Lightning Next Gen Workshop Steve Albers NOAA ESRL

Lightning Next. Gen Workshop Steve Albers NOAA / ESRL / GSD / FAB March 2010

Icing Next. Gen Workshop Steve Albers NOAA / ESRL / GSD / FAB March 2010

Derived products flow chart

Radar X-sect (wide/narrow band)

Ceiling and Visibility Next. Gen Workshop Steve Albers, Paul Schultz, Yuanfu Xie NOAA/ESRL/GSD/FAB March 2010

LAPS cloud analysis METAR

Hot-start and Cloud analysis LAPS hot-start scheme Dramatically improves Very short-range forecast, Importance to terminal Scale convective forecast References: ? ? ? The hot-start scheme will be adapted into STMAS, a multigrid variational data Assimilation system with satellite, radar, And conventional obs and model dynamic Constraint simultaneously.

3 D Cloud Image

Cloud Analysis Flow Chart

Cloud/precip cross section

Satellite use in Cloud Analysis • 11 micron IR • 3. 9 micron data • Visible (with terrain albedo database) • CO 2 -Slicing method (Cloud-top pressure)

End

Surface Precipitation Accumulation • Algorithm similar to NEXRAD PPS, but runs in Cartesian space • Rain / Liquid Equivalent – Z = 200 R ^ 1. 6 • Snow case: use rain/snow ratio dependent on column maximum temperature – Checks on Z and T could be added to reduce bright band effect

Storm-Total Precipitation

Future Cloud / Radar analysis efforts • Account for evaporation of radar echoes in dry air – Sub-cloud base for NOWRAD – Below the radar horizon for full volume reflectivity • Processing of multiple radars and radar types – Evaluate Ground Clutter / AP rejection

Future Cloud/Radar analysis efforts (cont) • Consider Terrain Obstructions • Improve Z-R Relationship – Convective vs. Stratiform • Precipitation Analysis – Improve Sfc Precip coupling to 3 D hydrometeors – Combine radar with other data sources • Model First Guess • Rain Gauges • Satellite Precip Estimates (e. g. GOES/TRMM)

11 micron imagery • T(11 u) best detects mid-high level clouds • Cloud Clearing Step • Cloud Building Step • Iterative Adjustment Step – Forward model converts cloud-sounding T(11 u) estimate – Constrained 1 DVAR iteration fits cloud layers to observed T(11 u)

3. 9 micron imagery • T(3. 9 u) – T(11 u) detects stratus at night – Currently used with 11 u cloud-tops for cloud building – Testing underway for cloud-clearing – Additional criteria include T(11 u) and land fraction • T(3. 9 u) – T(11 u) detects clouds in the daytime? – Visible may be similar in cloud masking properties – Visible may be easier for obtaining a cloud fraction • Cloud Phase? – Could work using T(3. 9 u) – T(11 u) at night – Cloud-top phase needs blending throughout LWC/ICE column

Visible Satellite • Improving visible with terrain albedo database – Cloud-clearing (done with current analysis) – Cloud-building (now being tested) • Accurate sfc albedo can work with VIS + 11 micron cloud -tops • Visible cloud fraction can be used to correct apparent brightness temperature to yield improved cloud-top temperature

Cloud Schematic

Visible Satellite Impact

CO 2 Slicing Method (cloud-top P) • Subset of NESDIS Cloud-Top Pressure data – CO 2 measurements add value – 11 u measurements (0 or 1 cloud fraction) redundant with imagery? – Imagery has better spatial and temporal resolution? • Treat as a “cloud sounding” similar to METARs and PIREPs

Selected references • • • Albers, S. , 1995: The LAPS wind analysis. Wea. and Forecasting, 10, 342 -352. Albers, S. , J. Mc. Ginley, D. Birkenheuer, and J. Smart, 1996: The Local Analysis and prediction System (LAPS): Analyses of clouds, precipitation and temperature. Wea. and Forecasting, 11, 273 -287. Birkenheuer, D. , B. L. Shaw, S. Albers, E. Szoke, 2001: Evaluation of local-scale forecasts for severe weather of July 20, 2000. Preprints, 14 th Conf on Numerical Wea. Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc. Cram, J. M. , Albers, S. , and D. Devenyi, 1996: Application of a Two-Dimensional Variational Scheme to a Meso-beta scale wind analysis. Preprints, 15 th Conf on Wea. Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc. Mc. Ginley, J. , S. Albers, D. Birkenheuer, B. Shaw, and P. Schultz, 2000: The LAPS water in all phases analysis: the approach and impacts on numerical prediction. Presented at the 5 th International Symposium on Tropospheric Profiling, Adelaide, Australia. Schultz, P. and S. Albers, 2001: The use of three-dimensional analyses of cloud attributes for diabatic initialization of mesoscale models. Preprints, 14 th Conf on Numerical Wea. Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc.

Precip type and snow cover

The End

Remapping Strategy • Polar to Cartesian – 2 D or 3 D result (narrowband / wideband) – Average Z, V of all gates directly illuminating each grid box – QC checks applied – Typically produces sparse arrays at this stage

Doppler & Other Wind Obs

Single / Multi-radar Wind Obs

LAPS 700 Hpa Winds

Remapping Strategy (reflectivity) • Horizontal Analysis/Filter (Reflectivity) – Needed for medium/high resolutions (<5 km) at distant ranges – Replace unilluminated points with average of immediate grid neighbors (from neighboring radials) – Equivalent to Barnes weighting at medium resolutions (~5 km) – Extensible to Barnes for high resolutions (~1 km) • Vertical Gap Filling (Reflectivity) – Linear interpolation to fill gaps up to 2 km – Fills in below radar horizon & visible echo

LAPS radar ingest

Horizontal Filter/Analysis Before After

Mosaicing Strategy (reflectivity) • Nearest radar with valid data used • +/- 10 minute time window • Final 3 D reflectivity field produced within cloud analysis – Wideband is combined with Level-III (NOWRAD/NEXRAD) – Non-radar data contributes vertical info with narrowband – QC checks including satellite • Help reduce AP and ground clutter

Reflectivity (800 h. Pa)

Future LAPS analysis work • Surface obs QC – Operational use of Kalman filter (with time-space conversion) – Handling of surface stations with known bias • Improved use of radar data for AWIPS – Multiple radars – Wide-band full volume scans – Use of Doppler velocities • Obtain observation increments just outside of domain – Implies software restructuring • Add SST to surface analysis • Stability indices – Wet bulb zero, K index, totals, Showalter, LCL (AWIPS) – LI/CAPE/CIN with different parcels in boundary layer – new (SPC) method for computing storm motions feeding to helicity determination • More-generalized vertical coordinate?

Recent analysis improvements • More generalized 2 -D/3 -D successive correction algorithm – – Utilized on 3 -D wind/temperature, most surface fields Helps with clustered data having varying error characteristics More efficient for numerous observations Tested with SMS • Gridded analyses feed into variational balancing package • Cloud/Radar analysis – Mixture of 2 D (NEXRAD/NOWRAD low-level) and 3 D (wide-band volume radar) – Missing radar data vs “no echo” handling – Horizontal radar interpolation between radials – Improved use of model first guess RH &cloud liq/ice

Cloud type diagnosis Cloud type is derived as a function of temperature and stability

LAPS data ingest strategy

Cloud/precip cross section

Wind Analysis Flow Chart