scholarly journals On the utility of individual tendency output: Revealing interactions between parameterised processes during a marine cold air outbreak

2021 ◽  
Author(s):  
Marvin Kähnert ◽  
Harald Sodemann ◽  
Wim C. de Rooy ◽  
Teresa M. Valkonen
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Specific Humidity ◽  
Shallow Convection ◽  
Cold Air ◽  
Cold Air Outbreak ◽  
Order Of Magnitude ◽  
Underlying Causes ◽  
The Individual

AbstractForecasts of marine cold air outbreaks critically rely on the interplay of multiple parameterisation schemes to represent sub-grid scale processes, including shallow convection, turbulence, and microphysics. Even though such an interplay has been recognised to contribute to forecast uncertainty, a quantification of this interplay is still missing. Here, we investigate the tendencies of temperature and specific humidity contributed by individual parameterisation schemes in the operational weather prediction model AROME-Arctic. From a case study of an extensive marine cold air outbreak over the Nordic Seas, we find that the type of planetary boundary layer assigned by the model algorithm modulates the contribution of individual schemes and affects the interactions between different schemes. In addition, we demonstrate the sensitivity of these interactions to an increase or decrease in the strength of the parameterised shallow convection. The individual tendencies from several parameterisations can thereby compensate each other, sometimes resulting in a small residual. In some instances this residual remains nearly unchanged between the sensitivity experiments, even though some individual tendencies differ by up to an order of magnitude. Using the individual tendency output, we can characterise the subgrid-scale as well as grid-scale responses of the model and trace them back to their underlying causes. We thereby highlight the utility of individual tendency output for understanding process-related differences between model runs with varying physical configurations and for the continued development of numerical weather prediction models.

The impact of Secondary Ice Processes on a stratocumulus-to-cumulus transition during a Cold-Air Outbreak

2021 ◽  
Author(s):  
Michail Karalis ◽  
Georgia Sotiropoulou ◽  
Steven J. Abel ◽  
Elissavet Bossioli ◽  
Paraskevi Georgakaki ◽  
...  
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Cumulus Clouds ◽  
Cold Air ◽  
Atmospheric Sciences ◽  
Boundary Layer Clouds ◽  
Cold Air Outbreak ◽  
Stratocumulus Clouds ◽  
Break Up ◽  
The Impact

<p>The representation of boundary layer clouds during marine Cold-Air Outbreaks (CAO) remains a great challenge for weather prediction models. Recent studies have shown that the representation of the transition from stratocumulus clouds to convective cumulus open cells largely depends on microphysical and precipitation processes, while Abel et al. (2017) further suggested that Secondary Ice Processes (SIP) may play a crucial role in the evolution of the cloud fields. In this study we use the Weather Research Forecasting model to investigate the impact of the most well-known SIP mechanisms (rime-splintering or Hallet-Mossop, mechanical break-up upon collisions between ice particles and drop-shattering) on a CAO case observed north of UK in 2013. While Hallet-Mossop is the only SIP process extensively implemented in atmospheric models, our results indicate that collisional break-up is also important in these conditions.</p><p> </p><p>Abel, S. J., Boutle, I. A., Waite, K., Fox, S., Brown, P. R. A., Cotton, R., Lloyd, G., Choularton, T. W., & Bower, K. N. (2017). The Role of Precipitation in Controlling the Transition from Stratocumulus to Cumulus Clouds in a Northern Hemisphere Cold-Air Outbreak, Journal of the Atmospheric Sciences, 74(7), 2293-2314. Retrieved Jan 9, 2021, from https://journals.ametsoc.org/view/journals/atsc/74/7/jas-d-16-0362.1.xml</p>

‘A Case Study on a Polar Cold Air Outbreak over Fram Strait using a Mesoscale Weather Prediction Model’

2005 ◽  
Vol 117 (2) ◽  
pp. 301-336 ◽  
Author(s):  
Ulrike Wacker ◽  
K. V. Jayaraman Potty ◽  
Christof Lüpkes ◽  
Jörg Hartmann ◽  
Matthias Raschendorfer
Keyword(s):  
Prediction Model ◽  
Weather Prediction ◽  
Fram Strait ◽  
Cold Air ◽  
Cold Air Outbreak

scholarly journals Seamless Stratocumulus Simulation across the Turbulent Gray Zone

2014 ◽  
Vol 142 (4) ◽  
pp. 1655-1668 ◽  
Author(s):  
I. A. Boutle ◽  
J. E. J. Eyre ◽  
A. P. Lock
Keyword(s):  
Boundary Layer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Aircraft Observations ◽  
Microphysical Parameterization ◽  
Grid Length ◽  
Numerical Weather Prediction Models

Abstract A pragmatic approach for representing partially resolved turbulence in numerical weather prediction models is introduced and tested. The method blends a conventional boundary layer parameterization, suitable for large grid lengths, with a subgrid turbulence scheme suitable for large-eddy simulation. The key parameter for blending the schemes is the ratio of grid length to boundary layer depth. The new parameterization is combined with a scale-aware microphysical parameterization and tested on a case study forecast of stratocumulus evolution. Simulations at a range of model grid lengths between 1 km and 100 m are compared to aircraft observations. The improved microphysical representation removes the correlation between precipitation rate and model grid length, while the new turbulence parameterization improves the transition from unresolved to resolved turbulence as grid length is reduced.

Diagnosing factors in parameterised and resolved convection with physical tendency output in AROME-Arctic during a Cold-Air Outbreak event

2020 ◽  
Author(s):  
Marvin Kähnert ◽  
Teresa M. Valkonen ◽  
Harald Sodemann
Keyword(s):  
Weather Prediction ◽  
Cloud Microphysics ◽  
High Impact ◽  
Surface Fluxes ◽  
The Arctic ◽  
Shallow Convection ◽  
Time Step ◽  
Cold Air ◽  
Weather Events ◽  
High Impact Weather

<p>Numerical weather prediction (NWP) models generally display comparatively low predictive skill in the Arctic. Particularly, the large impact of sub-grid scale, parameterised processes, such as surface fluxes, radiation or cloud microphysics during high-latitude weather events pose a substantial challenge for numerical modelling. Such processes are most influential during mesoscale weather events, such as polar lows, often embedded in cold air outbreaks (CAO), some of which cause high impact weather. Uncertainty in Arctic weather forecasts is thus critically dependent on parameterised processes. The strong influence from several parameterised processes also makes model forecasts particularly susceptible to compensation of errors from different parameterisations, which potentially limits model improvement.<br>Here we analyse model output of individual parameterised tendencies of wind, temperature and humidity during Arctic high-impact weather in AROME-Arctic, the operational NWP model used by the Norwegian Meteorological Institute Norway for the European Arctic. Individual tendencies describe the contribution of each applied physical parameterisation to a respective variable per model time step. We study a CAO-event taking place during 24 - 27 December 2015. This intense and widespread CAO event, reaching from the Fram Straight to Norway and affecting a particularly large portion of the Nordic seas at a time, was characterised by strong heat fluxes along the sea ice edge. <br>Model intern definitions for boundary layer type become apparent as a decisive factor in tendency contributions. Especially the interplay between the dual mass flux and the turbulence scheme is of essence here. Furthermore, sensitivity experiments, featuring a run without shallow convection and a run with a new statistical cloud scheme, show how a physically similar result is obtained by substantially different tendencies in the model.</p>

scholarly journals Atmospheric boundary layer dynamics from balloon soundings worldwide: CLASS4GL v1.0

2019 ◽  
Author(s):  
Hendrik Wouters ◽  
Irina Y. Petrova ◽  
Chiel C. van Heerwaarden ◽  
Jordi Vilà-Guerau de Arellano ◽  
Adriaan J. Teuling ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Prediction Models ◽  
Climate Adaptation ◽  
Weather Prediction ◽  
Potential Temperature ◽  
Specific Humidity ◽  
Climate Projections ◽  
Weather Extremes ◽  
Coupled Models

Abstract. The coupling between soil, vegetation and atmosphere is thought to be crucial in the development and intensification of weather extremes, especially meteorological droughts, heatwaves and severe storms. Therefore, understanding evolution of the atmospheric boundary layer (ABL) and the role of land–atmosphere feedbacks is necessary for earlier warnings, better climate projection and timely societal adaptation. However, this understanding is hampered by the difficulties to attribute cause–effect relationships from complex coupled models, and the irregular space–time distribution of in situ observations of the land–atmosphere system. As such, there is a need for simple deterministic appraisals that systematically discriminate land–atmosphere interactions from observed weather phenomena over large domains and climatological time spans. Here, we present a new interactive data platform to study the behaviour of the ABL and land–atmosphere interactions based on worldwide weather balloon soundings and an ABL model. This software tool – referred to as CLASS4GL (http://class4gl.eu) – is developed with the objectives to (a) mine appropriate global observational data from over 2 million weather balloon soundings since 1981 and combine them with satellite and reanalysis data, and (b) constrain and initialize a numerical model of the daytime evolution of the ABL that serves as a tool to interpret these observations mechanistically and deterministically. As a result, it fully automises extensive global model experiments to assess the effects of land and atmospheric conditions on the ABL evolution as observed in different climate regions around the world. The suitability of the set of observations, model formulations and global parameters employed by CLASS4GL is extensively validated. In most cases, the framework is able to realistically reproduce the observed daytime response of the ABL height, potential temperature and specific humidity from the balloon soundings. In this extensive global validation exercise, a bias of 0.2 m h−1, −0.052 K h−1 and 0.07 g kg−1 h−1 is found for the morning-to-afternoon evolution of the ABL height, potential temperature and specific humidity. The virtual tool is in continuous development, and aims to foster a better process-understanding of the drivers of the ABL evolution and their global distribution, particularly during the onset and amplification of weather extremes. Finally, it can also be used to scrutinize the representation of land–atmosphere feedbacks and ABL dynamics in Earth system models, numerical weather prediction models, atmospheric reanalysis, and satellite retrievals, with the ultimate goal to improve local climate projections, provide earlier warning of extreme weather, and foster a more effective development of climate adaptation strategies. The tool can be easily downloaded via http://class4gl.eu and is open source.

scholarly journals A PDF-Based Microphysics Parameterization for Shallow Cumulus Clouds

2014 ◽  
Vol 71 (3) ◽  
pp. 1070-1089 ◽  
Author(s):  
Yefim L. Kogan ◽  
David B. Mechem
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Distribution Functions ◽  
Cumulus Clouds ◽  
Microphysical Process ◽  
Eddy Simulation ◽  
Droplet Concentration ◽  
Accretion Rates ◽  
Order Of Magnitude ◽  
Les Model

Abstract Unbiased calculations of microphysical process rates such as autoconversion and accretion in mesoscale numerical weather prediction models require that subgrid-scale (SGS) variability over the model grid volume be taken into account. This variability can be expressed as probability distribution functions (PDFs) of microphysical variables. Using dynamically balanced large-eddy simulation (LES) model results from a case of marine trade cumulus, the authors develop PDFs of the cloud water, droplet concentration, and rainwater variables (qc, Nc, and qr). Both 1D and 2D joint PDFs (JPDFs) are presented. The authors demonstrate that accounting for the JPDFs results in more accurate process rates for a regional-model grid size. Bias in autoconversion and accretion rates are presented, assuming different formulations of the JPDFs. Approximating the 2D PDF using a product of individual 1D PDFs overestimates the autoconversion rates by an order of magnitude, whereas neglecting the SGS variability altogether results in a drastic underestimate of the grid-mean autoconversion rate. PDF assumptions have a much smaller impact on accretion, largely because of the near-linear dependence of the variables in the accretion rate formula and the relatively weak correlation between qc and qr over the small LES grid volumes. The latter is attributed to the spatial decorrelation in the vertical between the two fields. Although the full PDFs are both height and time dependent, results suggest that fixed-in-time and fixed-in-height PDFs give an acceptable level of accuracy, especially for the crucial autoconversion calculation.

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