scholarly journals Seasonal range test run with Global Eta Framework

2017 ◽  
Vol 14 ◽  
pp. 247-251 ◽  
Author(s):  
Dragan Latinović ◽  
Sin Chan Chou ◽  
Miodrag Rančić
Keyword(s):  
Model Performance ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Curvilinear Coordinates ◽  
Smooth Transition ◽  
Precipitation Pattern ◽  
Global Atmospheric Model ◽  
Coordinate Lines ◽  
Cubed Sphere

Abstract. Global Eta Framework (GEF) is a global atmospheric model developed in general curvilinear coordinates and capable of running on arbitrary rectangular quasi-uniform spherical grids, using stepwise (Eta) representation of the terrain. In this study, the model is run on a cubed-sphere grid topology, in a version with uniform Jacobians (UJ), which provides equal-area grid cells, and a smooth transition of coordinate lines across the edges of the cubed-sphere. Within a project at the Brazilian Center for Weather Forecasts and Climate Studies (CPTEC), a nonhydrostatic version of this model is under development and will be applied for seasonal prediction studies. This note describes preliminary tests with the GEF on the UJ cubed-sphere in which model performance is evaluated in seasonal simulations at a horizontal resolution of approximately 25 km, running in the hydrostatic mode. Comparison of these simulations with the ERA-Interim reanalyses shows that the 850 hPa temperature is underestimated, while precipitation pattern is mostly underestimated in tropical continental regions and overestimated in tropical oceanic regions. Nevertheless, the model is still able to well capture the main seasonal climate characteristics. These results will be used as a control run in further tests with the nonhydrostatic version of the model.

scholarly journals fv3gfs-wrapper: a Python wrapper of the FV3GFS atmospheric model

2021 ◽  
Vol 14 (7) ◽  
pp. 4401-4409
Author(s):  
Jeremy McGibbon ◽  
Noah D. Brenowitz ◽  
Mark Cheeseman ◽  
Spencer K. Clark ◽  
Johann P. S. Dahm ◽  
...  
Keyword(s):  
Model Performance ◽  
Atmospheric Model ◽  
Simulation Software ◽  
Storage Model ◽  
High Productivity ◽  
Global Atmospheric Model ◽  
Performance Requirements ◽  
Wide Range ◽  
Stringent Performance ◽  
Cubed Sphere

Abstract. Simulation software in geophysics is traditionally written in Fortran or C++ due to the stringent performance requirements these codes have to satisfy. As a result, researchers who use high-productivity languages for exploratory work often find these codes hard to understand, hard to modify, and hard to integrate with their analysis tools. fv3gfs-wrapper is an open-source Python-wrapped version of the NOAA (National Oceanic and Atmospheric Administration) FV3GFS (Finite-Volume Cubed-Sphere Global Forecast System) global atmospheric model, which is coded in Fortran. The wrapper provides simple interfaces to progress the Fortran main loop and get or set variables used by the Fortran model. These interfaces enable a wide range of use cases such as modifying the behavior of the model, introducing online analysis code, or saving model variables and reading forcings directly to and from cloud storage. Model performance is identical to the fully compiled Fortran model, unless routines to copy the state in and out of the model are used. This copy overhead is well within an acceptable range of performance and could be avoided with modifications to the Fortran source code. The wrapping approach is outlined and can be applied similarly in other Fortran models to enable more productive scientific workflows.

scholarly journals The Brazilian Global Atmospheric Model (BAM): Performance for Tropical Rainfall Forecasting and Sensitivity to Convective Scheme and Horizontal Resolution

2016 ◽  
Vol 31 (5) ◽  
pp. 1547-1572 ◽  
Author(s):  
Silvio N. Figueroa ◽  
José P. Bonatti ◽  
Paulo Y. Kubota ◽  
Georg A. Grell ◽  
Hugh Morrison ◽  
...  
Keyword(s):  
South America ◽  
Weather Prediction ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Southeastern Brazil ◽  
Rainfall Forecasting ◽  
Dynamical Core ◽  
Tropical Rainfall ◽  
Global Atmospheric Model ◽  
Convective Scheme

Abstract This article describes the main features of the Brazilian Global Atmospheric Model (BAM), analyses of its performance for tropical rainfall forecasting, and its sensitivity to convective scheme and horizontal resolution. BAM is the new global atmospheric model of the Center for Weather Forecasting and Climate Research [Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)], which includes a new dynamical core and state-of-the-art parameterization schemes. BAM’s dynamical core incorporates a monotonic two-time-level semi-Lagrangian scheme, which is carried out completely on the model grid for the tridimensional transport of moisture, microphysical prognostic variables, and tracers. The performance of the quantitative precipitation forecasts (QPFs) from two convective schemes, the Grell–Dévényi (GD) scheme and its modified version (GDM), and two different horizontal resolutions are evaluated against the daily TRMM Multisatellite Precipitation Analysis over different tropical regions. Three main results are 1) the QPF skill was improved substantially with GDM in comparison to GD; 2) the increase in the horizontal resolution without any ad hoc tuning improves the variance of precipitation over continents with complex orography, such as Africa and South America, whereas over oceans there are no significant differences; and 3) the systematic errors (dry or wet biases) remain virtually unchanged for 5-day forecasts. Despite improvements in the tropical precipitation forecasts, especially over southeastern Brazil, dry biases over the Amazon and La Plata remain in BAM. Improving the precipitation forecasts over these regions remains a challenge for the future development of the model to be used not only for numerical weather prediction over South America but also for global climate simulations.

scholarly journals Evaluation of the CAMS global atmospheric trace gas reanalysis 2003–2016 using aircraft campaign observations

2020 ◽  
Vol 20 (7) ◽  
pp. 4493-4521 ◽  
Author(s):  
Yuting Wang ◽  
Yong-Feng Ma ◽  
Henk Eskes ◽  
Antje Inness ◽  
Johannes Flemming ◽  
...  
Keyword(s):  
Chemical Species ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Trace Gas ◽  
Weather Forecasts ◽  
Global Atmospheric Model ◽  
Reactive Gases ◽  
Monitoring Service ◽  
Atmospheric Trace Gas ◽  
Atmospheric Concentrations

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) has produced a global reanalysis of aerosol and reactive gases (called CAMSRA) for the period 2003–2016. Space observations of ozone, carbon monoxide, NO2 and aerosol optical depth are assimilated by a 4D-Var method in the 60-layer ECMWF global atmospheric model, which for the reanalysis is operated at a horizontal resolution of about 80 km. As a contribution to the evaluation of the reanalysis, we compare atmospheric concentrations of different reactive species provided by the CAMS reanalysis with independent observational data gathered by airborne instrumentation during the field campaigns INTEX-A, INTEX-B, NEAQS-ITCT, ITOP, AMMA, ARCTAS, VOCALS, YAK-AEROSIB, HIPPO and KORUS-AQ. We show that the reanalysis rather successfully reproduces the observed concentrations of chemical species that are assimilated in the system, including O3 and CO with biases generally less than 20 %, but generally underestimates the concentrations of the primary hydrocarbons and secondary organic species. In some cases, large discrepancies also exist for fast-reacting radicals such as OH and HO2.

scholarly journals Vorticity-Divergence semi-Lagrangian Global Atmospheric Model SL-AV20: Dynamical Core

2016 ◽  
Author(s):  
Mikhail Tolstykh ◽  
Vladimir Shashkin ◽  
Rostislav Fadeev ◽  
Gordey Goyman
Keyword(s):  
Numerical Solutions ◽  
Climate Modeling ◽  
Region Of Interest ◽  
Weather Forecast ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
Medium Range Weather Forecast ◽  
Variable Resolution ◽  
Dynamical Core ◽  
Global Atmospheric Model

Abstract. SL-AV (Semi-Lagranginan Absolute Vorticity) is a global atmospheric model. Its latest version SL-AV20 provides global operational medium-range weather forecast with 20 km resolution over Russia. The lower resolution configurations of SL-AV20 are being tested for seasonal prediction and climate modeling. The article presents the model dynamical core. Its main features are vorticity-divergence formulation at the unstaggered grid, high-order finite-difference approximations, semi-Lagrangian semi-implicit discretization and the reduced latitude-longitude grid with variable resolution in latitude. The accuracy of SL-AV20 numerical solutions using reduced lat-lon grid and the variable resolution in latitude is tested with two idealized testcases. The results agree well with other published model solutions. It is shown that the use of the reduced grid having up to 25 % less grid points than the regular grid does not significantly affect the accuracy. Variable resolution in latitude allows to improve the accuracy of solution in the region of interest.

scholarly journals Limits, Variability, and General Behavior of Statistical Predictability of the Midlatitude Atmosphere

2008 ◽  
Vol 65 (1) ◽  
pp. 263-275 ◽  
Author(s):  
Richard Kleeman
Keyword(s):  
Initial Conditions ◽  
Storm Track ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Statistical Prediction ◽  
Ensemble Spread ◽  
Winter Storm ◽  
Global Atmospheric Model ◽  
Summer Storm

Abstract The nature of statistical predictability is analyzed in a T42 global atmospheric model that is able to adequately capture the main features of the midlatitude atmosphere. Key novel features of the present study include very large prediction ensembles and information theoretic techniques. It is found globally that predictability declines in a quasi-linear fashion with time for short-term predictions (3–25 days), while for long ranges (30–45 days) there is an exponential tail. In general, beyond 45 days the prediction and climatological ensembles have essentially converged, which means that beyond that point, atmospheric initial conditions are irrelevant to atmospheric statistical prediction. Regional predictions show considerable variation in behavior. Both of the (northern) winter storm-track regions show a close-to-quasi-linear decline in predictability toward a cutoff at around 40 days. The (southern) summer storm track shows a much more exponential and considerably slower decline with a small amount of predictability still in evidence even at 90 days. Because the winter storm tracks dominate global variance the behavior of their predictability tends to dominate the global measure, except at longer lags. Variability in predictability with respect to initial conditions is also examined, and it is found that this is related more strongly to ensemble signal rather than ensemble spread. This result may serve to explain why the relation between weather forecast skill and ensemble spread is often observed to be significantly less than perfect. Results herein suggest that the ensemble signal as well as spread variations may be a major contributor to skill variations. Finally, it is found that the sensitivity of the calculated global predictability to changes in model horizontal resolution is not large; results from a T85 resolution model are not qualitatively all that different from the T42 case.

scholarly journals Seasonal Performance of a Nonhydrostatic Global Atmospheric Model on a Cubed‐Sphere Grid

2021 ◽  
Vol 8 (4) ◽  
Author(s):  
Jung‐Eun Esther Kim ◽  
Myung‐Seo Koo ◽  
Changhyun Yoo ◽  
Song‐You Hong
Keyword(s):  
Atmospheric Model ◽  
Global Atmospheric Model ◽  
Seasonal Performance ◽  
Cubed Sphere

scholarly journals Evaluation of the CAMS global atmospheric trace gas reanalysis 2003–2016 using aircraft campaign observations

2019 ◽  
Author(s):  
Yuting Wang ◽  
Yong-Feng Ma ◽  
Henk Eskes ◽  
Antje Inness ◽  
Johannes Flemming ◽  
...  
Keyword(s):  
Chemical Species ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Trace Gas ◽  
Weather Forecasts ◽  
Global Atmospheric Model ◽  
Reactive Gases ◽  
Monitoring Service ◽  
Atmospheric Trace Gas ◽  
Atmospheric Concentrations

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) operated by the European Centre for Medium Range Weather Forecasts (ECMWF) has produced a global reanalysis of aerosol and reactive gases (called CAMSRA) for the period 2003–2016. Space observations of ozone, carbon monoxide, NO2 and aerosol optical depth are assimilated by a 4-D Var method in the 60-layer ECMWF global atmospheric model, which for the reanalysis is operated at a horizontal resolution of about 80 km. As a contribution to the evaluation of the reanalysis, we compare atmospheric concentrations of different reactive species provided by the CAMS reanalysis with independent observational data gathered by airborne instrumentation during the field campaigns INTEX-A, INTEX-B, NEAQS-ITCT, ITOP, AMMA, ARCTAS, VOCALS, YAK-AEROSIB, HIPPO and KORUS-AQ. We show that the reanalysis reproduces rather successfully the observed concentrations of chemical species that are assimilated in the system including O3 and CO with the biases generally less than 20 %, but generally underestimate the concentrations of the primary hydrocarbons and secondary organic species. In some cases, large discrepancies also exist for fast-reacting radicals such as OH and HO2.

scholarly journals The Evaluation of Real-Time Hurricane Analysis and Forecast System (HAFS) Stand-Alone Regional (SAR) Model Performance for the 2019 Atlantic Hurricane Season

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 617 ◽  
Author(s):  
Jili Dong ◽  
Bin Liu ◽  
Zhan Zhang ◽  
Weiguo Wang ◽  
Avichal Mehra ◽  
...  
Keyword(s):  
Real Time ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Forecast System ◽  
Improvement Project ◽  
Multi Scale ◽  
The North ◽  
Sar Model ◽  
Hydrostatic Model ◽  
Cubed Sphere

The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sphere (FV3) based convection-allowing HAFS Stand-Alone Regional model (HAFS-SAR) was successfully implemented during Hurricane Forecast Improvement Project (HFIP) real-time experiments for the 2019 Atlantic TC season. HAFS-SAR has a single large 3-km horizontal resolution regional domain covering the North Atlantic basin. A total of 273 cases during the 2019 TC season are systematically evaluated against the best track and compared with three operational forecasting systems: Global Forecast System (GFS), Hurricane Weather Research and Forecasting model (HWRF), and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model (HMON). HAFS-SAR has the best performance in track forecasts among the models presented in this study. The intensity forecasts are improved over GFS, but show less skill compared to HWRF and HMON. The radius of gale force wind is over-predicted in HAFS-SAR, while the hurricane force wind radius has lower error than other models.

scholarly journals fv3gfs-wrapper: a Python wrapper of the FV3GFS atmospheric model

2021 ◽  
Author(s):  
Jeremy McGibbon ◽  
Noah D. Brenowitz ◽  
Mark Cheeseman ◽  
Spencer K. Clark ◽  
Johann Dahm ◽  
...  
Keyword(s):  
Cloud Storage ◽  
Model Performance ◽  
Atmospheric Model ◽  
Simulation Software ◽  
Storage Model ◽  
High Productivity ◽  
Global Atmospheric Model ◽  
Performance Requirements ◽  
Wide Range ◽  
Stringent Performance

Abstract. Simulation software in geophysics is traditionally written in Fortran or C++ due to the stringent performance requirements these codes have to satisfy. As a result, these codes are often hard to understand, hard to modify and hard to interface with high-productivity languages used for exploratory work. fv3gfs-wrapper is an open-source Python-wrapped version of NOAA's FV3GFS global atmospheric model, which is coded in Fortran. The wrapper provides simple interfaces to progress the Fortran main loop and get or set state from the Fortran model. These interfaces enable a wide range of use cases such as modifying the behavior of the model, introducing online analysis code, or saving model state and reading forcings directly to and from cloud storage. Model performance is identical to the fully-compiled Fortran model, unless routines to copy state in and out of the model are used. This copy overhead is well within an acceptable range of performance, and could be avoided with modifications to the Fortran source code. The wrapping approach is outlined and can be applied similarly in other Fortran models to enable more productive scientific workflows.

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