Evaluating the Increasing Trend of Strength and Severe Wind Hazard of Philippine Typhoons Using the Holland-B Parameter and Regional Cyclonic Wind Field Modeling

Abstract

For the Philippines, a country exposed to multiple natural hazards, such as severe winds, sustainable development includes resiliency. A severe wind hazard is raised by tropical cyclones in the Western Pacific, known as typhoons, which frequent the Philippines. Therefore, adequately evaluating wind hazards and their impact is crucial for sustainable building design. Acknowledging the effects of climate change on said hazards requires adaptation to their consequences, which necessitates a deeper understanding of the changing behavior of typhoons in recent years. For this study, detailed wind information from the Japanese Meteorological Agency from 1977 to 2021, the Holland-B parameter, and the radius of maximum wind speed for each typhoon, are determined for simulation of the regional cyclonic wind field. The analysis of the Holland-B parameters, which represent the steepness of the pressure gradient and tropical cyclone convection, suggests that the Holland-B parameters have been increasing since 2011. The evaluation of the maximum regional wind fields and the return period wind fields caused by typhoons also indicate an increasing trend in severe wind hazards. Seasonality for the location of severe wind hazards is also observed, with Visayas and Mindanao experiencing an increase (decrease) during the Northeast (Southwest) Monsoon season and Luzon experiencing an increase (decrease) during the Southwest (Northeast) Monsoon season.

1. Introduction

Severe wind is a hazard that poses a risk to the integrity and sustainability of buildings in the Philippines. The Philippines, through its weather agency, the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA), has been monitoring the severe wind hazard primarily brought by typhoons that enter what is called the Philippine Area of Responsibility (PAR). An average of 20 typhoons enter PAR, of which an average of 10 typhoons make landfall [1].

Using 10-min sustained wind speeds in identifying the strength of typhoons, PAGASA distinguishes typhoons into five recent categories in 2022: tropical depression (55–61 kph), tropical storm (62–88 kph), severe tropical storm (89–117 kph), typhoon (118–184 kph), and super typhoon (>185 kph). Each category corresponds to a Public Storm Warning Signal shown in

Table 1. Tropical Cyclone Warning Signals by PAGASA.

Category	1970–1990	1991–2015	2015–2021	2022–Present
Tropical depression	#1	#1	#1	#1
Tropical storm	#2	#2	#2	#2
Severe tropical storm				#3
Typhoon	#3	#3	#3/#4	#4
Super Typhoon		#4	#5	#5

. Initially, with three (3) warning systems in 1970, the PAGASA issued Public Storm Warning Signals which were then revised, with the inclusion of Public Storm Warning Signal No (>185 kph) in 1991 as a result of Typhoon Mike in 1990 [2] and the inclusion of Public Storm Warning Signal No.5 (>220 kph) in 2015 as a result of Typhoon Haiyan in 2013 [3]. With the 2022 reclassification of typhoons, the Public Storm Warning Signals have adjusted to the current category and been renamed Tropical Cyclone Warning Signals (TCWS) [4].

The reclassification and the updates on TCWS are done to meet the risk posed by typhoons as part of disaster risk reduction management (DRRM). The Kyoto Protocol [5] and the Paris agreement [6] have acknowledged the need to address climate change and have made necessary commitments to meet the targets to mitigate the risk.

DRRM experts are asked whether climate change will affect typhoons as policy-making requires adaptation, particularly in sustainable development and building design. The Intergovernmental Panel on Climate Change (IPCC) reported in 2001 that there are some increases in tropical cyclone maximum intensities [7]. However, in years prior, there were no discernible trends in the rise in typhoon numbers and intensities from the historical analysis [8]. In 2004, a study estimated an increase of 5% to 10% by 2050 [9]. Treading upon this topic, however, requires caution. In 2017, a projection showed an increasing intensity of tropical cyclones across different basins, except for the Western Pacific typhoons [10]. However, it was noted that wind speed measurements in the 1940s and the 1960s in the Western Pacific basin were overestimated [11]. A subsequent analysis by the IPCC in 2020 shows that despite the lack of increase in the number of typhoons, the typhoons increase in intensity, intense typhoons increase in numbers, and typhoon precipitation also increases [12].

The known sources of uncertainty for future typhoon projections include sea surface temperature uncertainty, the vertical temperature gradient of the upper ocean [13], typhoon cyclogenesis, and atmospheric circulation changes. The question of those uncertainties is further pressed with Typhoon Rai (PAGASA Name: Odette) in 2021, which became the second costliest typhoon in Philippine history. Typhoon Rai underwent a rapid intensification, identified as the 95th percentile increase of maximum winds within a 24-hr period. Regions of rapid intensification were determined to have been occurring east of the Philippines, frequently before landfall, which has been attributed to the changes in the sea surface temperatures, which the models could not predict at that time [14].

Typhoon Rai is one of the December typhoons whose numbers have increased in the past ten years. Mindanao Island, which it struck, experienced a 480% increase in typhoon passage. The increase in the number of these December typhoons and the probability of Southern Philippines experiencing typhoon passage are attributed to the favorable large-scale sea surface conditions due to the positive shift of the Pacific Decadal Oscillation (PDO) [15]. The westward track of typhoons to the Philippines is also attributed to the Western Pacific Subtropical High (WPSH). The positive PDO and the stronger and more southern WPSH [16] resulted in large-scale environments favorable to tropical cyclones. The PDO is a decadal event, while the WPSH has seasonal characteristics. The variability of the WPSH is closely related to the onset of both the Southwest Monsoon season–which happens in the months of June, July, August, and September–and the Northeast Monsoon season–which occurs in the months of October, November, and December. Evaluating the cyclogenesis of typhoons between 1985 and 2010 reveals that typhoons that are wetter form closer to the Philippines during the Southwest Monsoon season, while typhoons that are drier originate farther at sea during the Northeast Monsoon season [17]. Typhoons tend to move peripherally with respect to the southern and western sections of WPSH. The increase in intensity and a westward shift of the WPSH results in typhoons forming at lower latitudes and presuming a more westward track, while the otherwise results in a shift from a northwest to a northeast recurving pattern of typhoons [18,19].

With the change in characteristics and behavior of typhoons due to climate change identified, the evaluation of the trend of severe wind hazards that typhoons are causing in the Philippines remains. This study aims to identify the changes in the wind hazard of typhoons in the Philippines by evaluating the changes in the regional cyclonic wind fields [20] within the Philippine Area of Responsibility. Identifying these changes in the wind hazard could prompt policy-makers and engineers to reconfigure their building design and disaster risk reduction and management measures to ensure sustainability that adapts to climate change.

2. Materials and Methods

2.1. Tropical Cyclone Modeling

For this study, the detailed wind information data of typhoons by the Japanese Meteorological Agency (JMA) was used. The data, spanning from 1977 to 2021, include maximum sustained winds, minimum central pressures, radii of storm winds, radii of gale winds, and storm locations (Figure 1) of each recorded typhoon.

The horizontal pressure profiles of typhoons must be estimated first to model the subsequent wind field. The pressure profile of typhoons resembles a rectangular hyperbola represented by shape parameters A and B [21], with B being known as the Holland-B parameter [22,23]:

$$B=\frac{V_{max}{}^2}{\rho e\left(p_n-p_0\right)}$$

(1)

where $V_{max}$ is the maximum gradient wind in m/s, $\rho$ is the air density in kg/m³, p_n is the ambient pressure assumed to be 1013 hPa, and $p_0$ is the minimum central pressure of the typhoon in hPa.

Obtaining the pressure profile results in determining the pressure gradient, which is one of the three primary forces, neglecting surface friction, and apart from Coriolis force and Centrifugal force due to the curvature of the motion of the parcel of air intending to move parallel to the curving pressure isobars. This results in the horizontal wind profile equation:

$$V\left(r\right)=-\frac{fr}{2}+\sqrt{{\left(\frac{fr}{2}\right)}^2+V_{max}{}^2{\left(\frac{R_{max}}{r}\right)}^B{e}^{1-{\left(\frac{R_{max}}{r}\right)}^B}}$$

(2)

where V(r) is the gradient wind speed at distance r from the typhoon’s center, f is the Coriolis parameter which is a function of the latitude, and R_max is the radius of maximum winds, related to the shape function A [22].

$$A=R_{max}{}^{1/B}$$

(3)

This study assumes that the momentum transfer from the gradient height to the near-surface height is uniform in deriving the storm profiles. With the temporal variation caused by turbulence removed through temporal averaging and with the satellite analysis, considering constant exposure (at-sea conditions), R_max, A, and B can be computed by considering the maximum winds, the radius of storm winds, and the radius of gale winds identified by JMA in the detailed wind information. The change in the surface winds due to the difference in the surface conditions can be factored in later by updating the ratio of the gradient wind to the surface wind using Prandtl’s law of the wall [24], wind direction factors to accommodate upstream terrain effects in the locality and gust factors to determine the additional turbulent effects [25]. Knowing that gale winds pertain to winds greater than 62 kph and storm winds pertain to winds greater than 89 kph [26], the gale winds and the storm winds can serve as the isotach to find the value for Rmax and A, shown in Figure 2.

2.2. Regional Wind Field Modeling

Since the forces involved do not include friction in the resulting horizontal wind profile, the effects of turbulence are factored out. Hence the winds are regional wind speeds assumed to be 10-min sustained winds. With the method of analysis made with respect to the center of the storm, for the stationary observer, the resulting regional wind speed is computed:

$${\overrightarrow{V}}_{10-min}\left(r\right)={\overrightarrow{V}}_{gradient}\left(r\right)+{\overrightarrow{V}}_{translation}$$

(4)

where ${\overrightarrow{V}}_{10-min}\left(r\right)$ is the 10-min sustained wind velocity at distance r from the center of the typhoon, ${\overrightarrow{V}}_{gradient}\left(r\right)$ is a gradient wind velocity computed using Equation (2), and ${\overrightarrow{V}}_{translation}$ is the translational velocity of the typhoon. The direction of the winds is estimated based on the correlation between the location of the observation point and the typhoon’s center. Please note that the variables are expressed in vector form, and vector operations must be conducted.

A total of 1148 typhoons (tropical storms and stronger) from 1977 to 2021 are subjected to the tropical cyclone modeling procedure, processing a total of 42,744 detailed wind information data, interpolating the 6-hourly and 3-hourly detailed wind information data and storm track to 1-h intervals and 15-min intervals resulting in what is called the regional cyclonic winds since they are free from surface friction and are cyclonic in nature. This study will focus on the regional cyclonic wind field, as the surface wind is more dependent on wind exposure which involves topography, upstream terrain effects, vegetation, and human settlement. Wind exposure varies throughout the Philippines and differs at sea and on land. Regional cyclonic wind fields are assumed to be independent of wind exposure [25] and are assumed to coincide with the 10-min sustained winds.

The regional cyclonic wind field is simulated over 961 stationary observation points, which are arranged in a 0.5° by −0.5° grid from 5° N to 20° N and from 115° E to 135° E, shown in Figure 3. Each observation point will contain a total of 131,704 hourly simulated regional cyclonic wind field data and 526,813 15-minutely simulated regional cyclonic wind field data, with an example shown in Figure 3.

2.3. Return Period Analysis

With the annual and monthly maxima being obtained from each observation point, an extreme value (GEV) analysis is being performed to determine the return period winds, with an example shown in Figure 4. The annual maxima at each observation point are fitted into a generalized extreme value (GEV) function using Type I distribution [27,28].

$$V\left(R\right)=u+a (-\ln (-\ln (1-\frac{1}{R}))$$

(5)

where u and a are the generalized extreme value function coefficients and V(R) is the return period wind speed at a return period of R years.

To determine how the recent data have resulted in the changes in the return period winds, for each observation point, the GEV analysis is performed on the regional cyclonic winds from 1977 to 2010, and the other GEV analysis is performed on the regional winds from 1977 to 2021. The 100-year winds for both GEV analyses are compared.

2.4. Historical Analysis

Apart from the return period winds, the historical maxima in the periods 1977–2010 and 2000–2010 are compared with the historical maxima of 2011–2021 to determine how the maxima have changed over different sectors of the Philippines described in Figure 1. The maxima of the Southwest Monsoon months–which are composed of the months of June, July, August, and September–and the Northeast Monsoon months–which are composed of the months of October, November, and December–of the two different periods are also compared to determine the changes in the seasonal variations of the wind hazard brought by typhoons.

2.5. ENSO Analysis

The computed Holland-B parameters are then related to the sea-surface temperature (SST) anomalies of the El Niño-Southern Oscillation (ENSO), as studies showed that a necessary condition for development lies in the SST anomalies, which coincide with the observed sea level pressure difference between Tahiti and Darwin, Australia, standardized by the Southern Oscillation Index (SOI) [29,30]. The Holland-B parameters of typhoons are specifically related to the warm and cold phases of SOI, indicating the onset of El Niño and La Niña (Figure 5).

3. Results

3.1. Timeline of Holland-B Parameter of Typhoons

The timeline of the Holland-B parameter of typhoons is determined and shown in Figure 6. It is essential to note that there was a shift from reconnaissance mission measurements to satellite measurements after 1987. Huge variations can be observed in the Holland-B parameters during the reconnaissance mission period. The variations lessened when satellite methods were used to make measurements. Determining the boxplots shown in Figure 7 reveals an increasing average trend of the Holland-B parameter since 2011.

3.2. SOI vs. Holland-B Parameter

The Holland-B parameters for the typhoon present in a particular month are correlated with the Southern Oscillation Index determined during that month. The compilation of the correlation results in the box plot is shown in Figure 8.

The positive shift in the SOI indicates the La Niña Phase, while the negative shift indicates the El Niño phase. The boxplots in Figure 8 suggest that higher Holland-B parameters are the highest when in the neutral phase.

3.3. Changes in the Annual Maximum Winds

With the peak winds captured over shorter intervals, this study uses the maximum winds determined from 2011 to 2021 (See Figures S1–S3) compared with the maximum winds from 2000 to 2010 (See Figures S4–S6) to limit the time when the JMA is in charge of the Western Pacific Basin. The comparison is made to maximum year-round winds, SW Monsoon season maximum winds, and NE Monsoon maximum winds. To compare with the overall period, including when the Joint Typhoon Warning Center was in charge of the Western Pacific Basin, the maximum winds determined from 2011 to 2021 are also compared with the maximum winds from 1977 to 2010 (See Figures S7–S9). The percentage change in maximum winds between the period 2000–2010 and 2011–2021 and between 1977–2010 and 2011–2021 over the identified sectors in Figure 1 are also tabulated in

Table 2. Percent Difference—2000–2010 vs. 2011–2021.

Region	Mean	Median	Min	Max	STDev	Outliers (−)	Outliers (+)
All year:
• Northern Luzon	9.47	5.78	−22.61	60.35	20.12	0.00	5.88
• Central and Southern Luzon	8.98	13.20	−22.86	33.63	13.20	3.77	0.00
• Palawan	26.90	28.24	−9.53	78.75	23.53	0.00	4.55
• Visayas	54.54	50.55	−9.58	78.75	36.25	0.00	2.22
• Mindanao	51.76	43.71	13.39	129.7	31.72	0.00	4.35
SW Monsoon Season:
• Northern Luzon	14.70	11.72	−10.21	60.35	18.01	0.00	5.88
• Central and Southern Luzon	−3.33	−0.32	−42.03	29.91	16.25	3.77	3.77
• Palawan	−13.30	−17.41	−30.55	4.20	10.55	0.00	0.00
• Visayas	−12.85	−7.66	−43.77	12.58	12.96	2.22	2.22
• Mindanao	1.26	4.01	−23.78	15.26	14.27	1.45	0.00
NE Monsoon Season:
• Northern Luzon	9.33	6.78	−16.91	40.97	13.94	0.00	2.94
• Central and Southern Luzon	14.24	14.20	−13.27	35.61	10.75	1.89	0.00
• Palawan	38.43	34.26	8.43	89.03	23.79	0.00	4.55
• Visayas	60.63	54.72	1.82	131.64	31.81	0.00	2.22
• Mindanao	54.78	44.54	8.46	133.9	34.78	0.00	5.80

and

Table 3. Percent Difference—1977–2010 vs. 2011–2021.

Region	Mean	Median	Min	Max	STDev	Outliers (-)	Outliers (+)
All year:
• Northern Luzon	−4.12	−4.86	−22.79	12.31	9.78	0.00	0.00
• Central and Southern Luzon	−10.86	−11.72	−33.34	15.06	10.49	1.89	3.77
• Palawan	−1.14	−2.37	−23.57	38.73	18.12	0.00	4.55
• Visayas	7.08	7.70	−21.97	47.01	16.09	0.00	4.44
• Mindanao	−0.04	−8.16	−29.05	50.03	18.52	0.00	7.25
SW Monsoon Season:
• Northern Luzon	0.86	2.25	−19.13	20.82	11.15	0.00	0.00
• Central and Southern Luzon	−12.50	−12.49	−42.03	29.82	15.74	0.00	3.77
• Palawan	−18.12	−20.66	−30.62	−0.80	10.61	0.00	0.00
• Visayas	−21.70	−22.94	−43.50	5.98	12.59	0.00	2.22
• Mindanao	−6.33	−0.37	−54.79	8.25	14.10	4.35	0.00
NE Monsoon Season:
• Northern Luzon	−12.88	−10.60	−34.91	1.75	11.73	0.00	0.00
• Central and Southern Luzon	−11.17	−12.12	−33.34	15.06	10.73	1.89	3.77
• Palawan	−1.17	−2.37	−23.57	38.73	18.16	0.00	4.55
• Visayas	8.78	12.09	−21.97	47.01	15.80	0.00	2.22
• Mindanao	0.06	−8.16	−29.05	50.03	18.43	0.00	7.25

, respectively. It is also important to note that before satellite measurements started in 1988, measurements were made in reconnaissance missions. Apart from the year-round winds shown in Figure 9, the seasonality of the winds is also considered with changes in the SW Monsoon season winds and NE Monsoon season winds shown in Figure 10 and Figure 11.

In Table 2 and Table 3, a vast difference between the mean and median meant that the percentage changes in wind speeds were more spread on one side of the distribution than the other. The outliers, which were identified to have exceeded the 95th percentile of the percentage change in wind speeds, are also counted on both the positive and the negative sides of the distribution with respect to the mean. These outliers indicate specific areas within those regions where the winds are either stronger or weaker. Bicol peninsula experiences stronger winds than the rest of Central and Southern Luzon. Northern Palawan experiences stronger winds than the rest of Palawan. Eastern and Northeastern Mindanao experience stronger winds than the rest of Mindanao.

The recent 11 years (2011–2021) have been noted to have stronger maximum wind than the 11 years prior (2000–2010). Although when compared to the 34 years prior (1977–2010), the changes are not that prominent, especially in the Northern Philippines. It is important to note that there may be slight changes in the estimation technique within the said period, most notably with the measurements done using reconnaissance missions before 1988.

Evaluating the seasonal maxima shows that during the Southwest Monsoon season, there is an increase in the wind hazard in the Northern Sector of the Philippines, with the exposure to the wind hazard shifting northward. On the other hand, during the Northeast Monsoon season, an increase in the wind hazard in the Southern Sector of the Philippines is observed with the exposure to the wind hazard shifting southward. Overall, the changes in the year-round maxima by comparing the maxima from 2011 to 2021 to the maxima from 2000 to 2010 also indicate an overall increase in wind hazard across the Philippines.

3.4. Changes in the Return Period Winds

The changes in the 100-year return period from the observation period of 1977–2010 (See Figure S10) to the observation period of 1977–2021 (See Figure S11) are also shown in Figure 12. The percent changes over the identified sectors in Figure 3, on the other hand, are tabulated in

Table 4. Percentage change in the 100-year winds from the period of 1977–2010 to the period of 1977–2021.

Region	Change in 100-Year Winds
	Mean	Median
Northern Luzon	9.02%	−1.31%
Central and Southern Luzon	3.27%	−6.01%
Palawan	2.67%	0.48%
Visayas	9.45%	8.62%
Mindanao	8.91%	5.55%

.

4. Discussion

It is essential to subdivide the duration of observation into four periods: (1) the reconnaissance era by the Joint Typhoon Warning Center from 1977 to 1987, (2) the satellite era by the Joint Typhoon Warning Center from 1988 to 1999, (3) the first 11 years of the Japanese Meteorological Agency in the new millennium from 2000 to 2010, and (4) recent 11 years of the Japanese Meteorological Agency from 2011 to 2021. The reconnaissance era is marked by the vast variations in the computed Holland-B parameters (Figure 6), showing possible uncertainties, especially when relating the maximum winds to the minimum central pressure and its pressure gradient. The satellite era is marked by fewer variations in the computed Holland-B parameters computed from the 10-min sustained winds, as accuracy up to the regional level (free from surface friction and turbulent effects) is ensured due to the broader scope of measurement.

The parametric typhoon wind field of this study mainly used the R_max and the B-parameter model, but in contrast to stochastic simulations and synthetic typhoon analysis used for the necessity of future predictions [31], this study used the parametric models to hindcast past typhoons and to provide a 10-min sustained wind profile, which is dubbed as regional cyclonic winds. As a result, this study is freed from producing probabilistic and empirical track models, which were done to estimate the wind hazard for China’s Pacific coastal areas [32]. Hindcasting also removes the need to model dissipation on the Holland-B parameter and R_max [33].

Focusing on the primary circulation of the modeled typhoons, the study mainly considers the proportionality of the gradient winds to the 10-min sustained winds, given that the wind exposure is uniform across the horizontal wind profile. Differences in surface roughness result in the difference in gradient wind height, resulting in different surface winds [34]. Using the geographically weighted regression-based (GWR-based) subregion algorithm and determining the upstream terrain effects, it was possible to estimate the surface winds in determining the wind hazard. [35,36]. There is still a need to fine-tune the wind exposure parameters of the Philippines [37], with return period winds from the previous synthetic typhoon analysis [38] with huge differences compared to return period winds computed from extreme value analysis of the surface data from synoptic stations in the Philippines [39].

The gradient wind, free from surface friction and turbulent effects, is often less than the surface winds. Wind profiles were determined to be closer in value to the sustained winds, such as in the case of Typhoon Haiyan in 2013 [40], Haima in 2016 [41], and Goni in 2020 [42]. Conversion factors are also introduced to relate the gradient wind to the surface wind [43,44]. Later analytical models for determining the surface winds show that the relationship mainly depends on wind exposure, which can be computed separately. [45]

When related to the SOI, the Holland-B parameters computed from the 10-min sustained winds revealed that typhoons with high pressure gradients are often present during the ENSO neutral phase. It has been noted that the genesis occurs farther at sea during the Northeast Monsoon season compared to El Niño and La Niña. During the Southwest Monsoon season, studies determined that genesis is even higher, and the mean locations of genesis are closer to the Philippines. [46] The Northeast Monsoon season conditions during the neutral phase allow typhoons to gather strength at the higher sea surface temperature in the Central Pacific. In contrast, the Southwest Monsoon season conditions bring the intertropical convergence regions closer to the Philippines, allowing typhoons to develop. The behavior of typhoons varies between these seasons due to the other large-scale motions.

This study noted an increase in wind hazards in the Visayas Region and Mindanao region, especially during the Northeast Monsoon season over recent years. The increase has occurred due to the positive shift in the Pacific Decadal Oscillation in the early 2010s. The shift has caused warm sea surface temperature anomalies, low-level westerlies, and easterlies favoring genesis during the Northeast Monsoon season. [15] The subsequent typhoon movement during the Northeast Monsoon season, which has shifted southwards, is caused by the Western Pacific Subtropical High (WPSH) variability. The WPSH has been shifting westwards and southwards toward the Philippines over the past decade. [16] The shift has resulted in a lesser frequency of typhoons recurving to the north and the southern regions in the Philippines, such as Visayas and Mindanao. [47] Studies also determined that long-term enhancement of the WPSH will be expected. However, the main driver will be the higher temperature contrast between land and sea, instead of rising sea temperatures alone. [48] Studies on the WPSH during the Southwest Monsoon season also show that the enhanced WPSH would increase the frequency of landfalling typhoons in Northern Luzon [49], which this study has supported with the noted increase in severe wind hazard. The transition period between the Southeast Monsoon season and Northeast Monsoon season, which occurs in the last weeks of September, is when wind hazard by typhoons is more expected in Southern Luzon.

As to what to expect with the future wind hazard, the extreme values analyses determine an overall increase in the 100-year winds for the Philippines. Visayas (9.45%) and Mindanao (8.91%) experienced the most increase in the 100-year winds. The time history of the Holland-B parameters shows an increasing trend since 2011, indicating that potentially destructive typhoons with higher pressure gradients and maximum sustained winds are expected. Studies that applied 10,000-year synthetic typhoon analysis using atmospheric data as indicators also determined a 5–10% increase in the 100-year wind speeds, which is the lowest compared to China (30–40%), Korea (5–20%) and Japan (5–20%) [50].

5. Conclusions

This study aims to evaluate the trends in wind hazards caused by typhoons in the Philippines. Typhoons from 1977 to 2021 are subjected to wind field modeling using the detailed wind information data by the Japanese Meteorological Agency. Using the wind field models of the typhoons, the regional cyclonic wind speeds are determined over observation points within the Philippine Area of Responsibility arranged in a 0.5° by −0.5° grid.

It was through the analysis of the trends of regional cyclonic winds that the overall increase of typhoon strength over the years has been determined. Climate change results in typhoons with more violent winds with steeper pressure gradients near the center, especially during the ENSO neutral phase.

The wind hazard has also shifted spatially, with the southern sectors of the Philippines or the Southern Philippines, in general, being more susceptible to typhoons in recent years. The Southern Philippines experiences an increase (decrease) in wind hazards during the Northeast (Southwest) Monsoon season. The Northern Philippines experiences an increase (decrease) in wind hazards during the Southwest (Northeast) Monsoon season.

The overall increase in both the historical maximum and the return period wind should prompt an update to the wind design and construction practices to meet the demand of these noted increases to ensure that the updated building design will achieve sustainability.

There is also a need to determine the wind exposure parameters in the Philippines to convert the cyclonic winds computed in this study to surface winds, considering upland terrain roughness, wind directionality, and additional gustiness.