E-PWS-SCIExploratory actions on automatic present weather observations

Jitze P. van der Meulen,KNMI, the Netherlands

PB-OBS 8, 12-13 June 2003

Observing systemsExperiences thunderstorms, lightning ? snow OR rain OR hail OR mixture ? rain OR drizzle ? types of fog, obscuration to vision ? cloud amount (type) ? under cooled precipitation (icing) ?

Alternative policy on Observing system developments

- convert the data into information

data information

physicalquantities

temperature,wind, etc.

various typesof datasources

atmosphericmodels

algorithms

weatherinformation

Conversion matrix:INPUT: Data

ptu fd prec.remotesensing

atm.models

OUTPUT:Information (real

time) ptu

fd

(etc)

icing, slipperiness

cloud information

phenomena

Project rationale and objectives

To establish to what extent the information requested by a subset of the ET/AWS Table (related to present weather) can be obtained by using or combining current and future automatic observing techniques

To identify the needs for R&D work to progress towards a complete solution.

Prioritize PW-reports are of significance in case of (expected)

dangerous weather A number of variables can selected to be nominated as

primary PW variables with a high degrees of priority:1. The existence and rate of solid precipitation (esp.

snow)2. Icing (freezing of liquid precip) and its intensity

Other types of dangerous weather: current observing techniques are based on measuring the traditional physical quantities automatically and remote sensing techniques: low priority

Principle requirements (with recommended high performance, quality and without false alarms):

1. The ability to discriminate between solid and liquid precipitation (i.e. around freezing point).

2. The ability to measure precipitation rates (all types) accurately from a high level down to a very low level of intensity (in particular with respect to icing).

3. The ability to detect icing conditions, freezing precipitation and the accretion of ice.

4. The ability to have numerical data on cloudiness, radiation budget and state of the ground

variables are identified as with high relevance (1):

1. Temperature. Around freezing point: Air, dew point and surface temperature

2. Clouds: Position of cloud layers and cloud amount/coverage (coverage measured by satellites might be already accurate enough, so ground based measurements might be over-redundant)

3. Precipitation: Type, intensity and rate of ice accretion (typically the variables presented by PW-systems or weather identifiers)

4. Radiation: Net radiation (combination of global and long wave radiation; can be performed by the traditional surface based techniques in combination with satellite observations)

variables are identified as with high relevance (2):

1. Obscuration: MOR (or horizontal extinction coefficient; measurement is traditionally based on point measurement of the extinction coefficient)

2. Lightning: Intensity, polarity, type (can be performed by a regional network, therefore not relevant as output by an AWS to avoid confusion)

3. Other surface variables: Typically state-of-the-ground and snow depth

Promising technologies: Light scattering Radar signal reflection (Ultra)sounding and vibrating sensors to

detect hail, icing, etc Other types like simple detectors

Determination methods: Objective Subjective (acceptable?)

(currently) identified group/institutes

Swiss Federal Institute of Technology (ETH), Zurich: Development of a cloud mapping system using ground-based imagers

Institute für Meteorology und Klimaforschung, Karlsruhe: Development of an optical disdrometer and measurement of snow size spectra using radar.

Meteorologisches Institut, Universität Hamburg: Development of a vertically looking Micro Rain Radar (MRR)

Helsinki University of Technology and the Espoo-Vantaa Institute of Technology (Finland). Studies to enhance the performance of PWS by improving their algorithms.

Meteo France (Direction des Systèmes d'Observation de la Météorologie (DSO), Trappes): development of specific PW related instruments within the Solfege project

UKMO and Muir Matteson to determine cloud-types and visibility ranges based on digital image analyses.

Merge upper-air / satellite data

Upper air1. Radiosondes

2. AMDAR (from ascending and descending aircraft)

3. Profilers using (combined) RADAR, LIDAR or SODAR technologies

4. Doppler Weather Radar systems, also providing upper-air winds.

Satellites (EU projects)1. SATREP 2. CLOUDMAP

Targeted R&D for improving automatic PW observations/determinations         R&D TARGET #1, surface measurements:

Improved precipitation detection, discrimination and intensity (range: 0.02 mm/h - 2000 mm/h), with the ability to detect with high accuracy solid precipitation.

        R&D TARGET #2, upper air measurements:Cloudiness: classification and amount. (using satellite / ground based remote sensing)

Recommendations (General )

1. to continue the exploratory actions on automatic present weather observations

2. R&D activities to obtain more appropriate in situ observing technologies based on an integral concept of a set of observation technologies (using algorithms) should be further traced and stimulated.

3. Centers of R&D contributing today to the development of PWS should be contacted to stimulate a better understanding of the target requirements

4. Co-operation with the NMHS of USA & Canada on PWS development is recommended.

5. Tests on primary or additional sensors, which determine hail, freezing rain, etc., should be initiated.

Recommendations (General 2)

6. Decisions should be made if determining present weather using algorithms, more or less based on estimations or on pure empirical correlations are acceptable

7. A “performance” parameter (verification score or index), should be introduced and quantified for a better description of the functional specifications of PWS.

8. Developments in reporting weather from satellite observations should be considered seriously. Satellite weather reports should be accepted as an integral part of the synoptic observation network.

9. Surface measurements and upper-air measurements should be combined more effectively. The concept of a synoptic network with stand-alone AWS should be reconsidered by taking into account the ability of remote sensing the upper air by LIDAR and RADAR generating a 3D “image” of the atmosphere.

Recommendations (General 3)

10. As a result of new alternative sources informing the state of the atmosphere, the measurement of some specific parameters related to the present weather by PWS at AWS should be considered to discontinue.

11. In cases where automation is extremely costly (e.g. observation of specific phenomena) it should be considered to introduce camera systems for controlling the weather at a central location by human beings.

Proposals for action (1)1. To endorse by Eumetnet the two R&D targets on:

a. Precipitation: Improved detection, discrimination and intensity

b. Cloudiness: classification and amount2. To organize a management for the initiation, co-

ordination and stimulation of these targeted R&D activities within the Eumetnet countries.

3. To build up a relationship with R&D groups, in particular those nominated in this report, and with recognized experts on R&D to arrange new initiatives for R&D to meet the two recommended R&D targets.

Proposals for action (2)

1. To indicate proposals for R&D projects which meet the R&D targets

2. To draft proposals for the introduction of PW observing technologies and PW determination practices to be considered as standards.

3. To stimulate or initiate (in)formal meetings to exchange experiences, suggestions for new technologies and other relevant ideas on PWS.