scholarly journals The role of internal variability in climate change projections of North American surface air temperature and temperature extremes in CanESM2 large ensemble simulations

2020 ◽  
Vol 55 (3-4) ◽  
pp. 869-885
Author(s):  
Bin Yu ◽  
Guilong Li ◽  
Shangfeng Chen ◽  
Hai Lin
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Temperature Extremes ◽  
Large Ensemble ◽  
Climate Change Projections ◽  
Ensemble Simulations

The role of internal variability in climate change projections of North American surface air temperature and temperature extremes in CanESM2 large ensemble simulations

2020 ◽  
Author(s):  
Bin Yu ◽  
Guilong Li ◽  
Shangfeng Chen ◽  
Hai Lin
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Temperature Extremes ◽  
Large Ensemble ◽  
Climate Simulations ◽  
Ensemble Mean

<p>Recent studies indicated that the internal climate variability plays an important role in various aspects of projected climate changes on regional and local scales. Here we present results of the spreads in projected trends of wintertime North American surface air temperature and extremes indices of warm and cold days over the next half-century, by analyzing a 50-member large ensemble of climate simulations conducted with CanESM2. CanESM2 simulations confirm the important role of internal variability in projected surface temperature trends as demonstrated in previous studies. Yet the spread in North American warming trends in CanESM2 is generally smaller than those obtained from CCSM3 and ECHAM5 large ensemble simulations. Despite this, large spreads in the climate means as well as climate change trends of North American temperature extremes are apparent in CanESM2, especially in the projected cold day trends. The ensemble mean of forced climate simulations reveals high risks of warm days over the western coast and north Canada, as well as a weakening belt of cold days extending from Alaska to the northeast US. The individual ensemble members differ from the ensemble mean mainly in magnitude of the warm day trends, but depart from the ensemble mean in conspicuous ways, including spatial pattern and magnitude, of the cold day trends. The signal-to-noise ratio pattern of the warm day trend resembles that of the surface air temperature trend; with stronger signals over north Canada, Alaska, and the southwestern US than the midsection of the continent. The projected cold day patterns reveal strong signals over the southwestern US, north Canada, and the northeastern US. In addition, the internally generated components of temperature and temperature extreme trends exhibit spatial coherences over North America, and are comparable to the externally forced trends. The large-scale atmospheric circulation-induced temperature variability influences these trends. Overall, our results suggest that climate change trends of North American temperature extremes are likely very uncertain and need to be applied with caution.</p>

Projecting North American Climate over the Next 50 Years: Uncertainty due to Internal Variability*

2014 ◽  
Vol 27 (6) ◽  
pp. 2271-2296 ◽  
Author(s):  
Clara Deser ◽  
Adam S. Phillips ◽  
Michael A. Alexander ◽  
Brian V. Smoliak
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Radiative Forcing ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Climate Trends ◽  
Climate Change Projections ◽  
Temperature And Precipitation ◽  
Model Ensembles ◽  
Precipitation Trends

Abstract This study highlights the relative importance of internally generated versus externally forced climate trends over the next 50 yr (2010–60) at local and regional scales over North America in two global coupled model ensembles. Both ensembles contain large numbers of integrations (17 and 40): each of which is subject to identical anthropogenic radiative forcing (e.g., greenhouse gas increase) but begins from a slightly different initial atmospheric state. Thus, the diversity of projected climate trends within each model ensemble is due solely to intrinsic, unpredictable variability of the climate system. Both model ensembles show that natural climate variability superimposed upon forced climate change will result in a range of possible future trends for surface air temperature and precipitation over the next 50 yr. Precipitation trends are particularly subject to uncertainty as a result of internal variability, with signal-to-noise ratios less than 2. Intrinsic atmospheric circulation variability is mainly responsible for the spread in future climate trends, imparting regional coherence to the internally driven air temperature and precipitation trends. The results underscore the importance of conducting a large number of climate change projections with a given model, as each realization will contain a different superposition of unforced and forced trends. Such initial-condition ensembles are also needed to determine the anthropogenic climate response at local and regional scales and provide a new perspective on how to usefully compare climate change projections across models.

scholarly journals Climate and Climate Change over North America as Simulated by the Canadian RCM

2006 ◽  
Vol 19 (13) ◽  
pp. 3112-3132 ◽  
Author(s):  
D. A. Plummer ◽  
D. Caya ◽  
A. Frigon ◽  
H. Côté ◽  
M. Giguère ◽  
...  
Keyword(s):  
Climate Change ◽  
Boundary Conditions ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Summer Season ◽  
Warm Bias ◽  
Air Temperatures ◽  
Northern Regions ◽  
Physical Parameterizations

Abstract An analysis of several multidecadal simulations of the present (1971–90) and future (2041–60) climate from the Canadian Regional Climate Model (CRCM) is presented. The effects on the CRCM climate of model domain size, internal variability of the general circulation model (GCM) used to provide boundary conditions, and modifications to the physical parameterizations used in the CRCM are investigated. The influence of boundary conditions is further investigated by comparing the GCM-driven simulations of the current climate with simulations performed using boundary conditions from meteorological reanalyses. The present climate of the model in these different configurations is assessed by comparing the seasonal averages and interannual variability of precipitation and surface air temperature with an observed climatology. Generally, small differences are found between the two simulations on different domains, though both domains are quite large as compared with previously reported results. Simulations driven by GCM output show a significant warm bias for wintertime surface air temperatures over northern regions. This warm bias is much reduced in the GCM-driven simulation when an updated set of physical parameterizations is used in the CRCM. The warm bias is also reduced for simulations with the standard set of physical parameterizations when the CRCM is driven with reanalysis data. However, use of the modified physics package for reanalysis-driven simulations results in surface air temperatures that are colder than the observations. Summertime precipitation in the model is much larger than observed, a bias that is present in both the GCM-driven and reanalysis-driven simulations. The bias in summertime precipitation is reduced for both types of driving data when the updated set of physical parameterizations is used. Model projections of climate change between the present and future periods are also presented and the sensitivity of these projections to many of the above-mentioned modifications is assessed. Changes in surface air temperature are predicted to be largest over northern regions in winter, with smaller changes over more southerly regions and in the summer season. Changes in seasonal average precipitation are projected to be in the range of ±10% of present-day amounts for most regions and seasons. The CRCM projections of surface air temperature changes are strongly affected by the internal variability of the driving GCM over high northern latitudes and to changes in the physical parameterizations over many regions for the summer season.

scholarly journals Uncertainty in climate change projections: the role of internal variability

2010 ◽  
Vol 38 (3-4) ◽  
pp. 527-546 ◽  
Author(s):  
Clara Deser ◽  
Adam Phillips ◽  
Vincent Bourdette ◽  
Haiyan Teng
Keyword(s):  
Climate Change ◽  
Internal Variability ◽  
Climate Change Projections

scholarly journals Tropopause height at 78° N 16° E: average seasonal variation 2007–2010

2011 ◽  
Vol 11 (1) ◽  
pp. 39-52
Author(s):  
C. M. Hall ◽  
G. Hansen ◽  
F. Sigernes ◽  
K. M. Kuyeng Ruiz
Keyword(s):  
Climate Change ◽  
Seasonal Variation ◽  
Air Temperature ◽  
High Latitude ◽  
Column Density ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Tropopause Height ◽  
Vhf Radar ◽  
Ozone Column

Abstract. We present a seasonal climatology of tropopause altitude for 78° N 16° E derived from observations 2007–2010 by the SOUSY VHF radar on Svalbard. The spring minimum occurs one month later than that of surface air temperature and instead coincides with the maximum in ozone column density. This confirms similar studies based on radiosonde measurements in the arctic and demonstrates downward control by the stratosphere. If one is to exploit the potential of tropopause height as a metric for climate change at high latitude and elsewhere, it is imperative to observe and understand the processes which establish the tropopause – an understanding to which this study contributes.

scholarly journals Influence of ENSO on North American subseasonal surface air temperature variability

2021 ◽  
Vol 2 (2) ◽  
pp. 395-412
Author(s):  
Patrick Martineau ◽  
Hisashi Nakamura ◽  
Yu Kosaka
Keyword(s):  
North America ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Tropical Pacific ◽  
La Niña ◽  
Western North America ◽  
The North ◽  
Subseasonal Variability ◽  
La Nina

Abstract. The wintertime influence of tropical Pacific sea surface temperature (SST) variability on subseasonal variability is revisited by identifying the dominant mode of covariability between 10–60 d band-pass-filtered surface air temperature (SAT) variability over the North American continent and winter-mean SST over the tropical Pacific. We find that the El Niño–Southern Oscillation (ENSO) explains a dominant fraction of the year-to-year changes in subseasonal SAT variability that are covarying with SST and thus likely more predictable. In agreement with previous studies, we find a tendency for La Niña conditions to enhance the subseasonal SAT variability over western North America. This modulation of subseasonal variability is achieved through interactions between subseasonal eddies and La Niña-related changes in the winter-mean circulation. Specifically, eastward-propagating quasi-stationary eddies over the North Pacific are more efficient in extracting energy from the mean flow through the baroclinic conversion during La Niña. Structural changes of these eddies are crucial to enhance the efficiency of the energy conversion via amplified downgradient heat fluxes that energize subseasonal eddy thermal anomalies. The enhanced likelihood of cold extremes over western North America is associated with both an increased subseasonal SAT variability and the cold winter-mean response to La Niña.

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