Background: Deterministic atmospheric chemistry models are becoming increasingly important tools used by air quality policy makers. These models allow for simulation of future air quality under different conditions, such as a reduction in motor vehicle emissions. It is crucial when using these model to validate and calibrate their output with real monitored data. In this project, students will work with EPA scientists to quantify the biases in model output in different spatial locations and weather conditions.
Background: The NCDC is the world's largest repository for weather and climate data. One of their primary functions is to provide freely-available and reliable data products to be used by researchers across the world. Precipitation is notoriously difficult to measure because of its high variability both in space and time. Students will work with NCDC researchers to improve estimation of sub-hourly precipitation. In particular, students will develop quality control methods to identify outlying observations or new ways to merge station data with radar observations.
