Mother Jones news has an “alarming” article called “Our Coming Mega-Drought” in which they say “…virtually all of the world except for China and Russia will experience increased drought by 2030 and severe drought by 2060” and they cite these computer model maps at left.
Yes, it looks pretty bad. But the thing about models, is that they are very sensitive to starting conditions, and like we’ve learned with temperature measurement errors worldwide, so are there errors with precipitation measurement. Rain gauges are easily influenced by wind, and wind eddies. So things like buildings, shrubbery, trees, and station moves can all have an impact. Pierre Gosselin at No Tricks Zone has a good summary of issue related to precipitation measurement which I present below.
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Huge Global Precipitation Deficits Due To Woefully Inaccurate Measurement Techniques!
By P Gosselin on 24. Oktober 2010
NOAA 8 inch rain gage. Source: http://www.crh.noaa.gov/iwx/?n=coop_station
German Weather Service meteorologist Christoph Hartmann writes what I think is a surprising essay on measuring precipitation, and the errors in doing so. Indeed Hartmann says precipitation may be understated by up to 50%, or much more at some locations.
As Hartmann explains, measuring precipitation is by no means an exact science, and results have to be taken with a lump of salt.
There are many sources of errors, and in his essay here he looks at just two main sources: wind and instrumentation.
But first, let’s take a look at how precipitation is measured. In his previous essay he described two types of precipitation measuring gages. In Germany precipitation is measured with the unit of liters/m², e.g. 25.4 liters is an inch of rain.
Two methods of measuring precipitation
Hartman explains that precipitation is generally measured by a rain gage with a known opening area, for example 200 cm² in Germany, which is positioned 1 meter above the ground surface. The gage funnel catches the precipitation and leads it to either
1) a graduated measuring tube or a
2) an optical drop counter
Optical rain gage (drop counting). Source: atmos.washington.edu
With the measuring tube system, the tube is graduated and the amount of precipitation can be simply read off. With the optical rain gage (drop counter), the amount of precipitation is derived from the number of drops. If the precipitation is snow or ice, then the measuring tube or optical gage are brought inside and the captured precipitation is melted and measured.
Hartmann explains that the biggest sources of error are wind-related. This is easily seen when measuring snowfall. Just before a snowflake falls into the gage, air turbulence sucks it back out tosses it overboard. Just taking a look around after a blizzard, it’s easy to imagine how difficult it is to measure snowfall. Places exposed to wind are barren, while other places are covered by meter-deep snowdrifts. How much snow really fell?
Hartmann says measurement errors of up 400% can occur over time when measuring powdery snowfall in alpine, polar or windy areas.
One way to reduce error is to place the instrument in a wind-protected area. By measuring the wind speed, it is then possible to adjust precipitation measurements. But Hartmann writes:
Wind effects lead to an under-estimation of the actual fallen precipitation. The level of deviation depends on the speed of the wind and the type of precipitation.
Because wind speeds are factored into precipitation measurements, climatological precipitation trends without taking changes in wind speeds into account should always be deduced very carefully.
The second problem encountered arise from the two above described measurement instruments, especially with the optical rain gage, writes Hartmann. With frozen precipitation, the gages are heated up in order to melt the precipitation. But this involves evaporation. And under torrential rains, the optical gage becomes much less accurate. The result, writes Hartmann:
Under equal precipitation amounts, the optical gage measures less precipitation than the measuring tube, both in summer and in winter.
So if two different stations use different instruments, them they will show different precipitation amounts even when the actual precipitation is the same. In summary, Hartmann writes his stunning conclusion:
In total these two sources of errors lead to a precipitation deficit of 5 to 15% for liquid precipitation, and between 20 and 50% for solid [frozen] precipitation. In very windy locations, the deficits are substantially more.
Because instruments measure less precipitation than what actually falls, it means we have a worldwide precipitation deficit solely because of the measurement method.
What does it all mean? Are many of the reported droughts solely the product of faulty readings? And we all thought that the network of temperature measurement stations was a mess. This is a huge open floodgate to potential climatological data manipulation and bogus assertions. See here for example: motherjones – the coming mega-drought (h/t NTZ reader DirkH).
We always had shamans telling us that the world is gonna end in the year 62, 458 1002, 1704, 1922, 2000, 2012. Only in the old days they used to be laughed at and pilloried. These days they get billions in grant money from our taxes.
Here in the middle of the Mediterranean sea, on the tiny island of Malta, we are having one of the wettest Octobers ever and already have half the annual rainfall average, measured between 1st September and 31st August. I have been following the weather here and now globally, since I was born. My father, besides being a school teacher, also kept the weather records of our town for the Maltese met office until he retired in 1981 and I used to help him read the instruments and manually work out the maths. I can easily say that rain is as abundant and as scarce as it has been for the last 50 years, some years its good, others its bad. The year before we had 28 inches of rain, last year it was 16 inches while our average is around 20 inches. This year looks like its gonna be a good rainy one.
Rest assured that everything is normal, so drink that cup of tea and go back to sleep.
John and Christopher. Here’s a genuine Australian climate disaster, one which Tim Flannery could certainly confirm. Imagine what it would have been like further inland!:
“At 9 a.m., 85 degrees. At noon, 104. Half past twelve, 107½. From one p.m. until 20 minutes past two 108½. At 20 minutes past two, 109. At Sunset, 89. At 11 p.m., 78½. [By a large Thermometer made by Ramsden, and graduated on Fahrenheit’s scale.]…
“But even this heat was judged to be far exceeded in the latter end of the following February, when the north-west wind again set in, and blew with great violence for three days. At Sydney, it fell short by one degree of what I have just recorded: but at Rose Hill, it was allowed, by every person, to surpass all that they had before felt, either there or in any other part of the world. Unluckily they had no thermometer to ascertain its precise height. It must, however, have been intense, from the effects it produced. An immense flight of bats driven before the wind, covered all the trees around the settlement, whence they every moment dropped dead or in a dying state, unable longer to endure the burning state of the atmosphere. Nor did the ‘perroquettes’, though tropical birds, bear it better. The ground was strewn with them in the same condition as the bats.”
That’s an entry from the journal of Watkin Tench, Captain of Marines. He came out on the First Fleet. Curiously, Tim Flannery is particularly interested in Tench and the early settlement. Go figure.
The reference is to the Sydney summer of 1790-1791.
I measure max and min temp plus precipitation each day in my suburban back yard in London. Despite said back yard being what should be an example of a UHI-affected site, my recorded max temps are currently around 60% LOWER than the Met Office daily forecast. My recorded min temps are also usually a significant percentage below that forecast. The forecasts seem to pass into history without comment as the met office forecasters never refer to yesterday’s actual figures but move right on to the forecast for the next day. I believe that, while my quite rudimentary equipment may be in slight error, a consistent 60% error is way beyond acceptable in terms of believable forecasting.
I have come to the conclusion that the actual temperatures are rarely made public until a significant amount of time has elapsed or an unuasual weather event occurs and that the current reality is that the climate in the part of London where I live is much cooler than the general population are being led to believe.
mosomoso (12:23 am), 109°F would have been a bit of a shock I dare say
http://www.diggerhistory.info/images/diggers/soldier-rum-corps.jpg.
Just for the record, the maximum temperature ever recorded at Sydney Observatory (commenced 1858) was 45.3°C (114°F) on 14th January 1939 (the atmospheric CO2 concentration then was around 310 ppm)
http://www.bom.gov.au/climate/averages/tables/cw_066062_All.shtml.
Hmmm, I’m getting those ‘denier’ ideas http://hidethedecline.eu/media/Northern%20hemisphere%20temperatures/crumat.jpg.
Rainfall measurement is fraught with errors. Due to the localised rainfall problem there is little chance that the maximum rainfall will be measured if at all. Warm fronts produce large area showers which may be caught by the gauge and so the area rainfall can be calculated, provided the total area is known. Summer showers are thundery and very localised and the nearest gauge may not get any rain readings at all. Most rainfall readings will be an underestimate of actual rain that fell.
Models will produce any future scenario that you want but little of scientific substance.
Richard Sharpe says:
October 24, 2010 at 6:51 pm
Well, what will happen is that the moisture will precipitate out but it will evaporate again before hitting the ground, so there will be more droughts while there will also be an acceleration of the hydrological system so that there is tons more moisture in the atmosphere. Simple, isn’t it?
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Well, the problem with catastrophic climatism is that its proponents think that it is so simple, but it is not. It is very very complicated. That is why there’s this global discussion going on. What’s sure is that more and more scientists are coming out of the woodwork saying that they are skeptical about the very idea that CO2 = global warming and logically, the rest falls flat on its face. Because since AGW rests on one forcing; that an increase in atmospheric CO2 causes global warming, then once this theory is proven wrong, AGW theory collapses, as it has already done, in my opinion. Only it is being given life support by the MSM. politicians and the money-grabbing scientists.
I once had a chance to compare an official Australian BoM rain gauge with my own straight sided 2″cylinder sharpened to a knife edge at the orifice to the inside edge graduated with a machinists rule on the inside. Despite the fact that they were within 2 metres of each other, my simple tube registered 20% higher over several months with daily readings.
I could only conclude that there was some mismatch between the funnel area and the indirectly calibrated tube supplied with the official gauge. other explanations anyone?
Granted long term trends would not be affected, but only if all the gauges were equally in error.
One curious old Australian grain farmer’s personal experience.
Does seasonal rainfall vary much across a paddock?
Paddock size; 2 kms x 2 kms; ie; 4 sq kms = 400 ha’s = 980 acres.
No fences. No buildings. No obstructions.
No trees within a kilometre of the paddock [ exception; neighbour’s house yard approx 1/2 km from paddock.]
Terrain flat as in almost dead flat except for a large area where there is a very gentle fall of less than 3 metres onto another large flat area.
This particular farming region is renown for it’s flat terrain with the nearest mountain range some 80 kms to the South.[” hill’s” to Americans and Europeans. This is Australia, one of the oldest and most eroded continents on Earth where you can cross some 3000 kms from the Great Australian Bight in the south to the Gulf of Carpentaria in the north without getting more than 200 feet above sea level. ]
Soil type ; very even black cracking clays all over.
No internal fences or any obstructions, just a big open Australian paddock!
Crop was wheat all over.
Late Autumn / Winter / Spring season rainfall is by far the predominant pattern [ mid April to early November is our main rainfall period down here in the SE Australia.]
13 identical rain gauges gridded across the paddock with the outer ring of gauges placed some 50 metres in from the outside boundary fence to reduce fence effects and other influences.
Gauges were positioned after the wheat crop was sown in mid May which is our normal sowing window for cereals.
Gauges were measured and recorded weekly.
Kept myself and the old dog pretty fit walking and plugging our way in wet soil across that 2 km square paddock of growing wheat to measure and record those 13 gauges.
By late September it was quite clear from the gauge recordings that about one quarter of the paddock was consistently receiving less rainfall than the rest of the paddock.
The deficiency amounted to over 15% difference by the time I stopped recording in mid October.
Another corner, about 10% of the paddock received consistently higher precipitation than the rest of the paddock despite switching gauges around in case there were gauge inconsistencies.
There was no identifiable explanation or reason for this consistent seasonal variation in rainfall across this very flat terrain and very even paddock.
As somebody who had farmed that paddock for over some 30 years I had often noticed that where the lower rainfall had been measured in the paddock, it seemed to be consistently less yield over the years than the rest of the paddock area.
Item 2 ;
Grain yield and variety research plots located approximately 300 metres directly down wind a 200 metre long cross wind line of 10 metre high open forest Australian Buloke trees, with a total area of 9 ha’s.
This patch of 9 ha’s of open forest was located directly upwind of the plots in the the prevailing winter westerly winds
Plots extended another 60 metres down wind so the nearest plots to the tree line were at about 300 metres distance and the furtherest set of plots were at about 360 metres distance from the tree line, all directly down wind in the prevailing winter westerly winds.
Two identical precision rain gauges were installed, one at the plots nearest the trees [ 300 metres] and one on the furtherest downwind side of the plots [ 360 metres ]
Terrain again is dead flat with no other obstructions of any type other than that patch of Bulokes, within a couple of kilometres.
There was a completely consistent difference in readings over some 3 months winter rainfall of some 20% between those two gauges.
The gauge closest to the trees some 300 metres away gave the lowest readings.
We measured those gauges as accurately as we could with a variety of methods.
We swapped those two gauges a number of times but nothing we did changed that consistent difference in rainfall amounts between those two gauges only 60 metres apart.
To repeat; The terrain was an open dead flat, sown paddock right across to those trees and for at least a kilometre or more around.
The wind roll over effect from those trees was probably reason for that difference in rainfall amounts and that is the only explanation I can come up with for that remarkably consistent difference in those rainfall readings.
I believe that a similar rainfall / paddock experiment in Western Australia also found similar unexplainable differences in rainfall patterns that could not be accounted for by any logical explanation.
As an old Glider pilot with nearly 50 years glider flying plus some power flying , I have flown mountain wave systems and know the effects of airflow around hills and over mountains.
Twice I have come close to being killed by the roll over of strong winds over a dense line of trees located across and upwind of where I was landing a glider.
Despite a higher than normal airspeed I simply lost all my airspeed in a couple of seconds, as from 60 knots to zero when I hit the front down draft from the roll over and then a few very, very long seconds later it jumped to over 70 knots in about a second as I hit the backside updraft of that particular roll.
That line of trees were located some 2 kilometres directly upwind from where I was trying to land.
I know the turbulence that is generated a kilometre down wind from a steady wind across a hangar complex at a small country airport with one sealed strip, when a light aircraft is low down on approach for landing.
Even where there seems to be very good locations for weather recording stations, I look at those sites and photos and I can see immediately where serious measurement problems can originate from quite long distances away as in hundreds of metres away from small as well as large obstructions.
Obstructions and small terrain changes at distances that those with little knowledge or experience on just how our complex atmosphere is constantly changing and moving would discount as not worthy of bothering about.
Unfortunately the accuracy of the measurements of temperature, rainfall, humidity and temperature can be and are often seriously affected and in nearly every case the effects on rainfall and etc are unknown, unmeasured and are not even ever taken into consideration or recognised as a serious problem for accurate data measurement.
“Hartmann says measurement errors of up 400% can occur over time when measuring powdery snowfall in alpine, polar or windy areas.”
I wonder if that is what is happening in internal Antarctica. They say it is a “desert” with little precipitation. But there have been stories right here on WUWT showing people digging out instruments & having to raise instrument towers to account for snow covering it…all that snow & ice has to come from somewhere – it’s all not just being shuffled around.
Jeff
speaking of precipitation…
I live in Southern California.
Last year was officially the wettest year Southern California has ever had.
At this time this year we are at: 13.94 ”
Normal is: 9.92 ”
Last year at this time was: 5.27 ”
If I wanted to jump to conclusions, I’d say mother nature is turning So.Cal back into swampland.
Jantar says:
October 24, 2010 at 6:02 pm
The cause of error in measuring rainfall you described has not been mentioned in the article.
JKrob says:
October 25, 2010 at 5:27 am
You discussed the measurement error due to distortions by wind-driven snow. Without a doubt, snowfall measurements can be lower than the amount of snow that actually fell, for all of the reasons discovered and discussed. What was not discussed in the article by Christoph Hartmann is the possibility of more snow fall being measured than actually deposited.
Our farm is in a flat area in which during the winter arctic-like conditions prevail quite frequently. That means that in some locations in our area it can happen that, when strong winds blow, much snow that fell already weeks prior is picked up by winds and redeposited, so much so that daily snow-plowing is necessary even though no snow had been falling for weeks.
That sort of drifting does not involve just a bit of snow at ground level, but the snow can be lifted to such heights that the sun is obscured. Such conditions are very common in the Arctic. Those sort of conditions are not accounted for in the explanations of the measurement errors explained by Christoph Hartmann. However, that is hardly surprising, such conditions rarely, if ever, occur in Germany (except perhaps in the mountains, although I am not aware of rain gauges being located on any plains there).
John Trigge says:
October 24, 2010 at 11:10 pm
The article by Christoph Hartmann does not mention earthquakes as a cause of error when measuring rain fall. That does not mean that your observation is incorrect.
A search of the Internet for “precipitation “measurement error” earthquake” produces 1,910 results.
A search of the Internet for articles on “precipitation “measurement error” wind” produces 6,420 results.
Thanks, Anthony. There is nothing “these people” won’t falsify or fraudulently alter for their purposes, it seems. The technology for data gathering must be put through rigorous scrutiny and no one does it quite like you. I also like it when we not only read about “the science” but about “these people”, who funds them, and for what “purposes”.
As to Tim’s assertion (5:33 pm): “A warmer world is a wetter world so lets generate some more water vapor (you know that REAL GHG!).” Tim, it all depends on where you live when on Earth’s surface. The western U.S. goes into major droughts (according to the research I have seen) during warm periods, e.g., MWP. We do much better re water during the cold times. Is this the same for the west coast of South America? Is this true for Australia (with four oceans)? If I remember correctly the Sahel/Sahara greens during the warm times. So, I think we must differentiate between warm-wet, warm-dry, cold-wet and cold-dry — up to a point. Overall warmer is better, certainly better than advancing glaciers, but tell that to the Anasazi (major droughts 1130-1180 and 1276-1299).
Therefore, generalizations “should be” corrected for long term history — at least the Holocene, the warm periods of which are getting less warm with each cycle. (Please correct me if I am wrong.) What a powerful combination: technology (rain guages) corrected for observation and expermentation; transparent and accountable science with vigorous “scientific” debates; a knowledge of Earth’s history and changes.
“DesertYote says:
October 24, 2010 at 8:15 pm
The noise machine is setting up the ground work for what they anticipate might be a cooling trend. If it global temps cool, then they can start talking about drought. Warm-Wet or Cool-Dry, they will always have something to talk about, and its mans fault! ”
You got it buddy and their carbon tax will fix all problems!!
The paper demonstrates the failure of peer review in climate science. It uses the model output produced for the Fouth Assessment Report (AR4), without any acknowledgment or review of the diagnostic literature. Projections of drought without assessing the error introduced by Wentz’s finding that the models produced only one third to one half of the increase in precipitation associated with the warming are a travesty.
This later paper by Beate G. Liepert and Michael Previdi finds Wentz’s results confirmed in latent heat fluxes.
“Do Models and Observations Disagree on the Rainfall Response to Global Warming?”
http://journals.ametsoc.org/doi/abs/10.1175/2008JCLI2472.1
How did the author, his acknowledged Trenberth and the anonymous peer reviewers “miss” these papers? Maybe the only way to cleanup peer review in the climate science field is political. We need to lobby governments and legislatures to make sure that any that any model based studies they finance include a review of the diagnostic literature, and discussion of the implications of the known diagnostic issues of the models.
A worthwhile observation but the article lacks any connection between the modelled drought and the measured rainfall. Are you saying that models are tuned to measurements that are systematically low? Also, if measurement is systematically low, and always have been, how would this affect trend inference?
The piece is a good start, but I think it opens more questions than it closes. I guess that’s the point…
Oh, this is a huge issue. We’ve been testing various snow gauges for a number of winters now and it’s a very time consuming task. We had to hire contractors to come and monitor the gauges and collect manual measurements for every snow fall, 24/7. Getting accurate liquid water equivalents is very difficult. A couple of years ago, we had issues with a hot plate we were deploying to the field, and the manufacturer told us that it was because we were having wind with the snow, and that wasn’t normal. We still joke about that.
My big problem with all rainfall data is that it is reported as an arithmetic average. Yet it doesn’t matter over what time scale you measure it – the distribution of rain follows anything but a normal distribution. Weibull, yes, and even log-normal is quite a good approximation, but normal it is not. That means that the arithmetic average is biased high relative to the mode (or most likely). If you rely on the arithmetic average, you will generally get less than you expect. So predictions of drought are self-fulfilling, nothing less than a simple statistical artifact.
Are there any papers discussing precipitation and land use changes?
Would farmers changing how the farmed (irrigation methods, sprinklers vs gravity flooding, etc) as well as the types of crops grown (more water needed for some vs others).
All would seem to influence the amount of H2O in the air.
If there were more farms using more water in the past and fewer modern farmers using water more efficiently and drought tolerant crops could make a large difference.
Field measurements that are systematically biased by extraneous environmental factors are nothing new in geophysics. The critical question is whether that bias is static or variable over time. In the former case, we may not know the absolute amount, but we can determine the changes reasonably reliably, and even the abolute values may be estimated well. This may be the case with rainfall. However, if the bias evolves over time in some unknown fashion, as with UHI, then the measurements provide entirely unreliable indications of the variable of interest. The two distinct cases should not be confused with one another.