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Combined Aerosol Trajectory Tool, CATT Illustrated Instruction Manual. Supported by: MARAMA contract on behalf of Mid-Atlantic/Northeast Visibility Union (MANE-VU) for the Inter-RPO Workgroup for Data Analysis Supplemental funding from
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Combined Aerosol Trajectory Tool, CATTIllustrated Instruction Manual Supported by: MARAMA contract on behalf of Mid-Atlantic/Northeast Visibility Union (MANE-VU) for theInter-RPO Workgroup for Data Analysis Supplemental funding from Environmental Protection Agency, OAQPS , Agreement # 83114101-0 National Science Foundation, Grant #0113868 Performed by the Center for Air Pollution Impact and Trend Analysis (CAPITA, Washington University In collaboration with Cooperative Institute for Research in the Atmosphere, CIRA-VIEWS Program January 10, 2004
Acknowledgements • The CATT Tool is the result of an effective CIRA-CAPITA collaboration to create a sequential value-adding chain. CIRA has opened the VIEWS and the ATAD databases for use by CAPITA. In fact the current CATT ensemble trajectory browser is accessing the VIEWS database for chemical data in real time! CAPITA added the trajectory browser code and the user interface. • The result is a textbook illustration of the new distributed computing paradigm! It is hoped that the values that the CATT project added to the chain will be accessed and utilized by others and continue the value-adding process. The opportunities for mutual empowerment are truly endless • The functionality of CATT was strongly influenced by the dynamic infusion of ideas from Rich Poirot. Beyond setting the initial goal of the CATT-Tool project, he also supplied continuous feedback on both the initial CATT design as well as on other features that we have added for our own reasons. • Serpil Kayin of MARAMA made sure that we actually finished this un-finishable 'project'. • The entire DataFed/CATT code was written by Kari Höijärvi of CAPITA
Table of Contents Introduction The CATT Browser Web Page Data Query (Q) Interface (Q) Parameter Filter Location Filter Time Filter Trajectory Rendering Interface (RT) Application of Filters for Data “Slicing” Single Site, Single Day Trajectories Multi-Site, Single Day Trajectories All Visible Sites, Single Day Trajectories Limiting Trajectories by Parameter Value Single Site, Time-Range Trajectories Percentile Filter Seasonal aggregations Gridding and Grid Operators Incremental Probability Metric, IP (‘Rich Poirot’ Metric) Potential Source Contribution Function, PSCF (‘Phil Hopke’ Metric) Grid-Average Concentration Metric, DM (‘Donna Kenski’ Metric) Weighed Probability Metric, WP (‘Mark Green’ Metric) TrajAgg: User-Defined Trajectory Viewer
CATT Summary Links Single Site & Day Traj Multi-Site, Single Day Traj All Visible Sites, Single Day Traj User-Defined Trajectory Viewer Single Site, Time-Range Traj Percentile Filter Gridded Transport Metrics Inc. Prob. IP-‘Poirot’ Pot. Src. Contr,‘Hopke’ Avg. Conc, DM ‘Kenski’ Weighed Prob. WP-Green’
CATT Software Components and Data Flow • The CATT software consists of two rather independent components: • Chemical filter component. This component is accomplished through queries to chemical data sets. The output of this step is a list of “qualified” dates for a specific receptor location. • Trajectory aggregator component. This component receives the list of dates for a specific location and performs the trajectory aggregation, residence time calculation and other spatial operations to yield a transport pattern for specific receptor location and chemical conditions.
The CATT Browser Web Page • The CATT program is a standard web page accessible through a URL by any user. • The CATT browser has two data views, the Map and Time views. Each view serves double purpose: to display data as maps or time series and to accept user input (clicking on Map/Time view) for navigation (browsing) • To the left of each view are view-specific controls to change either the content or form of the view. The top group of controls, ViewControls relate to the entire view, the bottom group of buttons are the LayerControls and the changes depend on which active (current) layer is in the view. • The general map view settings include setting the overall image size, geographic zoom rectangle (latitude-longitude), image margins and axis labels. The form, accessible through the magnifying glass – button, is considered self-explanatory. The ‘T button allows the entry of user-specified title on the map image.
Status and Navigation Bar • The Layer menu, highlighted in a yellow box, is an important navigational control of CATT. It displays and allows the selection of the ‘current layer’. Most of the user interaction is confined to the current layer. In CATT, the three layers are: • Traj_Point which shows the value of the species at different loc and time. • Trajj_Line depicts the ensamble trajectories as lines. • Traj_Grid shows the gridded trajectories as shaded contours. The File menu item is for the design of new applications. It should only be used by developers and not by routine browsers of CATT.
Data Query (Q) Interface (Q) • Chemical filter conditions determine the subset of the chemical data for which the backtrajectories are extracted, rendered, or gridded. • The chemical filters fall into three major categories, filtering by parameter (e.g. SO4), location or by time. • The chemical filter settings are accessible through the Query form, loaded by the query button, Q, on the right side of the map view of the Data Viewer.
Trajectory rendering options • The trajectory rendering interface is accessed through the RT button, while the Traj_line layer is current. • The interface form is also shown
Details of the Incremental Probability Metric Normalized Filtered Restime matrix for LYBR, SO4f, 80th percentile. • The IP metric requires the computation of two residence time matrices: filtered and unfiltered reference matrix. The resulting IRTP matrix is simply the difference: • IRTP = (Filtered Restime Matrix – Unfiltered Restime Matrix) Normalized Un-Filtered Restime matrix
Incremental Probability mapLYBR, SO4, (80%), 2000-20004 • The IRTP metric highlights the differences between the filtered and unfiltered trajectory counts by literally calculating the difference of the two normalized matrices. The resulting difference matrix, has both positive and negative values • The positive, reddish areas have ‘higher than average’ probability of transport and the bluish areas ‘higher than average’ probability of transport for the selected filter conditions
Incremental Probability Metric, IP(‘Rich Poirot’ Metric) • http://webapps.datafed.net/dvoy_services/datafed.aspx?page=CATT/CATT_IP • Settings: • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_reference_grid' • param_filter = all_values • use_weight = none • Button ‘Q’:View: 'map'; Layers: 'Traj_Line', 'Traj_Grid'; ID='ws_data' • param_filter = percentile (80-100) • loc_filter = loc_code • time_filter = datatime_range • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_grid' • use_weight = none • normalize = true • Button ‘O’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_mgo' • Expression = a - b
Potential Source Contribution Function, PSCF (‘Phil Hopke’ Metric) • http://webapps.datafed.net/dvoy_services/datafed.aspx?page=CATT/CATT_SC • Settings: • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_reference_grid' • param_filter = all_values • use_weight = none • Button ‘Q’:View: 'map'; Layers: 'Traj_Line', 'Traj_Grid'; ID='ws_data' • param_filter = percentile (80-100) • loc_filter = loc_code • time_filter = datatime_range • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_grid' • use_weight = none • normalize = true • Button ‘O’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_mgo' • Expression = a / b
Grid-Average Concentration Metric, DM(‘Donna Kenski’ Metric) • http://webapps.datafed.net/dvoy_services/datafed.aspx?page=CATT/CATT_DM • Settings: • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_reference_grid' • param_filter = all_values • use_weight = none • Button ‘Q’:View: 'map'; Layers: 'Traj_Line', 'Traj_Grid'; ID='ws_data' • param_filter = all_data • loc_filter = loc_code • time_filter = datatime_range • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_grid' • use_weight = linear • normalize = true • Button ‘O’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_mgo' • Expression = a / b
Weighed Probability Metric, WP (‘Mark Green’ Metric) • http://webapps.datafed.net/dvoy_services/datafed.aspx?page=CATT/CATT_WP • Settings: • Button ‘Q’: View: 'map'; Layers: 'Traj_Line', 'Traj_Grid'; ID='ws_data' • param_filter = all_values • loc_filter = loc_code • time_filter = datatime_ramge • Button ‘G’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_grid' • use_wight = linear • normalize = true • Button ‘O’: View: 'map'; Layer: 'Traj_Grid'; ID='ws_mgo' • Expression = a
Button ‘G’Reference Grid Settings ( Same as for Traj_line Query)
TrajAgg viewer • Given a table of receptor locations, dates, and chemical concentration the TrajAgg tool draws the corresponding ensemble of backtrajectories or residence time contour plots. • The TrajAgg page has a single map view with trajectory Traj_line and Traj_grid layers.
Submission form for the chemical filter table • The user defined filter table can be submitted and edited using the form, accessible through the button E. • Following the submission (saving) of the data table on the server, the TajAgg viewer automatically displays the data in trajectory or grid mode. The table consists of simple comma separated fields with the first line indicating the column names. The fields loc-code and datetime are mandatory. Such csv tables can be exported from Excel. • The loc_code field has to contain location identifiers that are in the IMPROVE/STN list. The list can be viewed in the main viewer window through the drop-down box for locations. If the chemical data for this table are obtained at location other than the IMPROVE/STN site list, the user can hand-select a nearby IMPROVE/STN location for the backtrajectories
Setting for grid rendering of weighed trajectory aggregations