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Wu, S.

Publications and source records attributed to Wu, S..

At least 19 records

Enforcing Self-Consistent Kinematic Constraints in Neutrino Energy Estimators

Machine learning algorithms have long been utilized across many experimental collaborations within the neutrino physics community in applications to ascertain the singular kinematic quantity of initial neutrino energy for use in neutrino oscillation analyses. However, most of these algorithms do not incorporate a coherent physical picture of initial neutrino kinematics, opting to introduce loss functions involving knowledge of only |pν |. Here, we argue for the introduction of composite loss functions utilizing the full kinematic description of the neutrino, pν ≡ (E, px, py , pz ), compiling all relevant energy and angle information consistently. The use of such a fully defined variable can be seen as a usage of Physics Informed Machine Learning.

Richi, R. R.

The Challenges of Measuring Methane from Space with a Lidar

The global and regional quantification of methane fluxes and identification of its sources and sinks has been highlighted as one of the goals of the NASA 2017 Earth Science Decadal Survey. Detecting methane from space and airborne platforms with an active (laser) remote sensing instrument presents several unique technology and measurement challenges. The instrument must have a single frequency, narrow-linewidth light source, and photon-sensitive detector at the right spectral region to make continuous measurements from orbit, day and night, all seasons and at all latitudes. It must have a high signal to noise ratio and must be relatively immune to biases from aerosol/cloud scattering, spectroscopic and meteorological data uncertainties, and instrument systematic errors. At Goddard Space Flight Center (GSFC), in collaboration with industry, we have developed an airborne instrument to measure methane. Our instrument is a nadir-viewing lidar that uses Integrated Path Differential Absorption (IPDA), to measure methane near 1.65 µm. We sample the absorption line using multiple wavelengths from a narrow linewidth laser source and a sensitive photodetector. This measurement approach provides maximum information content about the CH4 column, and minimizes biases in the XCH4 retrieval. In this paper, we will review our progress to date and discuss the technology challenges, options and tradeoffs to measure methane from space and airborne platforms.

airborne instruments

ADEPT Sounding Rocket One (SR-1)Flight Experiment Overview

The SR-1 flight experiment will demonstrate most of the primary end-to-end mission stages including: launch in a stowed configuration, separation and deployment in exo-atmospheric conditions, and passive ballistic re-entry of a 70-degree half-angle faceted cone geometry.

mechanical

Space Qualification of the Optical Filter Assemblies for the ICESat-2/ATLAS Instrument

The Advanced Topographic Laser Altimeter System (ATLAS) will be the only instrument on the Ice, Cloud, and Land Elevation Satellite -2 (ICESat-2). ICESat-2 is the 2nd-generation of the orbiting laser altimeter ICESat, which will continue polar ice topography measurements with improved precision laser-ranging techniques. In contrast to the original ICESat design, ICESat-2 will use a micro-pulse, multi-beam approach that provides dense cross-track sampling to help scientists determine a surface's slope with each pass of the satellite. The ATLAS laser will emit visible, green laser pulses at a wavelength of 532 nm and a rate of 10 kHz and will be split into 6 beams. A set of six identical, thermally tuned optical filter assemblies (OFA) will be used to remove background solar radiation from the collected signal while transmitting the laser light to the detectors. A seventh assembly will be used to monitor the laser center wavelength during the mission. In this paper, we present the design and optical performance measurements of the ATLAS OFA in air and in vacuum prior to their integration on the ATLAS instrument.

Etalons

Source Attribution and Interannual Variability of Arctic Pollution in Spring Constrained by Aircraft (ARCTAS, ARCPAC) and Satellite (AIRS) Observations of Carbon Monoxide

We use aircraft observations of carbon monoxide (CO) from the NASA ARCTAS and NOAA ARCPAC campaigns in April 2008 together with multiyear (2003-2008) CO satellite data from the AIRS instrument and a global chemical transport model (GEOS-Chem) to better understand the sources, transport, and interannual variability of pollution in the Arctic in spring. Model simulation of the aircraft data gives best estimates of CO emissions in April 2008 of 26 Tg month-1 for Asian anthropogenic, 9.1 for European anthropogenic, 4.2 for North American anthropogenic, 9.3 for Russian biomass burning (anomalously large that year), and 21 for Southeast Asian biomass burning. We find that Asian anthropogenic emissions are the dominant source of Arctic CO pollution everywhere except in surface air where European anthropogenic emissions are of similar importance. Synoptic pollution influences in the Arctic free troposphere include contributions of comparable magnitude from Russian biomass burning and from North American, European, and Asian anthropogenic sources. European pollution dominates synoptic variability near the surface. Analysis of two pollution events sampled by the aircraft demonstrates that AIRS is capable of observing pollution transport to the Arctic in the mid-troposphere. The 2003-2008 record of CO from AIRS shows that interannual variability averaged over the Arctic cap is very small. AIRS CO columns over Alaska are highly correlated with the Ocean Nino Index, suggesting a link between El Nino and northward pollution transport. AIRS shows lower-than-average CO columns over Alaska during April 2008, despite the Russian fires, due to a weakened Aleutian Low hindering transport from Asia and associated with the moderate 2007-2008 La Nina. This suggests that Asian pollution influence over the Arctic may be particularly large under strong El Nino conditions.

Fisher, J. A.

A Test of Sensitivity to Convective Transport in a Global Atmospheric CO2 Simulation

Two approximations to convective transport have been implemented in an offline chemistry transport model (CTM) to explore the impact on calculated atmospheric CO2 distributions. GlobalCO2 in the year 2000 is simulated using theCTM driven by assimilated meteorological fields from the NASA s Goddard Earth Observation System Data Assimilation System, Version 4 (GEOS-4). The model simulates atmospheric CO2 by adopting the same CO2 emission inventory and dynamical modules as described in Kawa et al. (convective transport scheme denoted as Conv1). Conv1 approximates the convective transport by using the bulk convective mass fluxes to redistribute trace gases. The alternate approximation, Conv2, partitions fluxes into updraft and downdraft, as well as into entrainment and detrainment, and has potential to yield a more realistic simulation of vertical redistribution through deep convection. Replacing Conv1 by Conv2 results in an overestimate of CO2 over biospheric sink regions. The largest discrepancies result in a CO2 difference of about 7.8 ppm in the July NH boreal forest, which is about 30% of the CO2 seasonality for that area. These differences are compared to those produced by emission scenario variations constrained by the framework of Intergovernmental Panel on Climate Change (IPCC) to account for possible land use change and residual terrestrial CO2 sink. It is shown that the overestimated CO2 driven by Conv2 can be offset by introducing these supplemental emissions.

Bian, H.

GRACE: millimeters and microns in orbit

The Gravity Recovery and Climate Experiment launched March 17, 2002. The GPS data for this experiment are processed to contribute to the recover long wavelength gravity field; remove errors due to long term on-board oscillator drift; and align K/Ka-band measurments between the two spacecraft to 0.1 ns. This paper will concentrate on the use of GPS for these timing and calibration functions and will not address the recovery of the gravity field.

GRACE GPS K/Ka-band