Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014

责编:

Please download the latest version of this article and read suggestions below from editorial office for revision.  

About dataset:

1, About the data set "TyphoonTracks.zip", the author describes that it has five elements: TyphoonID, PositionID, YMD, Grade and Windspeed, but in the data set, in addition to these elements, it also has Id, ymd, Grade2, Wind and ID2, whether these are repeated or redundant? Suggest the author check it, if they are not necessary, please delete them; 2, Suggest the author add the address where the data set in the Science DB: http://www.sciencedb.cn/dataSet/handle/396 to the "Data service system"

About article:

1. Please check the geographical scope and complete the units.

2. Dataset composition part: Why in such timespans specified? Suggest to explain it in the text below.

3. What’s the difference between this dataset and similar datasets? What’s the advantage? If not mentioned in chapter 5, suggest you to add some introduction.

4. 53 or 63 years in chapter 1?

5. Data set or dataset? Western Pacific… or western North Pacific Ocean? Should those be unified in this article or not? You decide.

6. Only 2.1 in chapter 2, no 2.2? Anything missed?

7. "...windspeed data were available only for 1977–present", Could you add some explanation about it?

8. There four .zip mentioned in Dataset Profile, do you think you should demonstrate correspondingly in chapter 3? If not, ignore it.

9. " We also failed to detect clear temporal trends in typhoon characteristics that might relate to climate change processes occurring globally", Suggest to put it to chapter 4.

10. Reference part: ①All the reference formats are not fit standard. ②The authors are not intact in reference 4, 7, 9, 11.

E.g., Walther G, Post E, Convey P et al. Ecological Responses to Recent Climate Change. Nature 416 (2002): 389–395.   

Long Y, Mao Q & Shen Z. Urban form, transportation energy consumption, and environmental impact integrated simulation: A multi-agent model, in Spatial Planning and Sustainable Development: Approaches for Achieving Sustainable Urban Form in Asian Cities, 227 – 247, ed. Kawakami M et al. Berlin: Springer-Verlag, 2012.

【2017-04-19】 评论来自:版本 1
作者:

About dataset:

• About the data set "TyphoonTracks.zip", the author describes that it has five elements: TyphoonID, PositionID, YMD, Grade and Windspeed, but in the data set, in addition to these elements, it also has Id, ymd, Grade2, Wind and ID2, whether these are repeated or redundant? Suggest the author check it, if they are not necessary, please delete them.

The reviewer is correct. Those fields are repeated. We have eliminated them, and created a new version of TyphoonTracks.zip. This has been uploaded to KU Scholarworks, and is being provided to ScienceDB.

• Suggest the author add the address where the data set in the Science DB: http://www.sciencedb.cn/dataSet/handle/396 to the "Data service system"

Done.

About article:

• Please check the geographical scope and complete the units.

Added “latitude” and “longitude” for clarity, but otherwise was not sure what it was that was being requested.

• Dataset composition part: Why in such timespans specified? Suggest to explain it in the text below.

Now clarified.

• What’s the difference between this dataset and similar datasets? What’s the advantage? If not mentioned in chapter 5, suggest you to add some introduction.

A sentence has been added to make the point more clearly: no other such dataset exists.

• 53 or 63 years in chapter 1?

It is 63. Fixed. Thanks.

• Data set or dataset? Western Pacific… or western North Pacific Ocean? Should those be unified in this article or not? You decide.

Done.

• Only 2.1 in chapter 2, no 2.2? Anything missed?

A second subheading has now been added, to avoid this seemingly odd arrangement.

• "...windspeed data were available only for 1977–present", Could you add some explanation about it?

A brief explanation is now added—apparently those data were not available prior to that year

• There four .zip mentioned in Dataset Profile, do you think you should demonstrate correspondingly in chapter 3? If not, ignore it.

Done.

• " We also failed to detect clear temporal trends in typhoon characteristics that might relate to climate change processes occurring globally", Suggest to put it to chapter 4.

Moved to the end of part 1, which seemed most appropriate.

• Reference part: o All the reference formats are not fit standard. o The authors are not intact in reference 4, 7, 9, 11.

♣ E.g., Walther G, Post E, Convey P et al. Ecological Responses to Recent Climate Change. Nature 416 (2002): 389–395.

♣ Long Y, Mao Q & Shen Z. Urban form, transportation energy consumption, and environmental impact integrated simulation: A multi-agent model, in Spatial Planning and Sustainable Development: Approaches for Achieving Sustainable Urban Form in Asian Cities, 227 – 247, ed. Kawakami M et al. Berlin: Springer-Verlag, 2012.

The references have been updated to add the missing author names and to conform fully to CSD formats.

【2017-06-09】 评论来自:版本 1
责编:
Reviewer 1:
This dataset consists of grid data processed from information concerning the typhoon path in the Northwest Pacific, including typhoon frequency and intensity (average and maximum speed). It provides valuable data for studying the impact of climate disaster and typhoon on environment and ecology. The paper also gives a detailed introduction to the data sources, processing method, final variables, dataset names and websites. That said, I would suggest the author clarify the temperal resolution of the data - whether they are monthly or yearly recorded.  
Reviewer 2: 
In this draft, the author provides data about typhoons in the Northwest Pacific for 1951-2004 years.The data present a detailed dataset summarizing the frequency and intensity of typhoons across the Western Pacific north of the Equator, based on data characterizing tracks for 1673 typhoons from the Japan Meteorological Center. This set of data has obvious characteristics and advantages.This dataset is the only existing summary of broad, long-term patterns in typhoon frequency and strengthacross a major ocean basin, for use in diverse applications to questions in other fields.I think this set of data is useful for understanding the environmental and disturbance conditions of typhoon formation and development. Conducive to tackling climate problems and questions related to climate change.
The following questions need to be discussed in more detail.
1、How to deal with data distortion caused by uneven data distribution by line segment?
2、How to deal with the classification of typhoons in the Pacific Northwest considered in this JMC data?
3、What do you mean by "summarized for M" in the last second lines of the ninth page? 
【2017-08-09】 评论来自:版本 1
作者:

Reviewer 1:

I would suggest the author clarify the temporal resolution of the data - whether they are monthly or yearly recorded. We have now added verbiage regarding the temporal resolution of the data to the manuscript. See response to question 1 of reviewer 2, below.

Reviewer 2:

1. How to deal with data distortion caused by uneven data distribution by line segment?

This is a good point. In effect, the data available to us have a temporal resolution of one day. As a consequence, if a typhoon is moving fast, then the spatial resolution of the typhoon data is coarser; if it is moving slowly, then the spatial resolution of the typhoon data will be finer. There really is no remedy for this “basement level” of spatial resolution to these data, as there is no finer resolution in time (and consequently in space) to these data. We have added this point to the manuscript.

2. How to deal with the classification of typhoons in the Pacific Northwest considered in this JMC data?

We decided to concentrate on quantitative aspects of the typhoon phenomenon across the northwestern Pacific Ocean. As a consequence, we focused on windspeed and frequency of occurrence, rather than on categorical classifications in developing the datasets presented in this paper. We have added mention of the classifications in the text now, to clarify this point.

3. What do you mean by "summarized for M" in the last second lines of the ninth page?

Thanks for pointing out this phrase that is not as clear as it could be. We changed it to “and not in any summary form,” which should be more clear and understandable for the readers.

【2017-08-16】 评论来自:版本 1
责编委: In 6. Usage notes,"There are no copyright or proprietary restrictions for these datasets". In China Scientific Data, all data papers and their datasets should be free for reuse under cc-by 4.0 by default, so I would like to suggest the author to delete this sentence. 【2017-08-23】 评论来自:版本 1

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Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014

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Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014

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Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014

A. Townsend Peterson*, Lindsay P. Campbell, Rafe M. Brown

Biodiversity Institute, University of Kansas, Lawrence, Kansas 66045, USA

*Email: town@ku.edu

Abstract: Disturbance has been a repeated theme in ecology in recent decades, yet incorporating its frequency and pattern at broad spatial scales into ecological analyses has been difficult—rather, most environmental datasets used in broad-extent analyses represent average conditions. We present a detailed dataset summarizing the frequency (i.e., number of typhoons) and intensity of typhoons (average and maximum windspeeds) across the Western Pacific north of the Equator, based on data characterizing tracks for 1673 typhoons from the Japan Meteorological Center. The data presented are aggregated and resampled to 0.2° (~22 km at the Equator) spatial resolution; temporal coverage extends 1951–2014. We also present data specifically for prior to 1980 and after 1999, to respond to questions related to climate change, although no major changes were evident between the time periods.

Keywords: typhoon; disturbance; Western Pacific; maps

Dataset Profile

English title

Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014

Corresponding author

A. Townsend Peterson (town@ku.edu)

Data author(s)

A. Townsend Peterson, Lindsay P. Campbell, Rafe M. Brown

Time range

1951–2014

Geographical scope

0°–90°N, 90°E–160°W; Western Pacific Ocean north of the Equator and adjoining land areas

Spatial resolution

0.2° (~22 km at the Equator)

Data volume

1673 typhoon tracks

Data format

1 line shapefile, 3 GeoTIFF raster data files

Data service system

Science DB <http://www.sciencedb.cn/dataSet/handle/396>; KU Scholarworks <http://hdl.handle.net/1808/22466>

Source(s) of funding

U.S. National Science Foundation, grant number DEB-1418895

Dataset/Database composition

See summary of datasets and their characteristics in Table 1. For each data dimension, as feasible, we provide data subsets for the entire time span of the data, prior to 1980, and after 2000; the latter two time periods relate to before the onset of major global climate change, and after such changes had been ongoing for two decades.

TyphoonTracks.zip: Line shapefile summarizing 1673 typhoon tracks across the Western Pacific north of the Equator. Fields in attributes table:

TyphoonID: A unique code corresponding to each of the typhoons analyzed in the dataset from the Japan Meteorological Center

ID: A code unique to each TyphoonID that provides specific data for the typhoon at a point in time

ymd: Year, month, day corresponding to the particularly PositionID of the typhoon in question

Grade: The severity grade rating associated with the typhoon at that particular point in time

Windspeed: Windspeed measured for the typhoon at that particular point in time

Typhoons_avgwind.zip: GeoTIFF raster file summarizing the average value of windspeed for typhoons crossing the pixel in the timespan specified (_all = 1977–2014, _2000 = 2000–2014)

Typhoons_maxwind.zip: GeoTIFF raster file summarizing the maximum value of windspeed for typhoons crossing the pixel in the timespan specified (_all = 1977–2014, _2000 = 2000–2014)

Typhoons_count.zip: GeoTIFF raster file summarizing the number of typhoons crossing the pixel in the timespan specified (_all = 1951–2014, _1980 = 1951–1979, _2000 = 2000–2014)

1. Introduction/Overview

Disturbance has become the focus of intense interest in ecology[1-6], as part of a shift from focus on average conditions to a fuller appreciation of the dynamics of natural systems. Disturbance also—almost by definition—implies longer time scales, with different disturbance regimes associated with different temporal spans[7]. This new focus on extreme events on longer time scales becomes still more relevant in view of outputs of general circulation models that indicate that future climates may be characterized by more extreme and more frequent extreme events[8].

An important, large-scale agent of disturbance in many marine and coastal systems are typhoons and hurricanes[9], many of which cross the world’s oceans each year. Even though typhoon-disturbance-adaptation is well-documented in many ecosystems[10-11], incorporation of these unpredictable and episodic events into broader-scale, regional analyses and analyses of geographic distributions of species has been minimal or lacking. As such, here, we present datasets synthesizing typhoon frequency and intensity across the Western Pacific north of the Equator, based on a dataset that spans 63 years.

This dataset is rather unusual in that it summarizes large-scale disturbance frequency and intensity on a near-hemispheric scale. We are intrigued with region-to-region differences in typhoon-mediated disturbance, beyond the well-known tropical and subtropical concentration of these storms. That is, for example, we note strong contrasts between the central and northern Philippines versus the southern Philippines in terms of typhoon frequency. The striking contrasts in typhoon frequency across such a relatively restricted set of latitudes has important implications in terms of forest dynamics, dispersal opportunities, and extinction probabilities for species. We also failed to detect clear temporal trends in typhoon characteristics that might relate to climate change processes occurring globally.

2. Data collection and processing

2.1 Overview

This dataset summarizes the frequency (i.e., number) and intensity of typhoons (average and maximum windspeeds) across the Western Pacific north of the Equator. The data are summarized from individual typhoon track data from the Japan Meteorological Center, over the period 1951–2014 via a simple interpolation procedure (Figure 1). That is, the raw data are presented as a day by day series of points with information on typhoon strength; we extended daily values to the midpoints of connecting line segments to create continuous tracks with day-specific strength information for each typhoon (Figure 2). Finally, typhoon track data were processed into raster-format summaries of typhoon frequencies and strengths across the Western Pacific north of the Equator and adjacent landmasses (Figure 3). Data are presented for the entire time span, as well as for prior to 1980 and after 1999 (Table 1), to respond to questions related to climate change (Figure 4).

Figure 1 Summary of process by which point-format original data were transformed into continuous, line-format shapefiles. Note that the blue hash-marks represent the midpoints (spatially) between each consecutive pair of points. Note also that each line segment, from hash-mark to hash-mark, represents a separate entity in the shapefile, with distinct attributes (e.g., windspeed).

Figure 2 Visualization of individual typhoon tracks in the Western Pacific Ocean north of the Equator over the period 1951–2014.

Figure 3 Three views of gridded data summarizing typhoon frequency and intensity across the Western Pacific north of the Equator. Gray (on land) and white (at sea) indicates a zero value. Color ramps indicate values ranging from low (light) to high (dark).

Table 1 Summary of data dimensions, dataset names, and time spans regarding typhoon frequency and intensity in the Western Pacific Ocean north of the Equator, during 1951–2014.

Variable

Dataset

Time span

Number of typhoons

Typhoons_count_all

1951–2014

 

Typhoons_count_post2000

2000–2014

 

Typhoons_count_pre1980

1951–1979

Average windspeed

Typhoons_avgwind_all

1977–2014

 

Typhoons_avgwind_post2000

2000–2014

Maximum windspeed

Typhoons_maxwind_all

1977–2014

 

Typhoons_maxwind_post2000

2000–2014

Figure 4 Summary of changes in typhoon frequency between 1951–1980 and 2000–2014. Dark blue = 50–100% reduction, light blue = 1–50% reduction, gray = no change, light red = 1–25% increase in frequency, medium red = 25–50% increase, and dark red = >50% increase in frequency. Note that windspeed comparisons between these time periods were complicated by limited availability of windspeed data for the early time period.

2.2 Methods

Individual typhoon tracks were supplied by the Japan Meteorological Center in the form of ASCII, column-delimited files that summarize daily position, time, strength, etc., for each typhoon (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/trackarchives.html). Although it is easy to turn these files into GIS shapefiles, the line-format shapefile format does not permit lines to have different attributes at different points along their extents. As such, we created shapefiles that connect the consecutive points along the track of each typhoon, but that represent sets of objects within the shapefile, each centered on a point and connecting the midpoint of the line segment to the previous point to the midpoint of the line segment to the next point. Figure 1 summarizes the methodology by which these data were created; code in R12 is provided at http://hdl.handle.net/1808/22465. Individual typhoon shapefiles were merged to form a single shapefile including the tracks of all 1673 typhoons.

To convert the line-format typhoon tracks to a raster-format view of the region, we created a polygon-format, “fishnet” shapefile that consisted of square polygon elements that were 0.1° (~11 km) on each side. We used spatial joining procedures in ArcGIS 10.3 to attach fishnet identification codes to typhoon segments. From this intermediate product, we were able to create tables summarizing counts of typhoons, and averages of average and maximum wind speeds (note that wind speed data were available only for 1977–present, apparently because those data were not available previous to that year) for each polygon in the fishnet. Finally, the fishnet was converted to raster format, and resampled (cubic convolution) to 0.2° to generalize the results somewhat (further resampling may be advisable, to remove some spatial artifacts related to reporting of integer values for typhoon positions).

3. Sample description

The overall pattern of frequency of typhoons across the Western Pacific north of the Equator shows some fascinating patterns and nonlinearities (Figure 3). The broad-scale limitation of Western Pacific typhoons to approximately 7–53°N latitude was clear among our results, but even more striking was a clear concentration in terms of typhoon frequency at latitudes of 7–19°N. This concentration was not noticeable in terms of typhoon strength (Figure 3). The data were synthesized into four products, presented in this contribution: (1) a line shapefile summarizing 1673 typhoon tracks, and GeoTIFF raster files summarizing; (2) the average value of windspeed; (3) maximum value of windspeed; (4) number of typhoons across the Western Pacific north of the Equator. These summaries were developed—as feasible—for the entire time period of the data, and for before 1980 and after 2000; the latter two time periods were in response to the timing of major global temperature increases.

4. Quality control and assessment

Data quality assurance checking involved detailed inspection and exploration of patterns to detect any typographical or other data errors. The data provided herein were re-processed from the original data supplied by the Japan Meteorological Center, and as such depend on the quality and reliability of the original source data. We noted some level of ‘striping’ that coincided with integer values of latitude and longitude, which appears to reflect coarse-resolution reporting of typhoon positions (e.g., to the nearest integer degree). This problem was ameliorated by resampling to 0.2° (~22 km) resolution, but is still present; users concerned about these effects may wish to resample to still-coarser resolutions.

5. Value and significance

This dataset is, to our knowledge, the only synthesis of raw typhoon data into openly accessible, digital datasets. As such, this dataset is the first and only existing summary of broad, long-term patterns in typhoon frequency and strength across a major ocean basin, for use in diverse applications to questions in other fields. That is, several typhoon track datasets are available online, including the Japan Meteorological Agency (http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/trackarchives.html), Joint Typhoon Warning Center (https://metoc.ndbc.noaa.gov/web/guest/jtwc/best_tracks), and others. However, those data exist as series of coordinates and intensities only, and not in any synthesized or summarized form. As such, our shapefile compilation and GeoTIFF raster summaries appear to be unique, and summarize important dimensions of environmental conditions and disturbance.

6. Usage notes

Code for processing point-format data from the Japan Meteorological Center into shapefiles is available at http://hdl.handle.net/1808/22465. The actual data are available at http://hdl.handle.net/1808/22466. These data and code packets are housed in KU Scholarworks, a permanent digital repository providing open, global access to scholarly products of the faculty of the University of Kansas. There are no copyright or proprietary restrictions for these datasets.

Acknowledgments

We thank the Japan Meteorological Center for its commitment to maintaining high-quality data on typhoons in the Western Pacific, and for its generosity in making these invaluable data openly available to the scientific community. We thank Qiao Huijie for assistance with submission of the manuscript for publication.

Authors and contributions

A. Townsend Peterson, PhD, Professor; research area: biodiversity, biogeography, ecology. Contribution: motivation of study, data analysis, writing.

Lindsay P. Campbell, PhD, Post-doctoral Researcher; research area: disease ecology, landscape effects. Contribution: data analysis.

Rafe M. Brown, PhD, Professor; research area: systematics, biogeography. Contribution: motivation of study.

References

[1] Bazzaz F, Sipe T. Physiological ecology, disturbance, and ecosystem recovery, in Potentials and limitations of ecosystem analysis, 203-227, ed Schulze E-D and Zw?lfer H: Springer, 1987

[2] Meurant G. The Ecology of Natural Disturbance and Patch Dynamics: Academic Press, 2012.

[3] Brawn J, Robinson S, Thompson III F. The role of disturbance in the ecology and conservation of birds. Annual Review of Ecology and Systematics 32 (2001): 251-276.

[4] Nathan J, Osem Y, Shachak M et al. Linking functional diversity to resource availability and disturbance: A mechanistic approach for water-limited plant communities. Journal of Ecology 104 (2016): 419-429.

[5] Hubbell S T. The Unified Neutral Theory of Biodiversity and Biogeography. Princeton, N.J.: Princeton University Press, 2001.

[6] Roxburgh S, Shea K, Wilson J B. The intermediate disturbance hypothesis: Patch dynamics and mechanisms of species coexistence. Ecology 85 (2004): 359-371.

[7] Ogle K, Barber J, Barron-Gafford G et al. Quantifying ecological memory in plant and ecosystem processes. Ecology Letters 18 (2015): 221-235.

[8] Stott P. How climate change affects extreme weather events. Science 352 (2016): 1517-1518.

[9] Chi C-H, McEwan R, Chang C-T et al. Typhoon disturbance mediates elevational patterns of forest structure, but not species diversity, in humid monsoon Asia. Ecosystems 18 (2015): 1410-1423.

[10] Wang X, Wang W, Tong C. A review on impact of typhoons and hurricanes on coastal wetland ecosystems. Acta Ecologica Sinica 36 (2016): 23-29.

[11] Monoy C, Tomlinson K, Lida Y et al. Temporal changes in tree species and trait composition in a cyclone-prone Pacific dipterocarp forest. Ecosystems 19 (2016): 10-13.

[12] R Development Core Team R. R: A Language and Environment for Statistical Computing; http://www.r-project.org/. Vienna, 2013.

Data citation

A. Townsend Peterson, Lindsay P. Campbell, Rafe M. Brown. Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014 (Draft version). Science Data Bank, 2017. DOI: 10.11922/sciencedb.396.

Paper citation

A. Townsend Peterson, Lindsay P. Campbell, Rafe M. Brown. Typhoon frequency and intensity across the Western Pacific Ocean north of the Equator, 1951–2014 (Draft version). China Scientific Data, 2017. DOI: 10.11922/csdata.170.2017.0134.

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