Overview of the Model and Observation Evaluation Toolkit (MONET) Version 1.0 for Evaluating Atmospheric Transport Models

Barry Baker,Li Pan

doi:10.3390/atmos8110210

Abstract

This paper describes the development and initial applications of the Model and Observation Evaluation Tool (MONET) v1.0. MONET was developed to evaluate the Community Multiscale Air Quality Model (CMAQ) for the NOAA National Air Quality Forecast Capability (NAQFC) modeling system. MONET is designed to be a modularized Python package for (1) pairing model output to observational data in space and time; (2) leveraging the pandas Python package for easy searching and grouping; and (3) analyzing and visualizing data. This process introduces a convenient method for evaluating model output. MONET processes data that is easily searchable and that can be grouped using meta-data found within the observational datasets. Common statistical metrics (e.g., bias, correlation, and skill scores), plotting routines such as scatter plots, timeseries, spatial plots, and more are included in the package. MONET is well modularized and can add further observational datasets and different models.

Highlights

Ozone (O3 ) and particulate matter smaller than 2.5 μm in diameter (PM2.5 ) are among a handful of criteria air pollutants—pollutants the Clean Air Act requires to be monitored and regulated—that are primarily responsible for adverse impacts on human health [1]
In relation to health hazards caused by air pollutants, air quality has a direct impact on the economy
This paper describes the structure and functionality of the Model and Observation Evaluation Tool (MONET) Python package

Summary

Introduction

Ozone (O3 ) and particulate matter smaller than 2.5 μm in diameter (PM2.5 ) are among a handful of criteria air pollutants—pollutants the Clean Air Act requires to be monitored and regulated—that are primarily responsible for adverse impacts on human health [1]. The National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory (ARL) developed the Model and Observation Evaluation Tool (MONET) to aid in the assessment of the National Air Quality Forecasting Capability (NAQFC) [8,9]. MONET reads, interpolates, and organizes model results to observation sites in both space and time resulting in a fast and flexible method to evaluate air quality modeling simulations. MONET was originally created to only evaluate CMAQ simulations, it can be expanded to include different model outputs (e.g., the Weather Research and Forecasting model, Generation Global Prediction System, and Comprehensive Air Quality Model with Extensions), along with adding additional observational sources (e.g., different ground based networks, satellite observations, and other in-situ observations). A discussion and future directions of MONET will be provided

Tool Description

Creation of Model andand

Pairing Observations and Model Results

Example of Tool Applications

Examples

Conclusions