# Presentation: 832695

## Products expressed in terms of climate anomalies

- Yuejian Zhu and Zoltan Toth
- Environmental Modeling Center
- NCEP/NWS/NOAA
- September 27th  2005

## Input climate/forecast data -- current available

- NCEP/NCAR reanalysis data (or opr. Analysis)
- 4 cycles (00UTC, 06UTC, 12UTC and 18UTC) per day
- 40 years (Jan. 1st 1959 – Dec. 31th 1998)
- Need to consider the systematic difference between reanalysis to operational forecast
- Resolution and format
- 2.5*2.5 (lat/lon) grid, GRIB-1 format
- 1.0*1.0 (lat/lon) grid, GRIB-1 format (forecast only)
- Variables at levels (possible to add more)
- Height: 1000hPa, 700hPa, 500hPa, 250hPa
- Temperature: 2m, 850hPa, 500hPa, 250hPa
- Wind: 10m, 850hPa, 500hPa, 250hPa
- PRMSL, max/min temperature

## Climatological mean (estimation)

- To consider monthly mean (tested)
- Monthly mean (large data samples – 1240)
- Interpolate to daily (shifted from season)
- To consider daily mean (tested)
- 5-day running mean for daily climatology
- Data samples – 200
- 5-day center weighted mean for monthly climatology
- Data samples – 200
- (d-2)*0.12+(d-1)*0.22+d*0.32+(d+1)*0.22+(d+2)*0.12
- To consider annual cycle (working on)
- Fits the first two Fourier annual modes to daily data to obtain annual cycle.

## Higher moments (estimation)- work on the anomalies from mean

- To consider monthly (tested):
- Data size of 40 (year) * 31 (dom for Jan) = 1240
- Fitting distributions (three parameters)
- Gamma, Pearson type-III, GE3 (generalized extreme-value)
- Compute a smooth standard deviation (working on)
- Based on annual cycle
- Discussions and questions

## Products (plan)

- Climate anomaly:
- For each grid points.
- For selected variables.
- For each ensemble member.
- In percentile.
- Produce probabilistic products for NDGD from this individual climate anomaly.
- Additional data file

## NDGD FORECAST UNCERTAINTY RECOMMENDATION

- Provide 3 ensemble-based guidance products for inclusion in NDGD:
- 10, 50, and 90 percentile values
- SREF guidance out to day 3
- NAEFS guidance out to 16 days
- Use NDGD grid (5x5 km), with GRIB2 packing, minimal space overhead
- Approach
- Solicit comments on specific proposal from NCEP Service Centers and regions/field
- Use NAWIPS software (available soon?) to generate products
- Work with NAWIPS group to provide algorithm:
- Simple counting of members with linear interpolation now
- Gaussian Kernel method in later implementation
- Factor of 3 increase in disc space
- D. Ruth positively inclined (WG member at NDFD Workshop)

## NDGD FORECAST UNCERTAINTY - DOWNSCALING

- Ensemble uncertainty information
- Sent on NDGD grid for convenience (if no big overhead)
- Valid on model grids (32km for regional, 110 km for global ensemble)
- How to bridge gap between model and NDGD grids?
- Anomaly uncertainty information – proposed methodology
- Establish reanalysis climatology
- In progress for global (NAEFS), methods can be transferred to regional reanalysis
- Bias correct ensemble forecasts (wrt operational analysis)
- Take 10-50-90 percentile values from bias corrected ensemble
- (For establishing anomaly forecasts, adjust 10-50-90 percentile values to look like re-analysis)
- Check climatological percentile corresponding to 10-50-90 forecast percentiles
- Provide climatological percentiles corresponding to 10-50-90 percentile forecast values as second set of guidance products

## ENSEMBLE-BASED PRODUCTS FOR NDGD

- National Digital Forecast Database (NDFD)
- Official NWS forecast, prepared by WFO offices (central guidance, coordination)
- 5x5 (2.5x2.5) km grid, out to 7 days
- Selected parameters (~15)
- Available in digital format, query tools, etc
- No (minimal) provision for information on forecast uncertainty
- Recommendations from an NDFD workshop, Salt Lake City, 2003
- Interactive Forecast Preparation System (IFPS) offers tools to work with NDFD grids (forecasters can manipulate gridded data, etc)
- National Digital Guidance Database (NDGD)
- For posting numerical guidance products same way as NDFD
- New system, possibility to complement NDFD with forecast uncertainty info
- Based on global (NAEFS) and regional ensemble forecasts
- What forecast uncertainty info to post in NDGD?

## NDGD FORECAST UNCERTAINTY REQUIREMENTS

- Compact (conveys uncertainty without posting all members)
- Add minimal new info
- Current disc, telecommunication, etc limitations
- Simple to understand and use by both trained and novice users
- Expand existing lines of work
- Informative without additional knowledge, tools, that are not yet available
- Solid & scientifically based
- Can fit parametric pdf
- Allows to derive any univariate info
- Additional tools needed to use this feature
- Room for expansion
- Can easily be enhanced without major shift in direction
- More sophisticated methods can be added
- Possibly use Gaussian Kernel method of D. Unger

## NDGD FORECAST UNCERTAINTY ALTERNATIVES

- Current status (in NDFD):
- Expected value (mean, median, or mode??) of distribution only
- Scenario 1 – Add 1 variable
- Add spread to expected value (1 additional grid)
- Workshop WG felt that was not enough info
- Recommended adding 2 pieces of info
- Scenario 2 – Add 2 variables
- Add info on spread on 2 sides of mean/median/mode
- 10/90 or 20-80 percentile values
- Preferred as opposed to variance (spread) info that is more abstract
- NDFD Workshop recommendation

## NDGD FORECAST UNCERTAINTY QUESTIONS

- Use mean, mode, or median in NDGD?
- Mean – Expected value
- Can fall around minimum in pdf
- Requires additional info (what percentile it corresponds with)
- Mode – Most likely event
- Appealing heuristically (well defined meaning)
- Requires additional info (what percentile it corresponds with)
- Use in future when multiple modes can be considered?
- Median – 50 percentile
- Heuristic meaning (half below, half above)
- Consistent with 10/90 (or 20/80) percentile approach
- Verifies similarly to ensemble mean
- No need for additional info
- Used by HPC in PQPF context
- Use 10/90 OR 20/80 percentile?
- 10/90 is more inclusive (covering explicitly 80% of forecast distribution)

## GEV

- Monthly mean
- 5-day weighted mean

## GEV

- Monthly mean
- 5-day weighted mean

## Monthly mean

- GEV

- PE3

- PE3

- 5-day weighted mean

## Example of probabilistic forecast in terms of climatology

## ENSEMBLE 10-, 50- (MEDIAN) & 90-PERCENTILE FORECAST VALUES (BLACK CONTOURS) AND CORRESPONDING CLIMATE PERCENTILES (SHADES OF COLOR)