Atmospheric Processes Associated with Snow Atmospheric Processes Associated with Snow Cover Ablation Events and their Effect on the Cover Ablation Events and their Effect on the

Flood Hydroclimatology of the Chesapeake BayFlood Hydroclimatology of the Chesapeake Bay

Gina HendersonGina Henderson and Daniel J. Leathersand Daniel J. LeathersCenter for Climatic ResearchCenter for Climatic Research

University of DelawareUniversity of Delaware

Chesapeake Bay watershedChesapeake Bay watershedThe SusquehannaThe Susquehanna

The PotomacThe Potomac

The JamesThe James

www.usgs.govwww.usgs.gov

Research QuestionsResearch Questions

1.1. How important is the ablation of snow cover to the flood How important is the ablation of snow cover to the flood hydroclimatology of the Chesapeake Bay watershed?hydroclimatology of the Chesapeake Bay watershed?

2.2. Are their distinctive types of snow ablation events that Are their distinctive types of snow ablation events that contribute to flooding in this area?contribute to flooding in this area?

3.3. What are the general atmospheric processes What are the general atmospheric processes associated with these ablation events and how does this associated with these ablation events and how does this impact the hydrology of the region?impact the hydrology of the region?

www.usgs.govwww.usgs.gov

The Susquehanna, The Susquehanna, Potomac and James rivers Potomac and James rivers account for the majority of account for the majority of

Chesapeake dischargeChesapeake discharge

The three gaging stations The three gaging stations used were:used were:

1.1. Harrisburg, PAHarrisburg, PA

2.2. Point of Rocks, MDPoint of Rocks, MD

3.3. Bucanan, VABucanan, VA

Data SourcesData Sources

Snow Depth DataSnow Depth Data

11o o X 1X 1o o gridded daily snow depth gridded daily snow depth data set developed by Mote et al. data set developed by Mote et al.

Utilizes U.S. COOP and Canadian Utilizes U.S. COOP and Canadian daily surface observations daily surface observations

Extensive quality control routinesExtensive quality control routines

Gridded snow cover data used to Gridded snow cover data used to identify basin or sub-basin wide identify basin or sub-basin wide ablation episodes.ablation episodes.

Chesapeake watershed: 23 grid boxes used to calculate Chesapeake watershed: 23 grid boxes used to calculate

ablation valuesablation values

Ablation values Ablation values calculated using:calculated using:

day 1 – day 2day 1 – day 2

Area of the watershed Area of the watershed ~ 165,759 km~ 165,759 km22 (64,000 (64,000 mimi22) )

MethodologyMethodology

1.1. Identify major flooding events during the fifty year period Identify major flooding events during the fifty year period for the Chesapeake Bay watershed using stream flow for the Chesapeake Bay watershed using stream flow and snow depth criteria.and snow depth criteria.

2.2. Classify events based on type of snow cover ablation Classify events based on type of snow cover ablation taking place.taking place.

3.3. Identify principle atmospheric features associated with Identify principle atmospheric features associated with each classification type.each classification type.

4.4. Use SNTHERM to model atmosphere snow cover Use SNTHERM to model atmosphere snow cover interactions.interactions.

Selection of flooding eventsSelection of flooding events

Top flooding events were Top flooding events were identified from the period identified from the period 1950-20001950-2000

Selection criteria:Selection criteria:– > 4247 m> 4247 m33 s s-1 -1 (150,000 cf/s)(150,000 cf/s)– > 3.0 cm change in snow > 3.0 cm change in snow

depth from the previous depth from the previous dayday

– Only winter months Only winter months considered considered

Ablation episodes selected from the top 5% of daily discharge values.

ResultsResults

Selection of eventsSelection of events

Three types of ablation events:Three types of ablation events:1.1. AblationAblation2.2. Rain on snowRain on snow3.3. Ablation to rainAblation to rain

We will look at one of each type of eventWe will look at one of each type of event

1950 to 20001950 to 2000 23 events23 events 8 events8 events

Annual cycle of river discharge:Annual cycle of river discharge:Chesapeake watershedChesapeake watershed

Discharge based on the total of the Susquehanna, the Potomac and Discharge based on the total of the Susquehanna, the Potomac and the James Riversthe James Rivers

On average, spring months show highest discharge valuesOn average, spring months show highest discharge values Some maximum discharges occur in summer/autumn Some maximum discharges occur in summer/autumn tropical tropical

precipitationprecipitation

Annual cycle of snow depth:Annual cycle of snow depth:Chesapeake watershedChesapeake watershed

On average, largest snow depth months are January and FebruaryOn average, largest snow depth months are January and February Large decrease in snow depth in MarchLarge decrease in snow depth in March Maximum daily snow depth shows largest decrease in snow depth Maximum daily snow depth shows largest decrease in snow depth

from March to April from March to April late season ablation events late season ablation events

1.1. Ablation event: 16Ablation event: 16thth March 1978 March 1978

1.1. Ablation event: 16Ablation event: 16thth March 1978 March 1978

Steady ablation for 5 days Steady ablation for 5 days before flooding eventbefore flooding event

Decrease in snow depth from Decrease in snow depth from approx 28 cm to 5 cmapprox 28 cm to 5 cm

No significant precipitation No significant precipitation eventsevents

Discharge peaks at approx Discharge peaks at approx 8000 m8000 m33/s/s

Sea level pressure: 3/15/78Sea level pressure: 3/15/78 Precipitation rate: 3/14/78Precipitation rate: 3/14/78

2.2. Rain on snow: 20Rain on snow: 20thth January 1996 January 1996

2.2. Rain on snow: 20Rain on snow: 20thth January 1996 January 1996

Rapid loss of snow depth over Rapid loss of snow depth over the 3 days before eventthe 3 days before event

Snow depth decrease from Snow depth decrease from approx 30 cm to almost 0 cmapprox 30 cm to almost 0 cm

Large precipitation event the Large precipitation event the day before event (~4 cm)day before event (~4 cm)

Ablation most likely intensified Ablation most likely intensified flooding eventflooding event

Sea level pressure: 1/19/96Sea level pressure: 1/19/96 Precipitation rate: 1/19/96Precipitation rate: 1/19/96

3.3. Ablation to rain: 2Ablation to rain: 2thth April 1970 April 1970

3.3. Ablation to rain: 2Ablation to rain: 2thth April 1970 April 1970

Steady ablation of approx 10 Steady ablation of approx 10 cm of snowcm of snow

Precipitation event marks the Precipitation event marks the start of a peak discharge eventstart of a peak discharge event

Discharge peaks at approx Discharge peaks at approx 11,800 m11,800 m33/s two days after /s two days after eventevent

Sea level pressure: 4/2/70Sea level pressure: 4/2/70 Precipitation rate: 4/2/70Precipitation rate: 4/2/70

MethodologyMethodology

1.1. Identify major flooding events during the fifty year period Identify major flooding events during the fifty year period for the Chesapeake Bay watershed using stream flow for the Chesapeake Bay watershed using stream flow and snow depth criteria.and snow depth criteria.

2.2. Classify events based on type of snow cover ablation Classify events based on type of snow cover ablation taking place.taking place.

3.3. Identify principle atmospheric features associated with Identify principle atmospheric features associated with each classification type.each classification type.

4.4. Use SNTHERM to model atmosphere snow cover Use SNTHERM to model atmosphere snow cover interactions.interactions.

Calculation of energy fluxes during ablation events with Calculation of energy fluxes during ablation events with SNTHERM snow pack model…. developed by Jordan (1991)SNTHERM snow pack model…. developed by Jordan (1991)

http://www.crrel.usace.army.milhttp://www.crrel.usace.army.mil

Flux analysisFlux analysis

2.

1.

3.

4.

1.1. Bingahamton, NYBingahamton, NY

2.2. Williamsport, PAWilliamsport, PA

3.3. Harrisburg, PAHarrisburg, PA

4.4. Washington, DCWashington, DC

1.1. Ablation: 16Ablation: 16thth March 1978 March 1978

Net solar flux is largest component Net solar flux is largest component affecting snow packaffecting snow pack

Precipitation receipt on the 14Precipitation receipt on the 14thth cause sensible and latent heat to cause sensible and latent heat to spikespike

Sea level pressure: 3/15/78Sea level pressure: 3/15/78

2.2. Rain on snow: 20Rain on snow: 20thth January 1996 January 1996

Huge snow depth amounts. From 1 Huge snow depth amounts. From 1 meter of snow to 0 over 4 daysmeter of snow to 0 over 4 days

Huge sensible and latent heat Huge sensible and latent heat fluxes associated with precipitation fluxes associated with precipitation eventevent

Sea level pressure: 1/19/96Sea level pressure: 1/19/96

3.3. Ablation to rain: 2Ablation to rain: 2ndnd April 1970 April 1970

Consistent positive fluxes into the Consistent positive fluxes into the pack before eventpack before event

Snow pack evoulution leads to Snow pack evoulution leads to rapid ablation and precipitaitonrapid ablation and precipitaiton

Sea level pressure: 4/2/70Sea level pressure: 4/2/70

Summary of resultsSummary of results

1.1. It is possible to isolate the snow ablation signal for the It is possible to isolate the snow ablation signal for the Chesapeake Bay watershed.Chesapeake Bay watershed.

2.2. A common theme is strong low pressure in the lower A common theme is strong low pressure in the lower Great Lakes Region bringing warm and moist air across Great Lakes Region bringing warm and moist air across the Chesapeake watershed.the Chesapeake watershed.

3.3. Large values of sensible and latent heat flux are Large values of sensible and latent heat flux are typically the largest components of the energy budget typically the largest components of the energy budget during the most during the most intense ablation events.intense ablation events.

Questions or comments?Questions or comments?

Contact info:Contact info:

Gina HendersonGina HendersonDepartment of GeographyDepartment of Geography

University of DelawareUniversity of Delawareginah@udel.eduginah@udel.edu