Defining Philippine Climate Zones Using Surface and High-Resolution Satellite Data

Philippine climate zones traditionally were classified from a rain-gauge network, using the Modified Coronas Classification (MCC). MCC uses average monthly rainfall totals to define four climate zones: Types I-IV. Types I and III have wet and dry seasons, whereas Types II and IV have wet seasons but no dry seasons. The present study redefines Philippine climate zones by applying cluster analysis to the average monthly rainfall amounts from surface-based rain-gauge observations, and dense, high-resolution satellite data from the Tropical Rainfall Monitoring Mission (TRMM). To determine the optimal number of climate type clusters, both single-linkage hierarchical and K-means cluster analysis algorithms were used, together with known characteristics of Philippine rainfall distributions and attributes. Employing single linkage hierarchical and K-means methods in tandem identified six different Philippine climate types, which is two climate types more than the currently accepted MCC climate classification. Due to the far greater number of TRMM observations compared with the rain gauge network, the study provides more clearly defined cluster characteristics including the spatial and temporal variability of climate divisions. This study uses known meteorological factors contributing to the identification of six distinct climate types. This paper is intended to assist agricultural stakeholders with planning and decision-making

Cluster analysis of North Atlantic tropical cyclones

© 2014 Published by Elsevier B.V. Tropical cyclones (TCs) in the North Atlantic (NA) basin pose an annual risk to coastal regions, with hurricane Katrina (2005) the costliest TC in US history. This study employs K-means cluster analysis (CA) to detect the distinctive, important NA TC paths and lifecycles. Unlike previous TC cluster analyses, which examined TC tracks, the present work documents TC genesis and decay locations. Application of the silhouette coefficient provided an objective method to determine the optimal number of clusters (7 for genesis locations, 6 for preferred tracks, and 5 for decay locations). Additionally, silhouette coefficients provided the information necessary to remove storms that did not fit specific clusters, improving cluster cohesiveness. For TC genesis, K-means CA captured the separation between tropical and higher-latitude TCs. Clustering of genesis points identifies formative areas. The western NA cluster is the most active. TCs have distinct decay locations, notably in the western NA, Gulf of Mexico and western Caribbean Sea. Clustering TC tracks reveals that TCs moving to higher latitudes recurve generally, whereas Caribbean and Gulf coast TCs have straight-line tracks. Temporally, early season TC clusters form in the western Caribbean Sea, Gulf of Mexico, and western NA. Midseason TC clusters shift eastward, extending from the tropical NA to Africa. Late season TC clusters recur in the Caribbean Sea, Gulf of Mexico and western NA

Climatology of Philippine tropical cyclone activity: 1945–2011

© 2016 Royal Meteorological Society The Philippine region occupies the southwestern western North Pacific (WNP) Ocean, between 5°–25°N and 115°–135°E. About 70% of WNP tropical cyclones (TCs) formed in or entered the Philippine region during 1945–2011. Here, a climatology of Philippine TC metrics is developed, including mean annual frequencies, landfalls, TC days, season lengths, season earliest and latest start and end dates, genesis locations, and tracks. Two distinct TC seasons, the less active season (LAS; 1 January–31 May) and more active season (MAS; 1 June–31 December), are evident. Philippine TC annual median LAS frequency is 2 [interquartile range (IQR) is 2], and median landfalling frequency is 1. The annual median MAS frequency is 15 (IQR is 4.5), and median landfalling frequency is 6. About 55% of Philippine TCs reach typhoon intensity. A quiescent (TC-free) period occurs between LAS and MAS, ranging from 2 days to 5 months (median 1.2 months) for LAS to MAS transitions, and 6 days to 7 months (median 2.85 months) for MAS to LAS transitions. The interannual variability of the annual average lifetime maximum intensity (LMI) for all TCs and landfalling TCs decreased slightly during the satellite era (the years since 1980). The TC annual average latitude of LMI in the satellite era exhibits a poleward migration; however, for landfalling TCs it is equatorward. Wavelet analysis shows El Niño Southern Oscillation as the dominant mode affecting Philippine TCs, consistent with other studies. The wavelet analysis also indicates possible decadal and multi-decadal modes. In El Niño years, TCs frequently recurve or decay before reaching the Philippine region, producing below normal numbers and landfalls in LAS and MAS. In La Niña years, TC numbers and landfalls are below normal in January–March and July–September, but above normal in April–June and October–December. The climatology developed here has social and economic relevance: allowing planning, providing early risk assessment, and mitigating impacts through timely preparation and management

Impacts of ENSO on Philippine tropical cyclone activity

© 2016 American Meteorological Society. This study investigates the El Niño-Southern Oscillation (ENSO) contribution to Philippine tropical cyclone (TC) variability, for a range of quarterly TC metrics. Philippine TC activity is found to depend on both ENSO quarter and phase. TC counts during El Niño phases differ significantly from neutral phases in all quarters, whereas neutral and La Niña phases differ only in January-March and July-September. Differences in landfalls between neutral and El Niño phases are significant in January-March and October-December and in January-March for neutral and La Niña phases. El Niño and La Niña landfalls are significantly different in April-June and October-December. Philippine neutral and El Niño TC genesis cover broader longitude-latitude ranges with similar long tracks, originating farther east in the western North Pacific. In El Niño phases, the mean eastward displacement of genesis locations and more recurving TCs reduce Philippine TC frequencies. Proximity of La Niña TC genesis to the Philippines and straight-moving tracks in April-June and October-December increase TC frequencies and landfalls. Neutral and El Niño accumulated cyclone energy (ACE) values are above average, except in April-June of El Niño phases. Above-average quarterly ACE in neutral years is due to increased TC frequencies, days, and intensities, whereas above-average El Niño ACE in July-September is due to increased TC days and intensities. Below-average La Niña ACE results from fewer TCs and shorter life cycles. Longer TC durations produce slightly above-average TC days in July-September El Niño phases. Fewer TCs than neutral years, as well as shorter TC durations, imply less TC days in La Niña phases. However, above-average TC days occur in October-December as a result of higher TC frequencies