Post processing of numerical ozone model forecasts the land sea problem
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Post-Processing of Numerical Ozone Model Forecasts: The Land-Sea Problem. Bill Ryan Department of Meteorology The Pennsylvania State University [email protected] 2010 International Workshop on Air Quality Forecasting Research Quebec City, Quebec. The Problem: False Alarms of High O 3.

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Post-Processing of Numerical Ozone Model Forecasts: The Land-Sea Problem

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Post processing of numerical ozone model forecasts the land sea problem

Post-Processing of Numerical Ozone Model Forecasts:The Land-Sea Problem

Bill Ryan

Department of Meteorology

The Pennsylvania State University

[email protected]

2010 International Workshop on Air Quality Forecasting Research

Quebec City, Quebec


The problem false alarms of high o 3

The Problem: False Alarms of High O3

  • Operational air quality forecasters along the I-95 Corridor in the northeastern US are increasingly reliant upon photo-chemical models for O3 forecast guidance.

    • Significant recent changes in regional emissions have reduced skill of guidance methods that require training period.

  • Overall model performance in this region is good but suffers from frequent “false alarms” of unhealthy O3 levels.

  • The false alarm rate is primarily a function of strong forecast O3 gradients along land-sea boundaries.

  • Numerical guidance output (1200 UTC initialization) arrives close (within minutes in some cases) to forecast deadlines. Forecasters require a simple, quick method to deal with this issue.


Example of the land sea o 3 gradient

Example of the Land-Sea O3 Gradient

NOAA-EPA Numerical Ozone Forecast Model (www.weather.gov/aq)


Pattern recurs in certain locations

Pattern Recurs in Certain Locations


Not an issue with pm 2 5 forecasts

Not an Issue with PM2.5 Forecasts

Daily maximum 8-Hour Average

Ozone (ppbv), NOAA-EPA Model

24-hour (midnight-midnight)

average PM2.5 (µg/m3)


Complicating the issue sea breezes can drive steep coastal o 3 gradients

Complicating the Issue: Sea Breezes Can Drive Steep Coastal O3 Gradients

MODIS/Aqua

~ 1730 UTC

In this case (August 11, 2010) sea breeze circulations developed north of a

frontal boundary and re-circulated the previous day’s polluted air mass.


Simplest application philadelphia forecast area

Simplest Application: Philadelphia Forecast Area

The Philadelphia Metro Forecast Area, roughly enclosed in rectangle, is peripherally

affected by modeled sea breeze-O3 effects, primarily in southern NJ


How do us operational forecasters receive local scale model forecast information

How Do US Operational Forecasters Receive Local Scale Model Forecast Information?

Model forecast output is automatically

generated by NOAA-EPA by extracting

peak O3 concentrations over land

areas within designated warning areas

(using zipcodes) that are used for

email/Web notification. This is posted in

timely fashion at AirNow Tech

(http://www.airnowtech.org/).

Millville, NJ monitor location shown at left.

Interstates and zip code boundaries shown.

Millville


Forecast peak o 3 frequently skirts coastal areas

Forecast Peak O3 Frequently Skirts Coastal Areas

Simplest post-processing method to

remove land-sea effects is

to extract O3 forecast at locations

near monitors and/or away from the

boundary. This can be quickly

done using point data extraction from the

NOAA forecast web site.


Results of simple method 2010

Results of Simple Method (2010)

  • Removing coastal zip codes from the Millville forecast reduces bias at that location from 17 ppbv to 9 ppbv.

  • Because this location is often the location of peak modeled O3 in the Philadelphia metro area, Code Orange model forecast frequency in PHL is reduced from 44 to 20 days (Threshold for Code Orange - Air Quality Alert is 76 ppbv 8-hour average) .

  • Of the 20 forecast Code Orange cases, 16 observed Code Orange in PHL in 2010.


Effect on metropolitan scale forecasts 2010

Effect on Metropolitan Scale Forecasts (2010)

  • When this simple post-processing is applied to the PHL metro domain, numerical model skill equals, or exceeds, expert forecast skill and is a large improvement on earlier forecast methods (not shown).


Simple approach less useful when monitors are located immediately along sea land boundary

Simple Approach Less Useful When Monitors are Located Immediately Along Sea-Land Boundary

Southern Delaware forecast

area includes monitor along

coast at Lewes.


Bias correction post processing

Bias Correction Post-Processing

  • Use of Sonoma Tech Air Quality MOS (AQMOS)

    • http://aqmos.sonomatech.com/index.cfm

  • Not a true MOS, method is long term bias removal with additional correction in higher O3 cases (hierarchal bias correction method).

  • Applied to southern Delaware in 2010, reduces overall forecast bias by 4.6 ppbv.

  • Also, reduces number of false alarms of Code Orange O3 (76 ppbv) from 19 to 5.

  • At cost of 4 additional missed Code Orange cases although “close” forecasts (71,74,75 ppbv).


More difficult application baltimore metropolitan area

More Difficult Application: Baltimore Metropolitan Area

In 2010, the monitor at Edgewood,

located northeast of Baltimore,

reached the Code Orange range

on 75% of all Code Orange days

in the Baltimore region.

On half of the Code Orange days,

the three bayside monitors

were the only locations reaching

the alert threshold.


An example of the bay breeze effect on o 3 in the baltimore metro area

An Example of the Bay Breeze Effect on O3 inthe Baltimore Metro Area

2200 UTC hourly O3 observations and wind barbs, June 25, 2009.


Note on determining air quality forecast skill in the mid atlantic

Note on Determining Air Quality Forecast Skill in the mid-Atlantic

  • False alarms can be due to factors other than water-land effects.

  • A frequent problem is forecasting the timing and extent of convection.

  • At right, a late day thunderstorm on June 3 limited O3 to 74 ppbv.

  • A set of 7 convection cases excluded in further analysis of 2010 results.


Model forecast o 3 in baltimore

Model Forecast O3 in Baltimore

  • The problem is solving the “false alarm” issue in non-convective cases.

  • Using raw model output, 26 false alarm cases in 2010.

  • Using the simple method of excluding near-water zipcode locations reduces false alarms to 19.


Further post processing approaches

Further Post-Processing Approaches

  • Due to the close proximity of emissions sources to the sea-land boundary, improvement by removing bay side grid points (simple method) is useful but limited.

  • Skill decreases quickly if further exclude near-bayside locations.

  • Analysis of 2010 Cases (a very active O3 season) gives some hints:

    • On average, observed Code Orange cases feature a stronger modeled gradient from bay side to inland, but too much variability to use operationally (CART method).

    • Most useful method combines the magnitude of modeled bayside O3 and the mean domain modeled O3.


Forecast results for code orange threshold air quality alert 8 hour o 3 76 ppbv 2010

Forecast Results for Code Orange Threshold (Air Quality Alert, 8-hour O3 ≥ 76 ppbv, 2010)

Blue: Model Forecast (NAQC)

Red: Post-Processed Model (POST)

Green: Persistence (PERS)


Summary of baltimore results

Summary of Baltimore Results

  • Pro: Removal of bias and reduction of false alarm rate.

  • Hit rate also reduced but, at 75%, approximately equal to, or better than, historical expert forecast accuracy.

  • Small (~5%) improvement in skill scores.

  • Half of the misses and false alarms occur in range [74, 78] ppbv (close calls).


Application to connecticut ozone

Application to Connecticut Ozone

The majority of high O3 events occur at coastal

monitors (62%). Only 5 of 24 observed Code Orange

days did not have a coastal monitor above the

threshold (76 ppbv, 8-hour average).


Background on model performance in ct

Background on Model Performance in CT

  • The NOAA-EPA model, on a statewide domain basis, did a reasonable job in 2010. Over-prediction bias of 5 ppbv (~10%).

  • Bias correction, on the seasonal or synoptic scale, slightly improves forecasts but has little impact at the Code Orange (Air Quality Alert) threshold.

  • Hit rate of 84% but high false alarm rate (34%). High bias for warning forecasts.

  • Expert forecast, typical of most locations along I-95, has fewer false alarms but many more “misses”. Low bias for warning forecasts.


Behavior of model forecasts in long island sound similar to chesapeake bay baltimore

Behavior of Model Forecasts in Long Island Sound Similar to Chesapeake Bay/Baltimore

  • Used NOAA-EPA model forecasts for locations of all CT monitors.

  • As in Baltimore, exploratory analysis with CART suggests domain wide average peak O3 ([65-70 ppbv])and/or land-sea gradient ([15-20 ppbv]) are useful thresholds for analysis.


Results of post processed forecasts statewide

Results of Post Processed Forecasts (Statewide)

Model forecasts (NAQC) have a high hit and false alarm rate (high bias) while

the expert forecast (Forecast) is the reverse. The two post-processed forecasts

Mean and Mean plus Gradient straddle the bias threshold but provide

better skill scores (Threat Score, or CSI shown above in green.


Summary and conclusions

Summary and Conclusions

  • In populated NE US Corridor, numerical model O3 forecast guidance is useful but has high false alarm rate due to modeled steep O3 gradients along land-sea boundaries.

  • A variety of simple post-processing methods, available within operational time constraints, can limit false alarm frequency.

  • Efficacy of methods vary from location to location and include:

    • Removal of coastal locations

    • Bias correction (of various lengths)

    • Domain mean peak concentrations and/or strength of gradient


Acknowledgements

Acknowledgements

  • This research is supported by ongoing grants from the Delaware Valley Regional Planning Commission (including the State of Pennsylvania Department of Environmental Protection) and the State of Delaware Department of Natural Resources and Environmental Control.

  • Assistance for this presentation also provided by Sonoma Technology (Dianne Miller and Jessica Johnson) and Michael Geigert of the Connecticut Department of Environmental Protection.


Additional slides

Additional Slides


Preliminary comments

Preliminary Comments

  • This presentation is from the operational forecaster’s perspective.

  • Air quality forecasting in the US is a state/local government responsibility.

  • The air quality forecasting community in the US is therefore non-centralized and diverse in terms of expertise, experience and resources.


Sea breeze fronts can lead to high o 3

Sea Breeze Fronts Can Lead to High O3

NOAA-EPA Model O3 forecast for

August 11, 2010 (1200 UTC run)

HPC Surface Analysis, 1800 UTC,

August 11, 2010


Hi res nam forecast sea breeze front forming behind frontal boundary

Hi-Res NAM Forecast:Sea Breeze Front Forming Behind Frontal Boundary


Sea breeze is observed

Sea Breeze is Observed

Sea Breeze Verified

(left) 3-hour temperature change

and winds,

1900 UTC, August 11

Figure Courtesy:

SPC Mesoscale Analysis

http://www.spc.noaa.gov/exper/mesoanalysis/


Example of mean domain model o 3 and observations

Example of Mean Domain Model O3 and Observations

Scatter plot of observed peak

O3 and mean model

Air Quality Index (AQI) for

in CT.


Ct domain wide code orange threshold forecasts model and expert

CT Domain Wide Code Orange Threshold Forecasts: Model and Expert


Connecticut miss and false alarm cases

Connecticut Miss and False Alarm Cases

  • Missed cases (4) were marginal Code Orange cases (76-78 ppbv) with only one hour exceedance in each case.

  • Three of seven False Alarms were “close calls” (≥72 ppbv) and remaining four were False Alarms under any of the post-processing methods.

  • False Alarms: 6/20 (lingering clouds), 7/20 (clouds/frontal boundary), 8/1 (SE winds), 8/31(?).


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