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Dive into the research topics where Hongqing Liu is active.

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Featured researches published by Hongqing Liu.


Journal of Geophysical Research | 2014

Preliminary evaluation of S‐NPP VIIRS aerosol optical thickness

Hongqing Liu; Lorraine A. Remer; Jingfeng Huang; Ho-Chun Huang; Shobha Kondragunta; Istvan Laszlo; Min Oo; John M. Jackson

The Visible Infrared Imaging Radiometer Suite (VIIRS) is the next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. The VIIRS aerosol Environmental Data Record (EDR) is expected to continue the decade-long successful multispectral aerosol retrieval from the NASAs Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) for scientific research and applications. Since the launch of the Suomi National Polar-orbiting Partnership (S-NPP), the VIIRS aerosol calibration/validation team has been continuously monitoring, evaluating, and improving the performance of VIIRS aerosol retrievals. In this study, the VIIRS aerosol optical thickness (AOT) at 550 nm EDR at current Provisional maturity level is evaluated by comparing it with MODIS retrievals and measurements from the Aerosol Robotic Network (AERONET) and the Maritime Aerosol Network (MAN). The VIIRS global mean AOT at 550 nm differs from that of MODIS by approximately −0.01 over ocean and 0.03 over land (0.00 and −0.01 for the collocated retrievals) but shows larger regional biases. Global validation with AERONET and with MAN measurements shows biases of 0.01 over ocean and −0.01 over land, with about 64% and 71% of retrievals falling within the expected uncertainty range established by MODIS over ocean (±(0.03 + 0.05AOT)) and over land (±(0.05 + 0.15AOT)), respectively. The VIIRS retrievals over land exhibit slight overestimation over vegetated surfaces and underestimation over soil-dominated surfaces. These results show that the VIIRS AOT at 550 nm product provides a solid global data set for quantitative scientific investigations and environmental monitoring.


international geoscience and remote sensing symposium | 2008

An Evaluation of the GOES-R ABI Aerosol Retrieval Algorithm

Hongqing Liu; Istvan Laszlo; Pubu Ciren; Mi Zhou; Shobha Kondragunta

A multi-channel aerosol retrieval algorithm has been developed for the Advanced Baseline Imager (ABI) onboard the next generation US Geostationary Operational Environmental Satellite (GOES-R series). Testing and evaluation of this algorithm is carried out with model simulated and satellite-observed multi-spectral reflectance. Sensitivity tests with synthetic reflectance show that ABI retrieved aerosol optical depth at 0.55 mum (tau0.55 mum) is expected to change by 5% and 9% (14% and 24%) on average over water (land) corresponding to 3% and 5% uncertainties in calibration. Model identification is expected to have a 50%-60% success rate for a 3%-5% calibration uncertainty. Performance of ABI aerosol retrieval is evaluated with MODIS observations. Compared with AERONET ground measurements, on average, retrieved tau0.55 mum differs from AERONET measurements by -0.02plusmn0.05 over water and 0.05plusmn0.17 over land. The effect of sensor polarization sensitivity on ABI aerosol retrievals is also estimated as a bias of -0.01 over water and -0.05 over land for the retrieved tau0.55 mum.


Journal of Geophysical Research | 2013

Suomi‐NPP VIIRS aerosol algorithms and data products

John M. Jackson; Hongqing Liu; Istvan Laszlo; Shobha Kondragunta; Lorraine A. Remer; Jingfeng Huang; Ho-Chun Huang


Advances in Space Research | 2008

Remote sensing of aerosol and radiation from geostationary satellites

Istvan Laszlo; Pubu Ciren; Hongqing Liu; Shobha Kondragunta; J. Dan Tarpley; Mitchell D. Goldberg


Journal of Geophysical Research | 2016

Validation and expected error estimation of suomi‐NPP VIIRS aerosol optical thickness and ångström exponent with AERONET

Jingfeng Huang; Shobha Kondragunta; Istvan Laszlo; Hongqing Liu; Lorraine A. Remer; Hai Zhang; Stephen Superczynski; Pubu Ciren; Brent N. Holben; Maksym Petrenko


Journal of Geophysical Research | 2014

Preliminary evaluation of S-NPP VIIRS aerosol optical thickness: VIIRS AOT VALIDATION

Hongqing Liu; Lorraine A. Remer; Jingfeng Huang; Ho-Chun Huang; Shobha Kondragunta; Istvan Laszlo; Min Oo; John M. Jackson


Journal of Geophysical Research | 2013

Suomi-NPP VIIRS aerosol algorithms and data products: SUOMI-NPP VIIRS AEROSOL ALGORITHMS

John M. Jackson; Hongqing Liu; Istvan Laszlo; Shobha Kondragunta; Lorraine A. Remer; Jingfeng Huang; Ho-Chun Huang


Journal of Geophysical Research | 2008

Comparison of single‐channel and multichannel aerosol optical depths derived from MAPSS data

Istvan Laszlo; Hongqing Liu; Alexander Ignatov


Atmospheric Measurement Techniques | 2018

Screening for snow/snowmelt in SNPP VIIRS aerosol optical depth algorithm

Jingfeng Huang; Istvan Laszlo; Lorraine A. Remer; Hongqing Liu; Hai Zhang; Pubu Ciren; Shobha Kondragunta


international geoscience and remote sensing symposium | 2017

Exceptional events monitoring using S-NPP VIIRS aerosol products

Shobha Kondragunta; Istvan Laszlo; Pubu Ciren; Hai Zhang; Hongqing Liu; Jingfeng Huang; Amy K. Huff

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Istvan Laszlo

National Oceanic and Atmospheric Administration

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Shobha Kondragunta

National Oceanic and Atmospheric Administration

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Pubu Ciren

National Oceanic and Atmospheric Administration

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Hai Zhang

National Oceanic and Atmospheric Administration

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Ho-Chun Huang

National Oceanic and Atmospheric Administration

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Brent N. Holben

Goddard Space Flight Center

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Maksym Petrenko

Goddard Space Flight Center

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Min Oo

University of Wisconsin-Madison

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Stephen Superczynski

National Oceanic and Atmospheric Administration

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