John Dann wrote:

On Fri, 25 Sep 2009 08:47:53 +0100, "Will Hand"
wrote:
Put simply - chaos in action!

If I might be permitted a small hobby-horse aside here, I do wish this
word chaos had never become associated with atmospheric modelling. To
my way of thinking, this behaviour is not chaotic at all, it's
sensitive, or super/hyper-sensitive if you will (to the starting
conditions). Chaotic - to me - implies irrational or unknowable, which
is not what's happening here. Once you can define the starting
conditions with sufficient accuracy then the models can indeed run
with a rational outcome and so aren't chaotic.

JGD


I think the word chaos is used because so many of the important processes
taking place in the atmosphere are at scales that are orders of magnitude
smaller than can be resolved by the numerical models, at least the global and
regional models. If it can't be adequately modelled then it does appear chaotic

Norman

"Norman" wrote in message
...
John Dann wrote:

On Fri, 25 Sep 2009 08:47:53 +0100, "Will Hand"
wrote:
Put simply - chaos in action!

If I might be permitted a small hobby-horse aside here, I do wish this
word chaos had never become associated with atmospheric modelling. To
my way of thinking, this behaviour is not chaotic at all, it's
sensitive, or super/hyper-sensitive if you will (to the starting
conditions). Chaotic - to me - implies irrational or unknowable, which
is not what's happening here. Once you can define the starting
conditions with sufficient accuracy then the models can indeed run
with a rational outcome and so aren't chaotic.

JGD


I think the word chaos is used because so many of the important processes
taking place in the atmosphere are at scales that are orders of magnitude
smaller than can be resolved by the numerical models, at least the global
and
regional models. If it can't be adequately modelled then it does appear
chaotic

Norman


Chaos is a mathematical theory. Very simple looking equations can be
chaotic, i.e. miniscule changes in starting numbers can produce vast
differences very quickly. The Navier Stokes equations used to model the
atmosphere, I don't think are themselves chaotic, but they have no precise
analytical solution and so approximations have to be made using grids of
data. This introduces chaotic behaviour. Finer grids are not the ultimate
answer as errors can amplify more quickly then. There is a limit to
deterministic predictability with NWP, there will also be a limit to
statistical (ensemble) prediction as well, nobody is sure where those limits
are but they are there just the same. Some say 10 days, some say further
ahead before you get into climatology and dominant signals forced by
physics. HTH.

Will
--

On Sep 25, 8:47*am, "Will Hand" wrote:
"Dawlish" wrote in message

...
On Sep 24, 1:46 pm, Dawlish wrote:



On Sep 23, 7:20 pm, "Keith(Southend)"
wrote:

Seems to be consistency in all the models for a northerly plunge next
week as we enter the month of October.

September is turning out another very dry month here in Southend-on-Sea,
with currently only 8.0mm of rain (17% average), as it stands it will be
second driest after 1997 (7.6mm), 1985 (9.7mm, 3rd driest) temperatures
are also standing at 1.0°C above average.
--
Keith (Southend)http://www.southendweather.net
e-mail: kreh at southendweather dot net

There certainly *was* Keith!
I find the turn of events over this last week really interesting. 6
days ago, the models picked up the re-establishment of the high
pressure. The consistency and agreement was enough for me to forecast
at 10 days and barring something very strange, that forecast looks as
if it will be good. However, a short time after my forecast for the
29th, the ECM massively, then, to a lesser extent, the gfs showed a
northerly, which is likely not to occur. This "faux-northerly" stayed
on the charts for a couple of days and then over the last 36 hours has
been erased.

=====================

Paul, thank goodness it is not February, else you would see toys and tipped
over prams everywhere by now!

For me, substitute February for December and/or January. Bright and
mild weather in Feb is not at all unpleasant, it makes it seem like
spring has arrived (which, if one uses the criterion of winter being
the darkest three months, it has). On the other hand in Dec and Jan,
the cold and the snow are much more essential for aesthetic appeal,
there's little worse than endless dark, damp, drizzly days....

Nick

On Sep 25, 9:36*am, John Dann wrote:
On Fri, 25 Sep 2009 08:47:53 +0100, "Will Hand"

wrote:
Put simply - chaos in action!

If I might be permitted a small hobby-horse aside here, I do wish this
word chaos had never become associated with atmospheric modelling. To
my way of thinking, this behaviour is not chaotic at all, it's
sensitive, or super/hyper-sensitive if you will (to the starting
conditions). Chaotic - to me - implies irrational or unknowable, which
is not what's happening here. Once you can define the starting
conditions with sufficient accuracy then the models can indeed run
with a rational outcome and so aren't chaotic.

JGD

The term Chaos is quite appropriate to atmospheric
modelling because no matter how accurately the starting conditions are
defined (even down to the molecular level) the detailed state of the
system after a certain length of time is literally unknowable. That
length of time is less than a month, as far as I know. This behaviour
is called deterministic chaos because each successive condition
depends on the previous one but no-one can say which path the system
will evolve along. The individual infinitesimal steps in the process
are rational but the final outcome is not.

Tudor Hughes, Warlingham, Surrey.

On Fri, 25 Sep 2009 11:38:53 +0100, "Will Hand"
wrote:


"Norman" wrote in message
...
John Dann wrote:

On Fri, 25 Sep 2009 08:47:53 +0100, "Will Hand"
wrote:
Put simply - chaos in action!

If I might be permitted a small hobby-horse aside here, I do wish this
word chaos had never become associated with atmospheric modelling. To
my way of thinking, this behaviour is not chaotic at all, it's
sensitive, or super/hyper-sensitive if you will (to the starting
conditions). Chaotic - to me - implies irrational or unknowable, which
is not what's happening here. Once you can define the starting
conditions with sufficient accuracy then the models can indeed run
with a rational outcome and so aren't chaotic.

JGD


I think the word chaos is used because so many of the important processes
taking place in the atmosphere are at scales that are orders of magnitude
smaller than can be resolved by the numerical models, at least the global
and
regional models. If it can't be adequately modelled then it does appear
chaotic

Norman


Chaos is a mathematical theory. Very simple looking equations can be
chaotic, i.e. miniscule changes in starting numbers can produce vast
differences very quickly. The Navier Stokes equations used to model the
atmosphere, I don't think are themselves chaotic, but they have no precise
analytical solution and so approximations have to be made using grids of
data. This introduces chaotic behaviour. Finer grids are not the ultimate
answer as errors can amplify more quickly then. There is a limit to
deterministic predictability with NWP, there will also be a limit to
statistical (ensemble) prediction as well, nobody is sure where those limits
are but they are there just the same. Some say 10 days, some say further
ahead before you get into climatology and dominant signals forced by
physics. HTH.

Will

Hi Will,

I am not sure why you used the term statistical and ensemble together
here as ensembles of dynamic models are used in a probabilistic
framework. Is this what you were calling statistical models as it is
a term that is more often associated with empirical models e.g. those
that directly correlate rainfall over a region with SSTs etc.

Andy

"Andy" wrote in message
...
On Fri, 25 Sep 2009 11:38:53 +0100, "Will Hand"
wrote:


"Norman" wrote in message
...
John Dann wrote:

On Fri, 25 Sep 2009 08:47:53 +0100, "Will Hand"
wrote:
Put simply - chaos in action!

If I might be permitted a small hobby-horse aside here, I do wish this
word chaos had never become associated with atmospheric modelling. To
my way of thinking, this behaviour is not chaotic at all, it's
sensitive, or super/hyper-sensitive if you will (to the starting
conditions). Chaotic - to me - implies irrational or unknowable, which
is not what's happening here. Once you can define the starting
conditions with sufficient accuracy then the models can indeed run
with a rational outcome and so aren't chaotic.

JGD


I think the word chaos is used because so many of the important
processes
taking place in the atmosphere are at scales that are orders of
magnitude
smaller than can be resolved by the numerical models, at least the
global
and
regional models. If it can't be adequately modelled then it does appear
chaotic

Norman


Chaos is a mathematical theory. Very simple looking equations can be
chaotic, i.e. miniscule changes in starting numbers can produce vast
differences very quickly. The Navier Stokes equations used to model the
atmosphere, I don't think are themselves chaotic, but they have no precise
analytical solution and so approximations have to be made using grids of
data. This introduces chaotic behaviour. Finer grids are not the ultimate
answer as errors can amplify more quickly then. There is a limit to
deterministic predictability with NWP, there will also be a limit to
statistical (ensemble) prediction as well, nobody is sure where those
limits
are but they are there just the same. Some say 10 days, some say further
ahead before you get into climatology and dominant signals forced by
physics. HTH.

Will

Hi Will,

I am not sure why you used the term statistical and ensemble together
here as ensembles of dynamic models are used in a probabilistic
framework. Is this what you were calling statistical models as it is
a term that is more often associated with empirical models e.g. those
that directly correlate rainfall over a region with SSTs etc.


To me ensemble prediction is a form of statistical prediction as one uses
the ensemble mean and the members to determine the probability of an event
occuring. Of course correlation techniques are also statistical as you say.

Cheers,

Will
--