Understanding Well-being Data

‘Following the data’ is a now-familiar phrase in Covid-19 policy communications. Well-being data are pivotal in decisions that affect our life chances, livelihoods and quality of life. They are increasingly valuable to companies with their eyes on profit, organisations looking to make a social impact, and governments focussed on societal problems. This book follows well-being data back centuries, showing they have long been used to track the health and wealth of society. It questions assumptions that have underpinned over 200 years of social science, statistical and policy work. Understanding Well-being Data is a readable, introductory book with real-life examples. Understanding the contexts of data and decision-making are critical for policy, practice and research that aims to do good, or at least avoid harm. Through its comprehensive survey and critical lens, this book provides tools to promote better understanding of the power and potential of well-being data for society, and the limits of their application

Chemistry Simulations Using MERRA-2 Reanalysis with the GMI CTM and Replay in Support of the Atmospheric Composition Community

Simulations using reanalyzed meteorological conditions have been long used to understand causes of atmospheric composition change over the recent past. Using the new Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorology, chemistry simulations are being conducted to create products covering 1980-2016 for the atmospheric composition community. These simulations use the Global Modeling Initiative (GMI) chemical mechanism in two different models: the GMI Chemical Transport Model (CTM) and the GEOS-5 model developed Replay mode. Replay mode means an integration of the GEOS-5 general circulation model that is incrementally adjusted each time step toward the MERRA-2 analysis. The GMI CTM is a 1 x 1.25 simulation and the MERRA-2 GMI Replay simulation uses the native MERRA-2 approximately horizontal resolution on the cubed sphere. The Replay simulations is driven by the online use of key MERRA-2 meteorological variables (i.e. U, V, T, and surface pressure) with all other variables calculated in response to those variables. A specialized set of transport diagnostics is included in both runs to better understand trace gas transport and changes over the recent past

Joining up well-being and sexual misconduct data and policy in HE: ‘to stand in the gap’ as a feminist approach

This article joins up evidence and policy relating to two linked concerns in higher education (HE) that are treated as unrelated: postgraduate research student (PGR) well-being, and staff sexual misconduct towards students. Against the standard methodology of systematic reviews, we build on feminist approaches to apply a ‘re-performance’ approach to the review. Re-performance re-enacts established methods, contextualising previous analysis through ethnographic and desk-based research, exposing gaps in evidence, analysis, representation, care and policy. We reveal how aspects of PGR experience, particularly the cultures that engender ill-being and enable sexual misconduct, are silenced in evidence-making. Our ‘re-performance’ uncovers how this occurs in three ways, through: the (mis)construction of the ‘typical student’ in well-being literatures; the (mis)construction of the phenomenon of ‘well-being’ exacerbated by generic survey tools focusing on a medicalised model of mental health; the (mis)construction of HE institutions as integrated, agential and ethical, aided by the fragmentation of administrative systems and knowledge production between disciplines. Together, these organising modes conceal lack of care, staff sexual misconduct and poor well-being. From these findings, specific policy issues are identified: the risks to giving more responsibility to supervisors for PGR well-being; a pattern of institutional listening while silencing; and the need to explore feedback loops between patterns of vulnerability to ill-being and staff sexual misconduct. Through our analysis, the article demonstrates how to ‘stand in the gaps’ – between knowledges; and between evidence and action; between policy and care – in a way that can be generalised across policy domains, epistemologies and policy-making contexts

The Impact of New Estimates of Mixing Ratio and Flux-based Halogen Scenarios on Ozone Evolution

The evolution of ozone in the 21st century has been shown to be mainly impacted by the halogen emissions scenario and predicted changes in the circulation of the stratosphere. New estimates of mixing ratio and flux-based emission scenarios have been produced from the SPARC Lifetime Assessment 2013. Simulations using the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) are conducted using this new A1 2014 halogen scenario and compared to ones using the A1 2010 scenario. This updated version of GEOSCCM includes a realistic representation of the Quasi-Biennial Oscillation and improvements related to the break up of the Antarctic polar vortex. We will present results of the ozone evolution over the recent past and 21st century to the A1 2010, A1 2014 mixing ratio, and an A1 2014 flux-based halogen scenario. Implications of the uncertainties in these estimates as well as those from possible circulation changes will be discussed

Evaluation of MERRA-2-Based Ozone Profile Simulations with the Global Ozonesonde Network

Chemical transport model (CTM) hindcasts of ozone (O3) are useful for filling in observational gaps and providing context for observed O3 variability and trends. We use global networks of ozonesonde stations to evaluate the O3 profiles in two simulations running versions of the NASA Global Modeling Initiative (GMI) chemical mechanism. Both simulations are tied to the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) meteorological reanalysis: 1) The GMI CTM, and 2) The MERRA-2 GMI Replay (M2 GMI). Both simulations start in 1980, and are compared against >50,000 ozonesonde profiles from 37 global stations from the tropics to the poles. The comparisons allow us to evaluate how the Replay technique affects modeled O3 distribution, how an updated chemical mechanism in the GMI CTM affects simulated tropospheric O3 amounts, and how observed O3 distributions compare to the full set of model output. In general, M2 GMI O3 is ~10% higher than in the GMI CTM, and shows global near-surface and tropical upper troposphere/lower stratosphere (UT/LS) high biases. The updated chemical mechanism in the GMI CTM reduces these high biases. Both simulations show similar negative biases in tropical free-tropospheric O3, especially during typical biomass burning seasons. The simulations are highly-correlated with ozonesonde measurements, particularly in the UT/LS (r > 0.8), showing the ability of MERRA-2 to capture tropopause height variations. Both simulations show improved correlations with ozonesonde data and smaller O3 biases in recent years. We expect to use the sonde/model comparisons to diagnose causes of disagreement and to gauge the feasibility of calculating multidecadal O3 trends from the model output

Understanding Differences in the Response to Composition Change as Simulated by CCMVal Models

Chemistry climate models (CCMs) have a common conceptual basis. Differences in implementation lead to differences in the stratospheric ozone response to changes in composition and climate. Although evaluation by CCMVal-2 identified strengths and weaknesses of participant models, the evaluation results were not used to discriminate among projections for future ozone evolution, at least in part because the overall diagnostic evaluation did not cleanly relate to the differences in CCM response. Here we use a subset of CCMVal diagnostics and additional analysis to understand the differences in response. In the upper stratosphere, differences in simulated temperature and total odd nitrogen prior to increases in chlorine loading explain the large differences in CCM sensitivity. In the lower atmosphere, there are two principle contributions to differences in CCM sensitivity to chlorine and climate change. First, differences in the lower stratospheric ClO affect simulated sensitivity to chlorine. CCMs with best transport performance match NDACC column HCl measurements at a broad range of latitudes. Other CCMs disagree with observations due to differences in total inorganic chlorine, partitioning between HCl and ClONO2, or both. Differences in ClONO2 are directly related to differences in simulated ClO. Second, although all CCMs predict increased tropical upwelling, the rate of increase varies and contributes to differences in tropical ozone and the 60N-60S column average

Large-Scale Atmospheric Transport in GEOS Replay Simulations

Offline chemical transport models (CTMs) have traditionally been used to perform studies of atmospheric chemistry in a fixed dynamical environment. An alternative to using CTMs is to constrain the flow in a general circulation model using winds from meteorological analyses. The Goddard Earth Observing System (GEOS) "replay" approach involves reading in analyzed fields every six hours and recomputing the analysis increments, which are applied as a forcing to the meteorology at every model time step. Unlike in CTM, all of the subgrid-scale processes are recalculated on-line so that they are consistent with the large-scale analysis fields, similar in spirit to "nudged" simulations, in which the online meteorology is relaxed to the analysis. Here we compare the transport of idealized tracers in different replay simulations constrained with meteorological fields taken from The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). We show that there are substantial differences in their large-scale stratospheric transport, depending on whether analysis fields or assimilated fields are used. Replay simulations constrained with the instantaneous analysis fields produce stratospheric mean age values that are up to 30% too young relative to observations; by comparison, simulations constrained with the time-averaged assimilated fields produce more credible stratospheric transport. Our study indicates that care should be taken to correctly configure the model when the replay technique is used to simulate stratospheric composition

A Cloud-Ozone Data Product from Aura OMI and MLS Satellite Measurements

Ozone within deep convective clouds is controlled by several factors involving photochemical reactions and transport. Gas-phase photochemical reactions and heterogeneous surface chemical reactions involving ice, water particles, and aerosols inside the clouds all contribute to the distribution and net production and loss of ozone. Ozone in clouds is also dependent on convective transport that carries low troposphereboundary layer ozone and ozone precursors upward into the clouds. Characterizing ozone in thick clouds is an important step for quantifying relationships of ozone with tropospheric H2O, OH production, and cloud microphysicstransport properties. Although measuring ozone in deep convective clouds from either aircraft or balloon ozonesondes is largely impossible due to extreme meteorological conditions associated with these clouds, it is possible to estimate ozone in thick clouds using backscattered solar UV radiation measured by satellite instruments. Our study combines Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) satellite measurements to generate a new research product of monthly-mean ozone concentrations in deep convective clouds between 30oS to 30oN for October 2004 April 2016. These measurements represent mean ozone concentration primarily in the upper levels of thick clouds and reveal key features of cloud ozone including: persistent low ozone concentrations in the tropical Pacific of 10 ppbv or less; concentrations of up to 60 pphv or greater over landmass regions of South America, southern Africa, Australia, and Indiaeast Asia; connections with tropical ENSO events; and intra-seasonalMadden-Julian Oscillation variability. Analysis of OMI aerosol measurements suggests a cause and effect relation between boundary layer pollution and elevated ozone inside thick clouds over land-mass regions including southern Africa and Indiaeast Asia

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

Chemical Mechanisms and their Applications in the Goddard Earth Observing System (GEOS) Earth System Model

NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM) and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth-System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace-gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This manuscript describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided