Data extracted from numerical simulations of rotating Boussinesq convection in spherical geometry and published in Guervilly, Cardin & Schaeffer (2019, https://doi.org/10.1038/s41586-019-1301-5). The simulations were run with Ekman numbers varying between 1e-6 and 1e-11, Rayleigh numbers between 6e7 and 5.25e13 and Prandtl numbers between 0.1 and 0.01. The data include: power spectra of the kinetic energy as a function of the azimuthal wavenumber; Rossby numbers and convective length scale; radial velocity in the equatorial plane for 4 selected simulations at varying Ekman number (Ek=1e-8 to 1e-11).

This dataset contains the input data (initial conditions, boundary conditions, initial perturbations) for Met Office Unified Model simulations performed during the PRESTO (PREcipitation STructures over Orography) project. It also contains the 2D and 3D output files from these simulations. The PRESTO project was funded by the Natural Environment Research Council (NERC) with the grant references - NE/I024984/1 and NE/I026545/1 - led by Professor Suzanne Gray (University of Reading) and Professor David Schultz (University of Manchester). PRESTO provided a leap forward in the understanding and prediction of quasi-stationary orographic convection in the UK and beyond. This was achieved through an intensive climatological analysis over several regions of the globe where continuous radar data was available, which identified the environmental conditions that support the bands and their characteristic locations and morphologies. Complementary high-resolution numerical simulations pinpointed the underlying mechanisms behind the bands and their predictability in numerical weather prediction models. This work provides positive impacts for the forecasting community, general public, and other academics in the field. Forecasters benefit from the identification of simple diagnostics that can be used operationally to predict these events based on available model forecasts and/or upstream soundings. A series of activities were used to directly engage with forecasters to effectively disseminate our findings. The public benefit from this improved forecasting of potentially hazardous precipitation events. The academic community benefit from the advanced physical understanding (which was disseminated through conferences, workshops, and peer-reviewed publications) and the numerous international collaborations associated with this project.

This dataset contains the input data (initial conditions, boundary conditions, initial perturbations) for Met Office Unified Model simulations performed during the PRESTO (PREcipitation STructures over Orography) project. It also contains the 2D and 3D output files from these simulations. The PRESTO project was funded by the Natural Environment Research Council (NERC) with the grant references - NE/I024984/1 and NE/I026545/1 - led by Professor Suzanne Gray (University of Reading) and Professor David Schultz (University of Manchester). PRESTO provided a leap forward in the understanding and prediction of quasi-stationary orographic convection in the UK and beyond. This was achieved through an intensive climatological analysis over several regions of the globe where continuous radar data was available, which identified the environmental conditions that support the bands and their characteristic locations and morphologies. Complementary high-resolution numerical simulations pinpointed the underlying mechanisms behind the bands and their predictability in numerical weather prediction models. This work provides positive impacts for the forecasting community, general public, and other academics in the field. Forecasters benefit from the identification of simple diagnostics that can be used operationally to predict these events based on available model forecasts and/or upstream soundings. A series of activities were used to directly engage with forecasters to effectively disseminate our findings. The public benefit from this improved forecasting of potentially hazardous precipitation events. The academic community benefit from the advanced physical understanding (which was disseminated through conferences, workshops, and peer-reviewed publications) and the numerous international collaborations associated with this project.

Data extracted from simulations of Boussinesq convection in a rotating plane layer where the horizontal box sizes are unequal (Lx < Ly where the xy plane is horizontal). Data published in Guervilly & Hughes, 2017, Phys. Rev. Fluids 2, 113503 (DOI: 10.1103/PhysRevFluids.2.113503).

This dataset includes numerical simulation data of bottom heated convection in a rotating spherical shell. These numerical models are used to investigate the dynamics of convection in planetary cores. The simulations are performed over a range of thermal forcing and rotation rate [1-3] to study the various dynamical regimes of rotating convection. The dataset includes the simulation states to reproduce the simulations, time-series output of relevant variables from the simulations apart from post-processed diagnostic quantities. Due to large volume of the simulation state files only the initial, final and time averaged files are stored in the dataset in NETCDF format. The simulation diagnostics are provided in text, which includes time series, spatial and temporal averages of various diagnostic quantities (e.g. kinetic energy of convection) and forces to assess the underlying dynamics and heat transfer behaviour. The simulations have been performed using the Leeds Spherical Dynamo code [4], using ARC2, ARC3 and ARC4 HPC system in University of Leeds and the ARCHER and ARCHER2 HPC system. Refs: [1] https://doi.org/10.1017/jfm.2017.539 [2] https://doi.org/10.1017/jfm.2020.67 [3] https://doi.org/10.48550/arXiv.2410.03369 [4] https://github.com/Leeds-Spherical-Dynamo/leeds-spherical-dynamo