High‐resolution regional climate model projections of future tropical cyclone activity in the Philippines

Abstract

The Philippines is one of the most exposed countries in the world to tropical cyclones. In order to provide information to help the country build resilience and plan for a future under a warmer climate, we build on previous research to investigate implications of future climate change on tropical cyclone activity in the Philippines. Experiments were conducted using three regional climate models with horizontal resolutions of approximately 12 km (HadGEM3‐RA) and 25 km (HadRM3P and RegCM4). The simulations are driven by boundary data from a subset of global climate model simulations from the CMIP5 ensemble. Here we present the experimental design, the methodology for selecting CMIP5 models, the results of the model validation, and future projections of changes to tropical cyclone frequency and intensity by the mid‐21st century. The models used are shown to represent the key climatological features of tropical cyclones across the domain, including the seasonality and general distribution of intensities, but issues remain in resolving very intense tropical cyclones and simulating realistic trajectories across their life‐cycles. Acknowledging model inadequacies and uncertainties associated with future climate model projections, the results show a range of plausible changes with a tendency for fewer but slightly more intense tropical cyclones. These results are consistent with the basin‐wide results reported in the IPCC AR5 and provide clear evidence that the findings from these previous studies are applicable in the Philippines region.

Projected changes in rainfall and temperature over the Philippines from multiple dynamical downscaling models

“…These simulations were designed to cover the region of the western North Pacific where tropical cyclones affecting the Philippines are mostly generated and propagate ( Figure 1). To provide driving fields for the HadGEM3-RA experiments, three of the CMIP5-participating GCMs were selected based on their performance in representing some of the most important factors affecting the climate of the Philippines as well as those known to influence tropical cyclones-that is, the monsoons, tracks of tropical cyclone-like vortices, the Pacific Ocean warm pool, spatial representation of sea surface temperatures (SSTs) and sea level pressure (Daron et al, 2016;Gallo et al, 2018). The RCM experiments conducted in PAGASA, on the other hand, used driving fields from a single GCM, HadGEM2-ES, used in one of the HadGEM3-RA experiments and available for use with PRECIS and RegCM4, to incorporate the uncertainties underlying the assumptions of different RCMs (e.g., Im et al, 2017).…”

“…The Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) has worked collaboratively with international partners, including the UK Met Office and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in projects that have run a variety of high-resolution climate simulations covering the country using different GCMs and downscaling models (see Daron et al, 2018). To provide timely information to those planning for climate change in the Philippines, a subset of these dynamically downscaled simulations have been used to provide projections on changes in future tropical cyclone activity (see Gallo et al, 2018). Complementary to these recent studies, this present study focuses on assessing the available simulations against the observed climate of the country and developing outputs to provide future projections for temperature and rainfall over the Philippines.…”

Climate process chains: Examples from southern Africa

“…This could involve identifying models that demonstrate realistic simulation of the processes/system states in the chain, which would increase confidence in their projected changes of a particular outcome of importance. Alternatively, it could be used to exclude models from an ensemble that fail to adequately capture the observed CPC dynamics and so removing implausible projections from the ensemble (e.g., McSweeney et al, ; Gallo et al, ). While model exclusion on this basis will necessitate subjective decisions around thresholds of “adequate,” all model exclusion or weighting approaches involve subjective decisions whether around the criteria for weighting and/or the thresholds for exclusion.…”

Climatological characterization of tropical cyclones detected in the regional climate simulations over the CORDEX‐SEA domain

“…Good representation of historical TC climatology in Southeast Asia (SEA) can provide higher confidence in the projected TC climatology, and therefore can deliver useful information in mitigating damages from TC‐related disasters. Several studies have looked at the possible changes in the TC climatology in the near‐, mid‐, and late‐future projections (Yoshimura and Sugi, 2005; Oouchi et al ., 2006; Bengtsson et al ., 2007; Knutson et al ., 2007; Stowasser et al ., 2007; Camargo et al ., 2016; Gallo et al ., 2018; Herrmann et al ., 2020). However, there is still no consensus in the changes in the pattern of the future projection in WNP or SEA since different studies exhibit different signals in the future projection for this region.…”