A quantitative analysis of KALPANA-1 derived water vapor winds and its impact on NWP model

Mitra, Ashim K.; Kundu, Prabir Kumar; Giri, R. K.

doi:10.1007/s00703-012-0233-5

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…Wind field is an important physical quantity that characterizes the atmospheric state [1]. Current wind data can be widely obtained by ground-based detection [2] and indirect space-borne sensors [3]. However, these wind measurement methods are limited in both height coverage and temporal or spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Infrared Spectral Radiance of O2 1.27 μm Band Based on Space-Based Limb Detection

Bai,

et al. 2023

Remote Sensing

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The infrared spectral radiance of O2 is of great significance for space-based infrared detection. In this work, based on the demand for near-infrared spectral radiance of O2 limb detection, a method of spectral radiance calculation coupled with an atmospheric remote sensing model of limb detection is proposed. According to the selection criteria of fine spectral lines, the most suitable spectral lines of the O2 1.27 μm band for detection are given. Specifically, the limb infrared radiances of the O2 1.27 μm band were simulated by using the spectral line data from the spectral database, and the effects of molecular self-absorption were also considered. Furthermore, the infrared spectral radiance distribution of the O2 1.27 μm band was simulated under the influence of altitude, and finally, the detectability of the 1.27 μm band of O2 molecules was analyzed using the criteria of spectral line selection, radiance intensity, spectral separation range and temperature sensitivity. The calculation results show that the spectral radiance of the 1.27 μm band of O2 molecules first increases and then decreases with the decrease of the limb height, and the radiance reaches the peak value in the range of 40–50 km. In terms of the selection of spectral lines, the two groups of spectral lines R7R7, R7Q8 and R11R11, R11Q12 are most suitable for the limb detection and measurement of the O2 1.27 μm band.

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Section: Introductionmentioning

confidence: 99%

Analysis of Infrared Spectral Radiance of O2 1.27 μm Band Based on Space-Based Limb Detection

Bai,

et al. 2023

Remote Sensing

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“…Compared with mass or temperature observation, measuring the global wind field is much more difficult [3]. Current wind data can be obtained widely from conventional methods: direct balloon/rocket measurements, radars, RMR lidars, and simple Doppler lidars for local measurements [4] and indirect space-borne sensors, such as wind scatterometers [5] and cloud or water vapor tracking imagers [6]. However, these wind-measuring methods are limited in both altitude coverage and temporal or spatial resolutions.…”

Section: Introductionmentioning

confidence: 99%

Influence of Scattered Sunlight for Wind Measurements with the O2(a1Δg) Dayglow

Wang

et al. 2022

Remote Sensing

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Observing the O2(a1Δg) dayglow with the limb-viewing DASH instrument enables remote sensing of neutral wind in near space. Many advantages are gained by using this new approach, but the influence factors on measurement accuracy have not been thoroughly investigated. This paper reports the quantitative evaluation of the wind error caused by scattered sunlight. The spectral concept of the O2(a1Δg) band and the measurement technique are briefly described. A comprehensive truth model simulation that is based on atmospheric limb radiance spectra and the instrument concept are used to obtain interferogram images. The algorithm, which uses these images to retrieve the interferogram containing information solely from the target altitude, is described. The self-absorption effect is taken into account in the unraveling of the line-of-sight integration. The influence of scattered sunlight on the limb-viewing weight and signal-to-noise ratio, two definitive factors for wind definitive factors, are also described. Representative wind precision profiles and their variation with surface albedo, aerosol loading, and cloud are presented. This indicates that the random error for Doppler wind is in the range of 2–3 m/s for the tangent height range from 45–80 km, and the wind precision under 45 km suffers significantly from scattered sunlight background.

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“…Analyzing the satellite data for any weather event is not so simple, since it involves various technicalities. However, the scientists are continuously trying to make use of the satellite products in weather, ocean and climate studies (e. g. Mitra et al 2013). For example, the satellite derived data sets have been used for the study of surface and upper-air characteristics (Panda and Giri 2012), near-surface wind driven features over ocean surface (Deb et al 2009), heavy rainfall events (Deb et al 2008), and also for the studies related to tropical cyclones (Panda et al 2011;Deb et al 2011;Jaishwal et al 2012Jaishwal et al , 2013.…”

Section: Introductionmentioning

confidence: 99%

A New Algorithm to Classify the Homogeneity of ERS-2 Wave Mode SAR Imagette

Song

Panda

Zhang

et al. 2013

J Indian Soc Remote Sens

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A new classification parameter is developed using 1535 ERS-2 wave mode synthetic aperture radar (SAR) test imagettes to better differentiate homogeneous and inhomogeneous imagettes. The comparison between the new parameter (Min) and the previous one (Inhomo) (Schulz-Stellenfleth and Lehner, 2004) was done under varied threshold values of Inhomo. It is concluded that the performance of 'Min' is much better than 'Inhomo' when applying to the 1535 test imagettes. Furthermore, both Min and Inhomo are applied to nearly 1 million imagettes collected for the period from 1 September 1998 to 30 November 2000. The comparisons of the global inhomogeneous distribution between 'Min' and 'Inhomo' reveal that both the areas and percentage of inhomogeneity calculated by 'Min' are larger than that calculated by 'Inhomo'. By analyzing the low wind speed distribution of HOAPS data, we found that low wind speed over the ocean is one of the key reasons for the inhomogeneity of SAR imagettes.

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A quantitative analysis of KALPANA-1 derived water vapor winds and its impact on NWP model

Cited by 5 publications

References 17 publications

Analysis of Infrared Spectral Radiance of O2 1.27 μm Band Based on Space-Based Limb Detection

Analysis of Infrared Spectral Radiance of O2 1.27 μm Band Based on Space-Based Limb Detection

Influence of Scattered Sunlight for Wind Measurements with the O2(a1Δg) Dayglow

A New Algorithm to Classify the Homogeneity of ERS-2 Wave Mode SAR Imagette

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