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Analysis and Prediction of Convective Initiation on 24 May, 2002. June 14, 2004 Toulouse 2 nd IHOP_2002 Science Meeting. Ming Xue, William Martin and Geoffrey Stano School of Meteorology and Center for Analysis and Prediction of Storms University of Oklahoma. - PowerPoint PPT Presentation
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Analysis and Prediction of Convective Initiation on 24 May, 2002
June 14, 2004Toulouse 2nd IHOP_2002 Science Meeting
Ming Xue, William Martin and Geoffrey StanoSchool of Meteorology and Center for Analysis and Prediction of Storms
University of Oklahoma
Our work on May 24, 2002 CI Case
• MS Thesis work of Geoffrey Stano: Multi-scale study based-on ADAS analyses including special IHOP data sets, and by examining observations directly.
• High-resolution simulation study (focus of this talk)
• Very large (~2000) ensemble and adjoint I.C. sensitivity study. dP/dqv sensitivity fields.
Objectives
• Understand convective initiation in this case
• Predict and understand the convective systems involved
• Assess the sensitivity of precipitation forecast to initial conditions
Methodology
• Make use of special data sets collected during IHOP
• Create high-resolution gridded data to perform diagnostic analysis and for model initialization
• Verify model simulations against available data
• Analyze realistic high-resolution model simulations to understand CI process
Synopsis of the Event
• Convection started between 20:00 and 20:30 UTC in Texas panhandle area along a dryline. An intensive observation of IHOP_2002.
• Rapidly developed into a squall line and advanced across Oklahoma and northern Texas
• SPC reported almost 100 incidents of large hail, 15 wind reports, and two tornadoes in central Texas
Time and Location of Initiation(17UTC – 22 UTC)
Isotach Analysis: 250mb
TX Panhandle located at left-rear of upper level jetA short wave trough moved over western TX
19 UTC 20 UTC
CIN and CAPE AnalysesCIN 19UTC
CAPE 19UTC CAPE 20UTC
CIN 20UTC
Results of Stano’s diagnostic study
• Favorable condition pointing to initial initiation near Childress, TX– Placement of 250mb jet max and minimum– Surface heating and high surface dew points– Low Convective Inhibition values
• Causes for initiation– Weakening of cap over the boundary layer by turbulently
mixing – Break down of cap led to higher CAPE values– Convergence along the dryline or possibly from the cold
front approaching dryline
• More specifics limited by data resolutions
Model Simulation Study
• Model can provide much more complete data in both space and time
• Easier to examine cause and effect
• Model fields are dynamically consistent
• Caution - model solution may deviate from truth therefore verification against truth is necessary
Forecast Grids
4
Model Configurations
• 1 km grid nested inside 3 km one• ADAS analyses for ICs and 3 km BCs• NCEP ETA 18UTC and 00UTC analyses and
21UTC forecast used as analysis background• ARPS model with full physics, including ice
microphysics + soil model + PBL and SGS turbulence
• LBCs every 3h for 3km grid and every 15min for 1 km grid
• 6 hour simulation/forecast, starting at 18 UTC
OBS Used by ADAS
• ARM• COAG• IHOP Composite Upper Air - rawinsondes• KS Ground Water District 5• OK Mesonet• SAO• SW Kansas Mesonet• Western TX Mesonet• Profiler data absent
Surface Data Sets
Upper-Air Observing Sites
Dropsondes on 20 UTC Isodrosotherms
20:02UTC
20:32UTC
21:02UTC
21:32UTC
22:02UTC
22:58UTC
23:58UTC
Animation 20UTC-00UTC, KLBB radar
Animation 20UTC-00UTC, KFRD radar
3km model simulation/forecast
1 km simulation
T=2.5h20:30UTC
T=3.0h21:00UTC
T=3.5h21:30UTC
T=4.0h22:00UTC
T=4.5h22:30UTC
T=5h23:00Z
T=5h23:00Z
T=5.5h23:30Z
T=5h23:00Z
Animations
• Surface reflectivity
• 2km level w, winds
See movies(18:30 UTC – 00:00 UTC)
See Movies
19:16UTC
19:45UTC
20:30UTC
23:00UTC
Vertical cross-section animations
• w and • w and qv• qv and e
See Movies
See Movies
+
+
+
X-section at y=170 km
See movie
Conclusions
• Dryline convection occurred in favorable synoptic-scale environment (upper jet, sfc trough, convergence, moisture supply, CAPE, etc.)
• Realistic CI predicted by the model, especially at 1 km resolution
• Model CI associated with dryline was ~ 30min-1h late (related to spinup?)
• Active development of BL eddies observed before C.I. in convergence zone (50-100km wide) and in the moist air (underneath CAP)
Conclusions – continued
• A number of successfully penetration by B.L. parcels through the CAP before sustained convection is achieved
• Sustained convection occurred on the moist side near but not in the well mixed convergence zone or at the location of strong Td gradient
• Sloping terrain and surface heating played key roles• Cold frontal convection started earlier, due to lifting• Cold front or the triple point did not directly trigger dryline
convection – dryline did it on its own and initiated convection further south
• Cold air surge to the N.W. of dryline did not directly trigger convection (was in dry air, no CAPE)
Conclusions - continued
• Role of surface wind convergence induced by mixing unclear to C.I. – perhaps indirectly by destabilizing the zone
• B.L. depth increases with time, so does its temperature, due to surface heating and eddy mixing)
• Any role of played by gravity waves or their interaction with B.L. eddies – not clear.
• Eddies organize into rolls/cloud streets near the edges of the convergence zone, where background wind is present
• Fine westward-propagating echoes observed by KLBB radar at the low levels are associated with the rearward propagating outflow boundary
Comments very welcome!
Like to compare with fine-scale observations
Posters
• Dawson and Xue: Data sensitivity study on June 16 MCS case
• Liu and Xue: 3DVAR assimilation GPS slant path water vapor data with an isotropic spatial filter. Tested on simulated data from June 18, 2002 dryline case.
• Tanamachi: June 12, 2002 boundary layer water vapor oscillation case - undular bore? Observation and simulation study
• Sensitivity Study – Title Slide
TANGENT-LINEAR AND ADJOINT MODELS VERSUS PERTURBED FORWARD MODEL
RUNS
William J. MartinMing Xue
Center for Analysis and Prediction of Storms and the
University of Oklahoma, Norman, Oklahoma
6 hr. forecast total accumulated precipitation
• The sensitivity of a defined response function, J, such as the total rainfall in some area, is sought as a function of the initial fields.
• This is done by making a large number of forward model runs, each with a perturbation in a different location. The location of the perturbation is varied so as to tile a 2-D slice of the model domain.
• dx=dy=9km, no Cb parameterization
1 g/kg qv pert
Example of an initial perturbation
i
i vi
yx
yxqJ
)(
Response Function Defined As:
)),((1000),( controlJyxJyxS
Sensitivity Defined As:
Sensitivity field for the dependence of total PPT on initial boundary layer moisture perturbations
+1 g/kg perturbations