Climatological Probabilities of

Precipitation for South Florida

Daniel P. Brown

National Weather Service Forecast Office

Miami, Florida

April, 1998

Introduction
The use of climatological probabilities of precipitation (POP) can be a great tool for forecasters to become familiar with precipitation patterns in their forecast area. Because forecasting precipitation probabilities is much harder to visualize than temperature forecasting, an updated climatological POP study was needed for South Florida. Since large variations in precipitation frequency occur, studies computing the climatological probabilities of precipitation should be updated on a regular basis. The more recent the study has been updated, the more useful the results will be to a forecaster's knowledge of current precipitation patterns.
This study continues a previous study (Pifer and Haydu, 1990) which was completed in the same manner at the NWSFO in Miami from 1985 through 1989. With the continuation of the previous study climatological probabilities of precipitation can now be completed for a longer period of record. This updated study can also be compared with previous studies completed in the 1960's and mid 1980's.
Procedure
The National Weather Service began a local verification program called AEV (AFOS Era Verification) (Barker, 1987) at the local level in the early 1980's. This program is run twice daily on the AFOS (Automation of Field Operations and Services) computer system. The AEV verification program produces output which has the potential to improve local forecasts generated by the National Weather Service. Using output from the verification program, climatological probabilities of precipitation (> .01") for the twelve hour daytime and nighttime periods were computed for Palm Beach, Miami, and Key West.
The AEV local verification program was run for each month to obtain climatological POPs. Due to local computer problems, such as hardware or software crashes, some data was missing and was not available for this study. Therefore, the number of days in certain months do not equal the total number of days in that particular month. For example, hardware problems in January of 1989 caused the loss of 12 days of data so only 19 days of data were available. The time period covered by this study is 1985 through 1997 for Miami and from October 1986 through 1997 for Palm Beach and Key West.
Each day was broken into two periods: a daytime (12z to 00z) and nighttime period (00z to 12z). The reason each day was broken into two periods is because these are the two periods from which forecasters verify both temperature and precipitation forecasts. The two periods correlate well with the public perception of the Daytime (Today or tomorrow) and Nighttime (Tonight) periods of the local forecasts. To obtain climatological POPs, the number of precipitation cases (>.01") was divided by the total number of cases (days) available for each month which gives the climatological POPs observed at each observing site. Tables 1 through 12 breakdown each individual month to indicate how each monthly climatological POP was computed and also reveal the variability from year to year of precipitation frequency.
Results and Comparisons
The results of the entire study are listed in Table 13. The results are for the years 1985 though 1997 and are broken down by month as well as daytime and nighttime periods for each station. In Tables 14 through 16 results from local verification were compared with similar studies completed by Jorgensen (1967) and Jensenius and Erickson (1987). The study by Jorgensen was only available for Miami for the years 1949 through1964, however the study by Jensenius and Erickson study was available for all three South Florida verification stations for the years 1972 through 1985. Because each study was very similar in length, between 13 and 16 years, the average differences should be quite similar.
The average differences for Miami between the previous studies and this study ranged between 3.4 and 3.9 percent with the average overall difference of 3.7 percent. The overall average differences at Palm Beach and Key West between the Jensenius and Erickson study was 4.8 percent and 2.8 percent respectively. Since each report has a similar period of record, the average differences between the climatological reports are mostly likely the result of normal variations in climate. The most notable differences between the studies were at Miami were the climatological POP has increase by 8 and 7 percent respectively, from the 1949 to 1964 study, for the daytime periods in June and July. Other summer months also indicated slight increases in daytime POPs at Miami. Since the early study was not available for Palm Beach and Key West, significant trends were not detected. Because the AEV local verification program can be used to update climatological POPs on a regular basis, it will include the latest climatological trends and is probably a much better tool for the forecaster to use.
Conclusion
Hughes (1980) presents a discussion of problems and suggestions for forecasting improvements. From a forecasters point of view, forecasting precipitation probabilities is the hardest element to visualize and correctly forecast. Temperature forecasts can be monitored from surface observations each hour and can be verified by plotting current temperature fields.
When forecasting precipitation probabilities, radar loops can provide similar information as plotted temperatures fields. Unfortunately, there is no equivalent quantity available for forecasting precipitation probabilities. Smith (1977), Smith and Smith(1978) and Naber and Smith (1982) argue that 12 hour composites of hourly radar echo coverage can begin to give the forecaster a visualization of precipitation probabilities, especially in the southern sections of the county in the Summertime. Since most forecasters need a significant amount of time to become familiar with the precipitation patterns in their area, this is another reason why precipitation frequencies should play a larger role in the forecast process.
It is noted that addition products from the WSR-88D could be produced to aid the forecaster in verifying POP forecasts. Currently a 24 hour User Selectable Precipitation (USP) map can be produced to show total 24 hour radar rainfall estimates. However, it would be to the forecasters benefit to actually produce a composite 12 hour areal coverage of precipitation by the WSR-88D for each forecast zone in the forecasters area of responsibility. If a 12 hour areal precipitation coverage map was produced better verification information could be computed and improvements in forecasts would result.
After reviewing the results and variability of precipitation frequency, one realizes the importance of long term studies to smooth the variability. One advantage of the local AEV verification program is that the results of this study can be updated locally on a regular basis. However, as the National Weather Service continues to complete its modernized program it is hoped that a local verification program will be available on the new AWIPS (Advanced Weather Information Processing System) computer system. It is also expected that verification data from the AEV verification program can be incorporated into the new system so that valuable data is not lost through modernization.
The data and results of this study can be a great asset in forecasting probabilities of precipitation. Climatological POPs can be a great starting point to forecasting POPs in the summer in South Florida. It appears from the results of this study that higher summertime POPs may needed along the Southeast Florida Coast with perhaps lower POPs for the Keys. It is hoped that this study can be continued in the future so that variations in precipitation frequencies can be smoothed out. Therefore, representative probabilities of precipitation can be a computed for any recent changes in precipitation patterns and aid local forecasters in forecasting POPs for South Florida.
/TR>

Table 13: Climatological Probabilities of Precipitation for
South Florida from 1985-1997

Nighttime (00z to 12z) Probabilities of Precipitation*

STATION JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Palm Bch. 20% 15% 22% 17% 21% 30% 22% 31% 39% 25% 19% 13%
Miami 16% 12% 15% 13% 18% 29% 24% 24% 33% 26% 19% 11%
Key West 14% 10% 13% 11% 17% 23% 21% 25% 35% 26% 13% 13%

Daytime (12z to 00z) Probabilities of Precipitation*

STATION JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Palm Bch. 24% 19% 26% 22% 22% 43% 37% 40% 42% 29% 21% 15%
Miami 17% 14% 17% 18% 22% 44% 42% 46% 42% 31% 19% 13%
Key West 13% 9% 12% 12% 13% 24% 27% 31% 38% 25% 15% 11%
* From (1985-1997) for Miami and (October 1986-1997) for Palm Beach and Key West


Table 14: Comparison of Miami Climatological
Probabilities of Precipitation

Nighttime (00z to 12z)

  1949-1964 1972-1985 1985-1997
Months ESSA WB 5 NOAA NWS 39 Local Verification
January 11% 10% 16%
February 15% 15% 12%
March 10% 10% 15%
April 12% 12% 13%
May 15% 17% 18%
June 24% 24% 29%
July 25% 24% 24%
August 26% 34% 24%
September 36% 33% 33%
October 31% 29% 26%
November 16% 21% 19%
December 16% 13% 11%

Daytime (12z to 00z)

  1949-1964 1972-1985 1985-1997
Months ESSA WB 5 NOAA NWS 39 Local Verification
January 12% 12% 17%
February 15% 17% 14%
March 12% 11% 17%
April 15% 13% 18%
May 24% 28% 22%
June 36% 41% 44%
July 35% 37% 42%
August 35% 45% 46%
September 40% 46% 42%
October 33% 28% 31%
November 13% 21% 19%
December 12% 12% 13%

Table 15: Comparison of West Palm Beach Climatological
Probabilities of Precipitation

Nighttime (00z to 12z)

  1972-1985 1985-1997
Months NOAA NWS 39 Local Verification
January 17% 20%
February 17% 15%
March 12% 22%
April 10% 17%
May 21% 21%
June 22% 30%
July 25% 22%
August 26% 31%
September 33% 39%
October 22% 25%
November 24% 19%
December 18% 13%

Daytime (12z to 00z)

  1972-1985 1985-1997
Months NOAA NWS 39 Local Verification
January 17% 24%
February 21% 19%
March 13% 26%
April 16% 22%
May 31% 22%
June 37% 43%
July 34% 37%
August 40% 40%
September 44% 42%
October 27% 29%
November 24% 21%
December 19% 15%

Table 16: Comparison of Key West Climatological
Probabilities of Precipitation

Nighttime (00z to 12z)

  1972-1985 1985-1997
Months NOAA NWS 39 Local Verification
January 12% 14%
February 14% 10%
March 8% 13%
April 10% 11%
May 17% 17%
June 23% 23%
July 21% 21%
August 31% 25%
September 29% 35%
October 18% 26%
November 15% 13%
December 14% 13%

Daytime (12z to 00z)

  1972-1985 1985-1997
Months NOAA NWS 39 Local Verification
January 11% 13%
February 13% 9%
March 7% 12%
April 10% 12%
May 13% 13%
June 21% 24%
July 26% 27%
August 32% 31%
September 33% 38%
October 17% 25%
November 15% 15%
December 10% 11%
References
Barker, Timothy W., 1987: AEV Local Verification for Aviation, Precipitation, and Temperature Programs: AV, REL, TEM. Western Region Computer Programs and Problems, NWS WRCP-No. 42, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 33pp.

Hughes, Lawerence A., 1980: Probability Forecasting - Reasons, Procedures, Problems, NOAA Technical Memorandum NWS FCST 24, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 84 pp.

Jensenius, John S. Jr. and Erickson, Mary C., 1987: Monthly Relative Frequencies of Precipitation for the United States for 6-, 12- and 24-H Periods, NOAA Technical Report, NWS 39, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 262 pp.

Jorgensen, Donald L., 1967: Climatological Probabilities of Precipitation for the Conterminous United States. ESSA Technical Report WB-5, Environmental Science Services Administration, U.S. Department of Commerce, 60 pp.

Naber, Pamela S. and Smith, Daniel L., 1983: Evaluation of Point Precipitation Probability Forecasts Using Radar Estimates of Rainfall Areal Coverage, NOAA Technical Memorandum NWS SR-108, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 13 pp.

Pifer, Bob E. and Haydu, Kenneth J., 1990: Utiziling the AEV Program Output in the WSFO Public Forecast Program.

Smith, Daniel L., 1977: An Examination of Probability of Precipitation Forecasts in Light Rainfall Areal Coverage, NOAA Technical Memorandum NWS SR-89, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 20 pp.

Smith, Daniel L. and Smith, Matthew, 1978: A Comparison of Probability of Precipitation Forecasts and Radar Estimates of Rainfall Areal Coverage, NOAA Technical Memorandum NWS SR-96, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 17 pp.


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