Effects of Climate System Feedbacks and Inertia on Surface Temperature Power Spectrum Obtained from CMIP5 and Low-Order Models

2021 ◽  
Vol 57 (6) ◽  
pp. 659-668
Author(s):  
S. Soldatenko ◽  
Robert Colman
Keyword(s):  
Power Spectrum ◽  
Surface Temperature ◽  
Climate System ◽  
Low Order

scholarly journals BCC-CSM2-HR: A High-Resolution Version of the Beijing Climate Center Climate System Model

2020 ◽  
Author(s):  
Tongwen Wu ◽  
Rucong Yu ◽  
Yixiong Lu ◽  
Weihua Jie ◽  
Yongjie Fang ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate System ◽  
Sea Surface ◽  
System Model ◽  
Quasi Biennial Oscillation ◽  
Climate System Model ◽  
Medium Resolution ◽  
The Tropics

Abstract. BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model. Its development is on the basis of the medium-resolution version BCC-CSM2-MR which is the baseline for BCC participation to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamic core and physical processes. BCC-CSM2-HR is evaluated for present-day climate simulations from 1971 to 2000, which are performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. We focus on basic atmospheric mean states over the globe and variabilities in the tropics including the tropic cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR keeps well the global energy balance and can realistically reproduce main patterns of atmosphere temperature and wind, precipitation, land surface air temperature and sea surface temperature. It also improves in the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, is almost disappeared in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observation than their counterparts in BCC-CSM2-MR. We also note some weakness in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold Sea Surface Temperature (SST) biases and the insufficient number of tropical cyclones in the North Atlantic.

scholarly journals Estimates of climate system properties incorporating recent climate change

2018 ◽  
Vol 4 (1/2) ◽  
pp. 19-36 ◽  
Author(s):  
Alex G. Libardoni ◽  
Chris E. Forest ◽  
Andrei P. Sokolov ◽  
Erwan Monier
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
21St Century ◽  
Climate Sensitivity ◽  
Temperature Rise ◽  
Heat Content ◽  
Climate System ◽  
Model Parameters ◽  
Aerosol Forcing ◽  
Global Mean

Abstract. Historical time series of surface temperature and ocean heat content changes are commonly used metrics to diagnose climate change and estimate properties of the climate system. We show that recent trends, namely the slowing of surface temperature rise at the beginning of the 21st century and the acceleration of heat stored in the deep ocean, have a substantial impact on these estimates. Using the Massachusetts Institute of Technology Earth System Model (MESM), we vary three model parameters that influence the behavior of the climate system: effective climate sensitivity (ECS), the effective ocean diffusivity of heat anomalies by all mixing processes (Kv), and the net anthropogenic aerosol forcing scaling factor. Each model run is compared to observed changes in decadal mean surface temperature anomalies and the trend in global mean ocean heat content change to derive a joint probability distribution function for the model parameters. Marginal distributions for individual parameters are found by integrating over the other two parameters. To investigate how the inclusion of recent temperature changes affects our estimates, we systematically include additional data by choosing periods that end in 1990, 2000, and 2010. We find that estimates of ECS increase in response to rising global surface temperatures when data beyond 1990 are included, but due to the slowdown of surface temperature rise in the early 21st century, estimates when using data up to 2000 are greater than when data up to 2010 are used. We also show that estimates of Kv increase in response to the acceleration of heat stored in the ocean as data beyond 1990 are included. Further, we highlight how including spatial patterns of surface temperature change modifies the estimates. We show that including latitudinal structure in the climate change signal impacts properties with spatial dependence, namely the aerosol forcing pattern, more than properties defined for the global mean, climate sensitivity, and ocean diffusivity.

General Characteristics and Variability of Climate in the Amazon Basin and its Links to the Global Climate System

2001 ◽  
Author(s):  
Jose A. Marengo ◽  
Carlos A. Nobre
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Amazon Basin ◽  
Global Climate ◽  
River System ◽  
Climate System ◽  
Wet Season ◽  
Tropospheric Circulation ◽  
The Tropics

The Amazon region is of particular interest because it represents a large source of heat in the tropics and has been shown to have a significant impact on extratropical circulation, and it is Earth’s largest and most intense land-based convective center. During the Southern Hemisphere summer when convection is best developed, the Amazon basin is one of the wettest regions on Earth. Amazonia is of course not isolated from the rest of the world, and a global perspective is needed to understand the nature and causes of climatological anomalies in Amazonia and how they feed back to influence the global climate system. The Amazon River system is the single, largest source of freshwater on Earth. The flow regime of this river system is relatively unimpacted by humans (Vörösmarty et al. 1997 a, b) and is subject to interannual variability in tropical precipitation that ultimately is translated into large variations in downstream hydrographs (Marengo et al. 1998a, Vörösmarty et al. 1996, Richey et al. 1989a, b). The recycling of local evaporation and precipitation by the forest accounts for a sizable portion of the regional water budget (Nobre et al. 1991, Eltahir 1996), and as large areas of the basin are subject to active deforestation there is grave concern about how such land surface disruptions may affect the water cycle in the tropics (see reviews in Lean et al. 1996). Previous studies have emphasized either how large-scale atmospheric circulation or land surface conditions can directly control the seasonal changes in rainfall producing mechanisms. Studies invoking controls of convection and rainfall by large-scale circulation emphasize the relationship between the establishment of upper-tropospheric circulation over Bolivia and moisture transport from the Atlantic ocean for initiation of the wet season and its intensity (see reviews in Marengo et al. 1999). On the other hand, Eltahir and Pal (1996) have shown that Amazon convection is closely related to land surface humidity and temperature, while Fu et al. (1999) indicate that the wet season in the Amazon basin is controlled by both changes in land surface temperature and the sea surface temperature (SST) in the adjacent oceans, depending if the region is north-equatorial or southern Amazonia.

scholarly journals Impact of Subsurface Temperature Variability on Surface Air Temperature Variability: An AGCM Study

2008 ◽  
Vol 9 (4) ◽  
pp. 804-815 ◽  
Author(s):  
Sarith P. P. Mahanama ◽  
Randal D. Koster ◽  
Rolf H. Reichle ◽  
Max J. Suarez
Keyword(s):  
Surface Temperature ◽  
Soil Temperature ◽  
Air Temperature ◽  
Seasonal Cycle ◽  
Surface Air Temperature ◽  
Temperature Variability ◽  
Climate System ◽  
Boreal Summer ◽  
Temperature Anomalies ◽  
Subsurface Soil

Abstract Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies in the subsurface soil. The subsurface soil temperature (and the associated ground heat content) has significant memory—the dissipation of a temperature anomaly may take weeks to months—and thus subsurface soil temperature may contribute to the low-frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses three long-term AGCM experiments to isolate the contribution of subsurface soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of Atmospheric Model Intercomparison Project (AMIP)-type simulations in which the subsurface soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the subsurface soil temperature to the rest of the climate system is disabled; that is, at each grid cell, the local climatological seasonal cycle of subsurface soil temperature (as determined from the first experiment) is prescribed. Finally, a climatological seasonal cycle of sea surface temperature (SST) is prescribed in the third experiment. Together, the three experiments allow the isolation of the contributions of variable SSTs, interactive subsurface soil temperature, and chaotic atmospheric dynamics to meteorological variability. The results show that allowing an interactive subsurface soil temperature does, indeed, significantly increase surface air temperature variability and memory in most regions. In many regions, however, the impact is negligible, particularly during boreal summer.

The Analysis of Thermoelectric Signals in Metallic Sliding

1989 ◽  
Vol 111 (1) ◽  
pp. 114-120 ◽  
Author(s):  
Jui-Hsieh Shen ◽  
C. M. Ettles ◽  
H. A. Scarton
Keyword(s):  
Power Spectrum ◽  
Surface Temperature ◽  
Surface Topography ◽  
Temperature Rise ◽  
Signal Analysis ◽  
Steel Surface ◽  
Power Spectra ◽  
Average Temperature ◽  
Voltage Signal ◽  
Temperature Signal

The thermoelectric signal from an Alumel pin sliding over a steel surface was recorded and analyzed. The load, speed and surface topography were varied and correlations were attempted of the voltage signal against several parameters. The average temperature of the whole contact was found to agree fairly consistently with the surface temperature rise models of Blok and Archard. Of the available methods of signal analysis, the power spectrum of the voltage signal was found to give the best understanding of the micro-mechanisms of sliding, particularly when compared against the power spectra of profilometer signals. The largest component of the temperature signal was found to be caused by wavelength components equal to the extent of the contact. The correlation distance β* of the test surfaces was much less than the contact extent and contributed negligibly to the voltage signal rise.

scholarly journals The Community Climate System Model Version 4

2011 ◽  
Vol 24 (19) ◽  
pp. 4973-4991 ◽  
Author(s):  
Peter R. Gent ◽  
Gokhan Danabasoglu ◽  
Leo J. Donner ◽  
Marika M. Holland ◽  
Elizabeth C. Hunke ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Frequency Distribution ◽  
Arctic Sea Ice ◽  
Climate System ◽  
System Model ◽  
The Arctic ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Arctic Sea

The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Niño–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulation. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than CCSM3, and for several reasons the Arctic sea ice concentration is improved in CCSM4. An ensemble of twentieth-century simulations produces a good match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4°C. This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of shortwave and longwave cloud forcings.

An Exploration of Multivariate Fluctuation Dissipation Operators and Their Response to Sea Surface Temperature Perturbations

2015 ◽  
Vol 72 (1) ◽  
pp. 472-486 ◽  
Author(s):  
David Fuchs ◽  
Steven Sherwood ◽  
Daniel Hernandez
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sample Size ◽  
Southern Oscillation ◽  
Climate System ◽  
Sea Surface ◽  
Cloud Properties ◽  
Fluctuation Dissipation ◽  
Selection Of Variables ◽  
Low Dimensional

Abstract The fluctuation–dissipation theorem (FDT) has been proposed as a method of calculating the mean response of the atmosphere to small external perturbations. This paper explores the application of the theory under time and space constraints that approximate realistic conditions. To date, most applications of the theory in the climate context used univariate, low-dimensional-state representations of the climate system and an arbitrarily long sample size. The authors explore high-dimensional multivariate FDT operators and the lower bounds of sample size needed to construct skillful operators. It is shown that the skill of the operator depends on the selection of variables and features representing the climate system and that these features change once memory (slab ocean) is added to the system. In addition, it is found that the FDT operator has skill in estimating the response to realistic sea surface temperature (SST) patterns, such as El Niño–Southern Oscillation (ENSO), despite the fact that these patterns were not part of the data used to produce the operator. The response of clouds is also studied; for variables that represent cloud properties, the decrease in skill in relation to decrease in sample size still maintains the key features of the response.

scholarly journals Impact of Land–Atmosphere Interactions on Sahel Climate

2017 ◽  
Author(s):  
Yongkang Xue
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
Great Influence ◽  
Climate System ◽  
Sea Surface ◽  
Surface Processes ◽  
Severe Drought ◽  
Land Surface Processes

The Sahel of Africa has been identified as having the strongest land–atmosphere (L/A) interactions on Earth. The Sahelian L/A interaction studies started in the late 1970s. However, due to controversies surrounding the early studies, in which only a single land parameter was considered in L/A interactions, the credibility of land-surface effects on the Sahel’s climate has long been challenged. Using general circulation models and regional climate models coupled with biogeophysical and dynamic vegetation models as well as applying analyses of satellite-derived data, field measurements, and assimilation data, the effects of land-surface processes on West African monsoon variability, which dominates the Sahel climate system at intraseasonal, seasonal, interannual, and decadal scales, as well as mesoscale, have been extensively investigated to realistically explore the Sahel L/A interaction: its effects and the mechanisms involved. The Sahel suffered the longest and most severe drought on the planet in the 20th century. The devastating environmental and socioeconomic consequences resulting from drought-induced famines in the Sahel have provided strong motivation for the scientific community and society to understand the causes of the drought and its impact. It was controversial and under debate whether the drought was a natural process, mainly induced by sea-surface temperature variability, or was affected by anthropogenic activities. Diagnostic and modeling studies of the sea-surface temperature have consistently demonstrated it exerts great influence on the Sahel climate system, but sea-surface temperature is unable to explain the full scope of the Sahel climate variability and the later 20th century’s drought. The effect of land-surface processes, especially land-cover and land-use change, on the drought have also been extensively investigated. The results with more realistic land-surface models suggest land processes are a first-order contributor to the Sahel climate and to its drought during the later 1960s to the 1980s, comparable to sea surface temperature effects. The issues that caused controversies in the early studies have been properly addressed in the studies with state-of-the-art models and available data. The mechanisms through which land processes affect the atmosphere are also elucidated in a number of studies. Land-surface processes not only affect vertical transfer of radiative fluxes and heat fluxes but also affect horizontal advections through their effect on the atmospheric heating rate and moisture flux convergence/divergence as well as horizontal temperature gradients.

The Low-Resolution CCSM4

2012 ◽  
Vol 25 (12) ◽  
pp. 3993-4014 ◽  
Author(s):  
Christine A. Shields ◽  
David A. Bailey ◽  
Gokhan Danabasoglu ◽  
Markus Jochum ◽  
Jeffrey T. Kiehl ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Historical Record ◽  
Climate System ◽  
System Model ◽  
Computationally Efficient ◽  
Low Resolution ◽  
Sea Ice Extent ◽  
Climate System Model ◽  
Dynamical Core ◽  
Horizontal Grid

Abstract The low-resolution version of the Community Climate System Model, version 4 (CCSM4) is a computationally efficient alternative to the intermediate and standard resolution versions of this fully coupled climate system model. It employs an atmospheric horizontal grid of 3.75° × 3.75° and 26 levels in the vertical with a spectral dynamical core (T31) and an oceanic horizontal grid that consists of a nominal 3° resolution with 60 levels in the vertical. This low-resolution version (T31x3) can be used for a variety of applications including long equilibrium simulations, development work, and sensitivity studies. The T31x3 model is validated for modern conditions by comparing to available observations. Significant problems exist for Northern Hemisphere Arctic locales where sea ice extent and thickness are excessive. This is partially due to low heat transport in T31x3, which translates into a globally averaged sea surface temperature (SST) bias of −1.54°C compared to observational estimates from the 1870–99 historical record and a bias of −1.26°C compared to observations from the 1986–2005 historical record. Maximum zonal wind stress magnitude in the Southern Hemisphere matches observational estimates over the ocean, although its placement is incorrectly displaced equatorward. Aspects of climate variability in T31x3 compare to observed variability, especially so for ENSO where the amplitude and period approximate observations. T31x3 surface temperature anomaly trends for the twentieth century also follow observations. An examination of the T31x3 model relative to the intermediate CCSM4 resolution (finite volume dynamical core 1.9° × 2.5°) for preindustrial conditions shows the T31x3 model approximates this solution for climate state and variability metrics examined here.

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