Meteorological Service Singapore

<strong class="journal-contentHeaderColor">Abstract.</strong> This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data unlocking key research avenues in atmospheric science and provides justification for the resources needed to produce this data. Topics within the CMIP7 Atmosphere Theme centre around processes and feedbacks in atmospheric science such as clouds, aerosols and atmospheric chemistry, atmospheric circulation, temperature variability and extremes, radiative forcings, and Earth system model evaluation. These topics are summarised in this paper as scientific &lsquo;opportunities&rsquo; which will be realised through CMIP7 experiments and Earth system model outputs. These opportunities were submitted by a thematic group of atmospheric science community representatives combined with an extended consultation process. The production of these variables will close key gaps and uncertainties identified during previous rounds of CMIP, and will be broadly used by scientific, policy, governmental, industry, and other communities that rely on climate model projections for research and decision making, including supporting the 7th Intergovernmental Panel on Climate Change Assessment Report (AR7). As an author group, we also reflect on the process used to collate this data request and make recommendations to future CMIP governance on implementing a consultation on this scale in the future.

Abstract This study investigates the impact of the interaction between large‐scale and local‐scale forcings in regulating rainfall patterns and their propagation over coastal areas of Northeast (NE) Australia using a convective‐scale regional model run for 180 days. Over the coastal areas, spatially heterogeneous rainfall patterns are evident in both radar observations and model simulations. By classifying the characteristics of three distinct rainfall groups, we found that the rainfall propagation modulates the average rainfall patterns. Modelling results suggest that the large‐scale background wind and local‐scale land–sea breeze circulations are two important factors driving rainfall propagation. Offshore rainfall propagation, which is frequently observed in coastal regions in the tropics, occurs during the days with weak easterlies near the surface and strong upper‐and mid‐level westerlies. Rainfall is triggered during the afternoon by convergence driven by the sea breeze and then propagates offshore during the nighttime with the land breeze density current and large‐scale background westerlies. In contrast, onshore rainfall propagation is observed during days with strong background easterlies from the surface to upper levels. For the No‐Propagation group, rainfall occurs during the afternoon due to the convergence of sea breezes and low‐level background westerlies, and it persists over land during the nighttime with low‐ and mid‐level easterlies. Our results also suggest that the background wind regimes associated with different phases of intraseasonal variability modulate the direction and strength of rainfall propagation, leading to different coastal rainfall patterns.

Abstract We present a consistent coupling between two‐moment microphysics and bulk ice optics in the Met Office's 1.5‐km resolution regional weather model and study its impact on top‐of‐atmosphere (TOA) short‐ and long‐wave irradiances. The coupling links the prognostic moments (total mass and number) to bulk ice optical properties through the mass‐equivalent spherical radius using Padé approximants. Model runs were evaluated for Darwin, Australia (January–March 2017) and the UK (December 2017–March 2018). Using this consistent coupled parametrisation, we demonstrate improved simulation of TOA short‐wave irradiances over both regions compared to the non‐consistent ice optical parametrisation when validated against satellite observations. Similar improvements were found for TOA long‐wave irradiances over Darwin, though the consistent parametrisation was slightly too transmissive over the UK. Overall, our more consistent two‐moment coupling between microphysics and ice optics leads to generally better prediction of radiation fields than single‐moment parametrisations.

The large islands of the Maritime Continent experience a strong diurnal cycle, with enhanced convection and precipitation over land through the afternoon and evening. Convective storms that initiate over land may then propagate out over surrounding coastal waters overnight; the land breeze is typically assumed to drive the overnight convergence of moisture offshore, however some of the offshore moisture convergence may also be attributed to other density current drivers, such as cold pools.A regional configuration of the MetUM over southwest Sumatra has been used to isolate the influence of cold pool dynamics on the development of the diurnal cycle for three case study days by switching off precipitation re-evaporation (thereby preventing cold pool formation), and these results are compared with control runs with precipitation re-evaporation enabled.This presentation will offer insight into the contribution of cold pools to offshore propagation of convective storms under different large-scale conditions, and into the influence of model resolution on how well this contribution is resolved.

Global climate models and reanalysis products have revealed large, persistent downwelling shortwave radiation biases over the Southern Ocean and coastal Antarctica. The biases are hypothesized to be caused by the incapability of models to accurately s

Abstract Two aspects of ensemble localization for data assimilation are explored using the simplified nonhydrostatic ABC model in a tropical setting. The first aspect (i) is the ability to prescribe different localization length scales for different variables (variable-dependent localization). The second aspect (ii) is the ability to control (i.e., to knock out by localization) multivariate error covariances (selective multivariate localization). These aspects are explored in order to shed light on the cross-covariances that are important in the tropics and to help determine the most appropriate localization configuration for a tropical ensemble–variational (EnVar) data assimilation system. Two localization schemes are implemented within the EnVar framework to achieve (i) and (ii). One is called the isolated variable-dependent localization (IVDL) scheme and the other is called the symmetric variable-dependent localization (SVDL) scheme. Multicycle observation system simulation experiments are conducted using IVDL or SVDL mainly with a 100-member ensemble, although other ensemble sizes are studied (between 10 and 1000 members). The results reveal that selective multivariate localization can reduce the cycle-averaged root-mean-square error (RMSE) in the experiments when cross-covariances associated with hydrostatic balance are retained and when zonal wind/mass error cross-covariances are knocked out. When variable-dependent horizontal and vertical localization are incrementally introduced, the cycle-averaged RMSE is further reduced. Overall, the best performing experiment using both variable-dependent and selective multivariate localization leads to a 3%–4% reduction in cycle-averaged RMSE compared to the traditional EnVar experiment. These results may inform the possible improvements to existing tropical numerical weather prediction systems that use EnVar data assimilation.