Ozone deposition, scalar budgets and radiative heating over Texas coastal forest and ocean

April 1986.Includes bibliographical references.Sponsored by the National Science Foundation ATM-8114575.Sponsored by the National Science Foundation ATM 8312615

Chemistry and dynamics of marine stratocumulus, The

September, 1988.Bibliography: pages [82]-91

Global CO2 Distributions over Land from the Greenhouse Gases Observing Satellite (GOSAT)

January 2009 saw the successful launch of the first space-based mission specifically designed for measuring greenhouse gases, the Japanese Greenhouse gases Observing SATellite (GOSAT). We present global land maps (Level 3 data) of column-averaged CO2 concentrations (X(sub CO2)) derived using observations from the GOSAT ACOS retrieval algorithm, for July through December 2009. The applied geostatistical mapping approach makes it possible to generate maps at high spatial and temporal resolutions that include uncertainty measures and that are derived directly from the Level 2 observations, without invoking an atmospheric transport model or estimates of CO2 uptake and emissions. As such, they are particularly well suited for comparison studies. Results show that the Level 3 maps for July to December 2009 on a lO x 1.250 grid, at six-day resolution capture much of the synoptic scale and regional variability of X(sub CO2), in addition to its overall seasonality. The uncertainty estimates, which reflect local data coverage, X(sub CO2) variability, and retrieval errors, indicate that the Southern latitudes are relatively well-constrained, while the Sahara Desert and the high Northern latitudes are weakly-constrained. A probabilistic comparison to the PCTM/GEOS-5/CASA-GFED model reveals that the most statistically significant discrepancies occur in South America in July and August, and central Asia in September to December. While still preliminary, these results illustrate the usefulness of a high spatiotemporal resolution, data-driven Level 3 data product for direct interpretation and comparison of satellite observations of highly dynamic parameters such as atmospheric CO2

Detectability of CO2 flux signals by a space‐based lidar mission

Satellite observations of carbon dioxide (CO2) offer novel and distinctive opportunities for improving our quantitative understanding of the carbon cycle. Prospective observations include those from space‐based lidar such as the active sensing of CO2 emissions over nights, days, and seasons (ASCENDS) mission. Here we explore the ability of such a mission to detect regional changes in CO2 fluxes. We investigate these using three prototypical case studies, namely, the thawing of permafrost in the northern high latitudes, the shifting of fossil fuel emissions from Europe to China, and changes in the source/sink characteristics of the Southern Ocean. These three scenarios were used to design signal detection studies to investigate the ability to detect the unfolding of these scenarios compared to a baseline scenario. Results indicate that the ASCENDS mission could detect the types of signals investigated in this study, with the caveat that the study is based on some simplifying assumptions. The permafrost thawing flux perturbation is readily detectable at a high level of significance. The fossil fuel emission detectability is directly related to the strength of the signal and the level of measurement noise. For a nominal (lower) fossil fuel emission signal, only the idealized noise‐free instrument test case produces a clearly detectable signal, while experiments with more realistic noise levels capture the signal only in the higher (exaggerated) signal case. For the Southern Ocean scenario, differences due to the natural variability in the El Niño–Southern Oscillation climatic mode are primarily detectable as a zonal increase.Key PointsDetectability of regional changes in CO2 fluxes by space‐based lidarPermafrost thawing flux perturbation readily detectable by ASCENDS‐like missionSouthern Ocean ENSO‐related flux variability detectable as zonal changePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110893/1/jgrd51945.pd

Detectability of CO2 Flux Signals by a Space-Based Lidar Mission

Satellite observations of carbon dioxide (CO2) offer novel and distinctive opportunities for improving our quantitative understanding of the carbon cycle. Prospective observations include those from space-based lidar such as the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. Here we explore the ability of such a mission to detect regional changes in CO2 fluxes. We investigate these using three prototypical case studies, namely the thawing of permafrost in the Northern High Latitudes, the shifting of fossil fuel emissions from Europe to China, and changes in the source-sink characteristics of the Southern Ocean. These three scenarios were used to design signal detection studies to investigate the ability to detect the unfolding of these scenarios compared to a baseline scenario. Results indicate that the ASCENDS mission could detect the types of signals investigated in this study, with the caveat that the study is based on some simplifying assumptions. The permafrost thawing flux perturbation is readily detectable at a high level of significance. The fossil fuel emission detectability is directly related to the strength of the signal and the level of measurement noise. For a nominal (lower) fossil fuel emission signal, only the idealized noise-free instrument test case produces a clearly detectable signal, while experiments with more realistic noise levels capture the signal only in the higher (exaggerated) signal case. For the Southern Ocean scenario, differences due to the natural variability in the ENSO climatic mode are primarily detectable as a zonal increase

An Inversion Analysis of Recent Variability in Natural CO2 Fluxes Using GOSAT and In Situ Observations

About one-half of the global CO2 emissions from fossil fuel combustion and deforestation accumulates in the atmosphere, where it contributes to global warming. The rest is taken up by vegetation and the ocean. The precise contribution of the two sinks, and their location and year-to-year variability are, however, not well understood. We use two different approaches, batch Bayesian synthesis inversion and variational data assimilation, to deduce the global spatiotemporal distributions of CO2 fluxes during 2009-2010. One of our objectives is to assess different sources of uncertainties in inferred fluxes, including uncertainties in prior flux estimates and observations, and differences in inversion techniques. For prior constraints, we utilize fluxes and uncertainties from the CASA-GFED model of the terrestrial biosphere and biomass burning driven by satellite observations and interannually varying meteorology. We also use measurement-based ocean flux estimates and two sets of fixed fossil CO2 emissions. Here, our inversions incorporate column CO2 measurements from the GOSAT satellite (ACOS retrieval, filtered and bias-corrected) and in situ observations (individual flask and afternoon-average continuous observations) to estimate fluxes in 108 regions over 8-day intervals for the batch inversion and at 3 x 3.75 weekly for the variational system. Relationships between fluxes and atmospheric concentrations are derived consistently for the two inversion systems using the PCTM atmospheric transport model driven by meteorology from the MERRA reanalysis. We compare the posterior fluxes and uncertainties derived using different data sets and the two inversion approaches, and evaluate the posterior atmospheric concentrations against independent data including aircraft measurements. The optimized fluxes generally resemble those from other studies. For example, the results indicate that the terrestrial biosphere is a net CO2 sink, and a GOSAT-only inversion suggests a shift in the global sink from the tropics south to the north relative to the prior and to an in-situ-only inversion. We also find a smaller terrestrial sink in higher-latitude northern regions in boreal summer of 2010 relative to 2009

When Will the Antarctic Ozone Hole Recover?

The Antarctic ozone hole demonstrates large-scale, man-made affects on our atmosphere. Surface observations now show that human produced ozone depleting substances (ODSs) are declining. The ozone hole should soon start to diminish because of this decline. Herein we demonstrate an ozone hole parametric model. This model is based upon: 1) a new algorithm for estimating C1 and Br levels over Antarctica and 2) late-spring Antarctic stratospheric temperatures. This parametric model explains 95% of the ozone hole area s variance. We use future ODS levels to predict ozone hole recovery. Full recovery to 1980 levels will occur in approximately 2068. The ozone hole area will very slowly decline over the next 2 decades. Detection of a statistically significant decrease of area will not occur until approximately 2024. We further show that nominal Antarctic stratospheric greenhouse gas forced temperature change should have a small impact on the ozone hole

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments

On the ability of space-based passive and active remote sensing observations of CO2 to detect flux perturbations to the carbon cycle

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Atmospheres 123 (2018): 1460–1477, doi:10.1002/2017JD027836.Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT and OCO-2, however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint.NASA Grant Numbers: NNX15AJ27G, NNX15AH13G2018-07-2

Prospects for Precision Measurement of CO2 Column from Space

In order to address the problem of sources and sinks of CO2 measurements are needed on a global scale. Clearly a satellite is a promising approach to meeting this requirement. Unfortunately, most methods for making a CO2 measurement from space involve the whole column. Since sources and sinks at the surface represent a small perturbation to the total column one is faced with the need to measure the column with a precision better than 1%. No species has ever been measured from space at this level. We have developed over the last 3 years a small instrument based upon a Fabry-Perot interferometer that is very sensitive to atmospheric CO2 and has a high signal to noise ratio. We have tested this instrument in a ground based configuration and from aircraft platforms simulating operation from a satellite. We will present results from these tests and discuss ways that this promising new instrument could be used to improve our understanding of the global carbon budget