Rocky Mountain Inventory and Monitoring Network11
Overview of Weather and Climate Monitoring For The Rocky
Mountain Network
Overview of Weather and Climate Monitoring For The Rocky
Mountain Network
Brent Frakes
National Park ServiceInventory and Monitoring Program
Fort Collins, COApril, 2008
Brent Frakes
National Park ServiceInventory and Monitoring Program
Fort Collins, COApril, 2008
Rocky Mountain Inventory and Monitoring Network22
Presentation OverviewPresentation Overview
• Objectives
• Variables
• Datasets
• Example Report
• Integration with NPClime
• Objectives
• Variables
• Datasets
• Example Report
• Integration with NPClime
Rocky Mountain Inventory and Monitoring Network33
Monitoring ObjectivesMonitoring Objectives• Monitor climate at numerous spatial and temporal scales• Help interpret/explain observations from other protocols
– Determine influence of climate on Vital Signs– Remove climate signal to minimize variance
• Provide useful and simple park metrics for application to management decisions– Fire Risk– Drought – Vegetation growth
• Consider both drivers and effects of climate variability and change
• Sustainable over long term– Cost-effective– Repeatable
• Monitor climate at numerous spatial and temporal scales• Help interpret/explain observations from other protocols
– Determine influence of climate on Vital Signs– Remove climate signal to minimize variance
• Provide useful and simple park metrics for application to management decisions– Fire Risk– Drought – Vegetation growth
• Consider both drivers and effects of climate variability and change
• Sustainable over long term– Cost-effective– Repeatable
Rocky Mountain Inventory and Monitoring Network44
Scales of Atmospheric ProcessScales of Atmospheric Process
• Positive relationship between space and time
• Small-scale processes embedded within larger-scale process
• Surface environment responds to various processes
Rocky Mountain Inventory and Monitoring Network55
Monitoring VariablesMonitoring Variables• Temperature
– TMIN, TMAX, TAVG– Frost free days
• Precipitation– Accumulated– Maximum
• Snow – Snow Water Equivalent– Extent
• Drought– Palmer Drought Severity Index (PDSI)– Surface Water Supply Index (SWSI)– Palmer Meteorological Drought Index (PMDI)
• Modes of climate variability– Atmosphere – North Atlantic Oscillation (NAO), Pacific North American Pattern
(PNA)– Oceans – Pacific Multi-decadal Oscillation (PDO), El Nino Southern Oscillation
(SOI)
• Temperature– TMIN, TMAX, TAVG– Frost free days
• Precipitation– Accumulated– Maximum
• Snow – Snow Water Equivalent– Extent
• Drought– Palmer Drought Severity Index (PDSI)– Surface Water Supply Index (SWSI)– Palmer Meteorological Drought Index (PMDI)
• Modes of climate variability– Atmosphere – North Atlantic Oscillation (NAO), Pacific North American Pattern
(PNA)– Oceans – Pacific Multi-decadal Oscillation (PDO), El Nino Southern Oscillation
(SOI)
Rocky Mountain Inventory and Monitoring Network66
Data SourcesData Sources
• Station-Level Summaries
• SNODAS
• PRISM
• Climate Division Drought Indices
• Atmospheric/Oceanic Indices
• Station-Level Summaries
• SNODAS
• PRISM
• Climate Division Drought Indices
• Atmospheric/Oceanic Indices
Rocky Mountain Inventory and Monitoring Network77
Representing ScalesRepresenting Scales
Daily Weather ObservationsPoint
PPT,TMAX,TMIN,TAVG
Daily Weather ObservationsPoint
PPT,TMAX,TMIN,TAVG
Daily Weather Index*Park
PPT,TMAX,TMIN,TAVG
Daily Weather Index*Park
PPT,TMAX,TMIN,TAVG
Monthly1 to 4-km grid
SWE, PPT,TAVG
Monthly1 to 4-km grid
SWE, PPT,TAVG
MonthlyClimate Region
Drought
MonthlyClimate Region
Drought
MonthlyNorthern hemisphere
Atmosphere/Ocean Index
MonthlyNorthern hemisphere
Atmosphere/Ocean Index
SPACE/TIME CONTINUUMSPACE/TIME CONTINUUM
NPClimeNPClime
Rocky Mountain Inventory and Monitoring Network88
Daily Station-Level SummariesDaily Station-Level Summaries• Mandatory and useful
– Represent point observation
– Capture microclimatic effects
– Ground truth
• TMAX, TMIN, TAVG, PPT, SWE
• NSW COOP, SNOTEL, SnowCourse
• Mandatory and useful– Represent point
observation– Capture microclimatic
effects– Ground truth
• TMAX, TMIN, TAVG, PPT, SWE
• NSW COOP, SNOTEL, SnowCourse
Rocky Mountain Inventory and Monitoring Network99
Daily Park IndexDaily Park Index
• Representative of entire park or meaningful units (from point to polygon…)
• Derived from relevant weather stations– Weighted by proximity to park– Account for elevation
• Value– Remove local effects and station
errors– One dataset vs. many
• Representative of entire park or meaningful units (from point to polygon…)
• Derived from relevant weather stations– Weighted by proximity to park– Account for elevation
• Value– Remove local effects and station
errors– One dataset vs. many
West
-4
-3
-2
-1
0
1
2
3
4
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Year
An
nu
al T
ME
AN
An
om
aly
fro
m 3
0yr
Ave
rag
e
30-yr TMEAN for West Slope of ROMO30-yr TMEAN for West Slope of ROMO
Rocky Mountain Inventory and Monitoring Network1010
Monthly PRISM DataMonthly PRISM Data
• Precipitation-elevation Regressions on Independent Slopes Model
• 4-km resolution
• 1895-present
• PPT, TMIN, TMAX, Dewpoint
• Precipitation-elevation Regressions on Independent Slopes Model
• 4-km resolution
• 1895-present
• PPT, TMIN, TMAX, Dewpoint
Rocky Mountain Inventory and Monitoring Network1111
Monthly SNODAS DataMonthly SNODAS Data
• 1-km resolution• Daily• 2003-present• Variables
– Snow Depth– Snow Water
Equivalent – Extent
• Remotely sensed, ground observations and model
• 1-km resolution• Daily• 2003-present• Variables
– Snow Depth– Snow Water
Equivalent – Extent
• Remotely sensed, ground observations and model
Rocky Mountain Inventory and Monitoring Network1212
Climate Division Drought IndicesClimate Division Drought Indices
• Monthly• 1895 – present• Multiple drought
indices to capture meteorological and hydrological drought
• Monthly• 1895 – present• Multiple drought
indices to capture meteorological and hydrological drought Palmer Drought Severity Index (PDSI) for East Slope of ROMO
-4
-3
-2
-1
0
1
2
3
1890
1895
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
CO-4 PDSI
3YrAvg
Linear (CO-4 PDSI)
Sufficient Moisture
Severe Drought
Rocky Mountain Inventory and Monitoring Network1313
Bringing the Data Together Snow -2006
Bringing the Data Together Snow -2006
• SWE – Snow Water Equivalent• SWE – Snow Water Equivalent
0%
20%
40%
60%
80%
100%
120%
140%
Oct Nov Dec Jan Feb Mar Apr May Jun
Month
Mo
nth
ly A
vera
ge
SW
E P
erce
nt
of
No
rmal
West
East
West
20%
40%
60%
80%
100%
120%
140%
160%
180%
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Year
An
nu
al S
WE
Dep
artu
re (
Per
cen
t) f
rom
th
e 30
-Yea
r M
ean
East
20%
40%
60%
80%
100%
120%
140%
160%
180%
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Year
An
nu
al S
WE
Dep
artu
re (
Per
cen
t) f
rom
th
e 30
-Yea
r M
ean
Rocky Mountain Inventory and Monitoring Network1414
Current DevelopmentCurrent Development
• SOPs for Data Collection and Processing
• Python Climate Modules– Stations (and other tabular)
• Read (SNOTEL, Snowcourse, climate division drought indices, other)
• Write to a standard format
• SOPs for Data Collection and Processing
• Python Climate Modules– Stations (and other tabular)
• Read (SNOTEL, Snowcourse, climate division drought indices, other)
• Write to a standard format
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To get from
here…
To get from
here…
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To there…To there…
• 9 standard output fields• 9 standard output fields
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Grid ModuleGrid Module– Read PRISM and SNODAS
• Unzip• Untar/Untar/Untar….• Read and clip bils
– Average of Many Grids– Grid Percentile
• Compare one grid to a climatology of others
– Multi-grid Zonal Stats• Drill polygon(s) through multiple grids
– Read PRISM and SNODAS• Unzip• Untar/Untar/Untar….• Read and clip bils
– Average of Many Grids– Grid Percentile
• Compare one grid to a climatology of others
– Multi-grid Zonal Stats• Drill polygon(s) through multiple grids
Rocky Mountain Inventory and Monitoring Network1818
Integration With NPClimeIntegration With NPClime
• Web Interface– Stations module can read other data sources
not part of NPClime (e.g., SnowCourse, SNOTEL, Climate Division Drought Indices)
– Standard methods for writing data
• Stand-alone Module– Enhanced functionality not possible with web– Especially with gridded datasets– Open source and will improve as needed
• Web Interface– Stations module can read other data sources
not part of NPClime (e.g., SnowCourse, SNOTEL, Climate Division Drought Indices)
– Standard methods for writing data
• Stand-alone Module– Enhanced functionality not possible with web– Especially with gridded datasets– Open source and will improve as needed
Rocky Mountain Inventory and Monitoring Network1919
ENDEND
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