Impacts of Lapse Rate Adjustments on Convective Parameters in the PLUVIA Mesoanalysis System

The PLUVIA Mesoanalysis is a high-resolution, hourly updating analysis of near-surface variables over the UK. The Mesoanalysis combines observations from Automatic Weather Stations (including citizen Automatic Weather Stations via the Weather Observations Website) with lagged ensemble Unified Model data (T+4 to T+9 hours) using Ensemble Optimal Interpolation. Analysed variables include mean sea-level pressure, temperature, dewpoint temperature, wind speed and direction, visibility, Convective Available Potential Energy (CAPE), Convective Inhibition (CIN) and vorticity. The high spatial density of ingested observations (~3,000 sites over the UK) allows the Mesoanalysis to resolve localised features such as convergence lines, regions of enhanced CAPE or reduced CIN, and cold pools, which may have a bearing on the initiation and/or evolution of convection. This allows Operational Meteorologists to make inferences about the likely evolution of convection on Nowcasting timescales. The Mesoanalysis also provides analysis minus model background fields, to highlight where conditions are deviating from model expectations. The Mesoanalysis has been successfully trialled as a prototype and is currently being prepared for operational release onto the Met Office’s new supercomputer. A key part of this work has been correcting errors that arise from the use of a smoothed orography field in the Unified Model (UM). Due to the smoothing, the model elevation is sometimes substantially different from the true elevation which can lead to error in the analysed temperature and/or dewpoint temperature fields. To address this problem, we have implemented variable lapse rate corrections to the temperature and dewpoint temperature fields. This requires approximating the local lapse rates using a nearest grid point neighbour gradient fitting approach. The lapse rates obtained are then multiplied by the height difference between the smoothed UM model and higher resolution (2km gridded) orography to give a temperature and dewpoint temperature correction at each grid point. In this presentation, we will give details of the correction methodology and explore how the correction influences other analysed variables, including the visibility, CAPE, and CIN. We will explore a range of case studies including cases of UK convection that resulted in substantial flooding impacts.