Dataset Information

Global Warming Threshold and Mechanisms for Accelerated Greenland Ice Sheet Surface Mass Loss.

ABSTRACT: The Community Earth System Model version 2.1 (CESM2.1) is used to investigate the evolution of the Greenland ice sheet (GrIS) surface mass balance (SMB) under an idealized CO2 forcing scenario of 1% increase until stabilization at 4× pre-industrial at model year 140. In this simulation, the SMB calculation is coupled with the atmospheric model, using a physically based surface energy balance scheme for melt, explicit calculation of snow albedo, and a realistic treatment of polar snow and firn compaction. By the end of the simulation (years 131-150), the SMB decreases with 994?Gt?yr-1 with respect to the pre-industrial SMB, which represents a sea-level rise contribution of 2.8?mm?yr-1. For a threshold of 2.7-K global temperature increase with respect to pre-industrial, the rate of expansion of the ablation area increases, the mass loss accelerates due to loss of refreezing capacity and accelerated melt, and the SMB becomes negative 6?years later. Before acceleration, longwave radiation is the most important contributor to increasing energy for melt. After acceleration, the large expansion of the ablation area strongly reduces surface albedo. This and much increased turbulent heat fluxes as the GrIS-integrated summer surface temperature approaches melt point become the major sources of energy for melt.

SUBMITTER: Sellevold R

PROVIDER: S-EPMC7540049 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Global Warming Threshold and Mechanisms for Accelerated Greenland Ice Sheet Surface Mass Loss.

Sellevold Raymond R Vizcaíno Miren M

Journal of advances in modeling earth systems 20200909 9

The Community Earth System Model version 2.1 (CESM2.1) is used to investigate the evolution of the Greenland ice sheet (GrIS) surface mass balance (SMB) under an idealized CO<sub>2</sub> forcing scenario of 1% increase until stabilization at 4× pre-industrial at model year 140. In this simulation, the SMB calculation is coupled with the atmospheric model, using a physically based surface energy balance scheme for melt, explicit calculation of snow albedo, and a realistic treatment of polar snow ...[more]

PMID: 33042389

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Project description:Measuring microbial abundance in glacier ice and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier ice samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the Greenland Ice Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier ice and tested the three methods on artificial ice samples of realistic cell (10(2)-10(7) cells ml(-1)) and mineral particle (0.1-100 mg ml(-1)) concentrations, simulating a range of glacial ice types, from clean subsurface ice to surface ice to sediment-laden basal ice. We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the ice sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of ice containing dust. Cell numbers in surface ice samples, determined by EFM, ranged from ~ 2 × 10(3) to ~ 2 × 10(6) cells ml(-1) while dust concentrations ranged from 0.01 to 2 mg ml(-1). The lowest abundances were found in ice sampled from the accumulation area of the ice sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the ice sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS.

Dataset Information

Global Warming Threshold and Mechanisms for Accelerated Greenland Ice Sheet Surface Mass Loss.

Publications

Global Warming Threshold and Mechanisms for Accelerated Greenland Ice Sheet Surface Mass Loss.

Similar Datasets

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