The following comments address the needs of the Forest Mapping Work Group. They are based on discussions with a few of the work group members and may not be inclusive
General Work Group Data Needs:
Wet deposition
The most recent five-year average should be reported for deposition chemistry. The mandatory parameters for deposition chemistry are:
Area-wide gridded compilations of all major ions (as noted above) are required. To start the process long term average numbers are fine. An annual summary of the last 20 years by grid cell would be useful. Point data from the various monitoring sties is also required
Dry deposition:
Dry deposition is required by the forest mapping work group for input into the Simple Mass Balance model. Any estimates that can be supplied by the Data Exchange group would be appreciated. We are ourselves are currently looking into a multiplier based on current scientific knowledge. We will share anything we come up with.
Fog deposition:
Fog deposition can play a significant role especially in the mountainous New England states. A geospatial model for the NE States has been developed by Eric Miller at Dartmouth College in Hanover NH. We are looking into the possibility of expanding the model to the Eastern Provinces in Canada.
Data Format Issues:
We will be using ArcInfo/ArcView for the forest mapping project. We would like to get a raster (gridded) coverage from the NatChem database to test the ease to which the coverage can be imported into ArcInfo. As for the grid size, based on the scale of the data we are working with a finer resolution would be preferable (even 10-20km). However, if the spacing of the monitoring sites makes this resolution artificial than there is no sense going finer than 40km.
With respect to projection, my initial thought is that we agree to work in decimal degrees (no projection). This will allow us the flexibility in ArcView of projecting the data into whatever projection we want for display purposes.
Future Steps
A spatio-temporal model that shows how deposition changes by area and time.
Dry deposition needs to be addressed sooner than later. I would suggest that this item come off the "back burner".
Data Needs
I think that Rich has identified the appropriate list of data needs, but would like to add a vote for also including the measured wet deposition concentration and precipitation volume data, i.e. the data underlying the spatial grids. These data would be useful for trend analyses, input into alternative spatial interpolation techniques and verification of models and regridded maps. Also, where possible, provide the raw data at a daily or weekly time step. Having the finer temporal resolution would enable one to perform episode analyses and source attribution studies.
Data Format: Grid Compatibility Issue
Obtaining gridded versions of the NAtChem maps and regidding these and/or other maps for comparison is a logical solution to the format conflict. To minimize any distortion and information loss in the regridding one would want as fine a grid as possible. So is the 40km grid fine enough? This depends on the monitoring site density and the spatial variability in the monthly data. As far as station density goes, 84% of the US NADP sites, east of the Mississippi, have the closest neighboring site 40 km or more away with an average distance of about 100 km. Unless the spatial data is very heterogeneous I would think that a 40 km grid is probably adequate.
Future Steps: Dry Deposition Estimates
The CASTNet network has about 45 sites throughout the Eastern US collecting data suitable for dry deposition estimates, and a number of people have published dry deposition estimates based upon these data. No matter how "non-representative" these CASTNet sites maybe to the neighboring non monitored area, spatial interpolating these data would have to provide a better estimate than simply assuming Dry = Wet. At a minimum the Dry/Wet ratio could be calculated at each CASTNet site which in conjunction with the wet deposition data could be used to estimate spatial patterns of dry deposition.
2. Agree that having data at its finest time resolution (daily, where available) is most useful for episode analysis and source attribution studies. However, a major value of the NAtChem system comes from its merging of data from more than a dozen monitoring networks in the US and Canada - only a few of which have daily time resolution, and several of which have monthly time resolution. For these reasons, I think that monthly time resolution may be the finest practical time resolution for NAtChem data products, and that data with shorter (daily) collection periods might best be obtained directly from data repositories for the specific daily networks (CAPMON and AIRMon). Conversely, maybe NAtChem can provide its version of the daily data from the daily networks - which would have the added advantage of having past through the additional NAtChem QA screening process. A Question for NAtChem?
3. Agree that grid density need not be greater than the spatial density of the original measurement data, and that 40 km seems like it may well be sufficient (and makes less work for NAtChem). However, since some of the envisioned NEG/ECP map products will likely focus on specific effects areas of concern in the NEG/ECP region, and since the density of monitors in sections of some of the eastern provinces may be somewhat higher (smaller) than 40 km, we might not want to rule out a finer "local" grid. Maybe this question could be addressed experimentally through an intercomparison of gridded results using several different levels of grid density? Another question for NAtChem?
4. Agree definitely that the simple assumption of "Dry=Wet" deposition is a poor choice for dry deposition estimates. Like the idea of using CASTNet (and maybe also NOAA AIRMon) wet and dry data to explore Dry/Wet ratios at individual sites. Can you provide references (or better yet copies of) the literature publications of dry deposition estimates?
Point 4. Some of the better references I have come across for dry deposition estimates are:
-U.S. Environmental Protection Agency (EPA), Office of Research and Development. 1998. Clean air status and trends network (CASTNet) Deposition Summary Report (1987-1995); EPA report nos. EPA/600/R-98/027
-Meyers, T.P.; Hiscks, B.B.; Hosker R.P.; Womack, J.D.; Satterfield, L.C. 1991. Dry deposition inferential measurement techniques-II. Seasonal and annual deposition rates of sulfur and nitrate. Atmos. Environ. 25, 2361-2370.
-Clarke, J.F.; Edgerton, E.S.; Martin, B.E. 1997. Dry deposition calculation for the clean air status and trends network. Atmos. Environ. 31, 3667-3678.
-Brook, J.R.; Sirois, A.; Clarke, J.F. 1996. Comparison of dry deposition velocities for SO2, HNO3 and SO42- estimated with two inferential models. Water, Air, and Soil Pollution 87, 205-218.
-Brook, J.R.; Di-Giovanni, F.; Cakmak, S.; Meyers, T.P. 1997. Estimation of dry deposition velocity using inferential models and site-specific meteorology - uncertainty due to siting of meteorological towers. Atmos. Environ. 22, 3911-3919.
The CASTNet web site also contains some information on the CASTNet network and dry deposition calculation methods. They also have a Data section, which is currently empty. Maybe CASTNet could be approached for supply dry deposition estimate data which could then be spatially interpolated.
First of all, I am willing to participate in a small Data Formats discussion group or a GIS related discussion group. I do have extended expertise in GIS and data analysis (Arcview, Atlas/GIS, SPANS/GIS, etc.). I also agree with the objectives of such a discussion group. Now, as for the document you posted on the NEARDAT site, I have the following comments to fforwardgive you:
Data format issues: Indeed, I think we need to look into at least 2 map scales (one for Northeastern America and one for the NEG/ECP area). I do not think we need a geographic scale too detailed because those maps will probably be used for presentation purposes in reports or slideshows. The NEG/ECP area map could range in the 1:2 000 000 to 1:5 000 000 scales, while the NorthEastern America map should be smaller (< 1:8 000 000). As for the map projection, we could look into a continental map projection such as Lambert, Mollweide or any other projections that reduce distortions in maps. Normally, distance in maps do not need to be constant, but some projections can take care of that, so that grid points may be separated by uniform distances. On the other hand, lat long coordinates should be easier to obtain from all juridictions. We could then reproject the data according to a given projection.
Next steps: I do agree with you
Future steps: These future steps would be definitely long term goals.
Best regards.
Jacques Dupont
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