An example of how you might use standardized anomalies to make a forecast.

Pattern recognition remains an important component of predicting extreme rainfall events in the mountains along the Pacific coast of North America.  The 500-hPa geopotental height and associated anomaly pattern is very similar for all heavy rainfall events with the primary difference being associated with the location of negative anomaly associated with the trough and the positive anomaly to the southeast.  Note how similar the anomaly pattern associated with the heavy precipitation events in the Pacific Northwest (below right) to the pattern associated with heavy events in northern California (below right) at the beginning of the period of heavy precipitation. These similarities suggest that once a forecaster is able to recognize the ingredients associated with heavy rainfall in one place along the west coast, he or she should be able to translate that knowledge to enable them to identify possible extreme events in other places along the west coast.

Composite mean 500-hPa departure from normal (positive departures are solid, negative departures are dashed, contour interval=3 dam). Shaded areas are the 95% and 99% probably that the composite belongs to a distinct population from climatology.

Pacific Northwest composite

Northern California composite

From Lackmann and Gyakum 1999

Composite mean 500-hPa normalized departures  from normal.   Unit is 0.3 standard deviations.  Negative values are below normal heights,  positive are above normal heights.  From Junker et al.  2007.

Now we’ll attempt to apply pattern typing and the use of normalized anomalies to forecast a rainfall event over the Pacific Northwest.  The first step is to compare the forecast geopotential height field to the composite for heavy events over that area.  Note the similarities between the GFS forecast 500-hPa geopotential height field to the composite (below).  Both exhibit a fairly strong trough in the height field over the Gulf of Alaska and distinct ridging over California. 

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Composite mean 500-hPa height (solid) and sea level pressure (dahsed , every 4 hPa) at the beginning of the period of heavy precipitation over the Pacific Northwest.

12-hr GFS forecast of 500-hPa geopotential height and vorticity valid 1200 UTC 6 Nov. 2006

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12-hr GFS forecast mslp and 100-500-hPa thickness (dashed) valid 1200 UTC 6 Nov. 2006

Also note the basic look of the forecast mslp pattern with both the surface low position in the Gulf of Alaska and the ridge axis extended from California west-southwest well into the Pacific and compare it to the composite (dashed line, above left).  The axis of the area of strongest surface pressure gradient is also similar. However,  there is a notable difference,  the gradient is much stronger in the forecast than in the Lackmann et al. composite.

In their article,  they defined a heavy rainfall day as one in which Seattle (SEA), Olympia (OLM) and Stampede Pass (SMP), WA and Astoria (AST), OR all received 0.50 inches of rain. Heavy but certainly not extreme precipitation.  The surface pressure gradient suggests that the precipitation might end up being considerably heavier than that.  The long fetch implied by the pressure gradient also argues that a strong low level jet may help pull a plume of tropical moisture east-northeastward. 

12-hr GFS forecast of PW and 850-hPA winds valid 1200 UTC 6 Nov. 2006

24-hr GFS forecast of PW and 850-hPA winds valid 0000 UTC 7 Nov. 2006

The GFS forecasts of PW and 850-hPa winds indicate there is an impressive fetch of deep moisture and that there is definitely and atmospheric river associated with the event.  One way to check if the model appears correct is by accessing the CIRA blended TPW product at

http://amsu.cira.colostate.edu/TPW/global.htm. During this case,  the blended product supported the model forecast PWs.  The “pineapple express” or atmospheric river was going to be a player in the forecast.

 

The strong 850-hPa winds coupled with the high PW suggest that higher than normal 850-hPa and 850-700-hPa moisture flux is present.  

 

 

 

 

 

 

 

 

 

An experienced forecaster would probably recognize that there was above normal PWs within this river but he or she still might not have an objective way of knowing how often such a plume occurs or how uncommon such high PWs are.  The individual would have an even tougher time assessing a less commonly used diagnostic tool like moisture flux.  Standardized anomalies offer a way of assessing how often the values of a particular meteorological field that are being forecast by the numerical models is present providing that the model has not observable bias in predicting that particular field. 

Mean distribution of vertical profile of moisture flux for Nov.-Jan. at Oakland during storm events in the Sierra. 

From Pandey et al. 1999

The figure at left illustrates the importance of low level moisture flux in modulating the precipitation in the Sierra Nevada mountains of California.  It also suggests that the largest differences in moisture flux for different type of events is at or just below 800-hPa.  The Pandey research suggests that moisture flux modulates orographic precipitation along the mountains of the west coast.

12-36 hr QPF from the NAM model, scale in inches at left. 

12-36 hr QPF from the GFS model.

Both the NAM and GFS predicted a significant rainfall event, however, the areal distribution of the rainfall differed between the models.  The model with the better horizontal resolution of the terrain predicted less rain then the coarser resolution GFS.  Both models predicted a relatively uncommon event but neither predicted amounts that suggested record rainfall might occur. 

SREF ensemble mean PW (brown lines, in inches) and standardized PW anomaly (dashed red) valid 1200 UTC 6 Nov 2006

SREF ensemble mean PW (brown lines, in inches) and standardized PW anomaly (dashed red) valid 0000 UTC 7 Nov 2006

SREF ensemble mean PW (brown lines, in inches) and standardized PW anomaly (dashed red) valid 1200 UTC 7 Nov 2006

The SREF ensemble mean forecast of of a  standardized PW anomaly of greater than 3 standard deviations (SD) is impressive since ensemble means average values so small differences in the location of the PW axis between the members tend to produce a broader moisture band and with lower maximum precipitable water than the individual members.  Therefore,  the high standardized anomalies suggest that there was strong agreement between the SREF members as to the location and movement of the band.  The 3 SD anomaly or greater PW anomalies also indicate that over 99 percent of time the observed precipitable water is lower than is being forecast suggesting that the PWs being forecast are in the top 1% of events occurring during the same time of year.  

SREF 850-hPa moisture flux (g/kg) ms-1 and standardized magnitude of moisture flux anomaly valid 1200 UTC 6 Nov. 2006.

SREF 850-hPa moisture flux (g/kg) ms-1 and standardized magnitude of moisture flux anomaly valid 0000 UTC 7 Nov. 2006.

SREF 850-hPa moisture flux (g/kg) ms-1 and standardized magnitude of moisture flux anomaly valid 1200 UTC 7 Nov. 2006.

The SREF ensemble mean 850-hPa moisture flux anomalies are even more impressive reaching over 5 standard deviations.  Such a high standardized anomaly suggests that November observed moisture flux has rarely, if ever,  exceeded the forecast values since 1950. Unless the SREF ensemble mean forecast of moisture flux has a high bias,  this has the potential to possibly be a rare event.  Such a slow moving moisture flux axis with such anomalously high moisture argues that this event might have the potential to be a historic one.