Engaging the Community in the Development of Physics for NWP Models

2020 ◽  
Author(s):  
Ligia Bernardet ◽  
Grant Firl ◽  
Dom Heinzeller ◽  
Laurie Carson ◽  
Xia Sun ◽  
...  
Keyword(s):  
Case Studies ◽  
Numerical Models ◽  
Weather Prediction ◽  
Forecast System ◽  
Linear Processes ◽  
Column Model ◽  
Model Code ◽  
Single Column ◽  
Single Column Model ◽  
The U.S

<p>Contributions from the community (national laboratories, universities, and private companies) have the potential to improve operational numerical models and translate to better forecasts. However, researchers often have difficulty learning about the most pressing forecast biases that need to be addressed, running operational models, and funneling their developments onto the research-to-operations process. Common impediments are lack of access to current and portable model code, insufficient documentation and support, difficulty in finding information about forecast shortcomings and systematic errors, and unclear processes to contribute code back to operational centers. </p><p>The U.S. Developmental Testbed Center (DTC) has the mission of connecting the research and operational Numerical Weather Prediction (NWP) communities. Specifically in the field of model physics, the DTC works on several fronts to foster the engagement of community developers with the Unified Forecast System (UFS) employed by the U.S. National Oceanic and Atmospheric Administration (NOAA).  As a foundational step, the UFS’ operational and developmental physical parameterizations and suites are now publicly distributed through the Common Community Physics Package (CCPP), a library of physics schemes and associated framework that enables their use with various models. The CCPP can be used for physics experimentation and development in a hierarchical fashion, with hosts ranging in complexity from a single-column model driven by experimental case studies to fully coupled Earth system models. This hierarchical capability facilitates the isolation of non-linear processes prior to their integration in complex systems. </p><p>The first public release of a NOAA Unified Forecast System (UFS) application is expected for February 2020, with a focus on the Medium-Range Weather Application. This global configuration uses the CCPP and will be documented and supported to the community. To accompany future public releases, the DTC is creating a catalog of case studies to exemplify the most prominent model biases identified by the US National Weather Service. The case studies will be made available to the community, who will be able to rerun the cases, to test their innovations and document model improvements. </p><p>In this poster we will summarize how we are using the UFS public release, the single-column model, the CCPP, and the incipient catalog of code studies to create stronger connections among the groups that diagnose, develop, and produce predictions using physics suites.</p>

scholarly journals Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite

2012 ◽  
Vol 93 (9) ◽  
pp. 1389-1400 ◽  
Author(s):  
R. A. J. Neggers ◽  
A. P. Siebesma ◽  
T. Heus
Keyword(s):  
Case Studies ◽  
General Circulation ◽  
Column Model ◽  
Parameterization Schemes ◽  
Numerical Predictions ◽  
Single Column ◽  
Weather And Climate ◽  
Single Column Model ◽  
Process Level

Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate.

scholarly journals Using a single column model (SGRIST1.0) for connecting model physics and dynamics in the Global-to-Regional Integrated forecast SysTem (GRIST-A20.8)

2020 ◽  
Author(s):  
Xiaohan Li ◽  
Yi Zhang ◽  
Xindong Peng ◽  
Jian Li
Keyword(s):  
Reference Model ◽  
Deep Convection ◽  
Operator Splitting ◽  
Shallow Convection ◽  
Forecast System ◽  
Time Step ◽  
Detailed Model ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. A single column model (SGRIST1.0) is developed as a tool for coupling a full-physics package (from Community Atmosphere Model, version 5 (CAM5)) to the Global-to-Regional Integrated forecast System (GRIST). In a two-step approach, the full-physics package is first isolated and coupled to SGRIST1.0 for reducing the uncertainties associated with model physics and assessing its behavior, then assimilated by the model dynamical framework. In the first step, SGRIST1.0 serves as a tool for evaluating the physical parameterization suite in the absence of 3D dynamics. Three single column model test cases, including the tropical deep convection, shallow convection, and stratocumulus, demonstrate that the parameterization suite mimics the behaviors in the observations and the reference model (SCAM) outputs. Cloud fraction, cloud liquid, and some other micro- and macro-physical variables are sensitive to the model time step, suggesting time-step dependency of the corresponding parameterization schemes. The second step couples the physics package to the 3D dynamical modeling system, and the verified parameterization suite works well in GRIST. Two physics-dynamics coupling strategies are examined and found to have a clear impact on the intensity of the simulated storm. The incremental operator splitting strategy (ptend_f1_f1), produces a weaker storm than the pure operator splitting strategy (ptend_f2_sudden). Comparing these two splitting approaches, the ptend_f2_sudden coupling strategy has higher large-step stability than the ptend_f1_f1 option, but the intensity of the simulated storm is substantially reduced by ptend_f2_sudden provided that the time step becomes quite large. Some detailed model configuration strategies are suggested when using the CAM5 parameterization suite in GRIST.

scholarly journals Improving Wind Predictions in the Marine Atmospheric Boundary Layer through Parameter Estimation in a Single-Column Model

2016 ◽  
Vol 145 (1) ◽  
pp. 5-24 ◽  
Author(s):  
Jared A. Lee ◽  
Joshua P. Hacker ◽  
Luca Delle Monache ◽  
Branko Kosović ◽  
Andrew Clifton ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Parameter Estimation ◽  
Atmospheric Boundary Layer ◽  
Weather Prediction ◽  
Sea Surface ◽  
Offshore Wind ◽  
Forecast Errors ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract A current barrier to greater deployment of offshore wind turbines is the poor quality of numerical weather prediction model wind and turbulence forecasts over open ocean. The bulk of development for atmospheric boundary layer (ABL) parameterization schemes has focused on land, partly because of a scarcity of observations over ocean. The 100-m FINO1 tower in the North Sea is one of the few sources worldwide of atmospheric profile observations from the sea surface to turbine hub height. These observations are crucial to developing a better understanding and modeling of physical processes in the marine ABL. In this study the WRF single-column model (SCM) is coupled with an ensemble Kalman filter from the Data Assimilation Research Testbed (DART) to create 100-member ensembles at the FINO1 location. The goal of this study is to determine the extent to which model parameter estimation can improve offshore wind forecasts. Combining two datasets that provide lateral forcing for the SCM and two methods for determining , the time-varying sea surface roughness length, four WRF-SCM/DART experiments are conducted during the October–December 2006 period. The two methods for determining are the default Fairall-adjusted Charnock formulation in WRF and use of the parameter estimation techniques to estimate in DART. Using DART to estimate is found to reduce 1-h forecast errors of wind speed over the Charnock–Fairall ensembles by 4%–22%. However, parameter estimation of does not simultaneously reduce turbulent flux forecast errors, indicating limitations of this approach and the need for new marine ABL parameterizations.

scholarly journals Large-Eddy Simulation and Single-Column Modeling of Thermally Stratified Wind Turbine Arrays for Fully Developed, Stationary Atmospheric Conditions

2015 ◽  
Vol 32 (6) ◽  
pp. 1144-1162 ◽  
Author(s):  
Adrian Sescu ◽  
Charles Meneveau
Keyword(s):  
Thermal Stratification ◽  
Layer Structure ◽  
Potential Temperature ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Shear Stresses ◽  
Column Model ◽  
Large Eddy ◽  
Single Column ◽  
Single Column Model

AbstractEffects of atmospheric thermal stratification on the asymptotic behavior of very large wind farms are studied using large-eddy simulations (LES) and a single-column model for vertical distributions of horizontally averaged field variables. To facilitate comparisons between LES and column modeling based on Monin–Obukhov similarity theory, the LES are performed under idealized conditions of statistical stationarity in time and fully developed conditions in space. A suite of simulations are performed for different thermal stratification levels and the results are used to evaluate horizontally averaged vertical profiles of velocity, potential temperature, vertical turbulent momentum, and heat flux. Both LES and the model show that the stratification significantly affects the atmospheric boundary layer structure, its height, and the surface fluxes. However, the effects of the wind farm on surface heat fluxes are found to be relatively small in both LES and the single-column model. The surface fluxes are the result of two opposing trends: an increase of mixing in wakes and a decrease in mixing in the region below the turbines due to reduced momentum fluxes there for neutral and unstable cases, or relatively unchanged shear stresses below the turbines in the stable cases. For the considered cases, the balance of these trends yields a slight increase in surface flux magnitude for the stable and near-neutral unstable cases, and a very small decrease in flux magnitude for the strongly unstable cases. Moreover, thermal stratification is found to have a negligible effect on the roughness scale as deduced from the single-column model, consistent with the expectations of separation of scale.

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