making climate products digestible kelly redmond western regional climate center
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Making Climate Products Digestible Kelly Redmond Western Regional Climate Center Desert Research Institute. 31st Climate Diagnostics and Prediction Workshop Earth System Research Laboratory Boulder CO, 2006 October 23-27. - PowerPoint PPT PresentationTRANSCRIPT
Making Climate Products Digestible
Kelly Redmond
Western Regional Climate Center
Desert Research Institute
31st Climate Diagnostics and Prediction WorkshopEarth System Research Laboratory
Boulder CO, 2006 October 23-27
Climate questions span a large range of complexity and purposes (orders of magnitude), and span a range from past to future.
In most cases, some kind of decision is involved.
Decisions take place in the future, and involve future conditions.
Actual forecasts pertinent to a specific question would be best, but mostoften such forecasts are not available, or would not be credible.
Many requests for past data or information pertain to an upcomingdecision.
Thus past behavior is often treated as a de facto forecast.
Past is prologue. The fact that something has happened once conveys considerable credibility.
A programmer’s perspective:
If it’s easy to use, it was hard for the programmer.
If it’s hard to use, it was easy for the programmer.
(from an NPS software consultant)
“The engineers who design cars never seem to have to fix them”
parental observation
“))^&*@*^$!_)!_)^&^%!#$#)(*&$%(*”
supplemental observation
Products are much better if users, or user perspectives, are integrated into design.
Better yet if designer has experience as both a user and a provider of information.
Benevolent Dictator ? vs. Committee ?
Learning by doing.
Start with a best guess.
This can often be pretty good. Dictated by experience.
Listen.
Iterate.
This approach can be slow and halting, but it has a rich track record.
Allowing for growth
First time users – handholding and help
Experienced users – shortcuts, and elaboration and sophistication
Well designed web pages have both levels available at once.
Fewer web pages to manage.
Short Attention Span Syndrome (“Faster,” James Gleick)
Even industrious people can be lazy about certain things
Saving labor (minimal hand movement, clicking and scrolling)
Ease and efficiency
Compactness
CDC Composites page
With thanks to Cathy Smith
Many other examples as well
WRCC Divisional Data plot page
2006 Oct 23 11:00 PDT
“ … think like a mountain …” (Aldo Leopold, A Sand County Almanac, 1949)
With climate products: think like a user
How to do this???
Know the user.
Firsthand is better, not always practical on an industrial scale.Secondhand can work, but needs intermediaries.
Provider push vs user pull
Provider has (actually or potentially) useful information for user
User wants certain information (perhaps needs, but does not recognize)
Role of climate services provider
Help the user to structure their thinking
Suppose your own personal resources were on the line … not just an abstraction!
What would you do ?How would you decide ?How confident would you want, or need, to be ?
Is this a voluntary decision, or a mandatory (imposed) decision ?
What makes you trust information ?
Track record is probably most frequently cited as desired information.
“How do I know I am not getting a pig in a poke?” (recent question)
What kind of track record information is most convincing?What kind of track record information is most relevant (objectively (?) )?
According to a climate scientist ?According to an average user ?
Skill measured how?Overall patterns, events, specific locations, specific circumstances, new or emergent phenomena
How well can humans evaluate pattern similarities by eye ? (O’Lenic talk)
Precip (Fcst / Obs) Jul-Aug-Sep 2006 Temp (Fcst / Obs)A real track record based on real forecasts, of which this is just one.
But, it is the most recent.
Precip (Fcst / Obs) Nov-Dec-Jan 2005-06 Temp (Fcst / Obs)A real track record based on real forecasts, of which this is just one.
This one is from the previous October.
Monthly Oct init 700 mb Height Skill 1982-2003 Seasonal
All areas CFS monthly 2006 Oct 22 With skill mask
All areas CFS seasonal 2006 Oct 22 With skill mask
Monthly Oct init Precip Skill 1982-2003 Seasonal
Monthly Oct init Temp Skill 1982-2003 Seasonal
The track record of real forecasts rather than
simulated forecasts.Here, CFS.
Disadvantage: short record.
Many other measures could also be
utilized:
CorrelationsSkill scores
Percent “right”Percent of application-
dependent events captured
A Noble Experiment: The Drought Outlook
Most of the forecast consists of expansion, contraction, weakening or strengthening of existing areas,
seldom new areas of formation.
This is partly the nature of drought, and partly the nature of drought forecasters
An new source of concern
What reference period should be used ?
Year
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
An
nu
al M
ean
Tem
per
atu
re (
F )
47
48
49
50
51
52
53
Western United States (11 states) Annual Jan-Dec TemperatureProvisional data from NCDC / CPC. Blue: 11-year running mean.Units: Deg F. Data source NOAA cooperative network, thru Apr 2006.
Western Regional Climate Center
End Year
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Oc
tob
er-
Ma
rch
Te
mp
era
ture
(F
)
32
33
34
35
36
37
38
39
40
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Western United States (11 states) Winter Temperature (October-March)Provisional data from NCDC / CPC. 11-year running mean in blue.Units: Deg F. Data source NOAA cooperative network, thru Apr 2006.
Western Regional Climate Center
Annual Mean Temperatures, 2000-2005. Departures from 1895-2000 Mean.
Non-standardized. Units: Degrees F. Normalized (standard deviations).
The West dominates recent U.S. warming.
Summer (Jun-Jul-Aug) Mean Temperatures, 2000-2006. Departures from 1895-2000 Mean.
Non-standardized. Units: Degrees F. Normalized (standard deviations).
The West dominates recent U.S. warming.
Autumn (Sep-Oct-Nov) Mean Temperatures, 2000-2005. Departures from 1895-2000 Mean.
Non-standardized. Units: Degrees F. Normalized (standard deviations).
The West dominates recent U.S. warming.
Winter (Dec-Jan-Feb) Mean Temperatures, 1999/2000-2005/2006. Departures from 1895-2000 Mean.
Non-standardized. Units: Degrees F. Normalized (standard deviations).
The West dominates recent U.S. warming.
Spring (Mar-Apr-May) Mean Temperatures, 2000-2006. Departures from 1895-2000 Mean.
Non-standardized. Units: Degrees F. Normalized (standard deviations).
The West dominates recent U.S. warming.
End Year
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Oct
ob
er-M
arch
Pre
cip
itat
ion
(in
ches
)
4
6
8
10
12
14
16
Western United States (11 states) October-March Precipitation.Provisional data from NCDC / CPC. 112 Winters, 1895-2006.Units: Inches. Data source NOAA cooperative network, thru Apr 2006.
11-year running mean
individual winters
Western Regional Climate Center
End Year
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Wa
ter
Ye
ar
Pre
cip
ita
tio
n (
in
ch
es
)
12
13
14
15
16
17
18
19
20
21
22
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Western United States (11 states) Water Year (Oct-Sep) Precipitation.Provisional data from NCDC / CPC. Blue: 11-year running mean.Units: Inches. Data source NOAA cooperative network, thru Apr 2006.
Western Regional Climate Center
Climate events unfold slooooooowwwwwwwly
The relation between verification time, and preparation time, is different than for daily weather forecasts.
Weather:Three work shifts per day, each 8 hrs long. Four 12-hour forecasts updated every 6 hrs (4x per day). Approximately 0.75 work shift per forecast update.
Climate:90 days is 270 work shifts, or 90 daytime work shifts. One daytime work shift is 1/30=.033 forecast period (monthly), and 1/90=.011 daytime work shift per seasonal forecast.
Thus, lots of time to watch the forecast verify. Or, not. Perhaps, more temptation to update. Also, time enough to forget forecast.
Easier to intermingle observations and forecasts, the longer the duration and lead time of the phenomena being forecast. Aspects of the forecast system can evolve during as the verifying period is unfolding. Forecasts can be nudged, modified, or otherwise re-interpreted as they play out. This is more likely to occur the longer the interval covered: monthly, seasonal, annual, decadal …
ENSO discussion: Forecasts less tentative when ENSO event appears to have started. Are these really forecasts? More like “observacasts”
What matters to users can be, and often is, very application-specific.
A small difference in circumstances or context, and it can be a whole new problem.
Prof. Julien Clinton Sprott, UW Madison Physics
Provider and user relationship. A lock and key situation. Like biochemistry.
Steroid and nuclear hormones
Human estrogen receptor–ligand binding domain hER-alpha-LBD
Tanenbaum et alPNAS, 1998 Feb 18
Stereo Image
Fix on estradiol:carbon blackoxygen red
Evaluation
Not of forecasts themselves, but of their use, and of system effectiveness
Done properly, this takes lots of attention, and takes skill
Attention and skill imply need for resources, perhaps significant
Process has often expended most of its energy and budget by this point
This part is often viewed as “extra” rather than integral
Resource decision
How to allocate resources to the forecast system
Basic understanding (need for better forecasts)
Better packaging and presentation of forecast information
Better understanding of the use and decision environment
How effectively is this knowledge plowed back into the forecast system?
Local applicability. User orientation. My back yard.
Whale Point (600 ft) and Highlands Peak (2500 ft), Big Sur. 2 miles apart.
Whale Point600 ft
Highlands Peak2500 ft
Whale Point, Big Sur, 600 ft, 10-min Temperature, July 2006 Heat Wave.
Highlands Pk, Big Sur, 2470 ft, 10-min Temperature, July 2006 Heat Wave.
Audiences for climate and climate forecast products
General - casual users, minor economic decisions
Interested - modest economic decisions (eg, whitewater guide company)
Dependent - major decisions (eg, utilities, ag commodities, derivatives)
Water Year Temperature Departure700 mb (10,000 ft)1 Oct 2005Through31 Mar 2006
Warm Season Temperature Departure700 mb (10,000 ft)1 Apr 2006Through30 Sep 2006
Water Year Temperature Departure700 mb (10,000 ft)1 Oct 2005Through30 Sep 2006
Climate Test Bed offers many opportunities
Hydrologic forecasts could potentially benefit, perhaps considerably
NWS and NRCS, and many water managers.
Other resource managers
Providing model output that can link, or pipe directly, into applications
In an atmosphere of limited total resources, the ultimate importance of developing a supportive constituency for maintaining the research and operational infrastructure should not be underestimated.
Along with substance (assumed to be a given (!?!) ), the associated marketingsalesmanshippresentation
all take unexpectedly large amounts of time and resources.
A willingness to commit to this can mean the difference between success and failure.
What makes for a better dining experience?
Taste or presentation?
What makes for a better forecast use experience?
Accuracy or presentation?
What’s for supper?