scholarly journals What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET

2014 ◽  
Vol 7 (3) ◽  
pp. 2491-2543 ◽  
Author(s):  
M. Wiegner ◽  
F. Madonna ◽  
I. Binietoglou ◽  
R. Forkel ◽  
J. Gasteiger ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Special Focus ◽  
Data Sets ◽  
Backscatter Coefficient ◽  
Water Vapor Absorption ◽  
International Projects ◽  
Lidar Ratio ◽  
Aerosol Remote Sensing ◽  
Real Time Information ◽  
Aerosol Backscatter

Abstract. With the establishment of ceilometer networks by national weather services a discussion commenced to which extent these simple backscatter lidars can be used for aerosol research. Though primarily designed for the detection of clouds it was shown that at least observations of the vertical structure of the boundary layer might be possible. However, an assessment of the potential of ceilometers for the quantitative retrieval of aerosol properties is still missing. In this paper we discuss different retrieval methods to derive the aerosol backscatter coefficient βp with special focus on the calibration of the ceilometers. Different options based on forward and backward integration methods are compared with respect to their accuracy and applicability. It is shown, that advanced lidar systems as being operated in the framework of EARLINET are excellent tools for the calibration, so that aerosol retrievals based on forward integration can readily be implemented. Furthermore, we discuss uncertainties introduced by incomplete overlap, the unknown lidar ratio, and water vapor absorption. The latter is relevant for the very large number of ceilometers operating in the spectral range around λ = 905 nm. Nevertheless, the retrieval of βp with an relative error in the order of 10% seems feasible, so ceilometer networks can provide useful information to fill the spatial gaps between sophisticated lidar systems. As a consequence several international projects are underway to harmonize data sets from different ceilometer and lidar networks for the sake of providing near real time information for weather prediction and air quality issues.

scholarly journals What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET

2014 ◽  
Vol 7 (7) ◽  
pp. 1979-1997 ◽  
Author(s):  
M. Wiegner ◽  
F. Madonna ◽  
I. Binietoglou ◽  
R. Forkel ◽  
J. Gasteiger ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Case Studies ◽  
Special Focus ◽  
Backscatter Coefficient ◽  
Water Vapor Absorption ◽  
Long Term Stability ◽  
Vapor Absorption ◽  
Lidar Ratio ◽  
Favorable Conditions

Abstract. With the establishment of ceilometer networks by national weather services, a discussion commenced to which extent these simple backscatter lidars can be used for aerosol research. Though primarily designed for the detection of clouds it was shown that at least observations of the vertical structure of the boundary layer might be possible. However, an assessment of the potential of ceilometers for the quantitative retrieval of aerosol properties is still missing. In this paper we discuss different retrieval methods to derive the aerosol backscatter coefficient βp, with special focus on the calibration of the ceilometers. Different options based on forward and backward integration methods are compared with respect to their accuracy and applicability. It is shown that advanced lidar systems such as those being operated in the framework of the European Aerosol Research Lidar Network (EARLINET) are excellent tools for the calibration, and thus βp retrievals based on forward integration can readily be implemented and used for real-time applications. Furthermore, we discuss uncertainties introduced by incomplete overlap, the unknown lidar ratio, and water vapor absorption. The latter is relevant for the very large number of ceilometers operating in the spectral range around λ = 905–910 nm. The accuracy of the retrieved βp mainly depends on the accuracy of the calibration and the long-term stability of the ceilometer. Under favorable conditions, a relative error of βp on the order of 10% seems feasible. In the case of water vapor absorption, corrections assuming a realistic water vapor distribution and laser spectrum are indispensable; otherwise errors on the order of 20% could occur. From case studies it is shown that ceilometers can be used for the reliable detection of elevated aerosol layers below 5 km, and can contribute to the validation of chemistry transport models, e.g., the height of the boundary layer. However, the exploitation of ceilometer measurements is still in its infancy, so more studies are urgently needed to consolidate the present state of knowledge, which is based on a limited number of case studies.

scholarly journals Capabilities of an Automatic Lidar Ceilometer to Retrieve Aerosol Characteristics within the Planetary Boundary Layer

2021 ◽  
Vol 13 (18) ◽  
pp. 3626
Author(s):  
Dingdong Li ◽  
Yonghua Wu ◽  
Barry Gross ◽  
Fred Moshary
Keyword(s):  
Boundary Layer ◽  
New York ◽  
Planetary Boundary Layer ◽  
Relative Error ◽  
Satellite Observation ◽  
Calibration Error ◽  
Backscatter Coefficient ◽  
Ratio Error ◽  
Lidar Ratio ◽  
Aerosol Backscatter

Continuous observation and quantitative retrieval of aerosol backscatter coefficients are important in the study of air quality and climate in metropolitan areas such as New York City. Ceilometers are ideal for this application, but aerosol backscatter coefficient retrievals from ceilometers are challenging and require proper calibration. In this study, we calibrate the ceilometer (Lufft CHM15k, 1064 nm) system constant with the molecular backscatter coefficient and evaluate the calibrated profiles with other independent methods, including the water-phase cloud method and comparison with the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) attenuated backscatter coefficient profile. Multiple-day calibration results show a stable system constant with a relative uncertainty of about 7%. We also evaluate the overlap correction for the CHM15k ceilometer (provided by Lufft) with a Vaisala CL-31 ceilometer, and the results show good consistency between two ceilometers’ range-corrected signal (RCS) profiles above 200 m. Next, we implement a forward iterative method to retrieve aerosol backscatter coefficients from continuous ceilometer measurements. In the retrieval, the lidar ratio is constrained by the co-located NASA AERONET radiometer aerosol optical depth (AOD) retrieval and agrees with the AERONET lidar-ratio products, derived from aerosol microphysical parameters. The aerosol backscatter coefficient retrievals are validated with co-located elastic-Raman lidar retrievals and indicate a good correlation (R2≥0.95) in the planetary boundary layer (PBL). Furthermore, a case study shows that the ceilometer retrieved aerosol extinction coefficient profiles can be used to estimate the AOD of the PBL and the aloft plumes. Finally, simulations of the uncertainty of aerosol backscatter coefficient retrieval show that a calibration error of 10% results in 10–20% of relative error in the aerosol backscatter coefficient retrievals, while relative error caused by a lidar-ratio error of 10% is less than 4% in the PBL.

Enhanced inversion accuracy of aerosol backscatter coefficient based on simple de-noising operation

2020 ◽  
Vol 257 ◽  
pp. 107358
Author(s):  
Hongzhu Ji ◽  
Yinchao Zhang ◽  
Siying Chen ◽  
He Chen ◽  
Pan Guo ◽  
...  
Keyword(s):  
Backscatter Coefficient ◽  
Aerosol Backscatter

Aerosol Backscatter Coefficient Profiles Measured at 10.6μm

1981 ◽  
Vol 20 (2) ◽  
pp. 184-194 ◽  
Author(s):  
R. L. Schwiesow ◽  
R. E. Cupp ◽  
V. E. Derr ◽  
E. W. Barrett ◽  
R. F. Pueschel ◽  
...  
Keyword(s):  
Backscatter Coefficient ◽  
Aerosol Backscatter

scholarly journals The insoluble problems of books: what does Altmetric.com have to offer?

2018 ◽  
Vol 70 (6) ◽  
pp. 691-707 ◽  
Author(s):  
Daniel Torres-Salinas ◽  
Juan Gorraiz ◽  
Nicolas Robinson-Garcia
Keyword(s):  
Special Focus ◽  
Data Sets ◽  
Content Type ◽  
Social Sciences And Humanities ◽  
Promising Tool ◽  
The Social ◽  
Google Books ◽  
Data Source ◽  
Alternative Sources ◽  
The One

Purpose The purpose of this paper is to analyze the capabilities, functionalities and appropriateness of Altmetric.com as a data source for the bibliometric analysis of books in comparison to PlumX. Design/methodology/approach The authors perform an exploratory analysis on the metrics the Altmetric Explorer for Institutions, platform offers for books. The authors use two distinct data sets of books. On the one hand, the authors analyze the Book Collection included in Altmetric.com. On the other hand, the authors use Clarivate’s Master Book List, to analyze Altmetric.com’s capabilities to download and merge data with external databases. Finally, the authors compare the findings with those obtained in a previous study performed in PlumX. Findings Altmetric.com combines and orderly tracks a set of data sources combined by DOI identifiers to retrieve metadata from books, being Google Books its main provider. It also retrieves information from commercial publishers and from some Open Access initiatives, including those led by university libraries, such as Harvard Library. We find issues with linkages between records and mentions or ISBN discrepancies. Furthermore, the authors find that automatic bots affect greatly Wikipedia mentions to books. The comparison with PlumX suggests that none of these tools provide a complete picture of the social attention generated by books and are rather complementary than comparable tools. Practical implications This study targets different audience which can benefit from the findings. First, bibliometricians and researchers who seek for alternative sources to develop bibliometric analyses of books, with a special focus on the Social Sciences and Humanities fields. Second, librarians and research managers who are the main clients to which these tools are directed. Third, Altmetric.com itself as well as other altmetric providers who might get a better understanding of the limitations users encounter and improve this promising tool. Originality/value This is the first study to analyze Altmetric.com’s functionalities and capabilities for providing metric data for books and to compare results from this platform, with those obtained via PlumX.

scholarly journals Validation of aerosol backscatter profiles from Raman lidar and ceilometer using balloon-borne measurements

2021 ◽  
Vol 21 (3) ◽  
pp. 2267-2285
Author(s):  
Simone Brunamonti ◽  
Giovanni Martucci ◽  
Gonzague Romanens ◽  
Yann Poltera ◽  
Frank G. Wienhold ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
Aerosol Size Distribution ◽  
Spatial And Temporal Variability ◽  
Raman Lidar ◽  
Backscatter Coefficient ◽  
Custom Made ◽  
Aerosol Backscatter ◽  
Good Agreement

Abstract. Remote-sensing measurements by light detection and ranging (lidar) instruments are fundamental for the monitoring of altitude-resolved aerosol optical properties. Here we validate vertical profiles of aerosol backscatter coefficient (βaer) measured by two independent lidar systems using co-located balloon-borne measurements performed by Compact Optical Backscatter Aerosol Detector (COBALD) sondes. COBALD provides high-precision in situ measurements of βaer at two wavelengths (455 and 940 nm). The two analyzed lidar systems are the research Raman Lidar for Meteorological Observations (RALMO) and the commercial CHM15K ceilometer (Lufft, Germany). We consider in total 17 RALMO and 31 CHM15K profiles, co-located with simultaneous COBALD soundings performed throughout the years 2014–2019 at the MeteoSwiss observatory of Payerne (Switzerland). The RALMO (355 nm) and CHM15K (1064 nm) measurements are converted to 455 and 940 nm, respectively, using the Ångström exponent profiles retrieved from COBALD data. To account for the different receiver field-of-view (FOV) angles between the two lidars (0.01–0.02∘) and COBALD (6∘), we derive a custom-made correction using Mie-theory scattering simulations. Our analysis shows that both lidar instruments achieve on average a good agreement with COBALD measurements in the boundary layer and free troposphere, up to 6 km altitude. For medium-high-aerosol-content measurements at altitudes below 3 km, the mean ± standard deviation difference in βaer calculated from all considered soundings is −2 % ± 37 % (−0.018 ± 0.237 Mm−1 sr−1 at 455 nm) for RALMO−COBALD and +5 % ± 43 % (+0.009 ± 0.185 Mm−1 sr−1 at 940 mm) for CHM15K−COBALD. Above 3 km altitude, absolute deviations generally decrease, while relative deviations increase due to the prevalence of air masses with low aerosol content. Uncertainties related to the FOV correction and spatial- and temporal-variability effects (associated with the balloon's drift with altitude and different integration times) contribute to the large standard deviations observed at low altitudes. The lack of information on the aerosol size distribution and the high atmospheric variability prevent an accurate quantification of these effects. Nevertheless, the excellent agreement observed in individual profiles, including fine and complex structures in the βaer vertical distribution, shows that under optimal conditions, the discrepancies with the in situ measurements are typically comparable to the estimated statistical uncertainties in the remote-sensing measurements. Therefore, we conclude that βaer profiles measured by the RALMO and CHM15K lidar systems are in good agreement with in situ measurements by COBALD sondes up to 6 km altitude.

Introduction

2006 ◽  
Author(s):  
Huug van den Dool
Keyword(s):  
Physical System ◽  
Weather Prediction ◽  
Climate Prediction ◽  
Lead Times ◽  
Prediction Methods ◽  
Data Sets ◽  
Short Term ◽  
Global Data Sets ◽  
Geophysical System

This is first and foremost a book about short-term climate prediction. The predictions we have in mind are for weather/climate elements, mainly temperature (T) and precipitation (P), at lead times longer than two weeks, beyond the realm of detailed Numerical Weather Prediction (NWP), i.e. predictions for the next month and the next seasons out to at most a few years. call this short-term climate so as to distinguish it from long-term climate change which is not the main subject of this book. A few decades ago “short-term climate prediction” was known as “longrange weather prediction”. In order to understand short-term climate predictions, their skill and what they reveal about the atmosphere, ocean and land, several chapters are devoted to constructing prediction methods. The approach taken is mainly empirical, which means literally that it is based in experience. We will use global data sets to represent the climate and weather humanity experienced (and measured!) in the past several decades. The idea is to use these existing data sets in order to construct prediction methods. In doing so we want to acknowledge that every measurement (with error bars) is a monument about the workings of Nature. We thought about using the word “statistical” instead of “empirical” in the title of the book. These two notions overlap, obviously, but we prefer the word “empirical” because we are driven more by intuition than by a desire to apply existing or developing new statistical theory. While constructing prediction methods we want to discover to the greatest extent possible how the physical system works from observations. While not mentioned in the title, diagnostics of the physical system will thus be an important part of the book as well. We use a variety of classical tools to diagnose the geophysical system. Some of these tools have been developed further and/or old tools are applied in novel ways. We do not intend to cover all diagnostics methods, only those that relate closely to prediction. There will be an emphasis on methods used in operational prediction. It is quite difficult to gain a comprehensive idea from existing literature about methods used in operational short-term climate prediction.

scholarly journals Retrieval of atmospheric backscatter and extinction profiles with the aladin airborne demonstrator (A2D)

2018 ◽  
Vol 176 ◽  
pp. 02021 ◽  
Author(s):  
Alexander Geiss ◽  
Uwe Marksteiner ◽  
Oliver Lux ◽  
Christian Lemmerz ◽  
Oliver Reitebuch ◽  
...  
Keyword(s):  
Direct Detection ◽  
European Space Agency ◽  
Backscatter Coefficient ◽  
Detection Scheme ◽  
Space Agency ◽  
Fabry Perot ◽  
Lidar Ratio ◽  
Wind Lidar ◽  
Wind Retrievals ◽  
Atmospheric Backscatter

By the end of 2017, the European Space Agency (ESA) will launch the Atmospheric laser Doppler instrument (ALADIN), a direct detection Doppler wind lidar operating at 355 nm. An important tool for the validation and optimization of ALADIN’s hardware and data processors for wind retrievals with real atmospheric signals is the ALADIN airborne demonstrator A2D. In order to be able to validate and test aerosol retrieval algorithms from ALADIN, an algorithm for the retrieval of atmospheric backscatter and extinction profiles from A2D is necessary. The A2D is utilizing a direct detection scheme by using a dual Fabry-Pérot interferometer to measure molecular Rayleigh signals and a Fizeau interferometer to measure aerosol Mie returns. Signals are captured by accumulation charge coupled devices (ACCD). These specifications make different steps in the signal preprocessing necessary. In this paper, the required steps to retrieve aerosol optical products, i. e. particle backscatter coefficient βp, particle extinction coefficient αp and lidar ratio Sp from A2D raw signals are described.

scholarly journals ℓp-ICP Coastline Inflection Method for Geolocation Error Estimation in FY-3 MWRI Data

2019 ◽  
Vol 11 (16) ◽  
pp. 1886 ◽  
Author(s):  
Xinghui Zhao ◽  
Na Chen ◽  
Weifu Li ◽  
Shen ◽  
Peng
Keyword(s):  
Traditional Method ◽  
Weather Prediction ◽  
Real Data ◽  
Step Function ◽  
Data Sets ◽  
Sparse Regularization ◽  
The Real ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Geolocation Accuracy

Known as input in the Numerical Weather Prediction (NWP) models, Microwave Radiation Imager (MWRI) data have been widely distributed to the user community. With the development of remote sensing technology, improving the geolocation accuracy of MWRI data are required and the first step is to estimate the geolocation error accurately. However, the traditional method, such as the coastline inflection method (CIM), usually has the disadvantages of low accuracy and poor anti-noise ability. To overcome these limitations, this paper proposes a novel ℓ p iterative closest point coastline inflection method ( ℓ p -ICP CIM). It assumes that the field of views (FOVs) across the coastline can degenerate into a step function and employs an ℓ p ( 0 ≤ p < 1 ) sparse regularization optimization model to solve the coastline point. After estimating the coastline points, the ICP algorithm is employed to estimate the corresponding relationship between the estimated coastline points and the real coastline. Finally, the geolocation error can be defined as the distance between the estimated coastline point and the corresponding point on the true coastline. Experimental results on simulated and real data sets show the effectiveness of our method over CIM. The accuracy of the geolocation error estimated by ℓ p -ICP CIM is up to 0 . 1 pixel, in more than 90 % of cases. We also show that the distribution of brightness temperature near the coastline is more consistent with the real coastline and the average geolocation error is reduced by 63 % after geolocation error correction.

Sign in / Sign up

Export Citation Format

Share Document