Examining Internal and External Contributors to Greenland Climate Variability Using CCSM3

Abstract

Greenland climate variability is connected to internal and external sources of global climate forcing in six millennium simulations using Community Climate System Model, version 3. The external forcings employed are consistent with the protocols of Paleoclimate Modelling Intercomparison Project Phase 3. Many simulated internal climate modes are characterized over the years 850-1850, including the Atlantic meridional overturning circulation (AMOC), the Atlantic multidecadal oscillation (AMO), the east Atlantic pattern (EA), the El Niño-Southern Oscillation, the North Atlantic Oscillation (NAO), the North Atlantic sea ice extent, and the Pacific decadal oscillation (PDO). Lagged correlation and multivariate regression methods connect Greenland temperatures and precipitation to these internal modes and external sources of climate variability.Greenland temperature and precipitation are found to relate most strongly to North Atlantic sea ice extent, the AMO, and the AMOC, that are themselves strongly interconnected. Furthermore, approximately half of the multidecadal variability in Greenland temperature and precipitation are captured through linear relationships with volcanic aerosol optical depth, solar insolation (including total solar irradiance and local orbital variability), the NAO, the EA, and the PDO. Relationships are robust with volcanic aerosol optical depth, solar insolation, and an index related to latitudinal shifts of the North Atlantic jet. Differences attributable to model resolution are also identified in the results, such as lower variability in the AMOC and Greenland temperature in the higher-resolution simulations. Finally, a regression model is applied to simulations of the industrial period to show that natural sources alone only explain the variability in simulated Greenland temperature and precipitation up to the 1950s and 1970s, respectively.

Atmospheric summer teleconnections and Greenland Ice Sheet surface mass variations: insights from MERRA-2

“…The SWM result in figure 5(b) is similar to the positive phase of the EA pattern, though the negative anomaly somewhat shifts to the west compared to the typical EA pattern. This EA-like distribution supports the possibility that the NAO may be impacting the subsequent development of the EA Blackburn 2012, Andres andPeltier 2013). In fact we find that since the year 2000, 11 out of the 15 summers experienced a negative NAO, and all 11 of those summers were accompanied by a positive EA ( figure 5(c)).…”

“…Those studies argued that the relevant atmospheric processes are strongly linked to large-scale teleconnection patterns such as the North Atlantic Oscillation (NAO), which is known to have a negative relationship with GrIS temperature (Mosley-Thompson et al 2005, Overland et al 2012, Tedesco et al 2013, Hanna et al 2014. However, the broader relationships between Greenland temperature and precipitation and the NAO remain unclear (Andres and Peltier 2013), having seasonal dependence (Bromwich et al 1999, Seo et al 2015 and considerable regional complexity (Fettweis 2007, Fraunfeld et al 2011, Seo et al 2015. The NAO is known to have a strong negative relationship with the Greenland blocking index (GBI), which is defined as the areaaveraged 500 hPa geopotential height over 60-20°W and 60-80°N that covers the GrIS (Hanna et al 2014).…”

Resolving Seasonal Ice Velocity of 45 Greenlandic Glaciers With Very High Temporal Details

“…In this study, we expand on this recent research by investigating high temporal resolution seasonal ice velocity variations of 45 individual marine-terminating glaciers during 2015-01-01 to 2017-12-31 ( Figure 1). These regions are influenced by different external forcing, such as annual sea ice concentration, melt extent, and melt period length (Andres & Peltier, 2013). These regions are influenced by different external forcing, such as annual sea ice concentration, melt extent, and melt period length (Andres & Peltier, 2013).…”

Attributing observed Greenland responses to natural and anthropogenic climate forcings

“…In those cases, reversing the sign of this component of variability yields significant correlations between the estimated and observed accumulation values. be employed to fill this data gap, whether they be reanalysis products (Hanna et al 2008(Hanna et al , 2011Wake et al 2009), regional climate models of varying resolution (Wake et al 2009;Box et al 2009Box et al , 2013Fettweis et al 2013) or global climate models (Andres and Peltier 2013, hereafter referred to as AP13). However, over the earliest periods, different methods yield substantially different reconstructions, particularly for precipitation (Hanna et al 2011;Box 2013), and reconstructions remain much more accurate for Greenland averages than for different regions of the GrIS.…”