1	The Clarus System Brenda Boyce, PMP Mixon Hill, Inc. Road Weather Stakeholder Meeting Albuquerque, New Mexico September 7, 2011
2	The Clarus Initiative: 4 Objectives Provide a North American resource to collect, quality check, and disseminate weather and road condition observations Demonstrate that these observations will support general purpose weather forecasting Demonstrate that the observations will support real-time operational responses to weather Support the enhancement and creation of models to improve forecasts at and near the earth’s surface
3	Clarus Users in 2010 4993 unique addresses gaining access (3,524,702 hits) from 67 countries government agencies (federal, state, local) academic institutions weather providers TV stations private sector firms unknown sources (Internet providers, etc.) Clarus Users in 2009 - 314 unique addresses gaining access (59,000+ hits) from 19 countries
4	Clarus Users by Country 2011 United States Ireland Canada Unknown Israel 2010 United States Ireland Japan Canada Israel
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8	Quality Checking Algorithms Set by contributor to indicate “Don’t necessarily trust this value” Set by contributor to indicate “Out of Service” Manual Flag All tests that can be run have completed Why wouldn’t a test run? Not configured to run Not enough data to run Complete Flag
9	Quality Checking Algorithms Climate Range Test Sensor Range Test Observation compared to historical climate minimum and maximum values per month by geographic area – gridded field Example: Air Temperature: 25 C Climate Value for January: -10 C to 20 C Test did not pass Observation compared to manufacturer’s published minimum and maximum values Example: Air Temperature: 25 C Specs: -20 C to 50 C Test Passed
10	Quality Checking Algorithms Like Instrument Test Step Test Observation compared to the same observation types from the ESS Observation compared to previous observations over a configured time range to determine if the rate of change (plus or minus) was acceptable Example: Values: 10 C, 12 C, 15 C, 35 C Test did not pass
11	Quality Checking Algorithms Dewpoint Test Persistence Test Determine the neighbors Calculate a dewpoint value based on the temperature & relative humidity Conduct a spatial test Observation compared to previous observations to determine if the values had changed at all over a period of time Example: Values: 38.6%, 38.6%, 38.7% Test passed
12	Quality Checking Algorithms Barnes Spatial Test IQR Spatial Test Observation compared to neighboring ESS and ASOS/AWOS to determine if they are similar Neighboring ESS and ASOS/AWOS identified Eliminate the neighbors that are +-350 meters Eliminate the highest and lowest neighboring values Observation compared to remaining neighbors to determine if they are similar Requires 5 initial neighbors for the test to run
13	Quality Checking Algorithms Applies to: 3-hour 6-hour 12-hour 24-hour Uses Stage II & IV precipitation files to accumulate the precipitation for comparison Precipitation Accumulation Sea Level Pressure Test Calculate a sea level pressure from the station pressure and then conduct a spatial test Conversion based on current 700mb Rawinsonde observations or 30-year average gridded data
14	"Mobile Observations" Mobile Observations Data Need Elevation Observations are on the map for one hour Used in quality checking
15	Select Tools
16	Communication Notification Set up for “No File Received” Timing is configurable An email can be sent to one or more recipients – owner, vendor A file is attached that gives the number of observations received from each station over the past 24 hours
17	Google Earth – KML File
18	Contacts Paul Pisano FHWA, Road Weather Management Team 202-366-1301 Paul.Pisano@dot.gov U.S. DOT Brenda Boyce, PMP 913-239-8400 Brenda.Boyce@mixonhill.com Chris Hill, Principal 540-822-9717 Chris.Hill@mixonhill.com Mixon Hill