OTT PARSIVEL - ENHANCED PRECIPITATION IDENTIFIER AND NEW GENERATION

Transcription

1 OTT PARSIEL - ENHANCED PRECIPITATION IDENTIFIER AND NEW GENERATION OF PRESENT WEATHER SENSOR BY OTT MESSTECHNIK, GERMANY Authors: (1) Kurt Nemeth OTT Messtechnik GmbH & Co. KG Ludwigstrasse Kempten Germany () Martin Löffler-Mang HTW Fachbereich GIS Goebenstrasse Saarbruecken Germany (1) k.nemeth@ott-hydrometry.com () loeffler-mang@htw-saarland.de Abstract OTT Parsivel : Laser based optical Disdrometer for simultaneous measurement of PARticle Size and ELocity of all liquid and solid precipitation. The state of the art instrument features a multipurpose meteorological instrument for all weather conditions as present weather sensor, optical precipitation gauge, enhanced precipitation identifier, and disdrometer for spectrum classification, visibility and radar reflectivity. Parsivel can be operated as reliable and unattended sensor for automatic weather stations and /or as PC based instrument for science or meteorological applications. The comparison of radar reflectivity between Parsivel and weather radar shows reasonable results and radar reflectivity of Parsivel can be considered even as alternative data source. Parsivel can support and improve significantly the quality based information of the weather radar with ground based enhanced precipitation data. 1. SYSTEM DESCRIPTION 1.1. Background and design requirements The design requirements for the instrument lead to a universal Commercial Off-The-Shelf (COTS) equipment which meets substantially the meteorological and hydrological requirements of the sensor specification according to WMO and NWS regulation as an enhanced precipitation identifier and present weather sensor. The patented extinction method for simultaneous measurements of particle size and velocity of all liquid and solid precipitation performs the direct physical measuring principle and classification of hydrometeors. The instrument provides a full picture of the precipitation event in all weather phenomena and provides accurate reporting of precipitation types and intensities without degradation of performance in severe outdoor environments. Parsivel operates in any climate weather regime and the incorporated heating device minimizes the negative effect of freezing and frozen precipitation accreting critical surfaces on the instrument. 1

2 This piece of equipment detects and identifies 8 different precipitation types as drizzle, mixed drizzle/rain, rain, mixed rain/snow, snow, snow grains, freezing rain and hail. The output data - consisting of raw data, classification related to size and velocity of particles, rain accumulation and intensity, present weather reports and housekeeping data - make the instrument suitable to any kind of meteorological and hydrological application. Fig. 1: OTT Parsivel - Enhanced Precipitation Identification Sensor Parsivel can be integrated into an Automated Surface/Weather Observing System (ASOS/AWOS) as part of the sensor suite. The derived data can be processed and included into the transmitted weather observation report and messages (WMO, SYNOP, METAR and NWS codes). The new generation of Parsivel disdrometer provides the latest state of the art laser optical technology. The data performance has been tested successfully in comparison with a meteorological observer with a distinction rate better than 97%. Due to modern and high speed DSP technology the wide spectrum of precipitation from drizzle to tropical rain with extreme intensities up to 0 mm/min can be acquired and processed without limitation regarding influence of wind and effecting catching orifice problems concerning conventional rain gauges. The instrument supports meteorological observer missions in general and weather service missions for improving severe winter weather warnings for snow and ice conditions, flood forecast and warnings, support to aviation and road traffic, and severe thunderstorm forecast and warnings. The derived radar reflectivity coefficient together with ground based precipitation data improves essentially the performance of the spatial weather radar information, improves the regional weather forecasts and high water early warning system by combination and correlation of precise and overall precipitation network data. 1.. Parsivel feature unique performance Patented extinction measurement procedure Unattended and reliable operation, using maintenance-free laser technology Operable in all environmental and weather conditions (lightning protection and self-regulated heating) Low power and heating operation by software commands Identification of all precipitation types, including mixed precipitation in the melting layer Comprehensive precipitation analysis using -dimensional distribution of size and velocity Special measuring head prevents secondary spectra caused by drops splashing on the sensor head Transmitter and receiver head in perfect design with no obstacles for precipitation catching

3 1.3. Extinction measuring principle The new generation of enhanced precipitation identifier measures directly each single hydrometeor and performs a revolutionary change compared to forward scattered laser optical systems which needs additional sensors onboard and is based on experimental and proofed algorithm to determine the rain rate and identification of precipitation types. U U i U i D A) B) t t C) v A) The sensor's transmitter unit generates a flat, horizontal beam of light, which the receiver unit converts into an electric signal. Fig. : Extinction measuring principle B) This signal changes whenever a hydrometeor falls through the beam anywhere within the measurement area C) The degree of dimming is a measure of the hydrometer s size, and together with duration of the signal, the fall velocity can be derived Multipurpose instrument featuring enhanced precipitation measurements The full data output of precipitation is accomplished with additional algorithm and the derived data make the instrument suitable for the use in various meteorological and hydrological applications featuring five single instruments in one unique unit: Present Weather Sensor ww - Code Parsivel isibility in Precipitation Extinction- Coefficient Rain Gauge Rain Rate Energy of Precipitation Soil Erosion Z/R-Correlation Adjustment of weather Radars Flood waters warning Fig. 3: Meteorological and hydrological applications 3

4 . THE DIFFERENT FEATURES OF THE PARSIEL.1. Precipitation Measurements designed for determining the distribution and amount of precipitation can be carried out maintenance-free with Parsivel, regardless of the intensity, duration or type of precipitation. Additionally, its composition i. e. the distribution of particles with respect to their type is obtained directly from the measured sizes and velocities of each single particle and is recorded statistically... Present Weather Sensor (PWS) The present weather and the types of precipitation (rain, drizzle, snow, hail and sleet) are classified in accordance with a weather code established by the WMO. Unmanned weather stations require automatic detection, reliably and unambiguously. Parsivel can ascertain the type, quantity and composition of the hydrometeor and the atmospheric visibility in every kind of weather!.3. Monitoring of disposal sites The functions of precipitation kinetic energy distribution and precipitation measurement are utilised by Parsivel to record the effect of rain on the condition of the disposal sites in conjunction with other sensors, e. g. ground-condition probes..4. Monitoring road conditions Local intense precipitation can lead to aquaplaning or packed snow on roads. Therefore, rapid traffic warning and control systems are necessary in order to prevent accidents. Precipitation measurement, hydrometeor composition and atmospheric visibility are of considerable importance in such systems. Parsivel is an integrated instrument that measures all required parameters in accurate quality and performance..5. Flood early warning To assure a timely warning of impending high water it is necessary to measure the amount and spatial distribution of precipitation rapidly and accurately. This goal can be achieved by combining weather radar measurements (spatial information with reduced accuracy) and ground based disdrometer measurements: Parsivel provides drop size distributions on the ground and a function to derive a local Z/R relation ready to be used to adjust the radar data. In combination with water level sensors and drainage modelling, a high-performance regional flood early warning system can be erected..6. Expert Software ASDO The corresponding Software ASDO monitors the outdoor precipitation event to comfortable indoor evaluation with windows performance. 4

5 Fig. 4: Screenshot ASDO Tabular view and D Mode The sensor transmits all data to a PC and supports the observer with full information of present weather and precipitation and provides a history of precipitation falls stored in a data base. Present weather icon, all derived precipitation data and weather codes as well as housekeeping data like supply, voltage laser output energy and firmware related information are displayed as digital information. Fig. 5: Screenshot ASDO- 3D Mode The precipitation spectrum can be evaluated as graphical displays and spectrum distribution in and 3 dimensional mode. All data are stored in a powerful data base and can be retrieved by browser with related date and time and displayed in equal form as online display. All configuration tasks like time interval from 10 sec to 10 minutes, baud rate and size of telegram and others can be selected and stored as configured variables. 5

6 3. COMPARISON WITH WEATHER RADAR 3.1. Radar reflectivity in case of rain Conventional precipitation radars measure the radar reflectivity which is the total backscatter cross section of all scatterers divided by the pulse volume P. If the Rayleigh approximation is valid and the individual particles are assumed to be spherical with a diameter D k, can be written as = 1 P 5 K k = 4 P P P D (1) 6 k where is the wavelength and K = ( r 1) ( r + ) is the dielectric factor ( r = n ; r relative permittivity, n complex index of refraction). The equivalent radar reflectivity factor Z e is defined as Z e 5 4 K = () w where w K is the dielectric factor for water, indicating that the scatterers are expected to be water spheres. In rain K in (1) is identified by K w. Therefore, the estimate of the radar reflectivity factor from measured drop size distributions, Z M, can be expressed as the sixth moment of the drop size distribution with respect to the volume, N D ) : ( Z M = N( D ) D dd (3) 6 Because rain drops with a volume equivalent diameter, D, larger than 1 mm are oblate rather than spherical, the backscatter cross sections of these particles differ from those of spheres with the same volume. The difference depends on the departure from the spherical shape and the spatial distribution of their orientation. The error in estimating Z e with (3) (when assuming the drops are spherical with a diameter equal to D ) is not considered a predominant source of error compared to other uncertainties when comparing radar measured Z e to estimates from ground measurements of drop size distributions. Therefore, (3) can be accepted to be a good estimate of Z e. In the case of Parsivel the integral can be evaluated as a sum over discrete measured size classes by: Z M = i ni D tfv 6 i i (4) where n i = number of measured drops in class i during time t, D i = mean diameter in class i, F = measuring area, and v i = mean velocity of drops in class i. The denominator tfv i is neccessary because the drops are counted by area and time and have to be transferred to a volume distribution. Here t was chosen as 30 s. 6

7 50 a) 40 PARSIEL radar reflectivity dbz radar time in hours 50 b) 40 radar reflectivity in dbz PARSIEL radar time in hours Fig. 6: a) Time series of the radar reflectivity factor in dbz during a rain event, 6 May 1999, 00:00-04:00 CEST, comparison of measured (C-Band Radar, dashed line) and estimated data from drop size spectra (Parsivel, solid line); additionally, the error bars represent the standard deviation of the area average of the radar data. b) Same as a), but for the period 04:00-08:00 CEST. 7

8 Reflectivity data in dbz are presented for the early hours of 6 May 1999 (Figs. a and b) derived (i) from drop size distributions obtained by the optical disdrometer Parsivel and (ii) from radar data. The Parsivel was mounted on a platform in the Forschungszentrum Karlsruhe, 0 m to the side and 15 m below the antenna of the C-band-radar ( = 5.4 cm). For further operational concepts Parsivel can be connected directly at weather radar site and installed in the surrounding of the radar in order to provide differentiated radar support data for calibration purpose. For a reasonable comparison, the radar signals were averaged over a complete azimuthal scan on the lowest elevation (0.4 degrees) in the nearest range gate (1.5 to km) using the following procedure: A volume scan was performed every 5 minutes, then the spatial average and standard deviation of the innermost scan-circle was calculated. This average was taken as an estimate of the radarmeasured, five-minute averaged reflectivity at the radar site. The spatial standard deviation provides an indication of the uncertainty of that estimate. From the drop size distribution measured with Parsivel, Z M was calculated every 30 s with (4) and then averaged over five minutes. During the 8 hours of measurement, Z e (radar) attained values between 5 and 40 dbz. The spatial standard deviation of the radar data (error bars), which also serves as a measure for the spatial homogeneity of the rainfall, ranged from 10 to 40 dbz (minimum at 0:30 hours, maximum at 6:15 hours). From 3:30 hours its level increased from 15 dbz to the maximum and then came to rest at a level of approximately 5 dbz. The compared data agree reasonably well when taking the error bars into account, since most differences between radar means and Parsivel estimates range from 0 to ± 5 dbz and do not exceed 10 dbz. Point measurements are compared with volume data! 3.. Estimation of radar reflectivity from snow measurements In case of snow it is also possible to calculate some radar reflectivity factors from the measured snow size spectra. But a lot of more aspects have to be taken into account. For readers who are interested in such estimations there exists a special paper: M. Löffler-Mang and U. Blahak, Estimation of the Equivalent Radar Reflectivity Factor from Measured Snow Size Spectra. J. Appl. Meteorol., ol. 40, No. 4, pp , April 001. OTT MESSTECHNIK GmbH & Co. KG Ludwigstraße 16 D Kempten GERMANY Tel. 0831/ Fax 0831/ info@ott-hydrometry.de 8