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Topics in Theoretical Physics

This award supported a broadly based research effort in theoretical particle physics, including research aimed at uncovering the laws of nature at short (subatomic) and long (cosmological) distances. These theoretical developments apply to experiments in laboratories such as CERN, the facility that operates the Large Hadron Collider outside Geneva, as well as to cosmological investigations done using telescopes and satellites. The results reported here apply to physics beyond the so-called Standard Model of particle physics; physics of high energy collisions such as those observed at the Large Hadron Collider; theoretical and mathematical tools and frameworks for describing the laws of nature at short distances; cosmology and astrophysics; and analytic and computational methods to solve theories of short distance physics. Some specific research accomplishments include + Theories of the electroweak interactions, the forces that give rise to many forms of radioactive decay; + Physics of the recently discovered Higgs boson. + Models and phenomenology of dark matter, the mysterious component of the universe, that has so far been detected only by its gravitational effects. + High energy particles in astrophysics and cosmology. + Algorithmic research and Computational methods for physics of and beyond the Standard Model. + Theory and applications of relativity and its possible limitations. + Topological effects in field theory and cosmology. + Conformally invariant systems and AdS/CFT. This award also supported significant training of students and postdoctoral fellows to lead the research effort in particle theory for the coming decades. These students and fellows worked closely with other members of the group as well as theoretical and experimental colleagues throughout the physics community. Many of the research projects funded by this grant arose in response to recently obtained experimental results in the areas of particle physics and cosmology. We describe a few of these below. Relativity is founded on a symmetry property of nature called "Lorentz Invariance". Like all symmetry properties, it is essential to determine precisely how symmetric nature actually is; that is, do the laws of nature fully respect the symmetry or is there room for tiny symmetry violating effects? An important consequence of Lorentz invariance is the existence of a universal limiting velocity for all physical particles. Light travels at this limiting velocity so it is frequently referred to as simply "the speed of light", but relativity requires that ALL particles travel more slowly than this speed. Once the Higgs particle was discovered in 2012 a natural question was whether or not this particle's speed was consistent with relativity. Although the speed of the Higgs particle is not measurable directly, Cohen has shown that, if the maximal speed of the Higgs particle was not precisely the same as the speed of light, then the Higgs would have some unusual properties. In some cases the Higgs would be unstable to some unusual decay modes; in other cases the interactions of the Higgs with other particles would change the properties of these other particles in ways that could be observed in so-called cosmic rays, very energetic particles (such as photons, protons and other atomic nuclei) coming from space. Once these particles hit the upper atmosphere they produce a "shower" of particles that can be seen by ground-based instruments. If the Higgs has a maximal speed that differs even a tiny bit from the speed of light these showers would look quite different from what is observed. In this way Cohen was able to establish that the Higgs travels with a maximal speed that cannot differ from the speed of light by more than one part in a thousand-trillion. This is by far the most precisely determined property of the Higgs particle. Cohen and Schmaltz reviewed evidence from the Large Hadron Collider (LHC), a particle physics experiment operating at the CERN laboratory near Geneva, for a new particle sometimes called a W'. This evidence included certain unexpected by-products in collisions of protons at very high energy. While the evidence was not significant enough to claim a discovery, it was sufficiently intriguing that many particle theorists worked to construct explanations for this signal. Cohen and Schmaltz were able to determine that such explanations are highly constrained by previous experiments involving collisions of very energetic particles. Nevertheless they were able to construct a theory that adequately explains the LHC data and remain consistent with prior experiments. Their explanation predicts the existence of yet another new particle, called a Z', with a mass slightly greater than that of the W'. This additional particle, if it exists, should be seen as more data is collected from the LHC. Amusingly, there is one collision by-product that has already been seen by the CMS experiment at the LHC that supports the existence of this new particle; however, it is not unlikely that this single event is a so-called "background" event, that is a somewhat atypical by-product of a conventional Standard Model process. This theory for the anomalous LHC data will either be confirmed or excluded with further data-taking at the LHC. The ratio of the number of electrons produced in bottom quark decays over the number of muons produced has been measured at the LHC. This ratio is interesting because it can be predicted very precisely from a basic property of the Standard Model: lepton universality. If lepton universality is correct, the ratio of electrons to muons is predicted to be equal to 1. The first measurements of this ratio find a value different from 1 with a statistical significance of about 3 standard deviations. Schmaltz and collaborator proposed a new extension of the Standard Model which can explain the new data. In addition, Schmaltz and collaborators proposed several new measurements of ratios of decay rates which can confirm or rule out the surprising results from the earlier LHC data. The most recent and precise measurements of the cosmic microwave background from the Planck satellite, from a combination of measurements of the dark matter distribution in the universe, and from a measurement of the expansion rate of the universe today show some disagreement when interpreted in terms of the so-called LambdaCDM model. Schmaltz and collaborators proposed an alternative model to LambdaCDM in which the usual cold dark matter is replaced by a new ``dark sector". This sector consists of a cold dark matter particle which interacts with a newly postulated dark radiation component of the universe. The dark radiation can help explain the discrepancy in measurements of the expansion rate, and the dark matter interactions subtly modify the clumping of dark matter at large scales, thus potentially explaining both kinds of tensions in the data. In two publications Schmaltz described the new model and then performed a precision comparison of the predictions of the model with all currently available cosmological data. The results favor the new model at the level of three standard deviations with current data. Quantum Field Theory (QFT) is the language we use to describe quantum systems which are consistent with Einstein’s theory of Special Relativity. In particular, the requirement of Einstein’s theory that signals not travel faster than the speed of light constrains the types of interactions which particles can engage in. One consequence of relativity is that these interactions cannot preserve particle number. The stronger the interactions, the more severe the particle number violation in a given Relativistic QFT. When particle number violation is strong, it becomes very difficult to adequately parameterize the quantum wave function (which characterizes the state of a quantum system). For example, though we can formulate the QFT which describes the strong force as a set of interactions between quark and gluon particles, we have no clear idea how to express the proton state in terms of these quarks and gluons. This is because the proton, though a bound state of quarks and gluons, is not a state of a fixed number of particles due to strong interactions. Yet, understanding the proton state is very important in order to theoretically predict the reaction rates observed at the LHC in Geneva, which is a proton-proton collider. Katz has formulated a new approach to QFT, which among other things offers a way to adequately approximate the quantum wave function of a bound state at strong coupling. The approximation scheme is related to the fact that any sensible QFT (including that of the strong interactions) is at short distances approximately self-similar upon rescaling of space and time. It turns out that keeping track of the response upon this rescaling is important in efficiently parameterizing the state. Katz and collaborators have used this observation to approximate the state of the proton in toy versions of the strong force. In the late 60s Sheldon Glashow, Abdus Salam and Steven Weinberg (1979 Nobel Prize awardees) proposed a theory unifying weak and electromagnetic interaction which assumed the existence of new particles, the W and Z bosons. The W and Z bosons were eventually detected in high-energy collision in a particle accelerator at CERN, and the recent discovery of the Higgs meson at the Large Hadron Collider (LHC), always at CERN, completed the picture. However, deep theoretical considerations indicate that the theory by Glashow, Weinberg and Salam, often referred to as "the standard model" cannot be the whole story: the existence of new particles and new interactions at yet higher energies is widely anticipated. The experiments at the LHC are looking for these, while theorists, like Brower, Rebbi and collaborators, are investigating models for these new interactions. Working in a large national collaboration with access to the most powerful DOE computers Brower, Rebbi and colleagues have been using calculational techniques, similar to those successfully employed for many years to investigate the interactions among quarks in nucleons, to study theories that can describe the expected "beyond the standard model" (BSM) interactions. Their results, which include also a model for dark matter, have been published in several refereed papers in prestigious journals. Various ideas in topologically interesting field theories predict hypothetical objects such as fractional charges and Majorana excitations. However, such fascinating objects have not been seen in particle physics. Nevertheless, these objects demonstrate possible phenomena that quantum field theory can support. Pi used condensed matter physics as a laboratory to study possible realizations and observable effects of these objects predicted by quantum field theory. In recent times there has developed considerable interest among condensed matter field theorists in precisely the same geometrical and topological structures, which were first discovered in particle physics field theories. From particle physicists' point of view, this is an interesting development, since condensed matter provides an arena in which one can concretely realize particle physics ideas. Moreover, particle physicists can learn new ideas from condensed matter physics. Higgs phenomenon is precisely an important particle physics realization of condensed matter ideas. In contrast to the small distance characterizing condensed matter systems, field theory also describes large distance physics characterizing cosmology. Pi worked on various geometrical effects in the standard theory of cosmology, viz general relativity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Decreased growth of wild soil microbes after 15 years of transplant‐induced warming in a montane meadow

Abstract The carbon stored in soil exceeds that of plant biomass and atmospheric carbon and its stability can impact global climate. Growth of decomposer microorganisms mediates both the accrual and loss of soil carbon. Growth is sensitive to temperature and given the vast biological diversity of soil microorganisms, the response of decomposer growth rates to warming may be strongly idiosyncratic, varying among taxa, making ecosystem predictions difficult. Here, we show that 15 years of warming by transplanting plant–soil mesocosms down in elevation, strongly reduced the growth rates of soil microorganisms, measured in the field using undisturbed soil. The magnitude of the response to warming varied among microbial taxa. However, the direction of the response—reduced growth—was universal and warming explained twofold more variation than did the sum of taxonomic identity and its interaction with warming. For this ecosystem, most of the growth responses to warming could be explained without taxon‐specific information, suggesting that in some cases microbial responses measured in aggregate may be adequate for climate modeling. Long‐term experimental warming also reduced soil carbon content, likely a consequence of a warming‐induced increase in decomposition, as warming‐induced changes in plant productivity were negligible. The loss of soil carbon and decreased microbial biomass with warming may explain the reduced growth of the microbial community, more than the direct effects of temperature on growth. These findings show that direct and indirect effects of long‐term warming can reduce growth rates of soil microbes, which may have important feedbacks to global warming.

54 ENVIRONMENTAL SCIENCES↗

Impact of a New Sea Ice Thermodynamic Formulation in the CESM2 Sea Ice Component

Abstract The sea ice component of the Community Earth System Model version 2 (CESM2) contains new “mushy‐layer” physics that simulates prognostic salinity in the sea ice, with consequent modifications to sea ice thermodynamics and the treatment of melt ponds. The changes to the sea ice model and their influence on coupled model simulations are described here. Two simulations were performed to assess the changes in the vertical thermodynamics formulation with prognostic salinity compared to a constant salinity profile. Inclusion of the mushy layer thermodynamics of Turner et al. (2013, https://doi.org/10.1002/jgrc.20171 ) in a fully coupled Earth system model produces thicker and more extensive sea ice in the Arctic, with relatively unchanged sea ice in the Antarctic compared to simulations using a constant salinity profile. While this is consistent with the findings of uncoupled ice‐ocean model studies, the role of the frazil and congelation growth is more important in fully coupled simulations. Melt pond drainage is also an important contribution to simulated ice thickness differences as also found in the uncoupled simulations of Turner and Hunke (2015; https://doi.org/10.1002/2014JC010358 ). However, it is an interaction of the ponds and the snow fraction that impacts the surface albedo and hence the top melt. The changes in the thermodynamics and resulting ice state modify the ice‐ocean‐atmosphere fluxes with impacts on the atmosphere and ocean states, particularly temperature.

Bailey, David A.↗

Application of Satellite Observations to Manage Natural Disasters in the Lake Victoria Basin

Lake Victoria, the second largest fresh water lake in the Eastern part of Africa is a vital natural resource for the economic well being and prosperity of over 30 million people located in riparian regions of Uganda, Kenya and Tanzania. It covers a large area of about 68,870 km2 and produces a GDP of about US $30 billion per year. The region is also very much prone to natural disasters such as severe floods during heavy precipitation periods in the Eastern part of Africa. In addition to floods, the precipitation also produces large infestations of mosquito larvae due to the standing water in many areas. This further causes multiple vector borne diseases such as Malaria, Rift Valley Fever and more. These problems are of serious concern and require active and aggressive surveillance and management to minimize the loss of human and animal lives and property damage. Satellite imagery and observations along with the in situ measurements provide a great tool to analyze and study this area and inform the policy makers to make calculated policy decisions which are more beneficial to the environment. Recently, NASA and USAID have joined forces with the Regional Center for Mapping of Resources for Development (RCMRD) located in Nairobi, Kenya to utilize multiple NASA sensors such as TRMM, SRTM and MODIS to develop flood potential maps for the Lake Victoria Basin. The idea is to generate a flood forecasts and "nowcasts" that can be sent to the disaster management organizations of Uganda, Kenya, and Tanzania. Post flood event satellite imagery is becoming a common tool to assess the areas inundated by flooding. However, this work is unique undertaking by utilizing land imaging and atmospheric satellites to build credible flood potential maps. At same time, we are also studying the potential occurrence and spread of Rift Valley Fever disease based on the short term climate records and precipitation data. These activities require multi-nation coordination and agreements and multiple operational agencies within each respective country. It also requires credible in situ data such as precipitation, river flow rates and lake levels to further validate the global and regional Hood models and algorithms. This also requires a considerable amount of training and capacity building for the RCMRD experts who will help us validate the model results and eventually transition it for operational use. In a final analysis, Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid Hood mapping and distribution, and e) validation of Hood forecasting and detection products.

Habib, Shahid↗

Contrasting Parametric Sensitivities in Two Global Vegetation Models Using Parameter Perturbation Ensembles

Uncertainty in land model projections remains high and the roles of parametric and structural uncertainty are difficult to disentangle. To compare parametric sensitivity across model structures we present two parameter perturbation ensembles using the Community Land Model (CLM) operating in satellite phenology mode. The ensembles contrast two vegetation modules: (a) the default CLM vegetation module and (b) the Functionally Assembled Terrestrial Ecosystem Simulator (CLM-FATES). We perturbed over 300 parameters and quantified their effects on biophysical fluxes globally and across biomes. Most parameters have minimal impact on biophysical fluxes, with only a few substantially influencing results. While both models exhibit similar parameter sensitivity for some fluxes, CLM-FATES shows larger spread in gross primary productivity (GPP), driven by strong sensitivity to carboxylation rate. CLM-FATES also shows a weaker GPP response to soil hydrology parameters and exhibits higher water use efficiency (WUE). Cross-model comparisons reveal similar sensitivities for some parameters (e.g., leaf dimension) but divergent responses to others (e.g., stomatal intercept), highlighting underlying structural differences. Differences in WUE and sensitivity to hydrology and stomatal conductance parameters underscore how model structure fundamentally alters parametric sensitivity. The data sets generated from these ensembles can be used to identify influential parameters and guide future calibration efforts.

Foster, A. C. [NSF National Center for Atmospheric↗

An Ensemble Covariance Framework for Quantifying Forced Climate Variability and Its Time of Emergence

Climate variability and its response to increasing greenhouse gases are important considerations for impacts and adaptation. Modeling studies commonly assess projected changes in variability in terms of changes in the variance of climate variables. Despite the distant and impactful covariations that climate variables can exhibit, the covariance response has received much less attention. Here, a novel ensemble framework is developed that facilitates a unified assessment of the response of the regional variances and covariances of a climate variable to imposed external forcings and their time of emergence from an unforced climate state. Illustrating the framework, the response of variability and covariability of land and ocean temperatures is assessed in the Community Earth System Model Large Ensemble under historical and RCP8.5 forcing. The results reveal that land temperature variance emerges from its preindustrial state in the 1950s and, by the end of the twenty-first century, grows to 1.5 times its preindustrial level. Demonstrating the importance of covariances for variability projections, the covariance between land and ocean temperature is considerably enhanced by 2100, reaching 1.4 times its preindustrial estimate. The framework is also applied to assess changes in monthly temperature variability associated with the Arctic region and the Northern Hemisphere midlatitudes. Consistent with previous studies and coinciding with sea ice loss, Arctic temperature variance decreases in most months, emerging from its preindustrial state in the late twentieth century. Overall, these results demonstrate the utility of the framework in enabling a comprehensive assessment of variability and its response to external climate forcings.

54 ENVIRONMENTAL SCIENCES↗

Planning the Next Decade of Coordinated Research to Better Understand and Simulate Marine Low Clouds

Marine low clouds have a large impact on the Earth’s energy and hydrologic cycle. They strongly reflect incoming solar radiation, with little compensating impact on outgoing longwave radiation resulting in a net cooling of the climate. The representation of marine low clouds in climate models is one of the largest uncertainties in the estimation of climate sensitivity (e.g. Bony and Dufresne 2005), and marine low clouds are critical mediators of global aerosol radiative forcing (Zelinka et al. 2014). Despite the importance of these cloud systems to the Earth’s climate, their parameterization continues to be challenging, due to an incomplete understanding of key processes that regulate them and insufficient resolution of these processes in models. To help define research pathways to address outstanding issues related to our understanding of marine low clouds, a workshop was held January 27-29, 2016 at Brookhaven National Laboratory. The overarching goal was to identify current gaps in knowledge or simulation capabilities and promising strategies for addressing them, with a particular emphasis on improving the representation of marine low clouds in climate models and contributions that could be made with U.S. Department of Energy Atmospheric System Research support using Atmospheric Radiation Measurement facility measurements.

Wood, Robert↗

NASA's Soil Moisture Active and Passive (SMAP) Mission

The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the performance of candidate algorithms. SMAP conducted an Applications Workshop in September 2009 to coordinate with potential application users interested in the mission data. A draft Applications Plan describing the Project s planned outreach to potential applications users has been prepared and will be updated during Phase B. SMAP made a significant evaluation of the potential terrestrial radio frequency interference (RFI) source environment and established radiometer and radar flight hardware and ground processing mitigation approaches. SMAP finalized its science orbit and orbit injection approach to optimize launch mass and prepared launch and commissioning scenarios and timeline. A science data communications approach was developed to maximize available science data volume to improve science margins while maintaining moderately short data product latencies to support many potential applications using existing ground assets and with minimum impact to the flight system. SMAP developed rigid multi-body and flexible body dynamics and control models and system designs for the 6-meter rotating instrument reflector-boom assembly (RBA) and flight system to confirm pointing and control performance, and devised strategies to efficiently implement on-orbit balancing if needed. Industry partners were selected for the spin mechanism assembly (SMA) and RBA. Preliminary designs for the radar and radiometer were initiated, including constructing breadboards of key assemblies.

Kellogg, Kent↗

NASA's Aeroacoustic Tools and Methods for Analysis of Aircraft Noise

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The ability to quantify aircraft noise at the source and ultimately at observers is required to develop low noise aircraft designs and flight procedures. Predicting noise at the source, accounting for scattering and propagation through the atmosphere to the observer, and assessing the perception and impact on a community requires physics-based aeroacoustics tools. Along with the analyses for aero-performance, weights and fuel burn, these tools can provide the acoustic component for aircraft MDAO (Multidisciplinary Design Analysis and Optimization). Over the last decade significant progress has been made in advancing the aeroacoustic tools such that acoustic analyses can now be performed during the design process. One major and enabling advance has been the development of the system noise framework known as Aircraft NOise Prediction Program2 (ANOPP2). ANOPP2 is NASA's aeroacoustic toolset and is designed to facilitate the combination of acoustic approaches of varying fidelity for the analysis of noise from conventional and unconventional aircraft. The toolset includes a framework that integrates noise prediction and propagation methods into a unified system for use within general aircraft analysis software. This includes acoustic analyses, signal processing and interfaces that allow for the assessment of perception of noise on a community. ANOPP2's capability to incorporate medium fidelity shielding predictions and wind tunnel experiments into a design environment is presented. An assessment of noise from a conventional and Hybrid Wing Body (HWB) aircraft using medium fidelity scattering methods combined with noise measurements from a model-scale HWB recently placed in NASA's 14x22 wind tunnel are presented. The results are in the form of community noise metrics and auralizations.

Rizzi, Stephen A.↗

Interannual fires as a source for subarctic summer decadal climate variability mediated by permafrost thawing

Climate model simulations run under the Coupled Model Intercomparison Project Phase 6 (CMIP6) use an inhomogeneous biomass burning aerosol (BBA) emission dataset, which exhibits pronounced interannual variability from 1997–2014 due to the infusion of satellite data. Using the Community Earth System Model version 2 Large Ensemble (CESM2-LE) with original and smoothed CMIP6 BBA forcings, we show that the CMIP6 data inhomogeneity causes spurious decadal subarctic land warming. During years with reduced aerosol concentrations, increased solar radiation can trigger abrupt subarctic permafrost thawing, increased soil water drainage, upper soil drying, and subsequent surface warming. This slow process, which is further amplified by nonlinear cloud-aerosol interactions, cannot be completely offset during years of increased aerosol fluxes, thereby reddening surface temperature spectra in response to large-amplitude interannual aerosol forcing. More generally, our CESM2 experiments identify a pathway for generating decadal variability in high latitudes, involving interannual shortwave forcing and slow nonlinear soil responses.

54 ENVIRONMENTAL SCIENCES↗

Development of High Resolution Land Surface Parameters for the Community Land Model

There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0) are at 0.5° or coarser resolutions, released with the Community Earth System Model (CESM). Plant Functional Types (PFTs), vegetation properties such as Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land covers were developed using remotely sensed datasets retrieved in late 1990’s and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. Advantages and disadvantages of each dataset were discussed in order to provide guidance on the use of the data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM) applied to the western U.S. to demonstrate their use in high-resolution modeling. A remapping method from the latitude/longitude grid of the CLM data to the WRF grids with map projection was also demonstrated. Future work will include global offline CLM simulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

Environmental Molecular Sciences Laboratory↗

Will There Be a Significant Change to El Niño in the Twenty-First Century?

The El Niño–Southern Oscillation (ENSO) response to anthropogenic climate change is assessed in the following 1° nominal resolution Community Climate System Model, version 4 (CCSM4) Coupled Model Intercomparison Project phase 5 (CMIP5) simulations: twentieth-century ensemble, preindustrial control, twenty-first-century projections, and stabilized 2100–2300 “extension runs.” ENSO variability weakens slightly with CO 2 ; however, various significance tests reveal that changes are insignificant at all but the highest CO 2 levels. Comparison with the 1850 control simulation suggests that ENSO changes may become significant on centennial time scales; the lack of signal in the twentieth- versus twenty-first-century ensembles is due to their limited duration. Changes to the mean state are consistent with previous studies: a weakening of the subtropical wind stress curl, an eastward shift of the tropical convective cells, a reduction in the zonal SST gradient, and an increase in vertical thermal stratification take place as CO 2 increases. The extratropical thermocline deepens throughout the twenty-first century, with the tropical thermocline changing slowly in response. The adjustment time scale is set by the relevant ocean dynamics, and the delay in its effect on ENSO variability is not diminished by increasing ensemble size. The CCSM4 results imply that twenty-first-century simulations may simply be too short for identification of significant tropical variability response to climate change. An examination of atmospheric teleconnections, in contrast, shows that the remote influences of ENSO do respond rapidly to climate change in some regions, particularly during boreal winter. Finally, this suggests that changes to ENSO impacts may take place well before changes to oceanic tropical variability itself become significant.

54 ENVIRONMENTAL SCIENCES↗

Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean

Abstract Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystem stressors on monthly, seasonal, and multi‐month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecast skill of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation‐based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon (DIC), dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making.

Environmental Sciences & Ecology↗

Wildfire‐induced increases in photosynthesis in boreal forest ecosystems of North America

Abstract Observations of the annual cycle of atmospheric CO 2 in high northern latitudes provide evidence for an increase in terrestrial metabolism in Arctic tundra and boreal forest ecosystems. However, the mechanisms driving these changes are not yet fully understood. One proposed hypothesis is that ecological change from disturbance, such as wildfire, could increase the magnitude and change the phase of net ecosystem exchange through shifts in plant community composition. Yet, little quantitative work has evaluated this potential mechanism at a regional scale. Here we investigate how fire disturbance influences landscape‐level patterns of photosynthesis across western boreal North America. We use Alaska and Canadian large fire databases to identify the perimeters of wildfires, a Landsat‐derived land cover time series to characterize plant functional types (PFTs), and solar‐induced fluorescence (SIF) from the Orbiting Carbon Observatory‐2 (OCO‐2) as a proxy for photosynthesis. We analyze these datasets to characterize post‐fire changes in plant succession and photosynthetic activity using a space‐for‐time approach. We find that increases in herbaceous and sparse vegetation, shrub, and deciduous broadleaf forest PFTs during mid‐succession yield enhancements in SIF by 8–40% during June and July for 2‐ to 59‐year stands relative to pre‐fire controls. From the analysis of post‐fire land cover changes within individual ecoregions and modeling, we identify two mechanisms by which fires contribute to long‐term trends in SIF. First, increases in annual burning are shifting the stand age distribution, leading to increases in the abundance of shrubs and deciduous broadleaf forests that have considerably higher SIF during early‐ and mid‐summer. Second, fire appears to facilitate a long‐term shift from evergreen conifer to broadleaf deciduous forest in the Boreal Plain ecoregion. These findings suggest that increasing fire can contribute substantially to positive trends in seasonal CO 2 exchange without a close coupling to long‐term increases in carbon storage.

Biodiversity & Conservation↗

On the role of climate modes in modulating the air–sea CO 2 fluxes in eastern boundary upwelling systems

Abstract. The air–sea CO 2 fluxes in eastern boundary upwelling systems (EBUSs) vary strongly in time and space, with some of the highest flux densities globally. The processes controlling this variability have not yet been investigated consistently across all four major EBUSs, i.e., the California (CalCS), Humboldt (HumCS), Canary (CanCS), and Benguela (BenCS) Current systems. In this study, we diagnose the climatic modes of the air–sea CO 2 flux variability in these regions between 1920 and 2015, using simulation results from the Community Earth System Model Large Ensemble (CESM-LENS), a global coupled climate model ensemble that is forced by historical and RCP8.5 radiative forcing. Differences between simulations can be attributed entirely to internal (unforced) climate variability, whose contribution can be diagnosed by subtracting the ensemble mean from each simulation. We find that in the CalCS and CanCS, the resulting anomalous CO 2 fluxes are strongly affected by large-scale extratropical modes of variability, i.e., the North Pacific Gyre Oscillation (NPGO) and the North Atlantic Oscillation (NAO), respectively. The CalCS has anomalous uptake of CO 2 during the positive phase of the NPGO, while the CanCS has anomalous outgassing of CO 2 during the positive phase of the NAO. In contrast, the HumCS is mainly affected by El Niño–Southern Oscillation (ENSO), with anomalous uptake of CO 2 during an El Niño event. Variations in dissolved inorganic carbon (DIC) and sea surface temperature (SST) are the major contributors to these anomalous CO 2 fluxes and are generally driven by changes to large-scale gyre circulation, upwelling, the mixed layer depth, and biological processes. A better understanding of the sensitivity of EBUS CO 2 fluxes to modes of climate variability is key in improving our ability to predict the future evolution of the atmospheric CO 2 source and sink characteristics of the four EBUSs.

54 ENVIRONMENTAL SCIENCES↗

Regional Disparities in the Beneficial Effects of Rising CO2 Emissions on Crop Water Productivity

Rising atmospheric carbon dioxide concentrations are expected to enhance photosynthesis and reduce crop water use. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments and global crop models to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated carbon dioxide and associated climate change projected for a high-end greenhouse gas emissions scenario. We find carbon dioxide effects increase global CWP by 10[0;47]%-27[7;37]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rain fed wheat). If realized in the fields, the effects of elevated carbon dioxide could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4-17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modeling the effects of rising carbon dioxide across crop and hydrological modeling communities.

Deryng, Delphine↗

Observation-constrained kinetic modeling of isoprene SOA formation in the atmosphere

Isoprene has the largest global non-methane hydrocarbon emission, and the oxidation of isoprene plays a crucial role in the formation of secondary organic aerosol (SOA). Two primary processes are known to contribute to SOA formation from isoprene oxidation: (1) the reactive uptake of isoprene-derived epoxides on acidic or aqueous particle surfaces and (2) the absorptive gas–particle partitioning of low-volatility oxidation products. In this study, we developed a new multiphase condensed isoprene oxidation mechanism that includes these processes with key molecular intermediates and products. The new mechanism was applied to simulate isoprene gas-phase oxidation products and SOA formation from previously published chamber experiments under a variety of conditions and atmospheric observations during the Southern Oxidant and Aerosol Studies (SOAS) field campaign. Our results show that SOA formation from most of the chamber experiments is reasonably reproduced using our mechanism, except when the concentration ratios of initial nitric oxide to isoprene exceed ~ 2, the formed SOA is significantly underpredicted. The SOAS simulations also reasonably agree with the measurements regarding the diurnal pattern and concentrations of different product categories, while the total isoprene SOA remains underestimated. The molecular compositions of the modeled SOA indicate that multifunctional low-volatility products contribute to isoprene SOA more significantly than previously thought, with a median mass contribution of ~ 57 % to the total modeled isoprene SOA. However, this contribution is intricately intertwined with IEPOX-derived SOA (IEPOX: isoprene-derived epoxydiols), posing challenges for their differentiation using bulk aerosol composition analysis (e.g., the aerosol mass spectrometer with positive matrix factorization). Furthermore, the SOA from these pathways may vary greatly, mainly dependent on the volatility estimation and treatment of particle-phase processes (i.e., photolysis and hydrolysis). Our findings emphasize that the various pathways to produce these low-volatility species should be considered in models to more accurately predict isoprene SOA formation. The new condensed isoprene chemical mechanism can be further incorporated into regional-scale air quality models, such as the Community Multiscale Air Quality Modelling System (CMAQ), to assess isoprene SOA formation on a larger scale.

54 ENVIRONMENTAL SCIENCES↗

NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0: Stratospheric Composition

The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-29CF) provides recent estimates and five-day forecasts of atmospheric composition to the public in near-real time. To do this, the GEOS Earth system model is coupled with the GEOS-Chem tropospheric-stratospheric unified chemistry extension (UCX) to represent composition from the surface to the top of the GEOS atmosphere (0.01 hPa). The GEOS-CF system is described, including updates made to the GEOS-Chem UCX mechanism within GEOS-CF for improved representation of stratospheric chemistry. Comparisons are made against balloon, lidar and satellite observations for stratospheric composition, including measurements of ozone (O3) and important nitrogen and chlorine species related to stratospheric O3recovery. The GEOS-CF nudges the stratospheric O3towards the GEOS Forward Processing (GEOS FP) assimilated O3product; as a result the stratospheric O3in the GEOS-CF historical estimate agrees well with observations. During abnormal dynamical and chemical environments such as the 2020 polar vortexes, the GEOS-CF O3forecasts are more realistic than GEOS FP O3forecasts because of the inclusion of the complex GEOS-Chem UCX stratospheric chemistry. Overall, the spatial patterns of the GEOS-CF simulated concentrations of stratospheric composition agree well with satellite observations. However, there are notable biases – such as low NOx and HNO3 in the polar regions and generally low HCl throughout the stratosphere – and future improvements to the chemistry mechanism and emissions are discussed. GEOS-CF is a new tool for the research community and instrument teams observing trace gases in the stratosphere and troposphere, providing near-real-time three-dimensional gridded information on atmospheric composition.

GEOS-CF↗