The Impacts of GPSRO Data Assimilation and Four Ices Microphysics Scheme on Simulation of heavy rainfall Events over Taiwan during June 2012

Similar documents
COSMIC GPS Radio Occultation and

Impact of FORMOSAT 3/COSMIC Radio Occultation. near Taiwan

Shu-Ya Chen 1, Tae-Kwon Wee 1, Ying-Hwa Kuo 1,2, and David H. Bromwich 3. University Corporation for Atmospheric Research, Boulder, Colorado 2

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

ABSTRACT 3 RADIAL VELOCITY ASSIMILATION IN BJRUC 3.1 ASSIMILATION STRATEGY OF RADIAL

Impact of GPS RO Data on the Prediction of Tropical Cyclones

IMPACT OF ASSIMILATING COSMIC FORECASTS OF SYNOPTIC-SCALE CYCLONES OVER WEST ANTARCTICA

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

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

School of Earth and Environmental Sciences, Seoul National University. Dong-Kyou Lee. Contribution: Dr. Yonhan Choi (UNIST/NCAR) IWTF/ACTS

Numerical Simulation of Torrential Rainfall and Vortical Hot Towers in a Midlatitude Mesoscale Convective System

The GNSS-RO Data Impact on the Typhoon Predictions by MPAS-GSI Model

An improvement of the SBU-YLIN microphysics scheme in squall line simulation

Simulations of Convergence Lines

High Resolution Ensemble Prediction of Typhoon Morakot (2009) May 11, 2011

A WRF-based rapid updating cycling forecast system of. BMB and its performance during the summer and Olympic. Games 2008

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

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

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

Di Wu, Xiquan Dong, Baike Xi, Zhe Feng, Aaron Kennedy, and Gretchen Mullendore. University of North Dakota

Numerical Weather Prediction: Data assimilation. Steven Cavallo

Seoul National University. Ji-Hyun Ha, Gyu-Ho Lim and Dong-Kyou Lee

A New Method for Representing Mixed-phase Particle Fall Speeds in Bulk Microphysics Parameterizations

Ensemble Trajectories and Moisture Quantification for the Hurricane Joaquin (2015) Event

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

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

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

Research Article Numerical Simulations and Analysis of June 16, 2010 Heavy Rainfall Event over Singapore Using the WRFV3 Model

Key Laboratory of Mesoscale Severe Weather, Ministry of Education, School of Atmospheric Sciences, Nanjing University

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

5B.5 Intercomparison of simulations using 4 WRF microphysical schemes with dual-polarization data for a German squall line

The Impact of FORMOSAT-3/ COSMIC Data on Regional Weather Predictions

Sensitivity of tropical cyclone Jal simulations to physics parameterizations

Dynamic Ensemble Model Evaluation of Elevated Thunderstorms sampled by PRECIP

Comparison of Typhoon Track Forecast using Dynamical Initialization Schemeinstalled

THE IMPACT OF GROUND-BASED GPS SLANT-PATH WET DELAY MEASUREMENTS ON SHORT-RANGE PREDICTION OF A PREFRONTAL SQUALL LINE

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

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

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

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

Atmospheric Motion Vectors (AMVs) and their forecasting significance

WRF-RTFDDA Optimization and Wind Farm Data Assimilation

Numerical Simulation of a Severe Thunderstorm over Delhi Using WRF Model

Variable-Resoluiton Global Atmospheric Modeling Spanning Convective to Planetary Scales

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

NUMERICAL SIMULATION OF A BAY OF BENGAL TROPICAL CYCLONE: A COMPARISON OF THE RESULTS FROM EXPERIMENTS WITH JRA-25 AND NCEP REANALYSIS FIELDS


Air Force Weather Ensembles

Heavy Rainfall Event of June 2013

Real case simulations using spectral bin cloud microphysics: Remarks on precedence research and future activity

Application and Evaluation of the Global Weather Research and Forecasting (GWRF) Model

Goddard Space Flight Center

Convective-scale NWP for Singapore

Simulation of the Microphysical Processes and Effect of Latent Heat on a Heavy Rainfall Event in Beijing

Assimilation of GPS Data for Short- Range Precipitation Forecast. C. Rocken, Y.H. Kuo, J. Braun, T. Iwabuchi, S.Y. Ha

MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation using the SWIFT dataset

Low-end derecho of 19 August 2017

A Study of Convective Initiation Failure on 22 Oct 2004

CAPS Storm-Scale Ensemble Forecasting (SSEF) System

Modeling Study of Atmospheric Boundary Layer Characteristics in Industrial City by the Example of Chelyabinsk

Projected change in the East Asian summer monsoon from dynamical downscaling

Four- dimensional climate data sets of the AMMA Special Observing Period #3

Improvement and Ensemble Strategy of Heavy-Rainfall Quantitative Precipitation Forecasts using a Cloud-Resolving Model in Taiwan

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

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

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

Downscaling and Probability

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

Track sensitivity to microphysics and radiation

Blending Analysis with Spatial Filter in TWRF: Application to Typhoon Prediction over the Western North Pacific Ocean

P1.1 BAROCLINICITY INFLUENCES ON STORM DIVERGENCE IN THE SUBTROPICS

Arctic System Reanalysis *

Maximization of Historical Severe Precipitation Events over American, Yuba and Feather River Basins

School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou , China 2

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

The Global Weather Research and Forecasting (GWRF) Model: Model Evaluation, Sensitivity Study, and Future Year Simulation

Impact of different cumulus parameterizations on the numerical simulation of rain over southern China

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

Weather report 28 November 2017 Campinas/SP

EVALUATION OF THE WRF METEOROLOGICAL MODEL RESULTS FOR HIGH OZONE EPISODE IN SW POLAND THE ROLE OF MODEL INITIAL CONDITIONS Wrocław, Poland

Numerical Prediction of Tropical Cyclones (PAGASA Experience)

Lightning Data Assimilation using an Ensemble Kalman Filter

Some Applications of WRF/DART

Sensitivity to Humidity Data Assimilation for Hurricane Intensification and Heavy Rains

Chengsi Liu 1, Ming Xue 1, 2, Youngsun Jung 1, Lianglv Chen 3, Rong Kong 1 and Jingyao Luo 3 ISDA 2019

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

Characteristics of extreme convection over equatorial America and Africa

ture and evolution of the squall line developed over the China Continent. We made data analysis of the three Doppler radar observation during the IFO

WRFDA 2012 Overview. Xiang-Yu Huang. National Center for Atmospheric Research

Developing Applications for Nowcasting Heavy Rainfall over Complex Terrain

The Role of Post Cold Frontal Cumulus Clouds in an Extratropical Cyclone Case Study

Progress in the assimilation of groundbased GPS observations using the MM5. 4DVAR system

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

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

The sensitivity to the microphysical schemes on the skill of forecasting the track and intensity of tropical cyclones using WRF-ARW model

Egyptian Meteorological Authority Cairo Numerical Weather prediction centre

Forecasting Weather: Air Masses and Fronts

New applications using real-time observations and ECMWF model data

CORDEX Simulations for South Asia

Multiscale Analyses of Inland Tropical Cyclone Midlatitude Jet Interactions: Camille (1969) and Danny (1997)

Transcription:

The Impacts of GPSRO Data Assimilation and Four Ices Microphysics Scheme on Simulation of heavy rainfall Events over Taiwan during 10-12 June 2012 Pay-Liam LIN, Y.-J. Chen, B.-Y. Lu, C.-K. WANG, C.-S. CHEN, Y.-L. CHEN C.-Y. Ke, T.-C. Chen Wang and Wei-Kuo TAO Department of Atmospheric Sciences National Central University

Outline Torrential Rainfall Occurred over Taiwan during 12 June 2012 Introduction Model Configuration Experiment Design Results & Discussion

Mesoscale Convective System 3

Introduction Heavy rainfall occurred over northern Taiwan, central Taiwan and southwestern Taiwan on June 12, 2012. Picture from: http://codweb.net/blog/article/760 410553942/

East Asia Study Case 2012/6/11 2000LST EC Analysis Mei-Yu Front L Taiwan Southwesterly Flow

10 11 12 Yangmei Max:123 mm/hr For 10 hours, 30 mm/hr Total:479.5 mm /10hr CWB:15 mm/hr (Heavy Rain) 350mm/24hr (Extremely Torrential Rain) 6

10 11 12 06/11 --- 1200UTC (2000LST) Con. Div. surface 850 mb 300 mb 7

Introduction- Analysis 2012/06/11 00Z 2012/06/11 06Z 2012/06/11 12Z Taiwan 2012/06/11 18Z 2012/06/12 00Z Mei-yu front near Taiwan SW wind prevails over Taiwan

JMA Analysis (850 hpa) 2012/6/12 00UTC Taiwan is over the wet Area (shading: T-Td<3 o C) Taiwan

JMA Analysis (300 hpa) 2012/6/12 00UTC the upper-level trough, which is favorable for the development of heavy rainfall Taiwan

Observation Summary This is a linear MCS along Mei-Yu front that bring more than 400mm of rain in the evening. Favorable environmental conditions for the the system east of short trough low-level convergence upper-level divergence It s difficult to forecast mesoscale systems evolution. 11

Model Configuration WRF V3.5.1 NCEP GFS MP: Goddard GCE scheme CU: Kain-Fritsch scheme (Domain 1 and 2) BL: YSU scheme SF: Unified Noah landsurface model 27/9/3 km

Experiment Design(1) COLD Without data assimilation CTRL Data assimilation(cycling) twice With GTS_GPS GTS_ONLY Cycling four times GTS_GPS Cycling four times GTS_ONLY GTS_GPS 06/10 12Z Goal: 1. Assimilate observational data to Improve rainfall prediction 2. Test GPS impact on rainfall distribution COLD CTRL 06/11 00Z 06/11 00Z 06Z 12Z Use WRF 3DVAR 18Z 06/11 00Z 06Z 12Z

Data Assimilation- data location (06/11 12Z) SYNOP SHIP SATEM BUOY AIREP METAR PILOT GPSREF SOUND

Results-radar reflectivities 2012/06/11 23Z LST COLD GTS_ONLY CTRL GTS_GPS

Accumulated precipitation COLD 06/12 00 06/13 00 LST CTRL GTS_GPS GTS_ONLY

Results- ETS score (ctl1112)ctrl (cold00)cold (fg1112)gts_gps (fo1112)gts_only

Experiment Design(2) CTRL Data assimilation(cycling) twice With GTS_GPS EC FNL GFS DA (GPS+GTS) Cycling four times Use WRF 3DVAR EC FNL GFS 1) 4ice 2) 3ice 1) 4ice 2) 3ice Goal: 1. Impact of DA Cycling Times 2. Test different boundary and initial condition (EC FNL GFS) 3.Test 4ice and 3ice scheme CTRL DA 06/10 12Z 18Z 06/11 00Z 06Z 12Z 06/11 00Z 06Z 12Z

Why do we need to have the 4-ICE scheme? Observation 3ICE-Hail 3ICE-Graupel Almost all microphysics schemes are 3-ICE (cloud ice, snow and graupel). Very few 3ICE schemes have the option to have hail processes (cloud ice, snow, graupel or hail) Both hail and/or graupel can occur in real weather events simultaneously, therefore a 4ICE scheme (cloud ice, snow, graupel and hail) is required for real time forecasts (especially for high-resolution prediction of severe local thunderstorms, midlatitude squall lines and tornadoes) Current and future global high-resolution cloud-resolving models need the ability to predict/simulate a variety of weather systems from weak to intense (i.e., tropical cyclones, thunderstorms) over the globe; this requires the use of a 4ICE scheme 19

Results-accumulated precipitation (EC) 06/12 00 06/13 00 LST CTRL- 3ice DA-3ice CTRL- 4ice DA-4ice mm

Results-max DBZ (EC) CTRL-3ice CTRL-4ice DB Z 2012/06/11 23Z LST DA- 3ice DA-4ice

Results-accumulated precipitation (FNL) 06/12 00 06/13 00 LST CTRL-3ice DA-3ice CTRL-4ice DA-4ice mm

Results-max DBZ (FNL) CTRL-3ice CTRL-4ice DB Z 2012/06/11 23Z LST DA-3ice DA-4ice

Results-accumulated precipitation (GFS) 06/12 00 06/13 00 LST mm CTRL-3ice DA-3ice CTRL-4ice DA-4ice

Results-max DBZ (GFS) CTRL-3ice CTRL-4ice DB Z 012/06/11 23Z LST DA-3ice DA-4ice

Discussion- I.C. B.C. Model starts from 06/11 00 UTC (08LST) 06/12 00 06/13 00 LST rainfall accumulation 3ice_3km_EC 3ice_3km_NCEP GFS Model initialized with EC reanalysis data show better rainfall simulation than the model results initialized with GFS forecast data.

Discussion- I.C. and B.C. Time: 2012/06/11 12 Z Field: RH Diff. (925hPa:left & 850hPa:right) EC - GFS FNL - GFS EC - GFS FNL - GFS

2015.06.11 12 Simulation Domain and initial time setup

Experiment Design GCM: FNL 0.5 vs ERA interim 0.75 Domain: different size and location on d02 Time: 6/10 08:00 vs 6/11 08:00 LST

2015.06.12 Accumulated Precipitation

Conclusion The frontal in the run with bigger domain on d02 can move faster than the run with smaller domain and land on time though the unideal frontal position makes an unideal precipitation pattern. Although the frontal in the run with earlier initial time lands late, the ideal structure of frontal can make an ideal pattern of precipitation.

2015.06.11 12 Simulation Microphysical Scheme

Experiment Design Domain: 9km 3km Landuse update Microphysics 4Ice JP WSM5 WSM6 Radiation Cumulus PBL Land-surface Surface-layer RRTM & Goddard previous Kain-Fritsch YSU Noah Monin-Obukhov Reference from MEFSEA

2015.06.12 Accumulated Precipitation

The experiment design for Mei-Yu case in Hybrid system: period1: 10 June 2012 06Z ~ 11 June 2012 06Z period2: 11 June 2012 06Z ~ 12 June 2012 06Z

Hybrid Day1 (20120610 06Z~0611 06Z)

Hybrid Day2 (20120611 06Z~0612 06Z)

Conclusion Initial conditions (ICs.) and boundary conditions (BCs.) are important for the model prediction. For 12 June 2012 case, EC reanalysis data are better ICs. and BCs. than GFS data resulting in better rainfall prediction. To improve the model run with GFS data as ICs. and BCs., data assimilation (WRF 3DVAR) has applied. With four cycles run, rainfall over northern Taiwan and southwestern Taiwan has improved as compared to COLD START run and CTRL run. Increasing DA times improves precipitation time lag in all simulations and precipitation pattern. With GPS data assimilation could be more realistic to simulate heavy rainfall. IC and BC input will result in different precipitation pattern and value over Taiwan, especially over northern Taiwan.