237 results on '"O'Dell, Christopher"'
Search Results
202. Global CO2 distributions over land from the Greenhouse Gases Observing Satellite (GOSAT).
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Hammerling, Dorit M., Michalak, Anna M., O'Dell, Christopher, and Kawa, S. Randolph
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- 2012
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203. Cloud Liquid Water Path from Satellite-Based Passive Microwave Observations: A New Climatology over the Global Oceans.
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O'Dell, Christopher W., Wentz, Frank J., and Bennartz, Ralf
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DIURNAL cloud variations , *CLIMATOLOGY , *MICROWAVE imaging , *GLOBAL Ocean Observing System , *RAINFALL , *PRECIPITATION variability , *METEOROLOGICAL precipitation - Abstract
This work describes a new climatology of cloud liquid water path (LWP), termed the University of Wisconsin (UWisc) climatology, derived from 18 yr of satellite-based passive microwave observations over the global oceans. The climatology is based on a modern retrieval methodology applied consistently to the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer (AMSR) for Earth Observing System (EOS) (AMSR-E) microwave sensors on eight different satellite platforms, beginning in 1988 and continuing through 2005. It goes beyond previously published climatologies by explicitly solving for the diurnal cycle of cloud liquid water by providing statistical error estimates, and includes a detailed discussion of possible systematic errors. A novel methodology for constructing the climatology is used in which a mean monthly diurnal cycle as well as monthly means of the liquid water path are derived simultaneously from the data on a 1° grid; the methodology also produces statistical errors for these quantities, which decrease toward the end of the time record as the number of observations increases. The derived diurnal cycles are consistent with previous findings in the tropics, but are also derived for higher latitudes and contain more information than in previous studies. The new climatology exhibits differences with previous observationally based climatologies and is found to be more consistent with the 40-yr ECMWF Re-Analysis (ERA-40) than are the previous climatologies. Potential systematic errors of the order of 15%–30% or higher exist in the LWP climatology. A previously unexplored source of systematic error is caused by the assumption that all microwave-based retrievals of LWP must make regarding the partitioning of cloud water and rainwater, which cannot be determined using microwave observations alone. The potentially large systematic errors that result may hamper the usefulness of microwave-based climatologies of both cloud liquid water and especially rain rate, particularly in certain regions of the tropics and midlatitudes where the separation of rain from liquid cloud water is most critical. [ABSTRACT FROM AUTHOR]
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- 2008
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204. The Successive-Order-of-Interaction Radiative Transfer Model. Part I: Model Development.
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Heidinger, Andrew K., O'Dell, Christopher, Bennartz, Ralf, and Greenwald, Thomas
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RADIATIVE transfer , *MICROWAVE spectroscopy , *ITERATIVE methods (Mathematics) , *SCATTERING (Physics) , *MONTE Carlo method , *NUMERICAL calculations , *SIMULATION methods & models , *ATMOSPHERIC effects on remote sensing - Abstract
This study, the first part of a two-part series, develops the method of “successive orders of interaction” (SOI) for a computationally efficient and accurate solution for radiative transfer in the microwave spectral region. The SOI method is an iterative approximation to the traditional adding and doubling method for radiative transfer. Results indicate that the approximations made in the SOI method are accurate for atmospheric layers with scattering properties typical of those in the infrared and microwave regions. In addition, an acceleration technique is demonstrated that extends the applicability of the SOI approach to atmospheres with greater amounts of scattering. A comparison of the SOI model with a full Monte Carlo model using the atmospheric profiles given by Smith et al. was used to determine the optimal parameters for the simulation of microwave top-of-atmosphere radiances. This analysis indicated that a four-stream model with a maximum initial-layer optical thickness of approximately 0.01 was optimal. In the second part of this series, the accuracies of the SOI model and its adjoint are demonstrated over a wide range of microwave remote sensing scenarios. [ABSTRACT FROM AUTHOR]
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- 2006
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205. The Successive-Order-of-Interaction Radiative Transfer Model. Part II: Model Performance and Applications.
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O'Dell, Christopher W., Heidinger, Andrew K., Greenwald, Thomas, Bauer, Peter, and Bennartz, Ralf
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RADIATIVE transfer , *SCATTERING (Physics) , *MICROWAVE imaging , *METEOROLOGICAL precipitation , *WEATHER forecasting , *JACOBIAN matrices - Abstract
Radiative transfer models for scattering atmospheres that are accurate yet computationally efficient are required for many applications, such as data assimilation in numerical weather prediction. The successive-order-of-interaction (SOI) model is shown to satisfy these demands under a wide range of conditions. In particular, the model has an accuracy typically much better than 1 K for most microwave and submillimeter cases in precipitating atmospheres. Its speed is found to be comparable to or faster than the commonly used though less accurate Eddington model. An adjoint has been written for the model, and so Jacobian sensitivities can be quickly calculated. In addition to a conventional error assessment, the correlation between errors in different microwave channels is also characterized. These factors combine to make the SOI model an appealing candidate for many demanding applications, including data assimilation and optimal estimation, from microwave to thermal infrared wavelengths. [ABSTRACT FROM AUTHOR]
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- 2006
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206. Fast Computation of Microwave Radiances for Data Assimilation Using the “Successive Order of Scattering” Method.
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Greenwald, Thomas, Bennartz, Ralf, O'Dell, Christopher, and Heidinger, Andrew
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RADIATIVE transfer ,ASTROPHYSICS ,RADIATION ,WEATHER forecasting ,MICROWAVES ,DETECTORS - Abstract
Fast and accurate radiative transfer (RT) models are crucial in making use of microwave satellite data feasible under all weather conditions in numerical weather prediction (NWP) data assimilation. A multistream “successive order of scattering” (SOS) RT model has been developed to determine its suitability in NWP for computing microwave radiances in precipitating clouds. Results show that the two-stream SOS model is up to 10 times as fast as and is as accurate as the commonly used delta-Eddington model for weaker scattering [column scattering optical depth (CSOD) < 0.01], but it is less accurate and is slower for higher frequencies (>30 GHz) in cases of moderately strong to strong scattering (CSOD > 5). If two- and four-stream SOS models are used in combination, however, it was found that 85.5-GHz brightness temperatures computed for 1° × 1° global forecast fields were more accurate (<0.5 K vs 1.5 K for CSOD > 0.1) and were executed 4 times as fast as the delta-Eddington model. The SOS method has been demonstrated as an alternative to other fast RT models for providing accurate and very rapid multiple-scattering calculations at thermal wavelengths for remote sensing studies and demanding applications such as operational NWP data assimilation. [ABSTRACT FROM AUTHOR]
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- 2005
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207. Toward robust and consistent regional CO2flux estimates from in situ and spaceborne measurements of atmospheric CO2
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Chevallier, Frédéric, Palmer, Paul I., Feng, Liang, Boesch, Hartmut, O'Dell, Christopher W., and Bousquet, Philippe
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We evaluate the robustness and consistency of global and regional posterior CO2flux estimates for 2010 inferred from two versions of bias‐corrected CO2column retrievals from the Japanese Greenhouse Gases Observing Satellite (GOSAT). Six satellite‐based inversions, generated from three atmospheric transport models and two independent Bayesian inference algorithms, facilitate a rigorous investigation of the uncertainty of the inverted fluxes. This ensemble shows hemispheric and regional differences in posterior flux estimates that are beyond 1 sigma uncertainties and in some regions are unrealistic. We recognize the importance of these satellite data in further understanding the contemporary carbon cycle but we argue that more resources should be invested in characterizing the errors of the prior fluxes, the systematic errors of the retrievals, and the systematic errors of the transport models, to improve confidence in the resulting posterior fluxes. Nine global CO2atmospheric inversions are comparedThe CO2fluxes inferred from the satellite data show limited realismThe satellite‐inferred fluxes show large sensitivity to all input information
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- 2014
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208. Solar-induced chlorophyll fluorescence from the Geostationary Carbon Cycle Observatory (GeoCarb): An extensive simulation study.
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Somkuti, Peter, O'Dell, Christopher W., Crowell, Sean, Köhler, Philipp, McGarragh, Gregory R., Cronk, Heather Q., and Burgh, Eric B.
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CARBON cycle , *GEOSTATIONARY satellites , *OBSERVATORIES , *CHLOROPHYLL spectra - Abstract
The Geostationary Carbon Cycle Observatory (GeoCarb), to be launched in 2023, will be capable of measuring solar-induced chlorophyll fluorescence (SIF) and add to the current space-based record which started in 1995. GeoCarb will be unique as it will be the first geostationary satellite capable of sensing SIF over the American continents. Consequently, SIF measurements from GeoCarb can be performed much more flexibly compared to polar-orbiting platforms. With its scan mirror assembly, the instrument can point to any location on the Earth disc. This will allow measurements to be collected at various times of day, and measurement locations can be re-visited several times within a day. In expectation of the launch, we conduct an extensive, SIF-focused simulation study and explore the capability and limitations of the instrument and its particular sampling approach. Using cloud information from real measurements, as well as other observation- and model-based data, we produce over four million atmospheric simulations of GeoCarb measurements that the instrument would see throughout a full day. We then apply dedicated SIF retrieval algorithms on the simulated spectra and investigate the results along with cloud-screening performance and emergent retrieval biases and subsequent bias correction. Finally, we make comparisons with currently operating instruments where appropriate and show future science users of GeoCarb SIF what a typical day of measurements will yield. • Solar-induced chlorophyll fluorescence (SIF) from GeoCarb • Simulation study using millions of realistic scenes with clouds and aerosols • Investigation of GeoCarb SIF and comparison with existing instruments [ABSTRACT FROM AUTHOR]
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- 2021
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209. Publisher Correction: Large Chinese land carbon sink estimated from atmospheric carbon dioxide data.
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Wang, Jing, Feng, Liang, Palmer, Paul I., Liu, Yi, Fang, Shuangxi, Bösch, Hartmut, O'Dell, Christopher W., Tang, Xiaoping, Yang, Dongxu, Liu, Lixin, and Xia, ChaoZong
- Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]
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- 2020
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210. A global perspective on CO2 satellite observations in high AOD conditions.
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Virtanen, Timo H., Sundström, Anu-Maija, Suhonen, Elli, Lipponen, Antti, Arola, Antti, O'Dell, Christopher, Nelson, Robert R., and Lindqvist, Hannakaisa
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ATMOSPHERIC aerosols , *SOLAR radiation , *AEROSOLS , *CARBON dioxide , *CITIES & towns , *ATMOSPHERIC acoustics - Abstract
Satellite-based observations of carbon dioxide (CO2) are sensitive to all processes that affect the propagation of radiation in the atmosphere, including scattering and absorption by atmospheric aerosols. Therefore, accurate retrievals of column-averaged CO2 (XCO2) benefit from detailed information on the aerosol conditions. This is particularly relevant for future missions focusing on observing anthropogenic CO2 emissions, such as the Copernicus Anthropogenic CO2 Monitoring mission (CO2M). To fully prepare for CO2M observations, it is informative to investigate existing observations in addition to other approaches. Our focus here is on observations from the NASA Orbiting Carbon Observatory -2 (OCO-2) mission. In the operational full-physics XCO2 retrieval used to generate OCO-2 level 2 products, the aerosol properties are known to have high uncertainty but their main objective is to facilitate CO2 retrievals. We evaluate the OCO-2 product from the point of view of aerosols by comparing the OCO-2 retrieved aerosol properties to collocated Moderate Resolution Imaging Spectro-radiometer (MODIS) Aqua Dark Target aerosol products. We find that there is a systematic difference between the aerosol optical depth (AOD, τ) values retrieved by the two instruments, such that τOCO−2 ∼ 0.4τMODIS. We also find a dependence of the XCO2 on the AOD difference, indicating an aerosol-induced effect in the XCO2 retrieval. In addition, we find a weak but statistically significant correlation between MODIS AOD and XCO2, which can be partly explained by natural covariance and co-emission of aerosols and CO2 but is partly masked by the aerosol-induced XCO2 bias. Furthermore, we find that issues in the OCO-2 aerosol retrieval may lead to misclassification of the quality flag for a small fraction of OCO-2 retrievals. Based on MODIS data, 4.1 % of low AOD cases are incorrectly classified as high AOD (low quality) pixels, while 16.5 % of high AOD cases are erroneously classified as low AOD (high quality) pixels. Finally, we investigate the effect of an AOD threshold on the fraction of acceptable XCO2 data. We find that relaxing the MODIS AOD threshold from 0.2 to 0.5 (at 550 nm), which is the goal for the CO2M, increases the fraction of acceptable data by 14 percentage points globally, and by 31 percentage points for urban areas. [ABSTRACT FROM AUTHOR]
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- 2024
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211. Carbon Dioxide Emissions During the 2018 Kilauea Volcano Eruption Estimated Using OCO‐2 Satellite Retrievals
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Johnson, Matthew S., Schwandner, Florian M., Potter, Christopher S., Nguyen, Hai M., Bell, Emily, Nelson, Robert R., Philip, Sajeev, and O'Dell, Christopher W.
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This study applies Orbiting Carbon Observatory‐2 (OCO‐2) column‐averaged dry‐air mole fractions of CO2(XCO2) to constrain CO2fluxes during the 2018 Kilauea volcano eruption. CO2enhancements (ΔXCO2) of 1–2 parts per million were observed far downwind of the eruption coincident with elevated sulfur dioxide (SO2) concentrations. The estimated CO2emission rate was 77.1 ± 49.6 kilotons per day (kt day−1) on 11 July 2018 with most of the uncertainty from modeled winds and XCO2retrievals. This emission rate is higher compared to flux estimates made with ground‐based measurements (30–40 kt day−1). However, cross‐sectional flux estimates made using OCO‐2 XCO2observations will inherently be larger than ground‐based measurements near the source as these estimates comprise all sources of CO2in the vicinity of the eruption (e.g., vegetation and soil burning). This study for the first time uses satellite XCO2data ~200 km downwind to estimate CO2emissions from a major volcanic eruption. Carbon dioxide (CO2) is a greenhouse gas that plays a predominant role in climate change. Volcanoes emit CO2and play a role in the global carbon cycle; however, the amount of CO2they emit is highly uncertain. One of the main reasons for this uncertainty is the limited amount of volcanic emission measurements available to estimate these CO2emissions. Satellites retrieving CO2have an advantage over ground‐based measurements as they have the potential to obtain data over the entire globe. After the launch of National Aeronautics and Space Administration (NASA)'s Orbiting Carbon Observatory‐2 (OCO‐2) satellite in 2014, spaceborne observations of volcanic CO2were possible. This study uses OCO‐2 measurements of CO2to estimate emissions during the 2018 Kilauea volcano eruption and is the first to trace satellite CO2data downwind from the source of a major volcanic eruption. Here we show that the Kilauea volcano eruption emitted large amounts of CO2and OCO‐2 proved capable to observe the large atmospheric concentrations associated with these emissions. Orbiting Carbon Observatory‐2 retrievals were applied to estimate CO2emissions during the 2018 Kilauea volcano eruptionA CO2emission rate of 77.1 ± 49.6 kt day−1was estimated from volcanic and other emission sources on 11 July 2018This study is the first attempt to use satellite retrieved CO2data far downwind of a major volcanic eruption to estimate emissions
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- 2020
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212. Local Anomalies in the Column‐Averaged Dry Air Mole Fractions of Carbon Dioxide Across the Globe During the First Months of the Coronavirus Recession
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Chevallier, Frédéric, Zheng, Bo, Broquet, Grégoire, Ciais, Philippe, Liu, Zhu, Davis, Steven J., Deng, Zhu, Wang, Yilong, Bréon, François‐Marie, and O'Dell, Christopher W.
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We use a global transport model and satellite retrievals of the carbon dioxide (CO2) column average to explore the impact of CO2emissions reductions that occurred during the economic downturn at the start of the Covid‐19 pandemic. The changes in the column averages are substantial in a few places of the model global grid, but the induced gradients are most often less than the random errors of the retrievals. The current necessity to restrict the quality‐assured column retrievals to almost cloud‐free areas appears to be a major obstacle in identifying changes in CO2emissions. Indeed, large changes have occurred in the presence of clouds, and in places that were cloud free in 2020, the comparison with previous years is hampered by different cloud conditions during these years. We therefore recommend to favor all‐weather CO2monitoring systems, at least in situ, to support international efforts to reduce emissions. The first half of 2020 represents an extreme period for the global carbon cycle with both exceptionally low carbon dioxide emissions from the use of fossil fuels and exceptionally high temperatures around the world. Here, we study the changes in human emissions witnessed from space by NASA's second Orbiting Carbon Observatory (OCO‐2) from February to May 2020. We then reassess user needs for future carbon‐dioxide observing systems that will monitor human emissions. Covid‐19 impacted the CO2column mostly in the vicinity of a few emission locations that changed over timeThese places have not been well observed by the OCO‐2 satellite because of frequent or persistent cloud conditionsTo support the Paris Agreement on climate, priority should be given on the development of all‐weather carbon‐monitoring systems
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- 2020
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213. Assessing the feasibility of using a neural network to filter Orbiting Carbon Observatory 2 (OCO-2) retrievals at northern high latitudes.
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Mendonca, Joseph, Nassar, Ray, O'Dell, Christopher W., Kivi, Rigel, Morino, Isamu, Notholt, Justus, Petri, Christof, Strong, Kimberly, and Wunch, Debra
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QUALITY control standards , *DATA quality , *OBSERVATORIES , *CARBON , *QUALITY control - Abstract
Satellite retrievals of XCO2 at northern high latitudes currently have sparser coverage and lower data quality than most other regions of the world. We use a neural network (NN) to filter Orbiting Carbon Observatory 2 (OCO-2) B10 bias-corrected XCO2 retrievals and compare the quality of the filtered data to the quality of the data filtered with the standard B10 quality control filter. To assess the performance of the NN filter, we use Total Carbon Column Observing Network (TCCON) data at selected northern high latitude sites as a truth proxy. We found that the NN filter decreases the overall bias by 0.25 ppm (∼ 50 %), improves the precision by 0.18 ppm (∼ 12 %), and increases the throughput by 16 % at these sites when compared to the standard B10 quality control filter. Most of the increased throughput was due to an increase in throughput during the spring, fall, and winter seasons. There was a decrease in throughput during the summer, but as a result the bias and precision were improved during the summer months. The main drawback of using the NN filter is that it lets through fewer retrievals at the highest-latitude Arctic TCCON sites compared to the B10 quality control filter, but the lower throughput improves the bias and precision. [ABSTRACT FROM AUTHOR]
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- 2021
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214. Regional impacts of COVID-19 on carbon dioxide detected worldwide from space.
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Weir, Brad, Crisp, David, O'Dell, Christopher W., Basu, Sourish, Chatterjee, Abhishek, Kolassa, Jana, Tomohiro Oda, Pawson, Steven, Poulter, Benjamin, Zhen Zhang, Ciais, Philippe, Davis, Steven J., Zhu Liu, and Ott, Lesley E.
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COVID-19 , *CARBON dioxide , *EARTH system science , *ATMOSPHERIC carbon dioxide , *COVID-19 pandemic , *EMISSION inventories - Abstract
The article focuses on regional impacts of COVID-19 on carbon dioxide detected worldwide from space. Topics include the activity reductions in early 2020 due to the coronavirus disease 2019 pandemic led to unprecedented decreases in carbon dioxide (CO2) emissions, and the atmospheric signals are smaller than and obscured by climate variability in atmospheric transport and biospheric fluxes, notably that related to the 2019–2020 Indian Ocean Dipole.
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- 2021
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215. Evaluation of OCO‐2 X CO2Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns
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Bell, Emily, O'Dell, Christopher W., Davis, Kenneth J., Campbell, Joel, Browell, Edward, Scott Denning, A., Dobler, Jeremy, Erxleben, Wayne, Fan, Tai‐Fang, Kooi, Susan, Lin, Bing, Pal, Sandip, and Weir, Brad
- Abstract
With nearly 1 million observations of column‐mean carbon dioxide concentration (X CO2) per day, the Orbiting Carbon Observatory 2 (OCO‐2) presents exciting possibilities for monitoring the global carbon cycle, including the detection of subcontinental column CO2variations. While the OCO‐2 data set has been shown to achieve target precision and accuracy on a single‐sounding level, the validation of X CO2spatial gradients on subcontinental scales remains challenging. In this work, we investigate the use of an integrated path differential absorption (IPDA) lidar for evaluation of OCO‐2 observations via NASA's Atmospheric Carbon and Transport (ACT)‐America project. The project has completed eight clear‐sky underflights of OCO‐2 with the Multifunctional Fiber Laser Lidar (MFLL)—along with a suite of in situ instruments—giving a precisely colocated, high‐resolution validation data set spanning nearly 3,800 km across four seasons. We explore the challenges and opportunities involved in comparing the MFLL and OCO‐2 X CO2data sets and evaluate their agreement on synoptic and local scales. We find that OCO‐2 synoptic‐scale gradients generally agree with those derived from the lidar, typically to ±0.1 ppm per degree latitude for gradients ranging in strength from 0 to 1 ppm per degree latitude. CO2reanalysis products also typically agree to ±0.25 ppm per degree when compared with an in situ‐informed CO2“curtain.” Real X CO2features at local scales, however, remain challenging to observe and validate from space, with correlation coefficients typically below 0.35 between OCO‐2 and the MFLL. Even so, ACT‐America data have helped investigate interesting local X CO2patterns and identify systematic spurious cloud‐related features in the OCO‐2 data set. OCO‐2 and lidar tend to agree on synoptic‐scale X CO2gradients, over a few hundred kilometers, to within 0.1 ppm per degree latitudeThere is very little agreement among tested data sets on smaller‐scale X CO2features, on the order of tens of kilometersThe OCO‐2 X CO2data set contains some systematic spurious retrievals apparently due to 3D cloud effects, which should be addressed in the future
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- 2020
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216. TECHNICAL COMMENT ABSTRACTS.
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Chevallier, Frédéric, Liu, Junjie, Bowman, Kevin W., Schimel, David, Parazoo, Nicolas C., Jiang, Zhe, Lee, Meemong, Bloom, A. Anthony, Wunch, Debra, Frankenberg, Christian, Sun, Ying, O’Dell, Christopher W., Gurney, Kevin R., Menemenlis, Dimitris, Gierach, Michelle, Crisp, David, and Eldering, Annmarie
- Published
- 2018
217. The potential of space-based carbon dioxide retrievals to evaluate land surface models.
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Lindqvist, Hannakaisa, O'Dell, Christopher, Schuh, Andrew, Baker, David, and Denning, Scott
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CARBON dioxide , *LAND use - Published
- 2018
218. NASA's Carbon Cycle OSSE Initiative - Informing future space-based observing strategies through advanced modeling and data assimilation.
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Ott, Lesley, Schimel, David, O'Dell, Christopher, Moore III, Berrien, Crowell, Sean, Baker, David, Baker, Ian, Bowman, Kevin, Chatterjee, Abhishek, Denning, Scott, Haynes, Kathy, Kawa, Stephan, Miller, Charles, O'Brien, Denis, Pawson, Steven, Poulter, Benjamin, Schuh, Andrew, and Taylor, Thomas
- Published
- 2018
219. Spaceborne detection of localized carbon dioxide sources.
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Schwandner, Florian M., Gunson, Michael R., Miller, Charles E., Carn, Simon A., Eldering, Annmarie, Krings, Thomas, Verhulst, Kristal R., Schimel, David S., Nguyen, Hai M., Crisp, David, O’Dell, Christopher W., Osterman, Gregory B., Iraci, Laura T., and Podolske, James R.
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- 2017
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220. Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño.
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Junjie Liu, Bowman, Kevin W., Schimel, David S., Parazoo, Nicolas C., Zhe Jiang, Meemong Lee, Anthony Bloom, A., Wunch, Debra, Frankenberg, Christian, Ying Sun, O’Dell, Christopher W., Gurney, Kevin R., Menemenlis, Dimitris, Gierach, Michelle, Crisp, David, and Eldering, Annmarie
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- 2017
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221. A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10.
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Keely, William R., Mauceri, Steffen, Crowell, Sean, and O'Dell, Christopher W.
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MACHINE learning , *ATMOSPHERIC carbon dioxide , *MOLE fraction - Abstract
Measurements of column-averaged dry air mole fraction of CO2 (termed XCO2) from the Orbiting Carbon Observatory-2 (OCO-2) contain systematic errors and regional-scale biases, often induced by forward model error or nonlinearity in the retrieval. Operationally, these biases are corrected for by a multiple linear regression model fit to co-retrieved variables that are highly correlated with XCO2 error. The operational bias correction is fit in tandem with a hand-tuned quality filter which limits error variance and reduces the regime of interaction between state variables and error to one that is largely linear. While the operational correction and filter are successful in reducing biases in retrievals, they do not allow for throughput or correction of data in which biases become nonlinear in predictors or features. In this paper, we demonstrate a clear improvement in the reduction in error variance over the operational correction by using a set of nonlinear machine learning models, one for land and one for ocean soundings. We further illustrate how the operational quality filter can be relaxed when used in conjunction with a nonlinear bias correction, which allows for an increase in sounding throughput by 14 % while maintaining the residual error in the operational correction. The method can readily be applied to future Atmospheric CO2 Observations from Space (ACOS) algorithm updates, to OCO-2's companion instrument OCO-3, and to other retrieved atmospheric state variables of interest. [ABSTRACT FROM AUTHOR]
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- 2023
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222. A Revised Cloud Overlap Scheme for Fast Microwave Radiative Transfer in Rain and Cloud.
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Geer, Alan J., Bauer, Peter, and O’Dell, Christopher W.
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RADIATIVE transfer , *MULTIPLE scattering (Physics) , *CLOUDS , *METEOROLOGICAL precipitation , *BRIGHTNESS temperature - Abstract
The assimilation of cloud- and precipitation-affected observations into weather forecasting systems requires very fast calculations of radiative transfer in the presence of multiple scattering. At the European Centre for Medium-Range Weather Forecasts (ECMWF), performance limitations mean that only a single cloudy calculation (including any precipitation) can be made, and the simulated radiance is a weighted combination of cloudy- and clear-sky radiances. Originally, the weight given to the cloudy part was the maximum cloud fraction in the atmospheric profile. However, this weighting was excessive, and because of nonlinear radiative transfer (the “beamfilling effect”) there were biases in areas of cloud and precipitation. A new approach instead uses the profile average cloud fraction, and decreases RMS errors by 40% in areas of rain or heavy clouds when “truth” comes from multiple independent column simulations. There is improvement all the way from low (e.g., 19 GHz) to high (e.g., 183 GHz) microwave frequencies. There is also improvement when truth comes from microwave imager observations. One minor problem is that biases increase slightly in mid- and upper-tropospheric sounding channels in light-cloud situations, which shows that future improvements will require the cloud fraction to vary according to the optical properties at different frequencies. [ABSTRACT FROM AUTHOR]
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- 2009
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223. Analysis of 3D cloud effects in OCO-2 XCO2 retrievals.
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Massie, Steven T., Cronk, Heather, Merrelli, Aronne, O'Dell, Christopher, Schmidt, K. Sebastian, Chen, Hong, and Baker, David
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BIAS correction (Topology) , *DEVIATION (Statistics) , *DATA integrity , *ABSOLUTE value , *STANDARD deviations , *RADIATIVE transfer - Abstract
The presence of 3D cloud radiative effects in OCO-2 retrievals is demonstrated from an analysis of 2014–2019 OCO-2 XCO2 raw retrievals, bias-corrected XCO2bc data, ground-based Total Carbon Column Observation Network (TCCON) XCO2, and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud and radiance fields. In approximate terms, 40 % (quality flag – QF = 0, land or ocean) and 73 % (QF = 1, land or ocean) of the observations are within 4 km of clouds. 3D radiative transfer calculations indicate that 3D cloud radiative perturbations at this cloud distance, for an isolated low-altitude cloud, are larger in absolute value than those due to a 1 ppm increase in CO 2. OCO-2 measurements are therefore susceptible to 3D cloud effects. Four 3D cloud metrics, based upon MODIS radiance and cloud fields as well as stand-alone OCO-2 measurements, relate XCO2bc–TCCON averages to 3D cloud effects. This analysis indicates that the operational bias correction has a nonzero residual 3D cloud bias for both QF = 0 and QF = 1 data. XCO2bc–TCCON averages at small cloud distances differ from those at large cloud distances by - 0.4 and - 2.2 ppm for the QF = 0 and QF = 1 data over the ocean. Mitigation of 3D cloud biases with a table lookup technique, which utilizes the nearest cloud distance (Distkm) and spatial radiance heterogeneity (CSNoiseRatio) 3D metrics, reduces QF = 1 ocean and land XCO2bc–TCCON averages from - 1 ppm to near ± 0.2 ppm. The ocean QF = 1 XCO2bc–TCCON averages can be reduced to the 0.5 ppm level if 60 % (70 %) of the QF = 1 data points are utilized by applying Distkm (CSNoiseRatio) metrics in a data screening process. Over land the QF = 1 XCO2bc–TCCON averages are reduced to the 0.5 (0.8) ppm level if 65 % (63 %) of the data points are utilized by applying Diastkm (CSNoiseRatio) data screening. The addition of more terms to the linear regression equations used in the current bias correction processing without data screening, however, did not introduce an appreciable improvement in the standard deviations of the XCO2bc–TCCON statistics. [ABSTRACT FROM AUTHOR]
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- 2021
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224. Retrieved wind speed from the Orbiting Carbon Observatory-2.
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Nelson, Robert R., Eldering, Annmarie, Crisp, David, Merrelli, Aronne J., and O'Dell, Christopher W.
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WIND speed , *WIND speed measurement , *ECONOMIC sectors , *WATER - Abstract
Satellite measurements of surface wind speed over the ocean inform a wide variety of scientific pursuits. While both active and passive microwave sensors are traditionally used to detect surface wind speed over water surfaces, measurements of reflected sunlight in the near-infrared made by the Orbiting Carbon Observatory-2 (OCO-2) are also sensitive to the wind speed. In this work, retrieved wind speeds from OCO-2 glint measurements are validated against the Advanced Microwave Scanning Radiometer-2 (AMSR2). Both sensors are in the international Afternoon Constellation (A-Train), allowing for a large number of co-located observations. Several different OCO-2 retrieval algorithm modifications are tested, with the most successful being a single-band Cox–Munk-only model. Using this, we find excellent agreement between the two sensors, with OCO-2 having a small mean bias against AMSR2 of - 0.22 ms-1 , an RMSD of 0.75 ms-1 , and a correlation coefficient of 0.94. Although OCO-2 is restricted to clear-sky measurements, potential benefits of its higher spatial resolution relative to microwave instruments include the study of coastal wind processes, which may be able to inform certain economic sectors. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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225. Fossil fuel CO2 emissions over metropolitan areas from space: A multi-model analysis of OCO-2 data over Lahore, Pakistan.
- Author
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Lei, Ruixue, Feng, Sha, Danjou, Alexandre, Broquet, Grégoire, Wu, Dien, Lin, John C., O'Dell, Christopher W., and Lauvaux, Thomas
- Subjects
- *
METROPOLITAN areas , *MONTE Carlo method , *CARBON offsetting , *FOSSIL fuels , *CARBON dioxide , *DATA analysis , *EMISSION inventories , *GREENHOUSE gases - Abstract
Urban areas, where more than 55% of the global population gathers, contribute more than 70% of anthropogenic fossil fuel carbon dioxide (CO 2ff) emissions. Accurate quantification of CO 2ff emissions from urban areas is of great importance for formulating global warming mitigation policies to achieve carbon neutrality by 2050. Satellite-based inversion techniques are unique among "top-down" approaches, potentially allowing us to track CO 2ff emission changes over cities globally. However, their accuracy is still limited by incomplete background information, cloud blockages, aerosol contamination, and uncertainties in models and priori emission inventories. To evaluate the current potential of space-based quantification techniques, we present the first attempt to monitor long-term changes in CO 2ff emissions based on the OCO-2 satellite measurements of column-averaged dry-air mole fractions of CO 2 (X CO2) over a fast-growing Asian metropolitan area: Lahore, Pakistan. We first examined the OCO-2 data availability at global scale. About 17% of OCO-2 soundings over the global 70 most populated cities from 2014 to 2019 are marked as high-quality. Cloud blockage and aerosol contamination are the two main causes of data loss. As an attempt to recover additional soundings, we evaluated the effectiveness of OCO-2 quality flags at the city level by comparing three flux quantification methods (WRF-Chem, X-STILT, and the flux cross-sectional integration method). The satellite/bottom-up emissions (OCO-2/ODIAC) ratios of the high-quality tracks with reduced uncertainties in emissions are better agreed across the three methods compared to the all-data tracks. This demonstrates that OCO-2 quality flags are useful filters of low-quality OCO-2 retrievals at local scales. All three methods consistently suggested that the ratio medians are greater than 1, implying that the ODIAC slightly underestimated CO 2ff emissions over Lahore. Additionally, our estimation of the a posteriori CO 2ff emission trend was about 734 kt C/year (i.e., an annual 6.7% increase). 10,000 Monte Carlo simulations of the Mann-Kendall upward trend test showed that less than 10% prior uncertainty for 8 tracks (or less than 20% prior uncertainty for 25 tracks) is required to achieve a greater-than-50% trend significant possibility at a 95% confidence level. It implies that the trend is driven by the prior and not due to the assimilation of OCO-2 retrievals. The key to improving the role of satellite data in CO 2 emission trend detection lies in collecting more frequent high-quality tracks near metropolitan areas to achieve significant constraints from X CO2 retrievals. • 17% of OCO-2 soundings over the 70 most populated cities are of high-quality. • OCO-2 quality flags are useful filters of low-quality retrievals at city scale. • Posteriori fossil fuel CO 2 emissions over Lahore showed a 6.7% annual increase. • More high-quality tracks are needed to better constrain urban CO 2 emission trends. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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- View/download PDF
226. Advances in quantifying power plant CO2 emissions with OCO-2.
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Nassar, Ray, Mastrogiacomo, Jon-Paul, Bateman-Hemphill, William, McCracken, Callum, MacDonald, Cameron G., Hill, Tim, O'Dell, Christopher W., Kiel, Matthäus, and Crisp, David
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- *
POWER plants , *COAL-fired power plants , *GOVERNMENT policy on climate change , *CARBON dioxide , *SMALL cities , *DATA quality , *GREENHOUSE gases - Abstract
We present CO 2 emission estimates for twenty power plants and related facilities in the United States, India, South Africa, Poland, Russia and South Korea, derived from space-based CO 2 observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. Improvements to OCO-2 data quality and to our methodology yield improved results relative to earlier work. These new results include emission quantification for both larger and smaller power plants, the first power plant emission estimate based on ocean glint data and emissions from a small city with multiple industrial facilities. CO 2 emission estimates are compared against reported facility emissions where available, including high temporal resolution data for the eight US sites. The difference with respect to reported values for the US sites ranges from 1.4% to 26.7%, with a mean of 15.1%, although the estimated emission sum for all US sites is within 0.8% of the reported value, suggesting the errors are largely random. This finding reinforces the importance of revisit rate for future space-based emission monitoring systems and furthermore confirms that making multiple overpasses of a power plant can reduce errors to an accuracy useful to support climate policy. • We quantify CO 2 emissions from power plants using observations from NASA's OCO-2. • Sum of estimates for 8 US power plants is within 0.8% of sum of reported values. • Results reinforce importance of revisit rate for satellite CO 2 emission monitoring. • Multiple revisits per power plant can lead to CO 2 emission accuracy useful for climate policy. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
227. Corrigendum to "Absorption coefficient (ABSCO) tables for the Orbiting Carbon Observatories: Version 5.1" [J. Quant. Spectrosc. Radiat. Transf. 255 (2020) 107217].
- Author
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Payne, Vivienne H., Drouin, Brian J., Oyafuso, Fabiano, Kuai, Le, Fisher, Brendan M., Sung, Keeyoon, Nemchick, Deacon, Crawford, Timothy J., Smyth, Mike, Crisp, David, Adkins, Erin, Hodges, Joseph T., Long, David A., Mlawer, Eli J., Merrelli, Aronne, Lunny, Elizabeth, and O'Dell, Christopher W.
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- *
ABSORPTION coefficients , *OBSERVATORIES , *ATMOSPHERIC radiation measurement , *CARBON - Published
- 2020
- Full Text
- View/download PDF
228. Absorption coefficient (ABSCO) tables for the Orbiting Carbon Observatories: Version 5.1.
- Author
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Payne, Vivienne H., Drouin, Brian J., Oyafuso, Fabiano, Kuai, Le, Fisher, Brendan M., Sung, Keeyoon, Nemchick, Deacon, Crawford, Timothy J., Smyth, Mike, Crisp, David, Adkins, Erin, Hodges, Joseph T., Long, David A., Mlawer, Eli J., Merrelli, Aronne, Lunny, Elizabeth, and O'Dell, Christopher W.
- Subjects
- *
ABSORPTION coefficients , *OBSERVATORIES , *SURFACE pressure , *ALGORITHMS , *WATER vapor , *TRACE gases , *ATMOSPHERIC carbon dioxide - Abstract
• Absorption coefficients for the Orbiting Carbon Observatory missions updated to v5.1 for the B10 Level 2 algorithm. • Improved spectroscopy for Oxygen A-band results in reduced spatial variability in surface pressure retrieval bias. • Orbiting Carbon Observatory retrievals are sensitive to changes to the water vapor continuum model. The accuracy of atmospheric trace gas retrievals depends directly on the accuracy of the molecular absorption model used within the retrieval algorithm. For remote sensing of well-mixed gases, such as carbon dioxide (CO 2), where the atmospheric variability is small compared to the background, the quality of the molecular absorption model is key. Recent updates to oxygen (O 2) absorption coefficients (ABSCO) for the 0.76 µm A-band and the water vapor (H 2 O) continuum model within the 1.6 µm and 2.06 µm CO 2 bands used within the Orbiting Carbon Observatory (OCO-2 and OCO-3) algorithm are described here. Updates in the O 2 A-band involve the inclusion of new laboratory measurements within multispectrum fits to improve relative consistency between O 2 line shapes and collision-induced absorption (CIA). The H 2 O continuum model has been updated to MT _ CKD v3.2, which has benefited from information from a range of laboratory studies relative to the model utilized in the previous ABSCO version. Impacts of these spectroscopy updates have been evaluated against ground-based atmospheric spectra from the Total Carbon Column Observing Network (TCCON) and within the framework of the OCO-2 algorithm, using OCO-2 soundings covering a range of atmospheric and surface conditions. The updated absorption coefficients (ABSCO version 5.1) are found to offer improved fitting residuals and reduced biases in retrieved surface pressure relative to the previous version (ABSCO v5.0) used within B8 and B9 of the OCO-2 retrieval algorithm and have been adopted for the OCO B10 Level 2 algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
229. Three-Dimensionally Printed Simulated Tracheas to Improve Cricothyrotomy Skills Among Anesthesia Providers.
- Author
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Hogan F, O'Dell C, Pearson J, Parrish J, and Simmons VC
- Subjects
- Humans, Trachea, Checklist, Printing, Three-Dimensional, Anesthesia, Anesthesiology
- Abstract
Cricothyrotomy proficiency is imperative for anesthesia providers; however, opportunities to perform this skill are infrequent making skill maintenance essential. Increased accessibility of three-dimensional (3D) printing allows for production of low-cost simulation models. The models used for simulation-based teaching and deliberate practice facilitate skill development and refinement. A cost-effective, 3D printed airway model was designed and allowed 47 anesthesia providers to complete hands-on practice during a cricothyrotomy simulation-based training program. Assessment and comparison of pre- to post- intervention was completed for self-efficacy, knowledge, time to skill completion, compliance of required steps checklist, Global Rating Scale score, and successful ventilation. Statistically significant improvement from pre- to posttest was demonstrated in: 1) self-efficacy survey scores (P < .001); 2) knowledge test scores (P < .001); and 3) decreased time (minutes:seconds) to task completion (P < .001). Time from initial posttest to 3-month posttest (P = .046) significantly increased, however, the time at 3 months posttest remained significantly lower than pretest (P < .001). Providers' ability to ventilate, compliance with procedural steps, and technical skills significantly improved. 3D printing can produce anatomically similar simulation airway models that allow providers to practice and improve cricothyrotomy knowledge and skills. Developing an affordable and accessible simulation model provides a sustainable tool that allows providers multiple cricothyrotomy practice attempts., Competing Interests: Name: Felicia Hogan, DNP, CRNA Contribution: This author made significant contributions to the conception, synthesis, writing, and final editing and approval of the manuscript to justify inclusion as an author. Disclosures: None. Name: Christopher O’Dell Contribution: This author made significant contributions to the conception, synthesis, writing, and final editing and approval of the manuscript to justify inclusion as an author. Disclosures: None. Name: Julie Pearson, PhD, CRNA Contribution: This author made significant contributions to the conception, synthesis, writing, and final editing and approval of the manuscript to justify inclusion as an author. Disclosures: None. Name: Joseph Parrish, MSN, CRNA Contribution: This author made significant contributions to the conception, synthesis, writing, and final editing and approval of the manuscript to justify inclusion as an author. Disclosures: None. Name: Virginia C. Simmons, DNP, CRNA, CHSE-A, FAANA, FAAN Contribution: This author made significant contributions to the conception, synthesis, writing, and final editing and approval of the manuscript to justify inclusion as an author. Disclosures: None, (Copyright © by the American Association of Nurse Anesthetists.)
- Published
- 2023
230. Reply to: The size of the land carbon sink in China.
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Wang J, Feng L, Palmer PI, Liu Y, Fang S, Bösch H, O'Dell CW, Tang X, Yang D, Liu L, and Xia C
- Subjects
- China, Carbon analysis, Carbon Sequestration
- Published
- 2022
- Full Text
- View/download PDF
231. Reply to: On the role of atmospheric model transport uncertainty in estimating the Chinese land carbon sink.
- Author
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Wang J, Feng L, Palmer PI, Liu Y, Fang S, Bösch H, O'Dell CW, Tang X, Yang D, Liu L, and Xia C
- Subjects
- China, Ecosystem, Uncertainty, Atmosphere, Carbon Sequestration
- Published
- 2022
- Full Text
- View/download PDF
232. Large Chinese land carbon sink estimated from atmospheric carbon dioxide data.
- Author
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Wang J, Feng L, Palmer PI, Liu Y, Fang S, Bösch H, O'Dell CW, Tang X, Yang D, Liu L, and Xia C
- Subjects
- China, Construction Materials, Data Analysis, Asia, Eastern, Fossil Fuels, Models, Theoretical, Plants, Satellite Imagery, Atmosphere chemistry, Carbon Dioxide analysis, Carbon Sequestration, Environmental Monitoring, Geographic Mapping
- Abstract
Limiting the rise in global mean temperatures relies on reducing carbon dioxide (CO
2 ) emissions and on the removal of CO2 by land carbon sinks. China is currently the single largest emitter of CO2 , responsible for approximately 27 per cent (2.67 petagrams of carbon per year) of global fossil fuel emissions in 20171 . Understanding of Chinese land biosphere fluxes has been hampered by sparse data coverage2-4 , which has resulted in a wide range of a posteriori estimates of flux. Here we present recently available data on the atmospheric mole fraction of CO2 , measured from six sites across China during 2009 to 2016. Using these data, we estimate a mean Chinese land biosphere sink of -1.11 ± 0.38 petagrams of carbon per year during 2010 to 2016, equivalent to about 45 per cent of our estimate of annual Chinese anthropogenic emissions over that period. Our estimate reflects a previously underestimated land carbon sink over southwest China (Yunnan, Guizhou and Guangxi provinces) throughout the year, and over northeast China (especially Heilongjiang and Jilin provinces) during summer months. These provinces have established a pattern of rapid afforestation of progressively larger regions5,6 , with provincial forest areas increasing by between 0.04 million and 0.44 million hectares per year over the past 10 to 15 years. These large-scale changes reflect the expansion of fast-growing plantation forests that contribute to timber exports and the domestic production of paper7 . Space-borne observations of vegetation greenness show a large increase with time over this study period, supporting the timing and increase in the land carbon sink over these afforestation regions.- Published
- 2020
- Full Text
- View/download PDF
233. The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP).
- Author
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Elsaesser GS, O'Dell CW, Lebsock MD, Bennartz R, Greenwald TJ, and Wentz FJ
- Abstract
The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988 - 2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) inter-calibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2 and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and monthly-mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, a correction for a CLWP bias (based on matchups to clear-sky MODIS scenes), and the construction of a total (cloud+rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e. CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from -15% (e.g. global oceanic stratocumulus decks) to +5-10% (e.g. portions of the higher-latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Science Data and Information Services Center (http://disc.sci.gsfc.nasa.gov).
- Published
- 2017
- Full Text
- View/download PDF
234. Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Niño.
- Author
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Liu J, Bowman KW, Schimel DS, Parazoo NC, Jiang Z, Lee M, Bloom AA, Wunch D, Frankenberg C, Sun Y, O'Dell CW, Gurney KR, Menemenlis D, Gierach M, Crisp D, and Eldering A
- Abstract
The 2015-2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO
2 ) was the largest on record. Here we quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO2 , solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability., (Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)- Published
- 2017
- Full Text
- View/download PDF
235. Evaluation of Cloud Liquid Water Path Trends Using a Multi-Decadal Record of Passive Microwave Observations.
- Author
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Manaster A, O'Dell CW, and Elsaesser G
- Abstract
In this study, observed cloud liquid water path (LWP) trends from the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) dataset (1988 - 2014) are compared to trends computed from the temporally-coincident records of 16 global climate models (GCMs) participating in the Coupled Model Intercomparison Project 5 (CMIP5). For many regions, observed trend magnitudes are several times larger than the corresponding model mean trend magnitudes. Muted model mean trends are thought to be the result of cancellation effects arising from differing interannual variability characteristics and differences in model physics/dynamics. In most regions, the majority of modeled trends were statisically consistent with the observed trends. This was thought to be because of large estimated errors in both the observations and the models due to interannual variability. Over the southern oceans (south of 40S latitude), general agreement between the observed trend and virtually all GCM trends is also found (~ 1-2 g m
-2 decade-1 ). Observed trends are also compared to those from the atmospheric model intercomparison project (AMIP). Like the CMIP5 models, the majority of modeled AMIP trends were statistically consistent with the observed trends. It was also found that, in regions where the AMIP model mean time series better captures observed interannual variability, it tends to better capture the magnitude of the observed trends.- Published
- 2017
- Full Text
- View/download PDF
236. Evidence for climate change in the satellite cloud record.
- Author
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Norris JR, Allen RJ, Evan AT, Zelinka MD, O'Dell CW, and Klein SA
- Abstract
Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.
- Published
- 2016
- Full Text
- View/download PDF
237. The DNA sequence of the human X chromosome.
- Author
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Ross MT, Grafham DV, Coffey AJ, Scherer S, McLay K, Muzny D, Platzer M, Howell GR, Burrows C, Bird CP, Frankish A, Lovell FL, Howe KL, Ashurst JL, Fulton RS, Sudbrak R, Wen G, Jones MC, Hurles ME, Andrews TD, Scott CE, Searle S, Ramser J, Whittaker A, Deadman R, Carter NP, Hunt SE, Chen R, Cree A, Gunaratne P, Havlak P, Hodgson A, Metzker ML, Richards S, Scott G, Steffen D, Sodergren E, Wheeler DA, Worley KC, Ainscough R, Ambrose KD, Ansari-Lari MA, Aradhya S, Ashwell RI, Babbage AK, Bagguley CL, Ballabio A, Banerjee R, Barker GE, Barlow KF, Barrett IP, Bates KN, Beare DM, Beasley H, Beasley O, Beck A, Bethel G, Blechschmidt K, Brady N, Bray-Allen S, Bridgeman AM, Brown AJ, Brown MJ, Bonnin D, Bruford EA, Buhay C, Burch P, Burford D, Burgess J, Burrill W, Burton J, Bye JM, Carder C, Carrel L, Chako J, Chapman JC, Chavez D, Chen E, Chen G, Chen Y, Chen Z, Chinault C, Ciccodicola A, Clark SY, Clarke G, Clee CM, Clegg S, Clerc-Blankenburg K, Clifford K, Cobley V, Cole CG, Conquer JS, Corby N, Connor RE, David R, Davies J, Davis C, Davis J, Delgado O, Deshazo D, Dhami P, Ding Y, Dinh H, Dodsworth S, Draper H, Dugan-Rocha S, Dunham A, Dunn M, Durbin KJ, Dutta I, Eades T, Ellwood M, Emery-Cohen A, Errington H, Evans KL, Faulkner L, Francis F, Frankland J, Fraser AE, Galgoczy P, Gilbert J, Gill R, Glöckner G, Gregory SG, Gribble S, Griffiths C, Grocock R, Gu Y, Gwilliam R, Hamilton C, Hart EA, Hawes A, Heath PD, Heitmann K, Hennig S, Hernandez J, Hinzmann B, Ho S, Hoffs M, Howden PJ, Huckle EJ, Hume J, Hunt PJ, Hunt AR, Isherwood J, Jacob L, Johnson D, Jones S, de Jong PJ, Joseph SS, Keenan S, Kelly S, Kershaw JK, Khan Z, Kioschis P, Klages S, Knights AJ, Kosiura A, Kovar-Smith C, Laird GK, Langford C, Lawlor S, Leversha M, Lewis L, Liu W, Lloyd C, Lloyd DM, Loulseged H, Loveland JE, Lovell JD, Lozado R, Lu J, Lyne R, Ma J, Maheshwari M, Matthews LH, McDowall J, McLaren S, McMurray A, Meidl P, Meitinger T, Milne S, Miner G, Mistry SL, Morgan M, Morris S, Müller I, Mullikin JC, Nguyen N, Nordsiek G, Nyakatura G, O'Dell CN, Okwuonu G, Palmer S, Pandian R, Parker D, Parrish J, Pasternak S, Patel D, Pearce AV, Pearson DM, Pelan SE, Perez L, Porter KM, Ramsey Y, Reichwald K, Rhodes S, Ridler KA, Schlessinger D, Schueler MG, Sehra HK, Shaw-Smith C, Shen H, Sheridan EM, Shownkeen R, Skuce CD, Smith ML, Sotheran EC, Steingruber HE, Steward CA, Storey R, Swann RM, Swarbreck D, Tabor PE, Taudien S, Taylor T, Teague B, Thomas K, Thorpe A, Timms K, Tracey A, Trevanion S, Tromans AC, d'Urso M, Verduzco D, Villasana D, Waldron L, Wall M, Wang Q, Warren J, Warry GL, Wei X, West A, Whitehead SL, Whiteley MN, Wilkinson JE, Willey DL, Williams G, Williams L, Williamson A, Williamson H, Wilming L, Woodmansey RL, Wray PW, Yen J, Zhang J, Zhou J, Zoghbi H, Zorilla S, Buck D, Reinhardt R, Poustka A, Rosenthal A, Lehrach H, Meindl A, Minx PJ, Hillier LW, Willard HF, Wilson RK, Waterston RH, Rice CM, Vaudin M, Coulson A, Nelson DL, Weinstock G, Sulston JE, Durbin R, Hubbard T, Gibbs RA, Beck S, Rogers J, and Bentley DR
- Subjects
- Animals, Antigens, Neoplasm genetics, Centromere genetics, Chromosomes, Human, Y genetics, Contig Mapping, Crossing Over, Genetic genetics, Dosage Compensation, Genetic, Female, Genetic Linkage genetics, Genetics, Medical, Humans, Male, Polymorphism, Single Nucleotide genetics, RNA genetics, Repetitive Sequences, Nucleic Acid genetics, Sequence Homology, Nucleic Acid, Testis metabolism, Chromosomes, Human, X genetics, Evolution, Molecular, Genomics, Sequence Analysis, DNA
- Abstract
The human X chromosome has a unique biology that was shaped by its evolution as the sex chromosome shared by males and females. We have determined 99.3% of the euchromatic sequence of the X chromosome. Our analysis illustrates the autosomal origin of the mammalian sex chromosomes, the stepwise process that led to the progressive loss of recombination between X and Y, and the extent of subsequent degradation of the Y chromosome. LINE1 repeat elements cover one-third of the X chromosome, with a distribution that is consistent with their proposed role as way stations in the process of X-chromosome inactivation. We found 1,098 genes in the sequence, of which 99 encode proteins expressed in testis and in various tumour types. A disproportionately high number of mendelian diseases are documented for the X chromosome. Of this number, 168 have been explained by mutations in 113 X-linked genes, which in many cases were characterized with the aid of the DNA sequence.
- Published
- 2005
- Full Text
- View/download PDF
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