James Hansen, head of the NASA Goddard Institute for Space Studies, has penned an essay/article titled “The Temperature of Science” in which he gives his perspectives on the politicization of climate science and describes his groups temperature monitoring program and products. I excerpt highlights below, but you can download the entire file here.
The Temperature of Science by James Hansen
Background: My experience with global temperature data over 30 years provides insight about how the science and its public perception have changed. In the late 1970s I became curious about well- known analyses of global temperature change published by climatologist J. Murray Mitchell: why were his estimates for large-scale temperature change restricted to northern latitudes? As a planetary scientist, it seemed to me there were enough data points in the Southern Hemisphere to allow useful estimates both for that hemisphere and for the global average. So I requested a tape of meteorological station data from Roy Jenne of the National Center for Atmospheric Research, who obtained the data from records of the World Meteorological Organization, and I made my own analysis.
Fast forward to December 2009, when I gave a talk at the Progressive Forum in Houston Texas. The organizers there felt it necessary that I have a police escort between my hotel and the forum where I spoke. Days earlier bloggers reported that I was probably the hacker who broke into East Anglia computers and stole e-mails. Their rationale: I was not implicated in any of the pirated e-mails, so I must have eliminated incriminating messages before releasing the hacked e- mails. The next day another popular blog concluded that I deserved capital punishment. Web chatter on this topic, including indignation that I was coming to Texas, led to a police escort.
GISS data updates: Each month we receive, electronically, data from three sources: weather data for several thousand meteorological stations, satellite observations of sea surface temperature, and Antarctic research station measurements. These three data sets are the input for a program that produces a global map of temperature anomalies relative to the mean for that month during the period of climatology, 1951-1980.The analysis method works in terms of temperature anomalies, rather than absolute temperature, because anomalies present a smoother geographical field than temperature itself. For example, when New York City has an unusually cold winter, it is likely that Philadelphia is also colder than normal. The distance over which temperature anomalies are highly correlated is of the order of 1000 kilometers at middle and high latitudes, as we illustrated in our 1987 paper.
Although the three input data streams that we use are publicly available from the organizations that produce them, we began preserving the complete input data sets each month in April 2008. These data sets, which cover the full period of our analysis, 1880-present, are available to parties interested in performing their own analysis or checking our analysis. The computer program that performs our analysis is published on the GISS web site.
Note, the GISS updates can be viewed, data can be downloaded, etc here.
The different hemispheric records in the mid-twentieth century have never been convincingly explained. The most likely explanation is atmospheric aerosols, fine particles in the air, produced by fossil fuel burning. Aerosol atmospheric lifetime is only several days, so fossil fuel aerosols were confined mainly to the Northern Hemisphere, where most fossil fuels were burned. Aerosols have a cooling effect that still today is estimated to counteract about half of the warming effect of human-made greenhouse gases. For the few decades after World War II, until the oil embargo in the 1970s, fossil fuel use expanded exponentially at more than 4%/year, likely causing the growth of aerosol climate forcing to exceed that of greenhouse gases in the Northern Hemisphere. However, there are no aerosol measurements to confirm that interpretation. If there were adequate understanding of the relation between fossil fuel burning and aerosol properties it would be possible to infer the aerosol properties in the past century. But such understanding requires global measurements of aerosols with sufficient detail to define their properties and their effect on clouds, a task that remains elusive…
Flaws in temperature analysis. Figure 2 illustrates an error that developed in the GISS analysis when we introduced, in our 2001 paper, an improvement in the United States temperature record. The change consisted of using the newest USHCN (United States Historical Climatology Network) analysis for those U.S. stations that are part of the USHCN network. This improvement, developed by NOAA researchers, adjusted station records that included station moves or other discontinuities. Unfortunately, I made an error by failing to recognize that the station records we obtained electronically from NOAA each month, for these same stations, did not contain the adjustments. Thus there was a discontinuity in 2000 in the records of those stations, as the prior years contained the adjustment while later years did not.
The error was readily corrected, once it was recognized. Figure 2 shows the global and U.S. temperatures with and without the error. The error averaged 0.15°C over the contiguous 48 states, but these states cover only 11⁄2 percent of the globe, making the global error negligible.
However, the story was embellished and distributed to news outlets throughout the country. Resulting headline: NASA had cooked the temperature books – and once the error was corrected 1998 was no longer the warmest year in the record, instead being supplanted by 1934.
This was nonsense, of course. The small error in global temperature had no effect on the ranking of different years. The warmest year in our global temperature analysis was still 2005. Conceivably confusion between global and U.S. temperatures in these stories was inadvertent. But the estimate for the warmest year in the U.S. had not changed either. 1934 and 1998 were tied as the warmest year (Figure 2b) with any difference (~0.01°C) at least an order of magnitude smaller than the uncertainty in comparing temperatures in the 1930s with those in the 1990s.
The obvious misinformation in these stories, and the absence of any effort to correct the stories after we pointed out the misinformation, suggests that the aim may have been to create distrust or confusion in the minds of the public, rather than to transmit accurate information…
Is it possible to totally eliminate data flaws and disinformation? Of course not. The fact that the absence of incriminating statements in pirated e-mails is taken as evidence of wrong- doing provides a measure of what would be required to quell all criticism. I believe that the steps that we now take to assure data integrity are as much as is reasonable from the standpoint of the use of our time and resources.
Temperature data – examples of continuing interest. Figure 3(a) is a graph that we use to help provide insight into recent climate fluctuations. It shows monthly global temperature anomalies and monthly sea surface temperature (SST) anomalies. The red-blue Nino3.4 index at the bottom is a measure of the Southern Oscillation, with red and blue showing the warm (El Nino) and cool (La Nina) phases of sea surface temperature oscillations for a small region in the eastern equatorial Pacific Ocean.
Strong correlation of global SST with the Nino index is obvious. Global land-ocean temperature is noisier than the SST, but correlation with the Nino index is also apparent for global temperature. On average, global temperature lags the Nino index by about 3 months.
During 2008 and 2009 I received many messages, sometimes several per day informing me that the Earth is headed into its next ice age. Some messages include graphs extrapolating cooling trends into the future. Some messages use foul language and demand my resignation. Of the messages that include any science, almost invariably the claim is made that the sun controls Earth’s climate, the sun is entering a long period of diminishing energy output, and the sun is the cause of the cooling trend.
Indeed, it is likely that the sun is an important factor in climate variability. Figure 4 shows data on solar irradiance for the period of satellite measurements. We are presently in the deepest most prolonged solar minimum in the period of satellite data. It is uncertain whether the solar irradiance will rebound soon into a more-or-less normal solar cycle – or whether it might remain at a low level for decades, analogous to the Maunder Minimum, a period of few sunspots that may have been a principal cause of the Little Ice Age.
The direct climate forcing due to measured solar variability, about 0.2 W/m2, is comparable to the increase in carbon dioxide forcing that occurs in about seven years, using recent CO2 growth rates. Although there is a possibility that the solar forcing could be amplified by indirect effects, such as changes of atmospheric ozone, present understanding suggests only a small amplification, as discussed elsewhere (Hansen 2009). The global temperature record (Figure 1) has positive correlation with solar irradiance, with the amplitude of temperature variation being approximately consistent with the direct solar forcing. This topic will become clearer as the records become longer, but for that purpose it is important that the temperature record be as precise as possible.
Frequently heard fallacies are that “global warming stopped in 1998” or “the world has been getting cooler over the past decade”. These statements appear to be wishful thinking – it would be nice if true, but that is not what the data show. True, the 1998 global temperature jumped far above the previous warmest year in the instrumental record, largely because 1998 was affected by the strongest El Nino of the century. Thus for the following several years the global temperature was lower than in 1998, as expected.
However, the 5-year and 11-year running mean global temperatures (Figure 3b) have continued to increase at nearly the same rate as in the past three decades. There is a slight downward tick at the end of the record, but even that may disappear if 2010 is a warm year. Indeed, given the continued growth of greenhouse gases and the underlying global warming trend (Figure 3b) there is a high likelihood, I would say greater than 50 percent, that 2010 will be the warmest year in the period of instrumental data. This prediction depends in part upon the continuation of the present moderate El Nino for at least several months, but that is likely.
Furthermore, the assertion that 1998 was the warmest year is based on the East Anglia – British Met Office temperature analysis. As shown in Figure 1, the GISS analysis has 2005 as the warmest year. As discussed by Hansen et al. (2006) the main difference between these analyses is probably due to the fact that British analysis excludes large areas in the Arctic and Antarctic where observations are sparse. The GISS analysis, which extrapolates temperature anomalies as far as 1200 km, has more complete coverage of the polar areas. The extrapolation introduces uncertainty, but there is independent information, including satellite infrared measurements and reduced Arctic sea ice cover, which supports the existence of substantial positive temperature anomalies in those regions.
In any case, issues such as these differences between our analyses provide a reason for having more than one global analysis. When the complete data sets are compared for the different analyses it should be possible to isolate the exact locations of differences and likely gain further insights.