Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models: COST Action ES0905 Final Report

Yano, Jun–Ichi; Geleyn, Jean-François; Köhler, Martin; Mironov, Dmitrii; Quaas, Johannes; Soares, Pedro M. M.; Phillips, Vaughan T. J.; Plant, Robert S.; Deluca, Anna; Marquet, Pascal; Stulic, Lukrecia; Fuchs, Željka

doi:10.3390/atmos6010088

Cited by 18 publications

(11 citation statements)

References 183 publications

(271 reference statements)

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“…The trend toward global cloud‐resolving models ( O (1 km)) presents several major challenges for the traditional mass‐flux‐based approaches (Satoh et al, 2019) where the standard assumption of quasi steady‐state equilibrium and typical statistical distributions of cloud size break down (Yano et al, 2015). Furthermore, with increasing resolution, clouds and subsiding shells cover a greater fraction of a model grid, and the classical assumption of a robust‐scale separation between the clouds and their environment is violated.…”

Section: Introductionmentioning

confidence: 99%

“…Each cloud element in the ensemble can be dealt with individually (as Arakawa & Schubert, 1974, do for deep convection) or, more commonly, the ensemble of clouds is averaged into a single updraft (bulk‐plume method) with an entrainment rate that is either prescribed as a constant or based on some parametric relationship with the cloud/environmental properties (de Rooy et al, 2013). The foundational assumption of the bulk‐plume method is that a clear distinction can be made between the buoyant plume and the environment, but this is challenged by the existence of substantial downward vertical velocities near the cloud edges (subsiding shells) (Jonker et al, 2008; Yano et al, 2015). Subsiding shells have been observed with aircraft (Jonas, 1990; Katzwinkel et al, 2014; Rodts et al, 2003), with the shell regions near cloud edge exhibiting dips in virtual potential temperature, increased turbulence, and significant downward mass transport.…”

Section: Introductionmentioning

confidence: 99%

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Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

McMichael

Yang

Marke

et al. 2020

Geophysical Research Letters

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The existence of subsiding shells on the periphery of shallow cumulus clouds has major implications concerning the parameterization of shallow convection, with the mass exchange between the shell and cloudy air representing a significant deviation from the commonly used bulk-plume parameterization. We examine the structure and frequency of subsiding shells in shallow cumulus convection using Doppler lidars at the Atmospheric Radiation Measurement Southern Great Plains facility in the central United States and at the Jülich ObservatorY for Cloud Evolution in western Germany. Doppler lidar indicates that the vertical subsiding shell extent is asymmetric, while shell width is typicallỹ 100 m. Large-eddy simulation can reasonably simulate the observed shell structure using a grid spacing of 10 m and suggests that much of the observed asymmetry is not a result of transient cloud evolution. Plain Language Summary Doppler lidars allow for the inference of vertical air motion. On the edges of the shallow "popcorn" cumulus clouds, regions of sinking air (subsiding shells) are observed. If we wish to understand how these clouds interact with their environment, we must understand the structure of the subsiding shells that envelop them. As a cloud passes over the lidar, the front edge of the cloud is sampled first, and the back edge is sampled later. The back-edge subsiding shell descends farther below cloud base than the front-edge shell. High-resolution models can resolve the observed shell structure and suggest that the differences between the front-and back-edge shells do not arise from the evolution of the cloud during the tens of seconds it takes to pass over the lidar.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

McMichael

Yang

Marke

et al. 2020

Geophysical Research Letters

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“…Many models use rather ad hoc criteria for the deep convection triggering (Randall et al, ; Suhas & Zhang, ). Conventional parameterizations unrealistically represent the coupling between cumulus processes and the low‐level environment (Randall et al, ; Yano et al, ). They also fail to represent the upscale effects associated with the evolution from the cumulonimbus into mesoscale systems and subsequent interaction with large‐scale dynamics (Moncrieff et al, ).…”

Section: Introductionmentioning

confidence: 99%

Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States?

Lin

Fan

Feng

et al. 2019

J Adv Model Earth Syst

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Mesoscale convective systems (MCSs) are a major source of precipitation in many regions of the world. Traditional global climate models (GCMs) do not have adequate parameterizations to represent MCSs. In contrast, the Multiscalex Modeling Framework (MMF), which explicitly resolves convection within the cloud-resolving model embedded in each GCM column, has been shown to be a promising tool for simulating MCSs, particularly over the Tropics. In this work, we use ground-based radar-observed precipitation, North American Regional Reanalysis data, and a high-resolution Weather Research and Forecasting simulation to evaluate in detail the MCS-associated precipitation over the central United States predicted by a prototype MMF simulation that has a 2°host-GCM grid. We show that the prototype MMF with nudged winds fails to capture the convective initiation in three out of four major MCS events during May 201x1 and underpredicts the precipitation rates for the remaining event, because the model cannot resolve the mesoscale drylines/fronts that are important drivers for initiating convection over the Southern Great Plains region. By reducing the host-GCM grid spacing to 0.25°in the MMF and nudging the winds, the simulation is able to better capture the mesoscale dynamics, which drastically improves the model performance. We also show that the MMF model performs better than the traditional GCM in capturing the precipitation intensity. Our results suggest that increasing resolution plays a dominant role in improving the simulation of precipitation in the MMF, and the cloud-resolving model embedded in each GCM column further helps to boost precipitation rate.Plain Language Summary Massive thunderstorms contribute a large proportion of warm season rainfall over the central United States. Previous studies have shown that the Multiscale Modeling Framework (MMF), which embeds a cloud-resolving model (CRM) into each global climate model grid column to simulate convection, provides a promising tool for simulating massive thunderstorms in the Tropics. However, it is unclear whether the MMF can simulate similar thunderstorms in midlatitudes such as in the central United States. Therefore, this study compares the MMF simulations with detailed available observations over the central United States. We find that the commonly used MMF with 2°-host-GCM (~200 km) grid spacing has difficulty in reproducing the observed rainfall because the host-GCM grid spacing is too coarse to capture the mesoscale circulations (at scales of approximately tens of kilometers) that are important for triggering the convection. When the host-GCM-grid spacing is reduced to a quarter degree (~25 km), the model succeeds to trigger the convection, so the rainfall simulation is improved. This study shows the importance of better representation of mesoscale circulations in models for predicting massive thunderstorms.

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“…Conventional parameterization unrealistically assumes scale separation between cumulus processes and the environment (Plant & Yano, ; Yano et al, ). The misrepresented parameterization has major impacts on the mesoscale convective systems (MCSs), which organize in and above the unresolved scale O(10–100 km) of large‐scale models.…”

Section: Introductionmentioning

confidence: 99%

Long‐Lived Mesoscale Convective Systems of Superparameterized CAM and the Response of CAM

Chen

Kirtman

2018

J Adv Model Earth Syst

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Mesoscale organized convection is generally misrepresented in the large‐scale convective parameterizations used in contemporary climate models. This impacts extreme weather events (e.g., Madden‐Jullian Oscillation) and the general circulation driven by the significant amount of latent heat released from mesoscale organized convection. Studies show that the missing processes could be partially recovered by embedding a 2‐D cloud‐resolving model in each general circulation model columns, that is, superparameterization. To enable analysis of mesoscale convective systems (MCSs) in the multiscale modeling framework, we apply a detection and hierarchical clustering algorithm on the 3‐hourly 2‐D cloud‐resolving model embedded in the superparameterized Community Atmosphere Model (SPCAM) 5.2. We then examine the fields of a long‐lived and large MCS cluster at the central Pacific. The MCS cluster shows a squall line‐like circulation throughout the life cycle in SPCAM. We simultaneously obtain the 3‐hourly CAM parameterized convection outputs based on the time step‐wise perfect initial conditions given by SPCAM. This allows pure model physics comparison without introducing initial condition errors. The results show that CAM has a systematically biased stratiform cooling and moistening response below 3 km to the given SPCAM deep convection favoring conditions. We show that this bias is mainly due to the CAM's stratiform microphysics scheme. The mesoscale organization in SPCAM thus provides a baseline for improvements of convective parameterization of CAM.

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Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models: COST Action ES0905 Final Report

Cited by 18 publications

References 183 publications

Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States?

Long‐Lived Mesoscale Convective Systems of Superparameterized CAM and the Response of CAM

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