Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Hydrometeorology Products, Services and Supporting Research

Ellen J. CooterU.S. Environmental Protection AgencyOffice of Research and Development

Prepared forOffice of the Federal Coordinator for

Meteorological Services and Supporting Research17 September, 2008

EPA Office of Research and Development Needs

2Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Environmental Protection Agency Mission

To protect human health and the environment

Office of Research and Development Goal

To solve problems of national significance and to support our

program/regional office needs through integrated,

multidisciplinary research

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3Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Land Air Water

Human and Ecosystem Health & Services

emissions

deposition emissions

deposition

Soil Acidification

Vegetation Ozone exposure

Deposition of Toxics to soil and vegetation

Exposure related pulmonary disease

(Ozone, PM2.5)

Integrated Multidisciplinary Research in ORD

EutrophicationAcidificationTMDL

Examples

•Air Quality model development and evaluation

• Linking air quality and water quality models

• Ecosystem Services

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4Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

EPA ORD is a consumer of hydrometeorological products, services and supporting research

Recurring Themes

• Retrospective applications such as regulatory development analyses and model evaluation that make use of a combination of simulated meteorology and historical and near-real time meteorological observations

• Prospective applications such accountability studies and emerging environmental issues, e.g., climate change that rely exclusively on meteorological simulations

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5Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Air Quality Model Development and Evaluation for Regulatory

Application

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6Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

.01 0.5 1.0 2.0 3.0

20:15

Synoptic Scale Meteorology 5 August, 2004

Max. 8-Hour Ozone Forecast Init: 4 Aug (12 Z) Valid: 5 Aug

Source: Eder, B., Kang, D., Mathur, R., Yu, S. and Schere, K. 2006. “An operational evaluation of the Eta-CMAQ air quality forecast model.”

24-hr Precipitation Total Mean Daily Temperature

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7Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Problem: Air quality model performance is poor along the cold front where cloud cover and heavy rain dominate

Retrospective Application Needs: •Adoption of the research version of the Weather Research & Forecasting (WRF) (complete)•Higher resolution (NAM) input as boundary conditions (complete)•Assimilation of satellite imagery to improve cloud cover location and extent (in development)•Assimilation of gridded national multi-sensor precipitation analysis data (under consideration)

Prospective Application Needs:• The biggest challenge is that observations or reanalyses cannot be used to constrain model solutions to realistic outcomes. • Adoption of the WRF model has resulted in some simulation improvement, but the simulation of summertime cloud location and extent and precipitation extent, intensity and duration still need further improvement to adequately support prospective studies.

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8Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Linking Air Quality and Water Quality Models

Water Quality

Water Quantity

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9Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Linking Air Quality and Water Quality Models: Water Quality

• The critical air-water linkage for water quality regulatory analysis is the delivery of pollutants from the atmosphere to land and water surfaces through dry and wet deposition.

• Accurate simulation of pollutant mass delivered to underlying surfaces requires accurate characterization of all aspects of the chemical mass balance including in-cloud scavenging and wet deposition.

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10Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

In-Cloud Pollutant Scavenging

Gases

Aerosols

Linking Air Quality and Water Quality Models through Pollutant Scavenging

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*1

iwashouti H

TWF

_2

RTWTWF

T

OH

rOH

cldT

washout P

zW

2

__

1 washouti

αi = Scavenging coefficient for pollutant i

Τwashout = cloud washout time

TWF = total water fraction

WT = mean total water content

Pr = precipitation rate

Hydrometeorological parameter

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11Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Weekly USGS Atrazine

Linking Air Quality and Water Quality Models through Wet Deposition

Source: Cooter, E.J., Hutzell, W.T., Foreman, W.T. and Majewski, M.S., 2002. “A Regional Atmospheric Fate and Transport Model for Atrazine. 2. Evaluation.” Environ. Sci. Technol., 36: 4593-4599.

Limited-source or minimally reactive pollutants such as pesticides and Hg exhibit a strongly logarithmic removal pattern for precipitation depths under 5cm.

Removal of more ubiquitous or highly reactive pollutants such as inorganic N exhibit a more linear pattern for precipitation depths under 5cm.

Weekly NADP Total Nitrogen

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12Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Problem: Models are needed that accurately portray the movement of pollutant from the atmosphere to underlying surfaces

Retrospective Application Needs:

• Data to evaluate, verify and, if needed, to improve current in- cloud process parameterizations.

• Access to precipitation rate and volume observation data sets for model evaluation and potential assimilation. A short term solution for pollutants whose concentration in rainfall is approximately volume independent is to scale model concentrations by observed precipitation volume (under consideration).

Prospective Application Needs:

• Improved model simulation of precipitation rate and volume.

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13Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Linking Air Quality and Water Quality Models:

Water Quantity

• Hydrologic (quantity) aspects of water quality models are usually

calibrated using many years of USGS stream gauge data and first order or cooperative meteorological station precipitation.

• The most common timestep in water quality models is daily or monthly, although some models use hourly data.

• Inconsistencies between observed and modeled precipitation lead to inconsistent coupling of air and water quality models.

• Poor evaluation results for meteorological simulation models under current conditions make regulatory water quality model clients “uncomfortable” with their use in retrospective or prospective analyses.

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14Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Are current precipitation simulations adequate to drive a gridded watershed water quality model?

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Run

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Runoff: USGS Stream Gage Data Runoff: Observed Precipitation

Runoff: 12km Simulated Precipitation (MM5) Runoff: 36km Simulated Precipitation (MM5)

Runoff: Observed Precipitation, NS=0.81, R 2 =0.82

Runoff: Simulated Precipitation (12km), NS=0.49, R 2 =0.54

Runoff: Simulated Precipitation (36km), NS=0.20, R 2 =0.24

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5000Runoff: Observed Precipitation, NS=0.83, R 2 =0.86

Runoff: Simulated Precipitation (12km), NS=0.47, R 2 =0.51

Runoff: Simulated Precipitation (36km), NS=0.47, R 2 =0.53

a)

Scale effects

Tropical storm simulation failure

Source: Golden, H.E., Knightes, C.D., Cooter, E.J. and Dennis, R.L., 2008. “Modeled watershed runoff associated with variations in precipitation data, with implications for contaminant fluxes: Initial results.” Presented at the Third Interagency Meeting on Research in the Watersheds, 8-11 September, 2008, Estes Park, CO.

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15Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

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Ru

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Q: Obs Precip (m3/s) Q: MM5 12km (m3/s)

Q: NPA Precip (m3/s) Q: Stream gage (m3/s)

r2=0.95 between monthly USGS observed outflow (runoff) and simulated runoff driven by national multi-sensor precipitation analysis (NPA) data*

* Results are preliminary

Are there better observed data?

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16Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Problem(s): Observed precipitation data used to drive water quality applications is spatially incomplete.

Inconsistencies between these observations and modeled precipitation lead to inconsistent coupling of air and water quality models.

Retrospective Application Need:

• Apply modifications proposed previously wrt simulation model and expanded data assimilation to improve precipitation simulation provided to both air and water quality models. Should add obs. nudging.

•Preliminary results suggest that a water quality model run on a monthly timestep can be efficiently calibrated using widely spaced cooperative station timeseries, but then applied using the same finer resolution, gridded data used to nudge metr. model simulations. Prospective Application Need:

• Need to improve model simulation of both summer convective precipitation and tropical storm events.

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17Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Hyrdometeorological Product, Service and Support Needs for Ecosystem Services

Research

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18Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Hydrometeorological Extreme

Impact Ecosystem Service Loss

Frozen Precipitation(snow/ice)

Snow-related recreationWildlife access to food/shelterVegetation mortality/morbidity

AestheticsRecreationalFood and Fiber production

Flooding(heavy rainfall, long-duration rainfall events, coastal storm surge, tropical storms, high/low tidal events)

Loss/damage to inland and coastal wetlandsLoss/damage to fishery and nursery environmentsMortality/morbidity of rare or endangered speciesDisruption of lake and stream bottom communitiesIncreased turbidity

Nutrient cyclingErosion controlBiodiversityClean WaterFood productionRecreationAesthetics

Drought Vegetation mortality/morbidityWildlife access to food and shelterReduced reservoir levelsIncreased pollutant concentrations in streamsDisappearance of ephemeral streamsReduced baseflow to streams and rivers

BiodiversityFood and Fiber productionRecreation (hunting and fishing stocks)AestheticsErosion controlEnergy (hydropower)Access to clean water

Most of this information already exists, but may need further processing to meet the spatial and temporal needs of the Program. Effective communication

is a key limiting factor.

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19Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Retrospective Application Needs:

• Observational or reanalysis-based assimilation datasets, e.g., satellite, multi-source precipitation analysis are critical. Availability of new products needs to be effectively communicated.

• The gridded multi-sensor precipitation analysis database holds promise for air quality model performance improvement and more consistent quality and water quality model linkage. It needs to be maintained and ease-of-access improved.

Summary

Prospective Application Needs:

• Continued research is needed to, in the absence of observation nudging, identify and communicate to the applications community a set of “best modeling practices” to adequately reproduce the observed precipitation climate (e.g. support for NARRCAP-type studies).

• Identification or, if needed, development of new cloud and precipitation parameterizations that will simultaneously reproduce the full suite of hydrometeorological and non-hydrometeorological variables.

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20Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Disclaimer

Although this work was reviewed by EPA and approved for publication, it may not necessarily

reflect official Agency policy.

21Office of Research and DevelopmentNational Exposure Research Laboratory | Atmospheric Modeling Division | Fluid Modeling Branch

Other Needs

Human Exposure:

•water borne diseases and disease vectors• recreational area closures due to storm water runoff or combined sewage overflow events

Water Supply and Quality:

• water treatment infrastructure

• water distribution systems

• septic system issues

• leaky underground storage tanks

• groundwater supplies and community drinking water systems

Homeland Security:• Hazardous waste release