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Year Initially FundedSorted By Year Initially Funded In Descending OrderPrincipal InvestigatorTitleTopicReportAbstractCo-PI
2019Arlyn Andrews (NOAA GMD)Data assimilation to leverage diverse datasets for improved CO2 & CH4 flux estimation and future observing system designLong Term Trends in Observations of Atmospheric Composition The surface and aircraft records from NOAA’s Global Greenhouse Gas Reference Network (GGGRN) provide a wealth of information about the spatial distributions and trends of CO2 and CH4, but key regions such as the Amazon and the Arctic are not adequately sampled due to expense and logistical challenges. Fortunately, complementary data records are available that will provide strong new constraints on flux estimates and simulated atmospheric transport. Newly available profile data from the Japanese CONTRAIL commercial aircraft sampling program and from the IPEN Brazilian regional aircraft network will provide especially useful constraints on previously under-sampled regions, and ground-based networks have greatly expanded over the past 10 years. Meanwhile, intensive sampling campaigns such as the global-scale HIPPO and ATom experiments and the Arctic-focused CARVE and ABoVE programs provide detailed snapshots of poorly observed regions. Satellite sensors such as GOSAT, OCO-2 and TROPOMI are providing new information in regions where other types of atmospheric data are sparse, but retrievals are complicated and susceptible to systematic errors that can complicate or confound flux estimation. Consequently, the best flux estimates will come from a rigorous combination of a variety of data types, and targeted research is needed to develop objective approaches for appropriately weighting and combining diverse data streams. Methods are needed that reliably reveal errors in simulated atmospheric transport, which can lead to biases in estimated fluxes if not corrected. 1. We will apply a novel data assimilation strategy developed at the University of Toronto that optimizes the 4-dimensional CO2 and CH4 distributions instead of, or together with, the surface fluxes. When sufficiently dense and accurate data are available, simulated atmospheric trace gas distributions can be locally adjusted to mitigate errors in the model transport. We will integrate aspects of this approach into NOAA’s CarbonTracker. 2. We will incorporate GGGRN and additional in situ data into the Harvard methane inversion framework. This system has already been used to estimate global CH4 emissions and OH fields using GOSAT retrievals. The Harvard effort will complement and extend GMD inhouse work to identify factors responsible for increased CH4 growth over the past decade. 3. We will conduct a limited set of observing system simulation experiments to investigate what optimal combinations of surface, aircraft, and satellite sampling are needed to reliably detect potential future changes in the global carbon cycle such as releases of CO2 and/or CH4 from permafrost thaw or from changes in the uptake of tropical forests. We aim to extract the maximum benefit from the GGGRN dataset by augmenting it with complementary data and using state-of-the science modeling tools to produce optimized estimates of the global CO2 and CH4 distributions and their uncertainties, along with optimized estimates of emissions and removal processes. We expect that the combined dataset will provide sufficient constraints to finally resolve long-standing questions about the relative influences of tropical versus northern land CO2 sinks and the distribution of sinks within the northern extratropics. We will estimate trends in methane emissions and removals, with particular emphasis on anthropogenic emissions in North America and Arctic emissions. Thus, our proposed work will powerfully demonstrate the value of sustained observation and directly responds to the request for proposals focused on methane.Dylan Jones (University of Toronto), Daniel Jacob (Harvard University)
2019Dr. Kenneth Davis (Pennsylvania State University)Diagnosis of North America CO2 and CH4 fluxes with the expanded in situ measurement networkLong Term Trends in Observations of Atmospheric Composition North American biogenic carbon dioxide (CO ) fluxes and total methane (CH.i) emissions remain poorly diagnosed at regional scales. Regional scales (areas smaller than the entire continent - the MidWest com belt, or MidAtlantic forests, for example) are critically important because they are the scales (biomes, geopolitical units) over which management activities take place, and over which climate and ecological processes drive terrestrial fluxes. A rapid expansion in North American, tower-based greenhouse gas (GHG) measurements over the last decade, and substantial advances in atmospheric inversion methodology provide an excellent opportunity for improving our understanding of regional CO2 and CH-1 fluxes. This project will take advantage of an extensive continental GHG measurement network (over 80 continuous, tower-based measurements, and over 20 flask measurement and aircraft profiling sites) and a newly operational continental-scale flux inversion system, CarbonTracker - Lagrange, to diagnose North American GHG fluxes at regional spatial and sub-seasonal temporal resolution from 2007 2018. These inverse flux estimates will be cross-evaluated with comparisons of posterior mole fractions to independent atmospheric GHG mole fraction observations from the Atmospheric Carbon and Transport (ACT) - America Earth Venture Suborbital (EVS) flight campaigns, and comparisons of posterior fluxes to regional clusters of flux towers. Sensitivity studies to inversion system inputs will explore the robustness of the results. The resulting inverse flux estimates will be compared to climate variations and trends in an effort to diagnose causal relationships between fluxes and climate conditions. The inverse fluxes will also be compared to terrestrial biogeochcmical models and inventory flux estimates when available, to demonstrate the utility of the atmospheric data for cross-evaluation of model and inventory methods of esti matin g regional GHG fluxes. Second, a range of data remo va l experiments will illustrate the value of currently available tower and aircraft data in resolving both spatia l structure and temporal patterns in GHG fluxes. This portion of the study will demonstrate the value of continued operation of an expanded in situ observational network and inform the design of a future integrated carbon observing system. This project responds to the AC4 request for studies of long-term trends in observations of atmospheric composition. In particular, the investigators will ..explain various trends, patterns and extremes detectable in the existing long-term observational records." We will illuminate "long-term trends patterns, anomalies and extremes in long-term trends, intra- and interannual variability and change, changes in amplitude of seasonal cycle, local or regional changes in the long-term trends" in continental GHG fluxes and the associated records of atmospheric composition. We will also provide new insight into regional CH4 emissions, thus responding to the request from the National Academy of Sciences for proposals that focus on anthropogenic methane emissions. Finally, by using complementary data from non-NOAA sources, the project will, "demonstrate future expansion capabilities and/or to test how detection limits for trends can be lowered." This project advances the Climate Program Office's objective to advance scientific understanding, monitoring, and prediction of climate, and will guide future investment in observational and analytic capabilities.Dr. Arlyn Andrews (NOAA GMD)
2019Colette L. Heald (Massachusetts Institute of Technology)Exploring the trend in inorganic aerosol depositionLong Term Trends in Observations of Atmospheric Composition Atmospheric aerosols degrade visibility, alter the radiative balance of the planet, are the leading environmental cause of premature mortality, and are a vector for the deposition of both nutrients and toxic species to the environment. Inorganic aerosol (sulfate, nitrate, and ammonium) make up a substantial fraction of fine aerosol particles in surface air. These particles largely reflect human activities, where emissions from mobile sources (nitrogen oxides, NOx), power generation (sulfur oxides, SOx) and agriculture (ammonia, NH3) are the major precursors. National networks in the United States have been making measurements of inorganic aerosol deposition both in precipitation (National Atmospheric Deposition Program, NADP) and from surface uptake (Clean Air Status and Trends Network, CASTNET) for decades. The goal of this project is to explore the trend in these observations of inorganic aerosol deposition and how these measurements can constrain aerosol precursor emissions and removal. Specifically, we propose to quantify the interannual variability and trend in inorganic aerosol deposition from 1995-2015 in the continental United States using quantile regression. We will then investigate how well measurements from the current networks of deposition monitoring reflect trends in bottom-up emissions over the same time interval. Finally, we will use these deposition measurements to test and identify biases in the representation of aerosol loss in a global model (GEOS-Chem). The proposed work directly addresses the AC4 program research priorities and solicitation by exploring long-term records of deposition collected by the NADP (supported by NOAA) and CASTNET monitoring networks. In addition, the proposed work will focus not only on trends, but also on extremes in the multi-decadal observational record as highlighted in the solicitation. Finally, we will make use of complementary datasets and use these to help comment on the intrinsic value of the United States deposition monitoring networks. 
2019Lu Hu (University of Montana)Long-term trends of tropospheric ozone constrained by global observation networks and GEOS-ChemLong Term Trends in Observations of Atmospheric Composition The two main tropospheric oxidants, ozone and OH radical, are critical drivers of photochemical processes that determine the lifetime of most air pollutants and methane. Current models, however, cannot explain the observed ozone trend and the inferred variability in global mean OH over the past few decades, which limits our capability to estimate ozone radiative forcing and policyrelevant ozone background. The failure of models to capture OH variability also makes it challenging to interpret trends in methane, whose main sink is OH. This project aims to explore the processes controlling long-term changes of tropospheric ozone over 1980-2018. Our proposal plans to examine the seasonal, intra- and interannual changes of the existing decades-long observational records of ozone, nonmethane volatile organic compounds (VOCs), and nitrate wet deposition fluxes. Comprehensive data analysis of the long-term observations will then be used to constrain the processes of the GEOS-Chem chemical transport model to address the following three sets of questions: 1. Can observations of nitrate wet deposition fluxes be used to derive the long-term trend of anthropogenic NOx emission over the U.S. and Europe? And, could NOx be a key driver for the observed ozone changes in the lower troposphere since the 1980s? 2. Do the seasonal cycles and interannual variabilities of non-methane VOCs such as aromatics and acetylene reflect not only the change of anthropogenic VOC emissions, but also provide a measure of seasonal and regional OH variability? 3. Has the long-term change of the tropospheric ozone budget over the last four decades been controlled by variations in anthropogenic emissions (NOx and non-methane VOCs), as well as stratosphere-troposphere exchange? We will examine the roles of anthropogenic VOCs and NOx emission trends and ozone variability in the lowermost stratosphere in driving tropospheric ozone change over the last four decades. With improved knowledge of the controlling factors, we will then quantify the radiative forcing from tropospheric ozone trends since the 1980s and also revisit previous estimates of the forcing due to anthropogenic ozone changes since the preindustrial era. Finally, we will also examine the implications of our results for global mean OH. This proposal targets the NOAA AC4 Call for Proposals in FY19, and aims to explain the trends and variabilities in tropospheric ozone and OH radical using existing long-term observational records of ozone, non-methane VOCs, and nitrate wet deposition. This work will also improve our understanding of the factors controlling tropospheric oxidation capacity, and represents a critical step toward better prediction of tropospheric chemistry and air quality in the future under a climate change regime.Loretta Mickley (Harvard University)
2019Scott J. Lehman (University of Colorado, Boulder)A 10-year analysis of North American anthropogenic and biospheric CO2 fluxes from network observations of Δ 14CO2 and CO2Long Term Trends in Observations of Atmospheric Composition With prior support from NOAA’s Climate Program Office and Global Monitoring Division, we have greatly expanded the use of high-precision Δ14CO2 measurements as a tracer of recently-emitted CO2 from combustion of fossil fuels and cement manufacture (FFCO2) within the NOAA Global Greenhouse Gas Reference Network (GGGRN) and developed the computational machinery needed in order to use the new observations in a dual-tracer inversion framework capable of separating fossil and biospheric CO2 fluxes. In recent work, we obtain inverse estimates of US FFCO2 emissions based on network observations from 2010 indicating emissions 5-7 % larger than from the most widely-used international emissions inventories. These differences are statistically significant with respect to rigorously-derived posterior FFCO2 flux uncertainties and apparently robust to differing specifications of the magnitude and seasonality of prior emissions. Furthermore, derived monthly FFCO2 emissions estimates are similar to monthly, national 2010 totals from the (forthcoming) US Vulcan 3.0 inventory. Here we propose to leverage the now long-term Δ14CO2 NOAA measurement effort led by the PIs in order to undertake a similar analysis of US monthly emissions for the decade of GGGRN CO2 and Δ14CO2 observations spanning 2010 through 2019. Our overall goal will be to determine whether differences between widely-used international emissions inventories and our estimates of US FFCO2 emissions from observations are real and persistent over time, based on a proposed analysis of uncertainties and possible biases in our dual-tracer inversion framework arising from assigned a priori fluxes and atmospheric transport. Our effort will include extending high resolution US Vulcan inventories through 2019 (Northern Arizona Univ.) and comparison to annual US EPA FFCO2 inventories reported to the UNFCCC. This proposal is directly responsive to CPO ESSM’s AC4 competition goals, aimed at the use of long-term observational records to constrain trends and processes influencing atmospheric composition and climate. The proposed work bears directly on a key CPO mandate, namely to advance scientific monitoring in support of effective decision making. The proposed work can be expected to provide improved understanding of US FFCO2 emissions and their uncertainties, informing the US carbon budget, US emissions reporting, and estimates of climate forcing. Detection of persistent biases in the US country portion of international emissions inventories would suggest that such biases may be widespread and of even greater significance.Kevin R. Gurney (Northern Arizona University)
2019John B. Miller (NOAA ESRL)Understanding three decades of terrestrial carbon exchange and vegetation drought dynamics through inverse modeling of globally distributed records of atmospheric carbon-13 and CO2Long Term Trends in Observations of Atmospheric Composition The long-term record of atmospheric CO2 increase shows that only about 50% of CO2 emitted by fossil fuel burning remains in the atmosphere, with the rest being absorbed by the oceans and terrestrial biosphere. Yet the persistence of this carbon sink is uncertain, with coupled carbon-cycle climate models in Earth system models (ESMs) exhibiting divergent behavior. Most of the model uncertainty appears to be related to differing parameterizations of carbon uptake and its sensitivity to environmental drivers like temperature and moisture. In this proposal, we aim to use a 30 year-long, globally distributed records of CO2 and its 13C:12C ratio (expressed as d13C) to begin to constrain the relationship between drought and carbon uptake. The relationships we observe via atmospheric measurements will be compared to the same relationships in carbon cycle models commonly used in ESMs, thus allowing us to test the validity of their carbon-climate linkages. In particular, we will use a newly developed dual-tracer variant of the CarbonTracker data assimilation system, CTDAS-C13, to use CO2 and d13C data to optimize values of terrestrial net flux (NEE) and isotopic discrimination during photosynthesis (Dph). Dph is related to stomatal conductance, and thus a sensitive indicator of a plant’s or ecosystem’s response to drought. Recent work by Peters et al. [2018] showed a strong relationship between NEE and Dph and additionally demonstrated that no biosphere model (out of six tested) exhibited even half the sensitivity of the data-constrained relationship. Here we propose to extend that analysis to more models, a much greater time span and examine the relationship between NEE, Dph and additional variables. As part of the project we will re-examine and improve numerous aspect of the CO2 and d13C budgets required for accurate modeling, including fluxes and isotopic parameters associated with fossil emissions, and oceanic, and terrestrial C exchange. We will also create a new harmonized long-term d13C data set that, along with all model input fluxes, and the CTDAS-C13 model itself, will be made freely available. 
2019Dr. Irina Petropavlovskikh (University of Colorado, Boulder)Status of ozone recovery detected in NOAA ground-based and satellite ozone recordsLong Term Trends in Observations of Atmospheric Composition The proposed work will assess long-term ozone trends from data collected by NOAA and its predecessors since the 1960s. The 1990 amendments to the US Clean Air Act responded to the US signing of the 1987 Montreal Protocol requires NOAA and NASA to monitor ozone and the reduction of ozone depleting substances. Signs of ozone recovery are occurring in the upper stratosphere. Questions are: is the ozone layer recovering globally and at what levels; and is the recovery at the rate expected from the reduction of ozone-depleting substances? To support this requirement NOAA’s Earth System Research Laboratory, Global Monitoring Division (ESRL/GMD) ozone monitoring program performs ground-based (GB) observations of total column ozone with the stable, well-calibrated Dobson Spectrometers. Changes in vertical ozone profiles are assessed with the Dobson Umkehr technique at 5 stations. These measurements are supplemented by balloon-borne ozonesonde instruments from 10 stations in collaboration with the NASA Southern Hemisphere ADditional OZonesondes (SHADOZ) program. Additionally NASA and NOAA provide satellite measurements of ozone profiles through the Solar Backscatter Ultraviolet (SBUV) and related instruments on NASA’s Nimbus-4 and -7, and on the NOAA Polar Orbiting Environmental Satellites (NPOES) yielding 40 years of continuous data. Since 2014 the Ozone Mapper Profiler Suite (OMPS) on Suomi National Polarorbiting Partnership (S-NPP) and recently the Joint Polar Satellite System (JPSS) augment the SBUV series. The SBUV Coherent dataset (SBUV COH) homogenizes data from these instruments to create a trend quality zonal mean dataset. This proposed project will integrate SBUV/OMPS satellite and NOAA’s GB data to ascertain how limited geospatial sampling can impact the accuracy of trends derived from the GB records. We will select satellite ozone observations over the GB stations, both by closest geographical proximity and by dynamical matching using equivalent latitude. To interpret trends and stratospheric ozone variability we will use dynamical and chemical tracers from the NASA Global Model Initiative (GMI) chemistry transport model (CTM). The model uses interactive chemistry and transport, driven by re-analyses data (MERRA2) to simulate hourly ozone fields since 1979. GMI simulations and SBUV overpass records will be used to study the effects of limited sampling in ground-based observational records that may be an issue for trend analyses. The stated goal of this funding opportunity is “explain various trends, patterns and extremes detectable in the existing long-term observational records”, in support of NOAA’s long-term research goal to “provide essential environmental information vital to our Nation’s safety, prosperity and resilience”. This study supports both, by deriving trends from the GB stations and satellite records, while investigating causes for the differences related to sampling limitations, to the representativeness of equivalent latitudes and to stability of the records. The outcome of this study will provide ozone recovery rates over the globe, will provide recommendations for improving network coverage and modeling products that can be used directly by policy makers and other stakeholders, and will improve attribution of ozone regional variability to the global circulation processes through the use of the explanatory parameters derived from the NASA CTM simulations of ozone profiles at the location of ground-based stations.Dr. Jeannette D. Wild (University of Maryland)
2019Ross J. Salawitch (University of Maryland)Quantification of the Uptake of Anthropogenic Emissions of Atmospheric CO2Long Term Trends in Observations of Atmospheric Composition There is concerted interest within the climate modeling community to define carbon emission pathways consistent with either 1.5°C warming (goal of the Paris Climate Agreement) or 2°C warming (upper limit of the Paris Agreement). Many Earth System Models (ESMs) and some prior data analyses suggest the airborne fraction of CO2 (AF) defined as the annual rise in global mean CO2 (CO2GM) divided by the sum of total anthropogenic fossil fuel, cement, and land use change emissions, has been rising over time. If so, this means feedbacks between the global carbon cycle and climate change are resulting in atmospheric residence of a greater fraction of human emission of CO2. Under this scenario, the limit on the cumulative human emissions of CO2 needed to limit warming to either 1.5°C or 2°C (relative to pre-industrial) would need to be revised downwards, relative to a model that neglects feedbacks between the global carbon cycle and climate change. We propose two types of analyses to quantify the temporal trend in AF. In year 1, we will use a multiple linear regression of CO2 growth rate as a function of anthropogenic emissions, an ENSO index, and stratospheric optical depth (SOD) to account for the effect of ENSO and volcanoes on the growth of CO2, then quantify the trend in AF based upon a time series of CO2 that has been adjusted for these two natural influences. In year 2, we propose to conduct an analysis of time series of CO2GM and the O2/N2 ratio to define changes in ocean and land uptake of atmospheric CO2. The statistical significance of the various trends will be assessed via a Monte- Carlo analysis that accounts for the uncertainties of all of the terms that enter into the analyses. The rationale of this proposed effort is that some of the prior, highly-cited studies that have quantified the trend in AF fail to adjust the data record for the influence of ENSO or volcanoes. Other studies adjust the record, albeit in a simplistic fashion, but do not provide a robust statistical analysis of the resulting trends. We have read the existing literature with great care and propose below an effort that applies a novel approach for quantitatively accounting for the effect of ENSO and volcanoes on the growth rate of atmospheric CO2, together with a state-ofthe- art statistical approach for assessing significance of the resulting trend in AF. We also propose to use measurements of the O2/N2 ratio to quantify the temporal evolution of the land and ocean sink. Our study is designed to provide clarity on how the airborne fraction of CO2 is changing, a critically important constraint for ESMs being used to guide global warming policy decisions. 1.3 Competition and Relevance AC4 aims to provide understanding of processes that govern the atmospheric abundance of trace gases. The FY2019 call states “The most relevant proposals will be those making most use of network data and demonstrating the intrinsic value of long-term monitoring.” Our proposal makes use of NOAA records of CO2 (global, Mauna Loa, and South Pole), the annual growth rate for CO2, indices for ENSO, as well as the rise in ocean heat content, combined with record for stratospheric optical depth that relies on NASA satellite observations, estimates of fossil fuel, cement, and land use emission of CO2 records that NOAA has helped provide, and the O2/N2 record from many NOAA stations that is provided by colleagues at Scripps Institution of Oceanography. This proposal seems ideally aligned to the FY2019 AC4 competition. 
2019Yuxuan Wang (University of Houston)A Holistic and Long-term Analysis of Atmospheric Composition Changes During Droughts in the Continental U.S.Long Term Trends in Observations of Atmospheric Composition Drought is a recurring extreme phenomenon in the climate system. Unlike most other natural hazards, droughts are a slowly developed process with timescales of a month or longer, for which our predictability ability is of critical importance toward seamless weather/climate modeling. Drought is also a complex extreme involving not only atmospheric changes but also perturbations to the land and biosphere conditions. Given these two features, drought is expected to bring significant changes in the abundance of both gaseous and aerosol species in the atmosphere, but few studies to date have investigated the nature and extent of such changes. This knowledge gap impedes our ability to predict air quality change in a warming climate that is widely projected to have more intense swings between droughts and floods. To fill this gap toward an improved understanding of drought impact on atmospheric composition, the proposed project will exploit the long-term comprehensive observations to conduct holistic analysis and derive quantitative characterization of the change of atmospheric aerosols and trace gases during the drought, and with that characterization and analysis, develop processed-based observational metrics to evaluate coupled chemistry-climate models. The scientific objectives of the proposed project are to: 1) Characterize the spatial and temporal anomaly of a variety of chemical species measured by the long-term networks associated with contemporary droughts (from the 1990s to the present) in the continental US, including co-variation of the anomalies among different species; 2) Develop observation-based hypotheses and process-level metrics from the synthesis of the multi-species changes associated with droughts; 3) Evaluate coupled chemistry-climate models using the process-level metrics as the benchmark and the observation-based hypothesis as the initial null hypothesis. To achieve the objectives, the proposed project will focus on the processes that can be more directly linked to the existing long-term observations and hence better constrained by these observations. The processes to be investigated include wet deposition, dust emissions, fire emissions, BVOC emissions, and surface radiation, and a three-step approach will be adopted. First, long-term surface observations will be analyzed to characterize the changes between drought and non-drought periods in wet deposition, surface radiation, PM10, PM2.5, O3, isoprene, and different aerosol components. Second, the observation-derived anomalies will be contrasted with modeled anomalies to develop process-level metrics to link with the aforementioned processes. Finally, an integrated comparison and contrast analysis will be conducted with advanced statistical techniques to study the impact of droughts on the analysis of atmospheric composition trend. The working hypothesis is that the abundance and covariation of different atmospheric species can be significantly altered during drought, and hence, analyzing the cross-associations of these anomalies and co-variations with drought characteristics (such as phase and severity) from long-term observations can provide a holistic constraint for process diagnosis and evaluation of chemistry-climate models for drought events. The proposed work is highly relevant to the solicitation that encourages exploration of factors influencing the gradient of the long-term trends of atmospheric composition, as well as patterns, anomalies, and extremes in the long-term trends.Jun Wang (University of Iowa)
2019Dr. Glenn M. Wolfe (UMBC)Mapping the Global Variability of Tropospheric Oxidizing CapacityLong Term Trends in Observations of Atmospheric Composition The hydroxyl radical, OH, controls the lifetime of methane (CH4), ozone-depleting substances, and numerous other gases relevant to climate and air quality. Current global OH constraints rely on budget closure of long-lived gases such as methyl chloroform (MCF). Though powerful, these methods are sensitive to uncertainties in emissions and provide limited spatiotemporal information. Furthermore, budget closure is becoming less viable as the abundance of MCF and similar compounds declines. There is a clear need for new constraints on OH, especially those that can bridge the scale-gap between globally-integrated and process-level information. Reducing systematic bias in OH is crucial for understanding long-term trends of CH4 and other gases, simulating tropospheric O3 production, and projecting future atmospheric composition. We will develop new constraints on the spatial and temporal variability of near-global tropospheric OH concentrations ([OH]) and production rates (POH). The foundation of this work is the strong steady-state relationship between OH and formaldehyde (HCHO). Recently, our group has synthesized observations from the Atmospheric Tomography (ATom) mission with OMI HCHO column retrievals to estimate tropospheric column [OH] over the remote troposphere. We will extend these products across the full OMI satellite record to elucidate the spatial and temporal variability of global remote OH. This research entails three linked objectives: Evaluation of HCHO retrievals in remote environments. We will inter-compare and validate multiple HCHO retrievals with a specific focus on remote ocean regions. Our goal is to identify and minimize systematic biases and robustly characterize uncertainties, thereby increasing confidence in satellite HCHO observations in remote environments. Refinement of HCHO scaling factors. We will utilize multiscale model analyses to quantify drivers of the relationship between HCHO and oxidizing capacity, focusing on the influence of variability in CO, reactive VOC, and NOx. Furthermore, we will develop a method to constrain these dependencies with additional satellite observations. This effort will improve the spatial and temporal representativeness of [OH] and POH estimates. Interpretation of a long-term OH dataset. We will produce robust near-global estimates of monthly, gridded tropospheric column [OH] and POH across the OMI record (Oct. 2004 – present). Datasets will be validated against MCF-based global estimates and ATom observations. We will use this data to explore regional drivers of intra- and inter-annual variability in oxidizing capacity, focusing on anthropogenic and natural (e.g. lightning) perturbations. We will also make this dataset available to the community for further analyses and global model evaluation. The NOAA AC4 FY19 solicitation specifically notes a focus on “large-scale atmospheric processes that control trace gas removal rates,” and our work is directly relevant to this topic across multiple scales. Constraining global OH is crucial, for example, for understanding long-term CH4 trends. This work is complementary to ongoing efforts within NOAA’s GMD and ties in with NOAA’s long-term climate research goals, specifically the development of “climate intelligence” with regard to changing atmospheric composition and its impacts.Dr. Julie Nicely (University of Maryland)
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Dr. Monika Kopacz (UCAR)
Program manager, Atmospheric Chemistry, Carbon Cycle and Climate (AC4)
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