Atmospheric & Oceanic Science
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Formerly known as the Department of Meteorology.
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Item The Role of Soil Hydro-physical Properties in Land-atmosphere Interactions and Regional Climate(2021) Dennis, Eli; Berbery, Ernesto H; Kalnay, Eugenia E; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Soil hydro-physical properties are necessary components in weather and climate simulation; yet, the parameter inaccuracies introduce considerable uncertainty in the representation of surface water and energy fluxes. The surface fluxes not only affect the terrestrial water and energy budgets, but through land-atmosphere interactions, they can influence the boundary layer, atmospheric stability, moisture transports, and regional precipitation characteristics. This set of three experiments explores aspects of soil hydro-physical properties, and their impact on coupled regional climate simulations in the North American region. In the first two experiments, two soil datasets are considered: State Soil Geographic dataset (STATSGO) and Global Soil Dataset for Earth System Modeling (GSDE). Each dataset’s dominant soil category allocations differ significantly at the model’s resolution. Large regional discrepancies exist in the assignments of soil category, such that, for instance, in the Midwestern United States, there is a systematic reduction in soil grain size. Because the soil grain size is regionally biased, it allows for analysis of the impact of soil hydro-physical properties projected onto regional scales. In the first experiment, in areas of reduced soil grain size, there is also a reduction in latent heat flux and an increase in sensible heat flux following the physical understanding of soil properties. These differences in surface fluxes affected low-level thermodynamics, and PBLH. The second experiment analyzed soil-induced differences in the general circulation, emphasizing horizontal moisture transports, vertically-integrated moisture flux convergence, and regional precipitation. It found that soil-induced differences in surface fluxes influenced each term of the atmospheric water budget via both thermodynamic and dynamic means. The third experiment assesses the impact of soil hydro-physical parameters on surface fluxes, and the atmospheric response. The default soil hydro-physical parameter table is replaced with a modernized soil parameter table. The findings indicate that the role of each soil hydro-physical parameter is sensitive to both climatic regimes (i.e., arid vs. temperate), and vegetation assignment. Collectively, this series of experiments improves our understanding of the physical mechanisms that link the soil to the atmosphere in the coupled land-atmosphere system. The improved understanding will inform the development of the next generation of land surface models.Item Satellite Remote Sensing of Smoke Particle Optical Properties, Their Evolution and Controlling Factors(2021) Junghenn, Katherine Teresa; Li, Zhanqing; Kahn, Ralph A.; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood, nor are those driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem and ambient conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging Spectrometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD), and to provide constraints on plume vertical extent, smoke age, and particle size, shape, light-absorption, and absorption spectral dependence. These capabilities are evaluated using near-coincident in situ data from two aircraft field campaigns. Results indicate that the satellite retrievals successfully map particle-type distributions, and that the observed trends in retrieved particle size and light-absorption can be reliably attributed to aging processes such as gravitational settling, oxidation, secondary particle formation, and condensational growth. The remote-sensing methods are then applied to numerous wildfire plumes in Canada and Alaska that are not constrained by field observations. For these plumes, satellite measurements of fire radiative power and land cover characteristics are also collected, as well as short-term meteorological data and drought index. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the tallest and thickest plumes containing the largest, brightest particles, and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution, over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.Item Quantification of the Past and Future Anthropogenic Effect on Climate Change Using the Empirical Model of Global Climate, an Energy Balance Multiple Linear Regression Model(2020) Hope, Austin Patrick; Salawitch, Ross J; Canty, Timothy P; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The current episode of global warming is one of, if not the, biggest challenge to modern society as the world moves into the 21st century. Rising global temperatures due to anthropogenic emissions of greenhouse gases are causing sea level rise, extreme heat waves, droughts and floods, and other major social and economic disruptions. To prepare for and potentially reverse this warming trend, the causes of climate change must not only be understood, but thoroughly quantified so that we can attempt to make reasonable predictions of the future rise in global temperature and its associated consequences. The project described in this dissertation seeks to use a simple model of global climate, utilizing an energy balance and multiple linear regression approach, to provide a quantification of historical temperature trends and use that knowledge to provide probabilistic projections of future temperature. By considering many different greenhouse gas and aerosol emissions scenarios along with multiple possibilities for the role of the ocean in the climate system and the extent of climate feedbacks, I have determined that there is a 50% probability of keeping global warming beneath 2 °C if society can keep future emissions on the pathway suggested by the RCP 4.5 scenario, which includes moderately ambitious emissions reductions policies, and a 67% probability of keeping global warming beneath 1.5 °C if society can keep emissions in line with the very ambitious RCP 2.6 scenario. These probabilities are higher, e.g. more optimistic, than similar probabilities for the same scenarios given by the most recent IPCC assessment report. Similarly, we find larger carbon budgets than those from GCM analyses for any warming limitation target and confidence level, e.g. the EM-GC predicts a total carbon budget of 710 GtC for limiting global warming to 1.5 °C with 95% confidence. The results from our simple climate model suggest that the difference in future temperatures is related to an overestimation of recent warming by the IPCC global climate models. We postulate that this difference is partially due to an overestimation of cloud feedback processes in the global climate models. Importantly, though, I also reaffirm the consensus that anthropogenic emissions are driving current warming trends, and discuss both the effects of shifting the energy sector toward increase methane emissions and the timeline we have for emitting the remainder of our carbon budget – less than a decade if we wish to prevent global warming from exceeding the 1.5 °C threshold with 95% certainty.Item DECADAL TO CENTENNIAL SCALE CLIMATE DYNAMICS IN MODELS OF VARYING COMPLEXITY(2020) Schwarber, Adria; Smith, Steven J; Hartin, Corinne A; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Though concerted climate action by the world's governments intends to limit long-term (e.g. 100 years) global average temperature rise, attention has recently focused on reducing climate impacts in our lifetime by reducing emissions of short-lived climate forcers (SLCFs). SLCFs are pollutants that remain in the atmosphere for a short time (e.g. methane or black carbon) and have the potential to impact the climate in the near-term by increasing or decreasing temperature, depending on the species emitted. There is a more limited set of literature, however, that robustly characterizes short-term climate dynamics in the 20-30 year time horizon within models or observations that can be used to inform scientific and policy work. In this dissertation, we seek to clarify climate dynamics on shorter time scales using models of varying complexity---from complex models, which take several months to simulate 100 years of climate on a supercomputer, to simple climate models (SCMs) that can simulate the same period on a personal computer in less than a minute, in addition to using several observational datasets. We first characterize the basic climate processes within several SCMs, finding that some comprehensive SCMs fail to capture response timescales of more complex models, for example under BC forcing perturbations. These results suggest where improvements should be made to SCMs, which affect numerous scientific endeavors and illustrates the necessity of integrating fundamental tests into SCM development. We then robustly determine how realistic complex model variability is compared to observations across all time scales using power spectra of temperature-time series. We investigate model variability at the regional level, using the continental-scale regions defined by PAGES2k. We find that compared to observations the suite of CMIP5 models investigated have lower variability in certain regions (e.g. Antarctica) and higher variability in others (e.g., Australasia), with some consistency across timescales. Our approach allows for a more robust assessment of complex model variability at time periods and regional levels important to human systems. From this, we analyze the range of temperature responses over time in complex model results from phase 5 of the Coupled Model Intercomparison Project (CMIP5) at the hemispheric scale to create a realistic range of possible temperature changes. We find that the range of responses of land/ocean varied less than the range of hemispheric responses. Our results are a first step of better quantifying the short-term climate responses to changes in SLCFs.