Remote Sensing of Local Warming Trend in Alberta, Canada during 2001-2020, and Its Relationship with Large-Scale Atmospheric Circulations

Here, the objective was to study the local warming trend and its driving factors in the natural subregions of Alberta using a remote-sensing approach. We applied the Mann–Kendall test and Sen’s slope estimator on the day and nighttime MODIS LST time-series images to map and quantify the extent and magnitude of monthly and annual warming trends in the 21 natural subregions of Alberta. We also performed a correlation analysis of LST anomalies (both day and nighttime) of the subregions with the anomalies of the teleconnection patterns, i.e., Pacific North American (PNA), Pacific decadal oscillation (PDO), Arctic oscillation (AO), and sea surface temperature (SST, Niño 3.4 region) indices, to identify the relationship. May was the month that showed the most significant warming trends for both day and night during 2001–2020 in most of the subregions in the Rocky Mountains and Boreal Forest. Subregions of Grassland and Parkland in southern and southeastern parts of Alberta showed trends of cooling during daytime in July and August and a small magnitude of warming in June and August at night. We also found a significant cooling trend in November for both day and night. We identified from the correlation analysis that the PNA pattern had the most influence in the subregions during February to April and October to December for 2001–2020; however, none of the atmospheric oscillations showed any significant relationship with the significant warming/cooling months.

[1]  Cristian Mattar,et al.  Warming trends in Patagonian subantartic forest , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[2]  H. B. Mann Nonparametric Tests Against Trend , 1945 .

[3]  Julia Boike,et al.  Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes , 2014 .

[4]  Marek Nawalany,et al.  Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland , 2018, Water.

[5]  Maduako N. Ikechukwu,et al.  Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study , 2017 .

[6]  R. Ahas,et al.  Onset of spring starting earlier across the Northern Hemisphere , 2006 .

[7]  Zhaoqi Wang,et al.  Spatiotemporal Variation of Land Surface Temperature and Vegetation in Response to Climate Change Based on NOAA-AVHRR Data over China , 2020, Sustainability.

[8]  Jaime Aguilar-Lome,et al.  Elevation-dependent warming of land surface temperatures in the Andes assessed using MODIS LST time series (2000-2017) , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[9]  Lixin Wu,et al.  Pacific-North American teleconnection and North Pacific Oscillation: historical simulation and future projection in CMIP5 models , 2018, Climate Dynamics.

[10]  Ashraf Dewan,et al.  Use of Remote Sensing in Comprehending the Influence of Urban Landscape's Composition and Configuration on Land Surface Temperature at Neighbourhood Scale , 2020, Remote. Sens..

[11]  H. Fowler,et al.  Elevation-dependent warming in mountain regions of the world , 2015 .

[12]  José A. Sobrino,et al.  Spatial and temporal patterns of the recent warming of the Amazon forest , 2013 .

[13]  M. H. Nokhandan,et al.  Using Mann Kendal and t-test methods in identifying trends of climatic elements: A case study of northern parts of Iran , 2012 .

[14]  Muhammad Dawood,et al.  Spatio-statistical analysis of temperature fluctuation using Mann–Kendall and Sen’s slope approach , 2017, Climate Dynamics.

[15]  Quazi K. Hassan,et al.  Introducing a New Remote Sensing-Based Model for Forecasting Forest Fire Danger Conditions at a Four-Day Scale , 2019, Remote. Sens..

[16]  Yuanzheng Li,et al.  Monitoring the Interannual Spatiotemporal Changes in the Land Surface Thermal Environment in Both Urban and Rural Regions from 2003 to 2013 in China Based on Remote Sensing , 2019, Advances in Meteorology.

[17]  Donald H. Burn,et al.  Climatic influences on streamflow timing in the headwaters of the Mackenzie River Basin , 2008 .

[18]  The nonlinear association between the Arctic Oscillation and North American winter climate , 2006 .

[19]  J. Orwin,et al.  Spatial and Temporal Shifts in Historic and Future Temperature and Precipitation Patterns Related to Snow Accumulation and Melt Regimes in Alberta, Canada , 2021, Water.

[20]  A. Anda,et al.  Comparison of parametric and non-parametric time-series analysis methods on a long-term meteorological data set , 2017 .

[21]  Quazi K. Hassan,et al.  Quantification of Local Warming Trend: A Remote Sensing-Based Approach , 2017, PloS one.

[22]  M. Gocić,et al.  Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia , 2013 .

[23]  J. Dozier,et al.  Driving forces of land surface temperature anomalous changes in North America in 2002–2018 , 2020, Scientific Reports.

[24]  R. Barry,et al.  Processes and impacts of Arctic amplification: A research synthesis , 2011 .

[25]  Jianping Huang,et al.  Evolution of land surface air temperature trend , 2014 .

[26]  Ninglian Wang,et al.  Variations in Winter Surface Temperature of the Purog Kangri Ice Field, Qinghai-Tibetan Plateau, 2001-2018, Using MODIS Data , 2020, Remote. Sens..

[27]  J. Miller,et al.  Climate change in mountains: a review of elevation-dependent warming and its possible causes , 2012, Climatic Change.

[28]  Xiaoyi Guo,et al.  Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology , 2019, Remote. Sens..

[29]  Shuwen Zhang,et al.  Land Surface Temperature Response to Irrigated Paddy Field Expansion: a Case Study of Semi-arid Western Jilin Province, China , 2019, Scientific Reports.

[30]  Yaoming Ma,et al.  Spatial and temporal variation of daytime and nighttime MODIS land surface temperature across Nepal , 2019, Atmospheric and Oceanic Science Letters.

[31]  Amir Shabbar,et al.  The impact of el Nino‐Southern oscillation on the temperature field over Canada: Research note , 1996 .

[32]  P. Sen Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[33]  R. Forthofer,et al.  Rank Correlation Methods , 1981 .

[34]  Abdul Razzaq Ghumman,et al.  Impact Assessment of Rainfall-Runoff Simulations on the Flow Duration Curve of the Upper Indus River—A Comparison of Data-Driven and Hydrologic Models , 2018, Water.

[35]  Darrell S. Kaufman,et al.  Mid-latitude net precipitation decreased with Arctic warming during the Holocene , 2019, Nature.

[36]  M. Ek,et al.  Influence of thermodynamic soil and vegetation parameterizations on the simulation of soil temperature states and surface fluxes by the Noah LSM over a Tibetan plateau site , 2009 .

[37]  Xin Huang,et al.  Irrigation cooling effect on land surface temperature across China based on satellite observations. , 2019, The Science of the total environment.

[38]  Barrie R. Bonsal,et al.  Impacts of low frequency variability modes on Canadian winter temperature , 2001 .

[39]  P. Shit,et al.  Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC) , 2016 .

[40]  Chris Huntingford,et al.  Amazon Basin climate under global warming: the role of the sea surface temperature , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[41]  Dorothy K. Hall,et al.  Greenland ice sheet surface temperature, melt and mass loss: 2000–06 , 2008, Journal of Glaciology.

[42]  Quazi K. Hassan,et al.  Investigative Spatial Distribution and Modelling of Existing and Future Urban Land Changes and Its Impact on Urbanization and Economy , 2019, Remote. Sens..