The Assimilation of Hyperspectral Satellite Radiances in Global Numerical Weather Prediction

Hyperspectral infrared radiance data present opportunities for significant improvements in data assimilation and Numerical Weather Prediction (NWP). The increase in spectral resolution available from the Atmospheric Infrared Sounder (AIRS) sensor, for example, will make it possible to improve the accuracy of temperature and moisture fields. Improved accuracy of the NWP analyses and forecasts should result. In this thesis we incorporate these hyperspectral data, using new assimilation methods, into the National Centers for Environmental Prediction's (NCEP) operational Global Data Assimilation System/Global Forecast System (GDAS/GFS) and investigate their impact on the weather analysis and forecasts. The spatial and spectral resolution of AIRS data used by NWP centers was initially based on theoretical calculations. Synthetic data were used to determine channel selection and spatial density for real time data assimilation. Several problems were previously not fully addressed. These areas include: cloud contamination, surface related issues, dust, and temperature inversions. In this study, several improvements were made to the methods used for assimilation. Spatial resolution was increased to examine every field of view, instead of one in nine or eighteen fields of view. Improved selection criteria were developed to find the best profile for assimilation from a larger sample. New cloud and inversion tests were used to help identify the best profiles to be assimilated in the analysis. The spectral resolution was also increased from 152 to 251 channels. The channels added were mainly near the surface, in the water vapor absorption band, and in the shortwave region. The GFS was run at or near operational resolution and contained all observations available to the operational system. For each experiment the operational version of the GFS was used during that time. The use of full spatial and enhanced spectral resolution data resulted in the first demonstration of significant impact of the AIRS data in both the Northern and Southern Hemisphere. Experiments were performed to show the contribution to the improvements in global weather forecasts from the increase in spatial and spectral resolution. Both spatial and spectral resolution increases were shown to make significant contributions to forecast skill. New methods were also developed to check for clouds, inversions and for estimating surface emissivity. Overall, an improved methodology for assimilating hyperspectral AIRS data was achieved

Evaluation of simulated O-3 production efficiency during the KORUS-AQ campaign: Implications for anthropogenic NOx emissions in Korea

We examine O3 production and its sensitivity to precursor gases and boundary layer mixing in Korea by using a 3-D global chemistry transport model and extensive observations during the KORea-US cooperative Air Quality field study in Korea, which occurred in May–June 2016. During the campaign, observed aromatic species onboard the NASA DC-8 aircraft, especially toluene, showed high mixing ratios of up to 10 ppbv, emphasizing the importance of aromatic chemistry in O3 production. To examine the role of VOCs and NOx in O3 chemistry, we first implement a detailed aromatic chemistry scheme in the model, which reduces the normalized mean bias of simulated O3 mixing ratios from –26% to –13%. Aromatic chemistry also increases the average net O3 production in Korea by 37%. Corrections of daytime PBL heights, which are overestimated in the model compared to lidar observations, increase the net O3 production rate by ~10%. In addition, increasing NOx emissions by 50% in the model shows best performance in reproducing O3 production characteristics, which implies that NOx emissions are underestimated in the current emissions inventory. Sensitivity tests show that a 30% decrease in anthropogenic NOx emissions in Korea increases the O3 production efficiency throughout the country, making rural regions ~2 times more efficient in producing O3 per NOx consumed. Simulated O3 levels overall decrease in the peninsula except for urban and other industrial areas, with the largest increase (~6 ppbv) in the Seoul Metropolitan Area (SMA). However, with simultaneous reductions in both NOx and VOCs emissions by 30%, O3 decreases in most of the country, including the SMA. This implies the importance of concurrent emission reductions for both NOx and VOCs in order to effectively reduce O3 levels in Korea

Demographic Inference and Representative Population Estimates from Multilingual Social Media Data

Social media provide access to behavioural data at an unprecedented scale and granularity. However, using these data to understand phenomena in a broader population is difficult due to their non-representativeness and the bias of statistical inference tools towards dominant languages and groups. While demographic attribute inference could be used to mitigate such bias, current techniques are almost entirely monolingual and fail to work in a global environment. We address these challenges by combining multilingual demographic inference with post-stratification to create a more representative population sample. To learn demographic attributes, we create a new multimodal deep neural architecture for joint classification of age, gender, and organization-status of social media users that operates in 32 languages. This method substantially outperforms current state of the art while also reducing algorithmic bias. To correct for sampling biases, we propose fully interpretable multilevel regression methods that estimate inclusion probabilities from inferred joint population counts and ground-truth population counts. In a large experiment over multilingual heterogeneous European regions, we show that our demographic inference and bias correction together allow for more accurate estimates of populations and make a significant step towards representative social sensing in downstream applications with multilingual social media.Comment: 12 pages, 10 figures, Proceedings of the 2019 World Wide Web Conference (WWW '19

The prevention of progression of arterial disease and diabetes (POPADAD) trial: factorial randomised placebo controlled trial of aspirin and antioxidants in patients with diabetes and asymptomatic peripheral arterial disease

Objective To determine whether aspirin and antioxidant therapy, combined or alone, are more effective than placebo in reducing the development of cardiovascular events in patients with diabetes mellitus and asymptomatic peripheral arterial disease

Airborne formaldehyde and volatile organic compound measurements over the Daesan petrochemical complex on Korea’s northwest coast during the Korea-United States Air Quality study

The U.S. National Aeronautics and Space Administration in partnership with Korea’s National Institute of Environmental Research embarked on the Korea-United States Air Quality (KORUS-AQ) study to address air quality issues over the Korean peninsula. Underestimation of volatile organic compound (VOC) emissions from various large facilities on South Korea’s northwest coast may contribute to this problem, and this study focuses on quantifying top-down emissions of formaldehyde (CH₂O) and VOCs from the largest of these facilities, the Daesan petrochemical complex, and comparisons with the latest emission inventories. To accomplish this and additional goals discussed herein, this study employed a number of measurements acquired during KORUS-AQ onboard the NASA DC-8 aircraft during three Daesan overflights on June 2, 3, and 5, 2016, in conjunction with a mass balance approach. The measurements included fast airborne measurements of CH₂O and ethane from an infrared spectrometer, additional fast measurements from other instruments, and a suite of 33 VOC measurements acquired by the whole air sampler. The mass balance approach resulted in consistent top-down yearly Daesan VOC emission flux estimates, which averaged (61 ± 14) × 10³ MT/year for the 33 VOC compounds, a factor of 2.9 ± 0.6 (±1.0) higher than the bottom-up inventory value. The top-down Daesan emission estimate for CH₂O and its four primary precursors averaged a factor of 4.3 ± 1.5 (± 1.9) times higher than the bottom-up inventory value. The uncertainty values in parentheses reflect upper limits for total uncertainty estimates. The resulting averaged top-down Daesan emission estimate for sulfur dioxide (SO₂) yielded a ratio of 0.81–1.0 times the bottom-up SO₂ inventory, and this provides an important cross-check on the accuracy of our mass balance analysis

Characterization, sources and reactivity of volatile organic compounds (VOCs) in Seoul and surrounding regions during KORUS-AQ

The Korea-United States Air Quality Study (KORUS-AQ) took place in spring 2016 to better understand air pollution in Korea. In support of KORUS-AQ, 2554 whole air samples (WAS) were collected aboard the NASA DC-8 research aircraft and analyzed for 82 C₁–C₁₀ volatile organic compounds (VOCs) using multi-column gas chromatography. Together with fast-response measurements from other groups, the air samples were used to characterize the VOC composition in Seoul and surrounding regions, determine which VOCs are major ozone precursors in Seoul, and identify the sources of these reactive VOCs. (1) The WAS VOCs showed distinct signatures depending on their source origins. Air collected over Seoul had abundant ethane, propane, toluene and n-butane while plumes from the Daesan petrochemical complex were rich in ethene, C₂–C₆ alkanes and benzene. Carbonyl sulfide (COS), CFC-113, CFC-114, carbon tetrachloride (CCl₄) and 1,2-dichloroethane were good tracers of air originating from China. CFC-11 was also elevated in air from China but was surprisingly more elevated in air over Seoul. (2) Methanol, isoprene, toluene, xylenes and ethene were strong individual contributors to OH reactivity in Seoul. However methanol contributed less to ozone formation based on photochemical box modeling, which better accounts for radical chemistry. (3) Positive Matrix Factorization (PMF) and other techniques indicated a mix of VOC source influences in Seoul, including solvents, traffic, biogenic, and long-range transport. The solvent and traffic sources were roughly equal using PMF, and the solvents source was stronger in the KORUS-AQ emission inventory. Based on PMF, ethene and propene were primarily associated with traffic, and toluene, ethylbenzene and xylenes with solvents, especially non-paint solvents for toluene and paint solvents for ethylbenzene and xylenes. This suggests that VOC control strategies in Seoul could continue to target vehicle exhaust and paint solvents, with additional regulations to limit the VOC content in a variety of non-paint solvents

Characterization, sources and reactivity of volatile organic compounds (VOCs) in Seoul and surrounding regions during KORUS-AQ

The Korea-United States Air Quality Study (KORUS-AQ) took place in spring 2016 to better understand air pollution in Korea. In support of KORUS-AQ, 2554 whole air samples (WAS) were collected aboard the NASA DC-8 research aircraft and analyzed for 82 C₁–C₁₀ volatile organic compounds (VOCs) using multi-column gas chromatography. Together with fast-response measurements from other groups, the air samples were used to characterize the VOC composition in Seoul and surrounding regions, determine which VOCs are major ozone precursors in Seoul, and identify the sources of these reactive VOCs. (1) The WAS VOCs showed distinct signatures depending on their source origins. Air collected over Seoul had abundant ethane, propane, toluene and n-butane while plumes from the Daesan petrochemical complex were rich in ethene, C₂–C₆ alkanes and benzene. Carbonyl sulfide (COS), CFC-113, CFC-114, carbon tetrachloride (CCl₄) and 1,2-dichloroethane were good tracers of air originating from China. CFC-11 was also elevated in air from China but was surprisingly more elevated in air over Seoul. (2) Methanol, isoprene, toluene, xylenes and ethene were strong individual contributors to OH reactivity in Seoul. However methanol contributed less to ozone formation based on photochemical box modeling, which better accounts for radical chemistry. (3) Positive Matrix Factorization (PMF) and other techniques indicated a mix of VOC source influences in Seoul, including solvents, traffic, biogenic, and long-range transport. The solvent and traffic sources were roughly equal using PMF, and the solvents source was stronger in the KORUS-AQ emission inventory. Based on PMF, ethene and propene were primarily associated with traffic, and toluene, ethylbenzene and xylenes with solvents, especially non-paint solvents for toluene and paint solvents for ethylbenzene and xylenes. This suggests that VOC control strategies in Seoul could continue to target vehicle exhaust and paint solvents, with additional regulations to limit the VOC content in a variety of non-paint solvents

Input and Output Inventories in General Equilibrium

We build and estimate a two‐sector (goods and services) dynamic stochastic general equilibrium model with two types of inventories: materials (input) inventories facilitate the production of finished goods, while finished goods (output) inventories yield utility services. The model is estimated using Bayesian methods. The estimated model replicates the volatility and cyclicality of inventory investment and inventory‐to‐target ratios. Although inventories are an important element of the model’s propagation mechanism, shocks to inventory efficiency or management are not an important source of business cycles. When the model is estimated over two subperiods (pre ‐ and post‐1984), changes in the volatility of inventory shocks, or in structural parameters associated with inventories play a minor role in reducing the volatility of output

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts