Newsgroups: lter.ced
Path: LTERnet!root
From: "Bruce P. Hayden" <bph@envsci.evsc.virginia.edu>
Subject: Nov 92 CED
Message-ID: <1992Oct29.202234.6207@lternet.washington.edu>
Sender: root@lternet.washington.edu (Operator)
Organization: Long Term Ecological Research
Date: Thu, 29 Oct 1992 19:13:07 GMT

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        Vol.1  No.9 :::::: file name:CED1.9 :::::: November 1, 1992

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CED is the Climate/Ecosystem Dynamics bulletin board of the LTER network. 
In CED, you will find exchanges of ideas, information, data,
bibliographies,
literature discussions, and a place to get to experts within the LTER
community.  We are interested in both climate controls on ecosystems and
ecosystem controls on climate.  As this is an inter-disciplinary activity,
we hope to provide things that you might not come across in your work at
your LTER site.

CED is a product of the LTER climate committee and contributions to CED for
general e-mail release may be sent to either David Greenland of Andrews
LTER [Greenlan@oregon.uoregon.edu] or to Bruce Hayden of the Virginia Coast
Reserve LTER [bph@envsci.evsc.virginia.edu].  We expect that the scope of
CED will evolve and reflect the interests of the contributors and users of
this service.  CED will be issued as the preparation work gets done
(monthly?).  Back-releases of CED may be requested from  Daniel Pommert
[daniel@lternet.washington.edu] by the file name given in the masthead. 
Daniel can also add people to the CED mailing list.   

Feedback on CED from LTER scientists is welcome (non-$$$$ contributions
also welcome.)  For example, please forward citations of climate &
ecosystem publications on your site.  We will keep a LTER wide bibliography
on Climate/Ecosystem Dynamics that we pass on via E-mail. 


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     ***           SHOULD WE TRUST MODELS OR OBSERVATIONS?         ***
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The title of this piece comes from a paper by Hugh Ellsaesser in
Atmospheric Environment [Ellsaesser, H.W. (1982). Should we trust models or
observations?   
Atm. Env. 16(2):197-205].  The compelling need for me to do this piece
arose from a comment made at a recent conference on integrated regional
models.  The comment  went like this: "The role of the biosphere on the
atmosphere was not recognized until Shukla published his paper."  Shukla is
a late comer to this topic.  Shukla's paper was a General Circulation Model
(GCM) paper.  There was not a lick of data in it.  How is it that we have
come to believe models and not the dozens of scientific papers using data
that come the same conclusion?  CED readers, readers-in-the-know that you
are, know that vegetation impacts on the dynamics of the atmosphere are
very real. A robust literature is available and it has a very long history
indeed.  Now, for a decade some of us have been pushing GCM modelers to
recognize the role of sulfates in cloudiness and climate change.  Paper
after published paper implicated sulfate as a cloud maker.  Then, Jim
Hansen published a paper using the GISS GCM output statistics that included
planetary albedo adjustments for the trend in atmospheric sulfate and found
it largely offset CO2 warming.  The IPCC report included it as fact.  We
need a new piece of jargon "model-fact."  With time the hyphen in
model-fact will disappear and it will appear in polite discourse as
modelfact.  It will then join metadata as a term we just can't do without. 
So here we are, if you can get a model to project it, somehow, it becomes
larger than life.  Chris Folland, an IPCC author, when questioned about
this strange inversion of science noted that "The data don't matter."  He
went on to note that "global warming is model driven not data driven.  The
data just don't matter."  Now I have been engaged in modeling of one sort
or another for 15 years and will continue to participate.  However, the
standard long held in the atmospheric sciences is that the models must be
proven to have skill!  It must out perform chance, climatology and simpler
models before you offer it as an icon for belief.  For example, the GFDL
GCM transient run with 1% CO2 increase per year  puts out a global field of
temperatures for each year.  If the model begins with background CO2 circa
1820 and runs forward in time, one could ask the question how well has the
model accounted for the variance in global temperature patterns that was
actually observed.  Such tests, here at the University of Virginia, show
that the model explains 4% of the variance.  Clearly, you would not want to
use a model to make "predictions" about future conditions if you were only
explaining 4% of the variance which equivalent to a correlation coefficient
of 0.2!  GCMs are wonderful tools of experimentation [change one thing and
hold all else constant] and hypothesis generation but have yet to prove
their stuff as prediction tools!



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     ***                    HOW DO YOU GET WEATHER                 ***
     ***                        OUT OF A GCM                       ***
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The grid cells used in GCM models are bigger than the weather systems you
see on the nightly TV weathercast.  So how do you get high spatial
resolution information out of your GCM to run your ecosystem models?  This
is the job of BAHC of IGBP!  Your-obedient-servant has just joined the BAHC
[Biospheric Aspects of the Hydrological Cycle] working group of IGBP.  One
of the objectives of this group is to bring into being a "WEATHER
GENERATOR."  The Weather Generator would take the model output statistics
of a GCM and translate, simulate, synthesize, divine, etc., the weather and
climate numbers needed in ecosystem modeling.  This is more of a stochastic
endeavour rather than a deterministic number crunching undertaking.  For
those of you who want to look into the literature on this subject, here are
some useful papers.


Giorgi, F. and L. O. Mearns.  1991.  Approaches to the simulation of
regional climate change: A review.  Rev.in Geophys. 29:191-216.

Hay, L. E., G. J. McCabe, Jr., D. M. Wolock and M. A. Ayers.  1992.  Use of
weather types to disaggregate general circulation model predictdions.  J.
of Geophys. Res. 97(D3):2781-2790.

Knox, J.L. and R. G. Lawford. 1990.  The relationship between Canadian
prairie dry and wet months and circulation anomalies in the
mid-troposphere.  Atmosphere-Ocean 28:189-215.

Moss, M. E. 1992.  Bayesian relative information measure: A tool for
analysing the outputs of Atmospheric General Circulation Models.  J. of
Geophys. Res., 97(D4):3711-3724.

Wilson, L. L., D. P. Lettenmaier, and E. Skyllingstad.  1992.  A
hierarchial stochastic model of large-scale atmospheric circulation
patterns and multiple station daily precipitation.  J. of Geophys. Res.
97(D3):2791-2809.

Wilson, L. L., D. P. Lettenmaier, and E. F. Wood.  1991.  Simulation of
daily precipitation in the Pacific Northwest using a weather classification
scheme.  Surveys in Geophysics 12:127-142.


You may wince at the notion of taking the broad scale output of a GCM and
getting detailed (in space and time) stochastic "weather" data out of a
black box.   Remember that we do that now with the daily weather forecast
that come out of the machine forecasts from the National Weather Service. 
NWS products do not predict surface weather conditions directly.  Rather,
the NWS models predict conditions in the atmosphere above the surface and
then use regression equations to translate conditions from the
easier-to-predict air aloft to the very heterogeneous and hard-to-predict
surface.  The regression equations developed for each weather station out
perform direct machine forecast and human, expert system, forecasts.  They
do a better job and so the NWS uses them.  They work and will continue in
service until the NWS finds a machine means of forecasting the
difficult-to-forecast surface conditions.  Roger Pielke of Colorado State
University thinks that one of the reasons the models don't do the job with
surface conditions is that the NWS models have no biosphere in them.  Until
they contain real time biosphere conditions, we will have to rely on
statistical prediction based on a long record of real data.  

Some day every weather station may have to report local conditions of the
biosphere to help run models that predict the weather.  What might they
have to report?  Soil moisture, surface roughness, phenological stage
relative to transpiration and sensible heating, crop harvesting phenology. 
There was a time when the weather service made such observations and
published them with the weather reports.  Below is an example of a station
report to the national office:

Report from Monthly Weather Review [January, 1879]

Birds on the move:  Geese at St. Meinrad, Ind. on the 16th, Fall River,
Mass on the 12th, etc., ... Winter Wrens at Fallston, Md. on the 25th. 
Blue Birds at Plattsmouth, Neb. on the 24th, etc., etc.

Frogs piping at Fort Barraneas, Florida on the 23rd; Okalooska, La on the
17th and Fayetteville, N. C. on the 24th.  Bees at Fayette, Miss. on the
28th carrying pollen.

Sacramento, California poplar in bud on the 23rd. Mayport, Florida oranges
encased in 1/2 ice -- fruit uninjured.  Georgia forsyth blooms on 29th,
alder bushes in full bloom.  Augsta, Georgia elms bud on the 25th.  

Why is the weather service reporting on the phenology of the biosphere? 
Well, in those days the weather service was part of the War Department!!!
and was within the domain of the Office of the Chief Signal Officer.  

The reason for all this might become clear from a statement in the May 1897
issue of Monthly Weather Review ..."The phenologist must be allowed to
consider his observations of plants as being a record of climate, just as
the meteorologist does his observations of the atmosphere, and both of
these students must be very careful about drawing hasty conclusion."  Sound
advice to us all. 

In the September 1896 issue of Monthly Weather Review Professor L. H.
Bailey of Cornell University provides a useful essay on Phenology.  On page
330 
he makes the point ..."Nearly all phenological records in this country have
been made by botanists, and they are printed in the botanical or natural
history publications.  This means that the subject is a biological one
rather than a climatological one.  I hope that this attitude may now be
shifted, so as to place phenological records with the science of climate
rather than with the science of organisms."  

Well, Roger Pielke at CSU may see the future and the biosphere will again
become part of the data collection business of the weather geek!  It would
be nice to be able to use NOAAs network of hundreds of weather stations to
collect phenology data!  Dream on.  

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     ***                 Phenology & Climate Change?               ***
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Not far from the current site of Virginia Coast Reserve facility at Oyster,
Virginia is the townette of Birdsnest.  This should not be confused with
Bird-in-the-hand.  That is a nice  little town in Amish Pennsylvania.
Birdsnest, Virginia was first a Smithsonian, then a Signal Service and then
a Weather Bureau installation.  Mr. C. R. Moore began keeping climate and
phenological records at Birdsnest in 1868.  By 1897 (Monthly Weather Review
May 1897) he had concluded that the climate of the Eastern Shore of
Virginia had changed.  Phenological data convinced him it was so.

Moore arrived at Birdsnest in 1867.   He was told that when the older men
of the area were boys you had to have your corn planted by April Court (1st
Monday) or you would be behind.  In the 1890s May court was the right time!
 The same old men said that in the first decade of the 1800s you could get
a peach crop every year!  In 1879 Moore set out an orchard of 2000 trees
including 200 peach trees.  In only one year in five could he get any
peaches.  Warm spells in February and March would bring out the buds and
blooms and April frosts would kill them.  

Corn and peaches convinced Mr. Moore that the climate had changed.  Today
the average date of the last killing frost of spring (28 F) is March 30. 
There is a 1 chance in 5 as late as the 11th of April.  The modern period
thus would appear to be much more like the early 1800s than the late 1800s.
 While we get three crops a year on Virginia's Eastern Shore, orchard crops
are not the choice of farmers.  Flowering in February and March is not the
orchardist delight!  

 

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        ***   One would rather see a wolf in February    ***
        ***   Than a peasant in his shirt sleeves.       ***

                              and

        ***   A February spring is not worth a pin.      ***

                              and

        ***   March flowers make no summer bowers.       ***

                              and

        ***   A year of snow, Fruit will grow.           ***

                              and

        ***   Year of snow, Year of Plenty.              ***

                              and

        ***   January blossoms fill no man's cellar.     ***
        
        *                                                  *
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     ***                 Reply: Pinhead or Fathead?                ***
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One of the Alaska CC meeting participants passes on this to all concerned
about the hat-button classification. "I looked at all the hats in my closet
and found that the number of buttons showing varied a lot."  My. My.  Here
are some explanations.  1] The hats are a long-term data base (the 6th core
area of an LTER!) and should be viewed in their proper chronological
sequence (a chronosequence).  It is possible that the sequence will show a
succession from fathead to pinhead or pinhead to fat head!  2] Like the
diameter of a tree there may be variations in head diameter proportional to
the level of scientific production when the hat was last used.  3] Graduate
students, they come in all cephlometric dimensions, have had access to the
hat collection and have used them in the mistaken belief in the osmosis
theory of education.  4] Graduate students, they come in all cephlometric
dimensions, have had access to the hat collection and have used them in the
mistaken belief in the theory of reverse osmosis. 5] Hat button size on a
specific day my be a function of days since last trip to the barber shop. 
Academics are notorious for stretching out the time between haircuts! 6]
Hat manufactures do not follow Hatcher-Capson-Dunce Baseball Cap Size
Control Act of 1988.  Violation of this federal law requires that the
breacher run for the office of Vice President in the next available
election. There was only one law breacher in 1992!

There is a substantial rush to the old, non-plastic-fastener, baseball cap.
 This may be due to the now recognized and feared pinhead to fathead scale
that was a product of LTER research.  The old style hat had a small white
hat size tag inside with a hat-size resolution in eighths like the stock
market.  These hat sizes are not visible to the public.  The return of the
old style caps may also be because they cost a lot more and the marginal
profits are better.  Who would pay $22.75 for a baseball cap?  LTER,
thick-skinned cheapskates will probably continue to wear the
size-detectable, plactic-fastener, style cap they have come to depend on.

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     ***                      PRAIRIE FIRES                        ***
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Prairie Fires were reported in Monthly Weather Review on a regular basis
during the late 1800s.  The location, dates and durations of the fires were
reported. Sometimes the extent of the fire was also noted. 

Report from Monthly Weather Review [January, 1879]

Prairie Fires at North Platte, Neb. (24th-26th); Independence, Ia. (29th);
Fort Sill, Ind. (22nd); Eagle Pass, Texas (15th & 16th), etc., etc. 

Now I am not a specialist on prairie fires but perhaps the Monthly Weather
Review reports are the only national record of prairie fires to be had.  As
this might be of value to our prairie-LTER friends I pass it on for what it
is worth.


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     ***                NEW ADMONITION ON SUNBATHING               ***
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From Reuters October 1992 -- The Chilean Government has warned residents at
Punta Arenas (53 S latitude) against sunbathing between 10 AM and 4 PM. 
That old devil ultra violet light (remember the blind sheep incident) is at
its pesty best again.  According to a local professor, the UV radiation has
increased 200% since July as the south polar ozone hole slipped across the
southern most part of Chile.  A check of the radiation tables indicates the
why of this story.  The average radiation at 45 S is 11 megajoules per day
in July.  In October, the average value is 22 megajoules per day.  200%
increase between July and October is what comes naturally!  At 55 S it is
250%.  The Chilean government might well have checked the mean temperatures
in this southern-most, sunbathing Mecca.  In October, the 10 AM to 4 PM
average temperature is 46 F.  Nice brisk sunbathing.  Being a generous
fellow, I assumed that the average wind speed in this climate, the "frantic
50s," [a bit breezier than the roaring 40s] is but a modest 15 mph.  The
wind chill would be below freezing. Think of the sunbathing costs.  At a
toasty 60 F and 15 mph and in your all-togheher, you would need 22 lbs/hour
of good high fiber, low-calorie cabbage to replace the losses in body heat.
 Unless you are addicted to cabbage, you should only take part in only
short periods of ray catching in Punta Arenas.  When you use Reuters as you
publication medium what chicken little has time for fact checking?


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For our readers who care here are some statistics on the November issue of
CED.  The Flesch Reading Ease Score is 54.0.  That falls into the
"standard" category.  The Flesch-Kincaid Grade Level was 9.5.  83% of U.S.
adults should have been able to read this issue of CED.  How will we get it
to them all?  The Gunning Fog Index was 12.9.  That means that this CED
could be shot with buckshot at 100 yards!  Flesch wrote the book Why Johnny
Can't Read.  I don't know who Gunning was but anyone who invents a fog
index for writings isn't a laywer.



----------------+--------------------------------+-------------------------
Bruce P. Hayden |  Dept. Environmental Sciences  |  bph@virginia.EDU
(804) 924-0545  |  Clark Hall, Univ. of Virginia |  bph@virginia.BITNET
(804) 924-7761  |  Charlottesville, VA 22903     |  (804) 982-2137(fax) 
----------------+--------------------------------+-------------------------

