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Unidata software and data usage at University of Wisconsin -
Madison
Pete PokrandtUW-AOS Computer Systems Admin
Unidata software and data usage at UW-AOS
Evolution of UW-Madison AOS involvement with UnidataOngoing research using Unidata software/dataUse in courses
Evolution of Unidata involvement at UW Madison
1986 – DIFAX to facsimile machineDDS, PPS to line feed printer
1987 – PC McIDAS1989 – DIFAX to Dot Matrix printer1992 – DDS, PPS to Sun Workstation
minimal data archiving to Exabyte tapewxp to plot dataDIFAX to laserprinter
Evolution of Unidata involvement at UW Madison
1994-1995 – GEMPAK installed, replaced McIDAS as primary data analysis/plotting tool1995 – switch from satellite feed to IDDDDPLUS, IDS, HDS, MCIDAS, NLDN1996 – archive DDPLUS, IDS, HDS, MCIDAS1998 NMC2/SPARE/CONDUIT2000 NEXRAD, FNEXRAD
Evolution of Unidata involvement at UW Madison
2002 – archive CONDUIT grid analyses2003 NIMAGE, CRAFT, IDV
Some uses of Unidata software/data
Products made available on the internet– Surface, Upper Air plots– NEXRAD Composites– Model plots and animations– Lightning strike plots (Restricted)
Analysis using NCEP Model GridsNCEP Model Grids used to initialize local mesoscale models
Products on the internet
Surface plots
Products on the internet
Surface plots
Products on the internet
Surface plots
Products on the internet
Upper air analyses
Products on the internet
Upper air analyses
Products on the internet
NEXRAD products and composites– National and Regional Composites
(live link)– Individual site products for regional sites
Products on the internet
Model plots and animations– Eta on the AWIPS 212 grid– Eta on the AWIPS 104 grid
– GFS on the 1 degree global grid300 hPa 500 hPa 850 hPa
Products on the internet
GFS/Ensemble 4-panel plots
1 day forecast
Products on the internet
GFS/Ensemble 4-panel plots
8 day forecast
Products on the internet
GFS/Ensemble 4-panel plots
10 day forecast
Products on the internet
GFS/Ensemble 4-panel plots
Products on the internet
Lightning data – plots and loopsUS regionUS region loopWI regionWI region loop
Use of NCEP Model Grids
Analysis using NCEP Model Grids
- Steve Decker – GFS Energetics plots
- Justin Mclay – Ensemble Verification
- Allison Hoggarth – PV tracking of easterlywaves
GFS Energetics plotsSteven Decker
Horizontal Kinetic Energy per unit mass (KE) at a point can be broken into two parts
- Mean KE is derived from the time mean wind at that point – 28 day time mean
- Eddy KE is derived from current wind minus mean wind: EKE = (1/2)(u’2 + v’2)
GFS Energetics plotsSteven Decker
Time tendency of EKE is determined by:
d(EKE)/dt = MAEKE + EAEKE + BTG + BCG + AGFC + CURV + RES (d/dt is local derivative)
MAEKE is mean advection of EKEEAEKE is eddy advection of EKEBTG is barotropic generationBCG is baroclinic generation
GFS Energetics plotsSteven Decker
Time tendency of EKE is determined by:
d(EKE)/dt = MAEKE + EAEKE + BTG + BCG + AGFC + CURV + RES (d/dt is local derivative)
AGFC is ageostrophic geopotential flux conv.CURV are terms related to earth curvatureRES is a residual, including friction
GFS Energetics plotsSteven Decker
d(EKE)/dt = MAEKE + EAEKE + BTG + BCG + AGFC + CURV + RES (d/dt is local derivative)
Advection terms move EKE around but do not create or destroy it
GFS Energetics plotsSteven Decker
d(EKE)/dt = MAEKE + EAEKE + BTG + BCG + AGFC + CURV + RES (d/dt is local derivative)
Generation terms create or destroy EKE in various ways
GFS Energetics plotsSteven Decker
d(EKE)/dt = MAEKE + EAEKE + BTG + BCG + AGFC + CURV + RES (d/dt is local derivative)
AGFC indicates collection (dispersion) of EKE radiation at (from) a point from (to) elsewhere in the domain
GFS Energetics plotsSteven Decker
d(EKE)/dt = MAEKE + EAEKE + BTG + BCG + AGFC + CURV + RES (d/dt is local derivative)
The other terms are usually not important
GFS Energetics plotsSteven Decker
Using GEMPAK and the 1 degree global GFS data set from the CONDUIT data stream, plots are created twice daily for EKE with AGF vectors, EAEKE, BCG, AGFC and a wave packet envelope function.
GFS Energetics plotsSteven Decker
300 hPa Geo Hgt EKE and AGF vectors
GFS Energetics plotsSteven Decker
Time tendency of EKE due to eddy advection
GFS Energetics plotsSteven Decker
Baroclinic Generation of EKE
GFS Energetics plotsSteven Decker
Wave Packet Envelope function
GFS Energetics plotsSteven Decker
Plots and further explanation available at
http://speedy.aos.wisc.edu/~sgdecker/realtime/realtime.html
Ensemble prediction of CAOsJustin Mclay
Daily 00 UTC ensemble initialization is being used in an ongoing assessment of deterministic and ensemble prediction of North American Cold Air Outbreaks (CAOs)
Ensemble forecasts frequently predict “Phantom” or “Sneak” CAOs (Postel 2002, personal communication)
Ensemble prediction of CAOsJustin Mclay
Phantom CAOs – where ensemble suggest a high likelyhood of a CAO, which ultimately does not verify
Sneak CAOs – where ensemble suggests a low, if any likelyhood of a CAO, which ultimately does verify
Ensemble prediction of CAOsJustin Mclay
Current effort is using GFS ensemble forecasts via the CONDUIT data stream to document the performance of the ensemble system with specific regard to CAOs.
Ensemble prediction of CAOsJustin Mclay
Some elements – Relative frequency of Phantom and Sneak CAOs– Relative skill in predicting moderate vs. extreme
CAO– First and second statistical moments of the
ensemble (mean and covariance) are also being investigated for incorporation into statistical post-processing schemes to improve ensemble prediction of CAOs.
PV Tracking of easterly wavesAllison Hoggarth
Using 1 degree global GFS analyses and GEMPAK, evaluate PV (and other quantities) over the tropical Atlantic basinIs there a way to categorize whether a wave will transform into a tropical depression or not?Tropical depression #2 (June 2003)
Use of NCEP Model Grids
Initialization for local operational mesoscale modeling
- Tripoli – UW-NMS
- Morgan/Kleist – MM5/Adjoint derivedforecast sensitivities
Operational UW-NMSTripoli, Pokrandt, Adams, et. al.
Began operational runs in 1992Data from inside source at NMC, later from public NMC serverSince 2000, via CONDUIT feed – locally available sooner than via ftp“Storm of the Century”, 1993Mainly lake breeze, lake effect snow – tied to the terrain/surface characteristics
Operational UW-NMSTripoli, Pokrandt, Adams, et. al.
Cooperation with NWS-Sullivan, studying predictability of local terrain/topo driven phenomena (lake breeze, lake effect snow)Fire Weather index predictionSupercell Index – supports severe storm observation class (Storm chasing)Vis5d animations, GEMPAK output support synoptic lab courses
Operational UW-NMSTripoli, Pokrandt, Adams, et. al.
Support of various field projects
- Lake ICE (Lake Effect Snow over Lake Michigan
- Recent Pacific field project – instrument testing – needed heavy precipitation over water
MM5/Adjoint derived fcst sensitivityMorgan/Kleist
MM5 Adjoint Modeling System (Zou et al., 1997)
All sensitivities to be described were calculated by integrating the adjoint model “backwards” using dry dynamics, about a moist basic state generated by the forward MM5 run, initialized with Eta initialization
MM5/Adjoint derived fcst sensitivityMorgan/Kleist
ForecastModel
'outx→→'
inx
outx∂∂← R
←∂∂
inxR Adjoint
Model
)( vqpTwvux ,',,,,=
)('R,R,R,R,RRpTwvux ∂∂
∂∂
∂∂
∂∂
∂∂=
∂∂
MM5/Adjoint derived fcst sensitivityMorgan/Kleist
Real-Time Forecast SensitivitiesGoal: To understand the characteristics and sensitivity to initial conditions of short range numerical weather prediction (NWP) forecasts and forecast errors over the continental United StatesAvailable:
– Sensitivity plots (updated twice daily) for two response functions:36 hour energy-weighted forecast error 36 hour forecast of average temperature over Wisconsin
– Adjoint-derived ensemble of forecasts of average temperature over Wisconsin (soon to be available)
0h 12h
24h 36h
MM5/Adjoint derived fcst sensitivityMorgan/Kleist
Sensitivity Based “Ensembles”Could run several forward models with different initial conditions (Eta, NGM, GFS, NOGAPS,etc), get an ensemble of average temps over WI boxInstead, multiply the sensitivity gradient by each initial condition to get estimates of the ensemble members
Use in after-the-fact analysis
Use of archived datasets for after-the-fact modeling and analysis- Hitchman/Buker – UW-NMS/middle atmosphere modeling
- Martin – GEMPAK libraries to create new datasets
Middle Atmosphere modelingMarcus Buker, Matt Hitchman
Real-time forecasting for flight planning for various field projects (POLARIS, SOLVE, TRACE-P)After-the-fact simulations to interpret observations
Middle Atmosphere modelingMarcus Buker, Matt Hitchman
POLARIS (Photochemical Ozone Loss in the Arctic Region In Summer)– Regional scale simulations were run for the
campaign area (50-70N, 120W-70E)– Ozone & passive tracers initialized to monitor
constituent transport across the tropopause– Found ozone is lost from the stratosphere to the
troposphere by stretching/folding of tropopause by breaking Rossby waves.
Middle Atmosphere modelingMarcus Buker, Matt Hitchman
SOLVE (SAGE III Ozone Loss and Validation Experiment)– Ozone loss in wintertime boreal polar region is
highly dependent on existence of polar stratospheric clouds – chemical makeup is conduscive for photochemical destruction of ozone.
– Form in coldest parts of stratosphere (~-80C), in areas where bouyancy waves induce relatively strong vertical motion
Middle Atmosphere modelingMarcus Buker, Matt Hitchman
SOLVE (SAGE III Ozone Loss and Validation Experiment)– Mountain waves are a major contributor to this type
of phenomenon– Hitchman et al. (2003) used UWNMS to show that
non-orographic bouyancy waves can also produce extensive areas of PSC formation, especially in early winter
Middle Atmosphere modelingMarcus Buker, Matt Hitchman
TRACE-P (TRansport And Chemical Evolution over the Pacific)
– UW-NMS simulations ongoing for flight dates in March, 2001.– Trying to differentiate between ozone from ground sources and
transport from the stratosphere, to determine contribution of tropospheric pollution from east Asian sector.
– Testing new methodology to get ozone flux between stratosphere/troposphere in regions of strong troposphericactivity
GEMPAK to create new data setsJon Martin
Use of GEMPAK libraries and locally written programsRead existing data sets, perform calculations, save out to new data set.Can be done recursively, or to trim size of a data set, compute complex functions, etc.
Unidata in UW Courses
GEMPAK/GARP – in class and in researchldm – to get dataMaps onlineTripoli – storm chasingSynoptic Lab – case studies
The future
IDV, THREDDSCRAFT
Questions?
Thank you!
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