102 research outputs found
A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals
National Aeronautics and Space Administration's Orbiting Carbon Observatoryâ2 (OCOâ2) satellite provides observations of total columnâaveraged CO2 mole fractions (X_(COâ)) at high spatial resolution that may enable novel constraints on surfaceâatmosphere 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 COâ observations and reliable representations of atmospheric transport. Since X_(COâ) 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 alongâtrack OCOâ2 soundings. We compare highâpassâfiltered (<250 km, spatial scales that primarily isolate mesoscale or finerâscale variations) alongâtrack spatial variability in X_(COâ) and X_(HâO) from OCOâ2 tracks to temporal synoptic and mesoscale variability from groundâbased X_(COâ) and X_(HâO) observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of alongâtrack, highâfrequency variability for OCOâ2 X_(HâO). For X_(COâ), both mesoscale transport variability and spatially coherent bias associated with other elements of the OCOâ2 retrieval state vector are important drivers of the alongâtrack variance budget
A Geostatistical Framework for Quantifying the Imprint of Mesoscale Atmospheric Transport on Satellite Trace Gas Retrievals
National Aeronautics and Space Administrationâs 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 Administrationâs 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 NASAâs OCO-2 satelliteAccounting for random errors, systematic errors, and real geophysical coherence in remotely sensed traceĂÂ 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
A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals
National Aeronautics and Space Administration's Orbiting Carbon Observatoryâ2 (OCOâ2) satellite provides observations of total columnâaveraged CO2 mole fractions (X_(COâ)) at high spatial resolution that may enable novel constraints on surfaceâatmosphere 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 COâ observations and reliable representations of atmospheric transport. Since X_(COâ) 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 alongâtrack OCOâ2 soundings. We compare highâpassâfiltered (<250 km, spatial scales that primarily isolate mesoscale or finerâscale variations) alongâtrack spatial variability in X_(COâ) and X_(HâO) from OCOâ2 tracks to temporal synoptic and mesoscale variability from groundâbased X_(COâ) and X_(HâO) observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of alongâtrack, highâfrequency variability for OCOâ2 X_(HâO). For X_(COâ), both mesoscale transport variability and spatially coherent bias associated with other elements of the OCOâ2 retrieval state vector are important drivers of the alongâtrack variance budget
Earthquakes, Volcanoes and God: Comparative Perspectives from Christianity and Islam
This paper asserts that both Christian and Islamic traditions of faith affect the ways in which people both try to make sense of, and respond to, disasters. This contention is supported by the results of empirical research, which demonstrates that differing Islamic and Christian perspectives on human suffering caused by disasters are neither as diverse, nor are they so intractable, as is commonly supposed. Today pastoral convergence between the two traditions may also be discerned, together with a general acceptance of the policies of both State agencies and Non-Governmental Organisations (NGOs) which are concerned with hazard relief and the propagation of policies of disaster risk reduction (DRR). Indeed some important disaster relief NGOs have emerged from Islamic and Christian faith communities and are supported by charitable donations
New Labour?new renaissance
This paper explores the term ?urban renaissance? in relation to the historiography of the Renaissance of the 15th and 16th centuries in Italy. It examines the place of the Renaissance in cultural history and considers how it has, since its inception, been utilised by writers to reflect on the present. The paper situates the urban renaissance within the context of New Labour rhetoric at the time of the Millennium. It argues that the idea of renaissance can, in this instance, be connected to a kind of millenarianism that was reflected in public rhetoric regarding the city and in a number of building projects
Splendor and misery of adaptation, or the importance of neutral null for understanding evolution
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