WETS Table Documentation
Natural Resources Conservation Service
National
Water and Climate Center
Portland, Oregon
May 15, 1995
Content Manager: Jolyne Lea
Table of Contents
Introduction
Wetlands have been identified as an important component to
healthy ecosystems. Climate plays an important role in the genesis
and identification of wetlands. With increased population, demands
on the wetlands will also increase. Therefore, to identify the
physical characteristics of wetlands adequately, specific tools and
procedures are needed.
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Objective
The objective of the WETS Table is to define the normal range for
monthly precipitation and normal range for growing season required
to assess the climatic characteristics for a geographic area over a
representative time period.
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Source of Data Used In WETS Table
National Weather Service Climate Stations and Network
The data used in the WETS Table are observed by the National
Weather Service (NWS) Cooperative Network. This nationwide network
currently consists of nearly 8,000 active climatic stations.
Observations at cooperative stations are performed by private
citizens, institutions (such as utilities and television stations),
or state and federal agencies.
The digital record of these observations is called the Summary of
Day (TD3200). The Climatic Data Access Facility (CDAF) obtained
this digital dataset from the National Climatic Data Center (NCDC)
in Asheville, North Carolina. Quality control procedures have been
performed on the dataset by NCDC as part of the ValHidd project
(Reek et al., 1991). The ValHidd project identified extreme data
errors, such as a maximum temperature of 99 degrees in the summer
or a precipitation amount of 40.00 inches instead of 0.40. ValHidd
also suggested replacement values where appropriate.
Extreme data errors were corrected or marked as missing and in
the Natural Resources Conservation Service's Centralized Database
System (CDBS) located in Portland, Oregon. The entire U.S. Summary
of the Day historical climate record consists of nearly 17,000
stations.
Of the nearly 17,000 NWS climate stations in CDBS, approximately
6,700 contain sufficient observation record length (greater than 20
years during the most recent normal period, 1971  2000, or no more
than 5 consecutive years of missing data) to provide representative
averages and probability information.
A brief description of each climate element used in the WETS
Table is included in the following sections.
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Air Temperature Measurement
Air temperature measurements are made five feet above the ground
with a liquidinglass maximum and minimum thermometer mounted in a
Cotton Region Shelter or with an electronic thermistorbased
Maximum, Minimum Temperature System mounted in a small
"beehive" like structure. Maximum and minimum air
temperatures are taken and recorded daily.
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Precipitation Measurement
Precipitation is measured with either a nonrecording gage
(standard NWS 8 inch), a recording weighing type gage (either
Universal or Belfort), or both. Precipitation amounts are taken and
recorded daily. Snowfall is the incremental depth of snow that has
fallen since the last snow depth measurement, usually 24 hours. It
is traditionally measured with a stiff stick graduated in inches.
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Probability Category Definitions
Five categories of temperature and precipitation departures have
been defined and are in widespread use. These categories were
defined by the National Climatic Data Center (NCDC). The five
quantitativelydefined categories (Table 1) are qualitatively
referred to as MUCH ABOVE NORMAL, ABOVE NORMAL, NORMAL, BELOW
NORMAL, AND MUCH BELOW NORMAL (NCDC, 1984a).
CATEGORY ZSCORE
 
Much Above Normal Z > 1.282
Above Normal .524 < Z <= 1.282
Normal 0.524 <= Z <= 0.524
Below Normal 1.282 <= Z < 0.524
Much Below Normal Z < 1.282
Table 1. Class limits for the Zscore categories.
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Temperature Categories Used for Growing Season Calculations
Monthly and annual temperatures are usually well represented by
the normal distribution; therefore, the Zscore (or standardized
departure from average) was used to classify, by category, the
growing season length. The growing season Zscore is calculated as
z(i) = (T(i)  T(avg))/s, where T(i) is the growing season length
associated with a given Zscore, z(i), T(avg) is the mean annual
growing season length over the selected period (e.g. 19712000), and
s is the standard deviation of the annual growing season lengths
over the selected period (e.g. 19712000).
For example, MUCH ABOVE NORMAL would represent any amount greater
than a 1.282 standard departure above the mean. In a normal
distribution, the NORMAL category will contain 40% of the values.
The ABOVE NORMAL and BELOW NORMAL categories will each contain 20%
of the values, and the MUCH ABOVE and the MUCH BELOW categories will
each contain 10% of the values.
The 30% category shown in the WETS Table represents the class
limit values associated with the NORMAL category Zvalues of 0.524
and 0.524.
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Precipitation Category Definitions
The same Zscore categories apply to precipitation, however,
monthly and annual precipitation exceedance probabilities are
calculated from fitting the observed monthly data to a twoparameter
gamma distribution.
The twoparameter gamma distribution is asymmetrical and is used
with continuous random variables such as precipitation. Its
probability density function has a lower limit of 0 and an upper
limit of infinity. The distribution was fit using the method
outlined by the Soil Conservation Service (1985).
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WETS Table Definitions
The WETS program was created from several existing computer
programs available at CDAF that summarize temperature and
precipitation, growing season lengths, and last and first freezing
dates. The summaries of precipitation, temperature, growing season
length and dates produced by the WETS Table provide representative
climatic information for the stations selected.
The WETS Table, shown in Table 2, summarizes monthly and annual
climatic information in a concise format. The table provides the
normal range for monthly and annual precipitation and growing season
dates required to assess the climatic characteristics for a
geographic area over a representative time period.
The table can be generated from any NWS Cooperative Climate
Station with 20 or more years of data. The user has control over the
starting and ending year and growing season threshold temperatures.
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Average Daily Maximum Temperature for a Month and Yearly Average
(Column #2)
The WETS table uses daily maximum (TMAX) and minimum (TMIN)
observations to calculate average daily maximum and minimum
temperatures for each month.
Average daily maximum temperatures are calculated by summing the
daily maximum temperatures for an individual month and dividing by
the number of values used in the summation for that month. The
monthly averages are then summed and divided by the number of months
used in the period (years) selected.
The yearly average is calculated by summing the monthly average
maximums and dividing by 12. The value represents the average over
the period selected.
WETS Station : DE SMET, SD2302
Latitude: 4423 Longitude: 09733 Elevation: 01750
State FIPS/County(FIPS): 46077 County Name: Kingsbury
Start yr.  1971 End yr.  2000
Temperature: 30 years available out of 30 requested in this analysis
Precipitation: 30 years available out of 30 requested in this analysis

 Temperature  Precipitation 
 (Degrees F.)  (Inches) 

     30% chance avg  
     will have # of avg 
 days total
Month  avg  avg  avg  avg  less  more w/.1 snow 
 daily  daily    than  than  or fall 
 max  min     more 

COL #1 COL #2 COL #3 COL #4 COL #5 COL #6 COL #7 #8 #9 
January  23.0  2.4  12.7  0.60  0.31  0.78  2  6.6 
February  29.3  9.0  19.2  0.68  0.41  0.89  2  7.0 
March  41.3  21.1  31.2  1.60  0.87  1.95  3  8.9 
April  58.7  34.2  46.5  2.26  1.28  2.75  4  1.6 
May  71.1  45.8  58.5  3.05  1.82  3.69  5  0.0 
June  80.3  55.8  68.0  4.02  2.59  4.84  6  0.0 
July  86.2  61.1  73.7  3.25  1.96  3.93  4  0.0 
August  83.9  58.6  71.3  2.44  1.51  2.95  4  0.0 
September  73.7  48.7  61.2  2.14  1.03  2.61  4  0.0 
October  61.0  36.8  48.9  1.78  0.83  2.25  3  0.8 
November  41.7  22.5  32.1  0.92  0.34  1.11  2  5.4 
December  26.7  8.1  17.4  0.58  0.32  0.73  1  6.0 


Annual  19.83  26.03 

Average  56.4  33.7  45.1           

Total        23.30      40  36.3 


GROWING SEASON DATES
Requested years of data: 30 Available years of data: 30
Years with missing data 24 deg = 0, 28 deg = 0, 32 deg = 0
Years with no occurrence 24 deg = 0, 28 deg = 0, 32 deg = 0
Data years used 24 deg = 30, 28 deg = 30, 32 deg = 30

 Temperature

Probability  24 F or higher  28 F or higher  32 F or higher

COL #10 COL #11 COL #12 COL #13
 Beginning and Ending Dates
 Growing Season Length

50 percent *  4/16 to 10/22  4/27 to 10/ 9  5/ 4 to 9/29
 189 days  165 days  148 days
  
70 percent *  4/12 to 10/27  4/22 to 10/13  5/ 1 to 10/ 3
 198 days  174 days  155 days
  

* Percent chance of the growing season occurring between the Beginning
and Ending dates.
Table 2. WETS Table Example
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Average Daily Minimum Temperature for a Month and Yearly Average
(Column #3)
Average daily minimum temperatures are calculated by summing the
daily minimum temperatures for an individual month and dividing by
the number of values used in the summation for that month. The
monthly averages are then summed and divided by the number of months
used in the period (years) selected.
The yearly average is calculated by summing the monthly average
minimums and dividing by 12. The value represents the average over
the period selected.
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Average Daily Temperature for a Month and Yearly Average (Column
#4)
Average daily temperature for a month is calculated by adding the
individual monthly average daily maximum temperatures and average
daily minimum temperatures shown in columns 2 and 3 and dividing by
two.
Average yearly temperature is calculated by summing the monthly
averages shown in Column 4 and dividing by 12. The value represents
the average over the period selected.
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Average Monthly and Annual Precipitation (Column #5)
The WETS Table uses daily precipitation to determine average
monthly precipitation. Monthly precipitation is calculated by
summing the daily precipitation for each month. All monthly amounts
are then summed and divided by the number of months used in the
period (years) selected. The Yearly Total is the sum of the averages
for individual months shown in Column 5.
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The "30% Chance Less Than" Values for Monthly
Precipitation and Annual Precipitation (Column #6)
This value represents the threshold for which 30 percent of
precipitation amounts will be less than or equal to the value shown.
Viewed inversely, 70 percent of all precipitation amounts can be
expected to exceed this value. These thresholds are calculated from
the fitted twoparameter gamma distributions (NRCS, 1985).
It should be noted that the annual threshold shown in Column 6 is
not the sum of the individual monthly thresholds. Individual
monthly, (e.g. all January totals) and annual precipitation totals
possess different statistical distributions which must be modeled
separately with the gamma distribution. Accordingly, monthly totals
are used to calculate the monthly threshold values and annual totals
are used to calculate the annual threshold values.
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The "30% Chance More Than" Values for Monthly
Precipitation and Annual Precipitation (Column #7)
This value represents the threshold for which 30 percent of
precipitation amounts will be greater than or equal to the value
shown. Viewed inversely, 70 percent of all precipitation amounts can
be expected to be less than this value. These thresholds are
calculated from the fitted twoparameter gamma distributions. The
monthly and annual thresholds are calculated in the same manner as
described in the "30% Chance Less Than" (Column #6).
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Average and Total Number of Days With .10 Inch or More of
Precipitation (Column #8)
The monthly average value is calculated by summing the number of
days with precipitation greater or equal to .10 inches for a
individual month over the period (years) selected and dividing by
the number of months used in summation. The yearly average is
calculated by summing the 12 monthly average values.
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Average Total Snowfall (Column #9)
Snowfall is the incremental depth of snow that has fallen since
the last snow depth observation. The time between snowfall
observations is usually 24 hours for the NWS Cooperative Network.
The monthly average value is calculated by summing the observed
daily snowfall values greater than or equal to 0.1 inch for an
individual month and dividing that sum by the number of months used
in the selected period (e.g. 19712000). The yearly average is
calculated by summing the 12 monthly average values.
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Accommodating Missing Temperature and Precipitation Data
Nearly all climate observations in the U.S. are made by
volunteers who are part of the NWS Cooperative Station Network.
Events such as sickness, vacation, or equipment failure can create
missing daily data values. Since missing data values do affect
climate statistics, guidelines have been established to accommodate
missing data and still provide representative statistics.
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Missing Temperature Algorithm for Calculating Averages
To create representative averages and totals, the WETS program
scans each month for missing temperature and precipitation values
using the following logic:
To be included in a temperature analysis, a month must contain at
least 21 maximum and minimum temperature values. Since temperature
is a continuous function, previous research has shown that
representative averages can be calculated using 21 or more
temperature values for a particular month (Duchon, 1981).
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Missing Precipitation Algorithm for Calculating Averages
To be included in a precipitation analysis, a month must contain
at least 25 observed daily precipitation values. (Zero is considered
a valid observation and not treated as missing.) Since precipitation
occurs as distinct events rather than continuously, and significant
amounts can occur in a single day, a more stringent criterion for
missing days has been imposed than for temperature.
One exception to the 25 day rule is the calculation of average
monthly snowfall. Since snowfall is observed less frequently than
liquid precipitation (rain) and larger sample sizes ensure more
stable estimates, no months are excluded from the calculation unless
an entire month's snowfall dataset is reported as missing.
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Accommodating Zero Monthly Precipitation Totals
Monthly precipitation totals of zero present a problem when one
uses the logarithmic transformations to calculate the exceedence
probabilities as shown in the WETS Table. The logarithm of zero is
undefined and cannot be included in the exceedence probability
calculation.
Zero monthly precipitation totals are a seasonal characteristic
of the West and Southwestern United States. They are most often
observed in the summer.
The WETS program adjusts for this situation by using a mixed
distribution, binomial and two parameter gamma, to calculate
representative probabilities (Kite, 1977). Given a dataset
containing zero monthly precipitation, the first step is to fit the
probability distribution to those events greater than zero. The next
step is to multiply the resulting probabilities by the ratio of the
number of events equal to zero to the total number of events in the
sample. This will result in the required probability of exceedence.
If, for example, 16 months out of 24 valid sample years reported
zero precipitation valid years (probability of non occurrence equal
to 67 percent), a 30 percent probability value could not be
calculated and would be shown as a zero in the table. This logic
applies to all probabilities calculated by the WETS table.
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WETS Growing Season Dates and Length
The growing season is defined as that part of the year when soil
temperatures at 19.7 inches below the soil surface are higher than
biologic zero (5 degrees C). As this quantitative determination
requires inground instrumentation which is not usually available,
growing season can be estimated by approximating the number of frost
free days. The growing season can be approximated as the period of
time between the average date of the last killing frost in the
spring to the average date of the first killing frost in the fall.
This represents a temperature threshold of 28 degrees F or lower at
a frequency of 5 years in 10.
The growing season length is determined from daily minimum
temperature values. Threshold surface temperatures of 32, 28, and 24
degrees Fahrenheit are generally used to determine the effects of
air temperature on plants using the following commonly accepted
classification (NCDC, 1984b):
32 to 29 degrees F. is a light freeze  tender plants
killed, with little destructive effect on other
vegetation.
28 to 25 degrees F. is a moderate freeze  widely
destructive effect on most vegetation with heavy
damage to fruit blossoms, tender and semihardy
plants.
24 degrees F. and less is a severe freeze  heavy
damage to most plants. At these temperatures,
the ground freezes solid, with the depth of the
frozen ground dependent on the duration and
severity of the freeze, soil moisture, and soil
type.
It should be noted that temperatures near the ground may be
significantly lower than temperatures measured at five feet, the
normal height that air temperatures are observed. It is not unusual
for surface temperature and air temperature to vary by four degrees
or more. For this reason, the WETS program allows users to select
the three threshold temperatures.
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Growing Season Definitions
All freeze dates are based upon the season August 1 through July
31 for each threshold temperature. Last spring dates of occurrence
for a given year are obtained from the period August 1 of the
previous year through July 31 of the given year (e.g., spring season
for 1971 runs from August 1, 1970, through July 31, 1971, except for
the selected starting year, which begins on January 1).
First fall dates of occurrence are obtained from the period
August 1 of a given year through July 31 of the following year
(e.g., fall season of 1971 runs from August 1, 1971, through July
31, 1972, except for the selected ending year, which ends on
December 31).
Therefore, for purposes of calculating the "growing
season" with the WETS program, the climatological year begins
on August 1 of the previous year and ends on July 31 of the
following year.
This season definition follows that of NCDC (1984b). It coincides
more closely with previous definitions of the annual march of
temperature, in which the warmest time of year occurs near August 1,
and the cold season extends beyond December and into the following
winter months. This allows for the first "fall" freeze to
occur after December 31, which sometimes happens in warmer climates.
The estimation of freeze probabilities was based upon the work of
Thom and Shaw (1958) and Thom (1959), which was later modified by
Vestal (1970, 1971).
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Growing Season Dates and Length Calculation
To determine the last occurrence of a temperature threshold in
the spring, the WETS program begins on July 31 of a given year and
progresses "back" toward August 1 of the previous year,
comparing each daily minimum temperature with the user selected or
default thresholds. The first date on which the temperature is less
than or equal to a threshold for that year is stored. This then
becomes the spring date.
To determine the first occurrence of a temperature threshold in
the fall, the program then starts on August 1 of the given year and
progresses "forward" toward July 31 of the following year
comparing each daily minimum temperature with the user selected or
default thresholds. The first date in which the temperature is less
than or equal to a threshold for that year is stored. This then
becomes the fall date.
During this search procedure, it is possible for a single date to
fulfill all three user selected thresholds. For example, an observed
minimum temperature of 20 degrees would fulfill thresholds of 24,
28, and 32 degrees.
Both the last spring and first fall dates are converted to Julian
days for calculation of summary statistics. The growing season
length is determined by counting the number of days from July 31
back to the threshold date in the spring and by counting the number
of days from August 1 forward to the threshold date in the fall. The
spring and fall counts are summed to determine the growing season
length for an individual year. The growing season length for the
period of selected (such as 19712000) is determined as the average
of the growing season lengths calculated for the individual years.
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Growing Season Dates and Length Probabilities
The average growing season length is shown in the WETS Table as
the 50% probability value. Associated with this length are the
average dates of the beginning and end of the growing season. The
70% value of growing season length represents the upper bound of the
NORMAL category; 70% of years will have a growing season less than
or equal to this length, and 30% will have a growing season greater
than this length. Associated with the 70% probability value of
growing season length are the average dates of the beginning and end
of a growing season of this length.
Since average growing season length is determined first (in total
days), starting and stopping dates must be calculated. The growing
season length calculation does not include the ending date in the
fall. Since minimum temperatures usually occur in the morning, the
effective last day of the growing season would have been the
previous day. Therefore the date of the threshold exceedance would
not be included in the growing season calculations.
Starting and ending dates are derived by first determining the
"average midpoint date" for each growing season for each
year in the selected period. The average probability start and end
dates are determined by dividing the average growing season length
by two, rounding as appropriate, and then adding and subtracting the
resulting number to the "average midpoint date." These
values are then converted to the calendar dates shown in the WETS
Table. Due to the effects of rounding, leap years, and the use of a
366 day Julian calendar, growing season start and end dates shown in
the WETS Table may differ by one day from the growing season
lengths.
The 70% starting and ending dates are then determined by taking
the difference (in days) between the 70% and the 50% probability
growing season lengths, adding half the difference to the 50%
probability ending date and subtracting half the difference from the
50% probability beginning date.
Since the minimum temperatures used to determine growing season
lengths can be modeled using a normal distribution, the assumption
of symmetry in both the 50% and 70% growing season length
distributions is valid. Therefore, adding and subtracting the
difference in days between the 70% and 50% growing season lengths
will provide reasonable results. The 70% probability average
beginning and ending dates are to be interpreted as the
"normal" growing season for wetland determinations.
The growing season dates for specified temperatures and
probabilities are shown in the bottom half of the WETS Table in
Columns 2, 3, and 4.
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Accommodating Missing Minimum Temperatures When Calculating the
Growing Season Dates and Length
Previous research (Ashcroft et al., 1992) has shown that
representative last and first frost dates can be calculated from
time series that contain missing data. Based on this research and
CDAF sensitivity tests (Pasteris, 1994), the WETS program excludes a
year from the calculation if a season (spring or fall) has 9
sequential or 18 random missing minimum temperatures. The number of
years excluded for each temperature threshold is shown at the top of
each WETS table. The WETS program requires a minimum of 20 valid
data years to produce a representative WETS table.
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Threshold Temperature NonOccurrence
Certain areas of the country, Florida or Arizona for example, do
not experience one or more of the threshold temperatures in some
years. The WETS program adjusts for this situation by using a mixed
distribution, binomial and normal, to calculate representative
probabilities (Vestal, 1970, 1971). The number of years with
nonoccurrence are shown at the top of the WETS Table.
A growing season length will not be calculated if the probability
of nonoccurrence is greater than the preselected probability. If,
for example, a temperature of 24 degrees or less was not recorded in
16 out of 30 valid years (probability of non occurrence equal to 53
percent), a 50 percent probability value could not be calculated.
This logic applies to all probabilities calculated by the WETS
table.
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Differences Between Last Spring and First Fall Frost Dates and
Growing Season Length
The number of days between the last frost in the spring and the
first frost in the fall derived from the dates for a selected
probability level in the CDBS FROST table will not, in general, be
equal to the growing season length for the same probability level
given the WETS table or the CDBS GROWTH table. They will only be
equal for the 50% (5 years in 10) probability level; otherwise, they
will not be equal.
This is because the CDBS FROST program treats the spring and fall
threshold date distributions as separate and independent. A growing
season for a particular year, however, is a "coupled
event," that is, it is the length of time between the spring
and fall temperature threshold occurrences in that year. One cannot,
therefore, determine the growing season lengths for selected
probability levels from the two independent distributions in the
FROST table. The WETS and GROWTH programs treat the growing season
as a coupled event and should be used to obtain growing season
lengths for different probability levels.
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STATS Table
STATS, shown in Table 3, is a companion table to WETS. It
displays monthly and annual totals summed from daily observed
precipitation. Months with at least one missing daily observation
are annotated with an "M". Months containing no daily
observations are shown as a blank.
STATS tables have been generated for all WETS stations for the
period of record available at the particular site. The actual data
record may or may not cover the entire averaging period.
Station : SD2302, DE SMET
total 19611993 prcp, Unit = inches
yr jan feb mar apr may jun jul aug sep oct nov dec annl
            
61 0.20 M0.57 0.86 1.34 4.51 5.48 2.75 0.36 1.94 4.39 0.43 0.84 23.67
62M0.32 1.58 2.03 2.25 8.17 4.73 7.09 2.59 1.43 0.48 0.23 0.15 31.05
63 0.80 0.72 1.12 2.61 2.14 2.14 5.82 0.72 1.76 1.04 0.75 1.32 20.94
64 0.03 0.21 1.73 2.43 1.87 2.10 2.59 2.79 1.33 0.00 0.32 0.64 16.04
65 0.13 0.70 2.11 3.05 7.36 5.89 1.78 1.38 4.54 1.00 0.73 0.31 28.98
66 0.24 0.75 1.43 2.30 1.06 1.75 2.27 3.47 1.50 1.80 0.17 0.29 17.03
67 1.18 1.32 0.09 1.80 0.75 7.75 2.82 0.95 1.92 0.84 0.23 0.30 19.95
68 0.39 0.00 0.57 4.96 2.34 4.87 2.32 2.96 2.20 3.43 0.69 2.03 26.76
69 1.36 1.81 0.56 0.31 2.93 2.32 3.34 1.19 1.35 3.21 0.17 0.81 19.36
70 0.51 0.00 1.53 3.82 2.28 4.63 3.07 1.13 1.20 2.10 2.09 0.70 23.06
71 0.06 1.45 0.05 2.07 2.69 3.88 2.08 2.23 1.07 M4.63 3.41 0.60 24.22
72 0.51 0.49 1.42 4.13 6.28 3.37 6.00 0.94 1.23 2.06 1.73 1.42 29.58
73 0.52 0.63 1.90 M0.59 M2.82 1.21 2.77 2.43 M2.72 1.12 0.81 0.87 18.39
74 0.00 1.12 1.39 M0.79 4.24 2.16 1.83 2.97 0.05 M0.14 0.08 0.12 14.89
75M2.22 0.23 M3.19 2.72 1.74 4.34 0.13 5.16 1.87 0.89 M1.68 0.15 24.32
76 1.41 0.58 1.45 1.50 M0.43 1.47 1.29 0.50 2.45 0.25 0.06 0.38 11.77
77 0.82 2.40 3.51 2.59 2.01 7.78 1.40 2.92 3.16 3.27 3.05 0.76 33.67
78 0.80 0.30 0.68 3.05 4.83 1.94 2.85 0.72 1.85 0.21 0.62 0.81 18.66
79 0.67 0.35 1.97 3.20 2.28 3.35 1.99 2.49 0.08 2.58 0.46 0.19 19.61
80 0.42 0.46 0.69 0.67 1.71 5.27 1.86 4.17 0.95 1.34 0.08 0.10 17.72
81 0.48 0.52 1.57 0.64 1.09 3.86 4.72 2.38 0.69 2.25 1.06 0.32 19.58
82 1.15 0.08 0.93 1.56 6.30 1.86 4.62 2.33 2.77 4.82 0.88 0.44 27.74
83 0.21 0.32 3.28 1.05 1.31 3.39 2.05 1.44 3.44 1.28 2.23 0.38 20.38
84 0.53 0.69 1.28 3.46 2.11 11.92 1.55 5.85 2.22 4.86 0.17 0.69 35.33
85 0.55 0.25 3.51 2.39 3.84 2.51 3.31 4.21 7.62 1.40 1.95 0.95 32.49
86 0.43 0.44 1.40 7.63 3.88 2.86 7.45 3.46 4.46 0.38 0.53 0.00 32.92
87 0.18 0.81 3.30 0.45 0.97 1.79 8.31 3.28 1.76 1.05 0.92 1.01 23.83
88 1.42 0.62 1.63 1.17 2.28 1.71 1.63 2.42 3.82 0.17 1.03 0.45 18.35
89 0.37 0.65 1.87 2.45 2.15 4.67 4.57 3.30 2.60 0.53 0.89 0.07 24.12
90 0.00 0.32 0.81 0.74 5.00 9.72 3.12 2.33 M0.17 2.02 0.05 M0.29 24.57
91 0.00 0.65 0.35 4.06 M6.54 1.51 1.50 2.13 0.63 1.31 M0.00 18.68
92 0.71 1.04 1.09 2.02 1.37 4.18 4.21 3.12 2.66 0.86 M0.89 0.61 22.76
93 0.50 0.46 1.25 3.11 3.64 8.74 5.34 3.24 2.07 0.00 M0.88 0.88 30.11
Notes: Data missing in any month have a 'M' flag
Data missing for all days in a month is blank
Table 3. STATS  Monthly and Annual Precipitation Totals
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Guidelines for WETS Table Usage
A. Select climate stations that observe both temperature and
precipitation. Precipitation only stations can be used if a
neighboring station has the temperature information necessary to
determine growing season. It should be noted that growing season
dates are more important in the spring and fall and that
determinations made in the middle of the growing season are more
dependent on precipitation.
B. Select stations with a minimum of 20 years of data.
C. There may be a great variation in climate for an individual
county, especially in the West. Therefore, it may necessary to
review several climate stations and select one that represents the
climate in the area under consideration.
D. Some areas of the country seldom experience temperatures of 28
degrees or less. These areas include coastal South Carolina, coastal
Georgia, Florida, southern Alabama, southern Mississippi, southern
Louisiana, coastal Texas, southern and coastal California, coastal
Oregon, coastal Washington, the Pacific and Caribbean Islands.
Thresholds temperatures of 34, 32, 28 degrees should be selected for
these areas.
E. Additional guidelines will be added as implementation begins.
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References
Ashcroft, G.L., D. Jensen, and J. Brown, 1992, Utah Climate, Utah
State University, pp. 97.
Duchon, C.E., 1981, The Design of Tools to Edit Daily Minimum and
Maximum Temperatures, NOAA/WMO Climatological Workshop, National
Climatic Data Center Manuscript, Asheville, NC,
Kite, G. W., 1977, "Frequency and Risk Analyses in
Hydrology," Water Resources Publication, Ft. Collins, Colorado,
pp. 57.
National Climatic Data Center, 1984a, Atlas of Monthly and
Seasonal Temperature Departures from the LongTerm Mean (18951983)
for the Contiguous United States, Historical Climatology Series 34,
U.S. Department of Commerce, National Climatic Data Center,
Asheville, NC.
National Climatic Data Center, 1984b, Climatography of the United
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Department of Commerce, National Climatic Data Center, Asheville,
NC.
Pasteris, P., 1994, Research Activities Associated with the
Creation of Temperature and Precipitation Climate Summaries for the
NRCS, Unpublished research manuscript.
Reek, T., S. Doty, and T. Owen, 1992, A Deterministic Approach to
Validation of Historical Daily Temperature and Precipitation Data
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Soil Conservation Service, U.S. Department of Agriculture, 1985,
Selected Statistical Methods, National Engineering Handbook, Section
4 Hydrology, Chapter 18, pp. 187  188.
Thom, H.C.S., and R.H. Shaw, 1958, Climatological Analysis of
Freeze Data For Iowa, Monthly Weather Review, Vol. 86, pp. 251257.
Thom, H.C.S., and Shaw, R.H., 1959, The Distribution of
FreezeDate and FreezeFree Period for Climatological Series with
Freezeless Years, Monthly Weather Review, Vol. 87, pp. 136144.
Vestal, C.K., 1970, Freeze Date Computations, Memo to All State
Climatologists Southern Region and Commonwealth Climatologist, San
Juan, Puerto Rico, U.S. Department of Commerce, National Weather
Service, Southern Region.
Vestal, C.K., 1971, First and Last Occurrences of Low
Temperatures During the Cold Season, Monthly Weather Review, Vol.
99, pp. 650652.
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This page last revised  Oct 9 1997
