PRECIPITATION PATTERNS IN THE LEE OF THE SANTA CRUZ MOUNTAINS OF CALIFORNIA
Chris Ineich
Writer’s comment: I
first learned about orographic uplift and the rain shadow effect from
watching a TV news weather segment. These con-cepts explained the
dramatic differences in rain totals between the very wet Santa Cruz
Mountains and the comparatively arid Santa Clara Valley. They also
confirmed my own weather observations. I had begun to measure rainfall
with a coffee can and ruler in my backyard in the Santa Cruz Mountains
and noticed the rain totals I collected were consistently greater than
those in the nearby flatlands around the bay. I was convinced my
elevated rain totals resulted from a local orographic effect.
Years later, I came across an article by another young weather
enthusiast that forced me to rethink my assumptions. The author
hypothesized it was possible for the orographic effect to increase
precipitation for a large distance downwind of mountains and offered
observational evidence to support this idea. I was intrigued—this
theory defied everything I had read in textbooks about lee-side rain
shadows. I set up my own rain collection study modeled after the
article’s. I used the statistics I learned in a college course to
analyze the data, and the results were more consistent than I expected.
This project was my first attempt at basic research and broadened my
perceptions of the impacts of mountainous terrain on precipitation
patterns.
—Chris Ineich
Instructor’s comment: One of my favorite things
about English 104E, Writing in the Sciences, is that students can write
about their own research. I was intrigued by Chris’s research on
rainfall patterns. He had read information about rainshadows that
contradicted what he had learned about rainfall patterns. But instead
of dismissing the author’s theories, he decided to test them. To
Chris’s surprise, his results confirmed the research. When I assigned a
report on field research, Chris did some reading on rainfall to put his
work into context then reanalyzed his data. The result is the
analytical report you see here; weather buffs and outdoors people will
find it fascinating.
—Margaret Eldred, English Department
Abstract
The factors influencing precipitation patterns in the lee of the Santa
Cruz Mountains of California were studied. The variables analyzed
included wind speed, wind direction, storm intensity, topography, and
distance downwind from the mountains. Five standard rain gauges were
set up along a SSW-NNE transect from the crest of the northern Santa
Cruz Mountains to approximately eleven kilometers downwind and data
were collected for five major storm events. A strong correlation was
found between precipitation and downwind distance for four of the five
storm events. A somewhat weaker precipitation-distance correlation that
resulted for one precipitation event was likely a result of the showery
nature of the storm and light winds. An index of storm intensity was
developed for the study and a moderately strong correlation was found
between lee-side precipitation totals and storm intensity. High
intensity storms tended to produce smaller declines in precipitation
from mountain to lee region than low intensity rain events. No
relationship was found between lee-side topography and precipitation
patterns.
Introduction
The effects of mountainous terrain on precipitation patterns can be
profound. When moist air is forced to rise over elevated terrain the
resulting cooling reduces the capacity of the air to hold water vapor
and condensation occurs. This process is called the orographic effect
and can result in much elevated precipitation on the windward slopes of
mountains. The enhanced condensation and precipitation on windward
slopes reduces the water vapor load of the atmosphere leading to
reduced precipitation in the “rain shadow” region of the mountain’s
lee.
Scientists have long been fascinated with the impacts of elevated
topography on precipitation patterns. Orographic precipitation
phenomena can certainly be dramatic. The world’s rainiest climates are
found on the windward slopes of major mountain ranges while the most
arid deserts often lie in the lee of the same mountain complexes. With
such a dramatic effect on regional climates and biomes, it is no
surprise that so many researchers have chosen to study this topic.
Atmospheric scientists, hydrologists, ecologists, geographers and soil
scientists have taken great interest in orographic precipitation
processes.
Recent contributions to the study of orographic precipitation have come
from around the world and highlight some of the critical interactions
that occur between moist air masses and complex terrain. Working in
Switzerland, Gysi (1996) found that the distribution of orographically
influenced rainfall was strongly dependent on the direction from which
a storm moved into a region of elevated topography. Those slopes that
faced in the direction of an approaching storm received more rain than
did terrain located downwind.
Another study in England revealed the influence of wind speed on
orographic enhancement with the greatest precipitation events
associated with the strongest winds (Hill, Browning, and Bader, 1981).
A similar study in Scotland verified the relationship between strong
winds and an enhanced orographic effect (Weston and Ray, 1994).
Rainfall increased almost linearly with increasing wind speed over the
first area of high ground encountered in a storm’s path.
Despite decades of intensive research, orographic precipitation
processes remain among the least understood of atmospheric phenomena.
Much of the research has focused on only a few of the world’s most
prominent mountain belts, leaving the vast majority of mountainous
regions unstudied. The potential effects of elevated topography on
precipitation processes are as diverse as the terrain itself, and
findings in one mountain region may not carry over well to another area
of complex terrain. The data gathering process is also hampered by the
inaccessibility of many remote mountainous regions.
The most significant gap in our understanding of orographic
precipitation phenomena concerns that precipitation which falls in the
lee of mountain barriers. Limited data suggest that precipitation
events in the lee of mountain ranges may be even more variable than on
windward slopes, yet precipitation research in these “rain shadow”
regions is particularly sparse.
Only two recent studies have focused on lee-side precipitation. Chater
and Sturman (1998) studied the conditions that favored the “spillover”
of precipitation to the lee of the Southern Alps. The researchers noted
the importance of wind speed, latent instability, and frontal intensity
in determining the significance of lee-side precipitation events.
With limited data, Haugland (1998) concluded that lee-side
precipitation was highly dependent on wind speed and storm intensity.
He found that storms with considerable precipitable water and strong
winds produced major rain totals in lee-side areas because the
moisture-laden clouds were rapidly carried downwind in their
orographically lifted positions.Weak winds and little precipitable
water produced storms that “rained out” on windward slopes, leading to
rapid sinking and drying of the air mass on the lee side.
To test the hypotheses of Haugland and to expand our general
understandings of lee-side precipitation patterns, we conducted a field
observational study of precipitation in the lee of the Santa Cruz
Mountains of California. We examined the influence of several variables
on precipitation events including wind speed and direction, atmospheric
instability, cloud water content, lee-side topography, and distance
from the crest of the mountain barrier. Precise measurements for some
of these variables, such as instability and cloud water content, were
not available and sound approximations were made when necessary. These
are noted in the text.
Study Site
The field data were collected in the lee of the northern Santa Cruz
Mountains, a sub-range of the California Coast Ranges (Figure 1). The
range spans approximately 80 km, from just south of San Francisco to
west of Gilroy, and runs more or less in a north-northwest to
south-southeast direction. To the west of the Santa Cruz Mountains lies
the Pacific Ocean, and to the east is San Francisco Bay in the north
and the Santa Clara Valley in the south. The crest of the range reaches
a maximum elevation of 1137 meters at Loma Prieta near its southern
terminus and averages about 550 meters in height. The elevation of the
crest along the western margin of our study transect is approximately
690 meters.
Despite the modest height of the Santa Cruz Mountains, orographic
enhancement of precipitation over much of the range is substantial and
a pronounced rain shadow exists in its lee. Long-term precipitation
data is limited but suggests that average annual rainfall in the more
orographically favored areas exceeds 1500 mm (Gilliam, 1962). No
long-term rainfall data was available for the segment of the range
considered in this study, but we conservatively estimated it to be
between 1000 and 1300 mm/yr along the crest. Precipitation near San
Francisco Bay, approximately 15 to 20 km downwind from the crest of the
mountains, averages about 500 mm/yr.

Figure 1. Map showing the locations of the rain gauges used in the study:
x1-El Corte de Madera, x2-Ca–ada Road, x3-Pulgas Ridge, x4-Crestview,
x5-Belmont.
An important consideration of the study was the role of lee-side
topography on precipitation patterns in our study region. The lee of
this part of the Santa Cruz Mountains is broken into hills and valleys
that we thought might impact precipitation on a very local scale. Our
study transect traversed the deep valley that marks the course of the
San Andreas fault and climbed over Pulgas Ridge, one of the prominent
ridgelines of the eastern San Francisco peninsula. Our Crestview study
site sits atop the high point of this ridge at approximately 270
meters. East of Pulgas Ridge are several hills of less than 200 meters
height. The northeastern most of our study points, Belmont, was located
among these low hills. Figure 2 shows a topographic cross section of
the study transect and the locations of each of the study sites
relative to the major terrain features.

Figure 2. A topographical profile of the study transect.
Materials and Methods
The design of our study was closely modeled after the work of Haugland
(1998). The materials consisted of five identical standard rain gauges
made by Taylor. The precision of the measurements taken between the
gauges was verified by pouring measured amounts of water among the
gauges and noting the equivalent readings.
A study transect, located along a south-southwest to north-northeast
orientation, was located in the lee of the northern Santa Cruz
Mountains. The orientation was chosen because it parallels the average
direction of the wind during most major storm events in this area.
Because this orientation reflects only the average wind direction
during storms, a certain amount of error was expected in our results
depending on how significantly the winds during particular storm events
deviated from the average.
The five rain gauges were located along the pre-selected route
beginning at the crest of the Santa Cruz Mountains and extending
downwind for approximately 11 kilometers (Figure 1, Table 1). The exact
locations of the rain gauges reflect a compromise between our desire to
maintain the integrity of the study transect, the need to respect
private property rights, and our interest in reducing the risk of
vandalism that would have sacrificed the quality of our results. Four
of the gauges were located within public wildlands in areas we felt
would be well concealed from potential vandals. The fifth gauge was
located in the backyard of the author. Every attempt was made to locate
the gauges away from obstructions that might impact the rain catch
during windy conditions; however, some error in this regard was
unavoidable. All precipitation measurements were made by the same
individual to minimize the error associated with manually read rain
gauges.
Table 1. Approximate distance in kilometers from the crest of the Santa Cruz Mountains and height in meters of the study sites.
Rain gauge location
Approximate distance from mountain crest (km)
Approximate height above sea level (m)
El Corte de Madera
0.0
690
Cañada Road
6.0
120
Pulgas Ridge
7.5
165
Crestview
9.0
270
Belmont
11.0
45
Precipitation totals were collected shortly after each precipitation
event during the study period, between February 1999 and November 2000.
Average wind speed and direction and maximum wind speed and direction
were determined for each storm event by examining hourly data logged at
a remote, automated weather station operated by the National Weather
Service and located near our Pulgas Ridge study site (Pulgas RAWS).The
precipitation and wind data are presented in Table 2.
Table 2. Precipitation totals (mm) and wind data (m/s) for each of five storm events.
Storm 1
Storm 2
Storm 3
Storm 4
Storm 5
Mean wind speed and direction for storm (m/s)
SSW 8
W 1
SW 4
WSW 2
SSW 5
Max. wind speed and direction for storm (m/s)
SSW 17
NW 8
SSW 15
SW 13
SW 17
Precipitation (mm)
El Corte de Madera
M*
37
49
51
33
Canada Road
55
15
39
35
19
Pulgas Ridge
52
15
39
27
15
Crestview
48
17
36
25
15
Belmont
43
19
34
23
11
*Missing Data
We were interested in determining the role of atmospheric instability
and cloud water content on precipitation in our study area, but precise
data for these parameters were lacking. We rationalized that a sound
approximation of these variables could be made by calculating the mean
total precipitation received among all the rain gauges for each storm.
Greater instability and cloud water content produce storms that dump
more precipitation. With this in mind, we combined the instability and
cloud water variables into a generalized parameter we termed storm
intensity. We felt confident in making this generalization because of
the qualitative rather than precise quantitative nature of the
research.
Correlation and least squares regression analysis were performed to
highlight the significance of the relationships between precipitation
events and the study variables. Table 3 depicts these values.
Table 3. Correlation and least squares regression analysis of precipitation to downwind distance data for five storm events.
| r | r2 | y = a + bx | |
| Storm 1 | 0.999 | 0.997 | 69.8 - 2.4x |
| Storm 2 | 0.807 | 0.651 | 32.7 - 1.8x |
| Storm 3 | 0.989 | 0.979 | 48.6 - 1.4x |
| Storm 4 | 0.983 | 0.967 | 50.3 - 2.7x |
| Storm 5 | 0.986 | 0.973 | 32.1 - 2.0x |
Results
The precipitation data for each storm are presented in Table 2. Our data clearly showed a linear relationship between storm totals and distance from the crest of the Santa Cruz Mountains.The calculated correlation values for each of storms 1, 3, 4, and 5 all exceeded .980 indicating a very strong linear relationship. The correlation for storm 2 was somewhat weaker than the others.
A similar, although less strong, correlation was noted between storm intensity and lee-side precipitation (Table 4). High intensity storms tended to produce less significant declines in precipitation from mountain summit to lee region as compared to lower intensity storms. The storm of lowest intensity resulted in the largest percent decline in precipitation from mountain crest to lee. The most intense storm by our definition, however, produced the second smallest decline in precipitation . Of the five storms analyzed, the smallest percent decline in precipitation occurred with the storm we defined to be the second most intense. No pattern was observed in the data between precipitation totals and the topographic variations of the lee region under study.
Table 4. Relationship between storm intensity and precipitation reaching lee region as calculated for five storm events.
| Storm 1 | Storm 2 | Storm 3 | Storm 4 | Storm 5 | |
| Storm intensity (mean precipitation for all study sites) | 54 | 21 | 39 | 32 | 19 |
| Mean precipitation for lee-side sites | 50 | 17 | 37 | 28 | 15 |
| % precipitation from mountain crest reaching lee region | 71 | 46 | 76 | 55 | 45 |
| % decline in precipitation from mountain to lee | 29 | 54 | 24 | 45 | 55 |
| Correlation between storm intensity and precipitation reaching lee region | 0.871 |
Discussion
Our results provide considerable support to the hypotheses outlined by Haugland (1998). Haugland stressed the significance of wind speed, wind direction, cloud water content, and atmospheric instability on lee side precipitation patterns. Our findings suggest that these variables affect lee-side precipitation to the same degree as they affect windward slope precipitation.
The strong linear relationship between lee-side precipitation totals and distance downwind from the crest of the Santa Cruz Mountains is made evident by the values in Figure 3. Most of the discrepancies in the correlation values away from the linear can be well explained based on wind speed and direction. The remarkable precipitation-distance correlation for storm 1 is likely a product of the strong and sustained south-southwesterly winds during that particular precipitation event. Haugland predicted that strong winds would carry orographically lifted clouds into the lee region rapidly enough to enhance precipitation for a distance downwind before the force of gravity pulled the clouds back to their un-lifted level. With a constant wind, we expect this situation to produce a linear decline in precipitation from mountain to lee region. Storm 1 clearly exemplifies this model.

Figure 3. Scatterplot of Storm 1 precipitation vs. distance downwind from the mountains with associated best fit line determined by linear regression analysis.
The much weaker precipitation-distance correlation evident for storm 2 is also explainable. The winds during this storm were the lightest of the five precipitation events analyzed. Light winds minimize the downwind enhancement of orographic precipitation producing generally light precipitation amounts in the lee region. The erratic precipitation totals measured at the lee-side sites probably reflected the very showery nature of the system and not the influence of any of the variables we studied.
Each of storms 3, 4, and 5 produced moderately strong precipitation-distance correlations reflecting their significant south-southwesterly winds. The correlations for these storms are somewhat less strong than for storm 1, probably as a result of minor deviations in wind directions from the SSW. A typical mid-latitude cyclone produces a succession of wind directions in passing a given location. Any precipitation that fell while the wind was blowing from a direction other than that which paralleled our study transect was expected to produce data inconsistencies. With enough wind data it would be possible to isolate that precipitation that falls with any given wind direction; the resulting precipitation data would likely produce very strong correlations.
Our findings also provide some evidence that the percent decline in precipitation from the crest of the Santa Cruz Mountains to the lee region is dependent on storm intensity but further studies on this relationship are necessary. We expected that a stable atmosphere and storm clouds of low water content would combine to produce major precipitation declines from mountain to lee region. Because the stable atmosphere limits the amount of orographic lifting that can be realized on the windward slopes, the modest height of the storm clouds is quickly lost on the lee side. The very limited water supply of such storms is also likely to be quickly depleted on the windward slopes, even with the weak orographics.
The calculated storm intensity—lee-side precipitation correlation was not as strong as we hoped to find, probably because of errors in our storm intensity measurements. We assumed that storm events accompanying a more unstable atmosphere and with high cloud water contents would always produce greater precipitation totals over our study area than storm events with less instability and cloud water content. This is not always the case, however. Other variables such as wind and temperature can greatly influence the distribution of precipitation over a given region. A very dense network of stations continually monitoring all of these parameters during the passing of a storm would be necessary for truly accurate calculations. The limited budget and manpower of this study made the establishment of such a dense network of monitoring stations an impossibility, however.
We found no evidence that the topographic variations of our lee-side study area has any effect on precipitation patterns. We suspected that the 270 meter tall Pulgas Ridge that bisected our study transect might impact precipitation on a very local basis. No such local impact is evident from our data, and the scatterplots presented in Figure 3 show a steady decline in precipitation across the ridge for four of the five storm events.
Precipitation actually increased across the ridge during storm 2 with a lee-side precipitation maximum recorded at Belmont. The Bel-mont site was the lowest in elevation of our study locations and the most distant from the Santa Cruz Mountains, leading us to suspect that this event was an anomaly resulting from the showery distribution of the precipitation and not a local orographic effect. It is likely that for storms with winds sufficient to produce an orographic effect, the potential orographic influence of the elevated lee-side topography is eliminated because of the much greater lift already provided by the neighboring Santa Cruz Mountains. The blocking effect of the Santa Cruz Mountains may also reduce low level wind speeds in the lee region to the point that orographic lifting can no longer be realized. This situation would lead to an obvious enhancement of precipitation along the crest of the Santa Cruz Mountains followed by a steady decline in precipitation across the lee region regardless of the shape of the topography.
It seems possible, however, that a low pressure system deep enough to produce strong southeasterly winds might result in local orographic lifting along the eastern slopes of Pulgas Ridge. In this case we would expect to see a local precipitation maximum at the elevated Crestview site and a decline westward until additional lifting was provided by the Santa Cruz Mountains. Additional research is necessary to test this hypothesis.
References
Chater, AM; Sturman, AP. (1998) Atmospheric conditions influencing the spillover of rainfall to lee of the Southern Alps, New Zealand. International Journal of Climatology. Vol 18, No 1, pp 77-92.
Gilliam, H. (1962) Weather of the San Francisco Bay Region. Berkeley: University of California Press.
Gysi, H. (1998) Orographic influence on the distribution of accumulated rainfall with different wind directions. Atmospheric Research. Vol 47-48, pp 615-633.
Haugland, M. (1998) The rain shadow effect,http://www.weatherpages.com/rainshadow/ accessed 2/10/00.
Hill, FF; Browning, KA; Bader, MJ. (1981) Radar and rain gauge observations of orographic rain over South Wales. Quarterly Journal of the Royal Meteorological Society. Vol 107, No 453, pp 640-670.
Weston, KJ; Roy, MG. (1994) The directional dependence of the enhancement of rainfall over complex orography. Meteorological Applications. Vol 1, No 3, pp 267-275.