Investigation Sea Surface Temperature Variation of Lake Van Using Avhrr

INVESTIGATION SEA SURFACE TEMPERATURE VARIATION OF LAKE VAN USINGAVHRR

Mehmet Tahir KAVAK1 Sabri KARADOĞAN2

1Yrd.Doç.Dr., Dicle Üniversitesi, Z.G.Eğitim Fak,. Fen Alanlar Eğt. Böl. Fizik Eğt. AB Dalı, 21280, Diyarbakır,[email protected]

2Doç.Dr.,Dicle Üniversitesi Z.G.Eğitim Fak., Sosyal Alanlar Eğt. Böl. Coğrafya Eğt. AB Dalı, 21280, Diyarbakır,[email protected]

ABTSRACT

Sea surface temperature (SST) is an important parameter which could be derived from space via satellites, Such as AVHRR(Advanced Very High Resolution Radiometer), and used in oceanography and meteorology due to its major influence on theexchange processes at the air-sea interface.Lake Van is as an enclosed tectonic basin on the Eastern region of Anatolia and mostly investigated in terms of water level,boundary and climatic parameters. Present work investigated long term SST variation using AVHRR data of Lake Vanincluding quake years which other scientists also interested in.

Keywords: Lake Van, Remote Sensing, AVHRR, Sea Surface Temperature SST.

ÖZET

SST (Sea-Surface Temperature) Deniz Yüzeyi Sıcaklığı hava ve deniz yüzeyleri arasındaki ısı değişiminin tahmin edilmesindekullanılan önemli bir jeofiziksel parametredir. Özellikle küresel iklim modelleri için gerekli olan dünyanın ısı dengesininortaya konması, atmosferik ve okyanus sirkülasyonlar ve anomalilerin durumunu ortaya koymak açısından SST büyük önemtaşımaktadır.Van Gölü Ülkemizde su seviyesi ve iklim parametreleri konusunda en çok izlenen ve çeşitli bilimsel çalışmalara konu olanalanlardan birisidir. Su yüzeyi ve sınırlarında yıldan yıla önemli değişimler gözlenen Van Gölü, ülkemizin Doğu AnadoluBölgesinde önemli tektonik ve kapalı bir havzadır. Özellikle son yaşanan deprem yerbilimcilerinin ve diğer disiplinlerindikkatini Van Gölü çevresine çekmiştir. Su yüzeyi sıcaklık değişimi tektonik açıdan bir parametre olarak kullanılabilir. Buçalışmada farklı yıllara ait AVHHR uydu verileri kullanılarak uzaktan algılama yöntemiyle göl yüzeyindeki su sıcaklıkkoşullarının yıllara göre ve yıl içindeki değişimleri gözlenmiştir.

Anahtar Sözcükler: Van Gölü, Uzaktan Algılama, AVHRR, Su Yüzeyi Sıcaklığı.

VAN GÖLÜNDE SU YÜZEYİ SICAKLIK DEĞİŞİMİNİN AVHRR UYDU VERİLERİYLEİNCELENMESİ

1. INTRODUCTION

Lake Van is the largest lake in Turkey, located in the far east of the country in Van district. It

is a saline soda lake, receiving water from numerous small streams that descend from the

surrounding mountains. Lake Van is one of the world's largest endorheic lakes (having no

outlet). The original outlet from the basin was blocked by an ancient volcanic eruption.

Although Lake Van is situated at an altitude of 1,640m with harsh winters, it does not freeze

due to its high salinity except occasionally the shallow northern section, Kadıoğlu et al.

M.T. Kavak, S Karadoğan Invest. SST Var. of Lake Van Using AVHRR

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(1997). Lake Van is 119 meter across at its widest point, averaging a depth of 171 meter with

a maximum recorded depth of 451 meter. The lake surface lies 1,640 meter above sea level

and the shore length is 430 kilometer. Lake Van has an area of 3,755km2 and a volume of 607

cubic kilometers Degens et al. (1984).

Figure 1. Geographic setting and bathymetric map of Lake Van. Huguet et al. (2011).

The western portion of the lake is deepest, with a large basin deeper than 400 m lying

northeast of Tatvan and south of Ahlat. The eastern arms of the lake are shallower. The Van-

Ahtamar portion shelves gradually, with a maximum depth of about 250 m on its northwest

side where it joins the rest of the lake. The Erciş arm is much shallower, mostly less than 50

m, with a maximum depth of about 150 m (Wong, 1978, Tomonaga, 2007)

Climate change is considered to be one of the most severe threats to ecosystems around

the globe (ACIA 2004; Rosenzweig et al. 2007). Monitoring and understanding the effects of

climate change pose challenges because of the multitude of responses within an

ecosystem and the spatial variation within the landscape. A substantial body of research

demonstrates the sensitivity of lakes to climate and shows that physical, chemical, and

biological lake properties respond rapidly to climate-related changes (ACIA 2004;

Rosenzweig et al. 2007). Previous studies have suggested that lakes are good sentinels of

global climate change because they are sensitive to environmental changes and can integrate

changes in the surrounding landscape and atmosphere (Carpenter et al. 2007; Pham et al.

2008; Williamson et al. 2008). One parameter, SST, which is important indicator of global

warming first, was studied for Lake Van by Sarı at al. (2000) from February 1998 to January


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1999 to map SST with bathymetry and current using remote sensing techniques. Level change

studied by Yıldız and Deniz (2005). Environmental Geology of Lake Van Basin studied by

Çiftçi et al. 2008. Affect by climate change studied by Kadıoğlu et al. 1997. Geologically

studied by Degens et al.1984. Present work extended SST study to 19 years which might be

useful for scientists to study Lake Van with other parameters such as level change, eco

system, dissolved organic carbon (DOC), regional air temperature etc., for today and after.

2. MATERIAL AND METHOD

To study SST of Lake Van two set of data from AVHRR was used. Although datasets were

from the same sensor there was difference in the way they were stored for instance data from

NASA was global set and the resolution was 4 km, data from DLR was covering western part

of Lake Van (see figure 2) but the resolution was 1 km.

2.1 Data from DLR

The monthly MCSST data with the resolution of 1 km AVHRR from March 1993 to

December 2011 was downloaded in geotiff format from

(http://eoweb.dlr.de:8080/servlets/template/welcome/entryPage.vm) Earth Observation on the

WEB interface (EOWEB). The SST values are stored as follows: “0” is reserved for

“LAND”, “31,875” is reserved for “CLOUD” and no “NO DATA”. Images were containing

whole Europe, so to study the area of interest images imported to ERMapper 5.2

(www.erdas.com) then the SST of each month for the Lake Van was calculated excluding

flagged pixels.

b (NASA) 4 Km


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a (DLR) 1Km

Figure 2. SST images of Lake Van.

2.2 Data from NASA

Night time (in order to remove solar heating) monthly mean a global Multi Channel Sea

Surface Temperature (MCSST) dataset based on measurement by Advanced Very-High

Resolution Radiometer on board NOAA satellites (McClain et al., 1985) which was available

from January 1985 to December 2009 was downloaded. The dataset was in 16 bit HDF

(Hierarchical Data Format) format and mean SST data have a temperature resolution of about

0,1 ºC and a spatial resolution of about 4 km. (see the description of AVHRR monthly Global

MCSSS at: http:///podaac.jpl.nasa.gov:2031/dataset_docs/avhrr_wwww_mcsst.html).

After the extraction of Lake Van from global dataset, to transform digital numbers (DN)

values to SST values, the following equation provided by AVHRR-NOAA was applied

SST=DN·0.075-3.0

In the absence of quasi-synchronous MCSST and in situ data relating to the same area of the

Lake Van, the validation of satellite-derived SSTs is impossible. In accordance with McClain

et al. (1985), the MCSST anomalies relative to the global ship (drifter) data are as follows:

biases, 0.3–0.4 ºC (0.1ºC) and standard deviation, 0.5–0.6 ºC (0.5 ºC), with the MCSST

values being lower than those of ship/drifter-based values.

3. RESULTS AND DISCUSSIONS


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Figure 3. Seasonal SST variation of western part of Lake Van for 19 years.

Seasonal SST variation of western part of Lake Van acquired from DLR data. The dark line

is general average. This figure does not show any abnormal behavior, seasonal SST’s entirely

are located about general average.


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Figure 4. Seasonal SST behavior of Lake Van from NASA 4 km resolution, the dark line is

general average.

Seasonal SST variation of Lake Van was acquired from NASA. The dark line is general

average. This figure does show minus (-) temperature values in winter (December, January,

February, and March) which may be indication of ice.


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Figure 5. Seasonal Averaged SST of two datasets. Western Van from DLR and whole Lake

Van from NASA

Figure 5 showing seasonally averaged SST. Effect of cold water input to general temperature

could be seen in the shallow region and which could affect the general average SST. This also

shows the importance of bathymetry when studying SST. And again this also shows the

eastern part of the lake reduces general temperature about 3°C. This difference is not due to

origin of the dataset, this issue was tested on 18 km GAC image (Global Area Coverage) by

Kavak, 2000, for the Black Sea; the difference between two datasets for summer was found

only about 0,7°C.


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Figure 6. Dataset from NASA along with general average.

Figure 6 showing monthly SST variation of the .lake Van along with the general average

from 1985 to 2009.

Figure 7. Yearly SST variations of Lake Van along with trend line.

Fluctuation could be observed along 19 years period, the trend line also shows Lake Van

affected from global warming.


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Figure 8. SST vs Number of sunspots.

Figure 8 generated using SST and sunspots (http://www.godandscience.org/ apologetics

/global_warming_myths.html#n01) count from 1985 to 2009. As seen no correlation between

yearly average SST and sunspots were detected.

El Nino event which was recorded strongest ever on 1997-1998

(http://apollo.lsc.vsc.edu/classes/ met130/notes/ chapter10/elnino.html) does not appear to

have effect SST of Lake Van.

Although present work does show that Lake Van has taken its account from global warming

this is not due to sun spot activities or El Nino event. The rise on SST may be due to tectonic

events which cause of energy discharge. Rise on SST, increase evaporation, accordingly

change in level, biological activities, and chemical constituents in and around the lake. These

changes with other parameters must be investigated using high resolution satellite data such as

Landsat, SPOT etc., since they provide synoptic view from space that biological patterns in a

whole region can be observed and measured, presumably allowing more accurate estimates of

primary productivity to be made.

4. REFERENCES


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Investigation Sea Surface Temperature Variation of Lake Van Using Avhrr