Time-dependent response of a zonally averaged ocean–atmosphere–sea ice model to Milankovitch forcing

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer-Verlag for personal use, not for redistribution. The definitive version was published in Climate Dynamics 6 (2010): 763-779, doi:10.1007/s00382-010-0790-6.An ocean-atmosphere-sea ice model is developed to explore the time-dependent response of climate to Milankovitch forcing for the time interval 5-3 Myr BP. The ocean component is a zonally averaged model of the circulation in five basins (Arctic, Atlantic, Indian, Pacific, and Southern Oceans). The atmospheric component is a one-dimensional (latitudinal) energy balance model, and the sea-ice component is a thermodynamic model. Two numerical experiments are conducted. The first experiment does not include sea ice and the Arctic Ocean; the second experiment does. Results from the two experiments are used to investigate (i) the response of annual mean surface air and ocean temperatures to Milankovitch forcing, and (ii) the role of sea ice in this response. In both experiments, the response of air temperature is dominated by obliquity cycles at most latitudes. On the other hand, the response of ocean temperature varies with latitude and depth. Deep water formed between 45°N-65°N in the Atlantic Ocean mainly responds to precession. In contrast, deep water formed south of 60°S responds to obliquity when sea ice is not included. Sea ice acts as a time-integrator of summer insolation changes such that annual mean sea-ice conditions mainly respond to obliquity. Thus, in the presence of sea ice, air temperature changes over the sea ice are amplified, and temperature changes in deep water of southern origin are suppressed since water below sea ice is kept near the freezing point.This work was supported by an NSERC Discovery Grant awarded to L.A.M. We also thank GEC3 for a Network Grant

What is the fate of the river waters of Hudson Bay?

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 88 (2011): 352-361, doi:10.1016/j.jmarsys.2011.02.004.We examine the freshwater balance of Hudson and James bays, two shallow and fresh seas that annually receive 12% of the pan- Arctic river runoff. The analyses use the results from a 3–D sea ice-ocean coupled model with realistic forcing for tides, rivers, ocean boundaries, precipitation, and winds. The model simulations show that the annual freshwater balance is essentially between the river input and a large outflow toward the Labrador shelf. River waters are seasonally exchanged from the nearshore region to the interior of the basin, and the volumes exchanged are substantial (of the same order of magnitude as the annual river input). This lateral exchange is mostly caused by Ekman transport, and its magnitude and variability are controlled by the curl of the stress at the surface of the basin. The average transit time of the river waters is 3.0 years, meaning that the outflow is a complex mixture of the runoff from the three preceding years.We thank NSERC and the Canada Research Chairs program for funding. FS acknowledges support from NSF OCE-0751554 and ONR N00014-08-10490

Predicting climate change using response theory: global averages and spatial patterns

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(105105) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO22 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change

A decade of acoustic thermometry in the North Pacific Ocean

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94643/1/jgrc11250.pd

DOE Climate Change Prediction Program

This essay is from: NERSC Annual Report 2002' edited by John Hules Publication Date: 01-31-2003 Abstract: The National Energy Research Scientific Computing Center (NERSC) is the primary computational resource for scientific research funded by the DOE Office of Science. The Annual Report for FY2002 includes a summary of recent computational science conducted on NERSC systems (with abstracts of significant and representativeScientists in the DOE Climate Change Prediction Program recently completed a 1,000-year run of a powerful new climate system model on a supercomputer at NERSC. The millennium long simulation of the new Community Climate System Model (CCSM2) ran for more than 200 uninterrupted days on the IBM SP supercomputer at NERSC. The lengthy run served as a kind of “shakedown cruise” for the new version of the climate model and demonstrated that its variability is stable, even when run for century-after-century simulations. The 1,000-year CCSM2 run had a total drift of just one-half of one degree Celsius, compared to older versions with two to three times as much variance.Department of Energ

U.K. HiGEM: the new U.K. high-resolution global environment model - model description and basic evaluation

This article describes the development and evaluation of the U.K.’s new High-Resolution Global Environmental Model (HiGEM), which is based on the latest climate configuration of the Met Office Unified Model, known as the Hadley Centre Global Environmental Model, version 1 (HadGEM1). In HiGEM, the horizontal resolution has been increased to 0.83° latitude × 1.25° longitude for the atmosphere, and 1/3° × 1/3° globally for the ocean. Multidecadal integrations of HiGEM, and the lower-resolution HadGEM, are used to explore the impact of resolution on the fidelity of climate simulations.Generally, SST errors are reduced in HiGEM. Cold SST errors associated with the path of the North Atlantic drift improve, and warm SST errors are reduced in upwelling stratocumulus regions where the simulation of low-level cloud is better at higher resolution. The ocean model in HiGEM allows ocean eddies to be partially resolved, which dramatically improves the representation of sea surface height variability. In the Southern Ocean, most of the heat transports in HiGEM is achieved by resolved eddy motions, which replaces the parameterized eddy heat transport in the lower-resolution model. HiGEM is also able to more realistically simulate small-scale features in the wind stress curl around islands and oceanic SST fronts, which may have implications for oceanic upwelling and ocean biology.Higher resolution in both the atmosphere and the ocean allows coupling to occur on small spatial scales. In particular, the small-scale interaction recently seen in satellite imagery between the atmosphere and tropical instability waves in the tropical Pacific Ocean is realistically captured in HiGEM. Tropical instability waves play a role in improving the simulation of the mean state of the tropical Pacific, which has important implications for climate variability. In particular, all aspects of the simulation of ENSO (spatial patterns, the time scales at which ENSO occurs, and global teleconnections) are much improved in HiGEM.<br/