Progress towards the assimilation of all‐sky infrared radiances: an evaluation of cloud effects

As a step toward the assimilation of cloud‐affected infrared radiances in multi‐layer cloud conditions, this study evaluates cloud effects on model first‐guess simulations (background) and observations using the Infrared Atmospheric Sounding Interferometer (IASI) radiances. It is found from an exten...

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Published inQuarterly journal of the Royal Meteorological Society Vol. 140; no. 682; pp. 1603 - 1614
Main Authors Okamoto, K., McNally, A. P., Bell, W.
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.07.2014
Wiley
Wiley Subscription Services, Inc
Subjects
all‐sky
Assimilation
cloud
Earth, ocean, space
Exact sciences and technology
External geophysics
IASI
IR radiances
Meteorology
Space remote sensing
Satellite observation
Infrared atmospheric sounding interferometer
Sky brightness
clouds
IASI
assimilation
IR radiances
cloud
Observation data
Cloudiness
all-sky
Measurement error
Data assimilation
radiance
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Summary:As a step toward the assimilation of cloud‐affected infrared radiances in multi‐layer cloud conditions, this study evaluates cloud effects on model first‐guess simulations (background) and observations using the Infrared Atmospheric Sounding Interferometer (IASI) radiances. It is found from an extensive statistical analysis that over oceans the magnitude of observation‐minus‐background departures (O–B) – even in the most cloud‐sensitive window channels – is typically less than 10 K for 85% of all‐sky IASI data. A parameter has been developed to express the magnitude of the cloud effect based upon observed and simulated cloudy radiances. It is shown that the variations in the standard deviation (SD) of O–B departures can be described (and thus predicted) by this cloud effect parameter – such that the probability density function (PDF) of O–B normalized with predicted O–B SD exhibits a near‐Gaussian form. It is argued that the predicted cloud effect can be used in an assimilation context to define cloud‐dependent quality controls and aid observation error assignment. Simple linear estimation theory is used to simulate the possible benefits of state‐dependent observation errors according to cloud effect.
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ISSN:0035-9009
1477-870X
DOI:10.1002/qj.2242