Denier weirdness from Philip Lloyd: An extreme rainfall event is a year in the making?

Deniers are weird people. Anthony Watts has another article from science denier Philip Lloyd, who's not unknown at HotWhopper. He's not a climate scientist, that's for sure. Philip decided to look at annual rainfall in England and Wales to see if extreme rainfall events have increased or not.

What's that?

No, I don't think it's a joke article. You can see for yourself.

It never rains but it pours...Interesting juxtaposition at WUWT

When I went to WUWT today there was this interesting juxtaposition of articles:

It doesn't come out in the same format in the archived version.

All but one were all about extra heavy precipitation, and even that one exception mentioned it. From left to right:

• Groundhog day - every day is groundhog day at denier blogs
• Pineapple Express - an article about how there may be heavy rain in northern California, (with no mention of the accompanying record temperatures in Canada)
• Storms are expected to get stronger - an article with, as usual, a misleading headline from Anthony - not exactly wrong but misleading
• The blizzard in north east USA - an article claiming that the heavy snowfall wasn't because of any extra water vapour in the air (yes, that's how I read it anyway. It was also arguing that the seas weren't warmer and that it's nothing to do with global warming).

Deniers are a funny breed. I don't know if any of them noticed.

It's raining, it's pouring

Perennially Puzzled Bob Tisdale has written a second article on precipitation, on WUWT.  It's mainly a gripe that he cannot find data sets that agree.  When I wrote about his first gripe I made the uninformed observation that precipitation must be one of the most difficult things to monitor globally.  This would be so for any number of reasons that I expect readers here could imagine.

Anyway I've done a bit more reading and came across this paper by Udo Schneider et al (2013), titled: GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle

Here is the abstract:

In 1989, the need for reliable gridded land surface precipitation data sets, in view of the large uncertainties in the assessment of the global energy and water cycle, has led to the establishment of the Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst on invitation of the WMO.

The GPCC has calculated a precipitation climatology for the global land areas for the target period 1951–2000 by objective analysis of climatological normals of about 67,200 rain gauge stations from its data base. GPCC's new precipitation climatology is compared to several other station-based precipitation climatologies as well as to precipitation climatologies derived from the GPCP V2.2 data set and from ECMWF's model reanalyses ERA-40 and ERA-Interim.

Finally, how GPCC's best estimate for terrestrial mean precipitation derived from the precipitation climatology of 786 mm per year (equivalent to a water transport of 117,000 km3) is fitting into the global water cycle context is discussed.

The paper is a very easy read.  It goes into a lot of detail, describing how the team collects data, corrects it, stores it etc.  And towards the end it has some information about global precipitation patterns, among other things.  I recommend it.

BTW - I'd say my uninformed observation was pretty close to the mark.

Bob Tisdale the Tedious on Precipitation

Bob Tisdale is probably the most boring writer on WUWT.  He regurgitates vast slabs of text from his own website and repeats it ad infinitum on WUWT.  This time he is writing about global precipitation.

I got curious about that.  Rainfall seems to me to be a tricky thing.  I would expect that temperature is a lot easier to estimate.  If it's hot in one place it's a fair bet it'll be hot in a neighbouring place.  Rain is different.  I've driven through rain bands that were no wider than 10 metres.  I've sat under a downpour and then looked at the radar and seen that a storm cloud has settled over our small town and released a torrent, but that this small area is the only place that's being rained upon for hundreds of kilometres in any direction.


I'm well aware that's taking a naive unscientific approach.  A downpour for twenty minutes over my home town doesn't mean squat in comparison with precipitation over south eastern Australia as a whole let alone over the entire earth.

That's by way of warning - I'm not even a beginner when it comes to assessing global precipitation.

Bob Tisdale seems to be on a lower level even than I am.  And I only started looking up this stuff this evening.  Bob has written an article on it for WUWT, taking on the guise of an "expert".

I started running into trouble with Bob's article from his very first sentence.  He writes:

We used NOAA’s CAMS-OPI satellite-era precipitation data in the post Model-Data Precipitation Comparison: CMIP5 (IPCC AR5) Model Simulations versus Satellite-Era Observations.

So I looked up NOAA's CAMS-OPI and this is what NOAA says about it:

The "CAMS_OPI" (Climate Anomaly Monitoring System ("CAMS") and OLR Precipitation Index ("OPI") is a precipitation estimation technique which produces real-time monthly analyses of global precipitation. To do this, observations from raingauges ("CAMS" data) are merged with precipitation estimates from a satellite algorithm ("OPI"). The analyses are on a 2.5 x 2.5 degree latitude/longitude grid, are updated each month, and extend back to 1979. This data set is intended primarily for real-time monitoring. For research purposes, we refer users to the GPCP and CMAP products which are more quality-controlled and use both IR and microwave-based satellite estimates of precipitation.

Bob Tisdale shouldn't have been using that data set to compare with model runs.  It's "intended primarily for real-time monitoring".

In his latest article Bob didn't use CAMS-OPI because he wanted to look at precipitation over land separately from precipitation over the ocean. So he went to NOAA’s Global Precipitation Climatology Project (GCPC) Version 2.2. I went to see what NOAA had to say about that. Here is what they write:

One of the major goals of GPCP is to develop a more complete understanding of the spatial and temporal patterns of global precipitation. Data from over 6,000 rain gauge stations, and satellite geostationary and low-orbit infrared, passive microwave, and sounding observations have been merged to estimate monthly rainfall on a 2.5-degree global grid from 1979 to the present....

...The GPCP data have already been found capable of revealing changes in observed precipitation on seasonal to interannual time scales and in validating model generated precipitation from re-analysis systems, such as those from NCEP/NCAR and ECMWF. GPCP also offers the potential for studying changes in the distribution of precipitation at longer time scales such as predicted by GCM simulations, especially in the pattern change over previously data-sparse ocean areas. GPCP estimates can validate both the magnitude and the spatial pattern of modeled rainfall to within the estimated error of the observations. However, realization of the full potential for the GPCP to provide precipitation estimates for climate change studies, especially over the oceans, requires further research and development. Specifically, investigation of inhomogeneities in the GPCP satellite component data sets, and enhanced calibration and validation efforts, especially over open oceans, are required.

How it's put together is by collecting and analysing data from rain gauges and merging it with data collected from satellites and then estimating monthly rainfall on a 2.5 degree global grid.  I'm sure it's of great value for research purposes, but it's not the sort of thing I'd be comparing to models in the way I'd compare a pattern of global temperatures.  A scientist skilled in this sort of analysis would be able to do this, but a blogger on HotWhopper or WUWT?  No way.  Here is a paper discussing GPCP, which includes a long list of other papers that cite it - a relatively small number of the 1442 cites indicated by Google.

The paper gives a solid overview but is very technical.  I went looking further afield at how the data is collected.  I came across a NASA website discussing TRMM, which was launched in 1997 and:

...has provided critical precipitation measurements in the tropical and subtropical regions of our planet. The Precipitation Radar (PR) can see through the precipitation column, providing new insights into tropical storm structure and intensification. The TRMM Microwave Imager (TMI) measures microwave energy emitted by the Earth and its atmosphere to quantify the water vapor, the cloud water, and the rainfall intensity in the atmosphere. TRMM precipitation measurements have made and continue to provide critical inputs to tropical cyclone forecasting, numerical weather prediction, and precipitation climatologies, among many other topics, as well as a wide array of societal applications.

Then there is the Global Precipitation Measurement (GPM) mission , a joint project initiated by NASA and JAXA.  The core GPM observatory is scheduled for launch next year.  You can read about it here.

To see more about how accurate is the measured precipitation I turned to Google.  Here is a 2010 paper discussing uncertainties in satellite precipitation data sets in the TRMM era.  The abstract states in part:

The uncertainties are relatively small (40–60%) over the oceans, especially in the tropics, and over southern South America. There are large uncertainties (100–140%) over high latitudes (poleward of 40° latitude), especially during the cold season. High relative uncertainties are also evident through the seasons over complex terrain areas, including the Tibetan Plateau, the Rockies and the Andes. Coastlines and water bodies also indicate high measurement uncertainty. The estimated global uncertainties also exhibit systematic seasonal, regional as well as rain-rate dependencies, with lowest uncertainties over tropical oceanic regions with strong, convective precipitation, and highest ones over wintery, complex land surfaces with light precipitation.

There is much more information out there, including lots of recent papers.  I'm intrigued by how much scientists can tell us about precipitation, by clever use of technology.  See, WUWT can't be all bad :)

As far as I can see, Bob Tisdale is not proving or disproving anything in his crude comparison of monthly global precipitation with his multi-model means from CMIP5.  He takes the observations at face value for one thing, without allowing for uncertainties in either the observations or the models.

And that, of course, is apart from the fact that just as in the past, unless his ensemble mean lines up exactly with observations, Bob is inclined to dismiss the models altogether.