Meemong Lee

Image processing software for imaging spectrometry data analysis

Abstract The advent of a new generation of remote sensing instruments, called imaging spectrometers, promises to provide scientists a greatly enhanced capability for detailed observations of the earths surface. These instruments collect image data in literally hundreds of spectral channels simultaneously from the near ultraviolet through the short wavelength infrared, and are capable in many cases of providing direct surface materials identification in a manner similar to that used in laboratory reflectance spectroscopy. The volume and complexity of data produced by these instruments offers a significant challenge to traditional multispectral image analysis methods, and in fact requires the development of new approaches to efficiently manage and analyze these data sets. This paper describes a software system specifically designed to provide the science user with a powerful set of tools for carrying out exploratory analysis of imaging spectrometer data utilizing only modest computational resources.

Carbon Monitoring System Flux Estimation and Attribution: Impact of ACOS-GOSAT X(CO2) Sampling on the Inference of Terrestrial Biospheric Sources and Sinks

Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite ‘IBUKI’ (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (XCO2 ) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is ~1132 for 1-yr of the 74 055 GOSAT XCO2 observations, which indicates that GOSAT provides ~1132 independent pieces of information about surface fluxes. We quantify the impact of GOSATs spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.

Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño

INTRODUCTION The influence of El Niño on climate is accompanied by large changes to the carbon cycle, and El Niño–induced variability in the carbon cycle has been attributed mainly to the tropical continents. However, owing to a dearth of observations in the tropics, tropical carbon fluxes are poorly quantified, and considerable debate exists over the dominant mechanisms (e.g., plant growth, respiration, fire) and regions (e.g., humid versus semiarid tropics) on the net carbon balance. RATIONALE The launch of the Orbiting Carbon Observatory-2 (OCO-2) shortly before the 2015–2016 El Niño, the second strongest since the 1950s, has provided an opportunity to understand how tropical land carbon fluxes respond to the warm and dry climate characteristics of El Niño conditions. The El Niño events may also provide a natural experiment to study the response of tropical land carbon fluxes to future climate changes, because anomalously warm and dry tropical environments typical of El Niño are expected to be more frequent under most emission scenarios. RESULTS The tropical regions of three continents (South America, Asia, and Africa) had heterogeneous responses to the 2015–2016 El Niño, in terms of both climate drivers and the carbon cycle. The annual mean precipitation over tropical South America and tropical Asia was lower by 3.0σ and 2.8σ, respectively, in 2015 relative to the 2011 La Niña year. Tropical Africa, on the other hand, had near equal precipitation and the same number of dry months between 2015 and 2011; however, surface temperatures were higher by 1.6σ, dominated by the positive anomaly over its eastern and southern regions. In response to the warmer and drier climate anomaly in 2015, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere than in 2011, which accounts for 83.3% of the global total 3.0–gigatons of carbon (gigatons C) net biosphere flux differences and 92.6% of the atmospheric CO2 growth-rate differences between 2015 and 2011. It indicates that the tropical land biosphere flux anomaly was the driver of the highest atmospheric CO2 growth rate in 2015. The three tropical continents had an approximately even contribution to the pantropical net carbon flux anomaly in 2015, but had diverse dominant processes: gross primary production (GPP) reduced carbon uptake (0.9 ± 0.96 gigatons C) in tropical South America, fire increased carbon release (0.4 ± 0.08 gigatons C) in tropical Asia, and respiration increased carbon release (0.6 ± 1.01 gigatons C) in Africa. We found that most of the excess carbon release in 2015 was associated with either extremely low precipitation or high temperatures, or both. CONCLUSION Our results indicate that the global El Niño effect is a superposition of regionally specific effects. The heterogeneous climate forcing and carbon response over the three tropical continents to the 2015–2016 El Niño challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability, which could also be due to previous disturbance and soil and vegetation structure. The similarity between the 2015 tropical climate anomaly and the projected climate changes imply that the role of the tropical land as a buffer for fossil fuel emissions may be reduced in the future. The heterogeneous response may reflect differences in temperature and rainfall anomalies, but intrinsic differences in vegetation species, soils, and prior disturbance may contribute as well. A synergistic use of multiple satellite observations and a long time series of spatially resolved fluxes derived from sustained satellite observations will enable tests of these hypotheses, allow for a more process-based understanding, and, ultimately, aid improved carbon-climate model projections. Diverse climate driver anomalies and carbon cycle responses to the 2015–2016 El Niño over the three tropical continents. Schematic of climate anomaly patterns over the three tropical continents and the anomalies of the net carbon flux and its dominant constituent flux (i.e., GPP, respiration, and fire) relative to the 2011 La Niña during the 2015–2016 El Niño. GtC, gigatons C. The 2015–2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO2) was the largest on record. Here we quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO2, solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability.

Image processing software for imaging spectrometry

Recent advances in remote sensing have enabled scientists to collect image data in literally hundreds of spectral channels simul-taneously, from the near ultraviolet through the short-wavelength infrared, using imaging spectrometers. In many cases this data is of sufficient resolution to provide a direct surface materials identification. Yet the volume and complexity of the data produced requires new algorithms and approaches beyond those traditionally used for multispectral image analysis, including algorithms for fast image segmentation, spectral identification and mixture analysis. This paper describes a software system specifically designed to provide the scientist with the tools necessary for exploratory analysis of imaging spectrometer data using only modest computa-tional resources.

Estimate of carbonyl sulfide tropical oceanic surface fluxes using Aura Tropospheric Emission Spectrometer observations

Author(s): Kuai, L; Worden, JR; Campbell, JE; Kulawik, SS; Li, KF; Lee, M; Weidner, RJ; Montzka, SA; Moore, FL; Berry, JA; Baker, I; Denning, AS; Bian, H; Bowman, KW; Liu, J; Yung, YL | Abstract:

Deep Space 1 mission and observation of comet Borrelly

NASAs Deep Space 1 mission was enabled by several break-through technologies including autonomous optical navigation (AutoNav), miniature integrated camera and spectrometer (MICAS), on-board data processing, model-based science observation sequence planning, and science information analysis. This paper describes a few notable challenges for the MICAS system with respect to flight calibration and observations of comet Borrelly.

Design-based mission operation

The Virtual Mission project led by the Mission Simulation and Instrument Modeling Group at JPL has been playing an active role in the NASA-wide information technology infusion programs, such as, Information System Technology, Next-Generation Infrastructure Technology, and Intelligent Synthesis Environment. The goal of the Virtual Mission project is to enable automated design space exploration, progressive design optimization, and lifecycle-wide design validation to ensure mission success. Design-based mission operation has been a major part of the research effort in order to establish system-wide as well as lifecycle-wide impact analysis as an integral part of the mission design process. The design-based mission operation is approached by implementing Virtual Mission Lifecycle (VML), modeling and simulation tools and system engineering processes for building a virtual mission system that can perform a realistic mission operation during the design phase of a mission. As in the real mission lifecycle convention, the VML is composed of design, development, integration and test, and operation phases. This paper describes the four phases of the VML addressing a major challenge per phase, mission model framework, virtual prototyping, agent-based mission system integration, and virtual mission operation.

Global and Brazilian Carbon Response to El Niño Modoki 2011–2010

The El Nino Modoki in 2010 led to historic droughts in Brazil. In order to understand its impact on carbon cycle variability, we derive the 2011-2010 annual carbon flux change (δF↑) globally and specifically to Brazil using the NASA Carbon Monitoring System Flux (CMS-Flux) framework. Satellite observations of CO2, CO, and solar induced fluorescence (SIF) are ingested into a 4D-variational assimilation system driven by carbon cycle models to infer spatially resolved carbon fluxes including net ecosystem production, biomass burning, and gross primary productivity (GPP). The global 2011-2010 net carbon flux change was estimated to be δF↑= -1.60 PgC while the Brazilian carbon flux change was -0.24 ± 0.11 PgC. This estimate is broadly within the uncertainty of previous aircraft based estimates restricted to the Amazon basin. The 2011-2010 biomass burning change in Brazil was -0.24 ± 0.036 PgC, which implies a near-zero 2011-2010 change of the net ecosystem production (NEP): the near-zero NEP change is the result of quantitatively comparable increases GPP (0.31 ± 0.20 PgC) and respiration in 2011. Comparisons between Brazilian and global component carbon flux changes reveal complex interactions between the processes controlling annual land-atmosphere CO2 exchanges. These results show the potential of multiple satellite observations to help quantify and spatially resolve the response of productivity and respiration fluxes to climate variability.

Improved western U.S. background ozone estimates via constraining nonlocal and local source contributions using Aura TES and OMI observations

Western U.S. near-surface ozone (O3) concentrations are sensitive to transported background O3 from the eastern Pacific free troposphere, as well as U.S. anthropogenic and natural emissions. The current 75 ppbv U.S. O3 primary standard may be lowered soon, hence accurately estimating O3 source contributions, especially background O3 in this region has growing policy-relevant significance. In this study, we improve the modeled total and background O3, via repartitioning and redistributing the contributions from nonlocal and local anthropogenic/wildfires sources in a multi-scale satellite data assimilation system containing global Goddard Earth Observing System–Chemistry model (GEOS-Chem) and regional Sulfur Transport and dEposition Model (STEM). Focusing on NASAs ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) field campaign period in June–July 2008, we first demonstrate that the negative biases in GEOS-Chem free simulation in the eastern Pacific at 400–900 hPa are reduced via assimilating Aura-Tropospheric Emission Spectrometer (TES) O3 profiles. Using the TES-constrained boundary conditions, we then assimilated into STEM the tropospheric nitrogen dioxide (NO2) columns from Aura-Ozone Monitoring Instrument to indicate U.S. nitrogen oxides (NOx = NO2 + NO) emissions at 12 × 12 km2 grid scale. Improved model skills are indicated from cross validation against independent ARCTAS measurements. Leveraging Aura observations, we show anomalously high wildfire NOx emissions in this summer in Northern California and the Central Valley while lower anthropogenic emissions in multiple urban areas than those representing the year of 2005. We found strong spatial variability of the daily maximum 8 h average background O3 and its contribution to the modeled total O3, with the mean value of ~48 ppbv (~77% of the total).

Mission lifecycle modeling and simulation

Mission synthesis and simulation research at JPL addresses mission model taxonomy, progressive lifecycle representation, model-based design, and simulation-in-the-loop design. The Virtual Mission (VM) project integrates the research activities and implements a virtual mission lifecycle to enable a globally optimal mission. The VM is composed of three interacting modeling and simulation layers: a mission model architecture layer, a mission system simulation layer, and a mission operation simulation layer. The three layers collectively simulate the development, integration, and operation phases of the mission cycle for comprehensive validation of mission design products. The VM was applied for the MICAS (Miniature Imaging Camera And Spectrometer) payload system of the Deep Space 1 mission (DS1) to validate the integrated systems performance to ensure the desired science return. The VM is being applied to design and to validate calibration scenarios and science observation scenarios for the extended science mission of the DS1 project.