LONG-LEAD FORECAST TOOL DISCUSSION AND ANALYSIS (REVISED 11/01) 

FORECAST TOOLS:

THE CMP IS AN ENSEMBLE MEAN FORECAST OF A SUITE OF 20 GCM RUNS 
FORCED WITH TROPICAL PACIFIC SSTS PRODUCED BY A COUPLED OCEAN-
ATMOSPHERE DYNAMICAL MODEL.  THE CMP SKILL HAS BEEN ESTIMATED 
THROUGH THE USE OF 45 YEARS OF SIMULATIONS USING THE NCEP 
CLIMATE GCM FORCED BY SPECIFIED OBSERVED SSTS.  THE SKILL OF THE 
CMP FORECASTS DEPENDS HEAVILY ON ENSO - BEING ALMOST ENTIRELY 
ASSOCIATED WITH EITHER COLD OR WARM EPISODES.  THE CMP FORECASTS 
ARE AVAILABLE ONLY FOR LEADS 1 THROUGH 4 FOR THE LOWER 48 STATES 
AND ALASKA.  BEGINNING IN MARCH 2000 - A NEW VERSION OF THE 
COUPLED MODEL - DESIGNATED AS CMS - THAT INCORPORATES INTER-
ACTION WITH LAND SURFACES VIA SOIL MOISTURE BECAME AVAILABLE.

CANONICAL CORRELATION ANALYSIS (CCA) LINEARLY PREDICTS THE 
EVOLUTION OF PATTERNS OF TEMPERATURE AND PRECIPITATION BASED 
UPON PATTERNS OF GLOBAL SST - 700MB HEIGHT - AND U.S. SURFACE 
TEMPERATURE AND PRECIPITATION FROM THE PAST YEAR FOR THE MOST 
RECENT FOUR NON-OVERLAPPING SEASONS.  CCA EMPHASIZES ENSO 
EFFECTS - BUT ONLY IN A LINEAR WAY - AND CAN ALSO ACCOUNT FOR 
TRENDS - LOW FREQUENCY ATMOSPHERIC MODES SUCH AS THE NORTH 
ATLANTIC OSCILLATION (NAO) AND OTHER LAGGED TELECONNECTIONS IN 
THE OCEAN-ATMOSPHERE SYSTEM.  CCA FORECASTS ARE AVAILABLE FOR 
ALL 13 FORECAST PERIODS FOR THE LOWER 48 STATES - HAWAII - 
AND ALASKA.

COMPOSITE ANALYSIS PROVIDES GUIDANCE FOR U.S. ENSO EFFECTS BY 
SUPPLYING HISTORICAL FREQUENCIES OF THE THREE FORECAST CLASSES 
IN PAST YEARS WHEN (FOR THE PARTICULAR FORECAST SEASON) THE 
CENTRAL EQUATORIAL PACIFIC WAS CHARACTERIZED BY MODERATE OR 
STRONG LA NINA OR EL NINO CONDITIONS OR NEAR NEUTRAL CONDITIONS 
INCLUDING WEAK EL NINO OR LA NINA STATES.  REGIONS INFLUENCED 
BY ENSO ARE DEFINED BY HISTORICAL FREQUENCIES THAT DIFFER 
SIGNIFICANTLY FROM CLIMATOLOGY.  PROBABILITY ANOMALIES ARE 
ESTIMATED BY THE USE OF HISTORICAL FREQUENCIES TEMPERED BY THE 
DEGREE OF CONFIDENCE THAT WARM - COLD - OR NEUTRAL ENSO 
CONDITIONS WILL BE IN PLACE IN A GIVEN TARGET SEASON.  
VERSIONS OF THE MAPS OF THE HISTORICAL FREQUENCIES USED TO MAKE 
THE FORECASTS CAN BE VIEWED UNDER "U.S. EL NINO IMPACTS" AND 
"U.S. LA NINA IMPACTS" ON THE CPC WEBSITE LOCATED AT 
HTTP://WWW.CPC.NCEP.NOAA.GOV.  A COMPOSITE ANALYSIS OF ALASKAN 
TEMPERATURES IS ALSO AVAILABLE BUT NOT YET PLACED ON THE WEB.

THE OPTIMAL CLIMATE NORMALS METHOD (OCN) PREDICTS T AND P ON 
THE BASIS OF PERSISTENCE OF THE OBSERVED AVERAGE ANOMALIES FOR 
A GIVEN SEASON DURING THE LAST 10 YEARS FOR T - AND THE LAST 15 
YEARS FOR P.  OCN EMPHASIZES LONG-TERM TRENDS AND MULTI-YEAR 
REGIME EFFECTS.  OCN FORECASTS ARE AVAILABLE FOR ALL 13 
FORECAST PERIODS - BUT ARE NOT YET AVAILABLE FOR HAWAII OR FOR 
ALASKAN PRECIPITATION.

A CONSTRUCTED ANALOG ON SOIL MOISTURE (CAS) IS BASED ON 
EMPIRICAL ORTHOGONAL FUNCTIONS (EOF) FROM DATA OVER THE LOWER 48
STATES BEGINNING IN 1932.  THIS TOOL CONSTRUCTS A SOIL MOISTURE
ANALOG FROM A WEIGHTED MEAN OF PAST YEARS.  THE WEIGHTS ARE 
DETERMINED FROM THE SIMILARITY OF SOIL MOISTURE CONDITIONS IN
PRIOR YEARS TO A COMBINATION OF RECENTLY SOIL MOISTURE OBSERVA-
TIONS AND A MEDIUM RANGE FORECAST OF SOIL MOISTURE OUT TO 14 
DAYS BASED ON MRF TEMPERATURE AND PRECIPITATION FORECASTS. THEN
THE TEMPERATURE AND PRECIPITATION OBSERVED IN SUBSEQUENT SEASONS
IN THOSE PAST YEARS ARE WEIGHTED IN THE SAME PROPORTION TO 
PRODUCE A FORECAST THAT IS CONSISTENT WITH CURRENT SOIL MOISTURE
CONDITIONS.  ALTHOUGH AVAILABLE THROUGHOUT THE YEAR - THE CAS IS
USED ONLY DURING THE WARM HALF OF THE YEAR FROM APRIL TO 
SEPTEMBER AND FOR THE SHORTER LEADS WHEN THEIR EFFECTS ARE THE 
MOST PRONOUNCED AND SKILLFUL.

A SCREENING MULTIPLE LINEAR REGRESSION (SMLR) TOOL IS USED TO 
EXTRACT INFORMATION FROM A VARIETY OF SOURCES TO PRODUCE A 
FORECAST FOR SEASONAL AND MONTHLY TEMPERATURE AND PRECIPITATION.
SMLR USES THE SAME PREDICTOR FIELDS AS FOR CCA BUT IS APPLIED TO
SINGLE STATIONS RATHER THAN MULTI-STATION ANOMALY PATTERNS AS IS
DONE IN CCA.  ADDITIONALLY - SMLR USES THE TWO WEEK MRF-BASED 
SOIL MOISTURE FORECAST AS A PREDICTOR.  THE SMLR FORECAST 
REPLACES THE SMT TOOL USED PRIOR TO MARCH 2000 - SINCE IT NOW 
INCLUDES THE SOIL MOISTURE AS A CANDIDATE PREDICTOR.  

FORECAST SKILL:

PREDICTIVE ACCURACY IN THE LOWER 48 STATES FOR TEMPERATURE 
PEAKS IN THE LATE WINTER WITH A SECONDARY PEAK IN THE LATE 
SUMMER - AND IS LOWEST IN THE LATE SPRING AND LATE FALL.  
ALASKAN TEMPERATURE SKILL IS HIGHEST IN THE EARLY WINTER AND 
ALSO GOOD IN EARLY SUMMER AND IS LOWEST IN EARLY FALL FOR CCA.  
THE CMP IS MOST SKILLFUL IN ALASKA FOR THE FALL SEASON.   

FOR ALL MODELS PRECIPITATION FORECASTS ARE GENERALLY LESS 
SKILLFUL THAN TEMPERATURE -- WITH MARGINAL SKILL FOR ALL TOOLS 
EVEN IN THEIR BEST SEASONS AND LOCATIONS UNDER NORMAL 
CIRCUMSTANCES.  HOWEVER WHEN STRONG EL NINO OR LA NINA 
CONDITIONS ARE PRESENT - PRECIPITATION SKILL CAN BE AS HIGH AS 
TEMPERATURE SKILL FOR COOL SEASON FORECASTS FOR A NUMBER OF 
AREAS OF THE U.S. - INCLUDING THE SOUTHERN THIRD - THE NORTHERN 
ROCKIES - THE HIGH PLAINS AND THE OHIO VALLEY.  STRONG LA NINA 
CONDITIONS IMPLY THE POSSIBILITY OF MODERATE PRECIPITATION 
SKILL FOR SOME PARTS OF THE WARM SEASON AS WELL.  

THE CONSTRUCTED ANALOG FORECAST FROM SOIL MOISTURE (CAS) GIVES 
HIGHEST SKILL FOR TEMPERATURE FROM APRIL THROUGH SEPTEMBER - 
WITH PEAK SKILL IN EARLY SUMMER.  THE MOST SKILLFUL SEASONS 
FOR PRECIPITATION FORECASTS ARE SON THROUGH JFM FOR OCN 
PREDICTIONS - AND THE LATE WINTER FOR THE OTHER TOOLS.  
ALASKAN SKILL PEAKS IN THE LATE FALL FOR BOTH CCA AND THE CMP.  

THE SCREENING MULTIPLE LINEAR REGRESSION (SMLR) TOOL HAS SKILL 
CHARACTERISTICS SOMEWHAT SIMILAR TO CCA - BUT SINCE IT IS 
DESIGNED TO PREDICT FOR INDIVIDUAL STATIONS AND REGIONAL 
CLIMATE DIVISIONS IT MAY DO BETTER THAN CCA IN SMALLER REGIONS 
HAVING UNIQUE RELATIONSHIPS SUCH AS THOSE CAUSED BY LOCAL TER-
RAIN - ADJACENT WATER BODIES - OR DEVELOPING URBAN HEAT ISLANDS. 

FORECAST FORMAT: 

FORECASTS ARE EXPRESSED AS THE PROBABILITY ANOMALY OF THE 
OBSERVATION OF MEAN TEMPERATURE (TOTAL PRECIPITATION) FALLING 
INTO THE MOST LIKELY OF THREE CLASSES - EITHER ABOVE - NEAR - 
OR BELOW NORMAL (MEDIAN).  CLASSES ARE DEFINED BY LIMITS THAT 
DIVIDE THE 1961-1990 CLIMATOLOGICAL DISTRIBUTION INTO THIRDS.  
THUS EACH CLASS HAS A CLIMATOLOGICAL CHANCE OF OCCURANCE OF 
33.3%.  THE FORECAST PROBABILITY ANOMALY IS THE DIFFERENCE 
BETWEEN THE ACTUAL FORECAST PROBABILITY OF THE VERIFYING 
OBSERVATION FALLING IN A GIVEN CATEGORY AND ITS CLIMATOLOGICAL 
VALUE OF 33.3%  PROBABILITY ANOMALY CONTOURS ARE DRAWN AT 10% 
ANOMALY INTERVALS WITH A SUPPLEMENTAL CONTOUR AT 5% TO HELP 
DEFINE THE AREAS OF ONLY WEAK SIGNAL. 

A FORECAST PROBABILITY ANOMALY OF EITHER ABOVE OR BELOW NORMAL 
IN THE THREE-CLASS SYSTEM IMPLIES A CORRESPONDING REDUCTION IN 
THE PROBABILITY OF THE OPPOSITE CLASS AND A FIXED PROBABILITY 
(AT 33.3%) OF THE NEAR NORMAL CLASS FOR PROBABILITY ANOMALIES 
UP TO 30%.  FOR PROBABILITY ANOMALIES GREATER THAN 30% OF ABOVE 
OR BELOW NORMAL THE PROBABILITY OF THE OPPOSITE CLASS IS FIXED 
AT 3.3% (A -30% ANOMALY) AND THE PROBABILITY OF THE NEAR NORMAL 
CLASS IS REDUCED BY THE EXCESS FORECAST PROBABILITY ANOMALY 
OVER 30%.  NOTE THAT THIS IS ONLY A CRUDE APPROXIMATION OF THE 
TRUE PROBABILITY OF THE NON-SPECIFIED CLASSES AND IS GENERALLY 
LESS ACCURATE FOR EXTREME SHIFTS (20% OR MORE) IN THE 
PROBABILITY ANOMALY OF THE MOST LIKELY CLASS. 

EXAMPLES:  FORECAST PROBABILITY ANOMALIES OF 20%, 30% AND 40% 
FOR ABOVE NORMAL IMPLY PROBABILITIES FOR ALL THREE CLASSES 
(ABOVE - NEAR - BELOW) OF 53.3% - 33.3% - 13.3% --- 63.3% - 
33.3% - 3.3% AND 73.3% - 23.3% - 3.3% RESPECTIVELY.

OCCASIONALLY THE FORECAST CALLS FOR AN INCREASED CHANCE OF THE 
OBSERVATION FALLING IN THE MIDDLE CLASS.  WHEN THIS OCCURS - 
HALF OF THE INCREASED PROBABILITY OF THE MIDDLE CLASS IS 
SUBTRACTED FROM EACH OF THE EXTREMES. 

FOR USERS WHO PREFER A 2-CLASS SYSTEM TO THE CURRENT 3-CLASS 
SYSTEM - CONVERSION TO A 2-CLASS SYSTEM CAN BE DONE VERY SIMPLY 
BY ALTERING 50-50 CLIMATOLOGICAL PROBABILITIES FOR THE BELOW 
VERSUS ABOVE NORMAL TWO CLASS CATEGORIES BY THE PROBABILITY 
ANOMALY SEEN ON OUR MAPS.  FOR EXAMPLE -- A 20% ANOMALY TOWARD 
ABOVE NORMAL W0ULD CONVERT TO AN 70% CHANCE FOR ABOVE AND A 30% 
CHANCE FOR BELOW IN A 2-CLASS SYSTEM - A 30% ANOMALY TO 80 AND 
20% - AND A 40% TO 85 AND 15%. 

FUTURE REVISIONS OF THIS MESSAGE WILL BE ISSUED WHENEVER 
SIGNIFICANT CHANGES IN THE AVAILABLE FORECAST TOOLS ARE MADE.

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