Development of moderate-resolution gridded monthly air temperature and degree-day maps for the Labrador-Ungava region of northern Canada

Way, Robert G.; Lewkowicz, Antoni G.; Bonnaventure, Philip P.

doi:10.1002/joc.4721

Cited by 24 publications

(24 citation statements)

References 67 publications

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“…Labrador has an area of 294 000 km 2 and contains the highest mountains in continental eastern Canada (Torngat Mountains) and the southernmost limits of the Arctic climate region in Canada . Mean annual air temperatures vary from + 1.5 to −9°C and annual temperature amplitudes (AT; July mean minus January mean) vary from 22°C near the coast to 45°C in the interior . Approximately 60% of Labrador is forested (typically black spruce, white spruce, tamarack and birch) while nearly 30% consists of alpine tundra, high sub‐Arctic tundra or low Arctic tundra .…”

Section: Study Areamentioning

confidence: 99%

“…22 Mean annual air temperatures vary from + 1.5 to −9°C and annual temperature amplitudes (AT; July mean minus January mean) vary from 22°C near the coast to 45°C in the interior. 23 Approximately 60% of Labrador is forested (typically black spruce, white spruce, tamarack and birch) while nearly 30% consists of alpine tundra, high sub-Arctic tundra or low Arctic tundra. 24 The remaining area is evenly divided between coastal barrens and wetlands.…”

Section: Study Areamentioning

confidence: 99%

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Environmental controls on ground temperature and permafrost in Labrador, northeast Canada

Way

Lewkowicz

2018

Permafrost & Periglacial

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Field data from 83 environmental monitoring stations across Labrador, 17 with permafrost, were used to analyze the interrelationships of key variables considered in the temperature at the top of permafrost model. Snow depth, not mean annual air temperature, was the strongest climatic determinant of mean temperatures at the ground surface and at the base of the annual freeze–thaw layer, and its variability was most closely related to land cover class. A critical late‐winter snow depth of 70 cm or more was inferred to be sufficient to prevent the formation of permafrost at the monitoring sites, which meant that permafrost was absent beneath forest but present in some tundra, peatland and bedrock locations. Analyses showed no statistically significant relations identified between topographic indices and various station parameters, challenging their utility for regional modeling. Testing of several different land cover datasets for model parameterization gave errors in ground surface temperature ranging from ± 0.9 to 2.1°C. These results highlight the importance of local field data and emphasize the necessity of high‐quality national‐scale land cover datasets suitable for permafrost modeling.

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Section: Study Areamentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

Environmental controls on ground temperature and permafrost in Labrador, northeast Canada

Way

Lewkowicz

2018

Permafrost & Periglacial

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“…The existing research on meteorological factor interpolation adopts different methods-Kriging and IDW (Inverse Distance Weighted) [11,40] for relative humidity, Kriging and IDW [11,32] for precipitation., and TPS (Thin Plate Spline) and Kriging [40,41] for air temperature. Considering that the spatial distribution was significantly different in relative humidity, precipitation, and air temperature, and air temperature had a certain degree of altitude sensitivity [40][41][42], on the basis of the previous study method, after being tested by comparing meteorological site data and other methods, IDW was selected to interpolate the relative humidity, and Kriging to interpolate the precipitation. TPS was selected and DEM acted as the covariate to assist spatial interpolation of air temperature data.…”

Section: Spatial Interpolation Of Meteorological Datamentioning

confidence: 99%

Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China

Zhang

et al. 2018

Remote Sensing

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Abstract:The Inner Mongolia Autonomous Region (IMAR) is a major source of rivers, catchment areas, and ecological barriers in the northeast of China, related to the nation's ecological security and improvement of the ecological environment. Therefore, studying the response of vegetation to climate change has become an important part of current global change research. Since existing studies lack detailed descriptions of the response of vegetation to different climatic factors using the method of grey correlation analysis based on pixel, the temporal and spatial patterns and trends of enhanced vegetation index (EVI) are analyzed in the growing season in IMAR from 2000 to 2015 based on moderate resolution imaging spectroradiometer (MODIS) EVI data. Combined with the data of air temperature, relative humidity, and precipitation in the study area, the grey relational analysis (GRA) method is used to study the time lag of EVI to climate change, and the study area is finally zoned into different parts according to the driving climatic factors for EVI on the basis of lag analysis. The driving zones quantitatively show the characteristics of temporal and spatial differences in response to different climatic factors for EVI. The results show that: (1) The value of EVI generally features in spatial distribution, increasing from the west to the east and the south to the north. The rate of change is 0.22/10 • E from the west to the east, 0.28/10 • N from the south to the north; (2) During 2000-2015, the EVI in IMAR showed a slightly upward trend with a growth rate of 0.021/10a. Among them, the areas with slight and significant improvement accounted for 21.1% and 7.5% of the total area respectively, ones with slight and significant degradation being 24.6% and 4.3%; (3) The time lag analysis of climatic factors for EVI indicates that vegetation growth in the study area lags behind air temperature by 1-2 months, relative humidity by 1-2 months, and precipitation by one month respectively; (4) During the growing season, the EVI of precipitation driving zone (21.8%) in IMAR is much larger than that in the air temperature driving zone (8%) and the relative humidity driving zone (11.6%). The growth of vegetation in IMAR generally has the closest relationship with precipitation. The growth of vegetation does not depend on the change of a single climatic factor. Instead, it is the result of the combined action of multiple climatic factors and human activities.

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“…They suggest that care should be taken in using these gridded products in local-or regionalscale applications. Additionally, Way et al (2017) recently showed that data taken from a new land-only product developed within the Berkeley Earth Surface Temperatures (BEST) project (Rohde et al 2013), and which were not used by Rapaić et al (2015), reveal an underestimation of recent warming in northern Canada when compared against data taken from the Adjusted and Homogenized Canadian Climate Dataset (ADHCCD) developed by Environment Canada. They also stated that automated station adjustment algorithms reduce air temperature changes in this region and are sensitive to declines in the long-term observing network.…”

Section: Introductionmentioning

confidence: 99%

Air temperature changes in the Arctic in the period 1951–2015 in the light of observational and reanalysis data

Przybylak

Wyszyński

2019

Theor Appl Climatol

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Recent air temperature changes in the high Arctic (HA) have been investigated based on mean seasonal and annual data calculated for the period 1951-2015 and for two sub-periods 1976-2015 and 1996-2015. Two kinds of air temperature data (observational and reanalysis) have been used in the research. The observational data were compared with data taken from six reanalysis products (20CRv2c, CERA-20C, ERA-Int, MERRA-2, NCEP-CFSRR, JRA-55). The scale of the HAwarming for the period 1996-2015 relative to the reference period 1951-1990 reached 1.6°C for annual mean and was greatest in autumn (1.9°C) and in winter (1.7°C), while it was smallest in summer (0.9°C). Evidently, the greatest warming was observed in the Atlantic and Siberian climatic regions, while in the rest of the HA, the rate of warming was usually weaker than trends calculated for the period 1976-2015. Air temperature tendencies in all study periods 1951-2015, 1976-2015 and 1996-2015 showed a predominance of positive trends that were statistically significant at the level of 0.05. In the two latter periods, the rate of warming was on average 2-3 times faster than for the entire study period. In the HA, there has not been a slowdown in the rate of warming ("hiatus") in the last two decades (in contrast to that which was noted for the Northern Hemisphere). Our results reveal that, in most cases, the closest fit to observations was obtained for two reanalysis products (the ERA-Interim and JRA-55, since 1979) and the six reanalysis average. Two new polar amplification (PA) metrics based on scaled and standardised values of surface air temperature (SAT) reveal the non-existence of this phenomenon in the period 1951-2015. One of the metrics shows very small

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Development of moderate-resolution gridded monthly air temperature and degree-day maps for the Labrador-Ungava region of northern Canada

Cited by 24 publications

References 67 publications

Environmental controls on ground temperature and permafrost in Labrador, northeast Canada

Environmental controls on ground temperature and permafrost in Labrador, northeast Canada

Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China

Air temperature changes in the Arctic in the period 1951–2015 in the light of observational and reanalysis data

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