Climatological characteristics of Arctic and Antarctic surface-based inversions
Surface-based inversions (SBIs) are frequent features of the Arctic and Antarctic atmospheric boundary layer. They influence vertical mixing of energy, moisture and pollutants, cloud formation, and surface ozone destruction. Their climatic variability is related to that of sea ice and planetary albe...
| Main Authors: | , , , , , |
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| Format: | Text |
| Language: | English |
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.9526 http://www.cgd.ucar.edu/staff/cdeser/docs/zhang.polar_sfcinversions.jclim11.pdf |
| Summary: | Surface-based inversions (SBIs) are frequent features of the Arctic and Antarctic atmospheric boundary layer. They influence vertical mixing of energy, moisture and pollutants, cloud formation, and surface ozone destruction. Their climatic variability is related to that of sea ice and planetary albedo, important factors in climate feedback mechanisms. However, climatological polar SBI properties have not been fully characterized nor have climate model simulations of SBIs been compared comprehensively to observations. Using 20 years of twice-daily observations from 39 Arctic and 6 Antarctic radiosonde stations, this study examines the spatial and temporal variability of three SBI characteristic—frequency of occurrence, depth (from the surface to the inversion top), and intensity (temperature difference over the SBI depth)—and relationships among them. In both polar regions, SBIs are more frequent, deeper, and stronger in winter and autumn than in summer and spring. In the Arctic, these tendencies increase from the Norwegian Sea eastward toward the East Siberian Sea, associated both with (seasonal and diurnal) variations in solar elevation angle at the standard radiosonde observation times and with differences between continental and maritime climates. Two state-of-the-art climate models and one reanalysis dataset show similar seasonal patterns and spatial distributions of SBI properties as the radiosonde observations, but with biases in their magnitudes that differ among the models and that are smaller in winter and autumn than in spring and summer. SBI frequency, depth, and intensity are positively correlated, both spatially and temporally, and all three are anticorrelated with surface temperature. 1. |
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