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Kuan-Man Xu (NASA)

Title: Senior Research Scientist
Technical Focus Area: Climate Science
Mission/Project: CERES
Study Topics: Cloud and climate modeling, boundary layer turbulence, low clouds, deep convection and convective organization


Over 30 years of experience in cloud/climate modeling and 20 years of experience in satellite data analysis, focusing on improving cloud parameterizations, cloud-system resolving modeling, study of distinct cloud systems (“cloud object”) identified from satellite data, and improving higher-order turbulence closure and cloud microphysics parameterizations, as well as contributing to the improvement of multi-scale modeling framework (MMF). Dr. Xu was involved with the DOE Atmospheric Radiation Measurement (ARM) program between 1991 and 2015. He was a partner of an NSF Science and Technology center between 2006 and 2016. He led case studies of the ARM/GCSS CRM and single-column model intercomparison. He led two NASA EOS interdisciplinary study projects and was a member of the NOAA-NSF Climate Process Team. Dr. Xu has published ~100 peer-reviewed papers. He served as an associate editor for Journal of Climate between 2001 and 2004, as an official reviewer for various international journals, NSF, DOE, NOAA, NASA, NERC (UK), CFCAS (Canada) and New Zealand Antarctic Research Institute proposals and as a member of various review panels within NASA and DOE.

Publication Bibliography:

Select Publications:

  •  Li, Z., K.-M. Xu, 2019: Arctic clouds simulated by a multiscale modeling framework and comparisons with observations and conventional GCMs. J. Geophys. Res., 124,
  • Xu, K.-M., Z. Li, A. Cheng, P. N. Blossey, and C. Stan, 2017: Differences in the hydrological cycle and sensitivity between multiscale modeling frameworks with and without a higher-order turbulence closure, J. Adv. Mod. Earth System, 9, 2120-2137. 
  • Xu, K.-M., and A. Cheng, 2016: Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework. J. Adv. Mod. Earth System, 8, doi: 10.1002/2016MS000767. 
  • Cheng, A., and K.-M. Xu, 2015: Improved low-cloud simulation from the Community Atmosphere Model with an advanced third-order turbulence closure. J. Climate, 28, 5737–5762. 
  • Xu, K.-M, and A. Cheng, 2013a: Evaluating low cloud simulation from an upgraded multiscale modeling framework. Part I: Sensitivity to spatial resolution and climatology. J. Climate, 26, 5717-5740. doi:10.1175/JCLI-D-12-00200.1. 
  • Xu, K.-M, and A. Cheng, 2013b: Evaluating low cloud simulation from an upgraded multiscale modeling framework. Part II: Seasonal variations over the Eastern Pacific. J. Climate, 26, 5741-5760. doi:10.1175/JCLI-D-12-00276.1. 
  • Xu, K.-M., and coauthors, 2002: An intercomparison of cloud-resolving models with the ARM summer 1997 IOP data. Q. J. Roy. Meteor. Soc., 128, 593-624.
  • Xu, K.-M., and D. A. Randall, 1996a: A semi-empirical cloudiness parameterization for use in climate models. J. Atmos. Sci., 53, 3084-3102.
  • Xu, K.-M., and S. K. Krueger, 1991: Evaluation of cloudiness parameterizations using a cumulus ensemble model. Mon. Wea. Rev., 119, 342-367. 
  • Xu, K.-M., and K. A. Emanuel, 1989: Is the tropical atmosphere conditionally unstable? Mon. Wea. Rev., 117, 1471-1479.


  • NASA Exceptional Scientific Achievement Medal, 2009
  • Henry J. E. Reid Award for best publication, Langley Research Center, 2008

Professional Memberships:

  • AGU
  • AMS
  • AOGS


  • Education Ph.D. – Atmospheric Sciences, UCLA, 1991
  • M.S. – Meteorology, MIT, 1987 B.A. – Marine Meteorology, Ocean University of China, 1982

Professional Experience:

  • Senior Research Scientist, NASA Langley Research Center (2000-present)
  • Research Associate & Scientist, Colorado State University (1991-2000)

Need to get in touch with Kuan-Man Xu? Fill out the contact form below. 

SD Profiles Contact
  • CAPABLE/CRAVE Full Site Photo from left to right site enclosures: 1196A NASA LaRC, MPLnet, Virginia DEQ
    CAPABLE/CRAVE Full Site Photo from left to right site enclosures: 1196A NASA LaRC, MPLnet, Virginia DEQ

  • NASA LaRC NAST-I and HU ASSIST side-by-side for intercomparison
    NASA LaRC NAST-I and HU ASSIST side-by-side for intercomparison

  • Virginia DEQ, NASA and Penn State-NATIVE Enclosures (from right to left)
    Virginia DEQ, NASA and Penn State-NATIVE Enclosures (from right to left)

  • Ozone-sonde away.
    Ozone-sonde away.
  • About to lift.
    About to lift.
PurpleAir PA-II-SD Air Quality Sensor
Laser Particle Counters
Type (2) PMS5003
Range of measurement 0.3, 0.5, 1.0, 2.5, 5.0, & 10 μm
Counting efficiency 50% at 0.3μm & 98% at ≥0.5μm
Effective range
(PM2.5 standard)*
0 to 500 μg/m³
Maximum range (PM2.5 standard)* ≥1000 μg/m³
Maximum consistency error (PM2.5 standard) ±10% at 100 to 500μg/m³ & ±10μg/m³ at 0 to 100μg/m³
Standard Volume 0.1 Litre
Single response time ≤1 second
Total response time ≤10 seconds
Pressure, Temperature, & Humidity Sensor
Type BME280
Temperature range -40°F to 185°F (-40°C to 85°C)
Pressure range 300 to 1100 hPa
Humidity Response time (τ63%): 1 s
Accuracy tolerance: ±3% RH
Hysteresis: ≤2% RH

Pandora capabilities










Total Column O3, NO2, HCHO, SO2, H2O, BrO

0.01 DU

0.1 DU



Virginia Department of Environment Quality in-situ instrumentation






Thermo Scientific 42C (Molybdenum converter)

60 s

NO and NOx

50 pptv


Teledyne API 200EU w/ photolytic converter
(EPA) PI-Szykman

20 s


50 pptv


Thermo Scientific 49C (VADEQ)

20 s


1 ppbv


Thermo Scientific 48i (VADEQ)

60 s


40 ppbv


Thermo Scientific 43i (VADEQ)

80 s


0.2 ppbv


Thermo Scientific 1400AB TEOM (VADEQ)

600 s

PM2.5 (continuous)


1 3%

Thermo Scientific Partisol Plus 2025 (VADEQ)

24 hr

PM2.5 (filter-based FRM)- 1/3 days



Large area view.
Latitude: 37.1038
Longitude: -76.3872
Elevation: 3 m Above sea level
Scenes: urban, marsh, bay, river and farm.


  • The inner red circle is a 20km CERES foot print centered on the BSRN-LRC site.
  • The pink circle represents a possible tangential 20km foot print.
  • The middle red circle represents the area in which a 20km foot print could fall and still see the site.
  • Yellow is a sample 40 deg off nadir foot print.
  • The outer red circle is the region which would be seen by a possible 40 deg off nadir foot print.
The BSRN-LRC sun tracker at the NASA Langley Research Center on a snowy day (02/20/2015) The BSRN-LRC sun tracker at the NASA Langley Research Center on a snowy day (02/20/2015)
CAPABLE-BSRN Google Site Location Image

Team Satellite Sensor G/L Dates Number of obs Phase angle range (°)
CMA FY-3C MERSI LEO 2013-2014 9 [43 57]
CMA FY-2D VISSR GEO 2007-2014
CMA FY-2E VISSR GEO 2010-2014
CMA FY-2F VISSR GEO 2012-2014
JMA MTSAT-2 IMAGER GEO 2010-2013 62 [-138,147]
JMA GMS5 VISSR GEO 1995-2003 50 [-94,96]
JMA Himawari-8 AHI GEO 2014- -
EUMETSAT MSG1 SEVIRI GEO 2003-2014 380/43 [-150,152]
EUMETSAT MSG2 SEVIRI GEO 2006-2014 312/54 [-147,150]
EUMETSAT MSG3 SEVIRI GEO 2013-2014 45/7 [-144,143]
EUMETSAT MET7 MVIRI GEO 1998-2014 128 [-147,144]
CNES Pleiades-1A PHR LEO 2012 10 [+/-40]
CNES Pleiades-1B PHR LEO 2013-2014 10 [+/-40]
NASA-MODIS Terra MODIS LEO 2000-2014 136 [54,56]
NASA-MODIS Aqua MODIS LEO 2002-2014 117 [-54,-56]
NASA-VIIRS NPP VIIRS LEO 2012-2014 20 [50,52]
NASA-OBPG SeaStar SeaWiFS LEO 1997-2010 204 (<10, [27-66])
NASA/USGS Landsat-8 OLI LEO 2013-2014 3 [-7]
NOAA-STAR NPP VIIRS LEO 2011-2014 19 [-52,-50]
NOAA GOES-10 IMAGER GEO 1998-2006 33 [-66, 81]
NOAA GOES-11 IMAGER GEO 2006-2007 10 [-62, 57]
NOAA GOES-12 IMAGER GEO 2003-2010 49 [-83, 66]
NOAA GOES-15 IMAGER GEO 2012-2013 28 [-52, 69]
VITO Proba-V VGT-P LEO 2013-2014 25 [-7]
KMA COMS MI GEO 2010-2014 60
AIST Terra ASTER LEO 1999-2014 1 -27.7
ISRO OceanSat2 OCM-2 LEO 2009-2014 2

The NASA Prediction Of Worldwide Energy Resources (POWER) Project improves the accessibility and usage NASA Earth Observations (EO) supporting community research in three focus areas: 1) renewable energy development, 2) building energy efficiency, and 3) agroclimatology applications. The latest POWER version enhances its distribution systems to provide the latest NASA EO source data, be more resilient, support users more effectively, and provide data more efficiently. The update will include hourly-based source Analysis Ready Data (ARD), in addition to enhanced daily, monthly, annual, and climatology ARD. The daily time-series now spans 40 years for meteorology available from 1981 and solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning 20 years from 2001.

The newly available hourly data will provide users the ARD needed to model the energy performance of building systems, providing information directly amenable to decision support tools introducing the industry standard EPW (EnergyPlus Weather file). One of POWER’s partners, Natural Resource Canada’s RETScreen™, will be simultaneously releasing a new version of its software, which will have integrated POWER hourly and daily ARD products. For our agroclimatology users, the ICASA (International Consortium for Agricultural Systems Applications standards) format for the crop modelers has been modernized.

POWER is releasing new user-defined analytic capabilities, including custom climatologies and climatological-based reports for parameter anomalies, ASHRAE® compatible climate design condition statistics, and building climate zones. The ARD and climate analytics will be readily accessible through POWER's integrated services suite, including the Data Access Viewer (DAV). The DAV has been improved to incorporate updated parameter groupings, new analytical capabilities, and the new data formats. Updated methodology documentation and usage tutorials, as well as application developer specific pages, allow users to access to POWER Data efficiently.

+Visit the POWER Program Site to Learn More.