Does Global Warming Decline with Increasing Elevation?
Reference
Seidel, T.M., Weihrauch, D.M., Kimball, K.D., Pszenny, A.A.P., Soboleski, R., Crete, E. and Murray, G. 2009. Evidence of climate change declines with elevation based on temperature and snow records from 1930s to 2006 on Mount Washington, New Hampshire, U.S.A. Arctic, Antarctic, and Alpine Research 41: 362-372.
Background
The authors write that “future predictions of climatic change and impacts on mountain ecosystems are frequently based on the most proximate low elevation data or on extrapolations from other mountain regions.” However, they say that “using surrogate climatic data to describe potential responses by mountain biota can result in compromised conclusions.” As one example, they note what they call “the assumption that alpine ecosystems may be at great risk,” as most climate alarmists vociferously contend they are, because of what they typically describe as unprecedented global warming.

What was done
Working at Mount Washington (44°16′N, 71°18′W, the highest point in the northeastern United States), Seidel et al. compared seasonal and annual temperature trends, growing and thawing degree-day trends, and trends in two indices of snow season length for the summit (1914 m a.s.l.) and for Pinkham Notch (a mid-elevation site on the mountain’s eastern side).

What was learned
Based on data for the period 1935-2003, the seven scientists determined that at the mid-elevation site “there is a statistically significant warming in both annual and summer temperatures, with greater warming than that observed on the summit and less than that reported for lower elevations in the region.” In addition, they say summit temperatures, “though trending towards warming, do not exhibit a statistically significant change.” What is more, they say there is evidence that “resistance to climate warming at the higher elevations on Mount Washington has considerable tenure,” citing the work of Spear (1989), who, “using pollen and plant macrofossil records from Mount Washington and surroundings, concluded that since 5000 years BP, the subalpine forest and treeline-alpine ecotone boundary on Mount Washington has not exhibited demonstrable shifts.”

One explanation for this mountaintop “climate stasis” may be related to the fact that Grant et al. (2005), as Seidel et al. describe it, estimated that “the summit of Mount Washington experiences free-atmosphere (troposphere) conditions on 50% of days in both summer and winter,” so that “the summit exhibits a weak but not statistically significant warming trend, because during these conditions the summit would not necessarily be coupled with events observed from the surrounding regional lower elevation trends.”

SOURCE

I believe that the answer to the inherent contradictions I pointed out lies in the nature of your study.

In your study, you used the difference between the USHCN data, and “reanalysis” data. I have great problems with “reanalysis” data. For example, see my analysis of the NCEP reanalysis data here. It shows that the NCEP reanalysis data does a very poor job at replicating the amplification behaviour of the atmosphere.

If you are going to use reanalysis data to do the type of analysis you have done, it seems to be incumbent on you to first verify the reanalysis data. You do not appear to have done so. In your study you say

Trends of monthly mean temperature anomalies show a strong agreement, especially between adjusted USHCN and NARR (r = 0.9 on average) and demonstrate that NARR captures the climate variability at different time scales.

However, this is a necessary but not sufficient investigation. The NARR is based on observations, so we would expect it to be close. But that is not enough.

What you need to look at is, when the USHCN disagrees with the NARR, what is the reason for the disagreement? These disagreements could be from a variety of causes, including LU/LC changes, random error, bad computer programming or assumptions, or other environmental factors.

You have assumed that the difference is due to changes in LU/LC. However, this is something that needs to be proven rather than asserted.

And in fact, your study establishes that there is a very good chance that the differences are merely random. I say this because of the contradictions in the results that I highlighted above. Since they go both ways, it certainly leaves random fluctuations high on the list of possible reasons.

There are other possibilities as well. For example, in the map shown at the top of this thread (Figure 5 in your study), there are huge areas where the NARR is significantly different from the USHCN data. One of them is roughly contiguous with the Rocky Mountains … so the first thing I would check is to see whether there is a correlation of the OMR (observation minus reanalysis) data with elevation data. You say there is a “qualitative correlation” that explains this (shown in Fig. 6 of your study), but absent a quantitative correlation, I am not convinced. I get nervous when someone reports a qualitative correlation and does not proceed to do and report a quantitative correlation.

Because frankly, I have a very hard time believing that there have been large LU/LC changes over the entirety of the Rocky Mountains as shown in the map at the top of this thread. For another example, look at the area shown in blue that stretches from Southern California to Nevada … I’ve driven that stretch many times, and there is no common LU/LC change that covers that area. Over much of it, there is little development of any kind. So clearly, while LU/LC may be a factor, there are also some other thing at play that affect large areas.

In short, while an OMR analysis may be able to be related to LU/LC at some future date, there are obviously huge confounding factors which have not been considered, much less allowed for in your analysis. You cannot simply say that OMR and LU/LC are correlated without removing those factors.

And this is clearly demonstrated by your results. If the OMR method were valid and the confounding factors had been removed, we would not see the curiosities I note above, viz:

• when forest is converted to barren, the OMR rises … and when barren is converted to forest, the OMR rises.

• when grass/shrub is converted to barren, the OMR rises … and when barren is converted to grass/shrub, the OMR rises.

• when urban is converted to barren, the OMR drops … and when barren is converted to urban, the OMR drops.

These contradictions demonstrate that using the OMR method to analyse LU/LC is not ready for prime time. It may be in the future, but at present, it gives contradictory results.

Again, Dr. Fall, many thanks for your comments. I am impressed that you are willing to publicly defend your results, as this is extremely uncommon with climate scientists.

These results are what we obtained from the analysis that examined the trends in areas that changed from one type to another using the NLCD 1992–2001 Retrofit Land Cover Change. Of course, the OMR values used in this specific analysis span the same period (as explained in section 2 of the paper).
While there is still much work to do, our results demonstrate a clearly discernible effect due to landscape change.

Some contributions in this blog pointed out the shortness of the study period to assess changes due to land use. Agree, but for now, despite the shortness of the period of acquisition, the NLCD dataset (30 meters grid spacing) is the only one that breaks down the data into non-changed vs. changed areas (a total of 87 classes). A closer look at this dataset shows that during this short period, some conversion have been important: e.g. (i) urbanization, especially from agriculture and forest to urban; and (ii) conversion to croplands, especially from barren and grass/shrub.
As mentioned in some contributions, there are some odd conversions, such as urban to barren or urban to grass/shrub, but our study did not invent these conversions. That’s the NLCD datasets that identifies such land use/cover conversions.

That said, it is important to have in mind that OMR values reflect not only land use/cover changes, but also a number of other factors such as various climatic and non-climatic biases that affect near-surface temperature trends, including the quality of station siting which, so far, has not been included in temperature trend assessments. Moreover, factors such as near-surface moisture and wind speed can influence temperature trends and make them unrepresentative of the regional trends. As a result, OMR should not simply be read as “warming” or “cooling”.

Last but not least, the issue that is presented in the press release focused only on temperature trends with respect to LULC types. The press release only reports on part of our research [in this paper and a number of other peer reviewed papers] on the issue of the uncertainties associated with homogeneity adjustments and multi-decadal surface temperature trends.

Regards

A fence built to prevent rabbits from entering the Australian outback has unintentionally allowed scientists to study the effects of land use on regional climates.

The rabbit-proof fence — or bunny fence — in Western Australia was completed in 1907 and stretches about 2,000 miles. It acts as a boundary separating native vegetation from farmland. Within the fence area, scientists have observed a strange phenomenon: above the native vegetation, the sky is rich in rain-producing clouds. But the sky on the farmland side is clear.

Researchers led by Tom Lyons of Murdoch University in Australia and Udaysankar S. Nair of the University of Alabama in Huntsville have come up with three possible explanations for this difference in cloudiness.

Part I of Chapter IX: The State of Germany till the
Invasion of the Barbarians, in the Time of the Emperor Decius of The
History of the Decline and Fall of the Roman Empire by Edward
Gibbon originally published in 1776:

Some ingenious writers have suspected that Europe was much colder formerly than it is at present; and the most ancient descriptions of the climate of Germany tend exceedingly to confirm their theory. The general complaints of intense frost and eternal winter, are perhaps little to be regarded, since we have no method of reducing to the accurate standard of the thermometer, the feelings, or the expressions, of an orator born in the happier regions of Greece or Asia.

But I shall select two remarkable circumstances of a less equivocal nature. 1. The
great rivers which covered the Roman provinces, the Rhine and the Danube, were frequently frozen over, and capable of supporting the most enormous weights. The barbarians, who often chose that severe season for their inroads, transported, without apprehension or danger, their numerous armies, their cavalry, and their heavy wagons, over a vast and solid bridge of ice. Modern ages have not presented an instance of a like phenomenon. 2. The reindeer, that useful animal, from whom the savage of the North derives the best comforts of his dreary life, is of a constitution that supports, and even requires, the most intense cold. He is found on the rock of Spitzberg, within ten degrees of the Pole; he seems to delight in the snows of Lapland and Siberia: but at present he cannot subsist, much less multiply, in any country to the south of the Baltic. In the time of Caesar the reindeer, as well as the elk and the wild bull, was a native of the Hercynian forest, which then
overshadowed a great part of Germany and Poland.

The modern improvements sufficiently explain the causes of the diminution of the cold. These immense woods have been gradually cleared, which intercepted from the earth the rays of the sun. The morasses have been drained, and, in proportion as the soil has been cultivated, the air has become more temperate. Canada, at this day, is an exact picture of ancient Germany. Although situated in the same parallel with the finest provinces of France and England, that country experiences the most
rigorous cold. The reindeer are very numerous, the ground is covered with deep and lasting snow, and the great river of St. Lawrence is regularly frozen, in a season when the waters of the Seine and the Thames are usually free from ice.

New Paper Documents A Warm Bias In The Calculation Of A Multi-Decadal Global Average Surface Temperature Trend – Klotzbach Et Al (2009)

“An Alternative Explanation For Differential Temperature Trends At The Surface And In The Lower Troposphere” By Klotzbach Et Al 2009

Willis, you aren’t missing anything (good eye). You have recognized the major inconsistencies with this paper.

What caught my eye in figure 9 were the claims concerning urban areas converted to forest, grass/shrub, agriculture etc. It conjured up in my minds-eye visions of cities being bulldozed to create farmland.

I think the problem is that the land use land cover change was estimated using satellite-based AVHRR data, which is iffy at best. For example, when a new suburban development is built, the trees are freshly-planted and small. As it ages, the trees grow taller, their crowns spread and eventually begin to join. The AVHRR classification then changes from “urban” to “forested”. How “urban” becomes “agricultural” I can’t imagine.

I also agree with your observations of the CI’s in fig 9. There really isn’t much useful information in that figure.

I was also bothered by the authors statements of the reliability of the results in that figure due to sample size, sometimes lesser, sometimes greater, with no mention of what the sample sizes were.

Frankly, I think the Pielke Sr. group has been banging the “land use change” drum a little too loudly, and got a little too carried away with this paper.

• when forest is converted to barren, the temperature rises … and when barren is converted to forest, the temperature rises.

• when grass/shrub is converted to barren, the temperature rises … and when barren is converted to grass/shrub, the temperature rises.

• when urban is converted to barren, the temperature drops … and when barren is converted to urban, the temperature drops.

What am I missing here?

The main problem is the huge range of the 95% confidence intervals. Of the fifteen possible pairings, I see only one pair (agriculture to grass/shrub, grass/shrub to agriculture) where the confidence intervals don’t overlap.

In all the rest (as is confirmed by the paradoxical results I quote above), the intervals overlap. It seems to me that the only scientifically sustainable conclusion is that when you go from agriculture to grass/shrub, it warms up, and vice versa.

Clearly, I don’t understand what is going on in the study. Help, anyone?

Gore tosses CO2 into the ash heap of his history:

“”Over the years I have been among those who focused most of all on CO2, and I think that’s still justified,” he told the magazine. “But a comprehensive plan to solve the climate crisis has to widen the focus to encompass strategies for all” of the greenhouse culprits identified in the Nasa study.”

“Gore acknowledged to Newsweek that the findings could complicate efforts to build a political consensus around the need to limit carbon emissions.”
…-

“”He is one of the only politicians that takes the time to actually talk to scientists who are producing the cutting-edge stuff and he comes in with questions. He doesn’t ask us how our results impinge on a particular policy he actually asks about science,” said Gavin Schmidt, a climatologist at Nasa’s Goddard Institute for Space Studies, who spoke to Gore along with colleagues four or five times for the book.

>>> “Nobody that we have dealt with has ever taken as much time to understand the subtlety of the science and all the different complications and what it all means as Al Gore.”

Those conversations led Gore to politically inconvenient conclusions in this new book. In his conversations with Schmidt and other colleagues at the beginning of the year, Gore explored new studies – published only last week – that show methane and black carbon or soot had a far greater impact on global warming than previously thought. Carbon dioxide – while the focus of the politics of climate change – produces around 40% of the actual warming.
Gore acknowledged to Newsweek that the findings could complicate efforts to build a political consensus around the need to limit carbon emissions.

“Over the years I have been among those who focused most of all on CO2, and I think that’s still justified,” he told the magazine. “But a comprehensive plan to solve the climate crisis has to widen the focus to encompass strategies for all” of the greenhouse culprits identified in the Nasa study.

The former vice-president has been working behind the scenes to try to nudge the White House and Congress to move forward on a 920-page proposed law to cut America’s greenhouse gas emissions and encourage its use of clean energy sources like solar and wind power.”

“Al Gore’s Inconvenient Truth sequel stresses spiritual argument on climate

Nobel winner adapts fact-based message to reach those who believe they have a moral duty to protect the planet in Our Choice: A Plan to Solve the Climate Crisis”

http://cnews.canoe.ca/CNEWS/Environment/2009/11/03/11617491-reuters.html

“I think this type of study must be considered before we convert 10-20% of the desert southwest into a mirror or other solar collector surface. These large solar farms that have been proposed could have a large regional impact on climate. ”

As a new resident of Burbank, I’m looking forward to cooler climate in the Mojave keeping the Santa Ana winds blowing cool air downhill for more of the year. Maybe it will help with precipitation as well…