1,721,100 research outputs found
Seasonal And Geographical Patterns Of Photochemistry And Physical Processes Transporting Asian Ozone To Model Surface Layer Over The Us
No full textClimate Extremes In A General Climate Model With Stochastic Parameterizations
No full textThis work employs techniques from extreme value theory to evaluate the representation of temperature and precipitation extremes in two climate models and an observational dataset. The climate models correspond to the general climate model, the NCAR Community Atmosphere Model version 4 (CAM4), with two stochastic parameterizations of sub-grid scale processes: the stochastic kinetic energy backscatter (SKEBS) scheme and the stochastically perturbed parameterization tendency (SPPT) scheme. The observational dataset is version 7 of the satellite-based Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 research product, developed at the National Aeronautics and Space Administration Goddard Space Flight Center. Temperature extremes are described in terms of the 95th percentile (20-yr return level) of the distribution of annual extremes of near-surface temperature, while precipitation extremes are characterized in terms of the analogous percentile with respect to daily precipitation amounts, in addition to less extreme precipitation statistics. The distribution of annual extremes is assumed to be well-approximated by the Generalized Extreme Value (GEV) distribution, which is fit at each gridpoint using a "block maxima" approach. A Bayesian hierarchical approach is used to estimate the parameters of the distribution of annual extremes in the 3B42 dataset. CAM4 overestimates warm and cold extremes over land regions, particu- larly over the Northern Hemisphere when compared against observations and reanalysis. The addition of a stochastic parameterization generally produces a warming of both warm and cold extremes relative to the unperturbed configuration, however, neither of the proposed parameterizations meaningfully reduce the biases in the simulated temperature extremes of CAM4. Similarly, the precipitation response to the use of stochastic parameterizations is remarkably muted, particularly that to SPPT. SKEBS is shown to enhance the dry bias of annual precipitation in CAM4 over the central contiguous United States, and also exacerbates the shortfall of moderate precipitation extremes over the same region. The 3B42 dataset shows severe overestimation of 20-yr return levels over eastern Asia. The analysis of the 3 parameters that define the GEV distribution enhances the understanding of the behavior of extremes, revealing valuable information that may potentially help modeling centers improve the simulation of extremes in the climate models
The Future Of The Amazon Post 2005 And 2010 Droughts: An Inter-Comparative Model Study
Get PDFThe Amazon Rainforest is a dynamically intricate hotspot region with high biodiversity and importance to the global hydrological and carbon cycles. Over the last decade, the frequency of extreme events in the Amazon has increased due to climate change. This study presents a brief background overview of the causes and impacts of the Amazon droughts of 2005 and 2010 based on past and current studies in literature. This study also reports the analysis of the performance of 34 fully coupled global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and a Community Land Model 4 (CLM4) run to simulate current seasonal cycles of precipitation, temperature, leaf area index (LAI), surface runoff, and aboveground biomass stock against observational datasets. The land and atmospheric model variables of interest include precipitation, temperature, leaf area index, carbon storage in vegetation, net primary production, total runoff, total surface runoff, and total soil moisture content. The present day climatology obtained from CMIP5 historical runs is 1980-2005, and future climatology from 4 representative concentration pathway scenarios (RCPs 2.6, 4.5, 6.0, and 8.5) is 2075-2100. All model outputs are monthly means from the r1i1p1 ensemble. The seasonal and interannual means extracted from the variables are analyzed to compare against observational data to evaluate model performance. Model variability index (MVI) was calculated to compare each model's variability in the North and South Amazon grid boxes to assess the standard deviation difference between model and observed datasets to identify biases in each model. MVI values differ among variables and location of the Amazon. Results also show that models were able to reproduce seasonal and annual cycles of precipitation in the Amazon better than other observed data. Two types of skill scores were used to rank models to provide comparison to the seasonal and interannual variability in observed data. The root mean square error (RMSE) statistical approach is used to check the model's ability to reproduce both the phase and amplitude of the observations during the climatology period and account for the errors in the spatial pattern and annual cycle. The probability density function (PDF) approach compares the common area under the PDF curves based on Epanechnikov kernel smoothing to evaluate the ability of the model to reproduce both the mean state and interannual variability of a variable. Poor model simulations are close to 0, and perfect model simulations are close to 1. The metrics in this study found no significant correlation between current skill scores and future projections of climate variables. However, correlation studies between variables suggest good relationship between temperature, precipitation, and LAI in models. Future changes in RCP 8.5 show overall decreases in precipitation and increases in temperature, surface runoff, soil moisture, and carbon stock, although uncertainty remains to the exact fate of the Amazon towards the end of the century. i
Nitrogen Constraints On Terrestrial Carbon Sequestration, From Trees To The Globe
Get PDFNitrogen (N) is an essential nutrient for plant growth that constrains the fixation and storage of carbon (C) in many ecosystems. Understanding how environmental change, especially increasing N deposition, carbon dioxide concentrations, and soil temperature, alters the N limitation of forest growth is critical for accurately predicting future C storage and climate change. Accurate predictions depend on developing a historical and present day evaluation of N controls on C storage and using this knowledge to assess and improve global models. In this dissertation, I first demonstrate that N deposition has increased C storage in trees during the 1980s and 1990s across the northeastern U.S. Second, I show how integrating four different observational and experimental datasets (N fertilization experiments, N deposition gradients, 15N tracer studies, and small catchment N budgets) provide unique insights for testing and improving Earth System models. By comparing model output to globally-distributed N fertilization experiments, I demonstrate that two prominent Earth System models (the CLM-CN and O-CN) differ widely in their sensitivity to step increases in N fertilization. Third, a separate analysis focused on the CLM-CN found that the model was not sensitive enough to N deposition in comparison to historical N deposition data. By comparing CLM-CN output to both 15N tracer studies and small catchment N budgets, I show that the low response to N deposition is partially due to low ecosystem retention of N. Model improvements to the CLM-CN that decreased photosynthesis and introduced a more closed N cycle (i.e., lower N inputs relative to internal cycling) increased ecosystem retention of N, decreased the productivity response to N fertilization, and increased the productivity response to N deposition, thereby yielding much more similar model predictions to observations. Overall, this dissertation increases our knowledge of how N deposition influences C storage and is the first to explicitly benchmark C and N interactions in Earth System models using a range of observations. In addition, my work sets a foundation for estimating the impact of N cycling on climate and creates a framework for future evaluations of Earth System models
Simulating Surface Air Pollution In The United States: An Examination Of Major Influences And A Diagnosis Of Model Capabilities
Get PDFIn this dissertation I explore various influences on the surface chemistry in the United States. The research is in three parts: (1) the influence of emissions from Asia on surface ozone mixing ratios in the US using a tracer chemistry scheme; (2) a diagnostic analysis of surface ozone chemistry simulations using a Global Climate Chemistry Model (GCCM) in the US; and (3) an examination of the changing freight transportation patterns and its influence on Black Carbon (BC) surface chemistry in the Midwestern and Northeastern US. For the first part, we find that the Asian influence on US surface ozone chemistry is maximum in the springtime and a minimum in the summertime. This springtime maximum is a result of a low, dispersed plume of Asian pollution entering the air space over North America in the springtime. In contrast, the plume of Asian pollution crosses North American air space in a tighter and higher plume and is inaccessible to surface dynamics which could impact surface ozone. For the second part, we find that overall the CESM CAM-Chem GCCM is capable of capturing many aspects of surface ozone chemistry in the US, especially in the Southeastern and Western US. However, biases result under different sets of paramaterizations in model configurations, which must be accounted for in interpretation of GCCM results, including: (1) a large positive ozone bias when a 26-layer configuration is used and a reduced, but still positive, bias when a 56-layer configuration is chosen; and (2) utilizing online meteorology performs as good as or better when simulated a variety of ozone metrics than a simulation using forced meteorology. In the third part find that although the overall demand for transportation is increasing due to globalization and a fragmentation of the production process, the increases in technological efficiencies and emission factor regulations have resulted in a regionally averaged leveling-off or decrease in BC emissions from 1977 - 2007. The fabricated metal and construction sectors, with generally heavy freight, dominate the emission of BC. Finally, increases in BC emissions in urban centers are increasing as they continue to develop into production and transportation nodes
Dependence Of Radiative Forcing On Mineralogy In The Community Atmosphere Model
Get PDFThe mineralogy of desert dust is important due to its effect on radiation, clouds and biogeochemical cycling of trace nutrients. This study presents the simulation of dust as a function of both mineral composition and size at the global scale using mineral soil maps. Externally mixed bulk mineral aerosols in the Community Atmosphere Model version 4 (CAM4) and internally mixed modal mineral aerosols in the Community Atmosphere Model version 5.1 (CAM5) embedded in the Community Earth System Model version 1.0.3 (CESM) coordinated by the National Center for Atmospheric Research (NCAR) are speciated into common mineral components in place of total dust. The simulations with mineralogy are compared to available observations of mineral atmospheric distribution and deposition along with observations of clear-sky radiative forcing efficiency. Based on these simulations, we estimate the all-sky direct radiative forcing at the top of the atmosphere as +0.04 and +0.10 Wm-2 for CAM4 and CAM5 simulations with mineralogy and compare this with simulations of dust with optimized optical properties, wet scavenging and particle size distribution in CAM4 and CAM5 of -0.05 and -0.11 Wm-2, respectively. The ability to correctly include the mineralogy of dust in climate models is hindered by its spatial and temporal variability as well as insufficient global in-situ observations, incomplete and uncertain source mineralogies and the uncertainties associated with data retrieved from remote sensing methods
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
The Response Of The Equatorial Tropospheric Ozone To The Madden–Julian Oscillation In Tes Satellite Observations And Cam-Chem Model Simulation
Get PDFThe Madden-Julian Oscillation (MJO) is the dominant form of the atmospheric intra-seasonal oscillation, manifested by slow eastward movement (about 5 m/s) of tropical deep convection. This study investigates the MJO s impact on equatorial tropospheric ozone (10N-10S) in satellite observations and chemical transport model (CTM) simulations. For the satellite observations, we analyze the Tropospheric Emission Spectrometer (TES) level-2 ozone profile data for the period of Jan 2004 to Jun 2009. For the CTM simulations, we run the Community Atmosphere Model with chemistry (CAM-chem) driven by the GOES-5 analyzed meteorological fields for the same data period as the TES measurements. Our analysis indicates that the behavior of the Total Tropospheric Column (TTC) ozone at the intraseasonal time scale is different from that of the total column ozone, with the signal in the equatorial region comparable with that in the subtropics. The model simulated and satellite measured ozone anomalies agree in their general pattern and amplitude when examined in the vertical cross section (the average spatial correlation coefficient among the 8 phases is 0.63), with an eastward propagation signature at a similar phase speed as the convective anomalies (5 m/s). The model ozone anomalies on the intraseasonal time scale are about five times larger when lightning emissions of NOx are included in the simulation than when they are not. Nevertheless, large-scale advection is the primary driving force for the ozone anomalies associated with the MJO. The variability related to the MJO for ozone reaches up to 47% of the total variability (ranging from daily to interannual), indicating the MJO should be accounted for in simulating ozone perturbations in the tropics
Forearc uplift in northern Chile: New Paleoaltimetric methods, constraints, and numerical experiments on the role of subduction channel flow
Get PDFThe lithosphere-scale geodynamic mechanisms that control forearc topography are still contentious. In northern Chile, this is in part due to a lack of paleoelevation constraints. In order to rectify this lack of data, this thesis carries out a series of studies.
First, a new paleoaltimetry proxy for the hyperarid Atacama Desert was developed, based on the elevation-dependent relationship of the 87Sr/86Sr ratio of Holocene surface accumulations of salts. Here, an important source of calcium sulfate comes from stratocumulus clouds that generate fog on the continent, transferring water droplets to the ground surface which, upon evaporation, precipitate calcium sulfate. The seawater ratio of 87Sr/86Sr (0.70917) is distinctly higher than that of weathered mean Andean rock (<0.70750). Sites below 1075 m.a.s.l. and above 225 m.a.s.l. display Holocene calcium sulfate 87Sr/86Sr of mean value 0.70807 ± 0.00004, while the ratio outside this altitudinal domain is 0.70746 ± 0.00010.
Based on these results for Holocene materials, Pliocene-Pleistocene paleoelevations of the forearc surface were inferred. We measured 87Sr/86Sr of dated ancient gypsic soils and applied appropriate corrections to the paleo-fog zone top and bottom. The results show that the magnitudes of paleo-elevation changes are small compared to the elevation of the study area: more than 45% of the ~1000 m.a.s.l. average elevation of the Central Depression and more than 70% of the ~900 m.a.s.l. average elevation of the westernmost Coastal Cordillera were achieved by pre-early Pliocene regional scale tectonic processes.
Finally, the response of the forearc surface to 2D viscoelastic flow in a subduction channel was characterized numerically. 800-1100-m-thick subduction channels with viscosities of 5-10 x1018 Pa s best fit the elevations of the Central Depression after steady-state topography is reached in less than 6 myr. The onset of hyperaridity at ~ 25 Ma starved the trench and subduction channel of sediments, raising shear stresses at the plate interface and uplifting the forearc. Short-lived phases of less aridity may have affected forearc topography transiently. The models predict that in order to accord with available Central Depression paleoelevation constraints, these phases translated to pulses of “weaker” subduction channels with viscosities between 2-7 x1018 Pa s
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