Solar Intelligence Lessons learnt in Australia Bruce W Forgan Observation & Infrastructure Branch Observations and Infrastructure Division Australian Bureau of Meteorology (ABoM)

Some Australia Statistics Climate: Desert & semi-arid - low rainfall Significant solar resources Populations: Aust 23 M Population Centres: >80% in 12 cities Energy source: fossil fuels National renewable solar plans: Solar Flagships (Aust)

BoM Solar Measurements Primary Focus: Data for Environmental Intelligence NationalInternational Climatology Water balance Global Climate Observing System (BSRN) Agriculture Architecture Materials degradation Solar power generation Numerical Weather Prediction WIGOS (WMO) CIMO (WMO) Global Atmosphere Watch (GAW) ~13 year cycle of boom and bust for solar resourcing monitoring since 1960s

Surface Network – pre – 1992 ‘Weather’ Solar Network Global exposure (30 min) Global & Diffuse (30 min) Tuned to 1963 Model (Archer, 1963) All major climate events tuned out

Post 1992: Bureau approach to solar monitoring Multi-Tiered approach initiated in st Tier – 3 state-of-art BSRN stations including in situ calibration 2 nd Tier – Basic network using identical instrumentation and protocols as tier 1 except reduced in situ calibration and audit frequency – Number fluctuates due to measurement priorities(13 -> 5 -> 13 -> ?) 3rd Tier – Satellite products – daily, hourly, (10 min) global & direct exposures

Fit for Purpose Basic - U95 Global Time ResolutionTier 1 GCOS Tier 2 Basic Tier 3 Satellite+ 1 minute (Wm -2 ) minutes (kJm -2 )1.83.5? Hour (kJm -2 ) * Day (kJm -2 ) * Monthly Daily Mean (kJm -2 )* Yearly (MJm -2 ) * 25 (7) 37 (10) 150 (45) * Can be dominated by either under-sampling or missing data + To surface network kWhm -2

Surface network – Basic Station

Standard Station Measurements Solar ( nm) – Direct (total) pyrheliometer (body temperature) – Direct Spectral transmission (412, 500, 610, 778, (368, 812,868), 10 nm FWHM) – Diffuse pyranometer (body temp) – (Global pyranometer, body temp) Terrestrial (>4000 nm) – shaded pyrgeometer Data acquisition – 1 Hz archived – Minute signal statistics (mean, max, min, std. devn, U95.) distributed – Sunshine seconds (120 Wm -2, 95 Wm --2, 144 Wm --2 ………) – ‘quick look’to intranet every 10 minutes – Daily for processing post midnight – Cleaning (and attendance) monitor – Local statistics for observer Ancillary – All weather elements monitored at the Bureau staffed station (T,P,RH,Ceilometer, ‘daily’ cleaning…….)

Surface Network: QA/QC

Surface Network: Irradiance Outputs

Aerosol Optical Depth Climate

Solar Flagships – Up to 4 large scale solar power stations – $Aust 1.5 billion Solar Mapping (+ ancillary data) component – Geoscience Australia, National Geographic Information Group $5 million – BoM solar resource component (~$Aust 3 m of $5m)

Partnership with Geosciences Australia: Pre-competitive mapping portal Regions of High Prospectivity Spatial Analysis resource mapping layers Solar Data National Datasets vegetation energy networks – electricity gas water sources infrastructure land tenure digital elevation Solar radiation, slope, aspect, proximity to grid………………

Project deliverables Gridded datasets (0.05° grid over Australian land) –Time series of daily & monthly global exposure (1990-) –Monthly climatologies of hourly global & direct exposure Uncertainty characterisation of each dataset Detailed online supporting information & metadata

Surface network & Solar Flagships expansion

How Many Stations Do We Need?

Benefits to Bureau Better quality, adjustment and uncertainty assessment of existing satellite data products Temporary network expansion provides data for analysing optimal network for satellite adjustment and assessment Some improvement in Climate Centre data handling - free 1 minute data access from web - total data set (station years satellite) for cost of media (~$200 for 1 Tb) Preparation of user support information to reduce Bureau staff interaction and better data use

User Support Services Enhance metadata and measurement intelligence Basic terminology Radiation theory and the relationship with other weather Discussion about instrumentation and processes Discussion of uncertainty International standards and benchmarking Practical data issues Delivering one minute solar statistics

Satellite-surface comparisons Before & after June 2012 revision for Solar Flagships project

What the Solar Flagships project does not provide Expanded network operation beyond Dec 2013 Viable climatology and long-term representativeness (e.g. typical year) Ability to adjust satellite data when new satellites come on stream in 2015

Lessons Learnt Typical 13 year boom-bust cycle for solar monitoring support Spending more on capital equipment and QA reduces the total end-to-end cost for fit-for-purpose data Solar power resource, water budgeting & climate change dominate the requirement for ‘high quality’ low U95 over long time scales – so work together Solar resource monitoring requirements push solar monitoring metrology to the practice limit.

Lessons Learnt Not having target uncertainties reduces network governance and effectiveness Redundancy & continuity are just as important as instrument calibration A good working definition: High quality measurements are those that require minimal cost to demonstrate they are fit for purpose

ACCESS-A Satellite MALAPS Second data NWP forecasts research Future Uses with NWP