A framework for testing global non‐hydrostatic models

Wedi, Nils; Smolarkiewicz, Piotr K.

doi:10.1002/qj.377

Cited by 70 publications

(87 citation statements)

References 40 publications

(75 reference statements)

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“…Obviously, there are many factors contributing to parametrization error within the design of the schemes themselves and so our truth forecasts will still be deficient at some level. Ideally, one would wish to have a truth forecast in which deep convection is explicitly represented but that is presently only achievable using the experimental 'small planet' configuration of the IFS [6]. In some respects, the present coarse-graining results could be interpreted as a lower bound on model error mainly associated with horizontal resolution truncation in NWP models.…”

Section: Coarse-graining Results From Ecmwf Forecastsmentioning

confidence: 98%

Assessing parametrization uncertainty associated with horizontal resolution in numerical weather prediction models

Shutts

Pallarès

2014

Phil. Trans. R. Soc. A.

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The need to represent uncertainty resulting from model error in ensemble weather prediction systems has spawned a variety of ad hoc stochastic algorithms based on plausible assumptions about sub-grid-scale variability. Currently, few studies have been carried out to prove the veracity of such schemes and it seems likely that some implementations of stochastic parametrization are misrepresentations of the true source of model uncertainty. This paper describes an attempt to quantify the uncertainty in physical parametrization tendencies in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System with respect to horizontal resolution deficiency. High-resolution truth forecasts are compared with matching target forecasts at much lower resolution after coarse-graining to a common spatial and temporal resolution. In this way, model error is defined and its probability distribution function is examined as a function of tendency magnitude. It is found that the temperature tendency error associated with convection parametrization and explicit water phase changes behaves like a Poisson process for which the variance grows in proportion to the mean, which suggests that the assumptions underpinning the Craig and Cohen statistical model of convection might also apply to parametrized convection. By contrast, radiation temperature tendency errors have a very different relationship to their mean value. These findings suggest that the ECMWF stochastic perturbed parametrization tendency scheme could be improved since it assumes that the standard deviation of the tendency error is proportional to the mean. Using our finding that the variance error is proportional to the mean, a prototype stochastic parametrization scheme is devised for convective and large-scale condensation temperature tendencies and tested within the ECMWF Ensemble Prediction System. Significant impact on forecast skill is shown, implying its potential for further development.

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Section: Coarse-graining Results From Ecmwf Forecastsmentioning

confidence: 98%

Assessing parametrization uncertainty associated with horizontal resolution in numerical weather prediction models

Shutts

Pallarès

2014

Phil. Trans. R. Soc. A.

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“…The aspects linked to the Earth's sphericity and rotation are not believed to have a specific impact on non-hydrostatic motion and therefore are not mentioned in the model description. It should finally be noted that the formulation of the EE system described here has also been jointly implemented (with ECMWF) in the global model IFS/ARPEGE for stretched and unstretched spherical geometries (Wedi and Smolarkiewicz, 2009), but this also is not further developed here, mainly because global NWP modelling does not currently allow resolutions fine enough for NH effects to become clearly beneficial. A version of the NH dynamical kernel for a 'deep atmosphere' has been implemented for both the global and limited-area versions of the dynamical kernel following Wood and Staniforth (2003), but for simplicity it is not used or documented here.…”

Section: Model Formulationmentioning

confidence: 99%

Dynamical kernel of the Aladin–NH spectral limited‐area model: Revised formulation and sensitivity experiments

Bénard

Vivoda

Mašek

et al. 2010

Quart J Royal Meteoro Soc

127

154

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† The contribution of C. Smith was written in the course of his employment at the Met Office, UK and is published with the permission of the controller of HMSO and the Queen's Printer for Scottland.Drawing from the results of theoretical studies about the behaviour of constantcoefficients semi-implicit schemes, the dynamical kernel of the Aladin-NH spectral limited-area numerical weather prediction (NWP) model has been modified in order to allow for a stable and efficient integration of the fully elastic Euler equations. The resulting dynamical kernel offers the possibility to use semi-Lagrangian transport schemes together with two-time-level discretizations at kilometric scales for NWP purposes. The main characteristics of the adiabatic part of the model formulation and the space and time discretization are described in this article. In order to illustrate the dependence of the results on adjustable parameters of the dynamical kernel, some real-case dynamical-adaptation forecasts performed with a basic physical parameterization package are presented. The results obtained with this model in real-case experiments fully confirm the conclusions drawn in previous numerical analysis studies. The good quality of the results is found to be compatible with a routine exploitation in a NWP framework. The Aladin-NH dynamical kernel has been used in the operational NWP 'AROME' model since December 2008 at the kilometric scale, with an appropriate physical parameterization package and data assimilation system.

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“…IFS, UM, GSM, GFS. SISL-based schemes guarantee boundedness of the solution and unconditional stability [96], which have the advantagecompared to explicit schemes-that they permit a relatively large time-step and a very competitive time-to-solution performance [24,73,105,111,114].…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Current and Emerging Time-Integration Strategies in Global Numerical Weather and Climate Prediction

Mengaldo

Wyszogrodzki

Diamantakis

et al. 2018

Arch Computat Methods Eng

Self Cite

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The continuous partial differential equations governing a given physical phenomenon, such as the Navier-Stokes equations describing the fluid motion, must be numerically discretized in space and time in order to obtain a solution otherwise not readily available in closed (i.e., analytic) form. While the overall numerical discretization plays an essential role in the algorithmic efficiency and physically-faithful representation of the solution, the time-integration strategy commonly is one of the main drivers in terms of cost-to-solution (e.g., time-or energy-to-solution), accuracy and numerical stability, thus constituting one of the key building blocks of the computational model. This is especially true in time-critical applications, including numerical weather prediction (NWP), climate simulations and engineering. This review provides a comprehensive overview of the existing and emerging time-integration (also referred to as time-stepping) practices used in the operational global NWP and climate industry, where global refers to weather and climate simulations performed on the entire globe. While there are many flavors of time-integration strategies, in this review we focus on the most widely adopted in NWP and climate centers and we emphasize the reasons why such numerical solutions were adopted. This allows us to make some considerations on future trends in the field such as the need to balance accuracy in time with substantially enhanced time-to-solution and associated implications on energy consumption and running costs. In addition, the potential for the co-design of time-stepping algorithms and underlying high performance computing hardware, a keystone to accelerate the computational performance of future NWP and climate services, is also discussed in the context of the demanding operational requirements of the weather and climate industry.

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A framework for testing global non‐hydrostatic models

Cited by 70 publications

References 40 publications

Assessing parametrization uncertainty associated with horizontal resolution in numerical weather prediction models

Assessing parametrization uncertainty associated with horizontal resolution in numerical weather prediction models

Dynamical kernel of the Aladin–NH spectral limited‐area model: Revised formulation and sensitivity experiments

Current and Emerging Time-Integration Strategies in Global Numerical Weather and Climate Prediction

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