NOAA Technical Memorandum NWS WR-268

NOAA Technical Memorandum 

NWS WR-268

Prediction of Heavy Snow Events in the Snake River Plain Using Pattern 

Recognition and Regression Techniques

Thomas Andretta and William Wojcik 

National Weather Service Office 

Pocatello, Idaho

October 2003 

ABSTRACT

This study examines the heavy snow climatology of the Snake River Plain of eastern Idaho. Heavy snow is defined 

as 6 inches or more of snowfall in a 24 hour period. This climatology is based on synoptic patterns collected from 

National Weather Service (NWS) climate observing stations available from the National Climatic Data Center 

(NCDC) archives covering the historical period from 1949 to 1997. Identification of two synoptic-scale patterns 

conducive to heavy snow are examined for the region of study. The manuscript uses analog and multiple linear 

regression techniques to derive equations to estimate mean snowfall amounts for the Snake River Plain which 

includes these subregions: Upper Snake River Plain, Lower Snake River Plain, and eastern Magic Valley. Based on 

the patterns, the snowfall equations are expanded as a function of longitude, latitude, and elevation. Finally, a 

heavy snow event that occurred on 15 April 2002 is selected to test the accuracy of the regression equations. 

1. Introduction

Forecasting heavy snow in the valleys of the western United States remains one of the most rewarding challenges 

for operational meteorologists. While there is an abundance of research on forecasting spatial distributions of snow 

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in the eastern and central United States, the use of circulation patterns and other synoptic indicators in the 

Northwest United States remains problematic (Terry 1992). However, magic charts (Chaston 1989) describing 

overlapping regions of strong vertical motion and cold 700 mb temperatures, Q vector convergence of deep layer 

relative humidity (Mathewson 2000), and favorable upper-level jet streak locations (Blank 1989) were tools 

developed by some forecasters to predict spatial distributions of heavy snow. Richmond (1992) examined the 

synoptic signatures conducive to heavy snowfall in Missoula, MT based on a 10 storm climatology. A similar 

technique was employed by Tardy (2002) for forecasting heavy snow amounts in the Sierra, Nevada region. In this 

study, both analog charts and regression techniques will be used as climatological indicators to predict heavy snow 

in the Snake River Plain of eastern Idaho.

a. Topography

Fig. 1a shows a map of the Northwest United States with the region of study (red inset region). City identifiers and 

points of reference in Idaho and surrounding states highlighted in this study are indicated in Figs. 1b and 1d. 

Contrasting with the width of the Snake River Plain (~ 100 km) (all heights MSL), the elevation of the plain rises 

gently in a leftward curving arc in a southwest to northeast orientation from roughly 1200 m in the eastern Magic 

Valley to 1600 m in the Upper Snake River Plain. The arc terminates in the shape of a fish hook at the Upper Snake 

River Plain (Figs. 1c, 1d). West of the “fish hook”, the central mountain valleys drain onto an expansive desert (Arco 

Desert) which varies in elevation from 1500 to 1900 m. The Snake River Plain is bounded by raised topography to 

the south and east ranging in elevation between 1700 and 2000 m. 

b. Climatology and Methods

From a climatological standpoint, the periodic topographic intersection of channeled northwest flow from the central 

mountain valleys and downslope low-level northeast flow in the Upper Snake River Plain with upslope low-level 

southwesterly winds in the Lower Snake River Plain is conducive to localized boundary layer convergence, leading 

to short duration snow events (~ 6 to 10 hrs) during the late fall and winter months (Andretta and Hazen 1998; 

Andretta 2003). On the other hand, major low pressure systems contribute to more longer-lived (~ 12 to 24 hrs) 

snowstorms over the valleys of eastern Idaho when cold frontal passages and Pacific cyclogenesis peak 

harmonically (Andretta 1999). This study examines the synoptic patterns that produce heavy snow (defined as 6 

inches or more of snow in a 24 hour period) and derives equations to predict the mean snowfall amounts for the 

Snake River Plain using synoptic pattern matches and multiple linear regression techniques. These methodologies 

are applied to a heavy snow event that occurred on 15 April 2002.

c. Case Study 

The 15 April 2002 snowstorm is selected in this study for several reasons. It ranks as the 8th greatest 24 hour 

snowfall ever recorded at the Pocatello WSO Airport and the 3rd greatest April snowfall ever measured for the 

station. In addition, the snowfall was also very persistent (~ 9 to 12 hrs) over a large area with accumulations over 

the entire Snake River Plain of at least 6 inches, peaking at 10 to 16 inches (~ 30% of the annual total snowfall 

normals) at some locations in the Upper Snake River Plain. From a forecasting perspective, the model grids 

performed very poorly in the prediction of snowfall amounts in the Snake River Plain. The high resolution MESO 

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ETA model run cycles initialized at 0000 UTC and 1200 UTC 15 April 2002 underestimated the rapid deepening of 

the surface low over northern Utah by 5 to 7 mb in the late morning hours of the event and did not indicate the cold 

air advection in the lowest 1500 ft in the forecast soundings.

2. Methodology

Table 1 lists the 19 National Weather Service (NWS) climate stations including their geographical locations used in 

this study. A Visual Basic program collected the NWS climate record snowfall amounts (historical records from 1899 

to 2001 for all stations) and extracted only those snow events (1949 to 1997) that amounted to 6 inches or more. 

Tables 2a and 2b list these 28 heavy snow events with the individual station snow amounts and the average snow 

amount per episode. Note that the event date is given as the reporting date of the observation and may actually be 

the day after the heavy snow event occurred. A further examination indicated that the heavy snow was clustered 

around NWS stations in similar geographical regions. The NWS historical synoptic records (1899 to 1994) on a CDROM entitled, Global Historical Fields, were examined to study the weather patterns that produced the heavy snow 

accumulations on those dates. These synoptic fields were based on radiosonde data for 0000 UTC and 1200 UTC 

and included: mean sea-level pressure (mb), 700 mb height (m) and temperature (deg C), 500 mb height (m) and 

temperature (deg C), and 300 mb height (m) and temperature (deg C). Unfortunately, other parameters like wind, 

vertical velocity, relative humidity, and stability were not available on the CD-ROM for this study. Historical records 

used in this study covered the period from 1949 to 1997. Finally, a regression formula was run on 16 of the 28 

events to check for specific correlated synoptic fields that could produce the heavy snow spatial distributions. 

3. Precipitation and Snowfall Climatology

a. Precipitation Climatology

As Figs. 1c and 1d indicate, the average annual precipitation totals (based on 1971 to 2000 NCDC normals) are 

correlated with terrain height. The Snake River Plain receives approximately 8 to 12 inches of precipitation per year 

with higher amounts in the mountains surrounding the valley walls (Sagendorf 1996; Andretta 1999). The figures 

indicate that locally higher valley amounts (~ 12 to 14 inches per year) are situated between Richfield (RIC) and 

Carey (CAR), near Massacre Rocks State Park (MAS), and near Rexburg Ricks College (RXE) in the eastern part 

of the Upper Snake River Plain.

b. Snowfall Climatology

Based on the NCDC monthly normals and period of record for each station, the snowfall climatology of the Snake 

River Plain is characterized by maxima during December and January with a second weaker maximum in February 

or March for all the NWS stations. Occurrences of snowfall in the plain between June and September are very rare. 

Annual snowfall totals vary from 15 to 25 inches in the eastern Magic Valley to 20 to 35 inches in the Lower Snake 

Plain, with a local maximum of 40 inches at Pocatello WSO Airport (PIH). A sharp gradient in total annual snowfall 

is evident in the Upper Snake River Plain with 35 inches at Idaho Falls FAA Airport (IDA) increasing with elevation 

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to 57 inches at Rexburg Ricks College.

4. Analog Signatures

Fig. 2 displays an example of one synoptic pattern from 1200 UTC 01 December 1982 that produced 6 to 10 inches 

of snow in the Snake River Plain. An intense surface low (~ 984 mb) (Fig. 2a) was located just east of Salt Lake 

City, UT with the 500 mb and 300 mb trough axes (Figs. 2c, 2d) negatively tilted back across western Idaho and 

Oregon. Moreover, Fig. 2b shows a closed 700 mb low center situated over eastern Idaho. This pattern was 

associated with cold air advection snows in eastern Idaho. By contrast, Fig. 3 illustrates a warm air overrunning 

pattern from 0000 UTC 29 December 1992 that produced 6 to 10 inches of snow in the region of study. The deep 

surface low (~ 988 mb) in Fig. 3a was positioned offshore along the coast of Washington and Oregon. The isobaric 

kink extending eastward from the low center suggested that the warm front was oriented across eastern Idaho with 

the Snake Plain in the warm sector of the storm. The 700 mb trough in Fig. 3b was situated off the Washington 

coast. The mid and upper-level trough patterns (Figs. 3c, 3d) were stacked up near the surface low position with 

southwest flow aloft over eastern Idaho. Table 2a and Table 2b summarize the snow events that were associated 

with these two synoptic patterns. The key indicators for the pattern types are listed below:

a. Type COLD Pattern (18 cases)

1) Closed surface low (~ 985 to 1000 mb) over northeast Nevada, northern Utah, southwest Wyoming, or westcentral Colorado 

2) Surface cold front over central and southern Utah (Snake River Plain in cold sector) 

3) 700 mb (~ 0 to -6 deg C) (usually) closed low center over eastern Idaho 

4) 500 mb negatively or neutrally tilted phased trough (~ -25 to -35 deg C) over western Idaho and Oregon 

5) 300 mb negatively or neutrally tilted phased trough over western Idaho and Oregon

b. Type WARM Pattern (10 cases)

1) Closed surface low (~ 990 to 1005 mb) off the coast of Washington and Oregon (low may be elongated and 

extending inland) 

2) Surface warm front over eastern Idaho (Snake River Plain in warm sector) 

3) 700 mb (~ -10 to -15 deg C) (usually) closed low center off coast of Washington and Oregon 

4) 500 mb neutrally or positively tilted phased trough axis near 700 mb trough position 

5) 300 mb neutrally or positively tilted phased trough axis near 700 mb trough position

c. Type Frequency

As indicated in Tables 2a and 2b, the Type COLD pattern occurred most (18 / 28 = 64%) of the time. Since the 

heavy snow climatology covered the period from 1949 to 1997, an operational meteorologist could expect the Type 

COLD pattern, 18 cases / 48 years = 1 event every 2.7 years and the Type WARM pattern, 10 cases / 48 years = 1 

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event every 4.8 years. Thus, both patterns occurred 28 times / 48 years or 1 pattern every 1.7 years. The frequency 

of the COLD / WARM events for the three subregions were: Upper Snake River Plain (13 / 7), Lower Snake River 

Plain (16 / 9), and eastern Magic Valley (11 / 8).

5. Multiple Linear Regression Technique

Using a multiple variable linear regression algorithm, it was possible to correlate certain synoptic fields that were 

prerequisites for heavy snow events in the Snake River Plain. Events from 1949 to 1962 were excluded from this 

study because of fragmentary radiosonde data and related synoptic fields. Accordingly, applying forward regression 

techniques to 16 out of the 28 cases, the following linear regression model was deduced (Wilks 1995):

a. General Equations

Type COLD and WARM patterns (16 cases): 

M ~ 7.36 + 0.03 MSLP (X) - 0.07 T H7 (BOI) + 0.04 T H7 (RKS) - 0.01 H H5 (Y) (1)

Type COLD pattern (10 cases): 

M ~ 10.58 + 0.12 MSLP (X) + 0.69 T H7 (BOI) - 0.49 T H7 (RKS) - 0.07 H H5 (Y) (2)

Type WARM pattern (6 cases): 

M ~ 13.60 + 0.04 MSLP (X) + 0.05 T H7 (BOI) + 0.49 T H7 (RKS) + 0.04 H H5 (Y) (3)

where: 

M = Mean Snow Amount (inches) 

MSLP = Mean sea-level pressure (mb) 

T = Temperature (degrees Centigrade) 

H = Height (m) 

H7 = 700 mb level 

H5 = 500 mb level 

X = [SLC (Salt Lake City, UT) - LLJ (Challis, ID)] + 

[EKO (Elko, NV) - WEY (West Yellowstone, WY)] 

Y = [BOI (Boise, ID) - RKS (Rock Springs, WY)]

Please see Fig. 1b for the locations of the key stations used in these regression equations. 

b. Regional Equations

Grouping the 16 cases into the regions of study (for both Type WARM and COLD patterns) yielded these equations:

For the Upper Snake River Plain (8 cases): 

M ~ 6.52 + 0.04 MSLP (X) - 0.18 T H7 (BOI) + 0.02 T H7 (RKS) + 0.01 H H5 (Y) (4)

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For the Lower Snake River Plain (9 cases): 

M ~ 7.16 + 0.03 MSLP (X) - 0.17 T H7 (BOI) + 0.12 T H7 (RKS) + 0.01 H H5 (Y) (5)

For the eastern Magic Valley (including the Lower Snake River Plain) (9 cases): 

M ~ 8.34 + 0.06 MSLP (X) - 0.16 T H7 (BOI) + 0.18 T H7 (RKS) + 0.01 H H5 (Y) (6)

where: 

M = Mean Snow Amount (inches) 

MSLP = Mean sea-level pressure (mb) 

T = Temperature (degrees Centigrade) 

H = Height (m) 

H7 = 700 mb level 

H5 = 500 mb level 

X = [SLC (Salt Lake City, UT) - LLJ (Challis, ID)] + 

[EKO (Elko, NV) - WEY (West Yellowstone, WY)] 

Y = [BOI (Boise, ID) - RKS (Rock Springs, WY)]

Please see Fig. 1b for the locations of the key stations used in these regression equations. 

c. Station Equations

A further examination of the heavy snow amounts for the Type COLD and Type WARM patterns yielded these 

equations for the individual NWS climate stations as a function of longitude, latitude, and elevation:

For the Type COLD case (36 cases): 

S(L1, L2, Z) ~ 151.43 - 55.62 cos(L1 + 180) - 173.01 sin(L2) - 0.001 Z + 

0.04 MSLP (X) - 0.04 T H7 (BOI) + 0.02 T H7 (RKS) - 0.03 H H5 (Y) (7)

For the Type WARM case (22 cases): 

S(L1, L2, Z) ~ -73.92 + 101.54 cos(L1 + 180) + 68.07 sin(L2) - 0.001 Z - 

0.10 MSLP (X) - 0.52 T H7 (BOI) + 0.49 T H7 (RKS) + 0.03 H H5 (Y) (8) 

where: 

S = Snow Amount (inches) 

L1 = Longitude (decimal degrees) of NWS station 

L2 = Latitude (decimal degrees) of NWS station 

Z = Elevation (feet MSL) of NWS station 

MSLP = Mean sea-level pressure (mb) 

T = Temperature (degrees Centigrade) 

H = Height (m) 

H7 = 700 mb level 

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H5 = 500 mb level 

X = [SLC (Salt Lake City, UT) - LLJ (Challis, ID)] + 

[EKO (Elko, NV) - WEY (West Yellowstone, WY)] 

Y = [BOI (Boise, ID) - RKS (Rock Springs, WY)]

Please see Fig. 1b for the locations of the key stations used in these regression equations. 

d. Statistical Correlation

Please see Table 3 for a summary of the correlated variables used in the regression output. Table 4 lists the 

pertinent output variables for each of the regression equations including degrees of freedom, correlation coefficient, 

and standard deviation for the predictand snow amounts (Wilks 1995). One noteworthy fact evident in Table 4 is 

that while the overall correlation score was weak ( r = 0.23) for the variables in all 16 cases, the best correlation 

occurred in equations (2) and (3) for each of the pattern types ( r > 0.70). Excluding (5), when the pattern types 

were resolved by geographical region and NWS station location, the correlation coefficients were moderate to 

strong ( r > 0.50).

6. Case Study: 15 April 2002

a. Synoptic Analysis

The FNL (final) model data is a product of the Global Data Assimilation System (GDAS), which uses the Global 

spectral Medium Range Forecast model (MRF) to assimilate multiple sources of measured data and forecast 

meteorology. The FNL model data used in this study was collected from the National Oceanic and Atmospheric 

Administration (NOAA) Idaho National Engineering and Environmental Laboratory (INEEL) daily repository. As Fig. 

4a indicates, an intense 990 mb surface low developed near Salt Lake City, UT (SLC) at 1800 UTC 15 April 2002. 

The 700 mb pattern was deep with the low pressure center over the Snake Plain with temperatures in the -10 to +6 

deg C band from Boise, ID (BOI) to Rock Springs, WY (RKS) (Fig. 4b). The upper-level charts (Figs. 4c, 4d) show 

the 500 and 300 mb troughs aligned over eastern Washington and eastern Oregon during the afternoon hours. 

These factors suggested the synoptic evolution of a Type COLD pattern heavy snow event for the Snake River 

Plain.

b. Mesoscale Analysis

Both the Boise, ID (BOI) (Fig. 5a) and Salt Lake City, UT (SLC) (Fig. 5b) observed soundings for 1200 UTC 15 April 

2002 indicated a deep layer of moisture from 600 to 300 mb. At 1800 UTC, the regional (Fig. 6a) and mesonet (Fig. 

6b) charts indicated a warm front extending from a 986 mb surface low over northern Utah with temperatures of 70 

to 75 deg F near SLC; temperatures north of the frontal boundary were between 30 and 38 deg F over the Lower 

Snake River Plain. A 998 mb surface low was located over central Idaho with a tight isobaric gradient and 

southwest flow in the Snake River Plain. The surface observations indicated snow falling at the Pocatello WSO 

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Airport (PIH) and Idaho Falls FAA Airport (IDA) as the warm air from northern Utah was advected northward and 

climbed over the colder air in place over eastern Idaho. The NOAA Air Resources Laboratory/Field Research 

Division (ARL/FRD) mesonet profiler (located about 10 km northwest of Big Southern Butte (BIG); elevation ~ 5200 

ft MSL) showed temperature decreasing with height from the surface to 1200 ft AGL (Fig. 6c). The KSFX WSR-88D 

composite reflectivity chart (Fig. 6d) indicated a large field of 20 to 35 dBZ over the Snake River Plain with localized 

40 to 45 dBZ returns just north of the radar tower and extending to PIH. 

By 2100 UTC, the 985 mb surface low over SLC had extended northeast to near RKS with widespread snow at 

most observation stations in the Snake River Plain (Figs. 7a, 7b). The ARL/FRD profiler in Fig. 7c indicated a 

cooling of 4 to 5 deg F from the surface up to 1000 ft AGL from 1800 to 2100 UTC. A rapid decrease of 

temperatures with height above 1700 ft AGL was evident, possibly indicative of the 700 mb trough passage (Fig. 

4b) and eastern Idaho located in the cold sector of the deepening surface low. There was little change to the radar 

echo morphology and intensity (Fig. 7d). 

Later that afternoon, at 0000 UTC 16 April 2002, the surface low center (985 mb) had moved very slowly to near 

RKS as snowfall persisted in the Snake River Plain (Figs. 8a, 8b). The NOAA ARL/FRD mesonet profiler indicated a 

temperature lapse rate of -9 deg F / 3500 ft with marked cooling above 2500 ft AGL versus 3 hours earlier (Fig. 8c). 

Cyclogenesis persisted over western Wyoming border but the radar echoes had weakened over the Snake Plain as 

dry air advection developed in the eastern Magic Valley (Figs. 8b, 8d). The steady snow caused by the synopticscale forcing tapered off by 0400 UTC 16 April 2002.

c. Cross Sectional Analysis 

The BUFKIT (Mahoney et al 1998) hourly data from the ETA model provided supplementary information regarding 

the heavy snowfall that occurred in the Snake River Plain. Figs. 9a and 9b illustrate the 24 hour time cross sections 

for vertical velocity (solid lines) and relative humidity (shaded regions) above 85% starting at 1200 UTC 15 April 

2002 for IDA and PIH, respectively. There was a deep layer of moisture from the surface to about 600 mb in both 

time series. Note the +15 to +20 ubar sec -1 vertical motion fields centered between 600 and 500 mb from 1700 

UTC 15 April 2002 to 0300 UTC 16 April 2002 in both instances.

d. Regression Analysis

The regression equations were used to estimate mean snowfall amounts for the different regions of the Snake River 

Plain. Accordingly, substituting the various parameters from the 1800 UTC 15 April 2002 FNL forecast (Figs. 4a, 4b, 

and 4c) and applying (2), (4), (5), (6), and (7) yielded the following results:

MSLP (X) = -9.0 mb 

T H7 (BOI) = -10.0 deg C 

T H7 (RKS) = +6.0 deg C 

H H5 (Y) = -150 m 

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For the Type COLD pattern: 

M ~ 10.58 + 0.12 MSLP (X) + 0.69 T H7 (BOI) - 0.49 T H7 (RKS) - 0.07 H H5 (Y) (2) 

M ~ 10.58 - 1.08 - 6.90 - 2.94 + 10.50 ~ 10.2 inches 

For the Upper Snake River Plain: 

M ~ 6.52 + 0.04 MSLP (X) - 0.18 T H7 (BOI) + 0.02 T H7 (RKS) + 0.01 H H5 (Y) (4) 

M ~ 6.52 - 0.36 + 1.80 + 0.12 - 1.50 ~ 6.6 inches

For the Lower Snake River Plain: 

M ~ 7.16 + 0.03 MSLP (X) - 0.17 T H7 (BOI) + 0.12 T H7 (RKS) + 0.01 H H5 (Y) (5) 

M ~ 7.16 - 0.27 + 1.70 + 0.72 - 1.50 ~ 7.8 inches

For the eastern Magic Valley (including the Lower Snake River Plain) 

M ~ 8.34 + 0.06 MSLP (X) - 0.16 T H7 (BOI) + 0.18 T H7 (RKS) + 0.01 H H5 (Y) (6) 

M ~ 8.34 - 0.54 + 1.60 + 1.08 - 1.50 ~ 9.0 inches

For the Type COLD pattern:

S(L1, L2, Z) ~ 151.43 - 55.62 cos(L1 + 180) - 173.01 sin(L2) - 0.001 Z + 

0.04 MSLP (X) - 0.04 T H7 (BOI) + 0.02 T H7 (RKS) - 0.03 H H5 (Y) (7)

Idaho Falls FAA Airport: 

S ~ 151.43 - 20.87 - 118.68 - 4.74 - 0.36 + 0.40 + 0.12 + 4.50 ~ 11.8 inches (7)

Pocatello WSO Airport: 

S ~ 151.43 - 21.16 - 117.00 - 4.45 - 0.36 + 0.40 + 0.12 + 4.50 ~ 13.5 inches (7)

Burley FAA Airport: 

S ~ 151.43 - 22.15 - 116.48 - 4.16 - 0.36 + 0.40 + 0.12 + 4.50 ~ 13.3 inches (7)

The forecast amounts generated from the regression equations agreed favorably with the observations. The mean 

snowfall over the Snake River Plain for the event was ~ 12.0 inches, closely matching the results in (2). Weather 

spotters recorded 10 to 16 inches of snow in the Upper Snake River Plain with 8 to 12 inches in the eastern Magic 

Valley and Lower Snake River Plain. However, approximately 1 to 3 inches of these snowfall totals were associated 

with a non-synoptic scale low-level convergence zone that formed in the Snake River Plain in the late night hours 

on 15 April 2002 (Andretta 2003). Note that the snowfall amounts obtained from the station equation in (7) 

superceded the regional equation estimates. 

7. Future Considerations

The authors plan to develop a computer application to assist operational forecasters in predicting heavy snowfall for 

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the Snake River Plain. The regression equations will be applied to high resolutions of the MESO ETA or MM5 

model with output generated in a time step dependent tabular format. The output tables may be used to supplement 

traditional numerical (e.g., FWC, MAV, MET, and MEX) forecast guidance. Hopefully, subsequent winters will afford 

an opportunity to test the veracity of the WARM regression equations with a case study. 

8. Conclusions

The heavy snowfall climatology of the Snake River Plain was explored focusing on analog pattern matches and 

regression forecasting techniques to derive equations for heavy snow episodes in the Upper Snake River Plain, 

Lower Snake River Plain, and eastern Magic Valley. This climatology was based on 19 NWS climate stations based 

on historical records from 1949 to 1997. Two synoptic-scale patterns were identified, Type COLD and Type WARM, 

which were critical to the development of heavy snowfall in the Snake River Plain. 

A regression model was developed for the entire Snake River Plain based on 16 out of 28 heavy snow events 

featuring three sets of snowfall regression equations. The correlation coefficient for all 16 cases was weak ( r = 

0.23). However, the regression equations dependent on pattern type were derived with strong positive correlation 

coefficients ( r > 0.70). A second set of equations independent of pattern type were developed for the Upper Snake 

River Plain, Lower Snake River Plain, and eastern Magic Valley. These equations yielded weak to moderate 

correlation. A third set of regression equations based on pattern type was derived as a function of longitude, 

latitude, and elevation for individual NWS stations. These equations yielded moderate to strong correlation ( r > 

0.50). Finally, the techniques were applied to the heavy snow episode on 15 April 2002 with favorable agreement 

between the regression forecasts and the observations of snowfall.

9. Acknowledgments 

The authors would like to thank MIC James Meyer and SOO Dean Hazen for proofreading this paper and proving 

helpful comments on the scientific content. A sincere appreciation to the NOAA ARL/FRD and INEEL for providing 

the model and profiler data used in this study.

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