Atmospheric Methane in GEOS-5: Development of the Methane Module in GEOS, Current Status and Planned Capabilities
No abstract available
Chatterjee, Abhishek↗
Engineering topics
Weir, B.
Publications and source records attributed to Weir, B..
Joint Assimilation of the Aura Microwave Limb Sounder and Ozone Mapping and Profiler Suite Limb Profiler Data: Towards a Reanalysis of Stratospheric Ozone for Trend Studies
The future trajectory of the stratospheric ozone recovery will be sensitive to greenhouse gas concentrations through thermal control of chemical loss and via stratospheric circulation changes. The latter in particular is subject to considerable uncertainty meriting continuing monitoring of the evolution of ozone throughout the depth of the stratosphere. Atmospheric reanalyses utilize the data assimilation methodology to obtain comprehensive representations of the state of the atmosphere, including its composition, on multidecadal scales by combining diverse measurements from satellite-borne and conventional data sources. Systematic biases among these various data types pose a challenge for assimilation by introducing spurious discontinuities that affect the utility of reanalyses for studies of long-term variability and trends.In this presentation we will outline an approach, developed at NASA's Global Modeling and Assimilation Office (GMAO), that allows joint assimilation of stratospheric ozone profiles from the Microwave Limb Sounder (MLS) on EOS Aura and the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) currently flying on the Suomi-NPP satellite with future missions projected into the 2030s. We will demonstrate that a simple offline correction significantly reduces biases between MLS and OMPS-LP ozone data providing a strategy for generating a long-term vertically resolved homogenized representation of stratospheric ozone in future reanalyses. One novel element of our approach compared to previous GMAO reanalysis is the use of a version of the Goddard Earth Observing System model with full stratospheric chemistry. We will show selected comparisons of MLS and OMPS-LP assimilation experiments with independent ozonesonde and satellite data as well as two examples of process-based evaluation focused on the 2016 QBO disruption and Arctic winter ozone loss focusing on the relative performance of the MLS and OMPS-LP analyses.
Wargan, K.↗
Establishing Calibration Standards for Remote Sensing Retrievals of Greenhouse Gases
While in situ greenhouse gas measurements have a concrete calibration standard, establishing a similar standard for remote sensing retrievals remains challenging. As the constellation of greenhouse gas observing satellites grows, such a standard is essential to ensure data are of the quality necessary to support scientific and policy applications. A primary goal of NASA's Atmospheric Carbon and Transport (ACT) - America aircraft campaign is to evaluate column CO2 retrievals from the Orbiting Carbon Observatory 2 (OCO-2) through coordinated underflights. The campaign also includes airborne lidar instruments that measure the amount of CO2 and CH4 below the aircraft. This presentation introduces a system that establishes calibration standards for OCO-2 and lidar retrievals based on in situ data from the ACT-America campaign. The system assimilates the in situ data into NASA's Goddard Earth Observing System (GEOS) to produce high-resolution, two-dimensional transects of CO2 along the flight path which we refer to as curtains. Excluding the ability to sample the entire atmosphere at once, any such analysis must make assumptions about the connection of measurements at different places and times to a given retrieval. We chose to use the GEOS general circulation model forced by meteorology from its data assimilation system because their scientific merits are extensively documented. Furthermore, in areas rich in data, the assimilated curtains approach a field constrained by data alone. Where data are lacking, e.g., the stratosphere, age of air and other transport diagnostics can be used to quantify the uncertainty introduced by the model. Given these uncertainties, we can determine the uncertainties of the curtains and thus our ability to evaluate remote sensing instruments. Here, we demonstrate this for several flights over North America and discuss possible applications to upcoming missions, e.g., GeoCarb.
Weir, B.↗
GEOS-Carb III: Delivering Mature Carbon Flux and Concentration Datasets in Support of NASA's Carbon Monitoring System
The GEOS-Carb project seeks to make high quality, data-driven products that support NASA's Carbon Monitoring System Program. These include bottom-up land and ocean flux estimates along with fossil fuel emissions, all informed by satellite data and the MERRA-2 reanalysis. These flux data support atmospheric carbon products that include both simulations and data assimilation products. We show examples of this work and discuss applications to future mission planning.
Ott, L.↗
The Use of Satellite Limb Observations of the Stratosphere in NASA's Reanalyses
No abstract available
Wargan, K.↗
Progress in Atmospheric Carbon Monitoring Using NASA's GEOS Model and Data from the OCO and GOSAT Missions
NASA's Global Modeling and Assimilation Office (GMAO) produces a variety of carbon products based the synthesis of satellite remote sensing data and outputs of the Goddard Earth Observing System (GEOS). This includes bottom-up surface fluxes due to fossil fuel emissions, biomass burning, terrestrial biospheric exchange, and ocean exchangeconstrained by measurements of nighttime lights, fire radiative power, normalized difference vegetation index, and ocean color. These fluxes are the basis of top-down estimates of carbon concentrations and fluxes. In particular, the GMAO system processes retrievals of column carbon dioxide (XCO2) from GOSAT and OCO-2 to produce a high-resolution, long-term global analysis of CO2 in three dimensions every 6 hours. Here, we discuss the potential applications of such products for satellite intercomparison and evaluation against independent, non-coincident data. We also highlight the ability to provide monthly global atmospheric growth rates inferred from the assimilated CO2 concentration product. Finally, we discuss the challenges facing such products including bias correction and the estimation and analysis of model transport errors.
Weir, B.↗
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.
Weir, B.↗
Improving NASA GEOS Atmospheric CO2 Simulations by Calibrating CASA Surface Fluxes with an Empirical Sink
With the adoption of the Paris climate accord, efforts to monitor and understand both anthropogenic and natural carbon sources and sinks are increasing across the world. Given their low latency and global coverage, satellite observations of atmospheric carbon dioxide (CO2) are poised to make important contributions to this field. The combination of satellite data and high resolution global models can be used to monitor changes in carbon fluxes and to evaluate the consistency of nationally reported emissions estimates in support of multiple stakeholder communities. However, a consistent challenge to such work has been the high latency of surface carbon flux estimates, which are often not available for a year or more. This presentation describes the construction of surface carbon flux estimates meant to improve the near real time simulation of atmospheric CO2 with NASA's Goddard Earth Observing System (GEOS) general circulation model. The surface flux estimates begin with a collection of bottom-up fluxes which incorporate satellite measurements in their construction, e.g. vegetation indices in the Carnegie-Ames-Stanford Approach (CASA) and nighttime lights in the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). From there, we take the additional step of using an empirical sink to calibrate terrestrial net biospheric exchange (NBE) to estimated values from atmospheric inversion systems. This approach removes a known, systematic bias in predicted atmospheric mixing ratios. Using these fluxes in a free running simulation, the model is able to reproduce in situ measurements with the same skill as when it uses gridded fluxes from a flux inversion system. Using these fluxes as a prior in an assimilation system, e.g. one incorporating retrievals of column CO2 from the Orbiting Carbon Observatory 2 (OCO-2), allows the analysis to capture variability in CO2 on scales that would be missed otherwise. This approach supports NASA's capability to forecast atmospheric CO2 up to two weeks in advance by leveraging a GEOS system used to produce quasi-operational weather analyses and forecasts, providing a valuable new tool to the carbon monitoring research and applications communities.
Weir, B.↗
Tracer Transport Differences: Challenges and Implications for Flux Inversions
This poster demonstrates that different chemistry transport models (CTMs), each extensively validated, can have significant differences in the predicted transport of long-lived trace gases. For carbon dioxide (CO2), this difference is 0.5 ppm or greater in the total column. The value exceeds the nominal retrieval error requirements of the Total Carbon Column Observing Network (TCCON) and the Orbiting Carbon Observatory 2 (OCO-2), which were chosen based on the understanding of the accuracy necessary to infer surface fluxes of CO2 on regional and seasonal scales. This suggests that the transport errors of CTMs play a considerable role in the surface flux inversion of satellite-based measurements of long-lived trace gases and the interpretation of the inferred fluxes requires a careful understanding of this role.
Weir, B.↗
Views from the 6 Aircraft Campaigns: ACT-America, HIPPO, CONTRAIL, ATom, ORCAS, and ABoVE
This presentation describes the assimilation of airborne measurements of carbon dioxide (CO2) into the Goddard Earth Observing System (GEOS) general circulation model. The main goal is to construct observationally constrained fields of CO2 starting from the bottom of the atmosphere and extending through the entire vertical column. These fields can then be compared directly to retrievals of column CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory 2 (OCO-2) by using the averaging kernel and a priori profile. This approach does not equire a direct satellite overpass, but rather an overpass of the much broader region impacted by the assimilation, which alleviates some of the jeopardy of coordinating flights with satellite tracks. Furthermore, checking if the story stays the same or if it changes when the unassimilated fields are compared to the satellite soundings allows us to separate model errors from retrieval errors. This work attempts to answer a number of questions including: What are the possible causes of systematic differences between model and satellite XCO2 over the Pacific Ocean? What is the contribution of tratospheric uncertainty to XCO2 errors? What is the impact of errors in boundary layer physics on modeled XCO2?
Weir, B.↗
An 8-Year, High-Resolution Reanalysis of Atmospheric CO2 Mixing Ratios Based on OCO-2 and GOSAT-ACOS Retrievals
The NASA GMAO (Global Modeling and Assimilation Office) reanalysis blends OCO-2 (Orbiting Carbon Observatory 2) and GOSAT-ACOS (Greenhouse Gases Observing Satellite-Atmospheric Carbon Observations from Space) retrievals (top) with GEOS (Goddard Earth Observing System) model predictions (bottom) to estimate the full 3D (three-dimensional) state of CO2 every 3 hours (middle). This poster describes monthly atmospheric growth rates derived from the reanalysis and an application to aircraft data with the potential to aid bias correction.
GEOS-Carb↗
The 2015-2016 El Nino and the Response of the Carbon Cycle: Findings from NASA's OCO-2 Mission
The El Nino Southern Oscillation (ENSO) is the most important mode of tropical climate variability on interannual to decadal time scales. Correlations between atmospheric CO2 growth rate and ENSO activity are relatively well known but the magnitude of this correlation, the contribution from tropical marine vs. terrestrial flux components, and the causal mechanisms, are poorly constrained in space and time. The launch of NASA's Orbiting Carbon Observatory-2 (OCO-2) mission in July 2014 was rather timely given the development of strong ENSO conditions over the tropical Pacific Ocean in 2015-2016. In this presentation, we will discuss how the high-density observations from OCO-2 provided us with a novel dataset to resolve the linkages between El Nino and atmospheric CO2. Along with information from in situ observations of ÎpCO2 from NOAA's Tropical Atmosphere Ocean (TAO) project and atmospheric CO2 from the Scripps CO2 Program, and other remote-sensing missions, we are able to piece together the time dependent response of atmospheric CO2 concentrations over the Tropics. Our findings confirm the hypothesis from studies following the 1997-1998 El Nino event that an early reduction in CO2 outgassing from the tropical Pacific Ocean is later reversed by enhanced net CO2 emissions from the terrestrial biosphere. This implies that a component of the interannual variability (IAV) in the growth rate of atmospheric CO2, which has typically been used to constrain the climate sensitivity of tropical land carbon fluxes, is strongly influenced and modified by ocean fluxes during the early phase of the ENSO event. Our analyses shed further light on the understanding of the marine vs. terrestrial partitioning of tropical carbon fluxes during El Nino events, their relative contributions to the global atmospheric CO2 growth rate, and provide clues about the sensitivity of the carbon cycle to climate forcing on interannual time scales.
CO2↗