scholarly journals Enhanced warming of seasonal cold extremes relative to the mean in the Northern Hemisphere extratropics

2019 ◽  
Author(s):  
Mia H. Gross ◽  
Markus G. Donat ◽  
Lisa V. Alexander ◽  
Steven C. Sherwood

Abstract. Cold extremes are anticipated to warm at a faster rate than both hot extremes and average temperatures for much of the Northern Hemisphere. The consequences of warming cold extremes can affect numerous sectors, including human health, tourism and various ecosystems that are sensitive to cold temperatures. Using a selection of Global Climate Models, this paper explores the enhanced warming of seasonal cold extremes relative to seasonal mean temperatures in the Northern Hemisphere extratropics. The potentially driving physical mechanisms are investigated by assessing conditions on the day, or prior to, when the cold extreme occurs to understand how the different environmental fields are related. During winter months, North America, Europe and much of Eurasia show enhanced warming of cold extremes projected for the late 21st century, compared to the mid-20th century. This is shown to be largely driven by reductions in cold air temperature advection, suggested as a likely consequence of Arctic amplification. In spring and autumn, cold extremes are expected to warm faster than average temperatures for most of the Northern Hemisphere mid- to high-latitudes, particularly Alaska, northern Canada and northern Eurasia. In the shoulder seasons, projected decreases in snow cover and associated reductions in surface albedo are suggested as the largest contributor affecting the accelerated rates of warming in cold extremes. This study uses a novel approach to examine the day in which the extreme occurs to improve our understanding of the environmental conditions that contribute to the accelerated warming of cold extremes relative to mean temperatures.

2020 ◽  
Vol 11 (1) ◽  
pp. 97-111
Author(s):  
Mia H. Gross ◽  
Markus G. Donat ◽  
Lisa V. Alexander ◽  
Steven C. Sherwood

Abstract. Cold extremes are anticipated to warm at a faster rate than both hot extremes and average temperatures for much of the Northern Hemisphere. Anomalously warm cold extremes can affect numerous sectors, including human health, tourism and various ecosystems that are sensitive to cold temperatures. Using a selection of global climate models, this paper explores the accelerated warming of seasonal cold extremes relative to seasonal mean temperatures in the Northern Hemisphere extratropics. The potential driving physical mechanisms are investigated by assessing conditions on or prior to the day when the cold extreme occurs to understand how the different environmental fields are related. During winter, North America, Europe and much of Eurasia show amplified warming of cold extremes projected for the late 21st century, compared to the mid-20th century. This is shown to be largely driven by reductions in cold air temperature advection, suggested as a likely consequence of Arctic amplification. In spring and autumn, cold extremes are expected to warm faster than average temperatures for most of the Northern Hemisphere mid-latitudes to high latitudes, particularly Alaska, northern Canada and northern Eurasia. In the shoulder seasons, projected decreases in snow cover and associated reductions in surface albedo are suggested as the largest contributor affecting the accelerated rates of warming in cold extremes. The key findings of this study improve our understanding of the environmental conditions that contribute to the accelerated warming of cold extremes relative to mean temperatures.


2003 ◽  
Vol 22 (1) ◽  
pp. 75-82 ◽  
Author(s):  
John E. Walsh ◽  
Michael S. Timlin

2016 ◽  
Vol 29 (24) ◽  
pp. 8823-8840 ◽  
Author(s):  
Paolo Davini ◽  
Fabio D’Andrea

Abstract The correct simulation of midlatitude atmospheric blocking has always been a main concern since the earliest days of numerical modeling of Earth’s atmosphere. To this day blocking represents a considerable source of error for general circulation models from both a numerical weather prediction and a climate perspective. In the present work, 20 years of global climate model (GCM) developments are analyzed from the special point of view of Northern Hemisphere atmospheric blocking simulation. Making use of a series of equivalent metrics, three generations of GCMs are compared. This encompasses a total of 95 climate models, many of which are different—successive—versions of the same model. Results from model intercomparison projects AMIP1 (1992), CMIP3 (2007), and CMIP5 (2012) are taken into consideration. Although large improvements are seen over the Pacific Ocean, only minor advancements have been achieved over the Euro-Atlantic sector. Some of the most recent GCMs still exhibit the same negative bias as 20 years ago in this region, associated with large geopotential height systematic errors. Some individual models, nevertheless, have improved and do show good performances in both sectors. Negligible differences emerge among ocean-coupled or atmosphere-only simulations, suggesting weak relevance of sea surface temperature biases. Conversely, increased horizontal resolution seems to be able to alleviate the Euro-Atlantic blocking bias.


2015 ◽  
Vol 15 (17) ◽  
pp. 9997-10018 ◽  
Author(s):  
J. Xing ◽  
R. Mathur ◽  
J. Pleim ◽  
C. Hogrefe ◽  
C.-M. Gan ◽  
...  

Abstract. The ability of a coupled meteorology–chemistry model, i.e., Weather Research and Forecast and Community Multiscale Air Quality (WRF-CMAQ), to reproduce the historical trend in aerosol optical depth (AOD) and clear-sky shortwave radiation (SWR) over the Northern Hemisphere has been evaluated through a comparison of 21-year simulated results with observation-derived records from 1990 to 2010. Six satellite-retrieved AOD products including AVHRR, TOMS, SeaWiFS, MISR, MODIS-Terra and MODIS-Aqua as well as long-term historical records from 11 AERONET sites were used for the comparison of AOD trends. Clear-sky SWR products derived by CERES at both the top of atmosphere (TOA) and surface as well as surface SWR data derived from seven SURFRAD sites were used for the comparison of trends in SWR. The model successfully captured increasing AOD trends along with the corresponding increased TOA SWR (upwelling) and decreased surface SWR (downwelling) in both eastern China and the northern Pacific. The model also captured declining AOD trends along with the corresponding decreased TOA SWR (upwelling) and increased surface SWR (downwelling) in the eastern US, Europe and the northern Atlantic for the period of 2000–2010. However, the model underestimated the AOD over regions with substantial natural dust aerosol contributions, such as the Sahara Desert, Arabian Desert, central Atlantic and northern Indian Ocean. Estimates of the aerosol direct radiative effect (DRE) at TOA are comparable with those derived by measurements. Compared to global climate models (GCMs), the model exhibits better estimates of surface-aerosol direct radiative efficiency (Eτ). However, surface-DRE tends to be underestimated due to the underestimated AOD in land and dust regions. Further investigation of TOA-Eτ estimations as well as the dust module used for estimates of windblown-dust emissions is needed.


2021 ◽  
Author(s):  
Kerttu Kouki ◽  
Petri Räisänen ◽  
Kari Luojus ◽  
Anna Luomaranta ◽  
Aku Riihelä

Abstract. Seasonal snow cover of the Northern Hemisphere (NH) is a major factor in the global climate system, which makes snow cover an important variable in climate models. Monitoring snow water equivalent (SWE) at continental scale is only possible from satellites, yet substantial uncertainties have been reported in NH SWE estimates. A recent bias-correction method significantly reduces the uncertainty of NH SWE estimation, which enables a more reliable analysis of the climate models' ability to describe the snow cover. We have intercompared the CMIP6 (Coupled Model Intercomparison Project Phase 6) and satellite-based NH SWE estimates north of 40° N for the period 1982–2014, and analyzed with a regression approach whether temperature (T) and precipitation (P) could explain the differences in SWE. We analyzed separately SWE in winter and SWE change rate in spring. The SnowCCI SWE data are based on satellite passive microwave radiometer data and in situ data. The analysis shows that CMIP6 models tend to overestimate SWE, however, large variability exists between models. In winter, P is the dominant factor causing SWE discrepancies especially in the northern and coastal regions. This is in line with the expectation that even too cold temperatures cannot cause too high SWE without precipitation. T contributes to SWE biases mainly in regions, where T is close to 0 °C in winter. In spring, the importance of T in explaining the snowmelt rate discrepancies increases. This is to be expected, because the increase in T is the main factor that causes snow to melt as spring progresses. Furthermore, it is obvious from the results that biases in T or P can not explain all model biases either in SWE in winter or in the snowmelt rate in spring. Other factors, such as deficiencies in model parameterizations and possibly biases in the observational datasets, also contribute to SWE discrepancies. In particular, linear regression suggests that when the biases in T and P are eliminated, the models generally overestimate the snowmelt rate in spring.


2013 ◽  
Vol 26 (18) ◽  
pp. 6904-6914 ◽  
Author(s):  
David E. Rupp ◽  
Philip W. Mote ◽  
Nathaniel L. Bindoff ◽  
Peter A. Stott ◽  
David A. Robinson

Abstract Significant declines in spring Northern Hemisphere (NH) snow cover extent (SCE) have been observed over the last five decades. As one step toward understanding the causes of this decline, an optimal fingerprinting technique is used to look for consistency in the temporal pattern of spring NH SCE between observations and simulations from 15 global climate models (GCMs) that form part of phase 5 of the Coupled Model Intercomparison Project. The authors examined simulations from 15 GCMs that included both natural and anthropogenic forcing and simulations from 7 GCMs that included only natural forcing. The decline in observed NH SCE could be largely explained by the combined natural and anthropogenic forcing but not by natural forcing alone. However, the 15 GCMs, taken as a whole, underpredicted the combined forcing response by a factor of 2. How much of this underprediction was due to underrepresentation of the sensitivity to external forcing of the GCMs or to their underrepresentation of internal variability has yet to be determined.


2020 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  

2008 ◽  
Vol 21 (8) ◽  
pp. 1669-1679 ◽  
Author(s):  
U. Ulbrich ◽  
J. G. Pinto ◽  
H. Kupfer ◽  
G. C. Leckebusch ◽  
T. Spangehl ◽  
...  

Abstract Winter storm-track activity over the Northern Hemisphere and its changes in a greenhouse gas scenario (the Special Report on Emission Scenarios A1B forcing) are computed from an ensemble of 23 single runs from 16 coupled global climate models (CGCMs). All models reproduce the general structures of the observed climatological storm-track pattern under present-day forcing conditions. Ensemble mean changes resulting from anthropogenic forcing include an increase of baroclinic wave activity over the eastern North Atlantic, amounting to 5%–8% by the end of the twenty-first century. Enhanced activity is also found over the Asian continent and over the North Pacific near the Aleutian Islands. At high latitudes and over parts of the subtropics, activity is reduced. Variations of the individual models around the ensemble average signal are not small, with a median of the pattern correlation near r = 0.5. There is, however, no evidence for a link between deviations in present-day climatology and deviations with respect to climate change.


2017 ◽  
Vol 30 (16) ◽  
pp. 6279-6295 ◽  
Author(s):  
Martin B. Stolpe ◽  
Iselin Medhaug ◽  
Reto Knutti

Recent studies have suggested that significant parts of the observed warming in the early and the late twentieth century were caused by multidecadal internal variability centered in the Atlantic and Pacific Oceans. Here, a novel approach is used that searches for segments of unforced preindustrial control simulations from global climate models that best match the observed Atlantic and Pacific multidecadal variability (AMV and PMV, respectively). In this way, estimates of the influence of AMV and PMV on global temperature that are consistent both spatially and across variables are made. Combined Atlantic and Pacific internal variability impacts the global surface temperatures by up to 0.15°C from peak-to-peak on multidecadal time scales. Internal variability contributed to the warming between the 1920s and 1940s, the subsequent cooling period, and the warming since then. However, variations in the rate of warming still remain after removing the influence of internal variability associated with AMV and PMV on the global temperatures. During most of the twentieth century, AMV dominates over PMV for the multidecadal internal variability imprint on global and Northern Hemisphere temperatures. Less than 10% of the observed global warming during the second half of the twentieth century is caused by internal variability in these two ocean basins, reinforcing the attribution of most of the observed warming to anthropogenic forcings.


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