Satellite instrument calibration for measuring global climate change

Ohring, George; Wielicki, Bruce A.; Spencer, Roy W.; Emery, Bill; Datla, Raju V.

doi:10.6028/nist.ir.7047

Cited by 79 publications

(89 citation statements)

References 24 publications

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“…Only spacebased observations can deliver the necessary global coverage with sufficient quality and long time frames. Particularly over the ocean and inaccessible regions satellites are largely the only data source (Ohring et al, 2005).…”

Section: A Werkmeister Et Al: Comparing Cloud Coverage -A Case Studymentioning

confidence: 99%

Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

et al. 2015

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Abstract. In this case study we compare cloud fractional cover measured by radiometers on polar satellites (AVHRR) and on one geostationary satellite (SEVIRI) to ground-based manual (SYNOP) and automated observations by a cloud camera (Hemispherical Sky Imager, HSI). These observations took place in Hannover, Germany, and in Lauder, New Zealand, over time frames of 3 and 2 months, respectively.Daily mean comparisons between satellite derivations and the ground-based HSI found the deviation to be 6 ± 14 % for AVHRR and 8 ± 16 % for SEVIRI, which can be considered satisfactory. AVHRR's instantaneous differences are smaller (2 ± 22 %) than instantaneous SEVIRI cloud fraction estimates (8 ± 29 %) when compared to HSI due to resolution and scenery effect issues. All spaceborne observations show a very good skill in detecting completely overcast skies (cloud cover ≥ 6 oktas) with probabilities between 92 and 94 % and false alarm rates between 21 and 29 % for AVHRR and SEVIRI in Hannover, Germany. In the case of a clear sky (cloud cover lower than 3 oktas) we find good skill with detection probabilities between 72 and 76 %. We find poor skill, however, whenever broken clouds occur (probability of detection is 32 % for AVHRR and 12 % for SEVIRI in Hannover, Germany).In order to better understand these discrepancies we analyze the influence of algorithm features on the satellite-based data. We find that the differences between SEVIRI and HSI cloud fractional cover (CFC) decrease (from a bias of 8 to almost 0 %) with decreasing number of spatially averaged pixels and decreasing index which determines the cloud coverage in each "cloud-contaminated" pixel of the binary map. We conclude that window size and index need to be adjusted in order to improve instantaneous SEVIRI and AVHRR estimates. Due to its automated operation and its spatial, temporal and spectral resolution, we recommend as well that more automated ground-based instruments in the form of cloud cameras should be installed as they cover larger areas of the sky than other automated ground-based instruments. These cameras could be an essential supplement to SYNOP observation as they cover the same spectral wavelengths as the human eye.

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Section: A Werkmeister Et Al: Comparing Cloud Coverage -A Case Studymentioning

confidence: 99%

Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

et al. 2015

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“…Detailed error analyses have been published (Kursinski et al, 1997;Hajj et al, 2002;Kuo et al, 2004;Hajj et al, 2004;Steiner and Kirchengast, 2005) that analyze nearly all of the known error sources. For monitoring decadal-scale climate change, measurement bias should be less than ∼0.1 K (Ohring et al, 2005;Goody et al, 1998;Steiner et al, 2001), which motivates a reexamination of these past analyses that were focused initially on establishing precision of individual soundings at the level of ∼1 K (Kursinski et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

The impact of large scale ionospheric structure on radio occultation retrievals

Mannucci

et al. 2011

Atmos. Meas. Tech.

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Abstract.We study the impact of large-scale ionospheric structure on the accuracy of radio occultation (RO) retrievals. We use a climatological model of the ionosphere as well as an ionospheric data assimilation model to compare quiet and geomagnetically disturbed conditions. The presence of ionospheric electron density gradients during disturbed conditions increases the physical separation of the two GPS frequencies as the GPS signal traverses the ionosphere and atmosphere. We analyze this effect in detail using ray-tracing and a full geophysical retrieval system. During quiet conditions, our results are similar to previously published studies. The impact of a major ionospheric storm is analyzed using data from the 30 October 2003 "Halloween" superstorm period. At 40 km altitude, the refractivity bias under disturbed conditions is approximately three times larger than quiet time. These results suggest the need for ionospheric monitoring as part of an RO-based climate observation strategy. We find that even during quiet conditions, the magnitude of retrieval bias depends critically on assumed ionospheric electron density structure, which may explain variations in previously published bias estimates that use a variety of assumptions regarding large scale ionospheric structure. We quantify the impact of spacecraft orbit altitude on the magnitude of bending angle and retrieval error. Satellites in higher altitude orbits (700+ km) tend to have lower residual biases due to the tendency of the residual bending to cancel between the top and bottomside ionosphere. Another factor affecting accuracy is the commonly-used assumption that refractive index is unity at the receiver. We conclude with remarks on the implications of this study for long-term climate monitoring using RO.

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“…In satellite remote sensing of cloud droplet number concentration, LWP uncertainties are one of the dominant retrieval errors [Bennartz, 2007]. Not only are LWP error estimates needed for climate studies and remote sensing, but also for defining satellite instrument requirements for measuring global climate change [Ohring et al, 2005].…”

Section: Introductionmentioning

confidence: 99%

Evaluating specific error characteristics of microwave‐derived cloud liquid water products

Greenwald

L’Ecuyer

Christopher

2007

Geophysical Research Letters

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Methods are presented for assessing minimum errors and cloud inhomogeneity effects in cloud liquid water path (LWP) products derived from passive microwave satellite measurements. Using coincident visible/infrared satellite data, errors are isolated by identifying certain cloud conditions within the microwave sensor's field of view. Analysis of 3 weeks of global pixel‐level LWP data revealed that 70% of the systematic errors occurred between −0.011 and +0.025 kgm−2, with the mean random error being 0.013 kgm−2. For overcast clouds these systematic errors translate to a mean lower‐bound relative error of about +23%. A significant correlation of these products with near‐surface wind speed was also shown. The LWP products were found to depend on cloud fraction as well, suggesting the influence of beam filling errors. This approach shows promise in characterizing the minimum errors in LWP products needed for climate and remote sensing studies as well as future data assimilation applications.

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Satellite instrument calibration for measuring global climate change

Cited by 79 publications

References 24 publications

Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

The impact of large scale ionospheric structure on radio occultation retrievals

Evaluating specific error characteristics of microwave‐derived cloud liquid water products

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