Places of the research

Investigation of urban heat island effect of Norilsk and Apatity cities in Russian Arctic with usage experimental measurements and remote sensing

Mikhail Varentsov(1,2), Pavel Konstantinov(1), Irina Repina(2), Timofey Samsonov(3)

(1) Lomonosov Moscow State University, Faculty of Geography, Department of Meteorology and Climatology, mvar91@gmail.com(2) A. M. Obukhov Institure of Atmosphere Physics, Air-Sea Interaction Lab.(3) Lomonosov Moscow State University, Faculty of Geography, Department of Cartography and Geoinformatics

Stationaryautomatic weather

stations (AWS)

Low-cost compact temperature sensors

(iButton)

Mobile weather station

MTP-5 microwave temperature profiler

(Norilsk only)

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The warmest urban point

The coldest point

AWS city center

AWS backround (forest)

Meteorological station

3-day averageCase with max. UHI

(1-hour average)

Spatial distribution of temperature anomaly - deviation from mean value at background points (Meteo station and iButton sensor at the north-east of the area). Solid isotherms goes every 1 ⁰C.

Spatial distribution of the temperature anomaly - deviation from meanvalue at background points (Meteo station, AWS in forest and severaliButton sensors). Solid isotherms go every 1 ⁰C.

Case with max. UHI (1-hour average)

6-days average

The biggestpolar cities:1. Murmansk

302 000 inh.2. Norilsk

177 000 inh3. Vorkuta

64 000 inh.4. Tromsø

61 000 inh5. Apatity

59 000 inh

NorilskVorkuta

Murmansk

Apatity

Tromso

Apatity (2015)

Data & methods

In situ measurements

Post-processing of the raw data

The problem: joining the data from local meteorological station (reliable), AWS (relatively reliable) and iButtons (less reliable)

Solution:

• Calibration of the sensors before the experiment – static correction for each sensor

• In points with AWS we also install iButtons – dynamic correction for control sensors

• Spatial interpolation of the dynamic correction for other sensors

𝑻(𝒕) = 𝑻𝒔𝒓𝒄(𝒕) + ∆𝑻 + ∆𝑻𝒅𝒚𝒏(𝒕, 𝒙, 𝒚)

Building 2D temperature fields

For Norilsk: 𝑻 𝒙, 𝒚 = 𝑻𝟎 𝒛 𝒙, 𝒚 , + 𝑺𝑲 ( ∆𝑻𝟏, … , ∆𝑻𝒏 , ∆𝑻𝒏𝒐 𝒖𝒓𝒃)

∆𝑻𝒏𝒐 𝒖𝒓𝒃 =𝟏

𝒌

𝒊=𝟏

𝒌

∆𝑻𝒊 ∆𝑻𝒊= 𝑻𝒊 − 𝑻𝟎 𝒁𝒊

where 𝑻𝒊 - temperate measurements by AWS and iButton sensors, 𝒏 – total number of measurement points, 𝒌 – number of points outside built territory𝒛𝒊 - height of measurement point (according ASTER DEM)𝑻𝟎(𝒛) – vertical temperature profile according MTP-5 measurements𝑺𝑲 ( 𝑿𝟏, … , 𝑿𝒏 , 𝑿 ) – simple kriging interpolation operator with prescribed mean 𝑿

For Apatity: 𝑻 𝒙, 𝒚 = 𝑺𝑲 ( 𝑻𝟏, … , 𝑻𝒏 , 𝑻𝒏𝒐 𝒖𝒓𝒃)

𝑻𝒏𝒐 𝒖𝒓𝒃 =𝟏

𝒌

𝒊=𝟏

𝒌

𝑻𝒊

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Apatity (2014)

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AWS city center

AWS background

Meteorological station

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Spatial distribution of the temperature anomaly - deviation from meanvalue at background points (Meteo station and AWS located outside ofthe map border). Solid isotherms go every 1 ⁰C.

5-days average

Case with max. UHI (1-hour average)

29 January – 03 February,favorable synoptic conditions (several calm periods)

29 January – 04 February, wider observation network, unfavorable synoptic conditions (except one night)

Mobile measurements vs stationary sensors

Norilsk (#7) Apatity, 2015 (#1)

Apatity, 2015 (#3)

Apatity, 2014 (#4) Apatity, 2014 (#6) Mean square error

# of soundingDyn.

correction No correction

1. Apatity 31.01.2015 1.19 1.4

2. Apatity 31.01.2015 0.36 0.31

3. Apatity 30.01.2015 0.32 0.67

4. Apatity 29.01.2014 1.64 1.69

5. Apatity 30.01.2014 0.9 1.14

6. Apatity 02.02.2014 0.45 1

7. Norilsk 21.12.2013 0.37 0.48

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Norilsk

Effect on the house heating

1. First experimental research of UHIs of the cities of the Russian Arctic was made;

2. Technology of experimental measurements and data processing was developed and tested;

3. Different types of observations (AWS, iButton’s, car-based sounding, MODIS data) shows the existence of the significant UHIs in these cities during the winter and polar night;

Main Results

20 – 23 December 2013:the middle of the polar night, transient synoptic conditions

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T at the warmest urban point

T used at power station

Apatity 2014:∆T=0.6⁰C

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Apatity 2015:∆T=-0.6⁰C

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Norilsk:∆T=-0.1⁰C

Cost of 1⁰C error:Apatity (686 mWt):

≈ 1000 €/dayNorilsk (2691 mWt):

≈ 3900 €/ day

According to the analysis of the work parameters of Apatitypower station (Jan-Feb 2014):

The question: is the UHI of the polar cities taken into consideration at power station, providing the house heating?Answer: generally yes, except the moments with strong frosts and the most significant UHI, when power station use lower temperature that it is really observed, and spent more fuel that is necessary

Question: is temperature anomaly inNorilsk real UHI, or effect of orography& atmospheric stratification?Answer: surface temperature data accordingto MODIS remote sensing shows that Norilskforms ‘Urban heat peninsula’.

TERRA 17 January 2014 Mean data (TERRA) for Nov. 2013 – Jan. 2014 To read about our research:Varentsov et al., Investigation of the urban

heat island phenomenon during polar night

based on experimental measurements and

remote sensing of Norilsk city. Current

problems in remote sensing of the earth from

space, 2014, Vol. 11, No. 4, pp. 329-337.

Konstantinov et al., Mapping of Arctic Cities

Urban Heat Island Based on the Composition

of Field Meteorological Measurements and

Satellite-Derived Imagery (Example of Apatity,

Kola Peninsula), Issledovanie Zemli iz

Kosmosa (ISSN 0205-9614), 2015, No. 3, pp.

27-33 (in print).

This study was supported by Russian GeographicSociety, research projects No. 69/2013-H7 and27/2013-НЗ and by RFBR, project No. 15-55-71004 (Belmont Fotum project “HIARC:Anthropogenic Heat Islands in the Arctic:Windows to the Future of the Regional Climates,Ecosystems, and Societies”)

Moscow

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∆T (urban - meteo station)The warmest urban pointMeteorological stationAWS Militaty base