Stefano Alessandrini

Analog-Based Ensemble Model Output Statistics

AbstractAn analog-based ensemble model output statistics (EMOS) is proposed to improve EMOS for the calibration of ensemble forecasts. Given a set of analog predictors and corresponding weights, which are optimized with a brute-force continuous ranked probability score (CRPS) minimization, forecasts similar to a current ensemble forecast (i.e., analogs) are searched. The best analogs and the corresponding observations form the training dataset for estimating the EMOS coefficients. To test the new approach for renewable energy applications, wind speed measurements at 100-m height from six measurement towers and wind ensemble forecasts at 100-m height from the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) are used. The analog-based EMOS is compared against EMOS, an adaptive and recursive wind vector calibration (AUV), and an analog ensemble applied to ECMWF EPS. It is shown that the analog-based EMOS outperforms EMOS, AUV, and the analog ensemble at all measurem...

A simplified version of the correct boundary conditions for skewed turbulence in Lagrangian particle models

Abstract Recently, Thomson and Montgomery (1994, Atmospheric Environment 28 , 1981–1987) stated the correct method of treating the reflection of particle velocity at the boundaries in Lagrangian particle diffusion models for non-Gaussian turbulence. Unfortunately, this method does not have an analytical solution. Two different approximated analytical solutions are proposed and compared. It is concluded that both of them satisfy the well-mixed condition and do not appreciably depart from the correct solution. The one consuming less time is proposed.

The Role of Unresolved Clouds on Short-Range Global Horizontal Irradiance Predictability

AbstractThe shortwave radiative impacts of unresolved cumulus clouds are investigated using 6-h ensemble simulations performed with the WRF-Solar Model and high-quality observations over the contiguous United States for a 1-yr period. The ensembles use the stochastic kinetic energy backscatter scheme (SKEBS) to account for implicit model uncertainty. Results indicate that parameterizing the radiative effects of both deep and shallow cumulus clouds is necessary to largely reduce (55%) a systematic overprediction of the global horizontal irradiance. Accounting for the model’s effective resolution is necessary to mitigate the underdispersive nature of the ensemble and provide meaningful quantification of the short-range prediction uncertainties.

Application of a Bivariate Gamma Distribution for a Chemically Reacting Plume in the Atmosphere

The joint concentration probability density function of two reactive chemical species is modelled using a bivariate Gamma distribution coupled with a three-dimensional fluctuating plume model able to simulate the diffusion and mixing of turbulent plumes. A wind-tunnel experiment (Brown and Bilger, J Fluid Mech 312:373–407, 1996), carried out in homogeneous unbounded turbulence, in which nitrogen oxide is released from a point source in an ozone doped background and the chemical reactions take place in non-equilibrium conditions, is considered as a test case. The model is based on a stochastic Langevin equation reproducing the barycentre position distribution through a proper low-pass filter for the turbulence length scales. While the meandering large-scale motion of the plume is directly simulated, the internal mixing relative to the centroid is reproduced using a bivariate Gamma density function. The effect of turbulence on the chemical reaction (segregation), which in this case has not yet attained equilibrium, is directly evaluated through the covariance of the tracer concentration fields. The computed mean concentrations and the O3–NO concentration covariance are also compared with those obtained by the Alessandrini and Ferrero Lagrangian single particle model (Alessandrini and Ferrero, Physica A 388:1375–1387, 2009) that entails an ad hoc parametrization for the segregation coefficient.

A Lagrangian particle model with chemical reactions: application in real atmosphere

In this work, a Lagrangian particle model able to account for simple chemical reactions between NO and O3 has been improved to consider the photolysis of NO2. A system of chemical equations is numerically solved on a Eulerian grid, while the particle trajectories are moved in a Lagrangian frame. The NOx emissions of a power plant in real atmosphere, situated in a complex topography environment, have been considered as a test case. The simulated episodes refer to the diurnal time, when the ultraviolet radiation activates the NO2. Comparisons between NO/NO2’s concentrations ratio are presented in terms of scatter plots and statistical indexes analysis.

Statistical Downscaling of a High-Resolution Precipitation Reanalysis Using the Analog Ensemble Method

AbstractThis study explores the first application of an analog-based method to downscale precipitation estimates from a regional reanalysis. The utilized analog ensemble (AnEn) approach defines a metric with which a set of analogs, i.e., the ensemble, can be sampled from the observations in the training period. Based on the determined AnEn estimates, also the uncertainty of the generated precipitation time series can easily be assessed. The study investigates tuning parameters of the AnEn such as the choice of predictors or the ensemble size, in order to optimize the performance. The approach is implemented and tuned based on a set of over 700 rain gauges with 6-hourly measurements for Germany and a 6.2km regional reanalysis for Europe which provides the predictors. The obtained AnEn estimates are evaluated against the observations over a 4-year verification period. With respect to deterministic quality, the results show that AnEn is able to outperform the reanalysis itself depending on location and preci...

Model chain for buoyant plume dispersion

A new original software interface between the WRF mesoscale meteorological model and the SPRAYWEB dispersion model has been developed. The model chain was designed such a highly responsive tool for risk assessment and emergency-response purposes. The model interface reads the wind and temperature fields provided by WRF and interpolates them on a fixed-in-time grid, which is the input to the dispersion model. Furthermore, it calculates the turbulence-parameter vertical profiles, based on the surface-layer data provided by WRF. In this work we simulate the dispersion of a high-buoyancy plume. The model chain performances were tested against the Bull-Run dataset.

Probabilistic Wind and Solar Power Predictions

The added value of probabilistic wind and solar power predictions with respect to deterministic forecasting is demonstrated. A review of the current state-of-the-science approaches to generate probabilistic predictions and uncertainty quantification is provided, follow by an example of a comparison of probabilistic vs. deterministic estimates based on real data.

Analytical offline approach for concentration fluctuations and higher order concentration moments

We developed a fluctuating plume model able to evaluate all the higher order moments of concentration only requiring the knowledge of the first one. The simple algorithm used to calculate the meander centroid component is independent of the method used to obtain the mean concentration field and makes the computational time lower than most meandering plume model versions. Thus, it is especially suitable for practical applications.

Annual simulation of secondary pollution over northern Italy

A secondary pollution modelling system for simulating airborne dispersion and chemical reactions is applied over a regional scale domain located in the North-West of Italy, where urban and industrial areas are present. It was found an overestimation of NO2 in the urban areas, probably due to an underestimation of the vertical diffusivity; the analysis of OX confirms that the discrepancies in O3 and NO2 are mainly due to local scale effects; the model shows a general underestimation of the observed PM10 concentrations due to the uncertainties in the emission inventories, spatial resolution, and the adopted aerosol modelling approach.