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Journal of Southern Hemisphere Earth Systems Science Journal of Southern Hemisphere Earth Systems Science SocietyJournal of Southern Hemisphere Earth Systems Science Society
A journal for meteorology, climate, oceanography, hydrology and space weather focused on the southern hemisphere
RESEARCH ARTICLE (Open Access)

APS2-ACCESS-C2: the first Australian operational NWP convection-permitting model

Greg Roff https://orcid.org/0000-0002-8428-3153 A * , Ilia Bermous A , Gary Dietachmayer https://orcid.org/0000-0001-8056-732X A , Joan Fernon A , Jim Fraser A , Wenming Lu A , Susan Rennie A , Peter Steinle https://orcid.org/0000-0002-0996-3386 A and Yi Xiao A
+ Author Affiliations
- Author Affiliations

A Australian Bureau of Meteorology, GPO Box 1289, Vic. 3001, Australia.

* Correspondence to: greg.roff@bom.gov.au

Journal of Southern Hemisphere Earth Systems Science 72(1) 1-18 https://doi.org/10.1071/ES21013
Submitted: 31 May 2021  Accepted: 8 December 2021   Published: 14 February 2022

© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of BoM. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

The Australian Bureau of Meteorology’s ‘Australian Parallel Suite’ (APS) operational numerical weather prediction regional Australian Community Climate and Earth-System Simulator (ACCESS) city-based system (APS1 ACCESS-C1) was updated in August 2017 with the commissioning of the APS2 ACCESS-C2. ACCESS-C2 runs over six regional domains. Significant upgrade changes included implementation of Unified Model 8.2 code; nesting in the 12 km resolution APS2 ACCESS-R2 regional model; and, importantly, an increased horizontal resolution from 4 to 1.5 km, enabling C2 to become the first Australian operational convection-permitting model (CPM). Traditional rainfall verification metrics and Fractions Skill Score show C2 forecast skill over ACCESS-C domains in summer and winter was generally, and in many cases, significantly better than C1. Case studies showed that C2 forecasts had better-detailed wind and precipitation fields, particularly at longer forecast ranges and higher rain rates. The improvements in C2 forecasts were principally due to its CPM ability to simulate high temporal and spatial resolution features, which continue to be of great interest to forecasters. C2 also laid the groundwork for the present day APS3 ACCESS-C forecast C3 and ensemble CE3 models and further development of higher resolution (down to 300 m) fire weather and urban models.

Keywords: ACCESS model, convection permitting model, Fractional Skill Score, high resolution NWP, verification metrics.


References

Bierdel L, Friederichs P, Bentzien S (2012) Spatial kinetic energy spectra in the convection-permitting limited-area NWP model COSMO-DE. Meteorologische Zeitschrift 21, 245–258.

Bryan GH, Wyngaard JC, Fritsch JM (2003) Resolution Requirements for the Simulation of Deep Moist Convection. Monthly Weather Review 131, 2394–2416.
Resolution Requirements for the Simulation of Deep Moist Convection.Crossref | GoogleScholarGoogle Scholar |

Bureau of Meteorology (2013) NMOC APS1 ACCESS-C Operational Bulletin No. 99. APS1 upgrade of the ACCESS-C Numerical Weather Prediction system. Available at http://www.bom.gov.au/australia/charts/bulletins/apob99.pdf

Bureau of Meteorology (2016a) BNOC Operations Bulletin No. 105. APS2 Upgrade to the ACCESS-G Numerical Weather Prediction System. Available at http://www.bom.gov.au/australia/charts/bulletins/APOB105.pdf

Bureau of Meteorology (2016b) BNOC Operations Bulletin No. 107. APS2 Upgrade to the ACCESS-R Numerical Weather Prediction System. Available at http://www.bom.gov.au/australia/charts/bulletins/apob107-external.pdf

Bureau of Meteorology (2018) NMOC Operations Bulletin Number 114 APS2 upgrade of the ACCESS-C Numerical Weather Prediction system. Available at http://www.bom.gov.au/australia/charts/bulletins/BNOC_Operations_Bulletin_114.pdf

Clark PA, Browning KA, Forbes RM, Morcrette CJ, Blythd AM, Leane HW (2014) The evolution of an MCS over southern England. Part 2: model simulations and sensitivity to microphysics. Quarterly Journal of the Royal Meteorological Society 140, 458–479.
The evolution of an MCS over southern England. Part 2: model simulations and sensitivity to microphysics.Crossref | GoogleScholarGoogle Scholar |

Clark PA, Roberts NM, Lean HW, Ballard SP, Charlton‐Perez C (2016) Convection‐permitting models: a step‐change in rainfall forecasting. Meteorological Applications 23, 165–181.
Convection‐permitting models: a step‐change in rainfall forecasting.Crossref | GoogleScholarGoogle Scholar |

Cooper S, Rennie S, Dietachmayer G, Steinle P, Xiao Y, Finch J, Marshall M (2020) ACCESS City Ensemble: Uncertainty in High Resolution NWP. Bureau of Meteorology Annual Research and Development Workshop. Available at http://www.bom.gov.au/research/workshop/2020/Talks/Shaun-Cooper.pdf

Davies T (2014) Lateral boundary conditions for limited area models. Quarterly Journal of the Royal Meteorological Society 140, 185–196.
Lateral boundary conditions for limited area models.Crossref | GoogleScholarGoogle Scholar |

Dos Reis JBC, Rennó CD, Lopes ESS (2017) Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil. Remote Sensing 9, 1240
Validation of Satellite Rainfall Products over a Mountainous Watershed in a Humid Subtropical Climate Region of Brazil.Crossref | GoogleScholarGoogle Scholar |

Evans A, Jones D, Smalley R, Lellyett S (2020) An enhanced gridded rainfall analysis scheme for Australia. Bureau of Meteorology Bureau Research Report 41. Available at http://www.bom.gov.au/research/publications/researchreports/BRR-041.pdf

Hagelin S, Son J, Swinbank R, McCabe A, Roberts N, Tennant W (2017) The Met Office convective-scale ensemble, MOGREPS-UK. Quarterly Journal of the Royal Meteorological Society 143, 2846–2861.
The Met Office convective-scale ensemble, MOGREPS-UK.Crossref | GoogleScholarGoogle Scholar |

Hartfield G (2017) How Convection-Allowing Models Have Changed Our World. Available at https://nwas.org/convection-allowing-models-changed-world/

Huffman GJ, Bolvin DT, Nelkin EJ (2017) Integrated Multi-satellite Retrievals for GPM (IMERG) Technical Documentation. Available at https://pmm.nasa.gov/sites/default/files/document_files/IMERG_technical_doc_3_22_17.pdf

Jakob D, Karoly DJ, Seed A (2011) Non-stationarity in daily and sub-daily intense rainfall – Part 2: Regional assessment for sites in south-east Australia. Natural Hazards and Earth System Sciences 11, 2273–2284.
Non-stationarity in daily and sub-daily intense rainfall – Part 2: Regional assessment for sites in south-east Australia.Crossref | GoogleScholarGoogle Scholar | 201

Matte D, Laprise R, Thériault JM, et al. (2017) Spatial spin-up of fine scales in a regional climate model simulation driven by low-resolution boundary conditions. Climate Dynamics 49, 563–574.
Spatial spin-up of fine scales in a regional climate model simulation driven by low-resolution boundary conditions.Crossref | GoogleScholarGoogle Scholar |

McBride J, Ebert E (2000) Verification of Quantitative Precipitation Forecasts from Operational Numerical Weather Prediction Models over Australia. Weather and Forecasting 15, 103–121.
Verification of Quantitative Precipitation Forecasts from Operational Numerical Weather Prediction Models over Australia.Crossref | GoogleScholarGoogle Scholar |

Mesinger F (2008) Bias Adjusted Precipitation Threat Scores. Advances in Geosciences 16, 137–142.
Bias Adjusted Precipitation Threat Scores.Crossref | GoogleScholarGoogle Scholar |

Mittermaier M, Roberts NM, Thompson SA (2013) A long term assessment of precipitation forecast skill using the fractions skill score. Meteorological Applications 20, 176–186.
A long term assessment of precipitation forecast skill using the fractions skill score.Crossref | GoogleScholarGoogle Scholar |

Prein AF, Langhans W, Fosser G, et al. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53, 323–361.
A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.Crossref | GoogleScholarGoogle Scholar | 27478878PubMed |

Puri K, Dietachmayer D, Steinle P, Dix M, Rikus L, Logan L, Naughton M, Tingwell C, Xiao Y, Barras V, Bermous I, Bowen R, Deschamps L, Franklin C, Fraser J, Glowacki T, Harris B, Lee J, Le T, Roff G, Sulaiman A, Sims H, Sun X, Sun Z, Zhu H, Chattopadhyay M, Engel C (2013) Implementation of the initial ACCESS numerical weather prediction system. Australian Meteorological and Oceanographic Journal 63, 265–284.

Rennie S, Rikus L, Eizenberg N, Steinle P, Krysta M (2020) Impact of Doppler Radar Wind Observations on Australian High-Resolution Numerical Weather Prediction. Weather and Forecasting 35, 309–324.
Impact of Doppler Radar Wind Observations on Australian High-Resolution Numerical Weather Prediction.Crossref | GoogleScholarGoogle Scholar |

Roberts NM, Lean HW (2008) Scale-selective verification of rainfall accumulations from high resolution forecasts of convective events. Monthly Weather Review 136, 78–96.
Scale-selective verification of rainfall accumulations from high resolution forecasts of convective events.Crossref | GoogleScholarGoogle Scholar |

Seed A, Duthie E, Chumchean S (2007) Rainfields: the Australian Bureau of Meteorology system for quantitative precipitation estimation. Proc. 33rd Conf. on Radar Meteorology, Cairns, Australia. Available at https://ams.confex.com/ams/33Radar/techprogram/paper_123340.htm

Seed A, Bell A, Steinle P, Rennie S (Eds) (2019) Forecasting Demonstration Project – Sydney 2014. Bureau of Meteorology Bureau Research Report 46. Available at http://www.bom.gov.au/research/publications/researchreports/BRR-046.pdf

Skamarock WC (2004) Evaluating Mesoscale NWP Models Using Kinetic Energy Spectra. Monthly Weather Review 132, 3019–3032.
Evaluating Mesoscale NWP Models Using Kinetic Energy Spectra.Crossref | GoogleScholarGoogle Scholar |

Sweeney CP, Lynch P, Nolan P (2013) Reducing errors of wind speed forecasts by an optimal combination of post-processing methods. Meteorological Applications 20, 32–40.
Reducing errors of wind speed forecasts by an optimal combination of post-processing methods.Crossref | GoogleScholarGoogle Scholar |

Tang Y, Humphrey WL, Bornemannb J (2013) The benefits of the Met Office variable resolution NWP model for forecasting convection. Meteorological Applications 20, 417–426.
The benefits of the Met Office variable resolution NWP model for forecasting convection.Crossref | GoogleScholarGoogle Scholar |

Tennant W (2015) Improving initial condition perturbations for MOGREPS-UK. Quarterly Journal of the Royal Meteorological Society 141, 2324–2336.
Improving initial condition perturbations for MOGREPS-UK.Crossref | GoogleScholarGoogle Scholar |