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Urban Heat Island Effects in the Northern High Latitudes As Revealed by Remote-Sensing Data Products

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Urban Heat Island Effects in the Northern High Latitudes As Revealed by Remote-Sensing Data Products Surface urban heat islands in northern West Siberian cities derived from MODIS satellite data sets Igor Ezau & Victoria Miles Nansen Environmental and Remote Sensing Center / Bjerknes Centre for Climate Research, Bergen, Norway 16.09.2020 Nadym, Photo by M. VarentsovENVIROMIS - 2020, 7-11 Sept. 1 Overview • Urban Arctic • Warmer Arctic • Urban Heat Island • Land use – land cover impact • Green belts and vegetation • Sustainability and risks – urban Arctic harbinger of future environment 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 2 The Urban North: More than 100 urban settlements Arctic population >4,000,000 85 % of Arctic population lives in a cities Norilsk (180.000) Vorkuta (60.000) Murmansk (300.000) Tromso Apatity (75.000) (57.000) 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 3 Cities in the northern West Siberia NWS We studied 28 cities in northern West Siberia located between 60°N and 73°N latitude. Total Population nearly 1.8 million The largest cities: Surgut (population 332,000), Nizhnevartovsk (266,000), Nefteyugansk (126,000) Noyabrsk (107,000). 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 4 Cities – Climate change agents on local scales Urban areas are warming significantly more rapidly than their natural background ▪ Modified land use – land cover ▪ Anthropogenic heat release ▪ Modified surface structure Noyabrsk Noyabrsk Example of strong the mean winter urban land surface temperature anomaly in Noyabrsk, West Siberia 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 5 Data and method: MODerate Resolution Imaging MODIS LST MODIS NDVI • 1000 m spatial resolution, • 250 m spatial resolution Spectroradiometer (MODIS) • 8-day composites • 16-day composites 2000 – 2018 Normalized Difference Urban Heat Island UHI (ΔT) Vegetation Index (NDVI) TUmax – maximum urban pixel temperature Tr – mean rural buffer temperature ΔT = TUmax-Tr Urban polygon and 2 km boundary buffer 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 6 SUE-UHI: Global MODIS SUHI dataset by Chakraborty et al. (2019) ΔT = TUmax-Tr BF-UHI – buffer-zone method SUE-UHI – inter-urban difference method Other drawbacks of the available global datasets: • No manual check – urban areas identified based on nightlight detection • E.g., misrepresentation of gas flares as urban areas • Problematic coverage of smaller urban areas and sub-urbs – • Misrepresentation of land use – land surface type • Poor coverage of the Arctic urban areas 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 7 Urban Heat Island in 11 High Arctic Cities In situ Arctic urban climate studies with UHIARC observational network: • In 6 cities (Apatity, Vorkuta, Nadym, Novy Urengoy, Murmansk, Norilsk) The review of 11 high Arctic Siberian cities Esau I., Varentsov M., Laruelle M., Miles M.W., Konstantinov P., Soromotin A., Baklanov A. A. and Miles V. V., 2020: Warmer Climate of Arctic Cities, in A review of 4 cities is published in Konstantinov P., Varentsov M., Esau I., 2018, the monography “The Arctic: Current Issues and Challenges”, Pokrovsky Environmental Research Letters, 13, doi: 10.1088/1748-9326/aacb84 O., et al. (Eds), NOVA Publishers, ISBN: 978-1-53617-306-2 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 8 Urban Heat Island in 28 Siberian Cities Miles V. and I. Esau, 2017, Remote Sensing, 9(10), 989, doi:10.3390/rs9100989 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 9 ΔT -2,00 -1,00 0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 16.09.2020 Urban Heat Island28UrbanHeatin Nizshnvartovsk Surgut Nefteugansk Nadym Labytnangi Salekhard Sovetskiy Nyagan Khanty-Mansyisk Uray Kogalym Noyabrsk Muravlenko Langepas Beloyarsky Raduzhnyi winter summer Novyi Urengoy Pyt_Yakh Bovanenkovskiy Tarko-Sale ENVIROMIS ENVIROMIS Gubkinsky Purpe Δ Δ Yar-Sale TW TS Pangody - Urengoy 2020, 7 Tazovskiy Siberian Pokachy - 11 Sept.11 Megion Miles Miles & Esau,2017 Cities 10 Surface UHI: Variations in the Nefteyugansk case study The 14 years (2001-2014) climatology of the MODIS LST in Nefteyugansk for (a) summer and (b) winter seasons. A Nefteugansk , Summer & Winter SUHI (∆T Day, ∆TNight ) black dot -the location of the WMO station. 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 11 Connecting Local and Global Scales: Urban Arctic climate is a harbinger of future Arctic warming «Swimming resort» in Norilsk – Winter season future temperatures − RCP8.5 world`s northernmost large city for the Arctic (60–90°N) − RCP4.5 69°20′N 88°13′E • 40% to 80% of infrastructure in the Arctic cities has been already damaged • Soil bearing capacity has decreased by 30% D. Streletsky and N. Shiklomanov (2016) in Earth’s Cryosphere 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 12 Connecting Local and Global Scales: Climate Analogues North West Siberian cities already have climate found ~600 km south Fitzpatrick, M. C., & Dunn, R. R. (n.d.). American urban areas in the late 21st century. Nature Communications, (2019), 1–7. https://doi.org/10.1038/s41467-019- 08540-3 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 13 Potential drivers for the surface UHI • Meteorological drivers: • Background temperature • Atmospheric stability • Continentality of climate • Cloudiness • Land use – land cover (LULC) factors – exogenous • LULC type features: NDVI, albedo, soil moisture etc. • LULC type relative abundance and diversity (the Shannon index) • Socio-economic factors – endogenous • Urban area extent • Urban LULC type features • Urban metabolism: Population density, AHF per capita 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 14 Exogenous LULC drivers: Example of Pokachy Example of the Pokachy city polygon and 2-km buffer polygon. Urban pixels were allocated to the city polygon and surrounding land in a 2- km buffer was considered as rural. The buffer polygon combined different land cover (LC) polygons. The land cover was extracted from LC CCI raster and converted to polygons. LC CCI original classes were joined into 9 new classes. The numbers represent mean LST for different LC classes in the buffer. The upper numbers are summer LST and the lower numbers are winter LST. 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 15 Exogenous LULC drivers: All 28 Siberian cities 12 Summer 8 c l ΔTT 4 0 -4 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.1 0.2 0 0.2 0.4 0 0.2 Woodland Spare Cropland Grassland Shrubland Wetland Bare land Water Artificial vegetation bodies land 6 Winter 4 2 c l 0 T ΔT -2 0 0.4 0.8 0 0.4 0.8 0 0.4 0.8 0 0.2 0.4 0 0.4 0.8 0 0.4 0.8 0 0.1 0.2 0 0.2 0.4 0 0.2 Woodland -4 Spare Cropland Grassland Shrubland Wetland Bare land Water Artificial vegetation bodies land -6 LULC fraction within 2 km buffer 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 16 Endogenous drivers: All 28 Siberian cities (a) Summer (a) Summer (b) Winter (b) Winter Area Area Area AreaT rw ΔTw SHEI log(P) Trs ΔTs SHEI Trs log(P)ΔT s SHEI log(P) Trw ΔTw SH2 EI log(P) km2 km2 km km2 |ϕ| –0,63 –0,39 0,47 –0,62 –0.36 |ϕ| –0,93 –0,77|ϕ| 0,44–0 ,93 –0–,630,7 7 –0,308,44 –0,63 –0,38 |ϕ| –0,63 –0,39 0,47 –0,62 –0.36 Trw 0.15Tr w –0.28 0.350.15 0.0–10.28 0.35 0.01 Trs 0,73 Trs –0,44 0,670,7 3 0,40–0,4 4 0,67 0,40 ΔTw –0,52 0,82 0,64 ΔTw –0,52 0,82 0,64 ΔTs ΔTs –0.25 0,81 0,50–0.2 5 0,81 0,50 SHEI SH EI –0,45 –0.32 –0,45 –0.32 SEI SEI –0.36 –0.30 –0.36 –0.30 log(P) log(P) 0,61 log(P) 0,61 log(P) 0,60 0,60 1 1 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 17 MODIS LST summer (JJA) Conclusions • Northern cities reveal large UHI (SUHI) • Related to the heat trapping in stably-stratified PBL • Temporal and spatial patterns are diverse • Northern UHIs might have a pronounced socio- environmental impact MODIS LST winter (DJF) • Driving/scalng factors: • Population is the most important • City area and density are less influential • Counterintuitive – Urban green spaces induce warming (not cooling) effects – subject of studies in the Belmont Forum project SERUS (Nansen Center in Norway, George Washington University in USA, Tyumen State University in Russia) The role of local green space and small-scale relief in cold climate cities: Khanty-Mansiysk 16.09.2020 ENVIROMIS - 2020, 7-11 Sept. 18.
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