From the James Hansen is just wrong department comes some inconvenient data, data that Dr. Hansen or anyone in the media could have easily looked up for themselves before writing irresponsible stories like this one:
Former Virginia State Climatologist Dr. Pat Michaels, in a guest opinion on WUWT said:
Hansen claims that global warming is associated with increased drought in the US. This is a testable hypothesis which he chose not to test, and, because PNAS isn’t truly peer-reviewed for Members like him, no one tested it for him.
I have [examined] drought data [that] are from NCDC, and the temperature record is Hansen’s own. His hypothesis is a complete and abject failure.
I’ve looked at the data too, and I agree, Hansen’s hypothesis is a dud, and in no way supported by NOAA’s own data to be “scientific fact”. But, because it has been spread by an irresponsible and incurious media, its is a dangerous “dud”.
Let’s go to the data…
In my research regarding why I didn’t think the July 2012 USA Temperature of 77.6F was a record (compared to July 1936 of 77.4F), I spent some time trying to understand how they computed the value, since NCDC offers no way to replicate it and so far has not responded to my query about how it is done.
In conjunction with a switchover to happen next year from simple division averages (TCDD) to gridded averages (GrDD, which they say will be more accurate) NOAA’s National Climatic Data Center (NCDC) offers a visualization tool to plot all sorts of data for the continental USA (CONUS). From NCDC’s U.S. Climate Divisions page:
A visualization toolkit was created to help users examine snapshots of both datasets for the comparison period (i.e., through December 2009). The tool allows the user to select criteria which are of interest and investigate the comparisons themselves. Parameters included in the toolkit are temperature, precipitation, and a variety of drought indices. Changes in monthly, seasonal and annual variability can be examined through the use of the interactive time series plots. In addition, slope (trend) values by decade and 30-year period may also be added to the output plots. This allows the user to take a closer look at the behavior of the data at a variety of smaller time scales throughout the record.
Unfortunately, they don’t have 2010-2012 data online, and I could go to the NCDC FTP site and get the remaining data and plot all of it, but since many people on the alarmist bandwagon don’t trust data plots from skeptics, I thought the fact that these are unmodified 100+ year plots from NCDC directly outweighed the 3 years of data they didn’t provide.
Here’s some screen caps output direct from that visualization toolkit. You can visit it and exactly replicate any of these for yourself.
First, CONUS temperature:
No surprise there. In my opinion, GHCN and all of its airport weather stations tends to make the present warmer than the past, with 1998 being warmer than 1934. But that’s another old story. My real interest in this essay is in precipitation trends and drought trends which don’t go through as many issues with equipment, siting, adjustments, as temperature does.
Here’s national precipitation:
Some people say the precip is down in the summer months due to “increasing drought”, that’s unsupported by the data:
Like with CONUS temperature, there’s an upward trend annual precipitation, and essentially no trend in summer months. This is curious, because if as Dr. Hansen is quoted as saying regarding U.S. Droughts…
“This is not some scientific theory,” Hansen told The Associated Press in an interview. “We are now experiencing scientific fact.”
…you’d expect a downward trend in U.S. precipitation. Interestingly, as shown in the plot above, the driest period for precipitation in the USA is 1951-1956, followed by a big upswing.
But precipitation totals alone is not a measure of drought, soil moisture and other factors figure in too. Let’s look at some drought data. Using NCDC’s visualization toolkit, I’ve plotted the major drought indices based on the Palmer Drought Index. Here’s a description of these indices from NCDC’s page on the current Palmer Index:
The Palmer Z Index measures short-term drought on a monthly scale.
The Palmer Drought Severity Index (PDSI) (known operationally as the Palmer Drought Index (PDI)) attempts to measure the duration and intensity of the long-term drought-inducing circulation patterns. Long-term drought is cumulative, so the intensity of drought during the current month is dependent on the current weather patterns plus the cumulative patterns of previous months. Since weather patterns can change almost literally overnight from a long-term drought pattern to a long-term wet pattern, the PDSI (PDI) can respond fairly rapidly.
The hydrological impacts of drought (e.g., reservoir levels, groundwater levels, etc.) take longer to develop and it takes longer to recover from them. The Palmer Hydrological Drought Index (PHDI), another long-term drought index, was developed to quantify these hydrological effects. The PHDI responds more slowly to changing conditions than the PDSI (PDI).
Here’s the plots, note that for the Palmer Index, negative values correlate to drier conditions, and positive values show wetter conditions. First PDSI:
And since some people will argue that summer months are the most affected:
The flatness of the Palmer Drought Severity Index, compared to the upward trends of temperature and precipitation, strongly suggest no correlation between CONUS temperature and CONUS drought severity. But let’s not stop there, let’s examine the other PDI data types.
Here’s the Modified Palmer Drought Severity Index, the operational version of the PDSI, which was defined in Heddinghaus and Sabol (1991).
Here’s the same data by months:
For summer months, the century scale trend is slightly down. But there is still no large century scale trend in drought.
How about the Palmer Hydrological Drought Index?
Still essentially flat. Note that while there are slight upward trends in the divisional data plots (suggesting less drought), NCDC says this is erroneous, and will introduce the new gridded method in 2013. The GHCN values are flat.
How about the short-term Palmer Z Index? Maybe Hansen’s drought correlation is hiding there?
Still pretty much flat, though there’s a spike in the monthly plot for 2009 that beats 1915. As we know, a couple of months of dry conditions does not a long-term trend make.
How about the summer months for the short-term Z-index?
Short term summer months Z index is slightly down in the last 114 years. But not largely so, certainly nothing like the inverse correlation with CONUS temperature we’d expect to see if Hansen’s hypothesis was true.
Pat Michaels, in his previous WUWT opinion piece, noted that Hansen is making a claim that global temperatures are driving U.S drought, and did a scatterplot to gauge correlation between Hansen’s own GISS temperature data (GISTEMP) and the U.S. Palmer Drought Severity Index with annual data through 2011:
There’s no correlation: zero, zip, nada. If there were, you’d see the dots align along a diagonal line, there’s not even a hint of that. Of course proponents might say that but, but, but, 2012 was a terrible drought. Yes, it was, it is, but a few months of a not yet complete year of data does not a long term trend make. And, we’ve seen worse in the past.
This 21 century reconstruction of rainfall for New Mexico, done by Henri D. Grissino-Mayer, University of Tennessee, in the paper “A 2,129-Year Reconstruction of Precipitation for Northwestern New Mexico, USA,” 1996; David M. Anderson, National Oceanic and Atmospheric Administration National Climatic Data Center. Full details here.
This paper suggests that what New Mexico experiences today, isn’t really any different from what it has been experiencing in the past, when CO2 levels were far lower. In fact, for the most recent period, New Mexico has had greater rainfall:Taken in toto these facts and data say to me that the “scientific fact” promoted by Dr. Hansen is pure political hogwash.
PNAS should withdraw the paper, and NASA should fire Dr. Hansen for promoting an opinion unsupported by data as “scientific fact”.