Evaluating photochemical model performance with vertically resolved data (Co-Investigator)
Most regional photochemical models are evaluated primarily based on performance in simulating pollutant concentrations in the boundary layer by comparison with measurements from surface stations. However, model ability to simulate the spatial and vertical distribution of trace species in the entire troposphere is critical to air quality management, especially for relatively short-lived species such as ozone and particulate matter which are simultaneously influenced by photochemistry and vertical transport. With a NASA DISCOVER-AQ field campaign planned for the Houston region in late summer 2013, evaluating model performance against vertically resolved data from satellite, sondes and aircraft during previous campaigns can help benchmark anticipated uncertainties and biases and highlight issues to explore in the upcoming campaign.
Quantifying the uncertainties in model-simulated tropospheric ozone and implication for ozone radiative forcing, using satellite-derived longwave radiative kernels
The estimate of radiative forcing of tropospheric ozone has remained substantially unchanged since the third assessment report of the Intergovernmental Panel of Climate Change (IPCC) both in the actual number (0.35 W/m2) and the “Level of Scientific Understanding” indicator. In comparison to the IPCC third assessment (TAR), the fourth Assessment (AR4) reported higher uncertainty, which may be an indication of the increase in the number of models since TAR because the uncertainty range represents the deviation of the models from multi-model median. Why would more models mean more uncertainties? What is the implication of model bias on the tropospheric ozone radiative forcing? How can observations be used to constrain models, especially in the tropics and mid-latitudes where models discrepancies are largest? Aghedo et al, 2011a demonstrates the application of instantaneous radiative forcing kernels of ozone obtained from NASA-AURA Tropospheric Emission Spectrometer (TES) retrievals in evaluating multimodel ozone longwave forcing (see the full text for more details), as a first step to addressing these questions (see Worden et al, 2011 full-text for a detailed discussion on the TES OLR Kernels).
The influence of satellite data sampling and resolution on multi-model evaluations with satellite observations
Ensemble climate model simulations used for the IPCC have become important tools for exploring the response of the Earth System to anthropogenic radiative forcing. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. However, there are number of technical steps that need to be carefully considered in order to quantify the differences between model predictions and remotely sensed observations. These differences include the differences between the spatio-temporal resolution of models and observations, the impact of spatially varying vertical resolution, limited diurnal coverage, and monthly-mean output. Aghedo et al., 2011b exemplifies these uncertainties by using TES and numerical model simulations of ozone, carbon monoxide, temperature and water vapor from three global climate and chemistry models (AM2-Chem, ECHAM5-MOZ, and GISS-PUCCINI).
Impact of emissions on regional and global tropospheric ozone
Emissions of trace species from soil, aircraft, biomass burning, lightning, vegetation and
anthropogenic sources to the atmosphere undergo chemical transformations through chemical reactions, deposition, destruction, and removal. Also, emissions of hydrocarbons (also known as volatile organic compounds) from living vegetation are driven by meteorological conditions such as temperature, soil moisture and humidity. Aghedo et al, 2007 uses a global chemistry and climate model to quantify the influence of emissions released from the African continent on the global tropospheric ozone. This paper was the first study to characterize the impact of African emissions on global air pollution and ozone, which is also a greenhouse gas. Click here for full text of article.
