Dataset of a kilometer-scale meso-NH simulation for C2OMODO: The RCElarge300 collection of MesoNHforC2OMODO.

Authors

Jean-Pierre Chaboureau

Published in

Data in brief. Volume 67. Pages 112954. Epub Jun 10, 2026.

Abstract

Measuring vertical velocity is essential for understanding deep convection. The Convective Core Observations through MicrOwave Derivatives in the trOpics (C2OMODO) mission will retrieve vertical velocity using ice-sensitive microwave measurements at two closely spaced time intervals. To prepare for this mission, it is critical to investigate how vertical velocity relates to satellite observations. However, vertical velocity within convective cores is rarely measured, and no comprehensive dataset currently exists. To address this gap, we created the MesoNHforC2OMODO RCElarge300 collection - a dataset of kilometer-scale Meso-NH simulations developed for C2OMODO. The dataset comprises 920 million atmospheric columns from a 25-day Radiative Convective Equilibrium (RCE) simulation, based on the large configuration of the Cloud Resolving Models (CRMs) with a fixed, uniform sea surface temperature of 300 K, following the RCE Model Intercomparison Project (RCEMIP). The dataset provides 3D atmospheric fields, 2D surface and atmospheric variables, 3D radar reflectivities, and satellite imagery in the infrared and microwave bands, computed from the simulation outputs using the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV) code. All 2D and 3D fields are available for 3600 time steps. For each 30-minute interval, fields are stored at times t, t + 60 s and t + 120 s. The RCElarge300 dataset is designed to help explore the relationships between microwave observations, cloud microphysics, and vertical velocity. By linking satellite signals to cloud dynamics, it offers new insights into the physical and dynamical processes driving deep convection.

PMID:
42339369
Bibliographic data and abstract were imported from PubMed on 24 Jun 2026.

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