Sensitivity of tropical cyclones to convective parameterization schemes in RegCM4Villafuerte II, M. Q., Lambrento, J. C. R., Hodges, K. I. ORCID: https://orcid.org/0000-0003-0894-229X, Cruz, F. T., Cinco, T. A. and Narisma, G. T. (2021) Sensitivity of tropical cyclones to convective parameterization schemes in RegCM4. Climate Dynamics, 56. pp. 1625-1642. ISSN 0930-7575
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1007/s00382-020-05553-3 Abstract/SummaryThis study investigates the sensitivity of simulated tropical cyclones (TC) affecting the Philippines to convective parameterization schemes (CPS) in the Regional Climate Model Version 4 (RegCM4). Five ERA-Interim driven RegCM4 simulations at 25-km horizontal resolution were conducted utilizing the CPS of Grell with Arakawa–Schubert closure (GR), Emanuel (EM), Kain–Fritsch (KF), Tiedtke (TE), and a combined Grell scheme over land and Emanuel over the ocean (GR-EM). Comparisons made between the observed and RegCM4-simulated TCs covering a 30-year period (1981–2010) indicate that the EM scheme yields an annual-mean TC frequency that is closest to observations. The GR-EM scheme, on the other hand, closely reproduces the observed seasonal patterns of TC tracks, spatial patterns of TC track density and TC-associated rainfall, and TC lifespan. The KF scheme is the only CPS that was able to simulate intense TCs (maximum wind speed > 40 m s–1) within the domain. In contrast, both GR and TE schemes largely underestimated the TC frequency, and were only able to simulate weak TCs. Such underestimation in the TC frequency and intensity in the GR and TE simulations can be attributed to the dry mid-tropospheric environment and the absence of a large area with positive low-level relative vorticity over the Pacific Ocean inhibiting TC formation and further development over the area. These findings would be helpful in selecting the more appropriate CPS for TC-related model simulations over the Philippines and in further model improvements, given the climate modeling imperfections and associated biases.
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