© Crown copyright Met Office New UK AWS System On-going Work Mike Molyneux and Matt Clark

© Crown copyright Met Office Outline – what’s coming Background Challenges for a network Overview Sensor details Performance snapshots Quick look at MMS Windows

© Crown copyright Met Office Who am I? Mike Molyneux United Kingdom - Met Office Team Leader for Development of Loggers Sensors For use in Automatic Weather Stations

© Crown copyright Met Office Background The UK Met Office is refreshing the infrastructure of its network of Automatic Weather Stations. 200 AWS interfacing to a variety of sensors This is titled Meteorological Monitoring System - MMS project.  MMS is NOT… “Mike Molyneux’s System”

© Crown copyright Met Office Scope of the Project At the start of the project some decisions were made on the scope of replacement. Broadly it was chosen to: Retain existing sensors (but not possible at all stations) Retain existing communication method at site Retain existing signal wiring Benefits – uniformity – response to customers needs – improved network management – cost saving – NOT ON DAY ONE! Issues Side-by-Side testing Other infrastructure example surge protection

© Crown copyright Met Office Network Challenges. Point A - Ensuring the best performance from complex instruments in remote locations Forward scatter - precipitation type Ultrasonic rangefinder - snow depth Laser rangefinder – cloud height Improved Error flagging Direct talk through for Engineers Link to “Tivoli” monitoring/alarm system “ITIL” best practice in support Older systems hard to migrate to best practice

© Crown copyright Met Office Expectations are very high in Climate Science Network Challenges. Point B – Quality of the measurements in many locations Top quality loggers – improved Engineering diagnostics

© Crown copyright Met Office Existing systems The UK has been using four major AWS systems. SAMOS - Semi-Automatic Met Observing System for manned and unmanned stations ESAWS - Extended Synoptic Automatic Weather Station an older unmanned system CDL - Climate data logger. Based on Campbell Scientific Loggers largely for simple sites SIESAWS – Severe Icing Environment Synoptic Automatic Weather Station for remote sites with a high icing environment

© Crown copyright Met Office SAMOS SAMOS – ISU - Intelligent sensor units Interfacing, processing, transmit onto the LAN LAN Configuration change from “ring” to “star”

© Crown copyright Met Office Network Challenges. Point C Move forward BUT control change  Re-Use existing Sensors  Largely achieved  Copy Algorithms and quality processes  Copied from our most common system but with 4 systems this can only minimise change

© Crown copyright Met Office Project Outline

© Crown copyright Met Office Project Outline System Specification The important parts of our existing systems Invitation to Tender Lots of high quality replies of course! Main Supplier CSE-Servelec Foundation in UK Water industry Campbell Scientific Limited Loggers Well known in meteorological industry

© Crown copyright Met Office Project Outline continued Design specification – to optimise components and software to meet specific requirements Test plan – Functional tests + data snapshots and longer side-by-side tests Internal “Process change” (more later) Sites installed by Campbell and Met Office teams

© Crown copyright Met Office Status in November 2008 Rollout program well underway for unmanned sites, 2 Manned test sites in operation in “Continuous Operational Monitoring” – These sites have different routines – so testing is more comprehensive. Data snapshots later Data Quality values and coding checks by our “QC team” at Edinburgh Final detailed rules being applied to Observer interface

© Crown copyright Met Office MMS overview diagram Issues Manned and unmanned sites Secure and open sites Components Firewalls DMZs

© Crown copyright Met Office AWS - Sensors Sensors interfaced to the AWS Parameter details

© Crown copyright Met Office ParameterTypeDetail Screen TemperaturePlatinum Resistance Thermometer Bought to external standard. Accurate and repeatable Calibration stable over 8 years. Sampled 4 times a minute Wind speedCup anemometerLightweight Vector instruments. Frequency output, sampled at 4 Hz Wind DirectionWind vaneLightweight Vector instruments. Linear Resistance, sampled at 4 Hz Station Level Pressure Triple cell Vaisala PTB220 for Aviation use. Serial output VisibilityForward Scatter Meter Belfort Instruments Sampled 2 times a minute Serial output Present WeatherForward Scatter plus, capacitive rainmeter and thermometer Vaisala FD12P Sampled 2 times a minute Serial output

© Crown copyright Met Office ParameterTypeDetail Cloud baseLaser rangefinder Belfort and Vaisala. Sampled 2 times a minute Serial output Cloud coverTime series cloud base strikes Exponential Decay over 40 minutes RainfallTipping BucketResolution of 0.2mm Area 750 sq cm 15 cc per tip Snow depthUltra Sonic range finder Campbell Scientific SR50 Grass, concrete and soil Temperature Resistance Thermometer or thermistor Calibration stable over 8 years. Sampled 4 times a minute Screen humidityCapacitive ProbeRotronics Hygroclip

© Crown copyright Met Office ParameterTypeDetail RadiationShortwave radiometer Kipp and Zonen CM11 MilliVolt output sampled at.5 Hz SunshineMultiple sensor unit Kipp and Zonen CSD1 MilliVolt output sampled at.5 Hz Severe Icing Environment Wind speed and direction Sonic anemometer Heated Thies unit – serial output Severe Icing Environment Temperature Thermistor, directly on “shaking” whip mount Self de-icing method – assuming radiative errors are acceptable

© Crown copyright Met Office AWS - Sensors Sensor Performance Snapshots Data snapshots

© Crown copyright Met Office Temperature Minute data – separate and same screens Day time variation within the screen Bias checked – not thermometer/logger Differential Radiative Heating?

© Crown copyright Met Office Wet bulb Temperature Ten minute samples Good agreement PRT same measurement as dry bulb

© Crown copyright Met Office RH probe values Minute data – separate screens Separation and probes introduce variabilty

© Crown copyright Met Office Wind direction Minute data Good agreement

© Crown copyright Met Office Wind speed Minute data – same mast Rounding is visible at times Averages and spread good

© Crown copyright Met Office Visibility Different instruments Good agreement

© Crown copyright Met Office AWS - Sensors Algorithms Cloud and Present Weather

© Crown copyright Met Office The “EDA” EDA - Exponential Decay Algorithm The EDA is a “sky condition algorithm” Cloud amount calculated from the LCBR Developed in-house Compared well with others

© Crown copyright Met Office Present Weather Arbiter Software to control Present Weather Instrument output and provide backup using input from Sensitive precipitation detector Screen Thermometer Visiometer Anemometer LCBR Results have been studied and a scoring system developed - outcome the arbiter improves results

© Crown copyright Met Office Process change Now we’ve got a new system we have to use it properly! System value will come from new ways of using it

© Crown copyright Met Office Process change Training for Engineers and Network managers Training for Observers But also Identification of key processes Processes have to change and be documented - they will evolve Remember to capture new requirements Start using improved methods coded output to database

© Crown copyright Met Office Examples of MMS windows Quick Selection of MMS User Screens All Web access (No easy interfaces to old systems)

© Crown copyright Met Office Examples of MMS windows

© Crown copyright Met Office Examples of MMS windows

© Crown copyright Met Office Examples of MMS windows

© Crown copyright Met Office Examples of MMS windows

© Crown copyright Met Office Examples of MMS windows

© Crown copyright Met Office Examples of MMS windows

© Crown copyright Met Office Hard work can be fun but…

© Crown copyright Met Office That’s all Any questions?

© Crown copyright Met Office