Background error covariance estimation for atmospheric CO 2 data assimilation

In any data assimilation framework, the background error covariance statistics play the critical role of filtering the observed information and determining the quality of the analysis. For atmospheric CO 2 data assimilation, however, the background errors cannot be prescribed via traditional forecast or ensemble‐based techniques as these fail to account for the uncertainties in the carbon emissions and uptake, or for the errors associated with the CO 2 transport model. We propose an approach where the differences between two modeled CO 2 concentration fields, based on different but plausible CO 2 flux distributions and atmospheric transport models, are used as a proxy for the statistics of the background errors. The resulting error statistics: (1) vary regionally and seasonally to better capture the uncertainty in the background CO 2 field, and (2) have a positive impact on the analysis estimates by allowing observations to adjust predictions over large areas. A state‐of‐the‐art four‐dimensional variational (4D‐VAR) system developed at the European Centre for Medium‐Range Weather Forecasts (ECMWF) is used to illustrate the impact of the proposed approach for characterizing background error statistics on atmospheric CO 2 concentration estimates. Observations from the Greenhouse gases Observing SATellite “IBUKI” (GOSAT) are assimilated into the ECMWF 4D‐VAR system along with meteorological variables, using both the new error statistics and those based on a traditional forecast‐based technique. Evaluation of the four‐dimensional CO 2 fields against independent CO 2 observations confirms that the performance of the data assimilation system improves substantially in the summer, when significant variability and uncertainty in the fluxes are present. Key Points Difference in modeled CO2 fields is used to define background errors in CO2‐DA Both atmospheric transport & flux pattern differences impact background errors Evaluation using independent data shows positive impact on analysis estimatesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100305/1/jgrd50654.pd

Methane Optical Density Measurements with an Integrated Path Differential Absorption Lidar from an Airborne Platform

We report on an airborne demonstration of atmospheric methane (CH4) measurements with an Integrated Path Differential Absorption (IPDA) lidar using an optical parametric amplifier (OPA) and optical parametric oscillator (OPO) laser transmitter and sensitive avalanche photodiode detector. The lidar measures the atmospheric CH4 absorption at multiple, discrete wavelengths near 1650.96 nm. The instrument was deployed in the fall of 2015, aboard NASA's DC-8 airborne laboratory along with an in-situ spectrometer and measured CH4 over a wide range of surfaces and atmospheric conditions from altitudes of 2 km to 13 km. In this paper, we will show the results from our flights, compare the performance of the two laser transmitters, and identify areas of improvement for the lidar

Ground and Airborne Methane Measurements Using Optical Parametric Amplifiers

We report on ground and airborne methane measurements with an active sensing instrument using widely tunable, seeded optical parametric generation (OPG). The technique has been used to measure methane, CO2, water vapor, and other trace gases in the near and mid-infrared spectral regions. Methane is a strong greenhouse gas on Earth and it is also a potential biogenic marker on Mars and other planetary bodies. Methane in the Earth's atmosphere survives for a shorter time than CO2 but its impact on climate change can be larger than CO2. Carbon and methane emissions from land are expected to increase as permafrost melts exposing millennial-age carbon stocks to respiration (aerobic-CO2 and anaerobic-CH4) and fires. Methane emissions from c1athrates in the Arctic Ocean and on land are also likely to respond to climate warming. However, there is considerable uncertainty in present Arctic flux levels, as well as how fluxes will change with the changing environment. For Mars, methane measurements are of great interest because of its potential as a strong biogenic marker. A remote sensing instrument that can measure day and night over all seasons and latitudes can localize sources of biogenic gas plumes produced by subsurface chemistry or biology, and aid in the search for extra-terrestrial life. In this paper we report on remote sensing measurements of methane using a high peak power, widely tunable optical parametric generator (OPG) operating at 3.3 micrometers and 1.65 micrometers. We have demonstrated detection of methane at 3.3 micrometers and 1650 nanometers in an open path and compared them to accepted standards. We also report on preliminary airborne demonstration of methane measurements at 1.65 micrometers

Observing System Simulations for the NASA ASCENDS Lidar CO2 Mission Concept: Substantiating Science Measurement Requirements

The NASA ASCENDS mission (Active Sensing of Carbon Emissions, Nights, Days, and Seasons) is envisioned as the next generation of dedicated, space-based CO2 observing systems, currently planned for launch in about the year 2022. Recommended by the US National Academy of Sciences Decadal Survey, active (lidar) sensing of CO2 from space has several potentially significant advantages, in comparison to current and planned passive CO2 instruments, that promise to advance CO2 measurement capability and carbon cycle understanding into the next decade. Assessment and testing of possible lidar instrument technologies indicates that such sensors are more than feasible, however, the measurement precision and accuracy requirements remain at unprecedented levels of stringency. It is, therefore, important to quantitatively and consistently evaluate the measurement capabilities and requirements for the prospective active system in the context of advancing our knowledge of carbon flux distributions and their dependence on underlying physical processes. This amounts to establishing minimum requirements for precision, relative accuracy, spatial/temporal coverage and resolution, vertical information content, interferences, and possibly the tradeoffs among these parameters, while at the same time framing a mission that can be implemented within a constrained budget. Here, we present results of observing system simulation studies, commissioned by the ASCENDS Science Requirements Definition Team, for a range of possible mission implementation options that are intended to substantiate science measurement requirements for a laser-based CO2 space instrument

Ground and Airborne Methane Measurements with an Optical Parametric Amplifier

Here we report on measurements made with an improved CO2 Sounder lidar during the ASCENDS 2014 and 2016 airborne campaigns. The changes made to the 2011 version of the lidar included incorporating a rapidly wavelength-tunable, step-locked seed laser in the transmittter, using a much more sensitive HgCdTe APD detector andusing an analog digitizer with faster readout time in the receiver. We also improved the lidar's calibration approach and the XCO2 retrieval algorithm. The 2014 and 2016 flights were made over several types of topographic surfaces from3 to 12 km aircraft altitudes in the continental US. The results are compared to the XCO2 values computed from an airborne in situ sensor during spiral-down maneuvers. The 2014 results show significantly better performance and include measurement of horizontal gradients in XCO2 made over the Midwestern US that agree with chemistry transport models. The results from the 2016 airborne lidar retrievals show precisions of 0:7 parts per million (ppm) with 1 s averaging over desert surfaces, which is an improvement of about 8 times compared to similar measurements made in 2011. Measurements in 2016 were also made over fresh snow surfaces that have lower surface reflectance at the laser wavelengths. The results from both campaigns showed that the mean values of XCO2 retrieved from the lidar consistently agreed with those based on the in situ sensor to within 1 ppm. The improved precision and accuracy demonstrated in the 2014 and 2016 flights should benefit future airborne science ampaigns and advance the technique's readiness for a spacebased instrument

Planning, implementation, and first results of the Tropical Composition, Cloud and Climate Coupling Experiment (TC4)

The Tropical Composition, Cloud and Climate Coupling Experiment (TC4), was based in Costa Rica and Panama during July and August 2007. The NASA ER-2, DC-8, and WB-57F aircraft flew 26 science flights during TC4. The ER-2 employed 11 instruments as a remote sampling platform and satellite surrogate. The WB-57F used 25 instruments for in situ chemical and microphysical sampling in the tropical tropopause layer (TTL). The DC-8 used 25 instruments to sample boundary layer properties, as well as the radiation, chemistry, and microphysics of the TTL. TC4 also had numerous sonde launches, two ground-based radars, and a ground-based chemical and microphysical sampling site. The major goal of TC4 was to better understand the role that the TTL plays in the Earth's climate and atmospheric chemistry by combining in situ and remotely sensed data from the ground, balloons, and aircraft with data from NASA satellites. Significant progress was made in understanding the microphysical and radiative properties of anvils and thin cirrus. Numerous measurements were made of the humidity and chemistry of the tropical atmosphere from the boundary layer to the lower stratosphere. Insight was also gained into convective transport between the ground and the TTL, and into transport mechanisms across the TTL. New methods were refined and extended to all the NASA aircraft for real-time location relative to meteorological features. The ability to change flight patterns in response to aircraft observations relayed to the ground allowed the three aircraft to target phenomena of interest in an efficient, well-coordinated manner

Measuring atmospheric CO2 enhancements from the 2017 British Columbia wildfires using a lidar

During the summer 2017 ASCENDS/ABoVE airborne science campaign, the NASA Goddard CO2 Sounder lidar overflew smoke plumes from wildfires in the British Columbia, Canada. In the flight path over Vancouver Island on 8 August 2017, the column XCO2 retrievals from the lidar measurements at flight altitudes around 9 km showed an average enhancement of 4 ppm from the wildfires. A comparison of these enhancements with those from the Goddard Global Chemistry Transport model suggested that the modeled CO2 emissions from wildfires were underestimated by more than a factor of 2. A spiral-down validation performed at Moses Lake airport, Washington showed a bias of 0.1 ppm relative to in situ measurements and a standard deviation of 1 ppm in lidar XCO2 retrievals. The results show that future airborne campaigns and spaceborne missions with this type of lidar can improve estimates of CO2 emissions from wildfires and estimates of carbon fluxes globally

Quantifying the Observability of CO2 Flux Uncertainty in Atmospheric CO2 Records Using Products from Nasa's Carbon Monitoring Flux Pilot Project

NASAs Carbon Monitoring System (CMS) Flux Pilot Project (FPP) was designed to better understand contemporary carbon fluxes by bringing together state-of-the art models with remote sensing datasets. Here we report on simulations using NASAs Goddard Earth Observing System Model, version 5 (GEOS-5) which was used to evaluate the consistency of two different sets of observationally constrained land and ocean fluxes with atmospheric CO2 records. Despite the strong data constraint, the average difference in annual terrestrial biosphere flux between the two land (NASA Ames CASA and CASA-GFED) models is 1.7 Pg C for 2009-2010. Ocean models (NOBM and ECCO2-Darwin) differ by 35 in their global estimates of carbon flux with particularly strong disagreement in high latitudes. Based upon combinations of terrestrial and ocean fluxes, GEOS-5 reasonably simulated the seasonal cycle observed at northern hemisphere surface sites and by the Greenhouse gases Observing SATellite (GOSAT) while the model struggled to simulate the seasonal cycle at southern hemisphere surface locations. Though GEOS-5 was able to reasonably reproduce the patterns of XCO2 observed by GOSAT, it struggled to reproduce these aspects of AIRS observations. Despite large differences between land and ocean flux estimates, resulting differences in atmospheric mixing ratio were small, typically less than 5 ppmv at the surface and 3 ppmv in the XCO2 column. A statistical analysis based on the variability of observations shows that flux differences of these magnitudes are difficult to distinguish from natural variability, regardless of measurement platform

NASA's Carbon Cycle OSSE Initiative - Informing Future Space-Based Observing Strategies Through Advanced Modeling and Data Assimilation

Land and ocean carbon sinks absorb half of human CO2 emissions. The fate of these sinks in a changing world is unknown, introducing large uncertainties in climate projections. Satellite measurements of atmospheric CO2 are required to better understand the processes governing carbon uptake. Careful planning of future missions using Observing System Simulation Experiments (OSSEs) can help ensure that they meet the needs of the scientific and policy communities. NASA's Carbon Cycle OSSE Initiative brings together researchers from multiple universities and NASA centers to create model-derived data products in support of informed mission planning

TransCom model simulations of methane: Comparison of vertical profiles with aircraft measurements

To assess horizontal and vertical transports of methane (CH4) concentrations at different heights within the troposphere, we analyzed simulations by 12 chemistry transport models (CTMs) that participated in the TransCom-CH4 intercomparison experiment. Model results are compared with aircraft measurements at 13 sites in Amazon/Brazil, Mongolia, Pacific Ocean, Siberia/Russia, and United States during the period of 2001-2007. The simulations generally show good agreement with observations for seasonal cycles and vertical gradients. The correlation coefficients of the daily averaged model and observed CH4 time series for the analyzed years are generally larger than 0.5, and the observed seasonal cycle amplitudes are simulated well at most sites, considering the between-model variances. However, larger deviations show up below 2 km for the model-observation differences in vertical profiles at some locations, e.g., at Santarem, Brazil, and in the upper troposphere, e.g., at Surgut, Russia. Vertical gradients and concentrations are underestimated at Southern Great Planes, United States, and Santarem and overestimated at Surgut. Systematic overestimation and underestimation of vertical gradients are mainly attributed to inaccurate emission and only partly to the transport uncertainties. However, large differences in model simulations are found over the regions/seasons of strong convection, which is poorly represented in the models. Overall, the zonal and latitudinal variations in CH4 are controlled by surface emissions below 2.5 kmand transport patterns in the middle and upper troposphere. We show that the models with larger vertical gradients, coupled with slower horizontal transport, exhibit greater CH4 interhemispheric gradients in the lower troposphere. These findings have significant implications for the future development of more accurate CTMs with the possibility of reducing biases in estimated surface fluxes by inverse modelling