Meteorological Variability Call

Wednesday, April 23, 1997

10:30 - 11:30 am

Attendees:

David Chock	Ford Motor Company

Bill Cox	U.S. EPA/AQMG

Ned Meyer	U.S. EPA/AQMG

S.T. Rao	New York

Jay Rosenthal	USN

David Sanders	U.S. EPA/OPSG

John Silvasi	U.S. EPA/OPSG

Bob Stallings	U.S. EPA/OPSG

Steve Ziman	Chevron

Igor Zurbenko	SUNY-Albany

Contractor Support:

Stephanie Bowens	SAIC

Summary of the Call

David Sanders opened the call stating that the purpose for the call was to look at the issue of meteorological variability , within the context of Question #3, which has been given to the STSWG by the NRSWG. Question #3 is as follows:

As discussed in item #1, there is a desire to assess air quality metrics at pre-determined intervals in order to determine if the emissions reduction program being implemented are bringing an area towards attainment at the planned rate. In general, the philosophy is "the shorter interval the better" so that if a mid-course correction is needed it can be implemented rapidly so the attainment dates are met. However, it is also recognized that meteorology may exert a short-term influence on these metrics that may have no bearing on whether or not the emissions reduction programs being implemented are having the desired influence on air quality. Is there a valid method for identifying meteorological events that result in ozone or PM-fine concentrations that should be considered "statistical outliers" in an air quality analysis? Also, are there tools that can be applied to "remove" the effect of meteorology in order to better understand true air quality trends? This would include tools not only to eliminate the influence of meteorology that increased concentrations of PM-2.5 and/or ozone but also meteorology that depresses concentrations (i.e., cool summers, etc.).

David Chock questioned what the group's emphasis was? He stated that if it was meeting the air quality standard, that this goal would make it very difficult to measure and assess progress. Mr. Chock suggested that instead of seeking the air quality standard for assessing progress, we should instead be looking for some type of general trend or some part of the overall distribution, which could be classified as being stable. He reiterated that the extreme value approach would not be useful. Mr. Chock said that the feasibility of attainment was being addressed elsewhere in the FACA process, specifically under the RFP Issue Paper.

S.T. Rao asked the rhetorical question, "Are the tools available to do these types of analyses". Mr. Rao answered himself saying that the tools were definitely available.

Steve Ziman said that there were issues that needed to be addressed, independent of whether attainment was feasible. Mr. Ziman indicated that we needed to be able to determine if air quality was actually improving. He stated that this would take 5-6 years of data collection and analysis in order track progress or determine a trend. He concluded that a 3-year data collection effort would be much too short to identify meteorological variations. Mr. Ziman questioned if the group was actually looking at extreme values, or simply looking at excursions above some "bright line"?

David Chock interjected that this process would be much more difficult utilizing an extreme value approach.

S.T. Rao again asked the group if the tools were currently available? Mr. Rao conceded that tools to accomplish all points may not be available. However, he agreed that 3 years of data was too short. He asked the group is it possible to distinguish the signal from the noise? Mr. Rao stated that the time needed to adequately predict trends was not the question before this group at this time. He said that temperature provides a good surrogate for long-term scales; over long time scales, temperature provides a surrogate for climatic changes. However, at medium time scales, this is indicative of seasonal changes, and at shorter time scales, temperature is a good indicator of daily effects. Mr. Rao concluded that he is extremely confused about Mr. Chock's statement about "fixing" meteorology; he questioned how one does this?

Jay Rosenthal reminded the group that changes in meteorology are unique to the location where they are observed. Thus, he cautioned the group no to ignore the spatial variability associated with meteorology. He encouraged the group not to look solely at temporal variability of the meteorology.

S.T. Rao agreed with Mr. Rosenthal's comment.

David Chock explained that "fixing" the meteorology was referring to normalizing or standardizing the meteorology in some way.

S.T. Rao reminded Mr. Chock that his analyses were capable of explaining over 85% of the variance in the system.

David Chock suggested that perhaps cluster analysis might be an useful tool to utilize here.

Steve Ziman suggested that these discussions were all well and good; however, he reminded the group that longer term climatic signals (e.g., El Niño, etc.) were important here as well.

S.T. Rao emphatically stated that the issue here was being able to separate the signal from the noise.

Jay Rosenthal asked if it would be possible for the individuals on the call to list the specific meteorological variables which would be relevant to conducting a trend analysis?

S.T. Rao stated that he had looked at meteorological variability in a number of different areas of the United States. He questioned whether actual trends could be identified? He concluded that this could be done if the appropriate precursor concentrations were available.

Steve Ziman and David Chock agreed that the precursor concentrations were necessary to adequately resolve this issue.

S.T. Rao reminded the group that what was necessary here was to generate a process that would demonstrate cause and effect, and lead to a better ability to separate the signal from the noise.

David Chock questioned how this could be done?

S.T. Rao indicated that this could be done using filtering and other statistical tools. Mr. Rao said that it was not feasible to look at all variables at every time scale. He stated that he and his colleague (Igor Zurbenko) at SUNY-Albany, accomplished their task by deconvolving the ozone time series into four (4) separate components, based on temperature time series. Mr. Rao stated that his research had looked at changes in the ozone data related to solar radiation, temperature, humidity and other meteorological variables.

Igor Zurbenko described the statistical analysis of ozone data, reminding the group of the need to separate the time series into their respective temporal components: climatic, seasonal and daily.

S.T. Rao stated this type of a process would lead to establishing a better cause and effect relationship between meteorological variability and the resultant changes in surface ozone patterns.

(NOTE: This summary is based on notes provided to Bob Wayland from John Silvasi and David Sanders (U.S. EPA/OPSG), and some very limited notes taken by Stephanie Bowens (SAIC)).