scholarly journals Seasonally changing contribution of sea ice and snow cover to uncertainty in multi-decadal Eurasian surface air temperature trends based on CESM simulations

2021 ◽  
Author(s):  
Zhaomin Ding ◽  
Renguang Wu
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Western Siberia ◽  
Russian Far East ◽  
Far East ◽  
Surface Air Temperature ◽  
The Caspian Sea ◽  
Sea Ice Concentration ◽  
Northern Siberia ◽  
The Impact

AbstractThis study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

scholarly journals The Impact of Milankovitch Solar Radiation Variations on Sea-Ice and Air Temperature in a Coupled Energy-Balance Climate-Sea-Ice Model

1990 ◽  
Vol 14 ◽  
pp. 144-147 ◽  
Author(s):  
Tamara Shapiro Ledley
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Air Temperature ◽  
Energy Transport ◽  
Model Simulation ◽  
Surface Air Temperature ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
The Mean ◽  
The Impact

The sensitivity of thermodynamically-varying sea-ice and surface air temperature to variations in solar radiation on the 104 to 105 time scales is examined in this study. Model simulation results show the mean annual sea-ice thickness is very sensitive to the magnitude of midsummer solar radiation. During periods of high midsummer solar radiation between 115 ka B.P. and the present the sea ice is thinner, producing larger summer time leads and longer periods of open ocean. This has an effect on the mean annual sea-ice thickness, but not on the mean annual air temperature. However, the changes in sea ice are accompanied by similar variations in the summer surface air temperature, which are the result of the variations in the solar radiation and meridional energy transport.

scholarly journals The Impact of Milankovitch Solar Radiation Variations on Sea-Ice and Air Temperature in a Coupled Energy-Balance Climate-Sea-Ice Model

1990 ◽  
Vol 14 ◽  
pp. 144-147 ◽  
Author(s):  
Tamara Shapiro Ledley
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Air Temperature ◽  
Energy Transport ◽  
Model Simulation ◽  
Surface Air Temperature ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
The Mean ◽  
The Impact

The sensitivity of thermodynamically-varying sea-ice and surface air temperature to variations in solar radiation on the 104 to 105 time scales is examined in this study. Model simulation results show the mean annual sea-ice thickness is very sensitive to the magnitude of midsummer solar radiation. During periods of high midsummer solar radiation between 115 ka B.P. and the present the sea ice is thinner, producing larger summer time leads and longer periods of open ocean. This has an effect on the mean annual sea-ice thickness, but not on the mean annual air temperature. However, the changes in sea ice are accompanied by similar variations in the summer surface air temperature, which are the result of the variations in the solar radiation and meridional energy transport.

scholarly journals An Investigation into the Impact of using Various Techniques to Estimate Arctic Surface Air Temperature Anomalies*

2015 ◽  
Vol 28 (5) ◽  
pp. 1743-1763 ◽  
Author(s):  
Emma M. A. Dodd ◽  
Christopher J. Merchant ◽  
Nick A. Rayner ◽  
Colin P. Morice
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Meteorological Station ◽  
The Arctic ◽  
Test Bed ◽  
Recent Climate ◽  
The Impact ◽  
Mean Square Errors

Abstract Time series of global and regional mean surface air temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice was investigated using reanalysis data as a test bed. Techniques that interpolated anomalies were found to result in smaller errors than noninterpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies, and simple kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, root-mean-square errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Noninterpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979–2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.

The impact of a warm moist air intrusion on dynamic and thermodynamic sea ice tendencies in the Arctic.

2020 ◽  
Author(s):  
Evelien Dekker
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Moist Air ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
The Impact

<p>Atmospheric blocking events in the Northern Hemishpere have been related to regional Arctic sea ice decline. During blocking events, pulses of warm and moist air enhance the radiative forcing on the sea ice in winter due to the increased longwave radiation associated with clouds. Several studies have shown that such events are related to regional sea ice concentration decline. Daily sea ice output with the latest version of CICE from the coupled Regional Arctic System model is used to study sea ice tendencies during January-February 2014. In this period there was a follow-up of a Atlantic warm moist air insturion and a Pacific warm moist air intrusion associated with surface air temperature perturbations up to 20 degrees locally.</p><p>A decline in sea ice concentration during wintertime does not neccesarily mean that ice melt has occurred. The goal of this case study is to distinguish the sea ice response between a dynamic and a thermodynamic component. In this way, we learn how much of the sea ice is advected into another region during such an event and how much the sea ice is lost due to the enhanced forcing and temperature increase.</p><p> </p><p> </p><p> </p>

scholarly journals Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

2021 ◽  
Author(s):  
Vidya Anderson ◽  
William A. Gough
Keyword(s):  
Urban Agriculture ◽  
Air Temperature ◽  
Green Infrastructure ◽  
Urban Climate ◽  
Surface Air Temperature ◽  
Green Roofs ◽  
Near Surface ◽  
Green Walls ◽  
The Impact ◽  
Agriculture Systems

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

scholarly journals Seasonal Surface Air Temperature and Precipitation in the FSU Climate Model Coupled to the CLM2

2005 ◽  
Vol 18 (16) ◽  
pp. 3217-3228 ◽  
Author(s):  
D. W. Shin ◽  
S. Cocke ◽  
T. E. LaRow ◽  
James J. O’Brien
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Climate Model ◽  
Initial Conditions ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
Community Land Model ◽  
Temperature And Precipitation ◽  
The Impact ◽  
Convective Scheme

Abstract The current Florida State University (FSU) climate model is upgraded by coupling the National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) as its land component in order to make a better simulation of surface air temperature and precipitation on the seasonal time scale, which is important for crop model application. Climatological and seasonal simulations with the FSU climate model coupled to the CLM2 (hereafter FSUCLM) are compared to those of the control (the FSU model with the original simple land surface treatment). The current version of the FSU model is known to have a cold bias in the temperature field and a wet bias in precipitation. The implementation of FSUCLM has reduced or eliminated this bias due to reduced latent heat flux and increased sensible heat flux. The role of the land model in seasonal simulations is shown to be more important during summertime than wintertime. An additional experiment that assimilates atmospheric forcings produces improved land-model initial conditions, which in turn reduces the biases further. The impact of various deep convective parameterizations is examined as well to further assess model performance. The land scheme plays a more important role than the convective scheme in simulations of surface air temperature. However, each convective scheme shows its own advantage over different geophysical locations in precipitation simulations.

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