. From the James Hanson is just wrong department comes some inconvenient data. Data that Dr. Hanson 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 what's up with that said, Hanson claims that global warming is associated with increased drought in the United States. This is a testable hypothesis which he chooses not to test and because PNS isn't truly peer reviewed for members like him, no one tested it for him. I have drought data that are from NCDC and the temperature record is Hanson's own. His hypothesis is a complete and abject failure. Mr. Watts looked at the data as well and he agrees, Hanson'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 is the dangerous dud. So let's go to the data. And Watts research regarding why he didn't think July 2012 USA temperature of 77.6 degrees Fahrenheit was a record compared to July 1936 of 77.4 degrees Fahrenheit. He spent some time trying to understand how they computed the value since NCDC offers no way to replicate it and has so far as not responded to any query about how it's done. In conjunction with a switchover to happen next year from simple division averages to gridded averages, NOAA's National Climate Data Center offers a visualization tool to plot all sorts of data for the continental USA from NCDC's US Climate Division's page. A visualization toolkit was created to help users examine snapshots of both data sets 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. pages in monthly, seasonal and annual variability can be examined through the use of the interactive time series plots. In addition, slope or 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 to 2012 data online. And Mr. Watts 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, he thought that the fact that these are unmodified 100 plus year plots from NCDC directly outweighed the three years of data they didn't provide. Here's some screen caps output direct from the visualization toolkit. You can visit it yourself and replicate exactly any of these for yourself. First, the coneus temperature. No surprise there. In his 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. Mr. Watts's real interest in this essay is in the precipitation trends and drought trends, which don't grow through as many issues with equipment, sitting, adjustments, as temperature does. Here's the national precipitation. Some people say precipitation is down in the summer months due to increasing drought. That's unsupported by the data. Like with coneus 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 US 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 US precipitation. Interestingly, as shown in the plot above, the driest period for precipitation in the United States is 1951 to 1956, followed by a big upswing. The precipitation totals alone is not a measure of drought, soil moisture, and other factors figuring too. Let's look at some drought data. Using NCDC's visualization tool kit, Anthony Watts plotted the major drought indices based on the polymer drought index. The polymer drought sensitivity index, known periodically as the polymer drought index or 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 a 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 to a long-term wet pattern, the PDSI or PDI can respond fairly rapidly. The hydrological impacts of drought, for example, like reservoir levels, groundwater levels, groundwater, take longer to develop, and it takes longer to recover from them. The polymer hydrological drought index, another long-term drought index, was developed to quantify these hydrological effects. The PHDI responds more slowly to changing conditions than the PDSI or PDI. Here's the plots. Note that for the polymer index, negative values correlate to drier conditions and positive values show where to conditions. In just in case some people might argue that summer months are most affected, check out this graph. The flatness of the polymer drought severity index compared to the upward trends of the temperature and precipitation strongly suggests there is no correlation between coneous temperature and coneous drought severity. But let's not stop there. Let's examine other PDI data types. Here's the modified polymer drought severity index, the operational version of the PDSI, which was defined in Hitting Huss and Cyborg 1991. Here's the same data by months. Notice for summer months, the century scale trend is slightly down, but there are still no large-century scale trend in drought. So how about the polymer 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 GHC and values are flat. How about the short-term polymer Z index? Maybe Hanson's drought correlation is hiding there? As you can see by the data, it's still pretty much flat. So 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 mean a long-term trend make. So how about the summer months for a short-term Z index? Notice 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 the coneous temperature we'd expect to see if Hanson's hypothesis was true. Pat Michaels, in his previous opinion piece, noted that Hanson is making a claim that global temperatures are driving US drought and did a scatter plot to gauge correlation between Hanson's own GISS temperature data and the United States Palmer drought severity index with annual data through 2011. There's no correlation. Zip. Zero. Nada. If there were, you'd see the dots align along a diagonal line. But there's not even a hint of that. Of course, the proponents might say that, but 2012 was a terrible drought. Well, yes, it was. It is. But a few months of a not yet complete year of data does not make a long-term trend. And we've seen worse in the past. In a tweet, New York Times reporter Andrew Reffkin agrees. Drung attention to this Sunday essay. This 21st century reconstruction of rainfall for New Mexico was done by this paper. Full details in the links are in the description below going back to whatsup with that dot com. This paper suggests that what New Mexico experiences today really isn't any different from what it has been experiencing in the past when CEO2 levels were far lower. In fact, for the most recent period, New Mexico had greater rainfall. Taking in total these facts and data say that the scientific fact promoted by Dr. Hansen is pure political hogwash. Peaness should withdraw the paper and NASA should fire Dr. Hansen for promoting an opinion unsupported by data as scientific fact.