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Dive into the research topics where Xianglei Huang is active.

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Featured researches published by Xianglei Huang.


Bulletin of the American Meteorological Society | 2013

Achieving Climate Change Absolute Accuracy in Orbit

Bruce A. Wielicki; David F. Young; M. G. Mlynczak; Kurt J. Thome; Stephen S. Leroy; James M. Corliss; J. G. Anderson; Chi O. Ao; Richard J. Bantges; Fred A. Best; Kevin W. Bowman; Helen E. Brindley; James J. Butler; William D. Collins; John Andrew Dykema; David R. Doelling; Daniel R. Feldman; Nigel P. Fox; Xianglei Huang; Robert E. Holz; Yi Huang; Zhonghai Jin; D. Jennings; David G. Johnson; K. Jucks; Seima Kato; Daniel Bernard Kirk-Davidoff; Robert O. Knuteson; Greg Kopp; David P. Kratz

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREOs inherently high absolute accuracy will be verified and traceable on orbit to Systeme Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earths thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which...


Geophysical Research Letters | 2007

A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations

Yi Huang; V. Ramaswamy; Xianglei Huang; Qiang Fu; Charles G. Bardeen

discrepancies in the water vapor v2 (1300–1650 cm 1 ) and carbon dioxide v2 (650–720 cm 1 ) bands are consistent with the model biases in atmospheric temperature and water vapor. The existence of radiance biases of opposite signs in different spectral regions suggests that a seemingly good agreement of the model’s broadband longwave flux with observations may be due to a fortuitous cancellation of spectral errors. Moreover, an examination of the diurnal difference spectrum indicates pronounced biases in the model-simulated diurnal hydrologic cycle over the tropical oceans, a feature seen to occur in other GCMs as well. Citation: Huang, Y., V. Ramaswamy, X. Huang, Q. Fu, and C. Bardeen (2007), A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations, Geophys. Res. Lett., 34, L24707, doi:10.1029/ 2007GL031409.


Journal of the Atmospheric Sciences | 2011

Temperature and Water Vapor Variance Scaling in Global Models: Comparisons to Satellite and Aircraft Data

Brian H. Kahn; João Teixeira; Eric J. Fetzer; Andrew Gettelman; Svetla M. Hristova-Veleva; Xianglei Huang; Adam K. Kochanski; M. Köhler; Steven K. Krueger; Robert Wood; Ming Zhao

AbstractObservations of the scale dependence of height-resolved temperature T and water vapor q variability are valuable for improved subgrid-scale climate model parameterizations and model evaluation. Variance spectral benchmarks for T and q obtained from the Atmospheric Infrared Sounder (AIRS) are compared to those generated by state-of-the-art numerical weather prediction “analyses” and “free-running” climate model simulations with spatial resolution comparable to AIRS. The T and q spectra from both types of models are generally too steep, with small-scale variance up to several factors smaller than AIRS. However, the two model analyses more closely resemble AIRS than the two free-running model simulations. Scaling exponents obtained for AIRS column water vapor (CWV) and height-resolved layers of q are also compared to the superparameterized Community Atmospheric Model (SP-CAM), highlighting large differences in the magnitude of CWV variance and the relative flatness of height-resolved q scaling in SP-...


Journal of Geophysical Research | 2005

Spatial and spectral variability of the outgoing thermal IR spectra from AIRS: A case study of July 2003

Xianglei Huang; Yuk L. Yung

Here we present a survey of the spatial variability in different climate zones seen from AIRS data using the spectral EOF analysis. Over the tropical and subtropical oceans, the first principal component (PC1) is mostly due to the thermal contrast between surface and thick cold cloud tops. The second principal component (PC2) is mainly due to the spatial variation of the lower tropospheric humidity (LTH) and the low clouds. The signature of dust aerosol over the Arabian Sea and the Atlantic off the coast of North Africa in the summertime can be clearly seen in the PC2. Both the PC1 and the PC2 capture the upper tropospheric water vapor variability due to the forced orthogonality of EOFs. The third principal component (PC3) is mainly due to the spatial variation of the lower stratospheric temperature. Over the midlatitude oceans, the PC1 is still due to the thermal contrast of emission temperature. During wintertime, the PC2 is mainly due to stratospheric temperature variations. In the summer, the PC2 over the southern hemisphere is still due to stratospheric temperature variations, but in the northern hemisphere it is mainly due to the variations of the LTH and the low clouds. An exploratory study using synthetic spectra based on a NCAR CAM2 simulation shows that the model could account for the essential features in the data as well as provide an explanation of the three leading PCs. Major disagreements exist in the location of the ITCZ, the dust aerosol, and the lower stratospheric temperature.


Journal of Climate | 2008

Winter-to-Spring Transition in East Asia: A Planetary-Scale Perspective of the South China Spring Rain Onset

L. H. Linho; Xianglei Huang; Ngar Cheung Lau

Analysis of observations from 1979 to 2002 shows that the seasonal transition from winter to spring in East Asia is marked with a distinctive event—the onset of the south China spring rain (SCSR). In late February, the reduced thermal contrast between ocean and land leads to weakening of the Asian winter monsoon as well as the Siberian high and the Aleutian low. Meanwhile, convection over Australia and the western Pacific Maritime Continent is suppressed on the passage of the dry phase of a Madden–Julian oscillation (MJO). In conjunction with the seasonal march of monsoon circulation in the Indonesian– Australian sector, this MJO passage weakens the local thermally direct cell in the East Asia–Australia sector. This development is further accompanied by a series of adjustments in both the tropics and midlatitudes. These changes include attenuation of the planetary stationary wave, considerable weakening of the westerly jet stream over much of the central Pacific adjacent to Japan, and reduction of baroclinicity near the East Asian trough. The influence of concurrent local processes in midlatitudes on the SCSR onset is also important. The weakened jet stream is associated with confinement of frontal activities to the coastal regions of East Asia as well as with rapid expansion of the subtropical Pacific high from the eastern Pacific to the western Pacific. A parallel analysis using output from an experiment with a GFDL-coupled GCM shows that the above sequence of circulation changes is well simulated in that model.


Geophysical Research Letters | 2002

Cloud variability as revealed in outgoing infrared spectra: Comparing model to observation with spectral EOF analysis

Xianglei Huang; John D. Farrara; Stephen Sylvain Leroy; Yuk L. Yung; Richard Goody

[1] Spectrally resolved outgoing radiance is a potentially powerful tool for testing climate models. To show how it can be used to evaluate the simulation of cloud variability, which is the principal uncertainty in current climate models, we apply spectral empirical orthogonal function (EOF) analysis to satellite radiance spectra and synthetic spectra derived from a general circulation model (GCM). We show that proper averaging over a correct timescale is necessary before applying spectral EOF analysis. This study focuses on the Central Pacific and the western Pacific Warm Pool. For both observation and GCM output, cloud variability is the dominant contributor to the first principal component that accounts for more than 95% of the total variance. However, the amplitude of the first principal component derived from the observations (2 � 3.4 Wm � 2 )i s 2� 6 times greater than that of the GCM simulation. This suggests that cloud variability in the GCM is significantly smaller than that in the real atmosphere. INDEX TERMS: 3359 Meterology and Atmospheric Dynamics: Radiative processes; 3360 Meterology and Atmospheric Dynamics: Remote sensing; 3337 Meterology and Atmospheric Dynamics: Numerical modeling and data assimilation; 3399 Meterology and Atmospheric Dynamics: General or miscellaneous


Proceedings of the National Academy of Sciences of the United States of America | 2014

Far-infrared surface emissivity and climate

Daniel R. Feldman; William D. Collins; Robert Pincus; Xianglei Huang

Significance We find that many of the Earths climate variables, including surface temperature, outgoing longwave radiation, cooling rates, and frozen surface extent, are sensitive to far-IR surface emissivity, a largely unconstrained, temporally and spatially heterogeneous scaling factor for the blackbody radiation from the surface at wavelengths between 15 μm and 100 μm. We also describe a previously unidentified mechanism that amplifies high-latitude and high-altitude warming in finding significantly lower values of far-IR emissivity for ocean and desert surfaces than for sea ice and snow. This leads to a decrease in surface emission at far-IR wavelengths, reduced cooling to space, and warmer radiative surface temperatures. Far-IR emissivity can be measured from spectrally resolved observations, but such measurements have not yet been made. Presently, there are no global measurement constraints on the surface emissivity at wavelengths longer than 15 μm, even though this surface property in this far-IR region has a direct impact on the outgoing longwave radiation (OLR) and infrared cooling rates where the column precipitable water vapor (PWV) is less than 1 mm. Such dry conditions are common for high-altitude and high-latitude locations, with the potential for modeled climate to be impacted by uncertain surface characteristics. This paper explores the sensitivity of instantaneous OLR and cooling rates to changes in far-IR surface emissivity and how this unconstrained property impacts climate model projections. At high latitudes and altitudes, a 0.05 change in emissivity due to mineralogy and snow grain size can cause a 1.8–2.0 W m−2 difference in the instantaneous clear-sky OLR. A variety of radiative transfer techniques have been used to model the far-IR spectral emissivities of surface types defined by the International Geosphere-Biosphere Program. Incorporating these far-IR surface emissivities into the Representative Concentration Pathway (RCP) 8.5 scenario of the Community Earth System Model leads to discernible changes in the spatial patterns of surface temperature, OLR, and frozen surface extent. The model results differ at high latitudes by as much as 2°K, 10 W m−2, and 15%, respectively, after only 25 y of integration. Additionally, the calculated difference in far-IR emissivity between ocean and sea ice of between 0.1 and 0.2, suggests the potential for a far-IR positive feedback for polar climate change.


Journal of the Atmospheric Sciences | 2004

A Common Misunderstanding about the Voigt Line Profile

Xianglei Huang; Yuk L. Yung

In this short note, a misinterpretation of the Voigt line profile is pointed out, which is in several popular textbooks of atmospheric physics. The correct interpretation is given based on mathematical and physical arguments, as well as numerical verification.


Journal of Climate | 2016

Observation-Based Longwave Cloud Radiative Kernels Derived from the A-Train

Qing Yue; Brian H. Kahn; Eric J. Fetzer; Mathias Schreier; Sun Wong; Xianglei Huang

AbstractThe authors present a new method to derive both the broadband and spectral longwave observation-based cloud radiative kernels (CRKs) using cloud radiative forcing (CRF) and cloud fraction (CF) for different cloud types using multisensor A-Train observations and MERRA data collocated on the pixel scale. Both observation-based CRKs and model-based CRKs derived from the Fu–Liou radiative transfer model are shown. Good agreement between observation- and model-derived CRKs is found for optically thick clouds. For optically thin clouds, the observation-based CRKs show a larger radiative sensitivity at TOA to cloud-cover change than model-derived CRKs. Four types of possible uncertainties in the observed CRKs are investigated: 1) uncertainties in Moderate Resolution Imaging Spectroradiometer cloud properties, 2) the contributions of clear-sky changes to the CRF, 3) the assumptions regarding clear-sky thresholds in the observations, and 4) the assumption of a single-layer cloud. The observation-based CRKs...


Geophysical Research Letters | 2014

Sensitivity of modeled far‐IR radiation budgets in polar continents to treatments of snow surface and ice cloud radiative properties

Xianglei Huang; Mark G. Flanner

While most general circulation models assume spectrally independent surface emissivity and nonscattering clouds in their longwave radiation treatment, spectral variation of the index of refraction of ice indicates that in the far IR, snow surface emissivity can vary considerably and ice clouds can cause nonnegligible scattering. These effects are more important for high-elevation polar continents where the dry and cold atmosphere is not opaque in the far IR. We carry out sensitivity studies to show that in a winter month over the Antarctic Plateau including snow surface spectral emissivity and ice cloud scattering in radiative transfer calculation reduces net upward far-IR flux at both top of atmosphere and surface. The magnitudes of such reductions in monthly mean all-sky far-IR flux range from 0.72 to 1.47 Wm−2, with comparable contributions from the cloud scattering and the surface spectral emissivity. The reduction is also sensitive to sizes of both snow grains and cloud particles.

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Yuk L. Yung

California Institute of Technology

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Xu Liu

Langley Research Center

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Daniel R. Feldman

Lawrence Berkeley National Laboratory

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V. Ramaswamy

Geophysical Fluid Dynamics Laboratory

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Brian H. Kahn

California Institute of Technology

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Hui Su

California Institute of Technology

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