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At least 523 records · Page 29

New Directions: GEIA’s 2020 Vision for Better Air Emissions Information

We are witnessing a crucial change in how we quantify and understand emissions of greenhouse gases and air pollutants, with an increasing demand for science-based transparent emissions information produced by robust community efforts. Today’s scientific capabilities, with near-real-time in-situ and remote sensing observations combined with forward and inverse models and a better understanding of the controlling processes, are contributing to this transformation and providing new approaches to derive, verify, and forecast emissions (Tong et al., 2011; Frost et al., 2012) and to quantify their impacts on the environment (e.g., Bond et al., 2013). At the same time, the needs for emissions information and the demands for their accuracy and consistency have grown. Changing economies, demographics, agricultural practices, and energy sources, along with mandates to evaluate emissions mitigation efforts, demonstrate compliance with legislation, and verify treaties, are leading to new challenges in emissions understanding. To quote NOAA Senior Technical Scientist David Fahey, "We are in the Century of Accountability. Emissions information is critical not only for environmental science and decision-making, but also as an instrument of foreign policy and international diplomacy." Emissions quantification represents a key step in explaining observed variability and trends in atmospheric composition and in attributing these observed changes to their causes. Accurate emissions data are necessary to identify feasible controls that reduce adverse impacts associated with air quality and climate and to track the success of implemented policies. To progress further, the international community must improve the understanding of drivers and contributing factors to emissions, and it must strengthen connections among and within different scientific disciplines that characterize our environment and entities that protect the environment and influence further emissions. The Global Emissions InitiAtive, GEIA (http://www.geiacenter.org/), is a center for emissions information exchange and competence building created in 1990 in response to the need for high quality global emissions data (Graedel et al., 1993). While the past two decades have seen considerable progress in developing, improving and assessing emission estimates, emissions continue to be a major contributor to overall uncertainty in atmospheric model simulations. Moving forward, GEIA aims to help build emissions knowledge in a rapidly evolving society by: 1) enhancing understanding, quantification, and analysis of emissions processes; 2) improving access to emissions information; and 3) strengthening the community of emissions groups involved in research, assessment, operations, regulation and policy.

Frost, G. J.↗

Arctic Cloud‐Base Ice Precipitation Properties Retrieved Using Bayesian Inference

Abstract Cloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented.

54 ENVIRONMENTAL SCIENCES↗

Absorbing Aerosols Workshop, January 20-21, 2016

A workshop was held at DOE Headquarters on January 20-21, 2016 during which experts within and outside DOE were brought together to identify knowledge gaps in modeling and measurement of the contribution of absorbing aerosols (AA) to radiative forcing. Absorbing aerosols refer to those aerosols that absorb light, whereby they both reduce the amount of sunlight reaching the surface (direct effect) and heat their surroundings. By doing so, they modify the vertical distribution of heat in the atmosphere and affect atmospheric thermodynamics and stability, possibly hastening cloud drop evaporation, and thereby affecting cloud amount, formation, dissipation and, ultimately, precipitation. Deposition of AA on snow and ice reduces surface albedo leading to accelerated melt. The most abundant AA type is black carbon (BC), which results from combustion of fossil fuel and biofuel. The other key AA types are brown carbon (BrC), which also results from combustion of fossil fuel and biofuel, and dust (crustal material). Each of these sources may result from, and be strongly influenced by, anthropogenic activities. The properties and amounts of AA depend upon various factors, primarily fuel source and burn conditions (e.g., internal combustion engine, flaming or smoldering wildfire), vegetation type (in the case of BC and BrC), and in the case of dust, soil type and ground cover (i.e., vegetation, snow, etc.). After emission, AA undergo chemical processing in the atmosphere that affects their physical and chemical properties. Thus, attribution of sources of AA, and understanding processes AA undergo during their atmospheric lifetimes, are necessary to understand how they will behave in a changing climate.

54 ENVIRONMENTAL SCIENCES↗

Monitoring 2009 Forest Disturbance Across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

This case study shows the promise of computing current season forest disturbance detection products at regional to CONUS scales. Use of the eMODIS expedited product enabled a NRT CONUS forest disturbance detection product, a requirement for an eventual, operational forest threat EWS. The 2009 classification product from this study can be used to quantify the areal extent of forest disturbance across CONUS, although a quantitative accuracy assessment still needs to be completed. However, the results would not include disturbances that occurred after July 27, such as the Station Fire. While not shown here, the project also produced maximum NDVI products for the June 10-July 27 period of each year of the 2000-2009 time frame. These products could be applied to compute forest change products on an annual basis. GIS could then be used to assess disturbance persistence. Such follow-on work could lead to attribution of year in which a disturbance occurred. These products (e.g., Figures 6 and 7) may also be useful for assessing forest change associated with climate change, such as carbon losses from bark beetle-induced forest mortality in the Western United States. Other MODIS phenological products are being assessed for aiding forest monitoring needs of the EWS, including cumulative NDVI products (Figure 10).

Spruce, J.↗

The Vertical Distribution of Thin Features Over the Arctic Analysed from CALIPSO Observations: Optically Thin Clouds - Part 1

Clouds play a crucial role in the Arctic climate system. Therefore, it is essential to accurately and reliably quantify and understand cloud properties over the Arctic. It is also important to monitor and attribute changes in Arctic clouds. Here, we exploit the capability of the CALIPSO-CALIOP instrument and provide comprehensive statistics of tropospheric thin clouds, otherwise extremely difficult to monitor from passive satellite sensors.We use 4 yr of data (June 2006.May 2010) over the circumpolar Arctic, here defined as 67-82 deg. N, and characterize probability density functions of cloud base and top heights, geometrical thickness and zonal distribution of such cloud layers, separately for water and ice phases, and discuss seasonal variability of these properties. When computed for the entire study area, probability density functions of cloud base and top heights and geometrical thickness peak at 200-400, 1000-2000 and 400-800 m, respectively, for thin water clouds, while for ice clouds they peak at 6-8, 7-9 and 400-1000 m, respectively. In general, liquid clouds were often identified below 2 km during all seasons, whereas ice clouds were sensed throughout the majority of the upper troposphere and also, but to a smaller extent, below 2 km for all seasons.

DeVasthale, Abhay↗

How Do UTLS Jet and Tropopause Dynamics Influence Ozone Variability? Investigations Supporting the SPARC OCTAV-UTLS Activity

Understanding changes in UTLS ozone is exceptionally challenging because of large spatial and temporal variability and because of the difficulty of satellite measurements in the UTLS. It is also exceptionally important: for example, to understand climate impacts of radiatively active substances and to understand physical and biological effects of pollution transport and stratosphere-troposphere exchange (STE). Multi-decadal global observations of UTLS ozone are now available from numerous satellite platforms, as well as local and regional observations from aircraft, balloons, and lidar. The upper tropospheric (UT) jets and tropopauses are important drivers of composition variability in the UTLS, acting as transport barriers and controlling STE and long-range transport. We report here on investigations of relationships between extratropical UTLS ozone variability and dynamical diagnostics of mixing / transport barriers, Rossby Wave breaking, and stratosphere-troposphere exchange. We will view these relationships in the context of ozone mapped into dynamical coordinates with respect to the UTLS jets and / or the tropopause. This work will help provide direction for analyses within the Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity, which aims to use dynamical coordinate mapping to help detect and attribute observed UTLS composition trends, and to project future data needs to better quantify those trends. The work we report on here will focus on satellite ozone observations (primarily from the Aura Microwave Limb Sounder, additionally from ACE-FTS and OSIRIS) and assimilated ozone and dynamical fields (from multiple reanalyses); we will also provide some examples of comparisons with aircraft and balloon observations.

Manney, Gloria L.↗

Trend Analysis and Detection of Changes in the Stratospheric Circulation

Increases in the circulation of the stratosphere appear to be a robust result of climate change in chemistry-climate models over decadal time scales. To date observations have yet to show a significant change in this circulation. It is important for the design of future observational missions to identify suitable atmospheric constituents and to determine the accuracy and length of record needed to identify a significant trend that can be attributed to circulation change. First, we determine what atmospheric variables can be used as proxies for stratospheric circulation changes. A few examples are changes in tropical lower stratospheric ozone, phase lag of the water vapor tape recorder, CO2, and SF6. Then, using both the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) and observations from satellites and balloon soundings, we calculate the number of years needed to detect a significant trend, taking into account observational uncertainty. Model simulations will be evaluated to see how well they represent observed variability. In addition, the impacts of autocorrelation among the output or data and gaps in the observational record will be discussed.

Oman, Luke↗

Simulation of the modern arctic climate by the NCAR CCM1

The National Center of Atmospheric Research (NCAR) Community Climate Model Version 1 (CCM1's) simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much storm activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenland topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial circum-Greenland trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the model simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. The moisture budget analysis shows that the model's net annual precipitation (P-E) between 70 deg N and the North Pole is 6.6 times larger than the observations and the model transports six times more moisture into this region. The bias in the advection term is attributed to the positive moisture fixer scheme and the distorted flow pattern. However, the excessive moisture transport into the Arctic basin does not solely result from the advection term. The contribution by the moisture fixer is as large as from advection. By contrast, the semi-Lagrangian transport scheme used in the CCM2 significantly improves the moisture simulation for this region; however, globally the error is as serious as for the positive moisture fixer scheme. Finally, because the model has such serious problems in simulating the present arctic climate, its simulations of past and future climate change for this region are questionable.

Bromwich, David H.↗

Joint effects of climate, tree size, and year on annual tree growth derived from tree–ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

generalized least squares (GLS)↗

Investigating Stable Oxygen and Carbon Isotopic Variability in Speleothem Records Over the Last Millennium Using Multiple Isotope-Enabled Climate Models

The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISS-E2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

isotope-enabled simulations↗

TPSAS-NF1676L-11382-DND

Long-range transport of ozone precursor species and carbonaceous aerosols emitted by wildfires may affect the atmospheric composition and regional climate far away from the location of the fires. Major outbreaks of fires occurred in 3 areas of Asia, Kazakhstan, Siberia, and Thailand, during the spring of 2008. Satellite and aircraft-based observations and trajectory studies have identified the transit of the plumes from these fires across the Pacific. We have conducted simulations of the effects of these fires on the atmospheric composition using the Real-time Air Quality Modeling System (RAQMS). RAQMS is a global scale meteorological and chemical modeling system with unified (stratosphere/troposphere) chemistry module. Model results, for example, indicate that increases of 10 ppbv in upper tropospheric ozone at 180W longitude and northern mid-latitudes in April, 2008 could be attributed to these fires. Large increases in aerosol optical depth due to carbonaceous aerosols are also seen nearer the fire location. Both tropospheric ozone and carbonaceous aerosols influence the atmospheric energy balance and climate. We use an off-line radiative transfer model along with the RAQMS chemical and aerosol analyses to calculate the direct radiative forcing during April, 2008, due to Asian wildfire emissions. Arctic indirect radiative forcing due to these emissions are evaluated using RAQMS aerosol extinction analyses in conjunction with MODIS retrievals of cloud liquid water and effective radius. We will discuss the radiative forcing results and the relative influences of the different fire events.

Murali Natarajan↗

Impact of Emissions and Long-Range Transport on Multi-Decadal Aerosol Trends: Implications for Air Quality and Climate

We present a global model analysis of the impact of long-range transport and anthropogenic emissions on the aerosol trends in the major pollution regions in the northern hemisphere and in the Arctic in the past three decades. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to analyze the multi-spatial and temporal scale data, including observations from Terra, Aqua, and CALIPSO satellites and from the long-term surface monitoring stations. We will analyze the source attribution (SA) and source-receptor (SR) relationships in North America, Europe, East Asia, South Asia, and the Arctic at the surface and free troposphere and establish the quantitative linkages between emissions from different source regions. We will discuss the implications for regional air quality and climate change.

Chin, Mian↗

Attributing land-use change carbon emissions to exported biomass

In this study, a simple, transparent and robust method is developed in which land-use change (LUC) emissions are retrospectively attributed to exported biomass products based on the agricultural area occupied for the production. LUC emissions account for approximately one-fifth of current greenhouse gas emissions. Increasing agricultural exports are becoming an important driver of deforestation. Brazil and Indonesia are used as case studies due to their significant deforestation in recent years. According to our study, in 2007, approximately 32% and 15% of the total agricultural land harvested and LUC emissions in Brazil and Indonesia respectively were due to exports. The most important exported single items with regard to deforestation were palm oil for Indonesia and bovine meat for Brazil. To reduce greenhouse gas (GHG) emissions effectively worldwide, leakage of emissions should be avoided. This can be done, for example, by attributing embodied LUC emissions to exported biomass products. With the approach developed in this study, controversial attribution between direct and indirect LUC and amortization of emissions over the product life cycle can be overcome, as the method operates on an average basis and annual level. The approach could be considered in the context of the UNFCCC climate policy instead of, or alongside with, other instruments aimed at reducing deforestation. However, the quality of the data should be improved and some methodological issues, such as the allocation procedure in multiproduct systems and the possible dilution effect through third parties not committed to emission reduction targets, should be considered. - Highlights: Black-Right-Pointing-Pointer CO{sub 2} emissions from land use changes are highly important. Black-Right-Pointing-Pointer Attribution of land use changes for products is difficult. Black-Right-Pointing-Pointer Simple and robust method is developed to attribute land use change emissions.

54 ENVIRONMENTAL SCIENCES↗

Phenolic compounds and black carbon feedback controls on peat decomposition and carbon accumulation in southeastern peatlands under regimes of seasonal drought, drainage and frequent fire

Peatlands store one-third of soil C in terrestrial ecosystems and have persisted through changing climate over millennia from the arctic to the tropics. Approximately one-third of peat stores are found in subtropical and tropical peatlands (STPs) formed from high-lignin woody biomass. In this project, our questions are: 1) why do these non-sphagnum peatlands (STPs) accumulate C under warmer-drier climates and 2) how might insights coming from studying control mechanisms in STPs improve the management and conservation of the vast C stores in boreal peatlands subject to increasing climate forcing. We hypothesized that a dual control or “latch mechanism” reduces decomposition in shrub/tree communities in STPs due to both (1) higher production of polyphenol and aromatic compounds in STPs than found in northern Sphagnum/Carex communities and (2) the buildup of recalcitrant organic matter produced by light fire-drought-warming-adapted communities, together leading to a reduction in the microbial decay rate of peat. After three-years of intensive biological and chemical analysis in a series of field and microcosm experiments along our north to south bog gradient from Minnesota to Peru, we show how previously unrecognized biotic factors, particularly dynamic interlinked above- and belowground attributes control C sequestration in peatlands. Our key findings include (1) phenolics-bridged plant-microbe symbioses, principally slow-growing microbes dominated in higher phenolic wooded STPs, preserving C in peatlands under climate change, 2) phenolics are the overarching factor controlling the relative abundance of slow-and fast-growing microbes, the slow-growing microbes in STPs metabolize C slowly and are inherently resistant to disturbance, 3) global data analysis shows that soil respiration does not increase exponentially from boreal to tropical peatlands, suggesting that slow-growing microbes may have become dominant in most non-boreal peatlands, 4) peat chemistry analysis from over 2000 samples show that across peatlands both from the arctic to tropics and from high to low elevation peatlands recalcitrance increases as aromatic content increases, and 5) peat affected by low-severity wildfires displays a similar pattern of higher aromatic content. Our findings all demonstrate links between peat recalcitrance and increased content of phenolics and other aromatic compounds in plants. Thus, linked plant–microbe symbiotic traits are a key to understanding ecological resilience and resistance developed in peatlands under disturbance. New trait-based approaches that can better link above-and below ground processes are needed to advance both the accuracy and precision of current abiotic-factor-based Earth system models in predicting future soil C responses to climate-change feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Characterization of Climate Change and Variability with GPS

We compared zonal mean specific humidity derived from the 21 June-4 July 1995 Global Positioning System (GPS)/MET occultation observations with that derived from the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The GPS/MET results indicate a drier troposphere, especially near the subtropical tradewind inversion. A small, moist bias in the GPS/MET upper northern-hemisphere troposphere compared to ECMWF may be due to a small radiosonde temperature bias. A diagram shows the difference (g/kg) between the GPS/MET zonal mean specific humidity and that for June-August derived from 1963-1973 radiosondes. Although the observing period is short, GPS and ECMWF results both indicate a significantly wetter boundary layer at most latitudes consistent with decadal trends observed in radiosonde data. GPS/MET results exhibit higher tropical convective available potential energy (CAPE), suggesting a more vigorous tropical Hadley circulation. Drier, free troposphere air in the descending branches of the Hadley circulation is due in part to a moist radiosonde bias but may also reflect some negative moisture feedback. Using 1992-1997 ground GPS observations and recent advancements in GPS technology, we removed an apparent altimetric drift (-1.2 +/- 0.4 mm/yr) due to columnar water vapor from the Topography (Ocean) Experiment (TOPEX) microwave radiometer, which brought the TOPEX mean sea level change estimates into better agreement with historical tide gauge records, suggesting global mean sea level is rising at a rate of 1.5-2.0 mm/yr. We can also discern a statistically significant increase of 0.2 +/- 0.1 kg/square m/yr in mean columnar water vapor over the ocean from 1992-1997. Optimal fingerprinting can be used for the detection and attribution of tropospheric warming due to an anthropogenic greenhouse. Optimal fingerprinting distinguishes between different types of signals according to their spatial and temporal patterns, while minimizing the influence of natural climate variability. S. Leroy concludes that the signal-to-noise ratio of global warming detection increases by unity approximately every 10 years if a single oceanic region is chosen. Less time for detection is likely when many global regions are considered simultaneously. GPS occultation constellations allow the possibility of detecting small changes in upper air temperature with inconsequential calibration errors, making occultation an ideal data type for global warming detection studies. Our initial study of a 22-GHz satellite-satellite occultation system predicts upper troposphere moisture sensitivities of 3-5 ppmv and 1-2 percent in the middle and lower troposphere. Additional information contained in original.

Kursinski, R.↗

A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties

This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric CO 2 Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar-Induced Chlorophyll Fluorescence

Recent studies have shown the promise of remotely sensed solar-induced chlorophyll fluorescence (SIF) in informing terrestrial carbon exchange, but analyses have been limited to either plot level (~1 km 2 ) or hemispheric/global (~108 km 2 ) scales due to the lack of a direct measure of carbon exchange at intermediate scales. Here we use a network of atmospheric CO 2 observations over North America to explore the value of SIF for informing net ecosystem exchange (NEE) at regional scales. We find that SIF explains space-time NEE patterns at regional (~100 km 2 ) scales better than a variety of other vegetation and climate indicators. We further show that incorporating SIF into an atmospheric inversion leads to a spatial redistribution of NEE estimates over North America, with more uptake attributed to agricultural regions and less to needleleaf forests. Our results highlight the synergy of ground-based and spaceborne carbon cycle observations.

54 ENVIRONMENTAL SCIENCES↗

Performance and durability of electrically conductive tape for shingled Si heterojunction technology cells

We report electrically conductive tape (ECT) was characterized and used to assemble shingled cell strings at low temperature to achieve high reliability Pb- and Ag-free interconnections. The volume resistivity for two considered ECTs are 0.13 ± 0.06 mΩ·cm and 0.47 ± 0.20 mΩ·cm and specific contact resistances, 6.85± 2.00 mΩ·cm 2 and 6.30 ± 0.37 mΩ·cm 2 using the emerging IEC 62788-8-1 Technical Specification for assessment of electrically conductive adhesives (ECA). Durability and performance of the technology in glass–glass mini modules were evaluated with temperature cycling, damp heat testing, and combined-accelerated stress testing (CAST). Through temperature cycling (-40°C to 85°C) applying five times the mini module short-circuit current in forward bias and in the multi climate CAST protocol, there was negligible degradation of fill factor after replacing connectors at the modules' cable leads; however, CAST resulted in short circuit current loss attributed to degradation in light collection by the cells, not the ECT. The IEC 61215-2 85°C, 85% relative humidity damp heat testing showed susceptibility of the HJT cells to effects of humidity in the electroluminescence intensity around the module perimeter that degraded power performance by 4% (relative). Contrasting the IEC 61215-2 qualification testing-based damp heat testing with CAST, factors such as the optical stress of CAST may precipitate the degradation of the modules whereas the humidity levels and duration of IEC 61215-2 damp heat testing may lead to excessive levels of humidity diffused into the modules, potentially resulting in degradation that is unrepresentative of the field.

14 SOLAR ENERGY↗