1. xmACIS • text only / no images (e.g. graphs, maps) • single station only • time series oriented • various time resolutions • summary statistics including • threshold-based‘counts of’ • XNPSD only Retrieving climate data ‘at a place’ from the Applied Climate Information System

2. xmACIS scACIS Form solutions to issues impacted by climate by using data-based products retrieved from the • Added functionality: • graphs • multi-station results incld. maps • variables in addition to XNPSD • transformations, e.g. indicies • expanded suite of statistics, e.g. dispersion, trend, stochastic models, etc. • scripting interface Applied Climate Information System

3. Graphical User Interface and results Map-based • point selection • geographical results including display • point values • contour lines Graph-based/tabular results • time series, possibly mulitvariate • other, e.g. • statistical distributions • scatter plots s.a. Prank vs. Trank scACIS

4. Graphical User Interface and results Map-based • point(s) selection • NWS office/area • state, climate division, county, other • user-defined group • geographical results • point values (w/location info) • display or GIS data set: grid, contour lines • Graphical User Interface and results Map-based • point(s) selection • NWS office/area scACIS

5. Graphical User Interface and results Tabular results • time series, possibly mulitvariate • other, e.g. • statistical distributions • scatter plots, e.g. T vs. P Graph-based/tabular results scACIS

6. Enhanced repertoire Data, more … • sources - e.g. ASOS, mesonet • variables - humidity, wind, radiation, etc. - transformations • multivariate, e.g. indicies • multiple conditions for counting statistics scACIS

7. Enhanced repertoire Time series definition • ‘season’ definition for annual time series and/or summary statistics - arbitrary portion of year • pick start and end day-of-year • months • years subset, e.g. • el-nino years, other index years • arbitrary, user-defined year set scACIS

8. Enhanced repertoire Time series characterizations • dispersion, e.g. stdDev, percentiles, histograms • trend • coefficients • stochastic models • frequency spectrum descriptors • return periods • e.g. implementation of many distributions w/ Hosking L-moments scACIS

9. Scripting interface and user preferences Scripting • simplified access to background Python functionality • alternate method of user-defined ‘procedure’ definition - ‘user defined’ sequence of operations ‘Remember’ user settings • cookies – simple ‘page-based’ settings • other (e.g. named) user definitions - e.g. list of stations scACIS

10. Next – Time and money Further planning and actions • who pays? • who develops? • more fact finding, decisions • Standing scACIS committee • ‘pow-wow’ – stakeholders meeting • SCs, RCCs, NCDC, ??? • meeting travel expense support • What will NCS product delivery systems look like? Is the scACIS effort of possible use? scACIS

11. Documentation Enhanced xmACIS (scACIS) functionality outlinehttp://climate.umn.edu/aasc/scACIS_071116.docTransforming xmACIS into scACIShttp://climate.umn.edu/aasc/scACIS2008.ppt scACIS Zandlo (MN), Dupigny-Giroux (VT), Angel (IL), Boyles (NC), Taylor (OR), Akyuz (ND), Eggleston (NERCC).