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Short Term Ensemble Prediction System: STEPS

Short Term Ensemble Prediction System: STEPS. Alan Seed Centre for Australian Weather and Climate Research. Outline. Statistical structure of rainfall Modelling the errors in a nowcast Temporal development Radar reflectivity to rain rate conversion Tracking Nowcast ensembles

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Short Term Ensemble Prediction System: STEPS

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  1. Short Term Ensemble Prediction System: STEPS Alan Seed Centre for Australian Weather and Climate Research

  2. Outline • Statistical structure of rainfall • Modelling the errors in a nowcast • Temporal development • Radar reflectivity to rain rate conversion • Tracking • Nowcast ensembles • Radar only nowcasts • Radar + NWP blending • Products • Ensembles for end users • Expected rainfall – ensemble mean • Probability of exceeding various thresholds • Meteograms • Products • Developments • Conclusions The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  3. 15-min rainfall over the UK 1000 km (15 min) The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  4. Adelaide Radar – 250 km (10 min) The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  5. Auckland 10 km (2 min) 15 km x 7.5 km box, 100 m resolution The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  6. Variability as a function of scale Modelling 1000 km domain, eastern half of the HRRR region The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  7. Nowcast skill as a function of scale and lead time Widespread rain in Sydney The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  8. Outline • Statistical structure of rainfall • Modelling the errors in a nowcast • Temporal development • Radar reflectivity to rain rate conversion • Tracking • Nowcast ensembles • Radar only nowcasts • Radar + NWP blending • Products • Ensembles for end users • Expected rainfall – ensemble mean • Probability of exceeding various thresholds • Meteograms • Developments • Conclusions The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  9. Conceptual model for rainfall • Rainfall usually has areas of higher intensity rainfall inside areas of lower intensity rainfall, and we get clusters of storms and not just a random pattern of storms- variability over a wide range of scales • The lifetime of a storm increases with the size of the storm as a power law • The simplest model is a multiplicative cascade model (used to model turbulence) for the spatial scaling and a hierarchy of AR(1) models for the Lagrangian temporal evolution so as to reproduce the dynamic scaling of the field Temporal development of rainfall The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  10. Multiplicative Cascade Model for Turbulence Each cascade level evolves in time Rate of development decreases with increasing scale Hierarchy of AR(1) models used for temporal development Temporal development of rainfall Lovejoy et al., 1987 J. Geophys. Res. The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  11. 128-256-512 km 64-128-256 km 32-64-128km 16-32-64 km 8-16-32 km 4-8-16 km 2-4-8 km Spectral decomposition of a rainfall field Temporal development of rainfall The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  12. Radar Gauge Radar Z-R error is coherent over scales that are significant for urban hydrology Z - R Error Radar measurement error The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  13. Space & Time correlations of radar z-r error Villarini et al, WRR 45, W01404 2009 Z - R Error The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  14. Errors due to observing above ground level Sampling Error Correlation as a function of height separation for pairs of radar observations where one observation is at the base scan and the other is below the wet bulb freezing level. The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  15. Model of radar ZR and sampling errorsObserved and ensembles for 10-min rainfall Radar measurement error Modelling QPE Error Ensemble 1 Ensemble 2 Radar observation error model includes Z-R and sampling errors due to observing at a height above the ground Observation The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  16. Verification of radar error model Modelling QPE Error Reliability of probabilities Power specta of observed and perturbed fields The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  17. Other radar observation errors are tricky, depending on the situation and the QC algorithms used Daily rainfall accumulation for Melbourne Beam blocking Clutter Radar measurement error Modelling QPE Error The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  18. Modelling the tracking error • We do not have a complete description of tracking error • Generating fields of U,V error components that are correlated with each other and in space and time is VERY tricky- at least I do not know how to do it • Not the most important source of error in the first 6 hours so we can keep it simple • Multiply the radar U,V components by a random number that has a mean of 1 and some (small) variance Modelling Tracking Error The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  19. Outline • Statistical structure of rainfall • Modelling the errors in a nowcast • Temporal development • Radar reflectivity to rain rate conversion • Tracking • Nowcast ensembles • Radar only nowcasts • Radar + NWP blending • Products • Ensembles for end users • Expected rainfall – ensemble mean • Probability of exceeding various thresholds • Meteograms • Developments • Conclusions The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  20. Short Term Ensemble Prediction System- radar only • Estimate the advection field using rainfall fields • Estimate the AR(1) and cascade parameters using the current observed field • For each ensemble member • Perturb the radar analysis with the observation error model • Perturb the advection field • Generate a conditional stochastic field for the next 90 minutes Modelling STEPS-nowcast The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  21. Beijing Olympics: 1 hr forecast & observation STEPS-nowcast The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  22. Beijing 2008 inter-comparison • Compared STEPS against 5 other international systems during the Beijing Games STEPS-nowcast The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  23. Short Term Ensemble Prediction System- NWP blend • Decompose NWP into a cascade • Decompose the rainfall field into a cascade • Use radar field to estimate stochastic model parameters • Calculate the skill of the NWP at each level in the cascade using the correlation between NWP and radar • Blend each level in the radar & NWP cascades using weights that are a function of the forecast error at that scale and lead time • For each forecast • Add noise component to the deterministic blend, the weight of the noise is calculated using the skill of the blended forecast • Combine the cascade levels to form a forecast STEPS-NWP The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  24. Blending with NWP – calculating the weights STEPS-NWP The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  25. Nowcast explained variance as a function of scale and lead time STEPS-NWP The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  26. NWP explained variance as a function of scale STEPS-NWP The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  27. Weights for nowcast & NWP Blending STEPS-NWP The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  28. Outline • Statistical structure of rainfall • Modelling the errors in a nowcast • Radar reflectivity to rain rate conversion • Tracking • Temporal development • Nowcast ensembles • Radar only nowcasts • Radar + NWP blending • Products • Ensembles for end users • Expected rainfall – ensemble mean • Probability of exceeding various thresholds • Meteograms • Developments • Conclusions The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  29. Status • QPE and STEPS-nowcast running on LINUX workstations in operational mode • STEPS-NWP (radar + NWP blend) running on a super computer • 16 radars with QPE, 15 QPF domains • Generating 1000 products (100 Mbytes) per hour • Up to 100 clients inside the Bureau being served with products on a busy day • QPE live to the public for capital city radars • Planning to go live to the public with QPF in May 2011 Products The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  30. Rainfall Estimates • Melbourne, Sydney, Brisbane, Adelaide • 30, 60, 120 min, since 9 AM, daily accumulations blended with rain gauges and updated every 30 min • 10 min accumulations radar only with real-time gauge adjustments and updated every 6 or 10 minutes Products The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  31. Rainfall Forecasts: 0 – 90 minutes • 4 major cities, 1 km & 6 min resolution, 250 km domain • 3 Regional forecasts, 2 km & 10 min resolution, 500 km domain • 30 member ensemble updated every 6,10 minutes • 30, 60, 90 min accumulations of ensemble mean (expected rain) • Probability that rain accumulation will exceed 1,2,5,10,20,50 mm in next 60 minutes Forecast time series at a point with uncertainty shown 60 min accumulation Probability of rain > 50 mm Products The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  32. Rainfall forecasts: 1 – 6 hours • Melbourne, Sydney, Brisbane – 500 km domain, 2 km & 10 min resolution • 30 member ensemble updated every hour • 10-min forecasts of rainfall intensity out to 6 hours • Probability products for hourly accumulations for next 6 hours Probability of rain > 1 mm for 2 & 3 hour lead times, Melbourne Rainfall intensity forecast, 150 min lead time, Brisbane Products The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  33. Example from east Victoria – NWP The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  34. Example from east Victoria- STEPS Ensemble member 1 The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  35. Met Service Canada: Point Mode Paul Joe, 2010 The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  36. Met Service Canada: Point-Time Mode Paul Joe, 2010 PDF of rainrates at a point for all time lagged nowcasts The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  37. Met Service Canada: POP for a validtime and rainrate threshold Paul Joe, 2010 Rainrate threshold is 1 mm/h; number of hits exceeding threshold / number of samples (60) The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  38. Probability Probability of 60 min accum > 5 mm The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  39. Outline • Statistical structure of rainfall • Modelling the errors in a nowcast • Radar reflectivity to rain rate conversion • Tracking • Temporal development • Nowcast ensembles • Radar only nowcasts • Radar + NWP blending • Products • Ensembles for end users • Expected rainfall – ensemble mean • Probability of exceeding various thresholds • Meteograms • Developments • Conclusions The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  40. 25 km Qualitative severe weather warning • THESPA • Calculates the probability of a TITAN cell passing over a point in the next 60 minutes based on the current velocity and cell size and a climatological TITAN tracking error • Being developed for aviation applications and use in TIFS • TIFS • Operational in most Regional Forecast Centres • Automatic version for aviation is operational • Revising the software architecture • Graphical and automated text editing feature development Developments The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  41. Development: Closing the gap between NWP & nowcasts • Strategic Radar Enhancement Project • $48 M project over 7 years, 8 people for three years in CAWCR • 4 new radars • Radar data assimilation in ACCESS • Roll out of a new radar data quality control system for ~50 radars • Characterise radar errors for use in data assimilation (and QPE) • Assimilate radar data (LH nudging, Doppler radial winds, reflectivity) into high res (~2 km) NWP meso-scale models over capital cities • Seamless rainfall prediction • Integrate rainfall forecasts from 0 – 10 days lead time into a seamless forecast • Use STEPS to blend the forecasts from the various models • Develop a portal for convenient access to the rainfall forecasts The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  42. Seamless rainfall forecasts • Rainfall portal • Data source transparent to user • Aggregation • Disaggregation • New science • STEPS downscaling • Blending strategy • Verification (esp. transition periods) ACCESS-G AGREPS-G ECMWF EPS PME/GOCF GFE TIGGE? 3-10 day forecasts 2 x daily 40-100 km ACCESS-A ACCESS-C AGREPS-R ECMWF EPS PME/GOCF GFE Down-scaled and blended using STEPS 1-2 day forecasts 2-4 x daily 5-25 km Cross-cutting programs: ESM, CWD, OEB, NMOC ACCESS-A ACCESS-C GFE 1-24 hour forecasts 4-8 x daily 2-10 km 1-6 hour forecasts ACCESS-C STEPS-NWP hourly 1-2 km 10-90 min nowcasts every 10 min 1 km STEPS-nowcast The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  43. Issues • Limited capacity in the Regional Forecast Centres Head Office support branches to deploy and learn new nowcasting systems, busy with the Next Generation Forecast and Warning System – slows the adoption of new algorithms • Focus has been on improving the service adoption of existing nowcasting science through • Delivering the products through a range of platforms – 3drapic, Google maps, web pages • Using formats that are carefully designed and that conform to formal geo-spatial standards (eg CF compliant netCDF) • Serving the data on a range of platforms (ftp, SOAP, directories) • Formalising the use of QPE&F products in the forecast process • Training Developments The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

  44. Conclusions • Nowcasting rainfall is an uncertain business • Have incomplete description of the error structure of QPE and QPF • Have enough of a description to make useful stochastic ensemble models • There is still a lot of work to do to make the stochastic models include more meteorological knowledge • There is even more work to do to help the end-users make full use of the ensemble members in their decision support systems The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

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