In order to identify the physical characteristics of wetlands adequately, the NRCS Climate Analysis for Wetlands Tables (WETS Tables), were developed.
Wetlands are an important component to healthy ecosystems. And, climate plays an important role in the genesis and identification of wetlands. In order to identify the physical characteristics of wetlands adequately, the NRCS Climate Analysis for Wetlands Tables, also known as WETS Tables, were developed.
The WETS Tables define the normal range for monthly precipitation and growing season required to assess the climatic characteristics for a geographic area over a representative period of time. The Tables gives a month-by-month summary and probability analysis of temperature and precipitation. The Tables also provide the average length of the growing season using three index temperatures (32, 28, and 24 degrees Fahrenheit) at 50% and 70% probabilities.
About Wetlands Climate Tables
Growing Season Dates and Length
The growing season is defined as that part of the year when soil temperatures at 50 cm (20 inches) below the soil surface are higher than biologic zero (5 degrees C, 41 degrees F). 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 (National Climatic Data Center, 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.
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 the National Climatic Data Center (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).
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 11, 12, and 13 (see WETS Table Example and Definitions).
Accommodating Missing Minimum Temperatures when Calculating 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 National Water and Climate Center sensitivity tests , 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.
Threshold Temperature Non-Occurance
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.
Missing Temperature and Precipitation Data
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. Because 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).
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.
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 western 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.
Example and Definitions
The WETS program summarizes temperature and precipitation, growing season lengths, and last and first freezing dates. 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. An example follows.
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.
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.
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.
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.
"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 (Soil Conservation Service, 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.
"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).
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.
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.
Precipitation Data Listing
At the end of the WETS Table is a listing of the precipitation data used to create the table. 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.
Climatic Data Elements
A climatic data element is a measured parameter which helps to specify the climate of a specific location or region, such as precipitation, temperature, wind speed and humidity. Descriptive terminology for climaticdata elements are:
Element Name - The full description of the element being referenced at the climate station (e.g., maximum temperature).
Element ID - Is a shortened identifier for the element, usually 4 characters in length (e.g., TMAX (maximum daily temperature), TMIN (minimum daily temperature), PRCP (precipitation, etc).
Element Duration - The interval between measurements of a data element. Common data element durations available for the station could include monthly, daily, or hourly.
More definitions can be found in the Climate Glossary.
Data Sources and Collection
The data used in the WETS Tables are observed by the National Weather Service (NWS) Cooperative Observer Program. This nationwide network consists of several thousand 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 data collection engine for creating WETS Tables is the Agricultural Applied Climate Information System (AgACIS). AgACIS was developed and is maintained by the NOAA Regional Climate Centers (RCCs) to manage the flow of information from climate data collectors to end users. Its main objective is to help people using climate data make management decisions.
- 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 wetlands determinations made in the middle of the growing season are more dependent on precipitation.
- Select stations with a minimum of 20 years of data.
- 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.
- 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.
AgACIS Climate Data Retrieval
Guidance for how to retrieve Agricultural Applied Climate Information System (AgACIS) climate data and summary reports.
Temperature and Precipitation Departure Probability Categories
Five categories of temperature and precipitation departures have been defined by the National Climatic Data Center (NCDC) and are in widespread use.Learn More
- 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.
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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. 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.