1. LAPS cloud analysis Steve Albers (NOAA/ESRL/GSD/FAB & CIRA) METAR

2. Cloud Analysis Flow Chart

3. Derived products flow chart

4. Cloud/precip cross section

5. 11 micron imagery T(11u) best detects mid-high level clouds
Cloud Clearing Step
Cloud Building Step
Iterative Adjustment Step
Forward model converts cloud-sounding to T(11u) estimate
Constrained 1DVAR iteration fits cloud layers to observed T(11u)

6. 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

7. 3.9 micron imagery T(3.9u) – T(11u) detects stratus at night
Currently used with 11u cloud-tops for cloud building
Testing underway for cloud-clearing
Additional criteria include T(11u) and land fraction
T(3.9u) – T(11u) 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(3.9u) – T(11u) at night
Cloud-top phase needs blending throughout LWC/ICE column

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

9. 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

10. Cloud/precip cross section

11. Storm-Total Precipitation

12. Cloud/Satellite Analysis Topics
11 micron IR
3.9 micron data
Improving visible with terrain albedo database
CO2-Slicing method (Cloud-top pressure)

13. Visible Satellite Impact

14. CO2 Slicing Method (cloud-top P)
Subset of NESDIS Cloud-Top Pressure data
CO2 measurements add value
11u 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

15. Selected references
Albers, S., 1995: The LAPS wind analysis. Wea. and Forecasting, 10,
Albers, S., J. McGinley, D. Birkenheuer, and J. Smart, 1996: The Local Analysis and prediction System (LAPS): Analyses of clouds, precipitation and temperature. Wea. and Forecasting, 11,
Birkenheuer, D., B.L. Shaw, S. Albers, E. Szoke, 2001: Evaluation of local-scale forecasts for severe weather of July 20, Preprints, 14th 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, 15th Conf on Wea. Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc.
McGinley, 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 5th 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, 14th Conf on Numerical Wea. Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc.