xt7jws8hg936 https://exploreuk.uky.edu/dips/xt7jws8hg936/data/mets.xml   Kentucky Agricultural Experiment Station. 1971 journals 202 English Lexington : Agricultural Experiment Station, University of Kentucky Contact the Special Collections Research Center for information regarding rights and use of this collection. Kentucky Agricultural Experiment Station Progress report (Kentucky Agricultural Experiment Station) n.202 text Progress report (Kentucky Agricultural Experiment Station) n.202 1971 2014 true xt7jws8hg936 section xt7jws8hg936   g( Precipitation
%”&/ Probabilities
Pi by A.B. Elam, Jr., C.T. Haan, B.J. Barfield and T.C. Bridges
 
   
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UNIVERSITY OF KENTUCKY .__   
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Agricultural Experiment Station "‘       ·
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in cooperation with
NATIONAL WEATHER SERVICE, NATIONAL OCEANIC
AND ATMOSPHERIC ADMINISTRATION, U. S. DEPARTMENT OF COMMERCE

 CONTENTS
PAGE
Introduction ......................... 3
Source of Data ........................ 3
Method of Analysis ....................... 5
Kentucky Precipitation Patterns .................. 5
i Precipitation Probabilities .................... 14 p
· Examples of How to Use Tables .................. 14
Other Uses of Tables ...................... 15
Literature Cited ........................ 16 ·
Appendix A — Precipitation Probabilities ............... 17
Appendix B - Stations Used ................... 55
ACKNOWLEDGMENT -
The authors express appreciation to the many National Weather Service
cooperative observers, without whose dedication the present data would not be
available; also, to Mr. Douglas Griffin of the Division of Water, Kentucky Depart-
ment of Natural Resources, for assistance in obtaining input data tapes, the
University of Kentucky Computer Center for assistance in data preparation and
special output requirements, and the authors of the computer program used
(G. L. Ashcroft and E. A. Richardson).
.2.
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 I PRECIPITATION PROBABILITIES FOR KENTUCKY I
By A. B. ELAM, ]R.,1 ci 71 HAAM2 B. j. BARFIELD,3 and T. C. BRIDGES4
A knowledge of precipitation patterns has great importance for the solving of many
practical problems. To make the best decisions, those who make precipitation-influenced plans
should be aware of the variability of precipitation according to location and time of year. Persons
who could make use of such information include farmers, contractors, engineers and recreation
planners.
In Kentucky, long-term average precipitation is distributed fairly uniformly throughout
the year, with the late summer and early fall months being the driest ones. During specific years,
periods of dry or wet conditions are experienced in any season. Unusual conditions can occur at
any time of the year but are more likely during some periods than others. Only a systematic
summary makes these patterns understandable. r
This report presents the probabilities of receiving specified amounts of precipitation
during 1-, 2-, and 3-week periods at 25 locations in or near Kentucky. An earlier report contains
the probabilities of various amounts of precipitation on a monthly basis  
l The tables of probabilities can be called a weather forecast "without date" (8) since they
are based on past weather observations and not on the current state of the atmosphere as are the V
National Weather Service’s daily synoptic weather forecasts.
The precipitation probabilities in Appendix A are based on many years of climatological
data, and these climatological predictions are estimates of what the rainfall will be several months
or even years from now. The daily weather forecasts are prepared from current weather observa-
tions and are periodically revised to take later information and changing conditions into account.
These daily local synoptic forecasts for specific dates are more reliable than the climatological
forecasts (i.e., precipitation probabilities) as the particular period in question comes closer.
SOURCE OF DATA
Figure l shows the location of the 25 stations analyzed. Appendix B contains a listing of
the stations, the period of record used in arriving at the probabilities and the mean values. In
some cases, missing data and changes in station location necessitated supplementing the records
with data from nearby stations. As an example, in the case of Addison Dam 45, data from
Irvington had to be used for the month of February 1962.
The raw or input data used consisted of precipitation data from the NOAA National
Weather Service Cooperative Climatological Network stations and some data from professionally .
operated NOAA National Weather Service and Federal Aviation Administration stations. The
choice of stations was limited to those with a sufficient period of record. The basic period of
record chosen was january 1932 through june 1969.
Daily rainfall data for the 25 stations were compiled on magnetic tapes for computer
processing. Some of the data were obtained from data tapes of the Kentucky Department of
lClimatologist for Kentucky, NOAA National Weather Service, Department of Agronomy.
2Associate Professor, Department of Agricultural Engineering.
3Assistant Professor, Department of Agricultural Engineering.
4Computer Technologist, Department of Agricultural Engineering.
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Natural Resources, Division of Water, and some were obtained from data tapes of (or prepared
from the published records of) the National Oceanic and Atmospheric Administration.
METHOD OF ANALYSIS
The format of this bulletin and the methods of data analysis are similar to the work of
the W-38 Technical Committee (7) and to earlier work of the NC—26 Committee (3,9). The data
were analyzed by the methods of H. C. S. Thom and G. L. Barger (2,10,11). The data were
processed using a computer program (1) which fitted a gamma distribution to the precipitation
data. The probability data in the tables were smoothed by harmonic analysis (Fourier series).
This smoothing minimizes random variations in the probabilities that result from using only 37
years of data but does not obscure the patterns of probability. The description of precipitation
probability by the incomplete gamma distribution permits probability statements for precipita-
tion amounts greater than those included in the data.
KENTUCKY PRECIPITATION PATTERNS
A Annual precipitation in Kentucky ranges from about 50 inches to the south and to about
38 inches in the north (Table 1, Fig. 2). The larger amounts in the south reflect the lesser A
distance from the Gulf of Mexico, the prime source of moisture for Kentucky precipitation.
Inspection of monthly median patterns (5) or patterns of normal precipitation (Table 1) indicates
that, in general, the decrease in amount from south to north is especially noticeable for the
colder months December-March inclusive. The warmer months of june, july and August present
a pattern with the maximum precipitation tending to occur in the central and/or eastern portions
of the state. The remaining months give evidence of little or no pattern. Patterns of one—week
intervals of precipitation of at least 0.60 inch tend to reflect the winter months’ decrease from
_ south to north (Fig. 3a). The sizable decrease in probability from south to north can be noted for
the week beginning january 16; a smaller decrease from south to north can be noted for the week
beginning March 15. It can be observed that there is a greater probability of rainfall in the east
than in the west for the one-week intervals be innin une 14 and uly 26 Fi . 3b .
8 S S
40   40
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44 r· mm  j  ml 40
4 4   ll JU       AV4¤(•wN$vILL1-I 1.01tK 6 5.36 4.25 5.06 4.15 3.75 4.25 4.10 4.23 1.30 2.64 3.98 4.09 49.16
GICCILIA 5.16 3.86 4.78 4.22 4.13 4.36 4.12 3.64 2.74 2.54 3.56 3.76 46.87
GREENSHUR0 5.35 3.97 5.24 3.87 4.28 4.83 4.47 3.86 3.18 2.38 3.56 3.96 48.95
IRVINGTDN 4.46 3.60 4.62 3.91 4.11 4.42 3.54 3.14 2.84 2.41 3.42 3.44 43.91
Ll·II'l`CHFIELD 5.33 3.99 5.01 4.18 4.12 4.50 4.11 3.38 2.97 2.65 3.89 4.02 48.21
L0llISVILL1·1 AP 4.10 3.29 4.59 3.82 3.90 3.99 3.36 2.97 2.63 2.25 3.20 3.22 41.32
WOODHURY LOCK 4 5.17 3.93 4.88 4.06 3.85 4.09 4.12 3.72 3.37 2.49 3.76 3.78 47.22
DIVISION 5.12 3.84 4.99 4.03 3.99 4.32 4.15 3.54 3.03 2.47 3.58 3.85 46.91
IILUE GRASS
IIEREA COL1.1~i01a 4.96 3.76 4.64 4.08 3.79 4.84 5.16 4.12 2.82 2.17 3.29 3.58 47.21
11111-1NT DAM 30 3.68 2.91 4.01 3.51 3.62 4.31 3.66 3.53 2.85 2.24 2.93 2.69 39.94
UARROLLTON LOCK 1 3.84 3.01 4.16 3.58 3.50 4.14 3.60 3.47 2.83 2.35 3.07 2.61 40.16
1t0Lu·;UE HILL LOCK 11 4.43 3.59 4.41 3.61 3.63 4.22 5.16 3.91 2.75 1.98 3.19 3.33 44.21 ,
COVINGTON AP 3.56 2.91 3.79 3.22 3.59 3.89 3.61 2.60 2.83 2.26 3.01 2.75 38.02
CYNTIIIANA 4.15 3.22 4.55 3.79 3.44 3.92 3.80 3. 33 2.73 2.06 3.24 3.03 41.26
I1.\NVILL11 5.10 3.98 4.96 3.98 3.96 4.69 4.61 3.94 3.07 2.14 3.32 3.54 47.29
F.\1M0\1T1I 3.89 3.25 4.53 3.94 3.88 4.43 4.26 3.01 2.91 2.23 3.43 3.04 42.80
|·`Ll*·}|IN\7SHlIRG 4,52 3.33 4.84 3.93 4.04 4.34 4.64 3.93 3.27 2.13 3.40 3.36 45.73
1-*01111 IDCK 10 4.41 3. 55 4.26 3.66 3.79 4.50 5.18 3.84 2.84 2.04 3.14 3.31 44.52
FRANKFURT LUQK 4 4.32 3.22 4.48 4.02 3.93 4.07 4.50 3.44 2.71 2.37 3.38 3.11 43.55
nmsr IDCK .s 4.02 3.09 4.41 3.87 3.61 4.15 4.35 3.29 2.92 2.17 3,18 2.92 41.98
GRANT DM 38 3.78 2.80 3.82 3.38 3.28 3.79 3.52 2.67 2.65 2.18 2.92 2.54 37.33
HIGH 111111xZE LUCK 7 4.79 3.74 4.55 3.85 3.70 4.68 4.47 3.47 3.06 2.14 3.32 3.35 45.12
L»\Nc.\sTbZH 5.23 4.21 5.21 3.80 4.05 4.72 5.31 3.84 2.91 2.21 3.60 3.79 48.88
1£xINOTON .11* 4.94 3.42 4.75 4.04 3.85 4.72 3.98 3.21 2.80 2.28 3.29 3.45 44.73
LITTLE HI<7kH.\N wax 8 4.83 3.86 4.74 3.72 3.77 4.73 4.66 3. 95 2.84 2.01 3.21 3.42 45.74
L0\TI\l‘\‘RT 1,01111 2 4.49 3.45 4.67 4.30 4.02 4.47 4.02 3.27 3.00 2.43 3.47 3.27 44.86
MAYSVILLE DAM 33 4.17 3.39 4.48 3.78 3.70 4.18 4.47 4.04 3.12 2.34 3.14 3.19 44.00
M\‘l'NT STFRLIN11 4.89 3.68 4.85 4.14 3.97 4.53 5,13 3.55 2.98 2.25 3.10 3.58 46.65
1\NF0NT7\ D.\‘1 35 3.60 2.83 3.85 3.60 3.68 3.97 3.80 2.94 2.86 2.10 2.84 2.54 38.61
SALVISA LWN 6 5.14 3.84 4.98 3.99 3.78 4.44 4.18 4.08 3.29 2.32 3.53 3.48 47.05
SH}·ZLR\’VI1,LE 4.68 3.54 5.12 4.19 4.01 4.44 3.89 3.62 2.95 2.49 3.64 3.46 46.03
Thwvli Lock 5 4.71 3.60 4.79 4.10 3.64 4.21 4.18 3.79 3.02 2.38 3.51 3.49 45.42
v.11.L1:\’ vim wax E1 4.66 3.79 4.46 3.53 3.67 4.49 5.20 4.28 3.11 2.00 3.29 3.40 45.88
V\R5,\\€ M.\8KL.\N11 11.01 4.00 3.28 4.40 3.88 3.64 4.17 3.88 3.38 2.87 2.28 3.03 2.89 41.70
\v'llLI.\HST\‘\vN 5 WSH 4.11 3.39 4.59 4.00 3.96 4.25 4.02 3.23 3.11 2.37 3.28 3.01 43.32
111VIsION 4.63 3.56 4,63 3.90 3.89 4.44 4.60 3.67 2.94 2.29 3.27 3.36 45.18
I-T1\5T1·`RN
.\sH13\ND 3,78 3.07 4.15 3.39 3.95 3,86 4.04 3.32 2.81 1.90 2.70 2.83 39.80
1·‘\R*111Rs 4.45 3.63 4.63 3.87 4.06 4.49 4.79 4.11 3.08 2.26 3.21 3.23 45.81
r11*1111·iL111:1a12 Loca 14 4.F7 4.00 4.71 3.h7 3.69 4.39 5.14 4.01 2.78 2.03 3.31 3.28 45.58
ll0\`I1 11R1i1·`N1‘1‘ 11.01 3.7.1 3.07 4.12 3.73 3.68 4.14 4.36 3.54 2.99 2.24 2.66 2.82 41.28
1‘11.1·‘V11.1.1·; 3.77 3.80 4.5: 3.65 4.01 4.40 5.19 3, 95 3.04 2.09 2.63 3.17 44.22
Rxvblwx LMA 1: 4.32 3.45 4.41 3.73 3.60 4.16 5.26 4.24 2.91 1.94 3.26 3.03 44.36
\`w1‘1·iI111<1: FW 3: 4.11 3.40 4.47 3.69 4.09 4.30 4.56 3.69 2.70 2.28 3.08 3.11 43.48
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 -7.
Table lb.--Average Precipitation (Inches), Period of Record to 1960, Kentucky.*
Station ggzgido; Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Ann'l
Hazard Water
Works 37-39 4.03 3.88 4.39 3.77 4.28 4.77 5.08 4.32 3.02 2.64 3.13 3.63 46.94
Dale Hollow
Dam, Tenn. 18-19 6.03 5.63 5.46 3.88 3.86 4.41 4.31 3.03 3.50 2.63 4.48 4.98 52.20
Mayfield 45-48 4.67 3.59 4.88 4.23 4.86 3.84 4.01 3.31 3.17 2.93 3.98 4.32 47.29
Middiesboro 62··67 4.90 4.34 5.36 4.31 4.01 4.59 4.67 4.11 2.77 2.47 3.55 4.71 49.79
Paintsville 25-28 4.27 3.49 4.68 3.62 4.10 3.94 4.84 4.06 3.34 1.94 2.90 3.17 44.35
Somerset 10-11 5.09 4.83 4.91 3.81 3.64 4.51 4.46 3.32 3.48 2.19 3.91 4.52 48.67
*Kentucky station, unless specified. Normal precipitation values not available.
#Depending on month. -
Sources: U. S. Weather Bureau, "The Decennial Census of United States Climate - Climatic Summary of the United States,
Siégglement for 1951 through 1960, Tennessee," Climatography of the United States No. 86-35, Washington, D. C.
‘ U. S. Weather Bureau, "The Decennial Census of United States Climate - Climatic Summary of the United States,
iiggplement for 1951 through 1960, Kentucky, " Climatography of the United States No. 86-13, Washington, D. C. _
( Probability of at least 0.60 inch of precipitation for all 52 weeks is shown for 8 specific
locations in Figs. 4a and 4b. In Fig. 4a, data for two northern locations in the western half of "
Kentucky are those for Henderson and Addison; data for two southern locations in the western
half of the state are for Mayfield and Bowling Green. It can be noted that the greatest probability
is in March and that the least probability is in October. In Fig. 4b, data for two northern
locations in the eastern half of Kentucky are for Carrollton and Vanceburg; data for a southern
Bluegrass location are those for Little Hickman; and for a southeastern location, for Hazard. It
can be noted that the minimum probability is in October and that for several of these eastern-half
locations there are two pronounced periods of maximum probability, in March and again in
_]une—_]uly.
- The variation in probability of a very dry week across Kentucky is indicated in Figs. 5a
and 5b (a very dry week is defined as precipitation less than 0.10 inch and is equal to 100%
minus probability of at least 0.10 inch). Pronounced increasing probability of a dry week from
east to west is indicated for the weeks beginning january l0,_]une 14 andjuly 26.
Probability of a very dry week at eight specific locations (same as those in Figs. 4a and A
4b) across Kentucky from week to week for all 52 weeks is indicated in Figs. 6a and 6b. It can
be noted that, in general, the four locations in the western half of Kentucky (Fig. 6a) have the
lowest probability of a dry week in March and the greatest probability in August—October. In the
eastern half (Fig. 6b) it can be seen that Vanceburg and Hazard have pronounced minimum
probabilities of a dry week in late March—ea.rly April and late july-early August; and maximum `
probabilities in the September—October period. It can also be noted the locations of Carrollton
and Little Hickman have minimum probabilities of a dry week in March and maximum likelihood
in the September—October period.
Another item of interest is the probability of occurrence of heavy rains, say 8 inches or
more, in a 3-week period at a particular location. A rainfall of this magnitude at Hopkinsville is
most likely (5.3% chance of occurrence) for the period beginning january 17, but at Little
Hickman it is most likely beginning june 7 (3.2%). (See Appendix A.)
These are just a few examples of studies of precipitation patterns that can be made based
on the data in Appendix A. For further study, it would be instructive to review additional data

 -8.
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Fig. 3:1.--Probability, in percent, of receiving at least 0.60 inch of precipitation, thrcc selected l—week
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DEC. JAN. FEB. MAR. APR. MAY JUNE JULY AUG. SEPT. OCTZ NO\L DEC.
Fig. 4a.·-Probability, in percent, of receiving at least 0.60 inch of precipitation, fifty-two 1-week intervals,
four western locations, Kentucky.
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Fig. 4b.--Probability, in percent, of receiving at least 0.60 inch of precipitation, fifty-two l-week intervals,
four eastern locations, Kentucky.
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Fig. 6a.--Probability, in percent, of a very dry week (less than 0.10 inch of precipitation), fifty-two
1-week intervals. four western locations, Kentucky.
50
STATION LOCATION
0-0 CARROLLTON .
40 ° •—• VANCEBURG I
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Fig. 6b.--Probability, in percent, of a very dry week (less than 0.10 inch of precipitation), fifty-two
1—week intervals, four eastern locations, Kentucky.

 -14-
plotted on graphs and maps; more than 2,000 such items could be prepared from data in the
tables in Appendix A.
PRECIPITATION PROBABILITIES
Precipitation probabilities for 1-, 2- and 3-week periods beginning at the first of each
climatological week are shown in Appendix A. The tables show the mean precipitation for the 1-,
* 2- and 3-week periods and the probabilities of receiving a specified amount or more of precipita-
 .. tion for these periods. For example, the average precipitation of Addison Dam for the periods
` beginning March 1 and continuing for 1, 2 and 3 weeks is 1.12, 2.37, and 3.67 inches, respective-
ly. The probability of receiving 1.00 inch or more of rain during the first week of March is seen n'
to be 39.7%. A probability simply gives the frequency of occurrence. In this instance, a probabil-
ity of 39.7% means that 1 inch or more of rain during the first week of March can be expected to
occur about 40 years in 100. However, there is no way of knowing in what years the 1.00 inch or
more will fall or whether the total will result from one or several storms.
The percent chance of receiving less than a given amount of rainfall during 1-, 2- or 1
3-week periods can be determined by subtracting the tabulated figures from 100.0. Thus, the
probability of receiving less than 0.10 inch during the first week of March at Addison Dam can be
found to be 14.9% by subtracting 85.1 (the probability of receiving at least 0.10 inch) from
100.0. There is 1.1% chance of receiving less than 0.10 inch during the first two weeks and only a
0.1% chance of receiving less than 0.10 inch during the first 3 weeks of March. Figure 5 shows
the probability of receiving less than 0.1 inch of precipitation during six selected 1-week intervals
across the state. Figure 6 shows the probabilities week-to-week for eight locations across the
state.
In using the probability tables, it is suggested that for a location not listed the nearest ·
listed location be used. All probability data are approximate, especially in rough or hilly country,
but these are the best estimates available.
One should keep in mind that these estimated probabilities are valid for a period of years
and not forecasts for specific periods of a designated year. The precipitation amounts listed refer
to probable totals, and a given amount of precipitation may fall in a few hours or over a number
of days. The probabilities for 3-week periods are better estimates than the probabilities for
2-week or 1-week periods. [Or in other words, "These estimated probabilities are subject to error,
of course. This error is greater for 1-week amounts than for 2-week or 3-week totals and is greater
in drier areas and seasons"   Also, estimates are better the longer the period of record used
(4). This should be kept in mind when using estimates for the shorter record stations (i.e.,
Somerset and Dale Hollow; see Appendix B for length of record).
EXAMPLES OF HOW TO USE TABLES
The use of the tables can best be indicated by example. Suppose a Cooperative Extension
Service specialist has been assigned the responsibility of planning a one-day outdoor event. He has
observed that rain is one of the biggest factors in the success of the event since rain greater than
0.1 inch will result in seriously reduced attendance.
Addison Dam being the station nearest the site of the meeting, he looks up the Addison
Dam precipitation table for 1-week periods (Appendix A). He finds that for the week of October
4-10 the chance of receiving at least 0.10 inch of precipitation is the least of the year, 60.2%.
This means that during 60 years out of each 100-year period, the rainfall for the week of October
I 5 ttttr     ...._     N.
  Q_ ( \

 .15-
 ` 4-10 will exceed 0.10 inch; or, that in 40 years out of 100 (100% minus probability of at least
0.10 inch, 100% - 60.2% = 39.8%), the precipitation will be less than 0.10 inch. Since this
amount can occur during any part of the week, the chances of getting a storm during a 1-day
interval are reduced. (See Fig. 6 for the probability of a very dry week, less than 0.10 inch, at
eight stations).
As a second example, consider a contractor who is bidding on a job that must be
completed in a 2-week period sometime during March or April. The job would be seriously
V hampered if the precipitation should exceed 1.5 inches. To determine the risk involved in the
( vicinity of Addison Dam, he turns to the precipitation table for the 2-week period. Since 1.5
inches is not listed, he looks in the 1.4 inch column. The greatest probability is for the period of
 · March 15-28 with a risk of 66 years in 100. The lowest probability is for the interval of April _
12-25 in which the risk is 54 years in 100. Tables for 3-week intervals may be used in a like
· manner.
. OTHER USES OF THE TABLES
Inspection of the tables and/or Figs. 4 and 6 will show for a number of locations a
( relatively drier period in late january and early February. This interval, other conditions being
1 favorable, could be used for the preparation of tobacco plant beds; for seeding clovers and grasses;
A and for the timely application of fertilizers   ·
It will be noted that for a number of locations during several weeks in April, the chance
of having drier weather is better than before or after this period. The probable occurrence of
this period would indicate that the seeding of legumes well in advance of this period would
enhance the chances of success. This April dry spell could also be a good time for planting corn,
other factors being favorable, since the ground would be in better shape for the operation of
machinery  
, It is apparent that some of the drier weeks of the year occur during late August to late
September. This indicates that seeding of alfalfa immediately prior to, or during this period,
A would have less chance of success unless supplemental irrigation is available  
As another example, assume a company needs to plan well in advance the itinerary of
_ one of its salesmen during the week of june 14-20 to take advantage of dry weather to demon-
strate a product. Figure 5b indicates that a dry week is more likely in western Kentucky; a dry
week (less than 0.10 inch of rain) occurs in 25 to 30 years out of 100 years in the jackson .
Purchase Area of western Kentucky and about 12 to 16 years out of 100 years in eastem
Kentucky. If, on the other hand, demonstration of the salesman’s product during the week of
july 26-August 1 required a week with at least 0.60 inch of rain, travel in southeastern Kentucky
would be indicated since the chance of this amount of rain is greater than 60 out of 100 years
. (Fig. 3b). _ (
The mean weekly precipitation is listed in a separate column of Appendix A. The greatest
weekly precipitation (1.31 inches) for Addison Dam is for the week of March 15-21. The least is
0.44 inch which occurs during the week of October 11-17. Thus, the weekly mean precipitation
reflects the general seasonal distribution of precipitation for the location. The 1-, 2-and 3-week
tables of means and probabilities are used in a similar manner.

 -16-
LITERATURE CITED
1. Ashcroft, G. L., and E. A. Richardson. Climate and Phenological Patterns for Agriculture in the
Western Region. Utah Interim Report of the Technical Committee, Western Regional Project W-48. Unpub.
Rept., Utah State Univ. 1964.
2. Barger, G. L., and H. C. S. Thom. Evaluation of Drought Hazard. Agron. _]., 41:519-526. 1949.
3. Barger, G. L., Robert H. Shaw and Robert F. Dale. Chances of Receiving Selected Amounts of
Precipitation in the North Central Region of the United States. First Report