Synoptic sea-level pressure patterns generated by a general circulation model: comparison with types derived from NCEP/NCAR re-analysis and implications for downscaling

2006 ◽  
Vol 26 (12) ◽  
pp. 1727-1736 ◽  
Author(s):  
I. G. McKendry ◽  
K. Stahl ◽  
R. D. Moore
Keyword(s):  
Sea Level ◽  
General Circulation Model ◽  
General Circulation ◽  
Model Comparison ◽  
Circulation Model ◽  
Sea Level Pressure ◽  
Level Pressure

Stratospheric trace constituents simulated by a three-dimensional general circulation model: Comparison with UARS data

1995 ◽  
Vol 100 (D7) ◽  
pp. 13951 ◽  
Author(s):  
Richard S. Eckman ◽  
William L. Grose ◽  
Richard E. Turner ◽  
W. Thomas Blackshear ◽  
James M. Russell ◽  
...  
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Model Comparison ◽  
Three Dimensional ◽  
Circulation Model ◽  
Trace Constituents

scholarly journals The response of the Greenland ice sheet to climate changes in the 21st century by interactive coupling of an AOGCM with a thermomechanical ice-sheet model

2002 ◽  
Vol 35 ◽  
pp. 409-415 ◽  
Author(s):  
Philippe Huybrechts ◽  
Ives Janssens ◽  
Chantal Poncin ◽  
Thierry Fichefet
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Sea Level Rise ◽  
Sea Level ◽  
Fresh Water ◽  
General Circulation Model ◽  
General Circulation ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Circulation Model

AbstractWe present results from a greenhouse warming experiment obtained from an atmosphere–ocean–sea-ice general circulation model that is interactively coupled with a three-dimensional model of the Greenland ice sheet. the experiment covers the period 1970–2099 and is driven by the mid-range Intergovernmental Panel on Climate Change SRESB2 scenario. the Greenland model is a thermomechanical high-resolution (20 km) model coupled with a viscoelastic bedrock model. the melt-and-runoff model is based on the positive degree-day method and includes meltwater retention in the snowpack and the formation of superimposed ice. the atmospheric–oceanic general circulation model (AOGCM) is a coarse-resolution model without flux correction based on the Laboratoire de Météorologie Dynamique (Paris) LMD 5.3 atmospheric model coupled with a primitive-equation, free-surface oceanic component incorporating sea ice (coupled large-scale ice–ocean (CLIO)). By 2100, average Greenland annual temperature is found to rise by about 4.5˚C and mean precipitation by about 35%. the total fresh-water flux approximately doubles over this period due to increased runoff from the ice sheet and the ice-free land, but the calving rate is found to decrease by 25%. the ice sheet shrinks equivalent to 4 cm of sea-level rise. the contribution from the background evolution is not more than 5% of the total predicted sea-level rise. We did not find significant changes in the patterns of climate change over the North Atlantic region compared with a climate-change run without Greenland fresh-water feedback.

scholarly journals Summertime circumglobal Rossby waves in climate models: Small biases in upper-level circulation create substantial biases in surface imprint

2021 ◽  
Author(s):  
Fei Luo ◽  
Frank Selten ◽  
Kathrin Wehrli ◽  
Kai Kornhuber ◽  
Philippe Le Sager ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Sea Level ◽  
General Circulation ◽  
Climate Models ◽  
Rossby Waves ◽  
Boreal Summer ◽  
Sea Level Pressure ◽  
Near Surface ◽  
Level Pressure ◽  
Upper Level

Abstract. In boreal summer, circumglobal Rossby waves can promote stagnating weather systems that favor extreme events like heatwaves or droughts. Recent work highlighted the risks associated with amplified Rossby wavenumber 5 and 7 in triggering simultaneous warm anomalies in specific agricultural breadbaskets in the Northern Hemisphere. These type of wave patterns thus pose potential risks for food production, as well as human health, and other impacts. The representation of such summertime wave events and their surface imprints in general circulation models (GCMs) has not been  systematically analyzed. Here we validate three state-of-the-art global climate models (EC-Earth, CESM, and MIROC), quantify their biases and provide insights into the underlying physical reasons for the biases. To do so, the ExtremeX  experiments output data were used, which are (1) historic simulations (1979–2015/2016) of a freely running atmosphere with prescribed ocean, and experiments that additionally nudge toward the observed (2) upper-level horizontal winds in the atmosphere, (3) soil moisture conditions, or (4) both. The nudged experiments are used to trace the sources of the model biases to either the large-scale atmospheric circulation or surface feedback processes. We show that while the wave position and magnitude is represented well compared to ERA5 reanalysis data. During high amplitudes (> 1.5 s.d.) wave-5 and wave- 7 events, the imprint on surface variables temperature, precipitation and sea level pressure is substantially underestimated: typically, by a factor of 1.5 in correlation and normalized standard deviations (n.s.d.) for near-surface temperature and mean sea level pressure. As for the precipitation, it’s still a factor of 1.5 for n.s.d. but 2 for correlation. The correlations and n.s.d. for surface variables do not improve if only the soil moisture is prescribed, but considerably increased when the upper-level atmosphere circulation is nudged. The underestimation factors are corrected almost entirely. When applying both soil moisture prescription and the nudging of upper-level atmosphere, both the correlation and n.s.d. values are quite similar to  only atmosphere component is nudged experiments. Hence, the near-surface biases can be substantially improved when nudging the upper-level circulation providing evidence that relatively small biases in the models’ representation of the upper-level waves can strongly affect associated temperature and rainfall anomalies.

scholarly journals Long-term evolution of Caspian Sea thermohaline properties reconstructed in an eddy-resolving ocean general circulation model

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 527-541 ◽  
Author(s):  
Gleb S. Dyakonov ◽  
Rashit A. Ibrayev
Keyword(s):  
Sea Level ◽  
General Circulation Model ◽  
Caspian Sea ◽  
General Circulation ◽  
Global Climate ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Atmospheric Conditions ◽  
Ocean General Circulation

Abstract. Decadal variability in Caspian Sea thermohaline properties is investigated using a high-resolution ocean general circulation model including sea ice thermodynamics and air–sea interaction forced by prescribed realistic atmospheric conditions and riverine runoff. The model describes synoptic, seasonal and climatic variations of sea thermohaline structure, water balance, and sea level. A reconstruction experiment was conducted for the period of 1961–2001, covering a major regime shift in the global climate during 1976–1978, which allowed for an investigation of the Caspian Sea response to such significant episodes of climate variability. The model reproduced sea level evolution reasonably well despite the fact that many factors (such as possible seabed changes and insufficiently explored underground water infiltration) were not taken into account in the numerical reconstruction. This supports the hypothesis relating rapid Caspian Sea level rise in 1978–1995 with global climate change, which caused variation in local atmospheric conditions and riverine discharge reflected in the external forcing data used, as is shown in the paper. Other effects of the climatic shift are investigated, including a decrease in salinity in the active layer, strengthening of its stratification and corresponding diminishing of convection. It is also demonstrated that water exchange between the three Caspian basins (northern, middle and southern) plays a crucial role in the formation of their thermohaline regime. The reconstructed long-term trends in seawater salinity (general downtrend after 1978), temperature (overall increase) and density (general downtrend) are studied, including an assessment of the influence of main surface circulation patterns and model error accumulation.

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