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Low Latency Flux and Concentration Datasets in Support of Greenhouse Gas Monitoring Based on NASA's GEOS Modeling and Data Assimilation System
We present efforts to develop space-based greenhouse gas monitoring systems that can provide low latency information and traceability to independent observations. Through support from its Carbon Monitoring System program, NASA has developed the capability to assimilate XCO2 retrievals from the Orbiting Carbon Observatory, 2 (OCO-2) into the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS) to create gap-filled, three-dimensional (3D) estimates of CO2 mixing ratio. When OCO-2 data are not available, concentration fields are further informed by a bottom-up flux package based on remotely sensed fire radiative power, nighttime lights, and vegetation reflectance combined with estimates of atmospheric growth rate based on surface in situ data. The 3D nature of this dataset supports evaluation with independent aircraft data, helping to ensure transparency of remotely sensed data products. These quasi-operational data are currently produced 2-3 months behind real time and are distributed via NASA and international dashboard services to a variety of end users. In this presentation, we provide an overview of the system as well as remaining data gaps and modeling challenges. We also highlight the application of this dataset for detecting emissions anomalies associated with COVID-19 and comparing against independent emissions estimates. Finally, we highlight a new NASA initiative called the Earth Information System (EIS), which aims to support open science and applications by leveraging emerging cloud computing capabilities to increase access to NASA’s greenhouse gas datasets, opportunities for co-development, and transparency in methods for analysis and flux attribution.
Greenhouse Gas Emissions from Food Systems: Building the Evidence Base
New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.
A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements
We review the singular value decomposition (SVD) framework and use it for quantifying and discerning vertical information in greenhouse gas retrievals from column integrated absorption measurements. While the commonly used traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We review the SVD method, explicitly recognize the use of an uninformative prior and show it to incur no bias from the choice of the prior. We also make the connection between the SVD method and the pseudo-inverse, which makes it more intuitive and easy to understand. We illustrate the use of the SVD method on an integrated path differential absorption CO2 lidar measurement model and verify our derivations and bias-free properties versus optimal estimation using numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. Hence, the SVD method is particularly useful for situations in which knowledge of the prior mean and prior covariance of the true state (e.g., greenhouse gas profiles) is inadequate.
A Methane Lidar for Greenhouse Gas Measurements
Atmospheric methane is the second most important greenhouse gas with 25 times the radiativeforcing of carbon dioxide. We will present results from an airborne campaign using a lidar at1.65m using optical parametric generation. OCIS codes: ((280.1910) DIAL, differential absorption lidar; (120.0280) Remote sensing and sensors; (010.1280) Atmospheric composition.
From CMS to the U.S. Greenhouse Gas Center – Improved Tracking of Recent Changes in Co 2 and Ch 4 From NASA’s Quasi-Operational Modeling Systems
Reliable, low latency delivery of high quality global flux and concentration information is a growing but still unmet need to advance expanding measurement, monitoring, reporting, and verification efforts that underpin federal climate mitigation strategies. Here we present on progress toward developing space-based greenhouse gas (GHG) monitoring systems that can provide comprehensive information trailing real time by a matter of weeks to a few months. Through support from its Carbon Monitoring System (CMS) program, NASA has developed the capability to assimilate XCO 2 retrievals from the Orbiting Carbon Observatory, 2 (OCO 2 ) into the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS) to create gap-filled, three-dimensional (3D) estimates of CO 2 mixing ratio. When observations are unavailable, concentration fields are further informed by observationally-informed bottom-up flux packages that incorporate remotely sensed fire, nighttime lights, and vegetation observations combined with estimates of atmospheric growth rate based on surface in situ data. The 3D nature of these datasets supports evaluation with independent aircraft data to improve confidence in satellite data, development of new regional modeling approaches, and quantification of the climate impacts of GHGs. The system has recently been expanded to assimilate XCH 4 from ESA’s TROPOspheric Monitoring Instrument (TROPOMI) instrument and is supported by companion efforts to improve delivery of estimates of bottom-up land and ocean fluxes. The quasi-operational GEOS-GHG system is contributing to the recently announced U.S. Greenhouse Gas Center (GHG Center) by delivering information on recent changes in CO 2 and CH 4 emissions and concentrations to support stakeholder and research communities. In this presentation, we provide an overview of the current system configured to support the GHG Center. We highlight examples of how this data contributes to broader NASA initiatives including the Earth Information Center, an innovative virtual and physical exhibit designed to show how NASA data helps the nation combat climate change. We conclude by discussing how innovations in CMS research can address remaining data gaps and modeling challenges to advance operational GHG monitoring in the future.
Irrigation Induced Surface Cooling in the Context of Modern and Increased Greenhouse Gas Forcing
There is evidence that expected warming trends from increased greenhouse gas (GHG) forcing have been locally masked by irrigation induced cooling, and it is uncertain how the magnitude of this irrigation masking effect will change in the future. Using an irrigation dataset integrated into a global general circulation model, we investigate the equilibrium magnitude of irrigation induced cooling under modern (Year 2000) and increased (A1B Scenario, Year 2050) GHG forcing, using modern irrigation rates in both scenarios. For the modern scenario, the cooling is largest over North America, India, the Middle East, and East Asia. Under increased GHG forcing, this cooling effect largely disappears over North America, remains relatively unchanged over India, and intensifies over parts of China and the Middle East. For North America, irrigation significantly increases precipitation under modern GHG forcing; this precipitation enhancement largely disappears under A1B forcing, reducing total latent heat fluxes and the overall irrigation cooling effect. Over India, irrigation rates are high enough to keep pace with increased evaporative demand from the increased GHG forcing and the magnitude of the cooling is maintained. Over China, GHG forcing reduces precipitation and shifts the region to a drier evaporative regime, leading to a relatively increased impact of additional water from irrigation on the surface energy balance. Irrigation enhances precipitation in the Middle East under increased GHG forcing, increasing total latent heat fluxes and enhancing the irrigation cooling effect. Ultimately, the extent to which irrigation will continue to compensate for the warming from increased GHG forcing will primarily depend on changes in the background evaporative regime, secondary irrigation effects (e.g. clouds, precipitation), and the ability of societies to maintain (or increase) current irrigation rates.
The Response of the North American Monsoon to Increased Greenhouse Gas Forcing
[1] We analyze the response of the North American Monsoon (NAM) to increased greenhouse gas (GHG) forcing (emissions scenario RCP 8.5) using new simulations available through the Coupled Model Intercomparison Project version 5 (CMIP5). Changes in total monsoon season rainfall with GHG warming are small and insignificant. The models do, however, show significant declines in early monsoon season precipitation (June-July) and increases in late monsoon season (September-October) precipitation, indicating a shift in seasonality toward delayed onset and withdrawal of the monsoon. Early in the monsoon season, tropospheric warming increases vertical stability, reinforced by reductions in available surface moisture, inhibiting precipitation and delaying the onset of the monsoon. By the end of the monsoon season, moisture convergence is sufficient to overcome the warming induced stability increases, and precipitation is enhanced. Even with no change in total NAM rainfall, shifts in the seasonal distribution of precipitation within the NAM region are still likely to have significant societal and ecological consequences, reinforcing the need to not only understand the magnitude, but also the timing, of future precipitation changes.
A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements
We describe a variation of the Optimal Estimation (OE) method for greenhouse gas remote sensing retrievals using a singular value decomposition (SVD) and an uninformative prior. The SVD method is capable of discerning vertical information in column integrated absorption measurements. While traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We discuss the method, illustrate its use on an integrated path differential absorption CO2 lidar measurement model, and compare it to traditional optimal estimation using numerical simulations. In the absence of forward model error, the mathematics behind the SVD method guarantee it to be bias-free, which is confirmed by the numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. While the SVD approach can be used for most trace gas retrievals, it is particularly useful for situations where prior knowledge of the trace gas profile is poor. The SVD analysis is also useful in illustrating how vertical information is treated by the traditional OE approach.
Challenges and opportunities for enhancing food security and greenhouse gas mitigation in smallholder farming in sub-Saharan Africa. A review
Smallholder farmers struggle to achieve food security in many countries of sub-Saharan Africa (SSA). It is urgently required to find appropriate practices for enhancing crop production while avoiding large increases in greenhouse gas (GHG) emissions in SSA. This review aims to identify common smallholder farming practices for enhancing crop production, to assess how these affect GHG emissions and to identify strategies that not only enhance crop production but also mitigate GHG emissions in SSA. To increase crop production and ensure food security, smallholder farmers usually expand agricultural land, develop water harvesting and irrigation techniques and increase cropping intensity and fertilizer use. These practices may result in changing carbon stocks and GHG emissions, potentially creating trade-offs between food security and GHG mitigation. Agricultural land expansion at the expense of forests is the most dominant source of GHG emissions in SSA. While water harvesting and irrigation can increase soil organic carbon, they can trigger GHG emissions. Increasing cropping intensity can enhance the decomposition of soil organic matter, thus releasing carbon dioxide. Increasing nitrogen fertilizer use can enhance soil organic carbon, but also leads to increasing nitrous oxide emissions. An integrated land, water and nutrient management strategy is necessary to enhance crop production and mitigate GHG emissions. Among the most relevant strategies found, agroforestry practices in degraded and marginal lands could replace expanding agricultural croplands. In addition, water management, via adequate rainwater harvesting and irrigation techniques, together with appropriate nutrient management should be considered. Therefore, a land-water-nutrient nexus (LWNN) approach will enable an integrated and sustainable solution to increasing crop production and mitigating GHG emissions. Various technical, economic and policy barriers hinder implementing the LWNN approach on the ground, but these may be overcome through developing appropriate technologies, disseminating them through farmer to farmer approaches and developing specific policies to address smallholder land tenure issues and motivate long-term investment.
Effects of Greenhouse Gas Increase and Stratospheric Ozone Depletion on Stratospheric Mean Age of Air in 1960-2010
The relative impacts of greenhouse gas (GHG) increase and stratospheric ozone depletion on stratospheric mean age of air in the 1960-2010 period are quantified using the Goddard Earth Observing System Chemistry-Climate Model. The experiment compares controlled simulations using a coupled atmosphere-ocean version of the Goddard Earth Observing System Chemistry-Climate Model, in which either GHGs or ozone depleting substances, or both factors evolve over time. The model results show that GHGs and ozone-depleting substances have about equal contributions to the simulated mean age decrease, but GHG increases account for about two thirds of the enhanced strength of the lower stratospheric residual circulation. It is also found that both the acceleration of the diabatic circulation and the decrease of the mean age difference between downwelling and upwelling regions are mainly caused by GHG forcing. The results show that ozone depletion causes an increase in the mean age of air in the Antarctic summer lower stratosphere through two processes: (1) a seasonal delay in the Antarctic polar vortex breakup that inhibits young midlatitude air from mixing with the older air inside the vortex, and (2) enhanced Antarctic downwelling that brings older air from middle and upper stratosphere into the lower stratosphere.
Historical Domestic Flights from 2016-2020 with Estimations of Greenhouse Gas Emissions by Aircraft Type
Data and analyses are presented on the utilization of aircraft fuel in the U.S. and the greenhouse gas emissions that they create. Aggregated commercial passenger and freight aviation flight data from 2016-2020 is captured from the Bureau of Transportation Statistics website is used to augment flight data from the Sherlock data warehouse at NASA Ames is used to determine the miles flown by major aircraft models. The corresponding fuel burn is estimated using the International Civilian Aviation Organization fuel burn tables and carbon dioxide emissions are calculated using a fuel-burn multiplicative factor. One key conclusion of this analysis is that long haul flights (i.e. >2485 statute miles) create a disproportionately large amount of carbon dioxide emissions in the U.S while short flights (i.e. < 311 statute miles) contribute less than five percent of the U.S. aviation-related carbon dioxide emission. Although these short-haul flights may not have a large impact on overall carbon dioxide emissions, they will be a critical entry point for the adoption of future, larger fuel-efficient novel vehicles and the impact to future airport and infrastructure requirements. The final paper will present some estimates of the impact of advanced technologies on fuel burn and CO₂ emissions in various scenarios.
Estimations of Aircraft and Airport Domestic Greenhouse Gas Emissions from 2016-2021
Data and analyses are presented on the utilization of aircraft fuel in the U.S. and the resulting greenhouse gas emissions. Commercial passenger and freight flight data and airport fuel consumption usage from 2016-2021 are captured from the Bureau of Transportation Statistics website and the Sherlock Data Warehouse managed at NASA Ames Research Center. The resulting dataset is used to determine the miles flown by major aircraft. The corresponding aircraft fuel burn is estimated based on the International Civilian Aviation Organization fuel burn tables, and carbon dioxide emissions are calculated using a fuel-burn multiplicative factor. One conclusion of this analysis is that long-haul flights (flight distances > 2485 statute miles) create a disproportionately large amount of carbon dioxide emissions in the U.S, while short flights (< 311 statute miles) contribute less than five percent of the U.S. aviation-related carbon dioxide emissions. Although these short-haul flights may not have a large impact on overall carbon dioxide emissions, they will be valuable as demonstration missions for the next generation of electric, hybrid, and hydrogen-powered vehicles and their supporting energy infrastructures. This paper discusses recent trends in short-haul missions, their associated aircraft and airport types, and extracts several key requirements for future short-haul vehicles.
Estimations of Aircraft and Airport Domestic Greenhouse Gas Emissions from 2016-2021
Data and analyses are presented on the utilization of aircraft fuel in the U.S. and the resulting greenhouse gas emissions. Commercial passenger and freight flight data and airport fuel consumption usage from 2016-2021 are captured from the Bureau of Transportation Statistics website and the Sherlock Data Warehouse managed at NASA Ames Research Center. The resulting dataset is used to determine the miles flown by major aircraft. The corresponding aircraft fuel burn is estimated based on the International Civilian Aviation Organization fuel burn tables, and carbon dioxide emissions are calculated using a fuel-burn multiplicative factor. One conclusion of this analysis is that long-haul flights (flight distances > 2485 statute miles) create a disproportionately large amount of carbon dioxide emissions in the U.S, while short flights (< 311 statute miles) contribute less than five percent of the U.S. aviation-related carbon dioxide emissions. Although these short-haul flights may not have a large impact on overall carbon dioxide emissions, they will be valuable as demonstration missions for the next generation of electric, hybrid, and hydrogen-powered vehicles and their supporting energy infrastructures. This paper discusses recent trends in short-haul missions, their associated aircraft and airport types, and extracts several key requirements for future short-haul vehicles.
Northern Hemisphere Winter Climate Response to Greenhouse Gas, Ozone, Solar and Volcanic Forcing
The Goddard Institute for Space Studies (GISS) climate/middle atmosphere model has been used to study the impacts of increasing greenhouse gases, polar ozone depletion, volcanic eruptions, and solar cycle variability. We focus on the projection of the induced responses onto Northern Hemisphere winter surface climate. Changes in the model's surface climate take place largely through enhancement of existing variability patterns, with greenhouse gases, polar ozone depletion and volcanic eruptions primarily affecting the Arctic Oscillation (AO) pattern. Perturbations descend from the stratosphere to the surface in the model by altering the propagation of planetary waves coming up from the surface, in accord with observational evidence. Models lacking realistic stratospheric dynamics fail to capture these wave flux changes. The results support the conclusion that the stratosphere plays a crucial role in recent AO trends. We show that in our climate model, while ozone depletion has a significant effect, greenhouse gas forcing is the only one capable of causing the large, sustained increase in the AO observed over recent decades. This suggests that the AO trend, and a concurrent strengthening of the stratospheric vortex over the Arctic, are very likely anthropogenic in origin.
Biomass Burning and Fossil Fuel Apportionment via Greenhouse Gas Enhancement Ratios Over Southeast Asia as Measured During ASIA-AQ
As Southeast Asian economies continue to grow, so will their contribution to global greenhouse gas (GHG) emissions, driven primarily by increases in fossil fuel combustion. Left unchecked, these emissions will negatively impact air quality and climate, therefore it is imperative that emission sources are properly identified and accounted for in emission inventories. Enhancement ratios of GHGs have been used to characterize regional emissions as either dominated by fossil fuel combustion or biomass burning. In particular, airborne assessment of short-term continuous emission ratios has proven useful to quantify relative contributions of fossil fuel and biomass burning to GHG emissions. The 2024 Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign, flying over the Philippines, Korea, Thailand, and Taiwan, sampled a variety of emissions including significant biomass burning, local urban pollution, and transport events. This work will explore the impact of GHG emissions on the distinctive pollution of the sampled locations. As airborne GHG measurements over Southeast Asia are scarce if not nonexistent, this work provides a crucial link between established ground-based measurements and state-of-the-art satellite observations such as those from South Korea’s Geostationary Environment Monitoring Spectrometer (GEMS). Analysis of GHG enhancement ratios in East Asia will lead to more accurate emission inventories which can be used to implement more effective GHG control measures leading to improved air quality and minimizing the effect on climate.
Detection of the greenhouse gas signal from space - A progress report
The spatial distribution of the expected changes in the atmospheric water vapor content and cloud cover, as predicted by the transient greenhouse gas (GHG) simulation of Hansen et al. (1988), are examined to determine whether the signals would be large enough and unique enough to be useful in a GHG detection study. The nature of the predicted GHG signal was first examined using the transient CO2 run from the GISS ocean/atmosphere general circulation model. Next, the remotely sensed irradiance characteristics data (as the measure of water vapor content) supplied by the HIRS/MSU sensors for the area of the equatorial cold tongue region (the region in which there are no measurement stations). It is shown that HIRS/MSU signals can provide data necessary for detecting GHS signals in atmospheric moisture for regions where ground observations are not possible.
Greenhouse Gas Emission Estimations for 2016-2020 using the Sherlock Air Traffic Data Warehouse
Data and analyses are presented on the utilization of aircraft in the U.S. and the greenhouse gas emissions that they create. Commercial passenger and cargo aviation flight data, captured in the Sherlock data warehouse at NASA Ames over the five years from 2016 to 2020, is used to estimate the miles flown by major aircraft models. The estimates for aggregate annual number of flights are validated against data published by the Bureau of Transportation Statistics. The corresponding fuel usage is estimated using the International Civilian Aviation Organization (ICAO) fuel use tables and carbon dioxide emissions are calculated using a fuel-use multiplicative factor. A key conclusion of this analysis is that a small number of long-haul flights (with ranges greater than 2485 statute miles) create a disproportionately large fraction (30%) of annual total U.S. aviation-related carbon dioxide emissions, while a relatively large number of short flights (less than 311 statute miles) contribute a small net amount (less than 5%) of U.S. aviation-related carbon dioxide emissions. These U.S. results are consistent with a similar recent 2020 emissions study conducted by EUROCONTROL.