scholarly journals The ability of the ICE-T microphysics scheme in HARMONIE-AROME to predict aircraft icing

2021 ◽  
Author(s):  
Tim Carlsen ◽  
Morten Køltzow ◽  
Trude Storelvmo
Keyword(s):  
Water Content ◽  
Numerical Weather Prediction ◽  
Liquid Water ◽  
Prediction Models ◽  
Weather Prediction ◽  
Supercooled Liquid ◽  
Liquid Water Content ◽  
Aircraft Icing ◽  
Microphysics Scheme ◽  
Numerical Weather

Abstract In-cloud icing is a major hazard for aviation traffic and forecasting of these events is an important task for weather agencies worldwide. A common tool utilised by aviation forecasters is an icing intensity index based on supercooled liquid water from numerical weather prediction models. We seek to validate the modified microphysics scheme, ICE-T, in the HARMONIE-AROME numerical weather prediction model with respect to aircraft icing. Icing intensities and supercooled liquid water derived from two 3-month winter season simulations with the original microphysics code, CTRL, and ICE-T are compared with pilot reports of icing and satellite retrieved values of liquid and ice water content from CloudSat-CALIPSO and liquid water path from AMSR-2. The results show increased supercooled liquid water and higher icing indices in ICE-T. Several different thresholds and sizes of neighbourhood areas for icing forecasts were tested out, and ICE-T captures more of the reported icing events for all thresholds and nearly all neighbourhood areas. With a higher frequency of forecasted icing, a higher false-alarm ratio cannot be ruled out, but is not possible to quantify due to the lack of no-icing observations. The increased liquid water content in ICE-T shows a better match with the retrieved satellite observations, yet the values are still greatly underestimated at lower levels. Future studies should investigate this issue further, as liquid water content also has implications for downstream processes such as the cloud radiative effect, latent heat release, and precipitation.

scholarly journals A New Visibility Parameterization for Warm-Fog Applications in Numerical Weather Prediction Models

2006 ◽  
Vol 45 (11) ◽  
pp. 1469-1480 ◽  
Author(s):  
I. Gultepe ◽  
M. D. Müller ◽  
Z. Boybeyi
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Liquid Water Content ◽  
Parameterization Scheme ◽  
Numerical Weather ◽  
Time Period ◽  
Simulation Domain ◽  
Forecast Models

Abstract The objective of this work is to suggest a new warm-fog visibility parameterization scheme for numerical weather prediction (NWP) models. In situ observations collected during the Radiation and Aerosol Cloud Experiment, representing boundary layer low-level clouds, were used to develop a parameterization scheme between visibility and a combined parameter as a function of both droplet number concentration Nd and liquid water content (LWC). The current NWP models usually use relationships between extinction coefficient and LWC. A newly developed parameterization scheme for visibility, Vis = f (LWC, Nd), is applied to the NOAA Nonhydrostatic Mesoscale Model. In this model, the microphysics of fog was adapted from the 1D Parameterized Fog (PAFOG) model and then was used in the lower 1.5 km of the atmosphere. Simulations for testing the new parameterization scheme are performed in a 50-km innermost-nested simulation domain using a horizontal grid spacing of 1 km centered on Zurich Unique Airport in Switzerland. The simulations over a 10-h time period showed that visibility differences between old and new parameterization schemes can be more than 50%. It is concluded that accurate visibility estimates require skillful LWC as well as Nd estimates from forecasts. Therefore, the current models can significantly over-/underestimate Vis (with more than 50% uncertainty) depending on environmental conditions. Inclusion of Nd as a prognostic (or parameterized) variable in parameterizations would significantly improve the operational forecast models.

scholarly journals RTTOV-gb v1.0 – updates on sensors, absorption models, uncertainty, and availability

2019 ◽  
Vol 12 (5) ◽  
pp. 1833-1845 ◽  
Author(s):  
Domenico Cimini ◽  
James Hocking ◽  
Francesco De Angelis ◽  
Angela Cersosimo ◽  
Francesco Di Paola ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Microwave Radiometer ◽  
Liquid Water Content ◽  
Absorption Model ◽  
Numerical Weather ◽  
Brightness Temperatures ◽  
Atmospheric Profile ◽  
Temperature Water

Abstract. This paper describes the first official release (v1.0) of RTTOV-gb. RTTOV-gb is a FORTRAN 90 code developed by adapting the atmospheric radiative transfer code RTTOV, focused on satellite-observing geometry, to the ground-based observing geometry. RTTOV-gb is designed to simulate ground-based upward-looking microwave radiometer (MWR) observations of atmospheric downwelling natural radiation in the frequency range from 22 to 150 GHz. Given an atmospheric profile of temperature, water vapor, and, optionally, cloud liquid water content, and together with a viewing geometry, RTTOV-gb computes downwelling radiances and brightness temperatures leaving the bottom of the atmosphere in each of the channels of the sensor being simulated. In addition, it provides the sensitivity of observations to the atmospheric thermodynamical state, i.e., the Jacobians. Therefore, RTTOV-gb represents the forward model needed to assimilate ground-based MWR data into numerical weather prediction models, which is currently pursued internationally by several weather services. RTTOV-gb is fully described in a previous paper (De Angelis et al., 2016), while several updates are described here. In particular, two new MWR types and a new parameterization for the atmospheric absorption model have been introduced since the first paper. In addition, estimates of the uncertainty associated with the absorption model and with the fast parameterization are given here. Brightness temperatures (TB) computed with RTTOV-gb v1.0 from radiosonde profiles have been compared with ground-based MWR observations in six channels (23.8, 31.4, 72.5, 82.5, 90.0, and 150.0 GHz). The comparison shows statistics within the expected accuracy. RTTOV-gb is now available to licensed users free of charge from the Numerical Weather Prediction Satellite Application Facility (NWP SAF) website, after registration. Coefficients for four MWR instrument types and two absorption model parameterizations are also freely available from the RTTOV-gb support website.

scholarly journals RTTOV-gb v1.0 – Updates on sensors, absorption models, uncertainty, and availability

2019 ◽  
Author(s):  
Domenico Cimini ◽  
James Hocking ◽  
Francesco De Angelis ◽  
Angela Cersosimo ◽  
Francesco Di Paola ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Microwave Radiometer ◽  
Liquid Water Content ◽  
Absorption Model ◽  
Numerical Weather ◽  
Brightness Temperatures ◽  
Atmospheric Profile ◽  
Temperature Water

Abstract. This paper describes the first official release (v1.0) of RTTOV-gb. RTTOV-gb is a FORTRAN 90 code developed by adapting the atmospheric radiative transfer code RTTOV, focused on satellite observing geometry, to the ground-based observing geometry. RTTOV-gb is designed to simulate ground-based upward-looking microwave radiometer (MWR) observations of atmospheric downwelling natural radiation in the frequency range from 22 to 150 GHz. Given an atmospheric profile of temperature, water vapour and, optionally, cloud liquid water content, and together with a viewing geometry, RTTOV-gb computes the bottom of atmosphere radiances and brightness temperatures in each of the channels of the sensor being simulated. In addition, it provides the sensitivity of observations to the atmospheric thermodynamical state, i.e. the Jacobians. Therefeore, RTTOV-gb represents the forward model needed to assimilate ground-based MWR data into numerical weather prediction models, which is currently pursued internationally by several weather services. RTTOV-gb is fully described in a previous paper (De Angelis et al., 2016), while several updates are described here. In particular, two new MWR types and a new parameterization for atmospheric absorption model have been introduced since the first paper. In addition, estimates of the uncertainty associated with the absorption model and with the fast parameterization are given here. Brightness temperatures (TB) computed with RTTOV-gb v1.0 from radiosonde profiles have been compared with ground-based MWR observations at six channels (23.8, 31.4, 72.5, 83.5, 90.0, and 150.0 GHz). The comparison shows statistics within the expected accuracy. RTTOV-gb is now available to licensed users free of charge from the Numerical Weather Prediction Satellite Application Facility (NWP SAF) website, after registration. Coefficients for four MWR instrument types and two absorption model flavors are also freely available from the RTTOV-gb support website.

scholarly journals Parametrizations of Liquid and Ice Clouds’ Optical Properties in Operational Numerical Weather Prediction Models

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 89
Author(s):  
Harel. B. Muskatel ◽  
Ulrich Blahak ◽  
Pavel Khain ◽  
Yoav Levi ◽  
Qiang Fu
Keyword(s):  
Optical Properties ◽  
Numerical Weather Prediction ◽  
Radiation Transfer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Effective Size ◽  
Asymmetry Factor ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models ◽  
Spectral Averaging

Parametrization of radiation transfer through clouds is an important factor in the ability of Numerical Weather Prediction models to correctly describe the weather evolution. Here we present a practical parameterization of both liquid droplets and ice optical properties in the longwave and shortwave radiation. An advanced spectral averaging method is used to calculate the extinction coefficient, single scattering albedo, forward scattered fraction and asymmetry factor (bext, v, f, g), taking into account the nonlinear effects of light attenuation in the spectral averaging. An ensemble of particle size distributions was used for the ice optical properties calculations, which enables the effective size range to be extended up to 570 μm and thus be applicable for larger hydrometeor categories such as snow, graupel, and rain. The new parameterization was applied both in the COSMO limited-area model and in ICON global model and was evaluated by using the COSMO model to simulate stratiform ice and water clouds. Numerical weather prediction models usually determine the asymmetry factor as a function of effective size. For the first time in an operational numerical weather prediction (NWP) model, the asymmetry factor is parametrized as a function of aspect ratio. The method is generalized and is available on-line to be readily applied to any optical properties dataset and spectral intervals of a wide range of radiation transfer models and applications.

Impact of Consistent Semi-Lagrangian Trajectory Calculations on Numerical Weather Prediction Performance

2017 ◽  
Vol 145 (10) ◽  
pp. 4127-4150 ◽  
Author(s):  
Syed Zahid Husain ◽  
Claude Girard
Keyword(s):  
Numerical Weather Prediction ◽  
Numerical Experiments ◽  
Prediction Models ◽  
Weather Prediction ◽  
Forecast Accuracy ◽  
Multiscale Model ◽  
Dynamical Equations ◽  
Numerical Weather ◽  
Trajectory Calculation ◽  
Trajectory Calculations

Inconsistencies may arise in numerical weather prediction models—that are based on semi-Lagrangian advection—when the governing dynamical and the kinematic trajectory equations are discretized in a dissimilar manner. This study presents consistent trajectory calculation approaches, both in the presence and absence of off-centering in the discretized dynamical equations. Both uniform and differential off-centering in the discretized dynamical equations have been considered. The proposed consistent trajectory calculations are evaluated using numerical experiments involving a nonhydrostatic two-dimensional theoretical mountain case and hydrostatic global forecasts. The experiments are carried out using the Global Environmental Multiscale model. Both the choice of the averaging method for approximating the velocity integral in the discretized trajectory equations and the interpolation scheme for calculating the departure positions are found to be important for consistent trajectory calculations. Results from the numerical experiments confirm that the proposed consistent trajectory calculation approaches not only improve numerical consistency, but also improve forecast accuracy.

scholarly journals EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models

2013 ◽  
Vol 6 (6) ◽  
pp. 1961-1975 ◽  
Author(s):  
K. Zink ◽  
A. Pauling ◽  
M. W. Rotach ◽  
H. Vogel ◽  
P. Kaufmann ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Birch Pollen ◽  
Small Scale ◽  
Pollen Emission ◽  
Numerical Weather ◽  
Pollen Concentrations ◽  
Scale Modelling ◽  
Reactive Trace Gases

Abstract. Simulating pollen concentrations with numerical weather prediction (NWP) systems requires a parameterization for pollen emission. We have developed a parameterization that is adaptable for different plant species. Both biological and physical processes of pollen emission are taken into account by parameterizing emission as a two-step process: (1) the release of the pollen from the flowers, and (2) their entrainment into the atmosphere. Key factors influencing emission are temperature, relative humidity, the turbulent kinetic energy and precipitation. We have simulated the birch pollen season of 2012 using the NWP system COSMO-ART (Consortium for Small-scale Modelling – Aerosols and Reactive Trace Gases), both with a parameterization already present in the model and with our new parameterization EMPOL. The statistical results show that the performance of the model can be enhanced by using EMPOL.

Forecasting wave height probabilities with numerical weather prediction models

2005 ◽  
Vol 32 (14-15) ◽  
pp. 1841-1863 ◽  
Author(s):  
Mark S. Roulston ◽  
Jerome Ellepola ◽  
Jost von Hardenberg ◽  
Leonard A. Smith
Keyword(s):  
Wave Height ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models

Differentiating Freezing Drizzle and Freezing Rain in HRRR Model Forecasts

2021 ◽  
Author(s):  
Sarah Tessendorf ◽  
Allyson Rugg ◽  
Alexei Korolev ◽  
Ivan Heckman ◽  
Courtney Weeks ◽  
...  
Keyword(s):  
Drop Size ◽  
Prediction Models ◽  
Water Drop ◽  
Weather Prediction ◽  
Supercooled Liquid ◽  
Drop Diameter ◽  
Aircraft Icing ◽  
Freezing Rain ◽  
Primary Focus

AbstractSupercooled large drop (SLD) icing poses a unique hazard for aircraft and has resulted in new regulations regarding aircraft certification to fly in regions of known or forecast SLD icing conditions. The new regulations define two SLD icing categories based upon the maximum supercooled liquid water drop diameter (Dmax): freezing drizzle (100–500 μm) and freezing rain (> 500 μm). Recent upgrades to U.S. operational numerical weather prediction models lay a foundation to provide more relevant aircraft icing guidance including the potential to predict explicit drop size. The primary focus of this paper is to evaluate a proposed method for estimating the maximum drop size from model forecast data to differentiate freezing drizzle from freezing rain conditions. Using in-situ cloud microphysical measurements collected in icing conditions during two field campaigns between January and March 2017, this study shows that the High-Resolution Rapid Refresh model is capable of distinguishing SLD icing categories of freezing drizzle and freezing rain using a Dmax extracted from the rain category of the microphysics output. It is shown that the extracted Dmax from the model correctly predicted the observed SLD icing category as much as 99% of the time when the HRRR accurately forecast SLD conditions; however, performance varied by the method to define Dmax and by the field campaign dataset used for verification.

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