NAMX (para) 1/2/3 day forecasts, 23 Apr – 30 Sept 2012 Physics modifications: ● GWD/mountain-blocking; more responsive to subgrid-scale terrain variability ● BMJ convection: moister convective profiles, convection triggers less, increase 12km bias ● RRTM radiation, latest version ● Ferrier-Aligo microphysics, tuned to improve severe storm prediction ● Improved snow depth algorithm in LSM Changes planned for NAM implementation in Spring 2014 Vector Wind RMS (m/s) 12km CONUS 1 Oct 2013 – 15 Jan 2014 Data assimilation modifications: ● Hybrid variational-ensemble analysis with global EnKF ● New satellite bias correction algorithm (same as in FY14 global upgrade) ● Cloud/radar assimilation in NDAS Ops Parallel Day 1 = Black Day 2 = Red Day 3 = Blue

P.4 NAM vs. NAMX (para) 1/2/3 day forecasts, 23 Apr – 30 Sept 2012 NAM vs. NAMX (para) 1/2/3 day forecasts, Jan – Dec 2013 NAM, NAMX(dashed line) 24,48,72h forecasts, ETS at 0.25”/day Apr 2012 NAMX: on-going NAM parallel experiment ETS Bias

P.5 NAM, NAMX h FSS, 23 Sep Feb mm/day 10mm/day 25mm/day 50mm/day 5km 300km

P.6 NAM 24,48,72h FSS at 62km scale, mm/day 10mm/day 25mm/day50mm/day

P.7 GFS 24,48,72h FSS at 62km scale, mm/day 10mm/day 25mm/day50mm/day