0900 – 1000 RAWS STATIONS
Final Objective/ History/ Background
1000 – 1130 Breakout groups to analyze RAWS
data
1130 – 1230 Lunch
1230 – 1430 Complete RAWS Station Selections
1430 – 1500 Wrap-up
MAKE A PRIORITIZED LIST OF RAWS STATIONS
WHICH REPRESENT LARGE SCALE CLIMATIC
ZONES FOR USE AS PART OF THE NATIONAL
RAWS AND AUTOMATED NFDRS SYSTEMS.
WHAT WE WANT
TO DO TODAY…
SELECT RAWS WEATHER STATIONS WHICH
WILL BE PRIORITY SITES
•
MAINTAINED TO ALL NFDRS STANDARDS
•
PURCHASE THE LATEST HARDWARE AND SOFTWARE
•
ENSURE MINIMUM DOWN TIME DURING FIRE SEASON
•
REPORTING TIMES NEAR 2PM
•
ANNUAL VEGETATION CONTROL AND SITE MAINT.
•
SEND RAWS STATION LIST TO PNWCG STEERING
COMMITTEE
WHAT WE ARE NOT
GOING TO DO TODAY…
FOCUS ON NON-RAWS OR LOCAL WEATHER
STATIONS USED FOR
• FORECASTS
• IFPLS
• SMOKE MANAGEMENT
• SPOT FORECASTS
CURRENT AND PAST PNWCG WWT MEMBERS
CURRENT PNWCG WWT MEMBERS
Roddy Baumann
US Fish and Wildlife Service
911 NE 11th Avenue
Portland, Oregon 97232-4181
Greg Sinnett
Washington Dept of Natural Resources
PO Box 47037
Olympia, Washington 98504-7037
Phone:
503-231-2075
Phone:
Fax:
503-231-2364
Fax:
Email: Roddy_Baumann@r1.fws.gov Email:
Gene Lonning
Bureau of Indian Affairs
911 NE 11th Ave
Portland , Oregon 97232
Phone:
Fax:
Email:
503- 231-6761
503-231-6774
glonning@bia.gov
360-902-1328
360-902-1781
Greg.Sinnett@wadnr.gov
Gerry Day
Northwest Int Coordination Center
5420 NE Marine Dr
Portland, Oregon 97218-1089
Phone: 503-808-2732
Fax: 503-808-2750
Email: Gerry_Day@or.blm.gov
Jim Brain
Paul Werth
Northwest Interagency Coordination Center US Forest Service Retired?
5420 NE Marine Dr
Portland, Oregon 97218-1089
Terry Marsha
National Weather Service
Phone:
503-808-2737
Portland Fire Weather Office
Fax:
503-808-2750
Email:
pwerth@fs.fed.us
Tom Nichols
National Park Service
600 Harrison Street
Suite 600
San Francisco, California 94107
Mike Ziolko, Chair
Oregon Department of Forestry
2600 State Street
Salem, Oregon 97310
Phone:
Fax:
Email:
Phone:
Fax:
Email:
415-427-1371
415-427-1487
Tom_Nichols@nps.gov
PAST MEMBERS
AND TASK GROUPS
503-945-7452
503-945-7454
MZiolko@odf.state.or.us
WEATHER STATION ANALYSIS
HISTORY
MID 1990’S EFFORTS WERE MADE TO ESTABLISH
WEATHER STATION NEEDS.
1996 – A USER SURVEY WAS COMPLETED BY PNWCG
MEMBERS AND THE FIRE WEATHER OFFICES.
1997-PRESENT - NWS MAR CHANGES CAUSED WEATHER
WORKING TEAM TO FOCUS ON FIRE WEATHER IMPACTS.
2000-PRESENT - JIM BRAIN AND TERRY MARSHA WORKED
ON SEPARATE APPROACHES TO ANALYZE WEATHER
STATIONS.
HISTORY /BACKGROUND
JIM BRAIN’S ANALYSIS
•1996 SURVEY
•NFDRS STUDY
•NFDRS STATION STANDARDS
•ALL WEATHER STATIONS STATEWIDE WERE ANALYZED
•FIRE FAMILY PLUS PROGRAM USING WIMS DATA
•WEATHER STATION COSTS, DATA QUALITY, ASCAD DATA
MAINTENANCE, HARDWARE, SITE PROBLEMS
Basic Station Data—This information came from the
WIMS station catalogs, ASCAD data base and NWS
operating plans. It is basic station data.
Observations available in NIFMID—
This data was developed from the observations that he
downloaded from the NIFMID data base into
FireFamily Plus.
Blanks represent obviously no data was available for that
year. It should be noted that this is data available in
NIFMID and may not represent the data that was
available at 1300 LST to the NWS as several units do not
enter their data until later in the day.
The maximum number of observations per year is 123.
90% data availability=111 observations per year. 80%
data availability= 99 observations per year. Information,
in 1992, lost during the conversion from AFFIRMS to
WIMS.
Comparison of Burning Index (BI) and
Energy Release Component (ERC) values—
What is displayed here are the 25th, 50th, 75th and 90th
percentile values for each of the NFDRS elements.
In other words, the value displayed under the 90th column
indicates that 90% of the time the NFDRS value is equal
to or less than that value.
The purpose for displaying the four different values is to
demonstrate that the frequency distribution pattern often
varies by station and that the traditional way of comparing
stations using the 90th percentile values may not tell the
whole story.
Comparison of Weather Elements—What is displayed
here is the 25th, 50th and 75th percentile values for RH
and Temperature.
In addition the mean monthly wind speed for July,
August and September are shown as is the percentage
of the observation days without measurable
precipitation.
The annual precipitation and station elevation figures are
from the WIMS catalog information and are included to
help explain possible causes for variation within the
weather zones.
HISTORY /BACKGROUND
TERRY MARSHA’S ANALYSIS
Goal: Define an objective method that could be
used to create a more efficient RAWS network
that adequately meets the needs of land/fire
managers while reducing needless redundancy.
Primary regard is given to NFDRS and forecasting
for fire weather and smoke management.
Given: A network of approximately 200 RAWS
currently exists in Washington and Oregon.
Assumptions:
1. The current network of RAWS adequately represents
the weather of the PacNW.
2. Within the current network of RAWS exists a smaller
subset of RAWS that is equally representative.
This analysis is comprised of two parts.
First a wind rating is determined for each RAWS in the
analysis.
Secondly, a cross correlation matrix of the daily
minimum afternoon relative humidity of the RAWS
within a particular area is developed. The results of
these two tools provides the means for determining
the final RAWS network.
Wind Rating:
The purpose of the wind rating is to objectively assess the wind
characteristics of each RAWS in order to try and ensure that as
many as possible of the RAWS in the final network are wind
sensitive.
A “good” wind sensitive RAWS should show an ability to
respond with elevated wind speeds when the weather dictates
and also show good variability.
These characteristics can be determined by inspection
of the distribution of the RAWS’s hourly wind speed.
Procedure:
Start with a database of hourly weather observations for all
RAWS covering several summers. For each day the peak wind
speed is determined for each of six “4-hour” time periods covering
the full 24 hours of the day. This is done for each RAWS in the
network analysis.
A “climatological” distribution of the peak wind speed for each
“4-hour” time period for each RAWS is generated and the median
and 90th percentile value of the peak wind speed is determined for
each time period.
A “spread statistic” is defined as:
(90th percentile peak WS) – (median peak WS) / (median peak WS)
This statistic indicates the amount of variability in the RAWS’s wind
speed frequency distribution (much like the standard deviation).
From the value of the 90th percentile peak WS and the “spread
statistic” defined above, the wind sensitivity rating for each
“4-hour” time period is determined for each RAWS using the
following criteria.
a. 90th percentile peak WS ≥ 10 mph during a “4-hour” time period
b.“spread statistic” for the same time period ≥ .50
The above criteria indicates adequate or better wind sensitivity.
Wind ratings are determined as follows:
RATING
0 - if the above criteria were not met for any of the six
“4-hour” time periods of the day
1 - if the above criteria were met for at least 1
“4-hour” time period of the day
2 - if the above criteria were met for at least 1 daytime
and 1 nighttime “4-hour” time period
A wind rating of :
0 is considered “inadequate” ; 1 is “adequate” ; 2 is “good”.
Effort should be made to ensure that as many of the RAWS as
possible in the final network have a wind rating of 1 or 2.
RH Correlation Analysis:
After the wind sensitivity rating is determined for each RAWS, the
cross-correlation analysis of the daily minimum relative humidities
of the RAWS can be done.
This is the main analysis for determining the “key” RAWS making
up the final network.
*note…Daily minimum RH is a good element to use for determining
similarity between RAWS but one could experiment with other
elements as well such as some NFDRS index or component.
Procedure:
Start with a database of daily afternoon minimum RH’s for all
RAWS in your analysis. Correlate the minimum daily RH of each
RAWS with the corresponding minimum RH of all other RAWS
in your analysis.
This results in a cross-correlation matrix showing how each
individual RAWS correlates with every other RAWS in your
Analysis in terms of daily afternoon minimum RH.
Select from your cross-correlation matrix the RAWS with the most
correlations at or above a chosen threshold and designate as
RAWS 1.
I have found that for RH, a correlation coefficient threshold of
around .90 is a good choice but really depends on the area
being analyzed. If you desire more stations in your network select
a higher threshold ( ie .92 ) or if you want less key stations,
choose a lower threshold. Remove from your analysis RAWS 1
and all the other RAWS that correlate with it at your threshold
value or higher.
Remove from your analysis RAWS 1 and all the other RAWS that
correlate with it at your threshold value or higher. From the
remaining RAWS, repeat step 2 and and designate as RAWS 2.
Again remove RAWS 2 and all those that correlate with it at your
threshold value or higher.
Continue repeating steps 2 through 4 until either no stations
remain or none of the remaining stations correlate with another
at your threshold value or greater.
What you are left with is a subset of “KEY RAWS” that are
uniquely different from one another as defined by your selection
of a correlation coefficient threshold. All other RAWS may be
discarded from your network because they correlate highly with
at least one of the Key RAWS.
You will find as you proceed through this analysis that often you
may have a “tie” between several RAWS and need to make a
choice on which to pick as a “key”. In such instances, I would
recommend placing high priority on stations having a wind rating
of a 1 or 2.
EXAMPLE
WESTERN WASHINGTON RAWS SITES
Area 1 - Olympics
Area 2 - Coastal
Area 3 – W Washington Cascades
Area 4 – NW Oregon Cascades
Area 5 – SW Oregon
Area 6 – NE Washington Mtns
Area 7 – Central Washington
Area 8 – N Central Oregon
Area 9 – S Central Oregon
Area 10 – Blue Mtns
Area 11 – SE Oregon
PROPOSED
RAWS SITES
PNWCG WEATHER WORKING
WEBSITE…
OTHER WEATHER SITES
TO RESEARCH…
DISCUSSION