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At least 487 records · Page 27

Solar Forced Dansgaard/Oeschger Events?

Climate records for the last ice age (which ended 11,500 years ago) show enormous climate fluctuations in the North Atlantic region - the so-called Dansgaard/Oeschger events. During these events air temperatures in Greenland changed on the order of 10 degrees Celsius within a few decades. These changes were attributed to shifts in ocean circulation which influences the warm water supply from lower latitudes to the North Atlantic region. Interestingly, the rapid warmings tend to recur approximately every 1500 years or multiples thereof. This has led researchers to speculate about an external cause for these changes with the variable Sun being one possible candidate. Support for this hypothesis came from climate reconstructions, which suggested that the Sun influenced the climate in the North Atlantic region on these time scales during the last approximately 12,000 years of relatively stable Holocene climate. However, Be-10 measurements in ice cores do not indicate that the Sun caused or triggered the Dansgaard/Oeschger events. Depending on the solar magnetic shielding more or less Be-10 is produced in the Earth's atmosphere. Therefore, 10Be can be used as a proxy for solar activity changes. Since Be-10 can be measured in ice cores, it is possible to compare the variable solar forcing directly with the climate record from the same ice core. This removes any uncertainties in the relative dating, and the solar-climate link can be reliably studied. Notwithstanding that some Dansgaard/Oeschger warmings could be related to increased solar activity, there is no indication that this is the case for all of the Dansgaard/Oeschger events. Therefore, during the last ice age the Be-10 and ice core climate data do not indicate a persistent solar influence on North Atlantic climate.

Muscheler, R.↗

Investigating Tropical Versus Extratropical Influences on the Southern Hemisphere Tropical Edge in the Unified Model

Abstract Since the late 1970s, observations have shown a widening of the tropical Hadley cell (HC) circulation. State‐of‐the‐art climate models reproduce the general trend along with a projected continuous expansion. Discrepancies in expansion rates of observation‐ and model‐based studies have been attributed to differences in applied methods, natural variability and model shortcomings. Furthermore, the driving influence of tropical or extratropical processes on these changes is not well understood. All of this highlights the dynamical mechanisms and the region of origin controlling the tropical width are still insufficiently understood. Here we examine the influence of systematic model biases of the atmosphere‐only Unified Model (UM) onto the simulation of the Southern Hemisphere (SH) tropical edge. We utilize nudged experiments with prescribed sea surface temperatures, where potential temperature and horizontal winds are relaxed back to ERA‐Interim reanalysis for a 20‐year period in selected regions. Correcting model biases in the tropics and extratropics separately allows us to dissect the dominant remote impacts of present model errors onto the SH tropical edge simulation. The experiments are applied to established tropical width metrics ranging from near‐surface to upper‐level metrics capturing the poleward flank of the HC. We find both regions work remotely to reduce errors in the UM fields and location of the tropical edge. Surprisingly, correcting the extratropical biases, south of 45°S, more consistently improves the tropical width across the metrics and seasons than nudging the tropics (10°N–10°S). These findings demonstrate the substantial role of extratropical influences in locating the SH tropical edge.

54 ENVIRONMENTAL SCIENCES↗

Climate Variability and Weather Extremes: Model-Simulated and Historical Data

Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).

Schubert, Siegfried D.↗

Chapter 10 - Remote Sensing Measurements of Aerosol Properties

Satellite instruments have proven especially capable at monitoring the quantity of airborne particles in columns of atmosphere, globally. This chapter describes the principles of satellite measurements and retrieval algorithms, and surveys current instruments and their capabilities. We outline the issues associated with retrieval algorithms, such as surface characterization and aerosol proximity to clouds, and the challenges with interpretation of the results. The relationship between measured aerosol properties and climate-relevant aerosol properties simulated in models is outlined, as well as how measurements are used to evaluate models. Most space-based aerosol instruments are passive sensors that measure reflected sunlight at multiple wavelengths, some at multiple viewing angles. A few are active sensors that send out their own laser light and measure the returned signal. Except when clouds are present, the excess amount of light scattered back to space, beyond that expected from the surface and atmospheric gas, is attributed to aerosol. Satellite measurements are used in many ways in aerosol research. They often provide the only method for monitoring hazardous phenomena such as major wildfire and volcanic eruption plumes, especially in remote areas. Stable, long-term, near-global-scale satellite data records make it possible to identify regional and global aerosol trends. Aerosol radiative effects on climate can be quantified on a near-global scale and used to estimate the strength of aerosol–radiation and aerosol–cloud interactions as well as to evaluate climate model simulations of these interactions. Aerosol-type mapping from satellite imagery is helpful for source attribution, model validation, and to constrain particle light-absorption properties that are essential for radiative forcing calculations. The range of aerosol properties retrieved from satellite observations has grown considerably since the first global estimates of aerosol optical depth (τ a) over ocean were made in the late 1970s. Methods for retrieving particle size and light-absorption properties were explored in the 1990s using multispectral, multi-angle observations, and polarization in visible and near-infrared wavelengths. Sensitivity to particle light absorption, primarily from black or brown carbon content, improved with the inclusion of UV channels, and sensitivity to very thin aerosol layers in the upper troposphere and lower stratosphere was advanced with the use of limb-sounding instruments and active sensors. There are limitations to every measurement technique, including satellite aerosol remote sensing. For wide-swath, passive instruments, aerosol retrievals near clouds can present substantial challenges as far as 15 km away due to cloud-scattered light contaminating the signal. In nearly all cases, retrievals over bright snow and ice surfaces are precluded because surface reflectance uncertainties can overwhelm the aerosol signal. Similarly, meteorological cloud is identified and masked out where possible. Data from passive sensors also lack vertical resolution except those that view toward the limb or where multi-angle imagery is acquired over plumes from wildfires, erupting volcanoes, and wind-blown dust. Yet, passive sensors provide vastly more coverage than the active instruments that mitigate these issues. Particle microphysical information is qualitative from all remote sensing techniques, relying on proxies to infer particle composition, hygroscopicity, and the amount of light-absorbing material. Further, particles smaller than about 200 nm diameter cannot be distinguished from atmospheric gas molecules with remote sensing, which hinders studies of cloud condensation nuclei and their effects on clouds. Most satellite instruments dedicated to aerosol observations are in low-Earth, near-polar, sun-synchronous orbits, which means they cross the equator at the same local time each day. Most are set on cycles that repeat approximately every 16 days, which makes it difficult to monitor aerosol evolution locally. Geostationary satellites make it possible to observe changes occurring from minutes to hours over regions up to 8000 km in size, but lack coverage of high latitudes, and often provide more limited constraints on aerosol properties. Ground-truth data are vital for satellite aerosol-retrieval validation. The AErosol RObotic NETwork (AERONET) of sun photometers was created in 1993 and has become an established global network of over 350 instruments for validating satellite measurements. The network, as well as global networks of ground-based lidars, solar flux radiometers and other sun photometers, are widely used for evaluating global satellite retrievals and model simulations. NASA's Earth Observing System (EOS) program beginning in 1999 led to improvements in reliability, spatial resolution, and spectral resolution (and hence, to improved particle size discrimination and light absorption properties). Satellite payloads include advanced broad-swath and multi-angle imagers, along with the first space-based active sensor focused largely on long-term aerosol monitoring. Since about 2002, Europe's SENTINEL and operational meteorological satellite fleets are also providing sustained aerosol observations, with planned continuation until at least 2030. Satellite remote sensing instruments offer valuable data for evaluating aerosol representations in global climate models. They have been used to assess aerosol optical and physical properties, trends and distributions, and are applied increasingly as direct model constraints in data assimilation to create global aerosol reanalysis products. Aerosol optical depth is the most common quantity adopted for routine model evaluation, including multiwavelength data to loosely constrain particle-size distributions. These evaluations of multiple models have revealed general biases in their regional aerosol amounts and seasonal patterns of transport and removal. Although satellite measurements have near-global coverage, substantial errors can be introduced into the model observation comparison unless attention is paid to spatial and temporal collocation, cloud screening, subgrid-scale variability, and measurement uncertainties that vary with retrieval conditions.

aerosol properties↗

Coupled Aerosol-Chemistry-Climate Twentieth-Century Transient Model Investigation: Trends in Short-Lived Species and Climate Responses

The authors simulate transient twentieth-century climate in the Goddard Institute for Space Studies (GISS) GCM, with aerosol and ozone chemistry fully coupled to one another and to climate including a full dynamic ocean. Aerosols include sulfate, black carbon (BC), organic carbon, nitrate, sea salt, and dust. Direct and BC snow-albedo radiative effects are included. Model BC and sulfur trends agree fairly well with records from Greenland and European ice cores and with sulfur deposition in North America; however, the model underestimates the sulfur decline at the end of the century in Greenland. Global BC effects peak early in the century (1940s); afterward the BC effects decrease at high latitudes of the Northern Hemisphere but continue to increase at lower latitudes. The largest increase in aerosol optical depth occurs in the middle of the century (1940s-80s) when sulfate forcing peaks and causes global dimming. After this, aerosols decrease in eastern North America and northern Eurasia leading to regional positive forcing changes and brightening. These surface forcing changes have the correct trend but are too weak. Over the century, the net aerosol direct effect is -0.41 Watts per square meter, the BC-albedo effect is -0.02 Watts per square meter, and the net ozone forcing is +0.24 Watts per square meter. The model polar stratospheric ozone depletion develops, beginning in the 1970s. Concurrently, the sea salt load and negative radiative flux increase over the oceans around Antarctica. Net warming over the century is modeled fairly well; however, the model fails to capture the dynamics of the observedmidcentury cooling followed by the late century warming.Over the century, 20% of Arctic warming and snow ice cover loss is attributed to the BC albedo effect. However, the decrease in this effect at the end of the century contributes to Arctic cooling. To test the climate responses to sulfate and BC pollution, two experiments were branched from 1970 that removed all pollution sulfate or BC. Averaged over 1970-2000, the respective radiative forcings relative to the full experiment were +0.3 and -0.3 Watts per square meter; the average surface air temperature changes were +0.2 degrees and -0.03 C. The small impact of BC reduction on surface temperature resulted from reduced stability and loss of low-level clouds.

Koch, Dorothy↗

Exploring a Multiresolution Modeling Approach within the Shallow-Water Equations

The ability to solve the global shallow-water equations with a conforming, variable-resolution mesh is evaluated using standard shallow-water test cases. While the long-term motivation for this study is the creation of a global climate modeling framework capable of resolving different spatial and temporal scales in different regions, the process begins with an analysis of the shallow-water system in order to better understand the strengths and weaknesses of the approach developed herein. The multiresolution meshes are spherical centroidal Voronoi tessellations where a single, user-supplied density function determines the region(s) of fine- and coarsemesh resolution. The shallow-water system is explored with a suite of meshes ranging from quasi-uniform resolution meshes, where the grid spacing is globally uniform, to highly variable resolution meshes, where the grid spacing varies by a factor of 16 between the fine and coarse regions. The potential vorticity is found to be conserved to within machine precision and the total available energy is conserved to within a time-truncation error. This result holds for the full suite of meshes, ranging from quasi-uniform resolution and highly variable resolution meshes. Based on shallow-water test cases 2 and 5, the primary conclusion of this study is that solution error is controlled primarily by the grid resolution in the coarsest part of the model domain. This conclusion is consistent with results obtained by others.When these variable-resolution meshes are used for the simulation of an unstable zonal jet, the core features of the growing instability are found to be largely unchanged as the variation in the mesh resolution increases. The main differences between the simulations occur outside the region of mesh refinement and these differences are attributed to the additional truncation error that accompanies increases in grid spacing. Overall, the results demonstrate support for this approach as a path toward multiresolution climate system modeling.

58 GEOSCIENCES↗

Relative importance between biogeochemical and biogeophysical effects in regulating terrestrial ecosystem-climate feedback in northern high latitudes

Warming-induced changes in structures and functions of northern terrestrial ecosystems (NTEs), including their regulation on terrestrial biogeochemistry and surface energy balance, may exert positive or negative feedback to the climate system. However, the relative importance among these biogeochemical and biogeophysical feedback is not well understood. Here we use a terrestrial ecosystem model to quantify spatially explicit ecosystem-climate feedback over NTEs (north of 50°N) under four climate change scenarios from 2010 to 2100, including biogeochemical feedback from climate-induced changes in net CH4 exchanges (NME) and net CO 2 exchanges (NCE) and biogeophysical feedback from changes in surface energy partitioning associated with snow cover and vegetation biomass dynamics. Our results indicate that (1) biogeochemical and biogeophysical feedback are attributed more to the changes in NME and snow cover dynamics, respectively; (2) net biogeophysical feedback is much larger than net biogeochemical feedback; (3) NTEs will cause a net positive radiative forcing of 0.04–0.26 Wm -2 between 2010 and 2100. Our findings support the notion that NTEs will exert positive net climate feedback; however, our estimation of positive net biogeochemical feedback including NME- and NCE-induced effects is contrary to previous studies showing negative net biogeochemical feedback including NCE-induced effect only. In conclusion, this study highlights the importance of NME-induced biogeochemical effect in regulating ecosystem-climate feedback in NTEs and implies that previous studies without considering NME-induced effect might have underestimated the intensity of total terrestrial feedback to the climate system.

54 ENVIRONMENTAL SCIENCES↗

CMIP6 Historical Simulations (1850‐2014) with GISS‐E2.1

Simulations of the CMIP6 historical period 1850‐‐2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to forcing than their CMIP5 predecessors (GISS‐E2), but warm less during recent decades due to reduced total forcing. This forcing reduction is attributed to an increase in longwave opacity in pre‐industrial simulations, resulting in an atmosphere less sensitive to further increases in opacity that result from rising greenhouse gas concentrations. This demonstrates the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin.

NASA Goddard Institute for Space Studies (GISS) Ea↗

Assessing direct and indirect emissions of greenhouse gases in road transportation, taking into account the role of uncertainty in the emissions inventory

Highlights: • The use-chain model implemented in this paper is effective in minimizing uncertainty. • Data integration is important to reduce uncertainty. • An innovative metric, Emission Value at Risk, was used to adjust uncertainty values. • Indirect impacts of economic activities change the estimate of GHG emissions. - Abstract: Greenhouse gas (GHG) concentration in the atmosphere has increased since the beginning of the industrial era, with dramatic effects on climate change. Transportation is one of the main sources of GHGs, with more than two-thirds of transport-related GHG emissions attributable to road vehicles. Any policy that aims to reduce GHG emissions needs robust measuring methods that guarantee the quality and reliability of primary data and estimates. However, these estimates are subject to uncertainty, both at the stage of compiling accounting tables and at the stage of using this information to formulate a specific policy question. This paper considers how to reduce uncertainty in estimating GHG emissions from road transportation, with specific reference to a regional emissions inventory in Italy. We propose the application of a use-chain model that can tackle uncertainty in measuring GHG emissions by enhancing the quality of the emissions data registry in the inventory. This new metric, which we call emission value at risk (VaR), draws from methodologies and concepts employed in the insurance and financial sectors. Moreover, additional assessments are performed, integrating the inventory data with those available in the regional energy balance and disaggregated sectoral economic dataset. The results show that a sound accounting method enables uncertainty in emission data to be taken into account, thus improving the design of appropriate strategies to reduce GHG emissions.

54 ENVIRONMENTAL SCIENCES↗

The association between ambient temperature and mortality in South Africa: A time-series analysis

Highlights: • Country-wide epidemiology study of temperature-mortality association in S. Africa. • Strongest associations were in children/elderly and from cardiorespiratory causes. • Total attributable mortality was 3.4%, mostly from cold (3.0%) rather than heat (0.4%). • Attributable mortality of 3.4% is on the low end of what is reported in other areas. • Results can help estimate future burdens from climate change and inform adaptation. There is an extensive literature describing temperature-mortality associations in developed regions, but research from developing countries, and Africa in particular, is limited.

54 ENVIRONMENTAL SCIENCES↗

Simulations With the Marine Biogeochemistry Library (MARBL)

Abstract The Marine Biogeochemistry Library (MARBL) is a prognostic ocean biogeochemistry model that simulates marine ecosystem dynamics and the coupled cycles of carbon, nitrogen, phosphorus, iron, silicon, and oxygen. MARBL is a component of the Community Earth System Model (CESM); it supports flexible ecosystem configuration of multiple phytoplankton and zooplankton functional types; it is also portable, designed to interface with multiple ocean circulation models. Here, we present scientific documentation of MARBL, describe its configuration in CESM2 experiments included in the Coupled Model Intercomparison Project version 6 (CMIP6), and evaluate its performance against a number of observational data sets. The model simulates present‐day air‐sea CO 2 flux and many aspects of the carbon cycle in good agreement with observations. However, the simulated integrated uptake of anthropogenic CO 2 is weak, which we link to poor thermocline ventilation, a feature evident in simulated chlorofluorocarbon distributions. This also contributes to larger‐than‐observed oxygen minimum zones. Moreover, radiocarbon distributions show that the simulated circulation in the deep North Pacific is extremely sluggish, yielding extensive oxygen depletion and nutrient trapping at depth. Surface macronutrient biases are generally positive at low latitudes and negative at high latitudes. CESM2 simulates globally integrated net primary production (NPP) of 48 Pg C yr −1 and particulate export flux at 100 m of 7.1 Pg C yr −1 . The impacts of climate change include an increase in globally integrated NPP, but substantial declines in the North Atlantic. Particulate export is projected to decline globally, attributable to decreasing export efficiency associated with changes in phytoplankton community composition.

Meteorology & Atmospheric Sciences↗

Declining tropical cyclone frequency under global warming

Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. Furthermore, we also present results from our 1-month proof-of-concept trial run designed to illustrate the utility and feasibility of the ARTMIP project.

58 GEOSCIENCES↗

NASA's Carbon Monitoring System Flux-Pilot Project: A Multi-Component Analysis System for Carbon-Cycle Research and Monitoring

The importance of greenhouse gas increases for climate motivates NASA s observing strategy for CO2 from space, including the forthcoming Orbiting Carbon Observatory (OCO-2) mission. Carbon cycle monitoring, including attribution of atmospheric concentrations to regional emissions and uptake, requires a robust modeling and analysis infrastructure to optimally extract information from the observations. NASA's Carbon-Monitoring System Flux-Pilot Project (FPP) is a prototype for such analysis, combining a set of unique tools to facilitate analysis of atmospheric CO2 along with fluxes between the atmosphere and the terrestrial biosphere or ocean. NASA's analysis system is unique, in that it combines information and expertise from the land, oceanic, and atmospheric branches of the carbon cycle and includes some estimates of uncertainty. Numerous existing space-based missions provide information of relevance to the carbon cycle. This study describes the components of the FPP framework, assessing the realism of computed fluxes, thus providing the basis for research and monitoring applications. Fluxes are computed using data-constrained terrestrial biosphere models and physical ocean models, driven by atmospheric observations and assimilating ocean-color information. Use of two estimates provides a measure of uncertainty in the fluxes. Along with inventories of other emissions, these data-derived fluxes are used in transport models to assess their consistency with atmospheric CO2 observations. Closure is achieved by using a four-dimensional data assimilation (inverse) approach that adjusts the terrestrial biosphere fluxes to make them consistent with the atmospheric CO2 observations. Results will be shown, illustrating the year-to-year variations in land biospheric and oceanic fluxes computed in the FPP. The signals of these surface-flux variations on atmospheric CO2 will be isolated using forward modeling tools, which also incorporate estimates of transport error. The results will be discussed in the context of interannual variability of observed atmospheric CO2 distributions.

Pawson, S.↗

Saint Joseph's University Institute for Environmental Stewardship

Task A: Examination of the physiological, morphological, and reproductive responses of Panicum virgatum (switchgrass) cultivars identified as potential biofuel producing cultivars as well as naturally-occurring varieties of switchgrass to projected changes in climate for the central portion of the United States. This project was a multi-year project set in a field site located at the Konza Prairie Biological Station near Manhattan, KS USA. The major objective of the study was to understand the physiological and growth responses of the important biofuel grass species, Panicum virgatum (switch grass) to simulated changes in precipitation expected for the Central Plains region of the United States. Population level adaptation to broad-scale regional climates or within-population variation in genome size of this genetically and phenotypically diverse C4 grass species may influence the responses to future precipitation variability associated with climate change. Therefore, we investigated switchgrass responses to water variability between natural populations collected across latitudinal gradient and populations. P. virgatum plants from natural populations originating from Kansas, Oklahoma, and Texas received frequent, small precipitation events (“ambient’) or infrequent, large precipitation events (‘altered”) to simulate contrasting rainfall variability expected from this region. We measured leaf-level physiology, aboveground biomass varied significantly by population origin but did not differ by genome size. Our results suggest that trait variation in P. virgatum is primarily attributed to population-level adaptation across latitudinal gradient, not genome size, and that neither population-level adaptation nor genome size may be important predictors of P. virgatum responses to future climatic conditions. Based solely on the data presented here, the most important consideration when deciding what varieties of switchgrass to cultivate for biofuel feedstocks under future climate scenarios is local adaptation and not necessarily genome size as has been hypothesized in the literature. Task B: Installation of an extensive green roof system on the Science Center at Saint Joseph's University for research, research-training and educational outreach activities. An experimental green roof system was designed and installed by an outside contractor (Roofmeadows) on the roof of the Science Center at Saint Joseph's University. The roof system includes four test plots, each with a different drainage system, instrumentation to monitor storm water retention, roof deck temperature, heat flux into and out of the building, rain fall, wind speed and direction, relative humidity and heat emission from the roof system. The vegetative roof was planted with 26 species of plants, distributed throughout the roof area, to assess species/variety growth and coverage characteristics, both in terms of the different drain layer systems, and in terms of the different exposures along the north to south axis of the building. Analysis of the drain layer performance, in terms of storm water retention, shows that the aggregate (stone) drainage layer system performed the best, with the moisture management mat system second, and the geotextile drain layer and reservoir sheet layer systems coming in last. This information is of value in the planning and design of vegetative roof systems since the different types of drainage layer systems have different installation costs and different weights. The different drainage layer systems also seem to be having an impact on plant growth and spread with the test plot with the reservoir sheet layer actually having the poorest plant coverage and plant spread of all areas of the roof studied. Plant growth performance analysis is ongoing, but significant differences have been observed in the third growing season ('13) along the north to south axis, with most species doing better towards the northern end of the roof (in terms of percent ground coverage and plant spread and reproduction). Interestingly, plant growth in all four of the test plots was reduced relative to the lower areas of the roof (the lower area was ca. 2 inches lower than the test plots, due to the space needed for sensors under the plots. The lower roof area uses an aggregate drain layer comparable to that in the third test plot), even when accounting for the north to south differences. The reasons for these differences are not clear and studies are underway to examine the impact of wind scour, drainage rates, temperature, and other factors. This information will be of value to planners of extensive vegetative roof systems in the Philadelphia (and broader) region, since plant growth and roof system overall performance is influenced by local climate, making broad generalizations of performance difficult. Task C: Education and community outreach efforts by the IES involving conferences at SJU, presentations by faculty and students off campus, and educational signage. The Institute for Environmental Stewardship hosted three storm water management workshops on the SJU campus in Philadelphia, in collaboration with the Lower Merion Conservancy, a not-for-profit organization located in Montgomery County, PA. These workshops were free and open to the public. The three workshops (held each year in March) drew more than 200 participants total. The presenters included local and state government agencies, not for profit organizations involved in storm water and open space preservation, designers, engineers, planners and others. Feedback was uniformly positive and we plan to continue the workshops for the foreseeable future. Educational signage has been installed at four locations on campus to explain campus infrastructure related to storm water (rain gardens, vegetative roof and green facades), as well as detailed signage installed on the Science Center roof for the vegetative roof system. More than 100 people (from in and outside of SJU) have thus far participated in tours of the roof system. A digital signage system has been installed in the adjacent library and this system provides information about the vegetative roof project and other efforts. A web camera system for the roof has also been installed and the video will be simulcast to the digital signage and with web site (www.sju.edu/ies) in the near future.

09 BIOMASS FUELS↗

Impact of Global Warming on U.S. Summertime Mesoscale Convective Systems: A Simple Lagrangian Parcel Model Perspective

Abstract Mesoscale convective systems (MCSs) are the dominant rainfall producer over the United States during the warm season, causing natural disasters and severe weather every year. Global climate models have large uncertainty in projecting precipitation changes in the future climate. Here, a simple Lagrangian parcel model is used to investigate the impact of global warming on MCS initiation and growth. The single-column parcel model projects a mean precipitation decrease over the central United States and an increase to its east, in agreement with the CMIP5 model projection. It also highlights the crucial role of current climate mean-state model bias in exaggerating the change in future mean precipitation projection by 25%. As for convective population, the model captures the decreased occurrence frequency of weak to moderate convection and increased frequency of strong convection due to the increased CAPE and CIN, in agreement with convection-permitting regional simulations. Novel parameterizations of gust-front propagation speed and subsidence strength are developed as guided by cloud-resolving simulations. The multicolumn parcel model employing those parameterizations captures readily the cold pool–induced upscale growth feature. It simulates smaller mesoscale clusters over the central United States under global warming due to gust-front slowdown and subsidence strength enhancement, which are further attributed to land aridity–induced weakening of initial accumulated precipitation and strengthening of updraft speed, respectively. That said, mesoscale clusters could become bigger under more favorable conditions in future climate, including boundary layer moistening, convection lifetime lengthening, and cold pool mechanical-lifting enhancement, which require further investigations to improve mechanistic understanding of future MCS changes.

54 ENVIRONMENTAL SCIENCES↗

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions of the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."

58 GEOSCIENCES↗

Variability in Modelled Airborne Dust Mineralogy Derived from Global Soil Composition Uncertainties

Dust aerosols consist on a variety of minerals with different physic and chemical properties. As such, they interact with short and long wave radiation, potentially form clouds, act as nutrients modulating biogeochemical cycles, or influence atmospheric chemistry, differently. Most current state-of-the-art Earth System Models (ESMs) neglect the complexity in dust composition, mainly due to computational constraints, but also to the existing uncertainties in the size resolved composition of parent soils, the resulting distribution of minerals in airborne dust, and the scarcity of observations to constrain them. Within this work, we assess the variability of global dust composition due to uncertainties in the characterization of the parent soil mineralogy. To that end, we consider two available global soil mineralogy atlases, developed by Claquin et al. (1999) –C1999- and Journet et al. (2014) –J2014-, which represent respectively 8 and 12 relevant minerals for climate (namely: illite, smectite/montmorillonite, kaolinite, calcite, gypsum, hematite, quartz, and feldspars in C1999, and those plus chlorite, vermiculite, goethite, and mica in J2014). Thanks to a recently developed feature of the MONARCH atmospheric-chemistry model, we are able to explicitly resolve the minerals’ atmospheric cycle. Therefore, we define two global experiments to assess changes on airborne dust composition attributed to the soil mineralogy assumptions and provide a measure of their variability. We also perform a preliminary evaluation of the global mineralogy results against available observations of mineral fractions in surface dust concentration. Our results will inform the climate modelling community about the potential variability in dust composition, an aspect that will gain relevance as ESMs continue growing in complexity and new processes to better characterize aerosols’ forcing or biogeochemical cycles are added. Further observational constraints, such as those that will derive from the EMIT NASA mission on soil composition or the FRAGMENT experimental campaigns on airborne dust characterization, will be key in the near future to improve our understanding of the impact of dust mineralogy on fundamental climate features.

Dust aerosols↗