This happens for every DO event, and it is a peculiar and tell - tale pattern that is also found
in model simulations of these events (see graph).
A recent study led by Lawrence Livermore National Laboratory climate scientist Ben Santer found that while the models ran hot, the «overestimation» was «partly due to systematic deficiencies in some of the post-2000 external forcings
used in the model simulations.»
To be sure, this isn't a demonstration that the tropical
trends in the model simulations or the data are perfectly matched — there remain multiple issues with moist convection parameterisations, the Madden - Julian oscillation, ENSO, the «double ITCZ» problem, biases, drifts etc..
Out of several factors we
considered in our model simulation, only one (sulphuric acid) could have made the surface ocean severely corrosive to calcite, but even then the amounts of sulphur required are unfeasibly large.
Böning, C.W., et al., 1995: An overlooked
problem in model simulations of the thermohaline circulation and heat transports in the Atlantic Ocean.
These uncertainties are
reflected in the model simulations of aerosol concentrations which all show similar total amounts, but have very different partitions among the different types.
However, the occurrence of El Niño
events in any model simulation is uncorrelated with their occurrence in the real world and so special care is needed to estimate their impact.
In a related paper, Santer et al compare the surface / lower - troposphere coupled tropical variability at different timescales in the data and
in model simulations performed for the new IPCC assessment.
The greater increases in erosion in the GGa1 scenario was attributed to greater variability in monthly precipitation and an increased frequency of large
storms in the model simulation.
The criticism mainly focused on the conceptual use of untested methods of CDR to keep global warming below 2C above pre-industrial
levels in model simulations, the potential risks of deploying CDR technologies at scale, and the role of science in climate policy negotiations.
For example, analysis of these measures shows a decrease in heating degree days for Canada and an increase in cooling degree days in the southwest
USA in model simulations of future climate with increased greenhouse gases (Zwiers and Kharin, 1998; Kharin and Zwiers, 2000), though this can be considered a general feature associated with an increase in temperature.
That means the observed warming is beyond the variability seen
in model simulations where greenhouse gases are kept constant, but is exactly what the models predict for a world in which humans change the composition of the atmosphere.
Inferences on sub-continental scales are indicative rather than definitive because of the absence of locally important forcings and
processes in model simulations, as well as model biases
As part of a European project (High Resolution Ten - Year Climate Simulations, HIRETYCS, 1998), it was found that increases in horizontal resolution did not produce systematic
improvements in model simulations and any improvements found were of modest amplitude.
The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether
absent in model simulations.
Our past work has shown that the lack of good observations in many parts of the world can badly distort the detected
trend in model simulations, losing much of the underlying signal of anthropogenic change.
In the model simulation, year - round ice - free conditions caused warmer conditions in the Arctic because the open water surface allowed for evaporation.
In the model simulations, that warming produced broadly similar cloud patterns to warming caused by greenhouse gases.
The period 1901 - 1960 is used for graphs that illustrate past changes in climate conditions, whether in observations or
in model simulations.
Figure 1: Past and projected abundances for carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), chlorofluorocarbons (CFCs), and chlorine (Cly) used
in the model simulation.
Because the model parameterizations are not scale aware, increased precipitation produces zonally asymmetric climate circulation patterns that characterize the «errors»
in the model simulations.
They found that,
in the model simulations, temperatures increased in all regions during the twenty - first century, and precipitation decreased the most in Central America, southern South America, the Mediterranean and northern Africa, Central Asia, southern Africa and Australia.