Estimation of planetary boundary layer height using Suomi NPP-CrIS soundings

Prijith, S. S.; Rao, Preeti; Sujatha, P.; Dadhwal, V. K.

doi:10.1080/2150704x.2016.1171921

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…However, remote sensing methods provide measurements over a particular location. Remote sensing measurements provide indirect measurements of ABL thickness from different platforms such as satellite [4]- [6], airborne [7] and ground based instruments [8], [9]. Ground based LIDARs provide high resolution measurements of ABL thickness or height and have been compared with other operational methods [10].…”

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confidence: 99%

Signal processing algorithm for autodetection of atmospheric boundary layer (ABL) height from lidar signals

Pradeep¹,

Kumar²,

Venkateswarlu³

2017

IJET

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Abstract-The atmospheric boundary layer (ABL), the lowest layer of the atmosphere, is a highly dynamic layer that is influenced byseveral parameters such as surface heating, turbulence, moisture transport etc.,. The detection of the height of ABL plays a crucial role in aviation, pollution monitoring,meteorology and agriculture sectors. At present, several methods are available to identify the height of the boundary layer (BL), however with coarse temporal and spatial resolutions. LIDAR offers high resolution measurements oncontinuous basis. LIDAR is one of the active remote sensors of atmosphere works on the principle of radar but employs laser with fine pulse widths. LIDAR technique has been employed to study the altitude profiles of aerosols, clouds, winds,temperature and humidity layers in the atmosphere. In this paper, we show a signal processing methodology to derive the ABL height from LIDAR signals. The signal processing methodology uses different analytical techniques such as Gradient, IPM, LGM, Variance and Wavelet as its modules to derive the height of ABL on an automatic basis. The automatic detection of ABL height from LIDAR signals employs an algorithm that employs a correlation process that works on inter-comparison results between different analytical methods. All these processes undergo in a systematic manner to present the ABL height detection automatically over a period of time frame set. The minimum time period required for detection of ABL height on automatic basis needs half-hour time period. In this presentation, we show the results of LIDAR measurements corresponds to convective period and present the detection of ABL height using the above signal processing algorithm.Keywords-Atmosphere, ABL, Remote sensing, aerosols, LIDAR I. INTRODUCTION ABL is a thin dusty layer that exists near the earth's surface. This layer contains a large part of particulate matter (PM) and other pollutants. Everyday several tons of PM is injected into the ABL by natural and manmade sources exist on the Earth's surface. Differential heating of landmasses generates winds in this layer. Winds play a key role in the transport and mixing of PM. The vertical column of PMchanges during the ABL evaluation. The ABL thickness varies with time and location on land surfaces. The thickness of ABL depends on the solar energy reaching the earth's surface. Land areas associated with strong convection and large winds mark deep ABL [1]. Shallow ABL exists over low temperate zones. This dusty layer acts as a dynamical fluid and the top portion of the layer undergo severe fluctuations during convective periods. Determination of ABL thickness during convective periods is difficult. In-situ and remote sensing methods are available to estimate ABL thickness. The atmospheric parameter, ABL thickness, is required for agriculture, meteorology, and aviation sectors. Radiosondes connected to Hydrogen filled balloons provide the in-situ or direct measurements of ABL thickness [2], [3].These units equipped with sensors for measurement of pre...

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