Convection-permitting climate simulations for South America with the Met Office Unified Model

Abstract

We present the first convection-permitting regional climate model (CPRCM) simulations at 4.5 km horizontal resolution for South America at near-continental scale, including full details of the experimental setup and results from the reanalysis-driven hindcast and climate model-driven present-day simulations. We use a range of satellite and ground-based observations to evaluate the CPRCM simulations covering the period 1998–2007 comparing the CPRCM output with lower resolution regional and global climate model configurations for key regions of Brazil. We find that using the convection-permitting model at high resolution leads to large improvements in the representation of precipitation, specifically in simulating its diurnal cycle, frequency, and sub-daily intensity distribution (i.e. the proportion of heavy and light precipitation). We tentatively conclude that there are also improvements in the spatial structure of precipitation. We see higher precipitation intensity and extremes over Amazonia in the CPRCMs compared with observations, though more sub-daily observational data from meteorological stations are required to conclusively determine whether the CPRCMs add value in this regard. For annual mean precipitation and mean, maximum and minimum near surface temperatures, it is not clear that the CPRCMs add value compared with coarser-resolution models with parameterised convection. We also find large changes in the contribution to evapotranspiration from canopy evaporation compared to soil evaporation and transpiration compared with the RCM. This is likely to be related to the shift in precipitation intensity distribution of the CPRCMs compared to the RCM and its impact on the hydrological requires further investigation.

The added value of using convective-permitting regional climate model simulations to represent cloud band events over South America

“…As observed by Halladay et al (2023), the UKMO CPRCM-PD (and the GCM) simulation is wetter than the CPRCM-ERA (and RCM). This difference is also evident when comparing the precipitation rate anomalies during simulated cloud band events.…”

“…This suggests that CPRCMs are more efficient in consuming energy and producing precipitation than their parent parametrised models. Thus, biases in the precipitation intensity are likely associated with explicitly resolving the convection and the interplay with the model's configurations and other parametrisations, such as cloud microphysics schemes, as suggested by Halladay et al (2023).…”

“…In these studies, the use of a regional climate model did not improve the simulation of an extremely wet season, but the convective-permitting simulations better captured the spatial distribution of the accumulated precipitation (Bettolli et al, 2021). Halladay et al (2023) documents the recently completed Met Office 10-year simulation of a continentalscale CPRCM over SAm, with improvements in the representation of the precipitation frequency, intensity, and diurnal cycle despite overestimating the frequency of intense precipitation. This simulation builds on a similar continental scale simulation over Africa, CP4-Africa (Stratton et al, 2018), which saw similar improvements in rainfall characteristics (Berthou et al, 2019).…”

“…Convective-Permitting Regional Climate Models (CPRCMs) are regional climate models running at kilometrescale horizontal grid-spacing (∼ 4 km or less). The higher resolution of those models enables explicitly resolving deep convective processes, even though small-scale processes are still under-resolved (Prein et al, 2015;Lucas-Picher et al, 2021;Halladay et al, 2023), and can improve the representation of processes related to topographic features and land-cover contrasts (Rowell and Berthou, 2023). Previous studies demonstrated that CPRCM simulations improve the representation of the precipitation diurnal cycle and extremes (e.g.…”

Future precipitation projections for Brazil and tropical South America from a Convection-permitting climate simulation

“…Similar larger future increases in short-duration precipitation extremes in CPRCMs were found in the UK, US and Europe (see Kendon et al, (2021) for more details). Despite the CPRCM benefits, which are mainly at sub-daily scales and are often referred to as the added value (Lucas-Picher et al, 2021), these models still have known biases when evaluated against observed distributions of rainfall: mainly that the heavy rainfall at grid-scale can be too intense Halladay et al, 2023;Kendon et al, 2021). Rowell and Berthou (2023) found that most regions (apart from for large mountains, and to lesser extent coastlines and urban areas) show a closer match between model and observations when spatial aggregation of the 4.5km CPRCM data to 25 km is performed before the rainfall analysis.…”