The Use of a Wetness Sensor in Precipitation Measurements for the U.S. Climate Reference Network William G. Collins Short and Associates, Inc., NOAA/Office of Systems Development and NOAA/National Climatic Data Center Suitland, MD / Asheville, NC C. Bruce Baker NOAA/National Climatic Data Center, Asheville, NC

Use of Wetness Sensor for Precipitation Determination Description of Geonor precipitation gauge Characteristics of wetness sensor Description of precipitation algorithm for Geonor gauge The nature of wire variations and false precipitation reports Examples of wetness sensor use to eliminate false precipitation reports Statistics on the use of the wetness sensor Summary

Description of Geonor Precipitation Gauge Mass/depth of precipitation is determined by frequency of wire variation. Picture is of single transducer/wire Geonor gauge. CRN site gauges have three transducers/wires around gauge. transducer/ wire June 2002 FSL Forum

Characteristics of Wetness Sensor The wetness sensor detects water on active portion of sensor plate. An integrated heater dries out water droplets and condensation. Two values are produced—the first changes crisply from about 1000 for no precipitation (‘dry’) to low value for precipitation (‘wet’). The second value—not used— varies with precipitation intensity.

Description of Precipitation Algorithm for Geonor Gauge There is a single depth of liquid in Geonor gauge and yet three independent measurements of this depth. The precipitation algorithm— Determines which wires are operating properly and uses them to determine the precipitation. Balances between capturing small increases in depth and not counting ‘wire noise’ as precipitation. (Examples of why this is so difficult will be shown shortly.) Processes 5-min. data in 3-hour groups, with precipitation from the last hour becoming ‘official’.

The precipitation algorithm (cont.)— First task is to establish a reference depth level for each of the 3 wires. –If precipitation last time, then equal to last depth –If precipitation within last 2 hours, then unchanged from last time. –If no precipitation within last 2 hours, then average of depths for the wire from last 2 hours –All depths used are checked for reasonableness 5-min. change in depth is calculated for each wire Inter-wire depth change differences are used to determine which wires are performing correctly Depth changes exceeding 0.2 mm from good wires are used to calculate the precipitation.

The Nature of Wire Variations and False Precipitation Reports Geonor wire variations respond to: –Precipitation –Additions of anti-freeze and oil –Emptying of gauge –Diurnal sources (unidentified) –Evaporation –Additional ‘noise’ Next figure shows typical wire depth variations in the absence of precipitation.

Note: Moderate magnitude of variations Correlation of wire #2, #3 variations Different variation for wire #3 Magnitude exceeding 0.2 mm Evaporation over 8 days of about 1 mm There were false reports at: 1 July 1135 UTC 7 July 1135 UTC

Examples of Wetness Sensor Use to Eliminate False Precipitation Reports The next figure shows the good correspondence between the wire depth changes and the accumulated precipitation. (The wetness sensor was used to eliminate false reports.) The wire variations, except those caused by precipitation, are not well-shown. Succeeding figures will show the wire depths with the precipitation removed. (The precipitation was determined by the precipitation algorithm with the wetness sensor used.)

Note that individual wire variations are not well shown.

Note: Diurnal variation, noise, and evaporation.

Detail for July 2006

Statistics on the Use of the Wetness Sensor The wetness sensor has been found to be extremely reliable in its determination of when there is precipitation. Out of 159 months of data, there were found to be only 27 instances (.002% of sensor readings) when the wetness sensor indicated “dry” and more than one precipitation gauge had a non-zero amount of precipitation. The following figure shows the distribution of false report events per month for CRN sites.

Summary The use of a wetness sensor at CRN sites for the determination of ‘wet’ and ‘dry’ periods was described. The wetness sensor was found to have little error in its discrimination between ‘wet’ and ‘dry’ times. This study shows that the precipitation algorithm is vulnerable to false precipitation from sufficiently large Geonor wire variations that are positively correlated, and that the wetness sensor is effective in removing this precipitation.