The Impact of Ice Microphysics on the Genesis of Hurricane Julia (2010) Stefan Cecelski 1 and Dr. Da-Lin Zhang Department of Atmospheric and Oceanic Science.

Slides:



Advertisements
Similar presentations
The Structural Evolution of African Easterly Waves Matthew A. Janiga and Chris Thorncroft DEPARTMENT OF ATMOSPHERIC AND ENVIRONMENTAL SCIENCES University.
Advertisements

Impact of environmental moisture on intensification of Hurricane Earl (2010) Longtao Wu, Hui Su, and Robert Fovell HS3 Science Meeting May 2014.
On the Rapid Intensification of Hurricane Wilma (2005) Hua Chen Committee members: Dr. Da-Lin Zhang (Advisor) Dr. James Carton Dr. Chuan Liu (Dean’s Representative)
Mesoscale Convective Vortices (MCVs) Chris Davis (NCAR ESSL/MMM and RAL) Stan Trier (NCAR ESSL/MMM) Boulder, Colorado 60-h Radar Composite Animation (00.
Hurricanes and climate ATOC 4720 class22. Hurricanes Hurricanes intense rotational storm that develop in regions of very warm SST (typhoons in western.
Hurricane Katrina (2005): Complex Lifecycle of an Intense Tropical Cyclone Eyad Atallah, Ron McTaggart-Cowan, Lance Bosart and John Gyakum.
Genesis of Hurricane Julia (2010) from an African Easterly Wave Stefan Cecelski 1 and Dr. Da-Lin Zhang Department of Atmospheric and Oceanic Science, University.
To perform statistical analyses of observations from dropsondes, microphysical imaging probes, and coordinated NOAA P-3 and NASA ER-2 Doppler radars To.
Probabilistic Verification of Ensemble Forecasts of Tropical Cyclogenesis Sharanya J. Majumdar RSMAS / University of Miami Ryan D. Torn SUNY at Albany.
E. C. Meyers, G. M. McFarquhar, B. F. Jewett, S. W. Nesbitt University of Illinois at Urbana-Champaign 11 May 2010 Vertical Velocity and Microphysical.
Precipitation Over Continental Africa and the East Atlantic: Connections with Synoptic Disturbances Matthew A. Janiga November 8, 2011.
A WRF Simulation of the Genesis of Tropical Storm Eugene (2005) Associated With the ITCZ Breakdowns The UMD/NASA-GSFC Users' and Developers' Workshop,
INTERACTIONS OF MIDDLE LATITUDE TROUGHS AND TROPICAL DISTURBANCES ON 2-4 WEEK TIME SCALES John Molinari and David Vollaro Department of Earth and Atmospheric.
Strong Polar Anticyclone Activity over the Northern Hemisphere and an Examination of the Alaskan Anticyclone Justin E. Jones, Lance F. Bosart, and Daniel.
The Effect of the Terrain on Monsoon Convection in the Himalayan Region Socorro Medina 1, Robert Houze 1, Anil Kumar 2,3 and Dev Niyogi 3 Conference on.
A Case Study of an Outbreak of Twin Tropical Cyclones Carl J. Schreck, III Department of Earth and Atmospheric Sciences University at Albany, SUNY.
Tropical Cyclogenesis Associated with African Easterly Waves THIS TALK 1.Multi-Scale Structure of African Easterly Waves 2.Importance of Guinea Highlands.
TROPICAL CYCLOGENESIS IN ASSOCIATION WITH EQUATORIAL ROSSBY WAVES John Molinari, Kelly Canavan, and David Vollaro Department of Earth and Atmospheric Sciences.
A Case Study of an Outbreak of Twin Tropical Cyclones Carl J. Schreck, III Department of Earth and Atmospheric Sciences University at Albany, SUNY.
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.
Some Preliminary Modeling Results on the Upper-Level Outflow of Hurricane Sandy (2012) JungHoon Shin and Da-Lin Zhang Department of Atmospheric & Oceanic.
Introduction and Methodology Daniel T. Lindsey*, NOAA/NESDIS/STAR/RAMMB Louie Grasso, Cooperative Institute for Research in the Atmosphere
1 26 April 2013 Future WorkResultsMethodologyMotivation Chip HelmsComposite Analyses of Tropical Convective Systems Composite Analyses of Tropical Convective.
Impact of Graupel Parameterization Schemes on Idealized Bow Echo Simulations Rebecca D. Adams-Selin Adams-Selin, R. D., S. C. van den Heever, and R. D.
Chris Birchfield Atmospheric Sciences, Spanish minor.
1 22 July 2013 Future WorkResultsMethodologyMotivation Chip HelmsComposite Analyses of Tropical Convective Systems Composite Analyses of Tropical Convective.
Tropical Cyclone Applications of GOES-R Mark DeMaria and Ray Zehr NESDIS/ORA, Fort Collins, CO John Knaff CIRA/CSU, Fort Collins, CO Applications of Advanced.
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.
USING THE ROSSBY RADIUS OF DEFORMATION AS A FORECASTING TOOL FOR TROPICAL CYCLOGENESIS USING THE ROSSBY RADIUS OF DEFORMATION AS A FORECASTING TOOL FOR.
Benjamin A. Schenkel Lance F. Bosart, and Daniel Keyser University at Albany, State University of New York.
Prediction of Atlantic Tropical Cyclones with the Advanced Hurricane WRF (AHW) Model Jimy Dudhia Wei Wang James Done Chris Davis MMM Division, NCAR Jimy.
In this study, HWRF model simulations for two events were evaluated by analyzing the mean sea level pressure, precipitation, wind fields and hydrometeors.
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.
Benjamin A. Schenkel and Robert E. 4 th WCRP International Conference on Reanalyses Department of Earth, Ocean,
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 6th Northeast.
Impact of global warming on tropical cyclone structure change with a 20-km-mesh high-resolution global model Hiroyuki Murakami (AESTO/MRI, Japan) Akio.
Hurricane Microphysics: Ice vs Water A presenation of papers by Willoughby et al. (1984) and Heymsfield et al. (2005) Derek Ortt April 17, 2007.
27 Sept Future WorkResultsMethodologyMotivation Chip HelmsComposite Analyses of Tropical Convective Systems1 Composite Analyses of Tropical Convective.
High-Resolution Simulation of Hurricane Bonnie (1998). Part II: Water Budget Braun, S. A., 2006: High-Resolution Simulation of Hurricane Bonnie (1998).
USING THE ROSSBY RADIUS OF DEFORMATION AS A FORECASTING TOOL FOR TROPICAL CYCLOGENESIS USING THE ROSSBY RADIUS OF DEFORMATION AS A FORECASTING TOOL FOR.
Towards parametrized GEC current sources for the CESM model FESD project meeting February 2014 Wiebke Deierling, Andreas Baumgaertner, Tina Kalb.
Tropical Transition in the Eastern North Pacific: Sensitivity to Microphysics Alicia M. Bentley ATM May 2012.
Genesis of Hurricane Julia (2010) from an African Easterly Wave Stefan Cecelski 1 and Dr. Da-Lin Zhang Department of Atmospheric and Oceanic Science, University.
Research on the HWRF Model: Intensification and Uncertainties in Model Physics Research on the HWRF Model: Intensification and Uncertainties in Model Physics.
Hurricane Karl’s landfall as seen by high-resolution radar data and WRF Jennifer DeHart and Robert Houze Cyclone Workshop NASA grants: NNX13AG71G.
High-Resolution Simulation of Hurricane Bonnie (1998). Part II: Water Budget SCOTT A. BRAUN J. Atmos. Sci., 63,
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 4 th.
An Investigation of Model-Simulated Band Placement and Evolution in the 25 December 2002 Northeast U.S. Banded Snowstorm David Novak NOAA/ NWS Eastern.
Dynamics and predictability of the rapid intensification of Hurricane Edouard (2014) Erin Munsell Summer 2015 Group Meeting August 17 th, 2015.
African easterly wave dynamics in a full-physics numerical model. Gareth Berry and Chris Thorncroft. University at Albany/SUNY, Albany, NY,USA.
Analysis of Typhoon Tropical Cyclogenesis in an Atmospheric General Circulation Model Suzana J. Camargo and Adam H. Sobel.
Background – Building their Case “continental” – polluted, aerosol laden “maritime” – clean, pristine Polluted concentrations are 1-2 orders of magnitude.
Jennifer Catto Supervisors: Len Shaffrey and Kevin Hodges Extra-tropical cyclones and Storm Tracks.
Identifying amplifying African waves from analysis of their temperature anomalies: how can the NAMMA aircraft, radiosonde and satellite data be merged.
Fuzzy Cluster Analysis Investigating Wavebreaking in the Tropics Philippe P. Papin Team Torn Meeting – April 15, 2015 Department of Atmospheric and Environmental.
Rapid Intensification of Tropical Cyclones by Organized Deep Convection Chanh Q. Kieu, and Da-Lin Zhang Department of Atmospheric and Oceanic Science University.
Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line: Comparison of One- and Two-Moment Schemes.
Shuyi S. Chen, Robert A. Houze Bradley Smull, David Nolan, Wen-Chau Lee Frank Marks, and Robert Rogers Observational and Modeling Study of Hurricane Rainbands.
Using Lightning Data to Monitor the Intensification of Tropical Cyclones in the Eastern North Pacific By: Lesley Leary1, Liz Ritchie1, Nick Demetriades2,
Dynamics and predictability of the rapid intensification of Hurricane Edouard (2014) Erin Munsell Fall 2015 Group Meeting December 11th, 2015.
Simulation of the Arctic Mixed-Phase Clouds
Alan F. Srock and Lance F. Bosart
Water Budget of Typhoon Nari(2001)
The predictability of Tropical Storm Alma 2008
Tong Zhu and Da-Lin Zhang 2006:J. Atmos. Sci.,63,
Tong Zhu and Da-Lin Zhang
A Multiscale Numerical Study of Hurricane Andrew (1992)
Scott A. Braun, 2002: Mon. Wea. Rev.,130,
XIAOLEI ZOU and QINGNONG XIAO J. Atmos. Sci., 57, 報告:黃 小 玲
Xu, H., and X. Li, 2017 J. Geophys. Res. Atmos., 122, 6004–6024
Presentation transcript:

The Impact of Ice Microphysics on the Genesis of Hurricane Julia (2010) Stefan Cecelski 1 and Dr. Da-Lin Zhang Department of Atmospheric and Oceanic Science University of Maryland College Park 1: Research is funded by NASA’s Earth and Space Science Fellowship (NESSF)

Motivation A lack of focus on the impacts of ice microphysics for tropical cyclogenesis (TCG) and related processes – Need to properly represent ice microphysical properties for tropical cyclone (TC) structure and intensity (Ji et. al. 2014) Our previous work investigating the TCG of Hurricane Julia (2010) depicted: – Meaningful ensemble differences for upper tropospheric outflow, warming, and cloud ice content – Warming in the upper troposphere was responsible for meso-α- scale MSLP falls leading to TCG Are the upper-tropospheric dynamical and thermodynamical changes during TCG at all related to ice microphysical processes? 2

Objectives Examine the role of ice microphysics and related heating during the TCG of Julia – Focus on depositional heating since our previous work has shown thermodynamic changes to the upper troposphere during TCG Analyze the changes of deep convection and other parameters pertinent to TCG when ice microphysical processes are modified 3

Hurricane Julia (2010) Background Declared a tropical depression (TD) 0600 UTC 12 Sep 2010 (hereafter 12/0600) – Tropical storm 12 h later at 1800 UTC 12 Sep 2010 Formed within a potent African easterly wave (AEW) Prominent features during TCG: – Pronounced upper-tropospheric warming Hydrostatically induced surface pressure falls on the meso-α-scale – Persistent deep convection within the AEW closed circulation Created a storm-scale outflow in the upper troposphere that expanded warming with time Growth of low-level cyclonic vorticity occurred from the bottom-up with mesovortex merging Right: METEOSAT-9 IR imagery at 1200 UTC 10, 1200 UTC 11, 0600, and 1800 UTC 12 Sep

Methodology Conduct 2 WRF high-resolution sensitivity simulations – Modify the Thompson graupel 2- moment microphysics scheme (Thompson 2004, 2008) used in the control – Compare to the control simulation from Cecelski and Zhang (2013) WRF Details – 3 domains: 9 (D1), 3 (D2), and 1 km (D3 is a moving domain; see right) – 66-h simulation from 0000 UTC 10 to 1800 UTC 12 Sep 2010 – Genesis occurs 54 h into simulation WRF simulation setup. D1, D2, and D3 represent 9, 3, and 1-km horizontal resolution domains, respectively. D3 is a moving domain with initial and final positions drawn. NOAA OI SSTs are shaded (°C). 5

Sensitivity Simulations Experiment 1: “No Fusion” – Removes latent heat of fusion in deposition/sublimation – Thompson scheme definitions for various enthalpies (uses standard values at 0°C): Sublimation (L s ) = 2.834×10 6 J kg -1 Vaporization (L v ) = 2.5×10 6 J kg -1 Fusion (L f ) = 3.34×10 5 J kg -1 – Modification: L s = L v = 2.5×10 6 J kg -1 Still allows for portion of cloud water mass to become cloud ice; Only reduces amount of heating released into the environment by that of L f Experiment 2: “No HFRZ” – Removes any homogeneous freezing of cloud water Occurs with rapid transport of cloud water to upper troposphere via intense convective updrafts – In Thompson scheme, the temperature at which all cloud water must be frozen to become cloud ice is K – Modification: Temperature at which cloud water must turn into cloud ice is changed to K Effectively turns off any homogeneous freezing 6

First-Order Simulation Results Above: Comparison of track and MSLP intensity of experiments (blue and red) with the control (black); Right: Comparison of WRF-derived brightness temperatures (gray shades; K) and composite radar reflectivity (color shades; dBZ) 1800 UTC 11 Sep – first differences Also in extent and intensity of deep convection “No Fusion” has weaker deep convection at time of TCG 7

Upper-tropospheric differences Above: 100 km × 100 km area-averaged temperature difference from 0600 UTC 11 Sep (shaded, °C), absolute vorticity (black contours every 2×10 -5 s -1 ) and cloud ice mixing ratio (blue contours at 2, 5, 10, and 20 ×10 -4 g kg -1. Above: 200 hPa temperatures (shaded, °C) and co- moving wind vectors (reference vector is 10 m s -1 ) with MSLP overlaid (contoured every 1 hPa). Lack of fusion heating during deposition leads to: i)Minimal meso-α-scale upper-tropospheric thermodynamic changes a)Results in no prominent meso-α-scale hydrostatic MSLP falls ii)Weaker and less expansive storm-scale outflow Less warming near storm center in comparison to control Lack of low-level cyclonic vorticity growth versus control Minimal differences between HFRZ and control 8

Convective differences Above: Time-series of 200 km × 200 km area-averaged upper- level Brunt-Vaisala frequency (×10 -3 s -1 ), Rossby radius for deformation (km), composite radar reflectivity (dBZ), and upper-level cloud ice divergence (×10 -5 s -1 ). Right: Count of convective updrafts exceeding various thresholds (m s -1 ) within a 100 km × 100 km area for No Fusion (blue), No HFRZ (right), and the control (black). Weaker and less convective development near storm center in “No Fusion” during TCG Upper-troposphere has greater static stability in “No Fusion” Results in less potent storm- scale upper-level outflow 9 Limits expansion of upper-level warming with time

Conclusions The latent heat of fusion taking place during deposition impacts the TCG of Julia via: – Augmenting the warming of the upper troposphere – Limiting the growth of TD-scale MSLP disturbance – Modifying the strength and spatial extent of deep convection Research Implications – Could properly representing ice microphysics be a critical factor for TCG? – Can we reproduce this characteristic using other microphysics schemes and for other cases? – Are we able to obtain suitable observational data to observe cloud ice and other upper-tropospheric changes? 10