Quantifying the internal variability in multi-decadal trends of spring surface air temperature over mid-to-high latitudes of Eurasia

2020 ◽  
Vol 55 (7-8) ◽  
pp. 2013-2030
Author(s):  
Zhaomin Ding ◽  
Renguang Wu
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
High Latitudes

Interannual variability of surface air temperature over mid-high latitudes of Eurasia during boreal autumn

2019 ◽  
Vol 53 (3-4) ◽  
pp. 1805-1821 ◽  
Author(s):  
Shangfeng Chen ◽  
Renguang Wu ◽  
Linye Song ◽  
Wen Chen
Keyword(s):  
Interannual Variability ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
High Latitudes

scholarly journals Projected Changes in Daily Variability and Seasonal Cycle of Near-Surface Air Temperature over the Globe during the Twenty-First Century

2019 ◽  
Vol 32 (24) ◽  
pp. 8537-8561 ◽  
Author(s):  
Jiao Chen ◽  
Aiguo Dai ◽  
Yaocun Zhang
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Seasonal Cycle ◽  
Surface Air Temperature ◽  
First Century ◽  
The Arctic ◽  
Boreal Summer ◽  
High Latitudes ◽  
Low Latitudes ◽  
Twenty First Century

Abstract Increases in atmospheric greenhouse gases will not only raise Earth’s temperature but may also change its variability and seasonal cycle. Here CMIP5 model data are analyzed to quantify these changes in surface air temperature (Tas) and investigate the underlying processes. The models capture well the mean Tas seasonal cycle and variability and their changes in reanalysis, which shows decreasing Tas seasonal amplitudes and variability over the Arctic and Southern Ocean from 1979 to 2017. Daily Tas variability and seasonal amplitude are projected to decrease in the twenty-first century at high latitudes (except for boreal summer when Tas variability increases) but increase at low latitudes. The day of the maximum or minimum Tas shows large delays over high-latitude oceans, while it changes little at low latitudes. These Tas changes at high latitudes are linked to the polar amplification of warming and sea ice loss, which cause larger warming in winter than summer due to extra heating from the ocean during the cold season. Reduced sea ice cover also decreases its ability to cause Tas variations, contributing to the decreased Tas variability at high latitudes. Over low–midlatitude oceans, larger increases in surface evaporation in winter than summer (due to strong winter winds, strengthened winter winds in the Southern Hemisphere, and increased winter surface humidity gradients over the Northern Hemisphere low latitudes), coupled with strong ocean mixing in winter, lead to smaller surface warming in winter than summer and thus increased seasonal amplitudes there. These changes result in narrower (wider) Tas distributions over the high (low) latitudes, which may have important implications for other related fields.

Observational estimation of radiative feedback to surface air temperature over Northern High Latitudes

2017 ◽  
Vol 50 (1-2) ◽  
pp. 615-628 ◽  
Author(s):  
Jiwon Hwang ◽  
Yong-Sang Choi ◽  
WonMoo Kim ◽  
Hui Su ◽  
Jonathan H. Jiang
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
High Latitudes ◽  
Radiative Feedback

scholarly journals Changes of Variability in Response to Increasing Greenhouse Gases. Part I: Temperature

2007 ◽  
Vol 20 (21) ◽  
pp. 5455-5467 ◽  
Author(s):  
R. J. Stouffer ◽  
R. T. Wetherald
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Annual Data ◽  
Tropospheric Temperature ◽  
High Latitudes ◽  
Near Surface ◽  
Temperature Variance ◽  
General Reduction

Abstract This study documents the temperature variance change in two different versions of a coupled ocean–atmosphere general circulation model forced with estimates of future increases of greenhouse gas (GHG) and aerosol concentrations. The variance changes are examined using an ensemble of 8 transient integrations for the older model version and 10 transient integrations for the newer one. Monthly and annual data are used to compute the mean and variance changes. Emphasis is placed upon computing and analyzing the variance changes for the middle of the twenty-first century and compared with those found in a control integration. The large-scale variance of lower-tropospheric temperature (including surface air temperature) generally decreases in high latitudes particularly during fall due to a delayed onset of sea ice as the climate warms. Sea ice acts to insolate the atmosphere from the much larger heat capacity of the ocean. Therefore, the near-surface temperature variance tends to be larger over the sea ice–covered regions, than the nearby ice-free regions. The near-surface temperature variance also decreases during the winter and spring due to a general reduction in the extent of sea ice during winter and spring. Changes in storminess were also examined and were found to have relatively little effect upon the reduction of temperature variance. Generally small changes of surface air temperature variance occurred in low and midlatitudes over both land and oceanic areas year-round. An exception to this was a general reduction of variance in the equatorial Pacific Ocean for the newer model. Small increases in the surface air temperature variance occur in mid- to high latitudes during the summer months, suggesting the possibility of more frequent and longer-lasting heat waves in response to increasing GHGs.

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>

scholarly journals Mid-summer surface air temperature and its internal variability over China at 1.5 °C and 2 °C global warming

2020 ◽  
Vol 11 (3) ◽  
pp. 185-197 ◽  
Author(s):  
Shu-Yue YIN ◽  
Tao WANG ◽  
Wei HUA ◽  
Jia-Peng MIAO ◽  
Yong-Qi GAO ◽  
...  
Keyword(s):  
Global Warming ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Internal Variability

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 Surface Air Temperature and Humidity from Intersatellite-Calibrated HIRS Measurements in High Latitudes

2012 ◽  
Vol 29 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Lei Shi ◽  
Ge Peng ◽  
John J. Bates
Keyword(s):  
Air Temperature ◽  
High Latitude ◽  
Surface Air Temperature ◽  
Ocean Surface ◽  
Specific Humidity ◽  
Large Set ◽  
High Latitudes ◽  
Neural Network Approach ◽  
Temperature And Humidity ◽  
Rms Errors

Abstract High-latitude ocean surface air temperature and humidity derived from intersatellite-calibrated High-Resolution Infrared Radiation Sounder (HIRS) measurements are examined. A neural network approach is used to develop retrieval algorithms. HIRS simultaneous nadir overpass observations from high latitudes are used to intercalibrate observations from different satellites. Investigation shows that if HIRS observations were not intercalibrated, then it could lead to intersatellite biases of 1°C in the air temperature and 1–2 g kg−1 in the specific humidity for high-latitude ocean surface retrievals. Using a full year of measurements from a high-latitude moored buoy site as ground truth, the instantaneous (matched within a half-hour) root-mean-square (RMS) errors of HIRS retrievals are 1.50°C for air temperature and 0.86 g kg−1 for specific humidity. Compared to a large set of operational moored and drifting buoys in both northern and southern oceans greater than 50° latitude, the retrieval instantaneous RMS errors are within 2.6°C for air temperature and 1.4 g kg−1 for specific humidity. Compared to 5 yr of International Maritime Meteorological Archive in situ data, the HIRS specific humidity retrievals show less than 0.5 g kg−1 of differences over the majority of northern high-latitude open oceans.

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