Near tropopause discrepancy in air temperature during the YOPP special observing period

The Tenth Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Wed. 4 Dec. / Entrance Hall (1st floor) , National Institute of Polar Researc

Variability and climate sensitivity of fast ice extent in the north-eastern Kara Sea

This work investigates the temporal and spatial variation of shore-fast ice extent in the north-eastern part of the Kara Sea during 1953–1990 and its sensitivity to interannual variability of the regional climate. The area of fast ice in spring months shows a bimodal distribution. This indicates the existence of two different regimes of fast ice formation driven by the system of prevailing winds. The westward wind transport during the cold season gives larger fast ice extent while the eastward wind transport suppresses the expansion of fast ice. There is a significant correlation (ca. –0.55) between the average winter temperature and the area of fast ice. Linear trends for time records of shore-fast ice area in spring show a decrease during 1953–1990. This decrease is most pronounced in April: the mean fast ice area in April is 12 % lower in 1988–1990 compared to 1953–55. A comparison of fast ice regimes for two particular years— 1979 and 1985—revealed a significant influence of cyclone activity on fast ice development over the course of the cold season. It is shown that partial break-ups of fast ice in spring 1985 are associated with the passage of cyclones across the area of fast ice

Assessment of Atmospheric Reanalyses with Independent Observations in the Weddell Sea, the Antarctic

Surface layer and upper-air in situ observations from two research vessel cruises and an ice station in the Weddell Sea from 1992 and 1996 are used to validate four current atmospheric reanalysis products: ERA-Interim, CFSR, JRA-55, and MERRA-2. Three of the observation data sets were not available for assimilation, providing a rare opportunity to validate the reanalyses in the otherwise datasparse region of the Antarctic against independent data. All four reanalyses produce 2 m temperatures warmer than the observations, and the biases vary from +2.0 K in CFSR to +2.8 K in MERRA-2. All four reanalyses are generally too warm also higher up in the atmospheric boundary layer (ABL), with biases up to +1.4 K (ERA-Interim). Cloud fractions are relatively poorly reproduced by the reanalyses, MERRA-2 and JRA-55 having the strongest positive and negative biases of about +30 % and -17 %, respectively. Skill scores of the error statistics reveal that ERA-Interim compares generally the most favorably against both the surface layer and the upper-air observations. CFSR compares the second best and JRA-55 and MERRA-2 have the least favorable scores. The ABL warm bias is consistent with previous evaluation studies in high latitudes, where more recent observations have been applied. As the amount of observations has varied depending on the decade, season, and region, the consistency of the warm bias suggests a need to improve the modeling systems, including data assimilation as well as ABL and surface parameterizations.Peer reviewe

Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM

Assessment of Atmospheric Reanalyses With Independent Observations in the Weddell Sea, the Antarctic

Surface layer and upper‐air in situ observations from two research vessel cruises and an ice station in the Weddell Sea from 1992 and 1996 are used to validate four current atmospheric reanalysis products: ERA‐Interim, CFSR, JRA‐55, and MERRA‐2. Three of the observation data sets were not available for assimilation, providing a rare opportunity to validate the reanalyses in the otherwise datasparse region of the Antarctic against independent data. All four reanalyses produce 2 m temperatures warmer than the observations, and the biases vary from +2.0 K in CFSR to +2.8 K in MERRA‐2. All four reanalyses are generally too warm also higher up in the atmospheric boundary layer (ABL), with biases up to +1.4 K (ERA‐Interim). Cloud fractions are relatively poorly reproduced by the reanalyses, MERRA‐2 and JRA‐55 having the strongest positive and negative biases of about +30 % and −17 %, respectively. Skill scores of the error statistics reveal that ERA‐Interim compares generally the most favorably against both the surface layer and the upper‐air observations. CFSR compares the second best and JRA‐55 and MERRA‐2 have the least favorable scores. The ABL warm bias is consistent with previous evaluation studies in high latitudes, where more recent observations have been applied. As the amount of observations has varied depending on the decade, season, and region, the consistency of the warm bias suggests a need to improve the modeling systems, including data assimilation as well as ABL and surface parameterizations.publishedVersio

Atmospheric-driven state transfer of shore-fast ice in the northeastern Kara Sea

Frequencies of observed occurrences of shore-fast ice in the northeastern Kara Sea for each month during 1953–1990 reveal a multimodality of shore-fast ice extent in late winter and spring. The fast ice extent exhibits mainly three different configurations (modes) associated with the regional topography of coasts and islands. These modes show fast ice areas equal to approximately 98 ± 6, 122 ± 6, and 136 ± 8 1000 km2. Analysis of the time series of fast ice extent shows that favorable conditions for expansion of fast ice seaward in winter and spring are met if the atmospheric circulation over the northeastern Kara Sea is controlled by the Arctic high, resulting in offshore winds and a significant (up to 6ºC) decrease of the monthly mean surface air temperature. In contrast, the penetration of the Icelandic low into the Kara Sea, accompanied by Arctic cyclones coming from the west, is responsible for the partial breakup and decrease of fast ice extent in winter or spring

Variation in CO2 and CH4 fluxes among land cover types in heterogeneous Arctic tundra in northeastern Siberia

Arctic tundra is facing unprecedented warming, resulting in shifts in the vegetation, thaw regimes, and potentially in the ecosystem-atmosphere exchange of carbon (C). However, the estimates of regional carbon dioxide (CO2) and methane (CH4) budgets are highly uncertain. We measured CO2 and CH4 fluxes, vegetation composition and leaf area index (LAI), thaw depth, and soil wetness in Tiksi (71 degrees N, 128 degrees E), a heterogeneous site located within the prostrate dwarf-shrub tundra zone in northeastern Siberia. Using the closed chamber method, we determined the net ecosystem exchange (NEE) of CO2, ecosystem respiration in the dark (ER), ecosystem gross photosynthesis (Pg), and CH4 flux during the growing season. We applied a previously developed high-spatial-resolution land cover map over an area of 35.8 km(2) for spatial extrapolation. Among the land cover types varying from barren to dwarf-shrub tundra and tundra wetlands, the NEE and Pg at the photosynthetically active photon flux density of 800 mu mol m(-2) h(-1) (NEE800 and Pg(800)) were greatest in the graminoid-dominated habitats, i.e., streamside meadow and fens, with NEE800 and Pg(800) of up to -21 (uptake) and 28 mmol M-2 h(-1), respectively. Vascular LAI was a robust predictor of both NEE800 and Pg(800) and, on a landscape scale, the fens were disproportionately important for the summertime CO2 sequestration. Dry tun- dra, including the dwarf-shrub and lichen tundra, had smaller CO2 exchange rates. The fens were the largest source of CH4, while the dry mineral soil tundra consumed atmospheric CH4, which on a landscape scale amounted to -9 % of the total CH(4 )balance during the growing season. The largest seasonal mean CH4 consumption rate of 0.02 mmol m(-2) h(-1) occurred in sand- and stone-covered barren areas. The high consumption rate agrees with the estimate based on the eddy covariance measurements at the same site. We acknowledge the uncertainty involved in spatial extrapolations due to a small number of replicates per land cover type. This study highlights the need to distinguish different land cover types including the dry tundra habitats to account for their different CO2 and CH4 flux patterns, especially the consumption of atmospheric CH4, when estimating tundra C exchange on a larger spatial scale.Peer reviewe

On Aethalometer measurement uncertainties and an instrument correction factor for the Arctic

Several types of filter-based instruments are used to estimate aerosol light absorption coefficients. Two significant results are presented based on Aethalometer measurements at six Arctic stations from 2012 to 2014. First, an alternative method of post-processing the Aethalometer data is presented, which reduces measurement noise and lowers the detection limit of the instrument more effectively than box-car averaging. The biggest benefit of this approach can be achieved if instrument drift is minimised. Moreover, by using an attenuation threshold criterion for data post-processing, the relative uncertainty from the electronic noise of the instrument is kept constant. This approach results in a time series with a variable collection time (Delta t) but with a constant relative uncertainty with regard to electronic noise in the instrument. An additional advantage of this method is that the detection limit of the instrument will be lowered at small aerosol concentrations at the expense of temporal resolution, whereas there is little to no loss in temporal resolution at high aerosol concentrations (>2.1-6.7Mm(-1) as measured by the Aethalometers). At high aerosol concentrations, minimising the detection limit of the instrument is less critical. Additionally, utilising co-located filter-based absorption photometers, a correction factor is presented for the Arctic that can be used in Aethalometer corrections available in literature. The correction factor of 3.45 was calculated for low-elevation Arctic stations. This correction factor harmonises Aethalometer attenuation coefficients with light absorption coefficients as measured by the co-located light absorption photometers. Using one correction factor for Arctic Aethalometers has the advantage that measurements between stations become more inter-comparable.Peer reviewe