Kinematic, Microphysical, and Precipitation Characteristics of MCSs in TRMM-LBA Robert Cifelli, Walter Petersen, Lawrence Carey, and Steven A. Rutledge.

Slides:



Advertisements
Similar presentations
POLARIMETRIC RADAR IMPROVEMENTS
Advertisements

Characteristics of Convection in an African Easterly Wave Observed During NAMMA Robert Cifelli, Timothy Lang, Steven A. Rutledge Colorado State University.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State.
Clear air echoes (few small insects) -12 dBZ. Echoes in clear air from insects Common is summer. Watch for echoes to expand area as sun sets and insects.
To perform statistical analyses of observations from dropsondes, microphysical imaging probes, and coordinated NOAA P-3 and NASA ER-2 Doppler radars To.
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.
Precipitation Over Continental Africa and the East Atlantic: Connections with Synoptic Disturbances Matthew A. Janiga November 8, 2011.
STEPS Severe Thunderstorm Electrification and Precipitation Study May-July 2000 S. Rutledge, S. Tessendorf, K. Wiens, T. Lang, J. Miller # Department of.
February 5th, TRMM Conference The 3-D Reflectivity Structure of Intense Atlantic Hurricanes as seen by the TRMM PR Deanna Hence, Robert Houze.
Radar signatures in complex terrain during the passage of mid-latitude cyclones Socorro Medina Department of Atmospheric Sciences University of Washington.
Deanna Hence, Stacy Brodzik and Robert Houze University of Washington Introduction Methodology TCSP Storms RAINEX Storms Combined TCSP + RAINEX Storms.
Continuing research on radar-observed precipitation systems during NAME 2004 Timothy J. Lang, Stephen W. Nesbitt, Steven A. Rutledge, Robert Cifelli, David.
Cirrus Production by a Mesoscale Convective System Sampled During TWP-ICE: Analysis via Water Budget Equations Jasmine Cetrone and Robert Houze University.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar by S. A. Rutledge, R. Cifelli, T. Lang and S. W. Nesbitt EGU 2009.
Hydrometeors Injected into the Large-scale Environment by Tropical Cloud Systems Robert A. Houze & Courtney Schumacher Co-PIs ARM Science Team Meeting,
Schumacher and Houze (2006) This Lecture: Review of Schumacher and Houze, 2006: Stratiform precipitation over sub- Saharan Africa and the Tropical.
1 Radar Displays PPI - Plan position Indicator Maps the received signals on polar coordinates in plan view. The antenna scans 360° at fixed elevation angle.
Relationship of Cloud Water Budgets to Heating Profile Calculations Austin and Houze 1973 Houze et al Houze 1982 Relationship of Cloud Water Budgets.
NASA N-Pol data collection in MC3E and…. S. A. Rutledge, B. Dolan, N. Guy, T. Lang, P. Kennedy, J. Gerlach, D. Wolff and W. Petersen November 2011 PMM.
Cirrus Production by Tropical Mesoscale Convective Systems Jasmine Cetrone and Robert Houze 8 February 2008.
Mesoscale Convective Systems Robert Houze Department of Atmospheric Sciences University of Washington Nebraska Kansas Oklahoma Arkansas.
Cirrus Production by Tropical Mesoscale Convective Systems Jasmine Cetrone and Robert Houze University of Washington Motivation Atmospheric heating by.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State.
TRMM Observations of Convection over the Himalayan Region R. A. Houze and D. C. Wilton University of Washington Presented 1 February 2005 at the International.
Mesoscale Convective System Heating and Momentum Feedbacks R. Houze NCAR 10 July 2006.
Characteristics of Isolated Convective Storms Meteorology 515/815 Spring 2006 Christopher Meherin.
Orographic triggering and mesoscale organization of extreme storms in subtropical South America Kristen Lani Rasmussen Robert A. Houze, Jr. ICAM 2013,
ON THE RESPONSE OF HAILSTORMS TO ENHANCED CCN CONCENTRATIONS William R. Cotton Department of Atmospheric Science, Colorado State University.
Some Preliminary Modeling Results on the Upper-Level Outflow of Hurricane Sandy (2012) JungHoon Shin and Da-Lin Zhang Department of Atmospheric & Oceanic.
On the relationship of in-cloud convective turbulence and total lightning Wiebke Deierling, John Williams, Sarah Al-Momar, Bob Sharman, Matthias Steiner.
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.
Scott W. Powell and Stacy R. Brodzik University of Washington, Seattle, WA An Improved Algorithm for Radar-derived Classification of Convective and Stratiform.
Using NPOL (the NASA S-band polarimetric radar), and a network of 2D video disdrometers for external radar calibration and rain rate estimation, and to.
Operational Forecasting of Turbulence in Radial Bands around Mesoscale Convective Systems (MCS’s) 06 August 2013 Midwest US Melissa Thomas, Lead & Training.
A Further Look at Q 1 and Q 2 from TOGA COARE* Richard H. Johnson Paul E. Ciesielski Colorado State University Thomas M. Rickenbach East Carolina University.
In this study, HWRF model simulations for two events were evaluated by analyzing the mean sea level pressure, precipitation, wind fields and hydrometeors.
The Role of Polarimetric Radar for Validating Cloud Models Robert Cifelli 1, Timothy Lang 1, Stephen Nesbitt 1, S.A. Rutledge 1 S. Lang 2, and W.K. Tao.
A Conceptual Model for the Hydrometeor Structure of Mesoscale Convective Systems during the MJO Active Stage Hannah C. Barnes Robert A. Houze, Jr. University.
Hyperspectral Data Applications: Convection & Turbulence Overview: Application Research for MURI Atmospheric Boundary Layer Turbulence Convective Initiation.
Monthly Precipitation Rate in July 2006 TRMM MMF DIFF RH84 New Scheme 3.3 Evaluate MMF Results with TRMM Data Zonal Mean Hydrometeor Profile TRMM TMI CONTROL.
High-Resolution Simulation of Hurricane Bonnie (1998). Part II: Water Budget Braun, S. A., 2006: High-Resolution Simulation of Hurricane Bonnie (1998).
Relationships between Lightning and Radar Parameters in the Mid-Atlantic Region Scott D. Rudlosky Cooperative Institute of Climate and Satellites University.
Polarimetric radar analysis of convection in northwestern Mexico Timothy J. Lang, Angela Rowe, Steve Rutledge, Rob Cifelli Steve Nesbitt.
2nd International GPM GV Workshop Taipei, Taiwan, September 27-29, 2005 Characteristics of Convective Systems Observed During TRMM-LBA Rob Cifelli, Steve.
Boundary-layer turbulence, surface processes, and orographic precipitation growth in cold clouds or: The importance of the lower boundary Qun Miao Ningbo.
Why is it important to HS3 science to estimate convective vertical velocity accurately? Ed Zipser and Jon Zawislak Dept. of Atmospheric Sciences University.
A Global Rainfall Validation Strategy Wesley Berg, Christian Kummerow, and Tristan L’Ecuyer Colorado State University.
Sensitivity of Squall-Line Rear Inflow to Ice Microphysics and Environmental Humidity Ming-Jen Yang and Robert A. House Jr. Mon. Wea. Rev., 123,
Towards a Characterization of Arctic Mixed-Phase Clouds Matthew D. Shupe a, Pavlos Kollias b, Ed Luke b a Cooperative Institute for Research in Environmental.
High-Resolution Simulation of Hurricane Bonnie (1998). Part II: Water Budget SCOTT A. BRAUN J. Atmos. Sci., 63,
Modelling and observations of droplet growth in clouds A Coals 1, A M Blyth 1, J-L Brenguier 2, A M Gadian 1 and W W Grabowski 3 Understanding the detailed.
Stratiform Precipitation Fred Carr COMAP NWP Symposium Monday, 13 December 1999.
Dual-pol obs in NW Environment B. Dolan and S. Rutledge OLYMPEX planning meeting Seattle, 22 January 2015.
A new look at – Tropical Mid-Troposphere Clouds P. Zuidema, B. Mapes, J. Lin, C. Fairall P. Zuidema, B. Mapes, J. Lin, C. Fairall CIRES/CDC NOAA/ETL Boulder,
Horizontal Variability In Microphysical Properties of Mixed-Phase Arctic Clouds David Brown, Michael Poellot – University of North Dakota Clouds are strong.
Cheng-Zhong Zhang and Hiroshi Uyeda Hydroshperic Atmospheric Research Center, Nagoya University 1 November 2006 in Boulder, Colorado Possible Mechanism.
High-Resolution Polarimetric Radar Observation of Snow- Generating Cells Karly Reimel May 10, 2016.
Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line: Comparison of One- and Two-Moment Schemes.
Observations of Specific Differential Phase, KDP Chris Collier Acknowledgements: Lindsay Bennett, Alan Blyth and David Dufton.
Statistical Analysis of S-Pol Polarimetric Radar Data from NAME 2004 Timothy J. Lang, Robert Cifelli, Steven A. Rutledge, Angela Rowe, and Lee Nelson Colorado.
Reflections on Radar Observations of Mesoscale Precipitation
MM5- and WRF-Simulated Cloud and Moisture Fields
By SANDRA E. YUTER and ROBERT A. HOUZE JR
Polarimetric radar analysis of convection in the complex topography
Polarimetric radar analysis of convection in northwestern Mexico
Application of radar observations to the evaluation and improvement of cloud permitting regional model simulations of MJO Samson M. Hagos, Zhe Feng, Kiranmayi.
Tong Zhu and Da-Lin Zhang 2006:J. Atmos. Sci.,63,
Dual-Aircraft Investigation of the Inner Core of Hurricane Nobert
Scott A. Braun, 2002: Mon. Wea. Rev.,130,
Xu, H., and X. Li, 2017 J. Geophys. Res. Atmos., 122, 6004–6024
Presentation transcript:

Kinematic, Microphysical, and Precipitation Characteristics of MCSs in TRMM-LBA Robert Cifelli, Walter Petersen, Lawrence Carey, and Steven A. Rutledge Department of Atmospheric Science Colorado State University Overview This study uses dual-Doppler and S-band polarimetric radar data to examine differences in the vertical structure of convection that were observed during TRMM-LBA. Two MCSs, occurring in distinct meteorological regimes (see Fig. 3 in Petersen et al. poster), were chosen for analysis. The first MCS occurred on 26 January 1999 in low-level easterly flow as a squall line with an intense leading line of convection and a trailing region of decaying convection and stratiform precipitation. In contrast, the second MCS event, 25 February 1999, occurred in low-level westerly flow. This system exhibited little apparent organization and was best characterized as widespread stratiform precipitation with embedded convection. This poster presents results showing significant differences between these MCSs in terms of kinematic and microphysical characteristics. Figure 4. Same as Fig. 3 except for water content. Ice (gm m -3 - thin solid lines), liquid (gm m -3 - color contours), mass weighted mean drop diameter (mm - heavy solid lines) Active mixed phase microphysics Copious ice in mid-upper troposphere Paucity of ice in mid-upper troposphere Water Content EasterlyWesterly Individual CAPPI’s and Cross Sections Composite Analysis Summary The two MCSs in this study, representing distinct meteorological regimes, have significant differences in terms of vertical structure characteristics. The easterly event was more intense in terms of overall reflectivity and kinematic structure (Figs. 6 and 7). The MCSs were sampled in similar lifecycle stages based on low-level reflectivity characteristics (Fig. 5) but displayed pronounced differences in terms of kinematic evolution (Fig. 10). Polarimetric data indicated large differences in the vertical distribution of hydrometeors. The easterly MCS showed evidence of a robust mixed phase region and large amounts of ice above 6 km that was largely absent in the westerly case (Figs. 3, 4, and 8). These observations can be used for validation of TRMM alogorithms and numerical models which utilize information on hydrometeor vertical structure to estimate latent heating (Tao et al. 1993; Olson et al. 1999). Method 2.5 (3.0) hours of continuous dual-Doppler and polarimetric radar data analyzed for the easterly (westerly) MCS at 10 minute resolution. Radar data partitioned into convective and non-convective components using reflectivity texture algorithm similar to Rickenbach and Rutledge (1998). Water contents and mean drop diameters calculated following methods of Carey and Rutledge (2000). Rainfall calculated over a 40,000 km 2 grid using optimization procedure among S-Pol Z H, Z DR, and K DP, similar to Chandrasekar et al. (1993) and Petersen et al. (1999). See Carey et al. handout for details. Acknowledgements This work is supported by the NASA TRMM Program TRMM-LBA Instrumentation Figure 1. Location of instrument platforms deployed during TRMM-LBA. NCAR S-Pol and NASA TOGA (C-band) radars used for analyses Dual-Doppler baseline ~ 60 km Radar data interpolated onto a km 2 cartesian grid Citation Flight Track Cross Section EasterlyWesterly Examples of Convective Organization Squall line with trailing stratiform and decaying convection Originated as outflow from previous convection Widespread stratiform with embedded convection MCS persisted over 8 hours Organization and evolution more complicated than easterly MCS Figure 2. Radar CAPPI of storm relative winds and reflectivity for the 26 January “easterly” MCS (left) and 25 February “westerly” MCS (right). Precipitation Characteristics Figure 8. Composite frequency histograms (left km height range) and mean profiles (right) of precipitation characteristics as determined from S-Pol observations of Z H and Z DR. (a) Precipitation ice mass (M i g m -3 ), (b) rain mass (M w g m -3 ), and (c) mass weighted mean drop diameter (D m mm). Large differences in ice content above 6 km suggest vertical drafts in the westerly case are not strong enough to levitate drops high and/or long enough for significant drop freezing to occur Reason for differences in location of peak D m above melt level are uncertain but may reflect differences in updraft strength and subsequent location of maximum collision-coalescence growth Larger D m for easterly MCS below melt level probably due to fallout and melting of large ice particles Height (km) Reflectivity (dBZ) Partitioned Reflectivity Figure 6. Composite CFAD’s of S-Pol reflectivity for the easterly MCS (top row) and the westerly MCS (middle row). Bottom row shows corresponding mean reflectivity profiles (easterly -red and westerly -blue). Columns from left to right are for the convective, non-convective, and total precipitation categories. ConvectiveNon-ConvectiveTotal Westerly convective profile has steeper gradient in mixed phase region Westerly has bright band signature in non-convective region Non-ConvectiveConvective Total Height (km) Vertical Air Motion (m s -1 ) Partitioned Vertical Air Motion Figure 7. Same as Fig. 6 except for vertical air motion. Modes of distributions for each MCS are nearly identical but mean profiles are different due to higher frequency of intense drafts in the easterly MCS Easterly convective profile ~100% larger below melt level Non-convective drafts have a significant impact on the total draft structure for the easterly MCS Non-convective drafts are insignificant (in the mean) for westerly MCS in lower tropossphere despite characteristic bright band signature (see Fig. 6) - lack of descent may reflect moist environment and reduced evaporation Significant differences in intensity and lifecycle characteristics 10 9 kg s -1 “Easterly” Convection “Westerly” Convection Time (UTC) Height (km) Vertical Mass Transport Figure 10. Time-height cross section of vertical mass transport Rain Rate Histogram Mean rain rate in easterly MCS is larger by a factor of 2 due to higher frequency of intense rain rates Easterly MCS Westerly MCS Rain rate (mm hr -1 ) Figure 9. Composite rain rate histogram for the easterly MCS (top) and westerly MCS (bottom). Easterly 10 m s -1 Westerly 5 m s -1 Figure 3. Cross sections of wind flow and selected polarimetric signatures for the easterly MCS (left) and westerly MCS (right). Locations of the respective cross sections are shown in Fig. 2. Radar reflectivity shaded as indicated, Z DR (blue) is contoured at 1 dB, incrementing at 1 dB. LDR (Red) contoured at -23, -21, and -19 dB. Note change in wind vector scale between panels. Polarimetric Comparison Easterly Z DR -LDR signature suggests hail production via drop freezing No evidence of significant mixed phase process in westerly MCS Convective Fraction Easterly MCS Westerly MCS Figure 5. Time series of convective fraction in each dual-Doppler synthesis volume for the easterly MCS (top) and westerly MCS (bottom). Time (UTC) Convective Fraction MCSs were in similar lifecycle stages during their respective sampling periods