Engineering topics

Zhaoyan Liu

Publications and source records attributed to Zhaoyan Liu.

At least 19 records

NASA NTRS2024

Differential Absorption Lidar for Searching Water Sources on Mars

Water vapor has been detected in the Martian atmosphere by multiple orbiting instruments. The Atmospheric Chemistry Suite (ACS) on the ExoMars Trace Gas Orbiter (TGO) observed H2O mixing ratios reaching up to 50 ppmv at altitudes of 100-120 km during global dust storms, while levels remained low (<2 ppmv) during other seasons. The Neutral Gas and Ion Mass Spectrometer (NGIMS) on the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft revealed that water transported to the upper atmosphere is dissociated by ions, producing atomic hydrogen that escapes into space, contributing to Mars’ water loss. This transport is seasonal, peaking in southern summer and intensifying during dust storms. Additionally, the Mars Reconnaissance Orbiter’s (MRO) imaging spectrometer detected hydrated minerals on slopes, suggesting that liquid water may intermittently flow on present-day Mars. However, an observational gap exists between high-altitude water vapor and surface water due to limitations in spatial resolution and a lack of measurements in the lower atmosphere. To address this gap, we propose using an airborne differential absorption lidar (DIAL) to search for water sources. DIAL provides high-resolution measurements both day and night, bridging the observational gap between high-altitude water vapor and surface water, thus enhancing our understanding of water transport and loss on Mars. Absorption lines of water vapor in the 2.7 μm and 1.8 μm bands have been selected in this study. Simulations show that both lines are capable of detecting water vapor sources with reasonable system parameters.

lidar↗

NASA NTRS2023

Wind Profiling With the Airborne Doppler Aerosol Wind Lidar During the 2022 Convective Processes Experiment

The 2017 Decadal Survey for Earth Science and Applications from Space (ESAS 2017) identifies a critical need for improving our understanding of Planetary Boundary Layer (PBL) processes and air-surface fluxes as well as why clouds, convection, and heavy precipitation occur when and where they do. Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space. The wind lidar team at the NASA Langley Research Center (LaRC) started the development of Doppler wind lidar more than a decade ago to demonstrate technologies required for an Earth-orbiting system to globally measure wind profiles. Since then, an airborne Doppler Aerosol WiNd (DAWN) lidar system has been developed and participated in a series of field campaigns. The Doppler Aerosol WiNd (DAWN) lidar uses atmospheric aerosol motion to derive vertical profiles of horizontal wind speed and direction beneath the aircraft. In September 2022, DAWN, along with a suite of other instruments, was flown on a NASA DC-8 as part of The Convective Processes EXperiment – Cabo Verde (CPEX-CV) field campaign. A main objective of CPEX was to obtain a comprehensive set of temperature, humidity and, particularly, wind observations over tropical waters in undisturbed conditions, Saharan dust outbreaks, and in the vicinity of scattered through organized deep convection in all phases of the convective life cycle. DAWN collected data for approximately 90 hours across 13 CPEX-CV science flights. Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes were dropped throughout the flight for profiling the atmosphere and validating the DAWN instrument. DAWN had co-located data with 347 AVAPS NRD41 dropsondes, providing 32,117 vertical levels for a comprehensive validation of DAWN wind retrievals. DAWN showed very good agreement with dropsondes of ~0.2 m/s bias and ~1.8 m/s RMS. Given this agreement, DAWN is considered to be a worthy reference dataset, and its retrievals have been compared to winds derived from GOES Atmospheric Motion Vectors (AMVs), Advanced Scatterometer winds (ASCAT), and model data from GFS, GEOS, and MERRA-2 to better understand the quality of our current models and satellite wind observations. The proposed presentation will provide a brief description of the DAWN instrument, discuss the synergistic observations collected across a wide range of atmospheric conditions sampled during the CPEX-CV flights, and a summary of comparisons between DAWN, GOES AMV, ASCAT, and model analyses/predictions, with an emphasis on the PBL.

DAWN↗

NASA NTRS2023

Polarization Calibration Using Solar Radiation Background Signal Scattered from Dense Cirrus Clouds in the Visible and Ultraviolet Wavelength Regimes

In this presentation we describe the application of a previously developed technique that is now being used to correct the daytime polarization calibration of the CALIPSO lidar. The technique leverages the fact that the solar radiation background signals from dense cirrus clouds are largely unpolarized due to the internal multiple reflections within the non-spherical ice particles and the multiple scattering that occurs among these particles. Therefore, the ratio of polarization components of the cirrus background signals provides a good estimate for the polarization gain ratio (PGR) of the lidar. Using airborne backscatter lidar measurements, this technique was demonstrated to work well in the infrared regime. However, in the visible and ultraviolet regime, the molecular contribution is too large to be ignored, and thus corrections must be applied to account for the highly polarizing characteristics of the molecular scattering. Ignoring molecular scattering contributions can cause PGR errors of 2-3% at 532 nm, where the CALIPSO lidar makes its depolarization measurement. Because of the wavelength dependence of -4 of the molecular scattering, the PGR error can be even larger at the 355 nm wavelength that will be used by ESA’s EarthCARE lidar. To correct the molecular scattering contributions to the lidar received solar background signal, a look-up table has been created using a polarization-sensitive radiative transfer model. This presentation describes the theory and implementation of the molecular scattering correction.

Zhaoyan Liu↗

NASA NTRS2018

CALIPSO Lidar Calibration at 532 nm: Version 4 Nighttime Algorithm

Data products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were recently updated following the implementation of new (version 4) calibration algorithms for all of the level 1 attenuated backscatter measurements. In this work we present the motivation for and the implementation of the version 4 nighttime 532 nm parallel channel calibration. The nighttime 532 nm calibration is the most fundamental calibration of CALIOP data, since all of CALIOP’s other radiometric calibration procedures – i.e., the 532 nm daytime calibration and the 1064 nm calibrations during both nighttime and daytime – depend either directly or indirectly on the 532 nm nighttime calibration. The accuracy of the 532 nm nighttime calibration has been significantly improved by raising the molecular normalization altitude from 30-34 km to 36-39 km to substantially reduce stratospheric aerosol contamination. Due to the greatly reduced molecular number density and consequently reduced signal-to-noise ratio (SNR) at these higher altitudes, the signal is now averaged over a larger number of samples using data from multiple adjacent granules. As well, an enhanced strategy for filtering the radiation-induced noise from high energy particles was adopted. Further, the meteorological model used in the earlier versions has been replaced by the improved MERRA-2 model. An aerosol scattering ratio of 1.01 ± 0.01 is now explicitly used for the calibration altitude. These modifications lead to globally revised calibration coefficients which are, on average, 2-3% lower than in previous data releases. Further, the new calibration procedure is shown to eliminate biases at high altitudes that were present in earlier versions and consequently leads to an improved representation of stratospheric aerosols. Validation results using airborne lidar measurements are also presented. Biases relative to collocated measurements acquired by the Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) are reduced from 3.6% ± 2.2% in the version 3 data set to 1.6% ± 2.4 % in the version 4 release.

Jayanta Kar↗

NASA NTRSDate not supplied

TPSAS-NF1676L-17926-DND

Validation of the CALIOP data products remains an ongoing task for the CALIPSO team. Validating the optical properties of aerosols located above clouds is especially difficult, because independent measurements are usually not available. In this presentation we analyze 532-nm aerosol optical depth (AOD) above clouds, comparing results from the standard CALIOP algorithm with two alternate algorithms applied to CALIOP data acquired along the transport pathways of African dust and biomass burning aerosols. Multiple years of the CALIPSO nighttime data (2007-2012) were examined. The analysis was limited to cases where there are opaque water clouds below aerosol layers that can be used as a reference to retrieve AOD of the overlying aerosol layer.

Zhaoyan Liu↗

NASA NTRSDate not supplied

TPSAS-NF1676L-23459-DND

This talk covers the needs for carbon science, laser absorption lidar approach for atmospheric CO2 measurements, recent campaign findings, and future work on atmospheric CO2 observations.

Bing Lin↗

NASA NTRSDate not supplied

An Overview of the NASA ADM-Aeolus Cal/Val Test Flight Campaign

Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space for over 30 years. The Atmospheric Dynamics Mission Aeolus (ADM-Aeolus), the first-ever spaceborne Doppler wind lidar, was developed by the European Space Agency and launched in August 2018. The ADM-Aeolus Atmospheric Laser Doppler Instrument (ALADIN) observes profiles of the component of the wind vector and aerosol optical properties along the instrument’s line-of-sight direction on a global scale. Two airborne lidar systems have been developed at NASA Langley Research Center in recent years that collect measurements in support of several NASA Earth Science Division focus areas. The Doppler Aerosol WiNd (DAWN) lidar measures vertical profiles of horizontal wind speed and direction. The High Altitude Lidar Observatory (HALO) measure high resolution profiles of atmospheric water vapor (WV) and aerosol and cloud optical properties. Though new space-based missions with advanced capabilities such as Aeolus are continuously being conceived and developed, there are limitations in terms of spatial and vertical detail and measurement precision that can be accomplished from space, thus airborne remote sensing observations like those from DAWN and HALO are required to fill these observational gaps as well as to calibrate and validate space-based measurements. Over a two-week period in April 2019 during their Aeolus Cal/Val Test Flight campaign, NASA conducted five research flights over the Eastern Pacific Ocean with the DC-8 aircraft to 1) demonstrate the DAWN Doppler wind lidar, HALO high spectral resolution lidar aerosol/cloud measurement and differential absorption lidar WV measurement capabilities across a range of atmospheric conditions, 2) demonstrate Aeolus Cal/Val flight strategies and compare DAWN and HALO measurements with Aeolus to gain an initial perspective of Aeolus performance, and 3) demonstrate how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, WV, and aerosol profile observations, coupled with numerical model and other remote sensing observations. This paper provides a brief description of the DAWN and HALO instruments, discusses the synergistic observations collected across a wide range of atmospheric conditions sampled during the DC-8 flights, and a summary of the validation of DAWN, HALO, and Aeolus observations and comparisons.

Kristopher M. Bedka↗

NASA NTRSDate not supplied