Long-term statistics, observations in multiple climate regimes, and detailed atmospheric characterizations make the ARM Climate Research Facility a key resource for evaluating satellite retrievals.
Satellites provide global-scale observations of key atmospheric state and cloud properties that are important to the weather and climate process. Algorithms are used to convert from the radiometric quantities actually measured by the satellites to the geophysical variables of interest. While based on physical relationships between the quantities of interest, satellite algorithms must make simplifying assumptions about factors that are not measured. The long-term and detailed observations from the Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility provide a comprehensive dataset for evaluating and characterizing the uncertainty of a wide variety of these satellite algorithms.
Four recent studies use ARM’s long-term observations in different climate regimes to evaluate, characterize, and improve retrievals of key climate and weather observations from satellite data. The resulting satellite datasets are useful for a variety of weather and climate applications.
A team, led by scientists from the National Aeronautics and Space Administration’s Langley Research Center, used observations from the “MAGIC” campaign, a year-long deployment of the ARM Mobile Facility on a container ship that conducted repeated transects of the northeast Pacific Ocean from Los Angeles, California, to Honolulu, Hawaii. The scientists evaluated satellite-based retrievals of liquid water path, a fundamental quantity for understanding climate feedbacks and evaluating climate model results. The team used the detailed ARM data to characterize how several geophysical parameters (near-surface wind speed, sea surface temperature, and water vapor), precipitation, beam-filling effects, and clear-sky biases affected the satellite retrievals.
Another team, from the Air Force Institute of Technology, used ARM observations from Oklahoma and four other ARM sites to conduct a system-level analysis and identify major sources of errors in the cloud base height product from the Visible/Infrared Imager/Radiometer Suite (VIIRS) sensor. For the Air Force, cloud base height, is a critical variable for safe aircraft operations; it is also an important climate parameter for understanding cloud formation processes and radiative impacts on the surface energy balance. The study found important limitations on when the satellite cloud base height product was accurate enough to support use for aircraft operations and suggested potential improvements.
A team of European investigators used ARM observations from the ARM Mobile Facility deployment to HyytiÃ¤lÃ¤ Finland for the Biogenic Aerosols: Effects on Clouds and Climate (BAECC) to evaluate satellite retrievals of cloud top height and liquid water path at high latitudes from three different sensors. Because the satellite algorithms are based on the geometry of light scattering, scientists were concerned about potential biases in the satellite retrievals due to the larger solar zenith angles observed at high-latitude locations. The team found minimal influence of the solar zenith angles on the satellite measurements, but they did detect a bias in liquid water path from one of the satellite sensors, which they attribute to a known drift in the reflectance bands of that instrument.
A final team, led by scientists from Dalhousie University, used ARM microwave radiometer observations from Barrow, Alaska, to develop an improved satellite algorithm for retrieving water vapor in the polar winter atmosphere. Because the polar atmosphere is so dry, changes in humidity in this region may have a large impact on the radiative balance; at the same time, the low values mean that very accurate satellite algorithms are needed to detect changes in polar humidity. The continuous measurements, relatively low uncertainties, and availability of complementary measurements make the ARM microwave radiometer observations an ideal instrument against which to test the new satellite retrieval, which is shown to have reduced errors compared to previous algorithms.
Contacts (BER PM)
ARM Program Manager
Science Systems and Applications Inc.
NASA Langley Research Center
Kyle E. Fitch
Air Force Institute of Technology
Lund University, Sweden
Moa K. Sporre (email@example.com)
Dalhousie University, Canada
All of the cited papers used data from the ARM Climate Research Facility. Funding for the studies varied, depending on the publication.
Painemal, D., T. Greenwald, M. Cadeddu,and P. Minnis. 2016. “First Extended Validation of Satellite Microwave Liquid Water Path with Ship-Based Observations of Marine Low Clouds,” Geophysical Research Letters 43(12), 6563-70. DOI: 10.1002/2016GL069061. (Reference link)
Fitch, K. E., K. D. Hutchison, K. S. Bartlett, R. S. Wacker, and K. C. Gross. 2016. “Assessing VIIRS Cloud Base Height Products with Data Collected at the Department of Energy Atmospheric Radiation Measurement Sites,” International Journal of Remote Sensing 37(11), 2604-20. DOI: 10.1080/01431161.2016.1182665. (Reference link)
Sporre, M. K., E. J. O'Connor, N. Håkansson, A. Thoss, E. Swietlicki, and T. Petäjä. 2016. “Comparison of MODIS and VIIRS Cloud Properties with ARM Ground-Based Observations over Finland,” Atmospheric Measurement Techniques 9(7), 3193-203. DOI: 10.5194/amt-9-3193-2016. (Reference link)
Perro, C., G. Lesins, T. J. Duck, and M. Cadeddu. 2016. “A Microwave Satellite Water Vapour Column Retrieval for Polar Winter Conditions,” Atmospheric Measurement Techniques 9(5), 2241-52. DOI: 10.5194/amt-9-2241-2016. (Reference link)
SC-23.1 Climate and Environmental Sciences Division, BER
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