scholarly journals Seasonal clear-sky flux and cloud radiative effect anomalies in the Arctic atmospheric column associated with the Arctic Oscillation and Arctic Dipole

2017 ◽  
Author(s):  
Bradley M. Hegyi ◽  
Patrick C. Taylor
Keyword(s):  
Arctic Oscillation ◽  
The Arctic ◽  
Radiative Effect ◽  
Clear Sky ◽  
Atmospheric Column ◽  
Cloud Radiative Effect ◽  
The Arctic Oscillation

scholarly journals Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations

2020 ◽  
Vol 59 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Kerstin Ebell ◽  
Tatiana Nomokonova ◽  
Marion Maturilli ◽  
Christoph Ritter
Keyword(s):  
Remote Sensing ◽  
The Arctic ◽  
Radiative Effect ◽  
Liquid Water Path ◽  
Ice Clouds ◽  
Surface Warming ◽  
Clear Sky ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
The Difference

AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.

scholarly journals Volcanic activity sparks the Arctic Oscillation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weizheng Qu ◽  
Fei Huang ◽  
Jinping Zhao ◽  
Ling Du ◽  
Yong Cao
Keyword(s):  
Volcanic Activity ◽  
Volcanic Eruption ◽  
Arctic Oscillation ◽  
Polar Vortex ◽  
Volcanic Eruptions ◽  
The Arctic ◽  
Vortex System ◽  
Significant Fluctuation ◽  
The Arctic Oscillation

AbstractThe parasol effect of volcanic dust and aerosol caused by volcanic eruption results in the deepening and strengthening of the Arctic vortex system, thus stimulating or strengthening the Arctic Oscillation (AO). Three of the strongest AOs in more than a century have been linked to volcanic eruptions. Every significant fluctuation of the AO index (AOI = ΔH_middle latitudes − ΔH_Arctic) for many years has been associated with a volcanic eruption. Volcanic activity occurring at different locations in the Arctic vortex circulation will exert different effects on the polar vortex.

Climate Extremes of the 2019/2020 Winter in Northern Eurasia: Contributions by the Climate Trend and Interannual Variability Related to the Arctic Oscillation

2021 ◽  
pp. 5-16
Author(s):  
V. N. Kryjov ◽  
Keyword(s):  
Interannual Variability ◽  
Arctic Oscillation ◽  
Global Climate ◽  
Linear Trend ◽  
Climate Extremes ◽  
The Arctic ◽  
Northern Eurasia ◽  
Climate Trend ◽  
Temperature And Precipitation ◽  
The Arctic Oscillation

The 2019/2020 wintertime (December–March) anomalies of sea level pressure, temperature, and precipitation are analyzed. The contribution of the 40-year linear trend in these parameters associated with global climate change and of the interannual variability associated with the Arctic Oscillation (AO) is assessed. In the 2019/2020 winter, extreme zonal circulation was observed. The mean wintertime AO index was 2.20, which ranked two for the whole observation period (started in the early 20th century) and was outperformed only by the wintertime index of 1988/1989. It is shown that the main contribution to the 2019/2020 wintertime anomalies was provided by the AO. A noticeable contribution of the trend was observed only in the Arctic. Extreme anomalies over Northern Eurasia were mainly associated with the AO rather than the trend. However, the AO-related anomalies, particularly air temperature anomalies, were developing against the background of the trend-induced increased mean level.

scholarly journals Toward a Consistent Definition between Satellite and Model Clear-Sky Radiative Fluxes

2020 ◽  
Vol 33 (1) ◽  
pp. 61-75 ◽  
Author(s):  
Norman G. Loeb ◽  
Fred G. Rose ◽  
Seiji Kato ◽  
David A. Rutan ◽  
Wenying Su ◽  
...  
Keyword(s):  
Tropical Pacific ◽  
Radiative Effect ◽  
The West ◽  
Model Calculations ◽  
Radiative Fluxes ◽  
Clear Sky ◽  
Cloud Radiative Effect ◽  
Adjustment Factors ◽  
The Impact ◽  
Global Mean

AbstractA new method of determining clear-sky radiative fluxes from satellite observations for climate model evaluation is presented. The method consists of applying adjustment factors to existing satellite clear-sky broadband radiative fluxes that make the observed and simulated clear-sky flux definitions more consistent. The adjustment factors are determined from the difference between observation-based radiative transfer model calculations of monthly mean clear-sky fluxes obtained by ignoring clouds in the atmospheric column and by weighting hourly mean clear-sky fluxes with imager-based clear-area fractions. The global mean longwave (LW) adjustment factor is −2.2 W m−2 at the top of the atmosphere and 2.7 W m−2 at the surface. The LW adjustment factors are pronounced at high latitudes during winter and in regions with high upper-tropospheric humidity and cirrus cloud cover, such as over the west tropical Pacific, and the South Pacific and intertropical convergence zones. In the shortwave (SW), global mean adjustment is 0.5 W m−2 at TOA and −1.9 W m−2 at the surface. It is most pronounced over sea ice off of Antarctica and over heavy aerosol regions, such as eastern China. However, interannual variations in the regional SW and LW adjustment factors are small compared to those in cloud radiative effect. After applying the LW adjustment factors, differences in zonal mean cloud radiative effect between observations and climate models decrease markedly between 60°S and 60°N and poleward of 65°N. The largest regional improvements occur over the west tropical Pacific and Indian Oceans. In contrast, the impact of the SW adjustment factors is much smaller.

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