Validation Study of Waray Text Readability Instrument

In 2012 the Leyte Normal University developed a computer software—modelled after the Spache Readability Formula (1953) made for English—made to help rank texts that can is used by teachers or research groups on selecting appropriate reading materials to support the DepEd’s MTB-MLE program in Region VIII, in the Philippines. However, “several experiments have already established that existing readability measures in English cannot directly be used to compute readability of other languages.” To validate the Waray Text Readability Instrument (WTRI) formula, 15 stories were rated by 24 randomly selected teachers from two elementary schools in Tacloban City. The WTRI software uses two factors in determining readability, namely: (a) sentence length and (b) frequency of commonly occurring words. The teachers’ task is to read the given text and rate the grade level of each text by considering these three factors: (1) frequency of commonly used words; (2) sentence length; and, (3) total number of words. The data gathered was compared with the WTRI’s ratings of the same texts. Statistical testing was done to determine if there is a significant difference between the teachers’ rating of the texts and the WTRI’s ratings. As a result, there was no significant difference between the software’s grade level ratings and that of the teachers’. It implied that the WTRI’s calculation is valid

‘Procedes Huc’: Voltaire, Newton, and Locke in Lettres Philosophiques

In Lettres philosophiques, Letter XIII is devoted to Locke, as are Letters XIV–XVII to Newton. The ordering of these letters is not adequately explained by comparing the dates of birth or death of the two thinkers. For the Letter on Locke not only precedes but also ‘frames’ those on Newton, in the sense that it provides the reader with a guide through the philosophical intricacies of Letters XIV–XVII. This works in two ways. On the one hand, in order to defend Newton against his detractors Voltaire broadly adopts Locke’s perspective on the relation among words, ideas and things. On the other hand, he subtly and misleadingly grafts Locke’s epistemology onto the Principia, though it differs from Newton’s epistemology in significant respects. For Locke, unlike Newton, holds that we can identify fixed, permanent limits concerning what kind of thing humanity can know of matter and the universe. Voltaire presents Newton’s ideas as though they respected Locke’s limits. However, we can glimpse Voltaire’s own attitude in the final words of Letter XV: ‘Procedes huc, et non ibis amplius’: Voltaire agrees more closely with Locke than Newton concerning the limits of epistemology

Satellite and ground-based measurements of XCO2 in a remote semiarid region of Australia

In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) taken in a semiarid region of Australia with an EM27/SUN portable spectrometer equipped with an automated clamshell cover. We compared these measurements to space-based XCO2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT). Side-by-side measurements of EM27/SUN with the Total Carbon Column Observing Network (TCCON) instrument at the University of Wollongong were conducted in 2015-2016 to derive an XCO2 scaling factor of 0.9954 relative to TCCON. Although we found a slight drift of 0.13 % over 3 months in the calibration curve of the EM27/SUN vs. TCCON XCO2, the alignment of the EM27/SUN proved stable enough for a 2-week campaign, keeping the retrieved Xair values, another measure of stability, to within 0.5 % and the modulation efficiency to within 2 %. From the measurements in Alice Springs, we confirm a small bias of around 2 ppm in the GOSAT M-gain to H-gain XCO2 retrievals, as reported by the NIES GOSAT validation team. Based on the reported random errors from GOSAT, we estimate the required duration of a future campaign in order to better understand the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at https://doi.org/10.4225/48/5b21f16ce69bc (Velazco et al., 2018)

Observed Hemispheric Asymmetry in Stratospheric Transport Trends From 1994 to 2018

©2020. American Geophysical Union. All Rights Reserved. Total columns of the trace gases nitric acid (HNO3) and hydrogen chloride (HCl) are sensitive to variations in the lower stratospheric age of air, a quantity that describes transport time scales in the stratosphere. Analyses of HNO3 and HCl columns from the Network for the Detection of Atmospheric Composition Change panning 77°S to 79°N have detected changes in the extratropical stratospheric transport circulation from 1994 to 2018. The HNO3 and HCl analyses combined with the age of air from a simulation using the MERRA2 reanalysis show that the Southern Hemisphere lower stratosphere has become 1 month/decade younger relative to the Northern Hemisphere, largely driven by the Southern Hemisphere transport circulation. The analyses reveal multiyear anomalies with a 5- to 7-year period driven by interactions between the circulation and the quasi-biennial oscillation in tropical winds. This hitherto unrecognized variability is large relative to hemispheric transport trends and may bias ozone trend regressions

Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model

The GEOS-Chem simulation of atmospheric CH$_{4}$ was evaluated against observations from the Thermal and Near Infrared Sensor for Carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Total Carbon Column Observing Network (TCCON). We focused on the model simulations at the 4°×5° and 2°×2.5° horizontal resolutions for the period of February–May 2010. Compared to the GOSAT, TCCON, and ACE-FTS data, we found that the 2°×2.5° model produced a better simulation of CH$_{4}$, with smaller biases and a higher correlation to the independent data. We found large resolution-dependent differences such as a latitude-dependent XCH$_{4}$ bias, with higher column abundances of CH$_{4}$ at high latitudes and lower abundances at low latitudes at the 4°×5° resolution than at 2°×2.5°. We also found large differences in CH$_{4}$ column abundances between the two resolutions over major source regions such as China. These differences resulted in up to 30 % differences in inferred regional CH$_{4}$ emission estimates from the two model resolutions. We performed several experiments using 222Rn, 7Be, and CH$_{4}$ to determine the origins of the resolution-dependent errors. The results suggested that the major source of the latitude-dependent errors is excessive mixing in the upper troposphere and lower stratosphere, including mixing at the edge of the polar vortex, which is pronounced at the 4°×5° resolution. At the coarser resolution, there is weakened vertical transport in the troposphere at midlatitudes to high latitudes due to the loss of sub-grid tracer eddy mass flux in the storm track regions. The vertical air mass fluxes are calculated in the model from the degraded coarse-resolution wind fields and the model does not conserve the air mass flux between model resolutions; as a result, the low resolution does not fully capture the vertical transport. This produces significant localized discrepancies, such as much greater CH$_{4}$ abundances in the lower troposphere over China at 4°×5° than at 2°×2.5°. Although we found that the CH$_{4}$ simulation is significantly better at 2°×2.5° than at 4°×5°, biases may still be present at 2°×2.5° resolution. Their importance, particularly in regards to inverse modeling of CH$_{4}$ emissions, should be evaluated in future studies using online transport in the native general circulation model as a benchmark simulation

Retrieval of atmospheric CO2 with enhanced accuracy and precision from SCIAMACHY: validation with FTS measurements and comparison with model results

The Bremen Optimal Estimation differential optical absorption spectroscopy (DOAS) (BESD) algorithm for satellite based retrievals of XCO 2 (the column-average dry-air mole fraction of atmospheric CO 2) has been applied to Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) data. It uses measurements in the O 2-A absorption band to correct for scattering of undetected clouds and aerosols. Comparisons with precise and accurate ground-based Fourier transform spectrometer (FTS) measurements at four Total Carbon Column Observing Network (TCCON) sites have been used to quantify the quality of the new SCIAMACHY XCO 2 data set. Additionally, the results have been compared to NOAA\u27s assimilation system CarbonTracker. The comparisons show that the new retrieval meets the expectations from earlier theoretical studies. We find no statistically significant regional XCO 2 biases between SCIAMACHY and the FTS instruments. However, the standard error of the systematic differences is in the range of 0.2 ppm and 0.8 ppm. The XCO 2 single-measurement precision of 2.5 ppm is similar to theoretical estimates driven by instrumental noise. There are no significant differences found for the year-to-year increase as well as for the average seasonal amplitude between SCIAMACHY XCO 2 and the collocated FTS measurements. Comparison of the year-to-year increase and also of the seasonal amplitude of CarbonTracker exhibit significant differences with the corresponding FTS values at Darwin. Here the differences between SCIAMACHY and CarbonTracker are larger than the standard error of the SCIAMACHY values. The difference of the seasonal amplitude exceeds the significance level of 2 standard errors. Therefore, our results suggest that SCIAMACHY may provide valuable additional information about XCO 2, at least in regions with a low density of in situ measurements. Copyright 2011 by the American Geophysical Union

Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface-Based and Space-Based Atmospheric CO2 Measurements

© 2020. The Authors. Top-down estimates of CO2 fluxes are typically constrained by either surface-based or space-based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface-based and space-based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6-year (2010–2015) CO2 flux inversions. Flux inversions are performed assimilating surface-based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space-based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root-mean-square differences between posterior flux-simulated CO2 and aircraft-based CO2 over midlatitude regions (0.33–0.56 ppm) in comparison to GOSAT (0.37–0.61 ppm), TCCON (0.50–0.68 ppm), or in situ and flask measurements (0.46–0.56 ppm) alone. These results suggest that surface-based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space-based and surface-based flux constraints

Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface-Based and Space-Based Atmospheric CO2 Measurements

Abstract Top-down estimates of CO2 fluxes are typically constrained by either surface-based or space-based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface-based and space-based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6-year (2010?2015) CO2 flux inversions. Flux inversions are performed assimilating surface-based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space-based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root-mean-square differences between posterior flux-simulated CO2 and aircraft-based CO2 over midlatitude regions (0.33?0.56?ppm) in comparison to GOSAT (0.37?0.61?ppm), TCCON (0.50?0.68?ppm), or in situ and flask measurements (0.46?0.56?ppm) alone. These results suggest that surface-based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space-based and surface-based flux constraints

Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment

Nitrous oxide (N$_{2}$O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N$_{2}$O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N$_{2}$O ν$_{3}$ band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N$_{2}$O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N$_{2}$O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals