Representing Equilibrium and Nonequilibrium Convection in Large-Scale Models

By P. Bechtold, N. Semane, P. Lopez, Jean-Pierre Chaboureau, Anton Beljaars, Niels Bormann. 2014

404 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/d8ff526b1efd3a6e6c7f52e6f9fbfcb94f6ccd8f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

In Global and Planetary Change

Citations in the corpus

Toward Convective-Scale Prediction within the Next Generation Global Prediction System (2019, background): “This subsection verifies the diurnal cycle of precipitation over the CONUS following Bechtold et al. (2014) and Zhou et al. (2015).”
Introducing independent patterns into the Stochastically Perturbed Parametrization Tendencies (SPPT) scheme (2017, methodology): “Most notably for our discussion, CY37R3 closes the deep convection scheme using a CAPE formulation (Bechtold et al., 2008), whereas more recent model cycles use the ‘PCAPE’ formulation outlined in Bechtold et al. (2014).”
Tropospheric chemistry in the integrated forecasting system of ECMWF (2014, positive): “Next, the tracers are vertically distributed by the diffusion scheme (Beljaars and Viterbo, 1998) and by convective mass fluxes (Bechtold et al., 2014).”
The Formation of Wider and Deeper Clouds as a Result of Cold-Pool Dynamics (2014, methodology): “(LES) model [see Stevens et al. (2005)].”
SEAS5: the new ECMWF seasonal forecast system (2018, methodology): “The convective parameterisation evolves with each cycle, and in SEAS5 it has a modified Convective Available Potential Energy (CAPE) closure leading to an improved diurnal cycle of convection (Bechtold et al., 2014) and a revised formulation of detrainment and convective momentum transport improving”
Can deep learning beat numerical weather prediction? (2021, background): “[36,37]), the turbulent transports in the planetary boundary layer (e.”
The ERA5 global reanalysis (2020, methodology): “Improvements in the diurnal cycle of convection, shifting the rainfall peak over land from noon to late afternoon, have been achieved by use of a modified convective available potential energy (CAPE) closure (Bechtold et al., 2014).”
A review on regional convection‐permitting climate modeling: Demonstrations, prospects, and challenges (2015, background): “…is important to mention that recently developed parameterization schemes lead to improvements of several of these common errors including the simulation of precipitation intensities [Donner et al., 2011], intraseasonal variability [Benedict et al., 2013], and diurnal cycles [Bechtold et al., 2014].”
Moist Orographic Convection: Physical Mechanisms and Links to Surface-Exchange Processes (2018, background): “The sensitivity of parameterized convection to the formulation of the convective trigger [135] and closure [136] are well established.”
Evaluation of the convection‐resolving climate modeling approach on continental scales (2017, background): “Although substantial advances have been achieved in recent years [e.g., Bechtold et al., 2014], parameterization schemes introduce uncertainties such as evident from a misrepresentation of the diurnal cycle of precipitation [Dai et al., 1999; Hohenegger et al., 2008] or an overestimation of the…”
Climate model configurations of the ECMWF Integrated Forecasting System (ECMWF-IFS cycle 43r1) for HighResMIP (2018, background): “…and include representations of radiative transfer (Morcrette et al., 2008; Iacono et al., 2008; Mlawer et al., 1997), convection (Tiedtke, 1989; Bechtold et al., 2014, 2008), clouds (Tompkins et al., 2007; Tiedtke, 1993; Forbes et al., 2011; Forbes and Tompkins, 2011), turbulent diffusion…”