Progress in ensemble forecasting and verification methodologies at ECMWF

<p>This talk focusses on progress in ensemble forecasting methodology (Part I) and ensemble verification methodology (Part II).</p><p>Operational ECMWF ensemble forecasts are global predictions from days to months ahead. At all forecast ranges, model uncertainties are represented stochastically with the Stochastically Perturbed Parametrization Tendency scheme (SPPT). Recently, considerable progress has been made in developing the Stochastically Perturbed Parametrization scheme (SPP). The SPP scheme offers improved physical consistency by naturally preserving the local conservation properties for energy and moisture of the unperturbed version of the corresponding parametrization. In contrast, the SPPT scheme lacks such local conservation properties, mainly because the scheme does not perturb fluxes at the surface and at the top of the atmosphere consistently with the tendency perturbations in the column.</p><p>NWP research and development relies on scoring rules to judge whether or not a change to the forecast systems results in better ensemble forecasts. A new tool will be presented that can improve the understanding of score differences between sets of forecasts for a widely used proper score, the Continuous Ranked Probability Score (CRPS). An analytical expression has been derived for the CRPS when a homogeneous Gaussian (hoG) forecast-observation distribution is considered. This leads to an approximation of the CRPS when actual verification data are considered, which deviate from a homogeneous Gaussian distribution. The hoG approximation of the CRPS permits a useful decomposition of score differences. The methodology will be illustrated with verification data for medium-range weather forecasts.</p>

Radiative properties of coated black carbon aggregates: numerical simulations and radiative forcing estimates

The formation of black carbon fractal aggregates (BCFAs) from combustion and subsequent aging involves several stages resulting in modifications of particle size, morphology, and composition over time. To understand and quantify how each of these modifications influences the BC radiative forcing, the radiative properties of BCFAs are modelled. Owing to the high computational time involved in numerical modelling, there are some gaps in terms of data coverage and knowledge regarding how radiative properties of coated BCFAs vary over the range of different factors (size, shape, and composition). This investigation bridged those gaps by following a state-of-the-art description scheme of BCFAs based on morphology, composition, and wavelength. The BCFAs radiative properties were investigated as a function of the radius of the primary particle (ao), fractal dimension (Df), fraction of organics (forganics), wavelength (λ), and mobility diameter (Dmob). The radiative properties are calculated using the multiple sphere T-matrix (MSTM) method. Amongst size, morphology, and composition, all the radiative properties showed the highest variability with changing size. The cross-sections varied from 0.0001 μm2 to 0.1 μm2 for BCFA Dmob ranging from 24 nm to 810 nm. After size or Dmob, the absorption cross-section (Cabs) and BC mass absorption cross-section (MACBC) showed the highest sensitivity towards composition or forganics, whereas the asymmetry parameter (g) showed higher dependence on morphology, which is represented by Df. The Ångstrom absorption exponent varied from 1.06 up to 3.6 and increases with the fraction of organics (forganics). The values of the absorption enhancement factor (Eλ) were found between 1.01 and 3.28 in the visible spectrum. The Eλ was derived from Mie calculations for coated volume equivalent spheres, and from MSTM for coated BCFAs. Mie calculated enhancement factors were found to be larger by a factor of 1.1 to 1.5 than their corresponding values calculated from the MSTM method. It is shown that radiative forcings are highly sensitive towards modifications in morphology and composition. The black carbon radiative forcing ΔFTOA (Wm−2) decreases up to 61 % as the BCFA becomes more compact in morphology. Whereas, there is a decrease of > 50 % in ΔFTOA as the organic content of the particle increase up to 90 %. Based on our results, which showed a significant effect of coating and morphology on the BC radiative properties, a parametrization scheme for radiative properties of BC fractal aggregates was developed, which is applicable for modelling, ambient, and laboratory-based BC studies. The parameterization scheme for the cross-sections (extinction, absorption, and scattering), single scattering albedo (SSA), and asymmetry parameter (g) of pure and coated BCFAs as a function of Dmob were derived from tabulated results of the MSTM method. Spanning over an extensive parameter space, the developed parametrization scheme showed promisingly high accuracy up to 98 % for the cross-sections, 97 % for single scattering albedos (SSA), and 82 % for asymmetry parameter (g).

Systematic error analysis of heavy-precipitation-event prediction using a 30-year hindcast dataset

The western Mediterranean region is prone to devastating flash floods induced by heavy-precipitation events (HPEs), which are responsible for considerable human and material losses. Quantitative precipitation forecasts have improved dramatically in recent years to produce realistic accumulated rainfall estimations. Nevertheless, there are still challenging issues which must be resolved to reduce uncertainties in the initial condition assimilation and the modelling of physical processes. In this study, we analyse the HPE forecasting ability of the multi-physics-based ensemble model Prévision d’Ensemble ARPEGE (PEARP) operational at Météo-France. The analysis is based on 30-year (1981–2010) ensemble hindcasts which implement the same 10 physical parameterizations, one per member, run every 4 d. Over the same period a 24 h precipitation dataset is used as the reference for the verification procedure. Furthermore, regional classification is performed in order to investigate the local variation in spatial properties and intensities of rainfall fields, with a particular focus on HPEs. As grid-point verification tends to be perturbed by the double penalty issue, we focus on rainfall spatial pattern verification thanks to the feature-based quality measure of structure, amplitude, and location (SAL) that is performed on the model forecast and reference rainfall fields. The length of the dataset allows us to subsample scores for very intense rainfall at a regional scale and still obtain a significant analysis, demonstrating that such a procedure is consistent to study model behaviour in HPE forecasting. In the case of PEARP, we show that the amplitude and structure of the rainfall patterns are basically driven by the deep-convection parametrization. Between the two main deep-convection schemes used in PEARP, we qualify that the Prognostic Condensates Microphysics and Transport (PCMT) parametrization scheme performs better than the B85 scheme. A further analysis of spatial features of the rainfall objects to which the SAL metric pertains shows the predominance of large objects in the verification measure. It is for the most extreme events that the model has the best representation of the distribution of object-integrated rain.

Comparing the diurnal cycle of precipitation in models and observations at different spatial scales over China

<p>Climate models have a long-standing bias in the diurnal cycle of precipitation over land - they produce peak rainfall at local midday, when insolation is at its maximum. As part of the COnvective Scale Modelling In China (COSMIC) project, we investigate this bias over China using high-resolution (13 km) global simulations with the HadGEM3 model. We compare the diurnal cycle of summer precipitation with satellite observations of precipitation from CMORPH. The simulations are run with and without a convection parametrization scheme, as this scheme has been shown to be important for controlling the timing of precipitation. We analyse the amount, frequency and intensity of the precipitation, investigating their diurnal cycle and spatial distribution.</p><p>The analysis is performed on a grid-point scale, as well as at larger scales based on the catchment basins across the region. Catchment basins provide a natural way of linking the meteorological precipitation data to the underlying physical geography of the region, in a way which is useful for decision makers and could be used to provide information to hydrological models in the future. We present a simple Python tool for performing the analysis: BAsin-Scale Model Assessment ToolkIt (BASMATI).</p><p>In line with previous studies, we find that the simulation performed with parametrized convection produces precipitation over land which peaks too early in the day. The simulation performed with explicit convection generally produces peaks in precipitation which occur later in the day - closer in time to the observed peak. By comparing our results with published work, we find that the presence or absence of a convection parametrization scheme is more important for determining the spatial distribution of the time of peak precipitation than the resolution of the simulations. We present comparisons of precipitation in the simulations and observations performed at grid points and over catchment basins using BASMATI. The catchment basins are chosen based on their size, which allows for the comparison to be done as a function of spatial scale.</p>

Systematic errors analysis of heavy precipitating events prediction using a 30-year hindcast dataset

The western Mediterranean region is prone to devastating flash-flood induced by heavy precipitation events (HPEs), which are responsible for considerable human and material damage. Quantitative precipitation forecasts have improved dramatically in recent years to produce realistic accumulated rainfall estimations. Nevertheless, challenging issues remain in reducing uncertainties in the initial conditions assimilation and the modeling of physical processes. In this study, the spatial errors resulting from a 30-year (1981–2010) ensemble hindcast which implement the same physical parametrizations as in the operational Météo-France short-range ensemble prediction system, Prévision d'Ensemble ARPEGE (PEARP), are analysed. The hindcast consists of a 10-member ensemble reforecast, run every 4-days, covering the period from September to December. 24-hour precipitation fields are classified in order to investigate the local variation of spatial properties and intensities of rainfall fields, with particular focus on the HPEs. The feature-based quality measure SAL is then performed on the model forecast and reference rainfall fields, which shows that both the amplitude and structure components are basically driven by the deep convection parametrization. Between the two main deep convection schemes used in PEARP, we qualify that the PCMT parametrization scheme performs better than the B85 scheme. A further analysis of spatial features of the rainfall objects to which the SAL metric pertains shows the predominance of large objects in the verification measure. It is for the most extreme events that the model has the best representation of the distribution of object integrated rain.

A Hybrid Stochastically Perturbed Parametrization Scheme in a Convection-Permitting Ensemble

Model error in ensemble prediction systems is often represented by either a tendency perturbation approach or a process-based parameter perturbation scheme. In this paper a novel hybrid stochastically perturbed parameterization (HSPP) scheme is proposed and implemented in the Convection Permitting Limited Area Ensemble Forecasting (C-LAEF) system developed at the Zentralanstalt für Meteorologie und Geodynamik (ZAMG). In HSPP, the individual parameterization tendencies of the physical processes radiation, shallow convection, and microphysics are perturbed stochastically by a spatially and temporally varying pattern. Uncertainties in the turbulence scheme are considered by perturbing key parameters on the process level. The proposed scheme HSPP features several advantages compared to the popular stochastically perturbed parameterization tendencies (SPPT) scheme: it considers a more physically consistent relationship between different parameterization schemes, deals with uncertainties especially adapted to the individual physical processes, respects conservation laws of energy and moisture, and eliminates the tapering function that has to be introduced to the SPPT scheme because of mainly numerical reasons. The hybrid scheme HSPP is evaluated over one summer and one winter month and compared to a reference ensemble without any stochastic physics perturbations and to two versions of the SPPT scheme. The results show that HSPP significantly increases the ensemble spread of temperature, humidity, wind speed, and pressure, especially in the lower levels of the atmosphere where a tapering function is active in the original SPPT approach. Precipitation verification yields a generally improved probabilistic performance of the HSPP scheme in summer when convection is dominating, which has also been demonstrated in a case study.

An Optimal Parametrization Scheme for Path Generation Using Fourier Descriptors for Four-Bar Mechanism Synthesis

Fourier descriptor (FD)-based path synthesis algorithms for generation of planar four-bar mechanisms require assigning time parameter values to the given points along the path. An improper selection of time parameters leads to poor fitting of the given path and suboptimal four-bar mechanisms while also ignoring a host of mechanisms that could be potentially generated otherwise. A common approach taken is to use uniform time parameter values, which does not take into account the unique harmonic properties of the coupler path. In this paper, we are presenting a nonuniform parametrization scheme in conjunction with an objective function that provides a better fit, leverages the harmonics of the four-bar coupler, and allows imposing additional user-specified constraints.

Physics-Based Design by Optimization of Unconventional Supercavitating Hydrofoils

A computational framework to design a new family of unconventional super cavitating (SC) hydrofoils with optimized hydrodynamic performance is developed. A low-order boundary element method is used to solve for the steady potential flow over the hydrofoil predicting its hydrodynamic characteristics, including the vapor-cavity interface. Shape variations are obtained by an ad hoc parametrization scheme by composite B-spline curves whose control points represent the design variables to the hydrodynamic optimization problem. The accuracy of the Computational Fluid Dynamics (CFD) tools is also preventively validated on the experimental characteristics of a conventional SC hydrofoil. A computational test case is performed to maximize the efficiency of a SC hydrofoil accounting for both shape and angle of attack variations. The new hydrofoil leads to 40% improvement on the lift over drag ratio compared to the initial reference shape. This result is confirmed by high-fidelity unsteady multiphase viscous solver.