Does Model Sensitivity to Changes in CO2 Provide a Measure of Sensitivity to the Forcing of Different Nature?

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).Simulation of both the climate of the 20th century and of possible future climate change requires taking into account numerous forcings of different nature. Climate sensitivities of existing general circulation models, defined as the equilibrium surface warming due to increase in atmospheric CO2 concentrations, vary over a rather wide range. A large number of simulations with the MIT climate model of intermediate complexity with forcings of different nature have been carried out to study to what extent sensitivity to changes in CO2 concentration represent sensitivities to other forcings. Sensitivity of the MIT model can be changed by changing the strength of the cloud feedback. Simulations with the versions of the model with different sensitivities show that the sensitivity to changes in CO2 concentration provides a reasonably good measure of the model sensitivity to other forcings with similar vertical stratifications. However the range of models’ responses to the forcings leading to the cooling of the surface is narrower than the range of models’ responses to the forcings leading to warming. This is explained by the cloud feedback being less efficient in the case of increasing sea ice extent and snow cover. The range of models’ responses to the forcings with different vertical structure, such as increase in black carbon concentration, is also smaller than that for changes in CO2 concentration

Sensitivity of Climate Change Projections to Uncertainties in the Estimates of Observed Changes in Deep-Ocean Heat Content

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).The MIT 2D climate model is used to make probabilistic projections for changes in global mean surface temperature and for thermosteric sea level rise under a variety of forcing scenarios. The uncertainties in climate sensitivity and rate of heat uptake by the deep ocean are quantified by using the probability distributions derived from observed 20th century temperature changes. The impact on climate change projections of using the smallest and largest estimates of 20th century deep ocean warming is explored. The impact is large in the case of global mean thermosteric sea level rise. In the MIT reference ("business as usual") scenario the median rise by 2100 is 27 and 43 cm in the respective cases. The impact on increases in global mean surface air temperature is more modest, 4.9 C and 3.9 C in the two respective cases, because of the correlation between climate sensitivity and ocean heat uptake required by 20th century surface and upper air temperature changes. The results are also compared with the projections made by the IPCC AR4's multi-model ensemble for several of the SRES scenarios. The multi-model projections are more consistent with the MIT projections based on the largest estimate of ocean warming. However the range for the rate of heat uptake by the ocean suggested by the lowest estimate of ocean warming is more consistent with the range suggested by the 20th century changes in surface and upper air temperatures, combined with expert prior for climate sensitivity.This work was supported in part by the Office of Science (BER), U.S. Dept. of Energy Grant No. DE-FG02-93ER61677, NSF, and by the MIT Joint Program on the Science and Policy of Global Change

Implementation of a Cloud Radiative Adjustment Method to Change the Climate Sensitivity of CAM3

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).Conducting probabilistic climate projections with a particular climate model requires the ability to vary the model’s characteristics, such as its climate sensitivity. In this study, we implement and validate a method to change the climate sensitivity of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 3 (CAM3) through a cloud radiative adjustment. Results show that the cloud radiative adjustment method does not lead to physically unrealistic changes in the model’s response to an external forcing, such as doubling CO2 concentrations or increasing sulfate aerosol concentrations. Furthermore, this method has some advantages compared to the traditional perturbed physics approach. In particular, the cloud radiative adjustment method can produce any value of climate sensitivity within the wide range of uncertainty based on the observed 20th century climate change. As a consequence, this method allows Monte Carlo type probabilistic climate forecasts to be conducted where values of uncertain parameters not only cover the whole uncertainty range, but cover it homogeneously. Unlike the perturbed physics approach which can produce several versions of a model with the same climate sensitivity but with very different regional patterns of change, the cloud radiative adjustment method can only produce one version of the model with a specific climate sensitivity. As such, a limitation of this method is that it cannot cover the full uncertainty in regional patterns of climate change.This study received support from the MIT Joint Program on the Science and Policy of Global Change, which is funded by a consortium of government, industry and foundation sponsors

Estimated PDFs of Climate System Properties Including Natural and Anthropogenic Forcings

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).We present revised probability density functions (PDF) for climate system properties (climate sensitivity, rate of deep-ocean heat uptake, and the net aerosol forcing strength) that include the effect on 20th century temperature changes of natural as well as anthropogenic forcings. The additional natural forcings, primarily the cooling by volcanic eruptions, affect the PDF by requiring a higher climate sensitivity and a lower rate of deep-ocean heat uptake to reproduce the observed temperature changes. The estimated 90% range of climate sensitivity is 2.4 to 9.2 K. The net aerosol forcing strength for the 1980s decade shifted towards positive values to compensate for the now included volcanic forcing with 90% bounds of -0.7 to -0.16 W/m2. The rate of deep-ocean heat uptake is also reduced with the effective diffusivity, Kv, ranging from 0.25 to 7.3 cm2/s. This upper bound implies that many coupled atmosphere-ocean GCMs mix heat into the deep ocean (below the mixed layer) too efficiently.This work was supported in part by the NOAA Climate Change Data and Detection Program with support from DOE, the Joint Program on the Science and Policy of Global Change at MIT, and the Office of Science (BER) DOE Grant No.DE-FG02-93ER61677

Constraining Climate Model Parameters from Observed 20th Century Changes

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).We present revised probability density functions for climate model parameters (effective climate sensitivity, the rate of deep-ocean heat uptake, and the strength of the net aerosol forcing) that are based on climate change observations from the 20th century. First, we compare observed changes in surface, upper-air, and deep-ocean temperature changes against simulations of 20th century climate in which the climate model parameters were systematically varied. The estimated 90% range of climate sensitivity is 2.0 to 5.0 K. The net aerosol forcing strength for the 1980s has 90% bounds of -0.70 to -0.27 W/m2. The rate of deep-ocean heat uptake corresponds to an effective diffusivity, Kv, with a 90% range of 0.04 to 4.1 cm2/s. Second, we estimate the effective climate sensitivity and rate of deep-ocean heat uptake for 11 of the IPCC AR4 AOGCMs. By comparing against the acceptable combinations inferred by the observations, we conclude that the rate of deep-ocean heat uptake for the majority of AOGCMs lie above the observationally based median value. This implies a bias in the predictions inferred from the IPCC models alone. This bias can be seen in the range of transient climate response from the AOGCMs as compared to that from the observational constraints.This work was supported in part by the Office of Science (BER), U.S. Dept. of Energy Grant No. DE-FG02-93ER61677, NSF, and by the MIT Joint Program on the Science and Policy of Global Change

A Three-Dimensional Ocean-Seaice-Carbon Cycle Model and its Coupling to a Two-Dimensional Atmospheric Model: Uses in Climate Change Studies

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).We describe the coupling of a three-dimensional ocean circulation model, with explicit thermodynamic seaice and ocean carbon cycle representations, to a two-dimensional atmospheric/land model. This coupled system has been developed as an efficient and flexible tool with which to investigate future climate change scenarios. The setup is sufficiently fast for large ensemble simulations that address uncertainties in future climate modeling. However, the ocean component is detailed enough to provide a tool for looking at the mechanisms and feedbacks that are essential for understanding the future changes in the ocean system. Here we show results from a single example simulation: a spin-up to pre-industrial steady state, changes to ocean physical and biogeochemical states for the 20th century (where changes in greenhouse gases and aerosol concentrations are taken from observations) and predictions of further changes for the 21st century in response to increased greenhouse gas and aerosol emissions. We plan, in future studies to use this model to investigate processes important to the heat uptake of the oceans, changes to the ocean circulation and mechanisms of carbon uptake and how these will change in future climate scenarios

The Influence on Climate Change of Differing Scenarios for Future Development Analyzed Using the MIT Integrated Global System Model

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).A wide variety of scenarios for future development have played significant roles in climate policy discussions. This paper presents projections of greenhouse gas (GHG) concentrations, sea level rise due to thermal expansion and glacial melt, oceanic acidity, and global mean temperature increases computed with the MIT Integrated Global Systems Model (IGSM) using scenarios for 21st century emissions developed by three different groups: intergovernmental (represented by the Intergovernmental Panel on Climate Change), government (represented by the U.S. government Climate Change Science Program) and industry (represented by Royal Dutch Shell plc). In all these scenarios the climate system undergoes substantial changes. By 2100, the CO2 concentration ranges from 470 to 1020 ppm compared to a 2000 level of 365 ppm, the CO2-equivalent concentration of all greenhouse gases ranges from 550 to 1780 ppm in comparison to a 2000 level of 415 ppm, sea level rises by 24 to 56 cm relative to 2000 due to thermal expansion and glacial melt, oceanic acidity changes from a current pH of around 8 to a range from 7.63 to 7.91. The global mean temperature increases by 1.8 to 7.0 degrees C relative to 2000.The IGSM model used here is supported by the U.S. Department of Energy, U.S. Environmental Protection Agency, U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, U.S. National Oceanographic and Atmospheric Administration and the Industry and Foundation Sponsors of the MIT Joint Program on the Science and Policy of Global Change

Evaluating the Use of Ocean Models of Different Complexity in Climate Change Studies

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).The study of the uncertainties in future climate projections requires large ensembles of simulations with different values of model characteristics that define its response to external forcing. These characteristic include climate sensitivity, strength of aerosol forcing and the rate of ocean heat uptake. The latter can be easily varied over a wide range in an anomaly diffusing ocean model (ADOM). The rate of heat uptake in a three-dimensional ocean general circulation model (OGCM) is, however, defined by large number of factors and is far more difficult to vary. Necessity to obtain a realistic ocean circulation places additional constraints, making it impossible to cover the range of values suggested by observations. As a result, a simpler model like an ADOM needs to be used in uncertainty studies. To evaluate the performance of the ADOM on different time scales we compare results of simulations with two versions of the MIT Integrated Global System Model (IGSM): one with a ADOM and the second with a full three-dimensional OCGM. Our results show that through the 20th and 21st century, the version of the IGSM with ADOM is able to reproduce important aspects of the climate response simulated by the version with the OCGM. However, the inability of the ADOM to depict feedbacks associated with the changes in the ocean circulation significantly affects its performance on the longer timescales. In particular, the ADOM overestimates sea level rise due to thermal expansion of the deep ocean. It also rather poorly depicts long term changes in oceanic carbon uptake, leading to underestimation of the atmospheric CO2 concentrations. Thus, the IGSM version with ADOM can be used to obtain probability distributions of changes in many of the important climate variables through the end of 21st century. On the other hand, studying longer-term climate change requires the use of the OGCM.This research was supported by the U.S Department of Energy, U.S. Environmental Protection Agency, U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, U.S. National Oceanographic and Atmospheric Administration; and the Industry and Foundation Sponsors of the MIT Joint Program on the Science and Policy of Global Change: Alstom Power (France), American Electric Power (USA), Chevron Corporation (USA), CONCAWE (Belgium), DaimlerChrysler AG (Germany), Duke Energy (USA), J-Power (Japan), Electric Power Research Institute (USA), Electricité de France, ExxonMobil Corporation (USA), Ford Motor Company (USA), General Motors (USA), Murphy Oil Corporation (USA), Oglethorpe Power Corporation (USA), RWE Power (Germany), Schlumberger (USA), Shell Petroleum (Netherlands/UK), Southern Company (USA), Statoil ASA (Norway), Tennessee Valley Authority (USA), Tokyo Electric Power Company (Japan), Total (France), G. Unger Vetlesen Foundation (USA)