EEWR Brown Bag Seminar with Joshua Roundy and Kang Sun, Graduate Students
Speaker: Joshua Roundy and Kang Sun, Graduate Students
Series: EEWR Brown Bag Seminars
Location: Engineering Quad E225
Date/Time: Friday, October 25, 2013, 12:00 p.m. - 1:30 p.m.
Speaker: Joshua Roundy
Title: Confidence in seasonal prediction through analysis across temporal and spatial scales
Extreme hydrologic events in the form of droughts and flood are a significant source of social and economic damage in many parts of the world. Having sufficient warning of these extreme events allows managers to prepare for and potentially reduce the severity of their impacts to society. A hydrologic forecast system gives seasonal predictions that can be used by mangers to make better decisions; however hydrologic predictions rely on the skill of the climate models in order to predict the hydrologic state at seasonal timescales. The skill of climate forecast models diminishes in the first month due to the chaotic nature of the climate system, however climate drivers such as El Niño-Southern Oscillation (ENSO) can provide predictability on seasonal time scales. The extent to which this skill propagates to the key forcing variables that are used in driving seasonal hydrologic prediction is not well understood. Most assessments of forecast skill rely on a single temporal and spatial scale and do not consider forecast skill across multiple scales. In this work we demonstrate a framework for assessing the predictability of climate models that considers the forecast skill across many spatial and temporal scales. This framework provides a sharper understanding of the spatial and seasonal variation of predictability and its connections to climate drivers such as ENSO. The framework is demonstrated with NCEPs Climate Forecasts System version 2 (CFSv2)over the hindcast period from 1982-2009.
Speaker: Kang Sun
Title: On-road emissions characterized by mobile, open-path measurements
On-road vehicles are a significant source of urban air pollution and are increasingly important contributors of anthropogenic CO2 and other greenhouse gases. On-road NH3 emissions by vehicles take a significant fraction of total NH3 sources, but are subject to significant uncertainties. A mobile platform is developed by mounting open-path NH3, CO, CO2, and CH4 sensors on top of a passenger car. The collocation of open-path sensors makes it straightforward to calculate real-time on-road emission factors with high time resolution. The mobile platform had conducted in total 127 hours on-road measurements in the US, covering 7000 km in New Jersey, California, and Texas. We also covered 3300 km in four provinces in the North China Plain with a driving time of 66 hours. On-road NH3 emission factors correlate with road gradient with enhancement of 53 mg/kg fuel per percentage of road gradient. High NH3 emissions were also observed in both stop-and-go driving conditions and freeway driving. Comparisons with existing NJ and CA emission inventories indicate that there may be underestimations of on-road NH3 emissions in both NJ and CA.