Extreme rainfall sensitivity in convective‐scale ensemble modelling over Singapore

Abstract

A convective‐scale ensemble system was developed to predict the occurrence of heavy convective rainfall around Singapore with a focus on the prediction of high‐impact events. The new ensemble SINGV‐EPS has been nested within two global ensembles, MOGREPS‐G (UK Met Office) and EC‐ENS (ECMWF). Predicting the occurrence of convective rainfall in an area such as Singapore is challenging and this article discusses the use of the convection‐permitting ensemble to characterize the uncertainties in the prediction of such localized heavy rainfall. First, verification of wind, temperature, and precipitation is performed for a month‐long period to assess the relative performance of each ensemble. This reveals differences, but no robust signal to say one is better than the other. The results are not statistically significant and not all variables are consistently better with one ensemble or the other. Secondly, the precipitation characteristics of SINGV‐EPS are analysed from probabilities of precipitation and variability among the ensemble members. SINGV‐EPS is sensitive to the choice of the global ensemble providing the initial conditions and boundaries. The results suggest there is benefit, in some cases, from combining the two ensembles. Thirdly, the spread of the ensemble precipitation is analysed using the dispersion Fractions Skill Score (dFSS). We compare the impact of the initial perturbations and the perturbations in lateral boundary conditions in both nesting options. The initial perturbations dominate in the beginning of the forecasts, with influence up to T+24 h, and are associated with an upscale growth of the uncertainties. The impact of the parent ensemble and lateral boundary conditions dominate at the end of the forecast and tend to influence larger scales more.

SINGV: A convective‐scale weather forecast model for Singapore

“…However, as described in Porson et al . (2019), the same model configuration is used when running CP ensemble forecasts for Singapore. These forecasts are run at 4.5 km resolution.…”

“…Subsequently these changes were found to improve forecasts in other parts of the Tropics as well, and so SINGV formed the starting point of the tropical science configuration in the UM science partnership (Bush et al ., 2020). The SINGV downscaler is the basis for the SINGV data assimilation system (SINGV‐DA: Heng et al ., 2020) and the SINGV ensemble prediction system (SINGV‐EPS: Porson et al ., 2019). Furthermore, SINGV is also used for sub‐kilometre urban‐scale modelling (Simón‐Moral et al ., 2020), regional climate modelling (Timbal et al ., 2019) and coupled atmosphere–ocean modelling (Thompson et al ., 2019), at CCRS.…”

Years of the Maritime Continent

“…Meanwhile, observed cases during YMC have been targeted for numerical modeling. In a study focusing on heavy rainfall events observed in October 2017, Porson et al (2019) examined predictions of convective rainfall over Singapore using convection-permitting regional model ensembles nested within two global ensembles. They found no clear difference of using one global ensemble versus the other, but their combination yields better results.…”

SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore

“…The ensemble prediction system (EPS) of SINGV (SINGV-EPS) is developed from the Met Office Global and Regional Ensemble Prediction System over UK (MOGREPS-UK, Hagelin et al 2017;Porson et al 2019). The system can be considered as an ensemble of SINGV-DS forecasts.…”