A Limited Area Modeling Capability for the Finite‐Volume Cubed‐Sphere (FV3) Dynamical Core and Comparison With a Global Two‐Way Nest

Black, Thomas L.; Abeles, J.; Blake, Benjamin T.; Rogers, Eric; Zhang, X.; Aligo, Eric; Dawson, Logan C.; Ying, Lin; Strobach, Edward; Shafran, P.; Carley, Jacob R.

doi:10.1029/2021ms002483

Cited by 15 publications

(4 citation statements)

References 45 publications

(92 reference statements)

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“…The National Centers for Environmental Prediction (NCEP) is currently developing the Rapid Refresh Forecast System (RRFS; Carley et al., 2021) as part of an effort to unify the NCEP operational forecast modeling systems using the finite volume cubed sphere (FV3; Putman & Lin, 2007) dynamical core. The RRFS is planned to run at a convection‐allowing grid spacing of 3 km using the FV3 limited area model (LAM; Black et al., 2021). The RRFS will replace current NCEP operational convection‐allowing model (CAM) systems that are based on the Weather Research and Forecasting (WRF; Skamarock et al., 2008) and Nonhydrostatic Multiscale Model on the B‐grid (Janjić & Gall, 2012; Janjić et al., 2001) dynamic cores which have been extensively evaluated, developed and tuned as a CAM over the years (e.g., Aligo et al., 2018; Clark et al., 2015; Grasso et al., 2014; Johnson & Wang, 2017, 2019; Johnson, Wang, Xue, & Kong, 2011; Kain et al., 2008; Weisman et al., 2008).…”

Section: Introductionmentioning

confidence: 99%

“…at a convection-allowing grid spacing of 3 km using the FV3 limited area model (LAM; Black et al, 2021). The RRFS will replace current NCEP operational convection-allowing model (CAM) systems that are based on the Weather Research and Forecasting (WRF; Skamarock et al, 2008) and Nonhydrostatic Multiscale Model on the B-grid (Janjić & Gall, 2012;Janjić et al, 2001) dynamic cores which have been extensively evaluated, developed and tuned as a CAM over the years (e.g., Aligo et al, 2018;Clark et al, 2015;Grasso et al, 2014;Johnson & Wang, 2017, 2019Kain et al, 2008;Weisman et al, 2008).…”

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confidence: 99%

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Verification and Model Configuration Sensitivity of Simulated ABI Radiance Forecasts With the FV3‐LAM Model

Johnson

Wang

Blake

et al. 2023

Earth and Space Science

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This study evaluates simulated radiance forecasts from a series of controlled experiments consisting of FV3‐LAM forecasts with different configurations of model physics and vertical resolution. The forecasts were produced during the 2020 Hazardous Weather Testbed Spring Forecasting Experiments on the same forecast cases. The evaluation includes grid‐point, neighborhood‐based and object‐based verification. The experiments include forecasts that were identical except for the physics (EMC‐LAM vs. EMC‐LAMx), vertical resolution (EMC‐LAMx vs. NSSL‐LAM), or combined initial conditions, physics and vertical resolution (GSL‐LAM). It is found that the EMC‐LAM generally provided better simulated radiance forecasts than the other three configurations at most forecast lead times, due to its unique physics configuration. All configurations generally over‐forecasted high level clouds. EMC‐LAM reduced the over‐forecasting of high clouds, but also under‐forecasted the coverage of mid‐level clouds. In contrast, at early lead times the EMC‐LAM had relatively poor performance relative to the other forecasts. Furthermore, EMC‐LAM was an outlier in terms of the vertical structure of clouds. It is also found that the NSSL‐LAM consistently improved upon the EMC‐LAMx, which had fewer vertical levels than NSSL‐LAM. Compared to EMC‐LAMx, NSSL‐LAM had less cloud over‐forecasting bias, especially with small cloud objects, and less overall error. The differences between EMC‐LAMx and GSL‐LAM were generally much smaller than the differences between EMC‐LAMx and EMC‐LAM/NSSL‐LAM. Finally, it is found that a non‐linear bias correction conditioned on symmetric brightness temperature reduced the overall root‐mean‐square error by about a factor of 2 while improving the unrealistic vertical structure of clouds in the EMC‐LAM.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Verification and Model Configuration Sensitivity of Simulated ABI Radiance Forecasts With the FV3‐LAM Model

Johnson

Wang

Blake

et al. 2023

Earth and Space Science

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“…Although JEDI also supports the limited area model version of FV3 (FV3‐LAM, Black et al., 2021), capabilities to assimilate regional data sets within JEDI for regional applications are still limited. No paper has been formally published testing and evaluating JEDI with FV3‐LAM according to our knowledge.…”

Section: Introductionmentioning

confidence: 99%

Implementation and Testing of Radar Data Assimilation Capabilities Within the Joint Effort for Data Assimilation Integration Framework With Ensemble Transformation Kalman Filter Coupled With FV3‐LAM Model

Park

Xue

Liu

2023

Geophysical Research Letters

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Capabilities to directly assimilate radar data are implemented within the local ensemble transform Kalman filter (LETKF) and the gain‐form LETKF (LGETKF) algorithms of the Joint Effort for Data assimilation Integration (JEDI) system. The capabilities are evaluated for the analysis and forecast of a severe convection case of 20 May 2019 in the Southern Great Plains using the limited area model version of the FV3 dynamical core (FV3‐LAM) from a recent release for Short‐Range Weather Application (SRW App). The LETKF and LGETKF implementations are shown to produce analyses and short‐range forecasts comparable to those using the ensemble square‐root Kalman Filter (EnSRF) within the Gridpoint Statistical Interpolation (GSI) framework used by current NCEP operational models. In addition, LGETKF retaining only 60% variances for model‐space vertical localization performs similarly to LGETKF retaining 99% of variance and LETKF using observation error‐based vertical localization. JEDI LETKF shows better parallel scalability than LGETKF and GSI EnSRF.

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“…Given the computational expense of GSRMs, for practical NWP and climate applications it remains necessary for national meteorological centers to use a regional nested approach to provide high‐resolution local scale information (Black et al., 2021; Dipankar et al., 2020; Milbrandt et al., 2016; Tang et al., 2013). This technique involves nesting a convection‐permitting (<5 km resolution) limited area model (LAM) inside a parameterized convection parent (global) model.…”

Section: Introductionmentioning

confidence: 99%

Impact of Domain Size on Tropical Precipitation Within Explicit Convection Simulations

Jones,

Sanchez,

Lewis

et al. 2023

Geophysical Research Letters

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We investigate the sensitivity of modeled tropical precipitation accumulation, intensity and structures to the extent of convection‐permitting limited area model (LAM) domain size. Our comparison focusses on two LAM domains, with identical physical parameterization schemes and using 2.2 km grid spacing. One LAM domain spans almost the full tropical belt while the other focusses on southeast Asia. We show that the LAMs both capture the complex diurnal cycle of precipitation and that the timing and intensity of precipitation are comparable with satellite observations. Systematic differences between the LAMs are largest within ∼1,000 km of the western and eastern boundaries of the southeast Asia LAM. This is due to convective spin‐up at the western boundary of the southeast Asia LAM and a lack of propagating deep convection. We highlight that showing the added value of global storm‐resolving models by comparing with LAMs will help to accelerate their operational implementation.

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A Limited Area Modeling Capability for the Finite‐Volume Cubed‐Sphere (FV3) Dynamical Core and Comparison With a Global Two‐Way Nest

Cited by 15 publications

References 45 publications

Verification and Model Configuration Sensitivity of Simulated ABI Radiance Forecasts With the FV3‐LAM Model

Verification and Model Configuration Sensitivity of Simulated ABI Radiance Forecasts With the FV3‐LAM Model

Implementation and Testing of Radar Data Assimilation Capabilities Within the Joint Effort for Data Assimilation Integration Framework With Ensemble Transformation Kalman Filter Coupled With FV3‐LAM Model

Impact of Domain Size on Tropical Precipitation Within Explicit Convection Simulations

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