Correlation Between Teacher Turnover Rates In The State Of Alaska And Standardized Test Scores In The Area Of Mathematics On The Standards Based Assessments/High School Qualifying Exam

Thesis (Ph.D.) University of Alaska Fairbanks, 2010This study utilized bivariate correlations, partial correlations, multivariate analysis including Hotelling-T, and observed power to investigate the possible correlations and connections of teacher turnover in Alaska's public school system to performance on the standards-based assessment of the Alaska High School Qualifying Exam (HSQE). The study focused on the results in the content area of mathematics involving the 10th grade standards-based assessment (SBA). Results from the study indicate two primary correlations exist as applied to the proficiency levels on the mathematics portion of the 10th grade mathematics SBA, teacher turnover and percent Alaska Native of school population. The results indicate that teacher turnover is statistically significant with an inverse relationship in relation to standards-based test scores, and the students most likely being impacted by teacher turnover are located in Alaska school districts that have large Alaska Native student populations

The Montana Dead Man Statute

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Sediment history mirrors Pleistocene aridification in the Gobi Desert (Ejina Basin, NW China)

Central Asia is a large-scale source of dust transport, but it also held a prominent changing hydrological system during the Quaternary. A 223 m long sediment core (GN200) was recovered from the Ejina Basin (synonymously Gaxun Nur Basin) in NW China to reconstruct the main modes of water availability in the area during the Quaternary. The core was drilled from the Heihe alluvial fan, one of the world's largest alluvial fans, which covers a part of the Gobi Desert. Grain-size distributions supported by endmember modelling analyses, geochemical-mineralogical compositions (based on XRF and XRD measurements), and bioindicator data (ostracods, gastropods, pollen and non-pollen palynomorphs, and n-alkanes with leaf-wax delta D) are used to infer the main transport processes and related environmental changes during the Pleistocene. Magnetostratigraphy supported by radionuclide dating provides the age model. Grain- size endmembers indicate that lake, playa (sheetflood), fluvial, and aeolian dynamics are the major factors influencing sedimentation in the Ejina Basin. Core GN200 reached the pre-Quatemary quartz- and plagioclase-rich "Red Clay" formation and reworked material derived from it in the core bottom. This part is overlain by silt-dominated sediments between 217 and 110 m core depth, which represent a period of lacustrine and playa-lacustrine sedimentation that presumably formed within an endorheic basin. The upper core half between 110 and 0 m is composed of mainly silty to sandy sediments derived from the Heihe that have accumulated in a giant sediment fan until modem time. Apart from the transition from a siltier to a sandier environment with frequent switches between sediment types upcore, the clay mineral fraction is indicative of different environments. Mixed-layer clay minerals (chlorite/smectite) are increased in the basal Red Clay and reworked sediments, smectite is indicative of lacustrine-playa deposits, and increased chlorite content is characteristic of the Heihe river deposits. The sediment succession in core GN200 based on the detrital proxy interpretation demonstrates that lake-playa sedimentation in the Ejina Basin has been disrupted likely due to tectonic events in the southern part of the catchment around 1 Ma. At this time Heihe broke through from the Hexi Corridor through the Heli Shan ridge into the northern Ejina Basin. This initiated the alluvial fan progradation into the Ejina Basin. Presently the sediment bulge repels the diminishing lacustrine environment further north. In this sense, the uplift of the hinterland served as a tipping element that triggered landscape transformation in the northern Tibetan foreland (i.e. the Hexi Corridor) and further on in the adjacent northern intracontinental Ejina Basin. The onset of alluvial fan formation coincides with increased sedimentation rates on the Chinese Loess Plateau, suggesting that the Heihe alluvial fan may have served as a prominent upwind sediment source for it

A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals

National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite provides observations of total column‐averaged CO2 mole fractions (X_(CO₂)) at high spatial resolution that may enable novel constraints on surface‐atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO₂ observations and reliable representations of atmospheric transport. Since X_(CO₂) observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along‐track OCO‐2 soundings. We compare high‐pass‐filtered (<250 km, spatial scales that primarily isolate mesoscale or finer‐scale variations) along‐track spatial variability in X_(CO₂) and X_(H₂O) from OCO‐2 tracks to temporal synoptic and mesoscale variability from ground‐based X_(CO₂) and X_(H₂O) observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along‐track, high‐frequency variability for OCO‐2 X_(H₂O). For X_(CO₂), both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO‐2 retrieval state vector are important drivers of the along‐track variance budget

Calibration of sealed HCl cells used for TCCON instrumental line shape monitoring

The TCCON (Total Carbon Column Observing Network) FTIR (Fourier transform infrared) network provides highly accurate observations of greenhouse gas column-averaged dry-air mole fractions. As an important component of TCCON quality assurance, sealed cells filled with approximately 5 mbar of HCl are used for instrumental line shape (ILS) monitoring at all TCCON sites. Here, we introduce a calibration procedure for the HCl cells which employs a refillable, pressure-monitored reference cell filled with C_2H_2. Using this method, we identify variations of HCl purity between the TCCON cells as a non-negligible disturbance. The new calibration procedure introduced here assigns effective pressure values to each individual cell to account for additional broadening of the HCl lines. This approach will improve the consistency of the network by significantly reducing possible station-to-station biases due to inconsistent ILS results from different HCl cells. We demonstrate that the proposed method is accurate enough to turn the ILS uncertainty into an error source of secondary importance from the viewpoint of network consistency

Methane retrieved from TROPOMI: Improvement of the data product and validation of the first 2 years of measurements

The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor (S5-P) satellite provides methane (CH4) measurements with high accuracy and exceptional temporal and spatial resolution and sampling. TROPOMI CH$_{4}$ measurements are highly valuable to constrain emissions inventories and for trend analysis, with strict requirements on the data quality. This study describes the improvements that we have implemented to retrieve CH$_{4}$ from TROPOMI using the RemoTeC full-physics algorithm. The updated retrieval algorithm features a constant regularization scheme of the inversion that stabilizes the retrieval and yields less scatter in the data and includes a higher resolution surface altitude database. We have tested the impact of three state-of-the-art molecular spectroscopic databases (HITRAN 2008, HITRAN 2016 and Scientific Exploitation of Operational Missions – Improved Atmospheric Spectroscopy Databases SEOM-IAS) and found that SEOM-IAS provides the best fitting results. The most relevant update in the TROPOMI XCH$_{4}$ data product is the implementation of an a posteriori correction fully independent of any reference data that is more accurate and corrects for the underestimation at low surface albedo scenes and the overestimation at high surface albedo scenes. After applying the correction, the albedo dependence is removed to a large extent in the TROPOMI versus satellite (Greenhouse gases Observing SATellite – GOSAT) and TROPOMI versus ground-based observations (Total Carbon Column Observing Network – TCCON) comparison, which is an independent verification of the correction scheme. We validate 2 years of TROPOMI CH4 data that show the good agreement of the updated TROPOMI CH4 with TCCON (−3.4 ± 5.6 ppb) and GOSAT (−10.3 ± 16.8 ppb) (mean bias and standard deviation). Low- and high-albedo scenes as well as snow-covered scenes are the most challenging for the CH4 retrieval algorithm, and although the a posteriori correction accounts for most of the bias, there is a need to further investigate the underlying cause

A Geostatistical Framework for Quantifying the Imprint of Mesoscale Atmospheric Transport on Satellite Trace Gas Retrievals

National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 (OCO-2) satellite provides observations of total column-averaged CO2 mole fractions (XCO2) at high spatial resolution that may enable novel constraints on surface-atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO2 observations and reliable representations of atmospheric transport. Since XCO2 observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along-track OCO-2 soundings. We compare high-pass-filtered (<250 km, spatial scales that primarily isolate mesoscale or finer-scale variations) along-track spatial variability in XCO2 and XH2O from OCO-2 tracks to temporal synoptic and mesoscale variability from ground-based XCO2 and XH2O observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along-track, high-frequency variability for OCO-2 XH2O. For XCO2, both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO-2 retrieval state vector are important drivers of the along-track variance budget.Plain Language SummaryNumerous efforts have been made to quantify sources and sinks of atmospheric CO2 at regional spatial scales. A common approach to infer these sources and sinks requires accurate representation of variability of CO2 observations attributed to transport by weather systems. While numerical weather prediction models have a fairly reasonable representation of larger-scale weather systems, such as frontal systems, representation of smaller-scale features (<250 km), is less reliable. In this study, we find that the variability of total column-averaged CO2 observations attributed to these fine-scale weather systems accounts for up to half of the variability attributed to local sources and sinks. Here, we provide a framework for quantifying the drivers of spatial variability of atmospheric trace gases rather than simply relying on numerical weather prediction models. We use this framework to quantify potential sources of errors in measurements of total column-averaged CO2 and water vapor from National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 satellite.Key PointsWe developed a framework to relate high-frequency spatial variations to transport-induced temporal fluctuations in atmospheric tracersWe use geostatistical analysis to quantify the variance budget for XCO2 and XH2O retrieved from NASA’s OCO-2 satelliteAccounting for random errors, systematic errors, and real geophysical coherence in remotely sensed trace gas observations may yield improved flux constraintsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151988/1/jgrd55658.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151988/2/jgrd55658_am.pd