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Title アラスカ・ランゲル山アイスコアから復元した北部北太平洋域への陸域起源物質沈着に関する研究

Author(s) 佐々木, 央岳

Citation 北海道大学. 博士(環境科学) 甲第12667号

Issue Date 2017-03-23

DOI 10.14943/doctoral.k12667

Doc URL http://hdl.handle.net/2115/65541

Type theses (doctoral)

File Information Hirotaka_Sasaki.pdf

Hokkaido University Collection of Scholarly and Academic Papers : HUSCAP

https://eprints.lib.hokudai.ac.jp/dspace/about.en.jsp

アラスカ・ランゲル山アイスコアから復元した

北部北太平洋域への陸域起源物質沈着に関する研究

（A study on depositions of crustal materials onto the northern North Pacific reconstructed from an ice core drilled at Mount Wrangell, Alaska）

佐々木央岳

SASAKI Hirotaka

北海道大学大学院環境科学院

博士論文

平成２９年３月

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ŵ 1.1 Ā�eTi2)ŻĲ$25ÈĝŃďľƃ&\gQCJƯUno et al., 2003ưƱ large horizontal gradients of SO4 are predicted around thelatitude of 40–45!N. Under such a situation, slight changesin the timing and/or spatial location of the transport path-ways (e.g., errors in modeled meteorology) can lead to largevariations in the time series at a fixed point. Sulfateconcentrations are simulated well after day 102.[44] A peak in BC, Radon and CO is observed on day 107

(17 April), which is not captured in the model. ObservedSO4 does not show this peak. Model simulated horizontalSO4 distribution is shown in Figure 8f. We can see that aclean air mass existed to the west of Rishiri. Matsumoto etal. [2003b] discussed this EC peak on the basis of opticalparticle counter (OPC) and other chemical tracers andindicated the possibility of biomass or forest fire influencesfrom the far east Russia. Further study is needed to identifythe origin of this plume.[45] The CFORS scaled radon and CO show good agree-

ment with the observations. As listed in Table 3, thestandard deviation and coefficient of variation (C.V.) are

Figure 6. Comparison between observed concentrations at Hachijo island and CFORS model output.(a) black carbon, (b) dust and Al, (c) nss-SO4 and (d) radon.

Table 3. Statistical Comparisons of Model and Observationsa

Tracers

Observations CFORS

Mean s.d. C.V. Mean s.d. C.V.

RishiriRadon, Bq/m3 4.88 1.20 0.25 5.42 1.47 0.27EC (BC), mg/m3 0.43 0.26 0.60 0.41 0.19 0.46SO4, mg/m3 2.52 1.37 0.54 3.34 2.11b 0.63Al (Dust),c mg/m3 1.41 1.59 1.13 21.3 19.7b 0.92CO, ppb 209.6 36.9 0.18 217.9d 35.6d 0.16

HachijoRadon, Bq/m3 1.23 0.52 0.42 1.23 0.48 0.39EC (BC), mg/m3 0.33 0.15 0.45 0.40 0.16 0.40SO4, mg/m3 3.70 1.51 0.41 4.82 2.20b 0.46Al (Dust),c mg/m3 0.83 0.63 0.75 22.9 24.9b 1.08

aHere, s.d., standard deviation; C.V., coefficient of variation.bEvaluated by daily averaged value.cAl is taken for observation and total dust concentration for model.dCalculated by (CO ! CFORS) " 2.

UNO ET AL.: REGIONAL CHEMICAL WEATHER FORECASTING ACE 36 - 11

13

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sand. However, the area of blowing sand was moved tonorthward in 2003 and 2004, so that high occurrenceareas of both wind velocity over 6.5 m s−1 and blowingsand were consistent in a degree. In the northeast part ofChina, it has been steadily occurred blowing sand withoccurrence over 8 times and 6.5 m s−1 wind over 100times.

Wind velocity of 14 m s−1 mainly occurred between40–50°N and 100–120°E, and occurrences more than40 times recorded in 1993, 1995, and 2000–2002 (Fig.7). In the Gobi region, wind velocity of 14 m s−1 morethan ten times has been steadily observed during theentire period, however, there were narrow distributionsin 1997, 1999, and 2003. This tendency was applied tothe distributions of 14 m s−1 wind in the InnerMongolia. In the northeast part of China, 14 m s−1

wind rarely occurred during the entire period, so that itcan be known that there is no strong wind occurring inthis region. The distributions of strong wind of 14 m s−1

were in accordance with those of DSI or dust storm.According to Wang et al. (2003), occurrence ofsandstorm is closely related to the strong wind.However, driving force of strong wind causing theoccurrence of sandstorm is different in many regionsbecause of the differences of land surface character-istics. Therefore, investigation on surface characteristicssuch as vegetation having an important effect to theoccurrence of sandstorm is also required.

4.3. Climatic and vegetation features at severalmeteorological stations

On the basis of occurrences of blowing sand and duststorm observed in the source regions such as China,Mongolia, and Inner Mongolia, and so forth, sourceregions are divided into three (A, B, C) regions (Fig. 8).Three regions are located in dry arid region (Gobiregion: 35–45°N, 100–110°E), semi-arid region (InnerMongolia: 40–45°N, 110–120°E), and cultivated region(northeast part of China: 40–50°N, 120–125°E) where

the Korea peninsula has been mainly affected wheneverAsian dust occurred during the springtime from 1993 to2004. Eight meteorological stations are also selected(Table 2). Each station has evenly frequent occurrencesof blowing sand during 1993–2004. Eight meteorolog-ical stations include one station in Mongolia and sevenstations in China, and five stations were selected in Aregion where Asian dust frequently occurs and twostations in C region where it has been affected to theKorean peninsula since 2001. Another one station islocated in B region.

Tables 3 and 4 show occurrences of blowing sandand dust storm respectively at eight meteorologicalstations during the springtime from 1993 to 2004. In thecase of blowing sand, it tends to decrease recently at I(Guaizihu) and II (Jartai) stations of A region. At I(Guaizihu) station, occurrence of ten times in 2002when the most severe Asian dust occurred was fewer

Table 2Eight meteorological stations in China and Mongolia

Station no. Lat. (°N) Lon. (°E) Station name (nation)

I 52378 41.37 102.37 Guaizihu (China)II 53502 39.78 105.75 Jartai (China)III 44347 44.42 105.32 Tsogt-ovoo (Mongolia)IV 53231 41.45 106.38 Hails (China)V 53723 37.78 107.4 Yanchi (China)VI 53276 42.4 112.9 Jurh (China)VII 50844 46.40 123.42 Tailai (China)VIII 54236 42.42 122.53 Zhangwu (China)

Table 3Occurrence of blowing sand (code #7) at eight meteorological stationsduring the springtime from 1993 to 2004

Year Meteorological stations

I II III IV V VI VII VIII

1993 46 74 39 13 36 19 5 181994 28 48 21 15 30 16 18 121995 34 68 7 26 48 19 5 111996 27 71 14 29 33 6 15 131997 20 41 14 9 15 2 8 211998 28 84 19 29 20 10 16 181999 17 47 24 10 19 1 8 82000 19 56 22 35 38 26 8 252001 29 75 5 41 39 32 22 482002 10 68 13 21 25 25 11 562003 21 43 110 26 23 2 24 382004 15 18 67 25 39 2 21 61

Table 4Occurrence of dust storm (code #9, 30–35) at eight meteorologicalstations during the springtime from 1993 to 2004



1993 10 2 61 13 26 12 0 01994 23 6 40 12 17 4 0 01995 13 0 42 3 16 14 0 01996 6 0 51 5 9 1 0 01997 5 0 34 5 0 1 0 01998 12 1 49 6 14 2 0 31999 5 0 42 1 4 3 0 02000 15 4 140 6 21 17 0 12001 29 5 154 20 9 23 1 02002 19 3 77 14 7 44 2 02003 23 – – 5 2 1 – 12004 10 4 27 6 3 3 – –

243J.-Y. Lim, Y. Chun / Global and Planetary Change 52 (2006) 231–247















1993 46 74 39 13 36 19 5 181994 28 48 21 15 30 16 18 121995 34 68 7 26 48 19 5 111996 27 71 14 29 33 6 15 131997 20 41 14 9 15 2 8 211998 28 84 19 29 20 10 16 181999 17 47 24 10 19 1 8 82000 19 56 22 35 38 26 8 252001 29 75 5 41 39 32 22 482002 10 68 13 21 25 25 11 562003 21 43 110 26 23 2 24 382004 15 18 67 25 39 2 21 61




1993 10 2 61 13 26 12 0 01994 23 6 40 12 17 4 0 01995 13 0 42 3 16 14 0 01996 6 0 51 5 9 1 0 01997 5 0 34 5 0 1 0 01998 12 1 49 6 14 2 0 31999 5 0 42 1 4 3 0 02000 15 4 140 6 21 17 0 12001 29 5 154 20 9 23 1 02002 19 3 77 14 7 44 2 02003 23 – – 5 2 1 – 12004 10 4 27 6 3 3 – –
















1993 46 74 39 13 36 19 5 181994 28 48 21 15 30 16 18 121995 34 68 7 26 48 19 5 111996 27 71 14 29 33 6 15 131997 20 41 14 9 15 2 8 211998 28 84 19 29 20 10 16 181999 17 47 24 10 19 1 8 82000 19 56 22 35 38 26 8 252001 29 75 5 41 39 32 22 482002 10 68 13 21 25 25 11 562003 21 43 110 26 23 2 24 382004 15 18 67 25 39 2 21 61




1993 10 2 61 13 26 12 0 01994 23 6 40 12 17 4 0 01995 13 0 42 3 16 14 0 01996 6 0 51 5 9 1 0 01997 5 0 34 5 0 1 0 01998 12 1 49 6 14 2 0 31999 5 0 42 1 4 3 0 02000 15 4 140 6 21 17 0 12001 29 5 154 20 9 23 1 02002 19 3 77 14 7 44 2 02003 23 – – 5 2 1 – 12004 10 4 27 6 3 3 – –


30, 31, 32, and 98), and LDE is local dust event (presentweather codes: 07 and 08).

Asian dust usually occurs in the loess and sandyregions with little vegetation. The only data to provideannual and seasonal variation of vegetation over a broadarea is the normalized difference vegetation index(NDVI) observed by the polar-orbiting meteorologicalsatellite (NOAA). An Advanced Very High ResolutionRadiometer (AVHRR) sensor mounted in the NOAAsatellite has five channels. Channel 1 (0.58–0.68 μm)contains the wavelengths absorbed strongly by chloro-phyll of leaves, and channel 2 (0.72–1.10 μm) repre-sents the wavelengths reflecting strongly by spongemesophyll. Difference of reflection between these twochannels is mainly affected by vegetating condition. Asa result, normalized difference of reflection betweenthem, NDVI= (Ch 2−Ch 1) / (Ch 2+Ch 1), has a goodcorrelation with vegetation factors such as total biomass,leaf area, therefore it is used as an important factor forvegetation monitoring (Hall et al., 1995; Sellers et al.,1995).

In this study, 10-day Pathfinder AVHRR for Land(PAL) data with resolution of 8 km provided by NOAA/NASA are used in order to investigate the vegetationamount over source regions (Smith et al., 1997). ThePAL is preprocessed data applied the most precisemethod for advancement in data utilization frommeteorological satellite and burden reduction of datapreprocessing. However, PAL includes some contami-nated pixels by clouds over continuously frequent-precipitating area such as East Asia. In addition, thereare some measurement problems of data missing due tothe lack of surface receiving stations over Mongoliandesert area and the upland ranges such as Tibet (Suh andSuh, 2003b). To minimize these problems, NDVIanomalies are calculated using the monthly PAL datain East Asia from 1993 to 2000 as modified by Suh and

Suh (2003b). In addition, the temperature and precip-itation in three regions are investigated using theClimate Research Unit (CRU) (http://www.cru.uea.ac.uk) data from England.

3. GTS SYNOP report

Present weathers related with dust phenomena in aSYNOP reports are ww=06( ), 07( ), 08( ), 09( ),30–35( , , , , , ), and 98( ) shown in Table1 (WMO, 1974; Chun, 1997; Kurosaki and Mikami,2003). “ww” is the symbolic letter identifying thepresent weather.

Floating dust (code #6) refers to airborne dustparticles in the air, and it is observed when Asian dustevent occurs. Blowing sand (code #7) refers to thephenomenon that dust particles are uplifted in the airover China, Mongolia, and Northeastern part of China.It can be estimated dust rise in the source regions. Duststorm contains code #9 (dust storm during the precedinghour) and codes #30–35 (slight, moderate and severedust storm, and increase or decrease trends of duststorm). Dust storm occurred in the north where blowingsand frequently occurs.

The Dust Storm Index is estimated to analyze theintensity and occurrence of dust phenomena at the sametime. In order to calculate the DSI, more dust codes areused in addition to the abovementioned nine dust codes.

Table 1Meteorological codes associated with dust phenomena

Code Symbol Remarks

6 Widespread dust in suspension in the air, not raisedby wind at the time of observation

7 Dust or sand raised by wind at the tine of observation

8 Well-developed dust whirl(s) seen at the stationduring the preceding hour, but no dust storm or sandstorm

9 Dust storm or sand storm within sight at the time ofobservation, or at the station during the precedinghour

30 Slight or moderate dust storm or sand storm hasdecreased during the preceding hour

31 Slight or moderate dust storm or sand storm noappreciable change during the preceding hour

32 Slight or moderate dust storm or sand storm hasincreased during the preceding hour

33 Severe dust storm or sand storm has decreased duringthe preceding hour

34 Severe dust storm or sand storm no appreciablechange during the preceding hour

35 Severe dust storm or sand storm has increased duringthe preceding hour

98 Thunderstorm combined with dust storm or sandstorm at time of observation

Fig. 1. WMO synoptic observatories are shown as dot in analysisregion.


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