Engineering topics
Publications and source records attributed to Qian Li.
Online conferences simplify planning needs, lower barriers to participation for a global audience, and reduce environmental footprints, but scheduling, pacing, and moderating sessions can be challenging.
A primary sink of air pollutants and their precursors is dry deposition. Dry deposition estimates differ across chemical transport models, yet an understanding of the model spread is incomplete. Here, we introduce Activity 2 of the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4). We examine 18 dry deposition schemes from regional and global chemical transport models as well as standalone models used for impact assessments or process understanding. We configure the schemes as single-point models at eight Northern Hemisphere locations with observed ozone fluxes. Single-point models are driven by a common set of site-specific meteorological and environmental conditions. Five of eight sites have at least 3 years and up to 12 years of ozone fluxes. The interquartile range across models in multiyear mean ozone deposition velocities ranges from a factor of 1.2 to 1.9 annually across sites and tends to be highest during winter compared with summer. No model is within 50 % of observed multiyear averages across all sites and seasons, but some models perform well for some sites and seasons. For the first time, we demonstrate how contributions from depositional pathways vary across models. Models can disagree with respect to relative contributions from the pathways, even when they predict similar deposition velocities, or agree with respect to the relative contributions but predict different deposition velocities. Both stomatal and nonstomatal uptake contribute to the large model spread across sites. Our findings are the beginning of results from AQMEII4 Activity 2, which brings scientists who model air quality and dry deposition together with scientists who measure ozone fluxes to evaluate and improve dry deposition schemes in the chemical transport models used for research, planning, and regulatory purposes.
Both the Greenland and Antarctic ice sheets have been melting at an accelerating rate over recent decades. Meltwater from Greenland might be expected to initiate a climate response which is distinct, and perhaps different from, that associated with Antarctic meltwater. Which one might elicit a greater climate response, and what mechanisms are involved? To explore these questions, we apply “Climate Response Functions (CRFs)” to guide a series of meltwater perturbation experiments using a fully-coupled climate model. In both hemispheres, meltwater drives atmospheric cooling, sea-ice expansion, and strengthened Hadley and Ferrel cells. Greenland meltwater induces a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) and a cooling of the subsurface ocean in the northern high-latitudes. Antarctic meltwater, instead, induces a slowdown of the Antarctic Bottom Water formation and a warming of the subsurface ocean around Antarctica. For melt-rates up to 2000 Gt yr −1 , the climate response is rather linear. However, as melt-rates increase to 5000 Gt yr −1 , the climate response becomes non-linear. Due to a collapsed AMOC, the climate response is super-linear at high Greenland melt-rates. Instead, the climate response is sub-linear at high Antarctic melt-rates, due to the halting of the northward expansion of Antarctic sea ice by warm surface waters. Finally, in the linear limit, we use CRFs and linear convolution theory to make projections of important climate parameters in response to meltwater scenarios, which suggest that Antarctic meltwater will become a major driver of climate change, dominating that of Greenland meltwater, as the current century proceeds.
A 10-member ensemble simulation using the NASA GISS-E2-1-G climate model shows a clear bifurcation in the Atlantic Meridional Overturning Circulation (AMOC) strength under the SSP2-4.5 future scenario, leading to 8 stable AMOC-on and 2 stable AMOC-off climate states after 400 years of integration, despite identical forcing of each ensemble member. Ocean models have previously shown a tipping point where sufficient forcing (e.g. by freshwater inputs) can shut down the AMOC. A variety of fully coupled models have demonstrated this, either through hosing experiments or increased precipitation and warming at high latitudes due to increased concentrations of greenhouse gases. In the GISS simulations, there are no external freshwater perturbations. The bifurcation arises freely in the coupled system and is the result of stochastic variability associated with sea-ice transport and melting in the Irminger Sea following a slowing of the GHG concentration increase at the end of the twenty-first century. We believe this is the first time that a CMIP-class model has shown such a bifurcation across an initial condition ensemble.
Recent mass loss from ice sheets and ice shelves is now persistent and prolonged enough that it impacts downstream oceanographic conditions. To demonstrate this, we use an ensemble of coupled GISS-E2.1-G (a CMIP6 model) simulations forced with historical estimates of anomalous freshwater, in addition to other climate forcings, from 1990 through 2019. In this ensemble there are detectable differences in zonal-mean sea surface temperatures (SST) and sea ice in the Southern Ocean, and in regional sea level around Antarctica and in the western North Atlantic. These impacts mostly improve the model's representation of historical changes, including reversing the forced trends in Southern Ocean surface temperature and Antarctic sea ice. The changes in SST may have implications for estimates of the SST pattern effect on climate sensitivity and for cloud feedbacks. We conclude that the changes are sufficiently large that model groups should strive to include more accurate estimates of these drivers in all-forcing historical simulations in future coupled model intercomparisons.