ALBERT

Description: In this paper, we discuss the development of this very sensitive long waelength infrared (LWIR) camera based on a GaAs/AlGaAs QWIP focal plane array (FPA) and its performance in quantum efficiency, NEAT, uniformity, and operability.

Description: In this presentation, we will discuss the development of this large format broadband infrared FPA based on a GaAs/AlGaAs materials system and its performance in quantum efficiency, noise equivalent differential temperature, uniformity, and operability.

Description: NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Description: The Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3, launched in 2015 and 2019, respectively, are intended to collect and deliver high-resolution observations of CO2 with unprecedented space and time coverage. Observations of CO2 from these remote-sensing missions (also known as XCO2, or column-based average, dry air mole fraction of CO2) are then used by the global carbon cycle community to answer a wide range of science questions, from the distribution and quantification of global and regional CO2 source-sink patterns to quantification of anthropogenic sources at urban scales. Even though we have had the OCO-2 mission flying for a few years now, the retrieval algorithms are continuously evolving and improving to deliver XCO2 retrievals with very high precision and high accuracy (or low biases). In this presentation, we will discuss a simple yet effective quantitative framework that has been developed by the OCO-2 flux team to evaluate the information content of these XCO2 retrievals as soon as they are released, i.e., with lower latency than full-scale flux inversions. This framework serves as a precursor to advanced inverse modeling frameworks and is intended to provide an early but accurate assessment of the signal present in the satellite retrievals, the robustness of that signal, and the ability of these retrievals to resolve patterns in CO2 surface fluxes that cannot be resolved by our current network of surface sites. Specific results will tackle a tiered set of questions that are being addressed using this framework: (a) what are the distribution of retrievals in the different modes of operation and how do they vary in space and time? (b) what is the information that is being given to the inverse modeling frameworks from the space-based data, information above and beyond what is provided by the in-situ data? and (c) how do these factors influence our choices for doing flux inversions with the satellite retrievals? While the primary focus of the results will be on application of this technique to mature OCO-2 retrievals, we will show early results for a couple of months of OCO-3 retrievals. For the time-period that the retrievals from the two missions overlap, we will highlight how this framework allows us to effortlessly put the information from OCO-3 and OCO-2 on an equal footing, thus enabling easy comparison between the two pioneering missions.

Description: In this paper, we will discuss the performance in terms of quantum efficiency, NEAT, uniformity, operability, and modulation transfer functions of the 1024x1024 pixel arrays and the progress of dualband QWIP focal plane array development work.

Description: Water scarcity is rapidly increasing in many regions. In a novel, multi-model assessment, we examine how human interventions (HI: land use and land cover change, man-made reservoirs and human water use) affected monthly river water availability and water scarcity over the period 1971 - 2010. Here we show that HI drastically change the critical dimensions of water scarcity, aggravating water scarcity for 8.8%(7.4 - 16.5 %) ) of the global population but alleviating it for another 8.3 % (6.4 -15.8 %). Positive impacts of HI mostly occur upstream, whereas HI aggravate water scarcity downstream; HI cause water scarcity to travel downstream. Attribution of water scarcity changes to HI components is complex and varies among the hydrological models. Seasonal variation in impacts and dominant HI components is also substantial. A thorough consideration of the spatially and temporally varying interactions among HI components and of uncertainties is therefore crucial for the success of water scarcity adaptation by HI.