https://doi.org/10.20575/00000052
Polar Data Journal, Vol. 8, 10–22, March 2024
Ⓒ 2024 National Institute of Polar Research. This work is distributed
under the Creative Commons Attribution 4.0 International license.

Spatiotemporally continuous temperature monitoring using opticalfibers (Loop1) in the internal forest areas in Alaska for the period
from 2017 to 2019
Kazuyuki SAITO1,2*, Go IWAHANA2, Hiroki IKAWA3, Hirohiko NAGANO4and Robert BUSEY2**

1

Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showamachi,Kanazawaku, Yokohama, Kanagawa 236-0001.

2International Arctic Research Center, University of Alaska Fairbanks, 2160 Koyukuk Drive,Fairbanks, AK 99775-7340, USA.

3

Hokkaido Agricultural Research Center, National Agriculture and Food Research Organization,
1 Hitsujigaoka, Toyohira, Sapporo, Hokkaido 062-8555.

4

Institute of Science and Technology, Niigata University, 8050 Ikarashi 2-no-cho, Nishiku, Niigata
City, Niigata 950-2181.
*Corresponding author. Kazuyuki Saito (ksaito@jamstec.go.jp)**

Current affiliation: Alaska-Pacific River Forecast Center, National Weather Service, National

Oceanic and Atmospheric Administration, 6930 Sand Lake Rd., Anchorage, AK 99502, USA.
(Received October 19, 2023; Accepted January 22, 2024)

Abstract:

This is the third report of the annually recurring, continuous measurements of the fiber-optic DTS (distributed temperature sensing) system using Raman-scattering optical time domainreflectometry, implemented at a research site in the interior of Alaska (Poker Flat Research Range).
This is the last portion of the measurement (called “Loop1”), which started in 2012, resumed in 2017
after the one-year intermission due to the sensor cable failures, and terminated indefinitely in 2019. In
this period, a fiber-optic cable sensor was deployed across the landscape to measure temperatures athigh spatiotemporal resolution (0.5-meter and 30-minute intervals) horizontally across the different
land surface cover types. It also had four sub-sections where the cable sensor was set in coilconfigurations (1.2 m high), installed vertically half below and half above the ground. The total cable

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ran 1.9 km for this period of measurements, within which about a 1.4 km section covered horizontal
surface paths. This dataset contains the measurements from September 23, 2017 to September 6, 2019(372 observation days). Due to potential deterioration of the measurement quality because ofoccasional partial and total interruptions, and of the occasional DTS equipment malfunctioning, thisperiod of data is archived separately from the previous datasets.

1. Background & Summary
This dataset updates the previous ones1,2 and concludes the Loop1 measurement conducted from2012 to 2019; the period consists of three distinct periods dissected by two substantial intermissions,that is, from 2012 to 20141, from 2015 to 20162, and from 2017 to 2019 (this dataset). As described in
the section 5 of this paper and in the previous accompanying papers1,2, the continuity, extent, andoverall quality of the measurement along the sensor cable is vulnerable to external direct physicaldisturbances, such as those from animals. In addition, the extensive operation of another Loopmeasurement (Loop2) was initiated in 2017 using two channels of the DTS equipment other than thoseused for Loop1. These factors likely induced occasional unstable performance with potentiallydeteriorated quality of the Loop1 DTS measurement for this period. Comprehensive evaluations of themeasured data across the whole periods are required in terms of relative attributions of the changes inambient background and the internal factors of the DTS system, however, it is beyond the scope of
this paper.

2. Location
The Poker Flat Research Range (65.12°N; 147.49°E, 210 meters above mean sea level) is a
facility managed by the University of Alaska Fairbanks, located about 50 km northeast of Fairbanks
in the interior of Alaska (Fig. 1). The area is in a discontinuous permafrost zone.

3. Methods
The cable sensor was initially installed in 2012 over 2.7 km long, of which surface paths (sixhorizontal sections) cover 2.0 km and the five vertical sections coiled around PVC pipes1 cover
0.7 km (Figure 2). Both the end part of the horizontal section (ca. 300 m) and the fifth tube (total ofca. 100 m) were damaged by attacks from wild animals and discarded in 20152, and further damaged
in 2017. For this period, the total cable ran 1.9 km, within which about a 1.4 km section covered
horizontal surface paths. See Figures 2 and 3 for the horizontal section locations from 1 to 5. The
version Ver.4.1.36 of the software “DTS Configurator” was used from 2017 to 2019, which ran on the11K. Saito et al.

Windows 7 operating system.
The general explanations of the measurement methods were provided in the previous papers1,2 interms of the physical principles, the equipment, and the fiber-optic cable sensors of the DTS
measurements, together with further details of the software specifications and the source of thevalidation data3.

4. Data Records
This entry is a new quality-controlled dataset covering the period from 2017 to 2019, compiled
from three separate data entries archived at the Arctic Data archive System as described below (#3).
The dataset consists of three different types of files, that is, two attribution files, one quality-controlledtemperature data file, and original output files.
1. Attribution files.
(1) Temporal information (1 file)
A comma-separated-value text file with entities of [data number, year, month, day, hour, minute,second, and date] (Table 1).
The number of stored items is 17256. Here, the date denotes the elapsed date, with the fraction ofa day, from January 1, 2017, beginning at noon, Alaska Standard Time.
Filename: TemporalData_Loop1_2017_2019.csv.
(2) Locational information (1 file)
A comma-separated-value text file with entities of [data number, longitude, latitude, section
number, section information, observation number in the section] (Table 2, Figure 3).
The number of stored items is 3871. Note that only the first half of the data was retained becauseof the lower quality of the data in the second half for this period of the measurement as describedin section 5 below.
Filename: SectionData_Loop1_2017_2019.csv.
2. Quality-controlled temperature data file (1 file)
An unformatted binary (4-byte float) data file only of the temperature [°C] data, extracted fromthe quality-controlled output files (i.e., checked for no missing or inappropriate values, as describedin section 5).
It has the (location, time) dimension as described above in #1. The file is in the size of
267,191,904 bytes (= 3871 x 17256 x 4). See Figure 4 for coverage of the successful, qualitycontrolled data in time and space.
Filename: Loop1_temperature_2017_2019.dat
3. Original output files
This new dataset is compiled from the three previously registered original trace files (the data12

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citations #2-4):(1) A20190625-002 “Spatio-temporally continuous temperature monitoring using optical fibers(Loop1) in the internal forest areas at Alaska in 2017” (https://ads.nipr.ac.jp/dataset/A20190625002)(2) A20190625-003 “Spatio-temporally continuous temperature monitoring using optical fibers(Loop1) in the internal forest areas at Alaska in 2018” (https://ads.nipr.ac.jp/dataset/A20190625003)(3) A20191021-001 “Spatio-temporally continuous temperature monitoring using optical fibers(Loop1) in the internal forest areas at Alaska in 2019.” (https://ads.nipr.ac.jp/dataset/A20191021001)
A trace file is produced by the “DTS Configurator” software in text (ASCII) format with the filename convention “dtsout1-YYYYMMDD00N000.tra”, where YYYY, MM, and DD are the year,
month, and day of the data production, and N is the order of products in the same day. The first 117
lines are header information on the measurement settings. Each observation output starts with“[Trace.xxx],” where xxx denotes the number of consecutive measurements and ends with temporal
information when the output was produced.
Each line of output has the following entries separated by a semicolon: “Number; distance[meter]; temperature [°C]; original DTS signal [-]; loss of signal [dB]”
Data example:[Trace.4069]
0;0;16.0011787414551;-8.26901149749756;-0.348246369759242
1;0.5;13.5141181945801;-8.3326940536499;-0.32830130259196
2;1;10.4333248138428;-8.41308689117432;-0.334304012854894
3;1.5;9.35385322570801;-8.44165992736816;-0.34427952170372(omission)
31;15.5;-2.62263703346252;-8.77354717254639;-0.381170624494553
32;16;-1.57275438308716;-8.74331474304199;-0.383834759394328
33;16.5;-1.42903351783752;-8.7391939163208;-0.3812262515227
34;17;-2.39346647262573;-8.76692867279053;-0.374911000331243(omission)
9319;4659.5;-2.73332405090332;-8.77674770355225;-10.7754872004191
9320;4660;-1.58336901664734;-8.74361896514893;-10.7812287648519
9321;4660.5;-1.27457284927368;-8.73476982116699;-10.8274384816488
9322;4661;-2.59927845001221;-8.77287197113037;-10.7515415827433(omission)
9344;4672;10.2049369812012;-8.41911506652832;-11.2823729197184

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9345;4672.5;9.34458446502686;-8.4419059753418;-11.3449542999268
9346;4673;9.33199691772461;-8.44224071502686;-11.3502987543742
Date.Year;2017
Date.Month;11
Date.Day;5Time.Hour;0Time.Minute;2Time.Second;3

5. Technical Validation
We have taken the same measures to assure the technical quality of the measurements and thecompiled data: 1) calibration of the measured temperature of the cable sensor, 2) comparison of theDTS measurement with another observation (namely, the JICS tower observations3. cf. Figure 51), and3) removal of the failed observations due to breaks or inappropriate fusion of the cables. Please referto the previous paper2 for the details. Figure 5 shows the daily mean values on the selected days. After
five years of operation, the DTS equipment started to function unstable, and the loss of signal became
prominent in the latter half of the measurement. Thus, this period of measurement is archived
separately from the previous datasets and retains only the first half of the go-back-and-forthmeasurements in the quality-controlled dataset. However, the original measurement data are also
provided as stated in section 4 3. Original output files.

6. Usage Notes
It should be noted that, as a nature of time domain reflectometry, each measured value at a point
does not necessarily indicate the point-wise temperature at the corresponding point but rather averaged
temperature along the intervals that contain the point.

7. Competing interests
There are no competing interests in this study.

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8. Figures

Figure 1. Location of the DTS system installed at the Poker Flat Research Range (PFRR;
University of Alaska Fairbanks). [Reproduced from Saito et al. (2018)]Figure 2. Installation information of the Loop1 fiber-optic cable from 2017 to 2019 at Poker Flat
Research Range. Horizontal sections of the cable sensor are delineated by different
lines. Numbers in white denote the tube sections. Colors show the surface cover types.

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Figure 3. Daily summary of the DTS observations on January 1, 2018. The daily average is shownin blue, and the range is in red. Sectioning of the cable for inter-tubes (#1 to #5) andtubes (tb1 to tb4) are also shown. The figure in round parentheses in the figure title
denotes the number of successful observations on the day.

Figure 4. Dates and locations of the successful observations by Distributed Temperature Sensing(DTS) system from 2017 to 2019. Successful observations are shown in red.

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Figure 5. Examples of Loop1 daily summary (average in blue, and range in red) from 2017 to2019. The figure in round parentheses in the figure title denotes the number ofobservations on the day.

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Figure 5. (Continued)

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9. Tables
Table 1. The data structure of the temporal information file.

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Table 2. The data structure of the locational information file.

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Author contributions
K. Saito initiated, designed, and supervised the entire project; procured the sets of equipment,
negotiated the use of PFRR, led the deployment of the cable sensor, and performed the calibrations,programming, and measurements of the DTS system. G. Iwahana and R. Busey contributed toinstallation of the DTS equipment. GI, H. Nagano, and H. Ikawa contributed to maintaining DTS
measurement. GI conducted land cover classification for the site and generated figures of geographicalinformation. RB supervised the technical aspects of the project. All the authors contributed to the final
manuscript with input, suggestions, and editing.

Acknowledgements
This project was conducted as a part of the JAMSTEC (Japan Agency for Marine-Earth Scienceand Technology) and IARC (International Arctic Research Center, University of Alaska, Fairbanks)
collaboration study, and in part supported by the “Integrated Research Program for Advancing Climate
Models (TOUGOU Program, JPMXD0717935715), the “Advanced Studies of Climate Change
Projection (SENTAN Program, JPMXD0722681344)”, the Arctic Challenge for Sustainability (ArCS,JPMXD1300000000), and the Arctic Challenge for Sustainability II (ArCS II, JPMXD1420318865).
KS is grateful to Drs. Masao Fukasawa, Hide Sakaguchi, Akira Noda, and Michio Kawamiya for theirsupport in initiating and conducting the DTS project. The authors are thankful to Dr. Kathe Rich andMr. Robert Valdez for their cooperation and facilitation in investigating at the PFRR site.

References
1. Saito, K., Iwahana, G., Ikawa, H., Nagano, H. and Busey, R. C. Links between annual surface
temperature variation and land cover heterogeneity for a boreal forest as characterized by continuous,fibre-optic DTS monitoring. Geosci. Instrum. Method. Data Syst. 2018, 7 (3), p. 223–234.
https://doi.org/10.5194/gi-7-223-2018.
2. Saito, K., Iwahana, G., Ikawa, H., Nagano, H. and Busey, R. Spatiotemporally continuous temperaturemonitoring using optical fibers (Loop1) in the internal forest areas in Alaska for the period from 2015
to 2016. Polar Data J. 2023, 7, p. 58–71. https://doi.org/10.20575/00000049.
3. Nakai, T. et al. Characteristics of evapotranspiration from a permafrost black spruce forest in interior
Alaska, Polar Sci. 2013, 7 (2), p. 136–148. https://doi.org/10.1016/j.polar.2013.03.003.

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Data Citations
1. Saito, K., Iwahana, G., Ikawa, H., Nagano, H., and Busey, R. Spatiotemporally continuous temperaturemonitoring using optical fibers (Loop1) in the internal forest areas in Alaska for the period from 2017
to 2019. 1.00, Japan, Arctic Data archive System (ADS), 2024. https://doi.org/10.17592/001.2023101901.
2. Saito, K., Iwahana, G., Ikawa, H., Nagano, H., and Busey, R. Spatio-temporally continuous temperaturemonitoring using optical fibers (Loop1) in the internal forest areas at Alaska in 2017. 1.00, Japan, Arctic
Data archive System (ADS), 2024. https://doi.org/10.17592/001.2019062502.
3. Saito, K., Iwahana, G., Ikawa, H., Nagano, H., and Busey, R. Spatio-temporally continuous temperaturemonitoring using optical fibers (Loop1) in the internal forest areas at Alaska in 2018. 1.00, Japan,Arctic Data archive System (ADS), 2024. https://doi.org/10.17592/001.2019062503.
4. Saito, K., Iwahana, G., Ikawa, H., Nagano, H., and Busey, R. Spatio-temporally continuous temperaturemonitoring using optical fibers (Loop1) in the internal forest areas at Alaska in 2019. 1.00, Japan, Arctic
Data archive System (ADS), 2024. https://doi.org/10.17592/001.2019102101.

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