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WETS Table Documentation

Natural Resources Conservation Service
National Water and Climate Center
Portland, Oregon
May 15, 1995
Content Manager: Jolyne Lea

Graphic of a Wetland

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 (TD-3200). 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 liquid-in-glass maximum and minimum thermometer mounted in a Cotton Region Shelter or with an electronic thermistor-based 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 non-recording 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 quantitatively-defined categories (Table 1) are qualitatively referred to as MUCH ABOVE NORMAL, ABOVE NORMAL, NORMAL, BELOW NORMAL, AND MUCH BELOW NORMAL (NCDC, 1984a).

     CATEGORY                       Z-SCORE
     -----------------       --------------------
     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 Z-score 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 Z-score (or standardized departure from average) was used to classify, by category, the growing season length. The growing season Z-score is calculated as z(i) = (T(i) - T(avg))/s, where T(i) is the growing season length associated with a given Z-score, z(i), T(avg) is the mean annual growing season length over the selected period (e.g. 1971-2000), and s is the standard deviation of the annual growing season lengths over the selected period (e.g. 1971-2000).

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 Z-values of -0.524 and 0.524.

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Precipitation Category Definitions

The same Z-score categories apply to precipitation, however, monthly and annual precipitation exceedance probabilities are calculated from fitting the observed monthly data to a two-parameter gamma distribution.

The two-parameter 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 two-parameter 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 two-parameter 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. 1971-2000). 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 in-ground 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 semi-hardy 
    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 1971-2000) 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 Non-Occurrence

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 non-occurrence are shown at the top of the WETS Table.

A growing season length will not be calculated if the probability of non-occurrence 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  1961-1993  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 Long-Term Mean (1895-1983) for the Contiguous United States, Historical Climatology Series 3-4, U.S. Department of Commerce, National Climatic Data Center, Asheville, NC.

National Climatic Data Center, 1984b, Climatography of the United States No. 20: Climatic Summaries for Selected Sites, 1951-80, U.S. 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 from the Cooperative Network, Bulletin of the American Meteorological Society, Vol. 73, No. 6, pp. 753-762.

Soil Conservation Service, U.S. Department of Agriculture, 1985, Selected Statistical Methods, National Engineering Handbook, Section 4 Hydrology, Chapter 18, pp. 18-7 - 18-8.

Thom, H.C.S., and R.H. Shaw, 1958, Climatological Analysis of Freeze Data For Iowa, Monthly Weather Review, Vol. 86, pp. 251-257.

Thom, H.C.S., and Shaw, R.H., 1959, The Distribution of Freeze-Date and Freeze-Free Period for Climatological Series with Freezeless Years, Monthly Weather Review, Vol. 87, pp. 136-144.

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. 650-652.

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This page last revised - Oct 9 1997