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Considerations for the blending of multiple precipitation datasets for hydrological applications

Considerations for the blending of multiple precipitation datasets for hydrological applications. Luigi Renzullo Research Scientist CSIRO Land & Water, Canberra, Australia 4 th IPWG Workshop, Beijing, China 13 October 2008. Background: Water Information R & D Alliance - WIRADA.

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Considerations for the blending of multiple precipitation datasets for hydrological applications

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  1. Considerations for the blending of multiple precipitation datasets for hydrological applications Luigi Renzullo Research Scientist CSIRO Land & Water, Canberra, Australia 4th IPWG Workshop, Beijing, China 13 October 2008

  2. Background:Water Information R & D Alliance - WIRADA • Commonwealth Water Act 2007 • Australian Bureau of Meteorology (BoM) • Mandate: ”Manage Australia’s water resources information …”; • new responsibilities; new BoM Water Division formed. • Water Information Research and Development Alliance (WIRADA) • An R & D initiative between the BoM and CSIRO; • partnership of $50M over 5 years (started July 2008) • 10 WIRADA Projects • Research incl. Water Accounting & Assessment; Water Availability Forecasting (Short- & Mid- to Long-term); Sensor Networks & Water Informatics • WIRADA Project 10: Precipitation & Actual Evapotranspiration Products • Aim: Blend rainfall radar, rain gauge, satellite-based PPT and QPF’s to service the need of the hydrological modelling/monitoring and forecasting community • Help BoM Water Division deliver on their mandate by the Federal Govt. 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  3. What is desired? Water Forecasting Obs: ≤ 1 km resolution (may be < 5 km); ≤ 1 hourly rates (e)QPF’s: ≤ 1 hourly rates; > 48 hrs lead time Water Accounting Obs: ≤ 5 km resolution; ≤ daily accumulations; continental coverage Rainfall intensity distribution: rainfall duration; area/ fraction of catchment wet What is available? Rain gauges ~1000 report < 1 hour of event; ~2000 report < 24 hrs; ~7000 report daily accumulation ~ 6 months after end-of-year; sparse coverage Rainfall radar ~1 km reflectivities; ~10 mins; coverage limited to populous areas Satellite-based estimates rates reported 0.5-3 hourly intervals; ~6-25 km resolution; latency ~ several hrs; continental coverage QPFs (BoM) ~5 km (regional) to ~38 km (continental) resolution; lead times 12 hrs (meso-scale) – 72 (continental); ensembles available Precipitation information “wish list” “Current & historical gridded rainfall products at a scale & quality useful for hydrological application.” WIRADA Science Plan, May 2008 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  4. Issues & Project Aims • Disparate spatial resolution & temporal frequency between data sets • Areas of hydrological significance (e.g. headwater catchments) often inadequately represented • No individual, definitive PPT data set that meets all requirements • Blending multiple data sets is the key • Idea is not new – e.g. rainfall radar • Project aims to : • Develop strategies for blending multiple PPT data sets to derive gridded precipitation for use in water accounting & assessment, and the short- & long-term water availability forecasting. • Demonstrate use of PPT distribution info (e.g. intensity, duration) to improve estimation • Humble first steps • Quantify spatial & temporal difference between data sets 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  5. Gridded precipitation estimates in Australia TRMM-derived Daily rainfall 5 January 2005 0 mm d-1 25 mm d-1 Interpolated surfaces of daily rain gauge observations - Total rainfall in 24 hrs to 9am (local time) (a) BoM AWAP --- BILO (c) Daily rain gauges (5-jan-05) (b) QDNR & M --- SILO 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  6. 7 Nov 2005 – 1200 UTC 69.7 mm of rain in 24 hours to 9am EST on 8 Nov 2005 2100 0000 0300 0600 0900 1200 1500 1800 2100 0000 UTC 6 Nov 2005 7 Nov 2005 0700 1000 1300 1600 1900 2200 0100 0400 0700 1000 EST 7 Nov 2005 8 Nov 2005 TRMM daily rainfall (mm day-1) Deriving daily rainfall totals from TMPA 3B42 (post- real-time) product Huffman et al (2007), J. Hydrometeor.,5, 38-55 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  7. UTC + 8 UTC + 9.5 UTC + 10 Daily TRMM Rainfall (mm d-1) > TRMM daily rainfall (mm day-1) 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  8. Average Annual Rainfall 1998-2007 (mm yr-1) BILO SILO TRMM 1500 mm yr-1 0 mm yr-1 BILO - TRMM SILO - TRMM BILO - SILO 4th IPWG W/shop,Beijing, China, 13-17 October 2008 500 mm yr-1 0 -500 mm yr-1

  9. Closer look:Differences in orographic rainfall: BILO - TRMM BILO – TRMM (mm yr-1) West coast Tasmania Snowy Mt – Victorian Alpine Region Darling Escarpment, WA 500 Which one is correct? 0 -500 Elevation (m) 1300 700 100 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  10. Closer look:Average annual rainfall for major Drainage Divisions Average differences for each basin • BILO – SILO • generally between ±20 mm yr-1 • Surfaces – TRMM • generally between ±70 mm yr-1 Rainfall intensity distribution: rainfall duration; area/ fraction of catchment wet • Overall exception is Tasmania • BILO > SILO ~ 70 mm yr-1 • Surfaces > TRMM ~800 mm yr-1 Max Min 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  11. Changes in Terrestrial Water Storage from GRACE Tapley et al (2004), Science.,305, 503-505 Rodell et al. (2006) Hydrogeol. J., 15, 159-166 Swenson et al (2008), Water Resour. Res., 44. Tasmania Trends in average annual rainfall (selected basins) Murray BILO SILO TRMM 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  12. Max Min Average monthly rainfall (selected basins) West Plateau (N) Gulf of Carpentaria PPT (mm month-1) PPT (mm month-1) SW Coast Murray PPT (mm month-1) PPT (mm month-1) 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  13. 1200 Z 1200 Z 1200 Z 0900 Z 1500 Z 0600 Z 0300 Z 1800 Z 0000 Z 2100 Z 1500 Z 0900 Z 2100 Z 0000 Z 1800 Z 0300 Z 0600 Z 0000 Z 0100 Z 0200 Z 1300 Z 0400 Z 0500 Z 0600 Z 0700 Z 0800 Z 0900 Z 0300 Z 1800 Z 1100 Z 2300 Z 1000 Z 1500 Z 2200 Z 2000 Z 1400 Z 1700 Z 1900 Z 1600 Z 2100 Z mm/hr 0 Gridded precipitation estimates in Australia NWP comparisons with TRMM data BoM’s Limited Area Prediction System (LAPS) Data and forecast from 0000 – 2300 UTC on 8 June 2007 * Hunter Valley Floods June 2007 TRMM 3B42 TRMM 3B42RT LAPS 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  14. Comparison of daily accumulations (single event) • Hunter Valley Floods, NSW • June 2007 • >$500M insurance (2nd largest deployment in SES history) • 24 hr accumulations to 9am on 9 June 2007 • Areal means for ROI: (a) 88.3 mm d-1 (b) 85.3 mm d-1 (c) 82.1 mm d-1 (d) SILO = 96.6 mm d-1 ( a ) LAPS-0.375º ( b ) mesoLAPS-0.05º ( d ) SILO ( c ) TRMM 3B42 mm d-1 1 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  15. Monthly accumulations based on daily data 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  16. Final comments & future directions • Still early days in WIRADA PPT & AET Products Project • Impact of different PPT on Hydrological model = f(scale) • Impact of difference on estimation (whole range of hydrological applications) needs to be investigated  further refine the requirements • Future research tasks include: • Blending radar rainfall with rain gauge observations • Assess impact of using BoM’s best-practice corrected radar rainfall data on lumped-catchment stream flow estimation by: • quantifying rainfall duration (i.e. sub-daily rainfall intensity distribution); and • quantifying rainfall spatial extent over a catchment. • Disaggregating daily rainfall using rainfall intensity distributions • Examine pluviometer observations (6 minutely observations) to define rainfall intensity distribution (RID) functions and assess: • various interpolation schemes for estimating RID parameter values at non-pluviometer locations (incl. locations with only daily rainfall gauges); and • the errors/biases in RID estimates and impact on disaggregation results. • Blending near real-time satellite-based precipitation rates with real-time rain gauge observations • Calibrate near real-time satellite-based precipitation products using the available real-time rain gauge data to produce continental-scale near real-time maps of precipitation. • Statistical downscaling of quantitative precipitation forecasts • Explore statistical approaches for downscaling QPFs in near real-time, exploiting satellite- and real-time gauge observations when/where available for uptake in stream flow forecasting. • Using satellite-based precipitation observations to aid interpolation of archived daily rain gauge data • Use satellite-based precipitation estimates as a covariate (along with e.g. elevation, distance-from-coast, …) in the interpolation of rain gauge observations, thus assessing: • the utility of the satellite observations to give useful information between gauge locations; and • the suitability of the 0.5-3 hrly sampling frequency to provide useful information on rainfall duration rates at 0.5–3 hrly intervals to capture spatial information between gauges locations 4th IPWG W/shop,Beijing, China, 13-17 October 2008

  17. CSIRO Land and Water Dr Luigi J Renzullo Research Scientist Phone: +61 2 6246 5758 Email: Luigi.Renzullo@csiro.au Thank you Contact UsPhone: 1300 363 400 or +61 3 9545 2176Email: Enquiries@csiro.au Web: www.csiro.au

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