Contrast Between 1992 and 1997 High Latitude Spring Haloe Observations of Lower Stratospheric HCl

HCl measurements from HALOE in the northern hemisphere during mid-May 1997 revealed vortex fragments in which the chlorine reservoir partitioning was strongly pushed toward HCl (approx. 90% HCl, approx. 10% ClONO2), similar to partitioning previously observed in the Antarctic vortex region. In contrast, observations of ClONO2 and HCl in the northern polar spring, 1992, and in other years, show these species established the balance typical for gas phase photochemical reactions in this region (approx. 60% HCl, approx. 40% ClONO2). Annually, chlorine reservoirs in the winter lower stratosphere polar vortex are converted to chlorine radicals via heterogeneous reactions on particle surfaces at very cold temperatures (less than about 200 K). As temperatures warm in spring, the heterogeneous processes become insignificant compared with gas phase reactions, and the chlorine reservoirs are reformed. Measurements through the northern winter/spring in 1992 show rapid formation of ClONO2, followed by steady loss of ClONO2 and increasing HCl. Although ClONO2 measurements are not available for 1997, the HCl increase in 1997 is observed to be much more rapid and the eventual HCl mixing ratio is about 50% greater than that of 1992. The observations are examined through comparison with the Goddard three-dimensional chemistry and transport model. This model utilizes winds and temperatures from the Goddard Earth Observing System Data Assimilation System and a complete integration scheme for stratospheric photochemistry. Analysis of the evolution of HCl and ClONO2 shows that the observed difference in the overall rate of HCl formation is explained by the sensitivity of the gas-phase chemistry to the ozone mixing ratio and the temperature. The results show that the model accurately simulates HCl and ClONO2 evolution during these two winters. Model validity is further supported by comparisons with O3 and reactive nitrogen species NO and NO2. This analysis provides a sensitive test of the lower stratospheric chlorine photochemistry, particularly because the analysis considers constituent evolution at a time when the HCl and ClONO2 are far from a photochemical stationary state

Fall vortex ozone as a predictor of springtime total ozone at high northern latitudes

Understanding the impact of atmospheric dynamical variability on observed changes in stratospheric O₃ is a key to understanding how O₃ will change with future climate dynamics and trace gas abundances. In this paper we examine the linkage between interannual variability in total column O₃ at northern high latitudes in March and lower-to-mid stratospheric vortex O₃ in the prior November. We find that these two quantities are significantly correlated in the years available from TOMS, SBUV, and POAM data (1978-2004). Additionally, we find that the increase in March O₃ variability from the 1980s to years post-1990 is also seen in the November vortex O₃, i.e., interannual variability in both quantities is much larger in the later years. The cause of this correlation is not clear, however. Interannual variations in March total O₃ are known to correspond closely with variations in winter stratospheric wave driving consistent with the effects of varying residual circulation, temperature, and chemical loss. Variation in November vortex O₃ may also depend on dynamical wave activity, but the dynamics in fall are less variable than in winter and spring. We do not find significant correlations of dynamic indicators for November such as temperature, heat flux, or polar average total O₃ with the November vortex O₃, nor with dynamical indicators later in winter and spring that might lead to a connection to March. We discuss several potential hypotheses for the observed correlation but do not find strong evidence for any considered mechanism. We present the observations as a phenomenon whose understanding may improve our ability to predict the dependence of O₃ on changing dynamics and chemistry

The Ability of GeoCarb to Constrain the Interannual Variability of Carbon Gases over the Amazon

We perform a number of idealized assimilation experiments with the GEOS constituent data assimilation system to test the ability of GeoCarb retrievals of CO, CO2, and CH4 to constrain the interannual variability of these gases over the Amazon. Retrievals for instruments on other satellites which observe in similar channels (e.g. MOPITT, GOSAT, and OCO-2) are limited due to persistent cloud coverage. Given its ability to sample the same location multiple times in one day, the expectation is that GeoCarb retrievals will return more soundings than those from previous missions. The goal of the assimilation experiments is to understand which scanning strategies lead to the best sounding densities and thus have the best chance of constraining interannual variability in the carbon species. The experiments each begin by picking a given year at random from a nature run (i.e., a model simulation meant to represent the truth). The model fields are sampled according to a given strategy and then screened to account for cloud coverage. Next, we pick another year at random and assimilate the synthetic GeoCarb samples into the GEOS model for that year. The output of the assimilation, 6-hourly, 3D fields of each constituent, is then directly comparable to the nature run. This comparison allows us to evaluate the ability of GeoCarb measurements to constrain the interannual variability of each gas

Using CO 2 spatial variability to quantify representation errors of satellite CO 2 retrievals

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95625/1/grl24793.pd

Comparing Global Atmospheric CO2 Flux and Transport Models with Remote Sensing (and Other) Observations

We report recent progress derived from comparison of global CO2 flux and transport models with new remote sensing and other sources of CO2 data including those from satellite. The overall objective of this activity is to improve the process models that represent our understanding of the workings of the atmospheric carbon cycle. Model estimates of CO2 surface flux and atmospheric transport processes are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, to provide the basic framework for carbon data assimilation, and ultimately for future projections of carbon-climate interactions. Models can also be used to test consistency within and between CO2 data sets under varying geophysical states. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 2000 through 2009. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-3), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to remote sensing observations from TCCON, GOSAT, and AIRS as well as relevant in situ observations. Examples of the influence of key process representations are shown from both forward and inverse model comparisons. We find that the model can resolve much of the synoptic, seasonal, and interannual variability in the observations, although reasons for persistent discrepancies in northern hemisphere vegetation uptake are examined. At this time, we do not find any serious shortcomings in the model transport representation, but this is still the subject of close scrutiny. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in CO2 fluxes and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time

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

Finding the Missing Stratospheric Br(sub y): A Global Modeling Study of CHBr3 and CH2Br2

Recent in situ and satellite measurements suggest a contribution of ~5 pptv to stratospheric inorganic bromine from short-lived bromocarbons. We conduct a modeling study of the two most important short-lived bromocarbons, bromoform (CHBr3) and dibromomethane (CH2Br2), with the Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) to account for this missing stratospheric bromine. We derive a "top-down" emission estimate of CHBr3 and CH2Br2 using airborne measurements in the Pacific and North American troposphere and lower stratosphere obtained during previous NASA aircraft campaigns. Our emission estimate suggests that to reproduce the observed concentrations in the free troposphere, a global oceanic emission of 425 Gg Br yr(exp -1) for CHBr3 and 57 Gg Br yr(exp -l) for CH2Br2 is needed, with 60% of emissions from open ocean and 40% from coastal regions. Although our simple emission scheme assumes no seasonal variations, the model reproduces the observed seasonal variations of the short-lived bromocarbons with high concentrations in winter and low concentrations in summer. This indicates that the seasonality of short-lived bromocarbons is largely due to seasonality in their chemical loss and transport. The inclusion of CHBr3 and CH2Br2 contributes ~5 pptv bromine throughout the stratosphere. Both the source gases and inorganic bromine produced from source gas degradation (Br~SLS) in the troposphere are transported into the stratosphere, and are equally important. Inorganic bromine accounts for half (2.5 pptv) of the bromine from the inclusion of CHBr3 and CHzBr2 near the tropical tropopause and its contribution rapidly increases to ~ 100% as altitude increases. More than 85% of the wet scavenging of Br(sub y)(sup VSLS) occurs in large-scale precipitation below 500 hPa. Our sensitivity study with wet scavenging in convective updrafts switched off suggests that Br(sub y)(sup SLS) in the stratosphere is not sensitive to convection. Convective scavenging only accounts for ~0.2 pptv (4%) difference in inorganic bromine delivered to the stratosphere

Sensitivity of CO2 Simulation in a GCM to the Convective Transport Algorithms

Convection plays an important role in the transport of heat, moisture and trace gases. In this study, we simulated CO2 concentrations with an atmospheric general circulation model (GCM). Three different convective transport algorithms were used. One is a modified Arakawa-Shubert scheme that was native to the GCM; two others used in two off-line chemical transport models (CTMs) were added to the GCM here for comparison purposes. Advanced CO2 surfaced fluxes were used for the simulations. The results were compared to a large quantity of CO2 observation data. We find that the simulation results are sensitive to the convective transport algorithms. Overall, the three simulations are quite realistic and similar to each other in the remote marine regions, but are significantly different in some land regions with strong fluxes such as Amazon and Siberia during the convection seasons. Large biases against CO2 measurements are found in these regions in the control run, which uses the original GCM. The simulation with the simple diffusive algorithm is better. The difference of the two simulations is related to the very different convective transport speed

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