Why there is a Warm Bias in the Existing Analyses of the Global Average Surface Temperature

Readers of this weblog know that there have been comments on the warm bias that we have identified, as reported in Matsui and Pielke, GRL, 2005, with respect to the global analysis of surface temperature trends. This is an important issue as this climate metric is used as an icon to communicate the concept of global warming to policymakers. The abstract of the Parker 2004 Nature paper , for example, stated that the

“Controversy has persisted over the influence of urban warming on reported large-scale surface-air temperature trends. Urban heat islands occur mainly at night and are reduced in windy conditions. Here we show that, globally, temperatures over land have risen as much on windy nights as on calm nights, indicating that the observed overall warming is not a consequence of urban development.â€?

Parker 2004 has been used as evidence to argue that the global surface temperature trends are robust (e.g. CCSP, 2006). In the Matsui and Pielke paper, we show, however, that trends of surface air temperature should not be expected to have the same values for the different sets of days used in the Parker paper. Based on well understood concepts of boundary level meteorology, because Parker found similar trends, there necessarily must be some error in Parker’s analysis. For those unfamiliar with boundary layer meteorology, the reason for this is that minimum temperatures on calm nights should in fact show a larger warming trend than on windy nights (explained below), and not the identical trends reported by Parker. We were motivated to look at this subject because of the obvious inconsistency in the Parker results, and what we found has much broader implications for the long-term surface temperature record.

Studies of the lower levels of the atmosphere (lowest tens of meters) show that it cools at night when winds do not move warm air into the area. This cooling occurs as heat is lost to space. For this reason, minimum daily temperatures typically occur near sunrise, due to cooling overnight. The nighttime cooling varies with height. With light winds, the cooling is greater near the surface and less aloft, while with stronger winds, which are associated with greater mixing of the air above a particular location, the cooling rate is more uniform with height. Light and strong winds can be documented at a particular location from observed wind data.

The rate of heat loss to space is dependent on several factors, including cloudiness and the local atmospheric concentrations of carbon dioxide and of water vapor. Under cloudy conditions, the cooling is much less. Similarly, an atmosphere with higher concentrations of the greenhouse gases, CO2 and H2O, also reduces the cooling at night. Consequently, if there is a long-term trend in greenhouse gas concentrations or cloudiness it will introduce a bias in the observational record of minimum temperatures that will necessarily result in a bias in the long-term surface temperature record.

Because of changes to the atmosphere over the past century, there are several reasons why we should expect the nighttime cooling in the lower atmosphere to have been reduced. One reason for this is that carbon dioxide concentrations have increased, such that the local effect of greenhouse gas concentrations on temperature measurements is larger. Also, an increase of cloudiness has been reported which has the effect of reducing nighttime cooling. An increase in water vapor content in the lower atmosphere would also reduce the cooling rate at night.

Our paper shows that in such circumstances where nighttime cooling is reduced systematically over time, i.e., under trends of greater atmospheric greenhouse gases or an increase in cloudiness, the resulting effect will be to increase minimum temperatures from what they would have been absent the reduced nighttime cooling. This increase in minimum temperatures is greater on nights with light winds than nights with strong winds, due to the mixing of air, and can be on the order of 1 degree C in the lowest 10m above the ground. Minimum daily temperatures are of course important because they are used as input to calculate the daily temperatures that comprise the long-term surface temperature record.

When there is a long-term trend of a reduction in nighttime cooling, then when temperature data are collected, the combination of all of the minimum temperatures on light and strong wind nights will result in an overstatement of warming trends by tenths of a degree. (Note that this assumes that the overall reduction of nighttime cooling such as due to more cloudiness over time and/or increases in the atmospheric concentration of carbon dioxide and/or water vapor is on the order of 1 watt per meter squared. Based on the IPCC, 2001 findings, this is a reasonable estimate of the change over the recent decades in the atmospheric radiative forcing).

What this means is that because (a) the land surface temperature record does in fact combine temperature measurements of light wind and windy nights and (b) there has been a reduction in nighttime cooling, the long-term temperature record may be contaminated by a warm bias that accentuates the observed trend of warmer temperatures. Such a bias would be of similar or larger magnitude to those biases recently discussed in the context of global satellite measurements of temperature. The reduction in nighttime cooling that leads to this bias may indeed be the result of human interference in the climate system (i.e., local effects of increasing greenhouse gases or human effects on cloud cover), but through a causal mechanism different than that typically assumed.

This effect results from a systemic microclimate effect in temperature data which are present in the global temperature record, but are unaccounted for in current analyses. This raises the possibility that those GCMs that appear to accurately represent global average temperature trends over recent decades may be obtaining results that look right when compared to data, but for the wrong physical reasons. If so, this would call into question their ability to accurately predict the future evolution of the climate system.

The broader implications of Matsui and Pielke (2005), which will be well understood by anyone with an understanding of the physics of the lower atmosphere, should cause consternation among anyone who uses the global temperature trend record for scientific or policy purposes. As we have emphasized here (as have others, such as Hansen, Levitus, Barnett, Willis) a more meaningful metric than global average temperature to assess global warming is ocean heat content.

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