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

Rocky Mountain Inventory and Monitoring Network1515

To get from

here…

To get from

here…

Rocky Mountain Inventory and Monitoring Network1616

To there…To there…

• 9 standard output fields• 9 standard output fields

Rocky Mountain Inventory and Monitoring Network1717

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

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