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- Author or Editor: Julienne Stroeve x
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Abstract
Atmospheric data from the Atmospheric Infrared Sounder (AIRS) were used to study an extreme warm and humid air mass transported over the Barents–Kara Seas region by an Arctic cyclone at the end of December 2015. Temperature and humidity in the region was ~10°C (>3σ above the 2003–14 mean) warmer and ~1.4 g kg−1 (>4σ above the 2003–14 mean) wetter than normal during the peak of this event. This anomalous air mass resulted in a large and positive flux of energy into the surface via the residual of the surface energy balance (SEB), compared to the weakly negative SEB from the surface to the atmosphere expected for that time of year. The magnitude of the downwelling longwave radiation during the event was unprecedented compared to all other events detected by AIRS in December/January since 2003. An approximate budget scaling suggests that this anomalous SEB could have resulted in up to 10 cm of ice melt. Thinning of the ice pack in the region was supported by remotely sensed and modeled estimates of ice thickness change. Understanding the impact of this anomalous air mass on a thinner, weakened sea ice state is imperative for understanding future sea ice–atmosphere interactions in a warming Arctic.
Abstract
Atmospheric data from the Atmospheric Infrared Sounder (AIRS) were used to study an extreme warm and humid air mass transported over the Barents–Kara Seas region by an Arctic cyclone at the end of December 2015. Temperature and humidity in the region was ~10°C (>3σ above the 2003–14 mean) warmer and ~1.4 g kg−1 (>4σ above the 2003–14 mean) wetter than normal during the peak of this event. This anomalous air mass resulted in a large and positive flux of energy into the surface via the residual of the surface energy balance (SEB), compared to the weakly negative SEB from the surface to the atmosphere expected for that time of year. The magnitude of the downwelling longwave radiation during the event was unprecedented compared to all other events detected by AIRS in December/January since 2003. An approximate budget scaling suggests that this anomalous SEB could have resulted in up to 10 cm of ice melt. Thinning of the ice pack in the region was supported by remotely sensed and modeled estimates of ice thickness change. Understanding the impact of this anomalous air mass on a thinner, weakened sea ice state is imperative for understanding future sea ice–atmosphere interactions in a warming Arctic.
Abstract
Lagrangian detection and tracking algorithms are frequently used to study the development, distribution, and trends of extratropical cyclones. Past research shows that results from these algorithms are sensitive to both spatial and temporal resolutions of the gridded input fields, with coarser resolutions typically underestimating cyclone frequency by failing to capture weak, small, and short-lived systems. The fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5) offers finer resolution, and, therefore, more precise information regarding storm locations and development than previous global reanalyses. However, our sensitivity tests show that using ERA5 sea level pressure fields at their finest-possible resolution does not necessarily lead to better cyclone detection and tracking. If a common number of nearest neighbors is used when detecting minima in sea level pressure (like past studies), finer spatial resolution leads to noisier fields that unrealistically break up multicenter cyclones. Using a common search distance instead (with more neighbors at finer resolution) resolves the issue without smoothing inputs. Doing this also makes cyclone frequency, life span, and average depth insensitive to refining spatial resolution beyond 100 km. Results using 6- and 3-h temporal resolutions have only minor differences, but using 1-h temporal resolution with a maximum allowed propagation speed of 150 km h−1 leads to unrealistic track splitting. This can be counteracted by increasing the maximum propagation speed, but modest sensitivity to temporal resolution persists for several cyclone characteristics. Therefore, we recommend caution if applying existing algorithms to temporal resolutions finer than 3 h and careful evaluation of algorithm settings.
Abstract
Lagrangian detection and tracking algorithms are frequently used to study the development, distribution, and trends of extratropical cyclones. Past research shows that results from these algorithms are sensitive to both spatial and temporal resolutions of the gridded input fields, with coarser resolutions typically underestimating cyclone frequency by failing to capture weak, small, and short-lived systems. The fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5) offers finer resolution, and, therefore, more precise information regarding storm locations and development than previous global reanalyses. However, our sensitivity tests show that using ERA5 sea level pressure fields at their finest-possible resolution does not necessarily lead to better cyclone detection and tracking. If a common number of nearest neighbors is used when detecting minima in sea level pressure (like past studies), finer spatial resolution leads to noisier fields that unrealistically break up multicenter cyclones. Using a common search distance instead (with more neighbors at finer resolution) resolves the issue without smoothing inputs. Doing this also makes cyclone frequency, life span, and average depth insensitive to refining spatial resolution beyond 100 km. Results using 6- and 3-h temporal resolutions have only minor differences, but using 1-h temporal resolution with a maximum allowed propagation speed of 150 km h−1 leads to unrealistic track splitting. This can be counteracted by increasing the maximum propagation speed, but modest sensitivity to temporal resolution persists for several cyclone characteristics. Therefore, we recommend caution if applying existing algorithms to temporal resolutions finer than 3 h and careful evaluation of algorithm settings.
