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Lee, Meemong

Publications and source records attributed to Lee, Meemong.

At least 19 records

Quantifying Northern High Latitude Gross Primary Productivity (GPP) Using Carbonyl Sulfide (OCS)

The northern high latitude (NHL, 40°N to 90°N) is where the second peak region of gross primary productivity (GPP) other than the tropics. The summer NHL GPP is about 80% of the tropical peak, but both regions are still highly uncertain. Carbonyl sulfide (OCS) provides an important proxy for photosynthetic carbon uptake. Here we optimize the OCS plant uptake fluxes across the NHL by fitting atmospheric concentration simulation with the GEOS-CHEM global transport model to the aircraft profiles acquired over Alaska during NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (2012–2015). We use the empirical biome-specific linear relationship between OCS plant uptake flux and GPP to derive the six plant uptake OCS fluxes from different GPP data. Such GPP-based fluxes are used to drive the concentration simulations. We evaluate the simulations against the independent observations at two ground sites of Alaska. The optimized OCS fluxes suggest the NHL plant uptake OCS flux of -247 Gg S year -1 , about 25% stronger than the ensemble mean of the six GPP-based OCS fluxes. GPP-based OCS fluxes systematically underestimate the peak growing season across the NHL, while a subset of models predict early start of season in Alaska, consistent with previous studies of net ecosystem exchange. The OCS optimized GPP of 34 PgC yr -1 for NHL is also about 25% more than the ensembles mean from six GPP data. Further work is needed to fully understand the environmental and biotic drivers and quantify their rate of photosynthetic carbon uptake in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Remotely Sensed Carbonyl Sulfide Constrains Model Estimates of Amazon Primary Productivity

We report understanding the magnitude of tropical gross primary production (GPP) is critical for carbon cycle modeling and climate projections, but this quantity is poorly constrained at regional scales. Biospheric uptake of carbonyl sulfide (OCS) provides a promising approach to estimating regional GPP. Here, we simulate OCS concentrations driven by surface flux scenarios encompassing a wide range of GPP estimates for the Amazon basin. We compare the model output to satellite retrievals and find a regional GPP estimate of 2375 ± 914 g(C) m –2 yr –1 , consistent with previous estimates, including the TRENDY model ensemble range of 1431–3812 g(C) m –2 yr –1 .

54 ENVIRONMENTAL SCIENCES↗

Surface Pressure Dependencies in the Geos-Chem-Adjoint System and the Impact of the GEOS-5 Surface Pressure on CO2 Model Forecast

In the GEOS-Chem Adjoint (GCA) system, the total (wet) surface pressure of the GEOS meteorology is employed as dry surface pressure, ignoring the presence of water vapor. The Jet Propulsion Laboratory (JPL) Carbon Monitoring System (CMS) research team has been evaluating the impact of the above discrepancy on the CO2 model forecast and the CO2 flux inversion. The JPL CMS research utilizes a multi-mission assimilation framework developed by the Multi-Mission Observation Operator (M2O2) research team at JPL extending the GCA system. The GCA-M2O2 framework facilitates mission-generic 3D and 4D-variational assimilations streamlining the interfaces to the satellite data products and prior emission inventories. The GCA-M2O2 framework currently integrates the GCA system version 35h and provides a dry surface pressure setup to allow the CO2 model forecast to be performed with the GEOS-5 surface pressure directly or after converting it to dry surface pressure.

Carbon Monitoring System↗

Surface Pressure Dependencies in the GEOS-Chem-Adjoint System and the Impact of the GEOS-5 Surface Pressure on CO2 Model Forecast

In the GEOS-Chem Adjoint (GCA) system, the total (wet) surface pressure of the GEOS meteorology is employed as dry surface pressure, ignoring the presence of water vapor. The Jet Propulsion Laboratory (JPL) Carbon Monitoring System (CMS) research team has been evaluating the impact of the above discrepancy on the CO2 model forecast and the CO2 flux inversion. The JPL CMS research utilizes a multi-mission assimilation framework developed by the Multi-Mission Observation Operator (M2O2) research team at JPL extending the GCA system. The GCA-M2O2 framework facilitates mission-generic 3D and 4D-variational assimilations streamlining the interfaces to the satellite data products and prior emission inventories. The GCA-M2O2 framework currently integrates the GCA system version 35h and provides a dry surface pressure setup to allow the CO2 model forecast to be performed with the GEOS-5 surface pressure directly or after converting it to dry surface pressure.

Lee, Meemong↗

Geostationary Coastal and Air Pollution Events (GEO-CAPE) Sensitivity Analysis Experiment

Geostationary Coastal and Air pollution Events (GEO-CAPE) is a NASA decadal survey mission to be designed to provide surface reflectance at high spectral, spatial, and temporal resolutions from a geostationary orbit necessary for studying regional-scale air quality issues and their impact on global atmospheric composition processes. GEO-CAPE's Atmospheric Science Questions explore the influence of both gases and particles on air quality, atmospheric composition, and climate. The objective of the GEO-CAPE Observing System Simulation Experiment (OSSE) is to analyze the sensitivity of ozone to the global and regional NOx emissions and improve the science impact of GEO-CAPE with respect to the global air quality. The GEO-CAPE OSSE team at Jet propulsion Laboratory has developed a comprehensive OSSE framework that can perform adjoint-sensitivity analysis for a wide range of observation scenarios and measurement qualities. This report discusses the OSSE framework and presents the sensitivity analysis results obtained from the GEO-CAPE OSSE framework for seven observation scenarios and three instrument systems.

Lee, Meemong↗

CMS Flux

No abstract available

Fossil Fuel Data Assimilation System (FFDAS)↗

An Atmospheric Science Observing System Simulation Experiment (OSSE) Environment

An atmospheric sounding mission starts with a wide range of concept designs involving measurement technologies, observing platforms, and observation scenarios. Observing system simulation experiment (OSSE) is a technical approach to evaluate the relative merits of mission and instrument concepts. At Jet Propulsion Laboratory (JPL), the OSSE team has developed an OSSE environment that allows atmospheric scientists to systematically explore a wide range of mission and instrument concepts and formulate a science traceability matrix with a quantitative science impact analysis. The OSSE environment virtually creates a multi-platform atmospheric sounding testbed (MAST) by integrating atmospheric phenomena models, forward modeling methods, and inverse modeling methods. The MAST performs OSSEs in four loosely coupled processes, observation scenario exploration, measurement quality exploration, measurement quality evaluation, and science impact analysis.

mission concepts↗

Juno Mission Simulation

The Juno spacecraft is planned to launch in August of 2012 and would arrive at Jupiter four years later. The spacecraft would spend more than one year orbiting the planet and investigating the existence of an ice-rock core; determining the amount of global water and ammonia present in the atmosphere, studying convection and deep- wind profiles in the atmosphere; investigating the origin of the Jovian magnetic field, and exploring the polar magnetosphere. Juno mission management is responsible for mission and navigation design, mission operation planning, and ground-data-system development. In order to ensure successful mission management from initial checkout to final de-orbit, it is critical to share a common vision of the entire mission operation phases with the rest of the project teams. Two major challenges are 1) how to develop a shared vision that can be appreciated by all of the project teams of diverse disciplines and expertise, and 2) how to continuously evolve a shared vision as the project lifecycle progresses from formulation phase to operation phase. The Juno mission simulation team addresses these challenges by developing agile and progressive mission models, operation simulations, and real-time visualization products. This paper presents mission simulation visualization network (MSVN) technology that has enabled a comprehensive mission simulation suite (MSVN-Juno) for the Juno project.

space vehicles↗

Virtual Mission Operation Framework (VMOF)

The Virtual Mission Operation Framework (VMOF) is one of the project lifecycle engineering process improvement efforts initiated by the institutional technology infrastructure program at JPL. The VMOF is composed of three frameworks: a model integration framework, a simulation framework, and a visualization framework. The model integration framework interfaces with spacecraft system design, mission design, and structure design. The simulation framework interfaces with the operation scenario design, environmental phenomena science, and science payload system design. The visualization framework interfaces with the flight system testbed, the ground system, and the science analysis. The three frameworks of the VMOF collaborate to create a comprehensive virtual mission operation that enables a "validation-in-the-loop" system design process and lifecycle-continuous science-return validation.This paper discusses the technical approaches for each framework implementation, challenges and approaches involved in streamlining mission information access, and on-going activities toward enabling Model-Based Engineering Design in a collaborative distributed environment.

virtual mission operations↗

Micro - helm - a mission operation visualization system

Micro-Helm is a PC based mission visualization system that can be employed for comprehensive monitoring of mission system states during operation. Micro-Helm was designed as a cost-effective system solution that can be adapted to multiple missions in various mission lifecycle phases. It has been successfully applied to DS1 mission during its entire operation phases and Mars Odyssey mission during its launch and orbit-insertion phase, providing scenario design and validation.

Micro-Helm↗

Image-Processing Software For A Hypercube Computer

Concurrent Image Processing Executive (CIPE) is software system intended to develop and use image-processing application programs on concurrent computing environment. Designed to shield programmer from complexities of concurrent-system architecture, it provides interactive image-processing environment for end user. CIPE utilizes architectural characteristics of particular concurrent system to maximize efficiency while preserving architectural independence from user and programmer. CIPE runs on Mark-IIIfp 8-node hypercube computer and associated SUN-4 host computer.

Lee, Meemong↗

Concurrent Image Processing Executive (CIPE). Volume 1: Design overview

The design and implementation of a Concurrent Image Processing Executive (CIPE), which is intended to become the support system software for a prototype high performance science analysis workstation are described. The target machine for this software is a JPL/Caltech Mark 3fp Hypercube hosted by either a MASSCOMP 5600 or a Sun-3, Sun-4 workstation; however, the design will accommodate other concurrent machines of similar architecture, i.e., local memory, multiple-instruction-multiple-data (MIMD) machines. The CIPE system provides both a multimode user interface and an applications programmer interface, and has been designed around four loosely coupled modules: user interface, host-resident executive, hypercube-resident executive, and application functions. The loose coupling between modules allows modification of a particular module without significantly affecting the other modules in the system. In order to enhance hypercube memory utilization and to allow expansion of image processing capabilities, a specialized program management method, incremental loading, was devised. To minimize data transfer between host and hypercube, a data management method which distributes, redistributes, and tracks data set information was implemented. The data management also allows data sharing among application programs. The CIPE software architecture provides a flexible environment for scientific analysis of complex remote sensing image data, such as planetary data and imaging spectrometry, utilizing state-of-the-art concurrent computation capabilities.

Lee, Meemong↗

Concurrent Image Processing Executive (CIPE). Volume 3: User's guide

CIPE (the Concurrent Image Processing Executive) is both an executive which organizes the parameter inputs for hypercube applications and an environment which provides temporary data workspace and simple real-time function definition facilities for image analysis. CIPE provides two types of user interface. The Command Line Interface (CLI) provides a simple command-driven environment allowing interactive function definition and evaluation of algebraic expressions. The menu interface employs a hierarchical screen-oriented menu system where the user is led through a menu tree to any specific application and then given a formatted panel screen for parameter entry. How to initialize the system through the setup function, how to read data into CIPE symbols, how to manipulate and display data through the use of executive functions, and how to run an application in either user interface mode, are described.

Lee, Meemong↗

Concurrent Image Processing Executive (CIPE)

The design and implementation of a Concurrent Image Processing Executive (CIPE), which is intended to become the support system software for a prototype high performance science analysis workstation are discussed. The target machine for this software is a JPL/Caltech Mark IIIfp Hypercube hosted by either a MASSCOMP 5600 or a Sun-3, Sun-4 workstation; however, the design will accommodate other concurrent machines of similar architecture, i.e., local memory, multiple-instruction-multiple-data (MIMD) machines. The CIPE system provides both a multimode user interface and an applications programmer interface, and has been designed around four loosely coupled modules; (1) user interface, (2) host-resident executive, (3) hypercube-resident executive, and (4) application functions. The loose coupling between modules allows modification of a particular module without significantly affecting the other modules in the system. In order to enhance hypercube memory utilization and to allow expansion of image processing capabilities, a specialized program management method, incremental loading, was devised. To minimize data transfer between host and hypercube a data management method which distributes, redistributes, and tracks data set information was implemented.

Lee, Meemong↗

Sea-ice software: ICEMAN

An oceanographer's work bench which provides tools for ice data display, ice type classification, global and local ice motion analysis, and data enhancing is presented. The user interface; ice texture analysis; and ice motion analysis are described.

Lee, Meemong↗