ARW/EnKF performance for the 2009 Hurricane Season

Similar documents
AHW Ensemble Data Assimilation and Forecasting System

2012 AHW Stream 1.5 Retrospective Results

Numerical Weather Prediction: Data assimilation. Steven Cavallo

Assimilate W88D Doppler Vr for Humberto 05

Tropical Cyclone Mesoscale Data Assimilation

Mesoscale Ensemble Data Assimilation: Opportunities and Challenges. Fuqing Zhang Penn State University

Ensemble Kalman Filters for WRF-ARW. Chris Snyder MMM and IMAGe National Center for Atmospheric Research

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

Radiance Data Assimilation with an EnKF

Ensemble Data Assimilation applied to. RAINEX observations of Hurricane Katrina (2005)

COAMPS-TC 2015 Version, Performance, and Future Plans

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

DA/Initialization/Ensemble Development Team Milestones and Priorities

PSU HFIP 2010 Summary: Performance of the ARW-EnKF Real-time Cloud-resolving TC Ensemble Analysis and Forecasting System.

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

The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones

Overview of HFIP FY10 activities and results

Discussion on HFIP RDITT Experiments. Proposal for extending the life of RDITT for one more year: Future Plans from Individual Groups

Ensemble Data Assimilation Applied to RAINEX Observations of Hurricane Katrina (2005)

Objectives for meeting

Some Applications of WRF/DART

The Use of GPS Radio Occultation Data for Tropical Cyclone Prediction. Bill Kuo and Hui Liu UCAR

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

Assimilation of cloud/precipitation data at regional scales

An Overview of COAMPS-TC Development and Real-Time Tests

GFDL Hurricane Model Ensemble Performance During the 2012 Hurricane Season

Retrospective and near real-time tests of GSIbased EnKF-Var hybrid data assimilation system for HWRF with airborne radar data

Tropical Cyclone Formation: Results

Ryan D. Torn Department of Atmospheric & Environmental Sciences June 16, 2013 Earth Science 229

Track sensitivity to microphysics and radiation

NHC Activities, Plans, and Needs

Na#onal Hurricane Center Official Intensity Errors

A pseudo-ensemble hybrid data assimilation system for HWRF

Recent COAMPS-TC Development and Future Plans

Application of Radio Occultation Data in Analyses and Forecasts of Tropical Cyclones Using an Ensemble Assimilation System

The Effects of Sampling Errors on the EnKF Assimilation of Inner-Core Hurricane Observations

2014 real-time COAMPS-TC ensemble prediction

The Impacts of GPS Radio Occultation Data on the Analysis and Prediction of Tropical Cyclones. Bill Kuo, Xingqin Fang, and Hui Liu UCAR COSMIC

Development and research of GSI based hybrid EnKF Var data assimilation for HWRF to improve hurricane prediction

Current and Future Experiments to Improve Assimilation of Surface Winds from Satellites in Global Models

Aircraft Observations of Tropical Cyclones. Robert Rogers NOAA/AOML Hurricane Research Division Miami, FL

Improving Air-Sea Coupling Parameterizations in High-Wind Regimes

Near-surface weather prediction and surface data assimilation: challenges, development, and potential data needs

18A.2 PREDICTION OF ATLANTIC TROPICAL CYCLONES WITH THE ADVANCED HURRICANE WRF (AHW) MODEL

Ensemble Prediction Systems

University of Oklahoma, Norman, Oklahoma. June 6, 2012 Submitted to Weather and Forecasting Revised November 3, 2012

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 25 OCTOBER 8, 2014

Structure & Intensity Change: Future Directions IWTC VI, Topic 1

Impact of Assimilating Aircraft Reconnaissance Observations in Operational HWRF

Developmental Testbed Center (DTC) Project for the Hurricane Forecast Improvement Program (HFIP)

Mesoscale Predictability of Terrain Induced Flows

Post Processing of Hurricane Model Forecasts

Tropical Cyclone Modeling and Data Assimilation. Jason Sippel NOAA AOML/HRD 2018 WMO Workshop at NHC

SIXTH INTERNATIONAL WORKSHOP on TROPICAL CYCLONES. Working Group: Phillipe Caroff, Jeff Callaghan, James Franklin, Mark DeMaria

IMPACT OF GROUND-BASED GPS PRECIPITABLE WATER VAPOR AND COSMIC GPS REFRACTIVITY PROFILE ON HURRICANE DEAN FORECAST. (a) (b) (c)

Convection-Resolving NWP with WRF. Section coordinator Ming Xue University of Oklahoma

OPERATIONAL CONSIDERATIONS FOR HURRICANE MODEL DIAGNOSTICS / VERIFICATION

Motivation & Goal. We investigate a way to generate PDFs from a single deterministic run

Precipitation Structure and Processes of Typhoon Nari (2001): A Modeling Propsective

Convective-scale data assimilation in the Weather Research and Forecasting model using a nonlinear ensemble filter

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

Tropical Cyclone Intensity and Structure Changes in relation to Tropical Cyclone Outflow

Typhoon Relocation in CWB WRF

Predictability and Genesis of Hurricane Karl (2010) Examined through the EnKF Assimilation of Field Observations Collected during PREDICT

Have a better understanding of the Tropical Cyclone Products generated at ECMWF

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 4-17, 2015

Lectures on Tropical Cyclones

University of Miami/RSMAS

Tropical Storm List

T PARC: Impact of dropsonde (and other) aircraft data

Deterministic and Ensemble Storm scale Lightning Data Assimilation

Hurricane Structure: Theory and Application. John Cangialosi National Hurricane Center

Fernando Prates. Evaluation Section. Slide 1

Lightning Data Assimilation using an Ensemble Kalman Filter

Improved Tropical Cyclone Boundary Layer Wind Retrievals. From Airborne Doppler Radar

Tropical cyclone simulations and predictions with GFDL s prototype global cloud resolving model

Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Comparison of Convection-permitting and Convection-parameterizing Ensembles

Advanced Research WRF High Resolution Simulations of Hurricanes Katrina, Rita and Wilma (2005)

Convection-permitting Ensemble Data Assimilation of Doppler Radar Observations for Hurricane Prediction

Flow and Regime Dependent Mesoscale Predictability

Atmosphere-Ocean Interaction in Tropical Cyclones

Predicting Typhoon Morakot s Catastrophic Rainfall with a Convection-Permitting Mesoscale Ensemble System

Coupled Wind, Wave, and Surge Modeling. Pat Welsh University of North Florida 10th International Wave Conference 12 November 2007

Exploring the Use of Dynamical Weather and Climate Models for Risk Assessment

April Forecast Update for North Atlantic Hurricane Activity in 2019

Applications Development and Diagnostics (ADD) Team Summary Part 2

DISTRIBUTION STATEMENT A: Distribution approved for public release; distribution is unlimited.

Hurricane Structure: Theory and Diagnosis

The EMC Mission.. In response to operational requirements:

Performance and Verification of HWRF/HMON Ensemble Prediction System in 2017 Real time Parallel Experiment. Zhan Zhang, Weiguo Wang

Initialization of Tropical Cyclone Structure for Operational Application

NHC Ensemble/Probabilistic Guidance Products

Transitioning Physics Advancements into the Operational Hurricane WRF Model

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 AUGUST 30, 2012

- Introduction - Technical Presentation 49 th Session of the Typhoon Committee. Yokohama, Japan 21 February Munehiko Yamaguchi

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 1 SEPTEMBER 14, 2015

Unmanned Aircraft Hurricane Reconnaissance. Pat Fitzpatrick GeoSystems Research Institute Mississippi State University Stennis Space Center branch

AMERICAN METEOROLOGICAL SOCIETY

Hybrid Variational Ensemble Data Assimilation for Tropical Cyclone

Transcription:

ARW/EnKF performance for the 2009 Hurricane Season Ryan D. Torn, Univ. at Albany, SUNY Chris Davis, Steven Cavallo, Chris Snyder, Wei Wang, James Done, NCAR/MMM 4 th EnKF Workshop 8 April 2010, Rensselaerville, NY

Background Models need high spatial resolution to resolve important features within TC such as eyewall, rainbands, etc. Initializing from bogus vortex can be problematic:

Vertical Motion Distribution Time + 1 hour Time + 5 hour Even with the finer-resolution GFDL initial condition, significant adjustment of the vortex occurred within the first 12 h. This shortcoming strongly supports the need for a data assimilation and initialization procedure that is specific to the AHW. - Davis et al. 2008 (WAF)

Background Torn and Hakim (2009) MWR

Overview NCAR was asked to participate in NOAA Hurricane Forecast Improvement Project (HFIP) multi-model ensemble. Required running realtime forecasts during 2009 Atlantic season Wanted initial conditions that: Have a good estimate of environment Have a decent estimate of TC structure Does not lead to initialization problem Provides a good opportunity to evaluate ensemble data assimilation systems over variety of storms

Assimilation System WRF ARW (v3.1), 36 km horizontal resolution, 96 ensemble members, DART assimilation system. Observations assimilated each six hours from surface and marine stations (P sfc ), rawinsondes, synoptic dropsondes, ACARS, sat. winds, TC advisory position and minimum SLP Initialized system at 0000 UTC 10 August. System cycled continuously beyond that point (through 10 November)

Assimilation System Cont. Anderson adaptive inflation (inflation computed from innovation statistics and correlations) Adaptive localization, where radius is reduced from 2000 km when number of observations greater than 1600 within 2000 km of observation location Fixed Covariance boundary perturbations Initial condition for high-resolution forecast chosen by minimizing:

2009 Storms

Verification Verify analysis and 6 hour forecasts against best track TC position and intensity Not the same as assimilated TC position and intensity Relationship between best track and advisory akin to analysis and background forecast

Cycling Errors

Bias RMS Error Cycling Error

Wind Radii Wind Radii not often discussed, but very important aspect of TC These distances determine: region of wind damage area over which fluxes occur wind driven stresses for storm surge models Davis et al. 2010

Bias RMS Error 34 Knot Wind Radii

High-Resolution Forecast

Tropical Storm Erika

Erika Forecast

Wind Cross Section

Summary & Conclusions Initial conditions from an EnKF system lead to reduced spin-up problems compared to bogus schemes Used this approach to generate coarse ICs for highresolution forecasts during 2009 season Analysis has larger position errors, similar intensity errors and lower TC size errors compared to operational TC models. High-resolution forecasts benefit from EnKF ICs during highly-sheared storms, stems from having tilted initial vortex and explicit convection Several planned improvements for upcoming season including higher resolution and treatment for pre-genesis systems

PREDICT PREDICT: PRE-Depression Investigation of Cloud-systems in the Tropics 15 August 30 Sept. 2010 Base: St. Croix Virgin Islands NCAR G-V: 200 research hours 10+ disturbances sampled, 25 flights 550 dropsondes Microwave Temperature Profiler Differential GPS (geopotential height on p-sfc) Small Ice Detector Cloud Particle Imager CVI Cloud radar Courtesy: Chris Davis, NCAR