Comparing Pulsed Doppler LIDAR with SODAR and Direct Measurements for Wind Assessment
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Variable Renewable Energy Forecasting System Design and Implementation Plan
VARIABLE RENEWABLE ENERGY FORECASTING SYSTEM DESIGN AND IMPLEMENTATION PLAN USAID ENERGY PROGRAM 4 February 2019 This publication was produced for review by the United States Agency for International Development. It was prepared by Deloitte Consulting LLP. The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government. VARIABLE RENEWABLE ENERGY FORECASTING SYSTEM DESIGN AND IMPLEMENTATION PLAN USAID ENERGY PROGRAM CONTRACT NUMBER: AID-OAA-I-13-00018 DELOITTE CONSULTING LLP USAID | GEORGIA USAID CONTRACTING OFFICER’S REPRESENTATIVE: NICHOLAS OKRESHIDZE AUTHOR(S): DAVIT MUJIRISHVILI LANGUAGE: ENGLISH 4 FEBRUARY 2019 DISCLAIMER: This publication was produced for review by the United States Agency for International Development. It was prepared by Deloitte Consulting LLP. The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government. USAID ENERGY PROGRAM VARIABLE RENEWABLE ENERGY FORECASTING SYSTEM DESIGN AND IMPLEMENTATION PLAN i DATA Reviewed by: Valeriy Vlatchkov, Daniel Potash, Ivane Pirveli, Eka Nadareishvili Practice Area: Variable Renewable Energy Forecasting Key Words: Variable Renewable Energy; Forecasting, Procurement of Forecasting Services, Forecasting System Conceptual Design, Implementation Plan USAID ENERGY PROGRAM VARIABLE RENEWABLE ENERGY FORECASTING SYSTEM DESIGN AND IMPLEMENTATION PLAN ii ACRONYMS -
Toward Non-Invasive Measurement of Atmospheric Temperature Using Vibro-Rotational Raman Spectra of Diatomic Gases
remote sensing Article Toward Non-Invasive Measurement of Atmospheric Temperature Using Vibro-Rotational Raman Spectra of Diatomic Gases Tyler Capek 1,*,† , Jacek Borysow 1,† , Claudio Mazzoleni 1,† and Massimo Moraldi 2,† 1 Department of Physics, Michigan Technological University, Houghton, MI 49931, USA; [email protected] (J.B.); [email protected] (C.M.) 2 Dipartimento di Fisica e Astronomia, Universita’ degli Studi di Firenze, via Sansone 1, I-50019 Sesto Fiorentino, Italy; massimo.moraldi@fi.infn.it * Correspondence: [email protected] † These authors contributed equally to this work. Received: 8 October 2020; Accepted: 15 December 2020; Published: 17 December 2020 Abstract: We demonstrate precise determination of atmospheric temperature using vibro-rotational Raman (VRR) spectra of molecular nitrogen and oxygen in the range of 292–293 K. We used a continuous wave fiber laser operating at 10 W near 532 nm as an excitation source in conjunction with a multi-pass cell. First, we show that the approximation that nitrogen and oxygen molecules behave like rigid rotors leads to erroneous derivations of temperature values from VRR spectra. Then, we account for molecular non-rigidity and compare four different methods for the determination of air temperature. Each method requires no temperature calibration. The first method involves fitting the intensity of individual lines within the same branch to their respective transition energies. We also infer temperature by taking ratios of two isolated VRR lines; first from two lines of the same branch, and then one line from the S-branch and one from the O-branch. Finally, we take ratios of groups of lines. -
CHAPTER CONTENTS Page CHAPTER 5
CHAPTER CONTENTS Page CHAPTER 5. SPECIAL PROFILING TECHNIQUES FOR THE BOUNDARY LAYER AND THE TROPOSPHERE .............................................................. 640 5.1 General ................................................................... 640 5.2 Surface-based remote-sensing techniques ..................................... 640 5.2.1 Acoustic sounders (sodars) ........................................... 640 5.2.2 Wind profiler radars ................................................. 641 5.2.3 Radio acoustic sounding systems ...................................... 643 5.2.4 Microwave radiometers .............................................. 644 5.2.5 Laser radars (lidars) .................................................. 645 5.2.6 Global Navigation Satellite System ..................................... 646 5.2.6.1 Description of the Global Navigation Satellite System ............. 647 5.2.6.2 Tropospheric Global Navigation Satellite System signal ........... 648 5.2.6.3 Integrated water vapour. 648 5.2.6.4 Measurement uncertainties. 649 5.3 In situ measurements ....................................................... 649 5.3.1 Balloon tracking ..................................................... 649 5.3.2 Boundary layer radiosondes .......................................... 649 5.3.3 Instrumented towers and masts ....................................... 650 5.3.4 Instrumented tethered balloons ....................................... 651 ANNEX. GROUND-BASED REMOTE-SENSING OF WIND BY HETERODYNE PULSED DOPPLER LIDAR ................................................................ -
Fraunhofer Lidar Prototype in the Green Spectral Region for Atmospheric Boundary Layer Observations
Remote Sens. 2013, 5, 6079-6095; doi:10.3390/rs5116079 OPEN ACCESS Remote Sensing ISSN 2072-4292 www.mdpi.com/journal/remotesensing Article Fraunhofer Lidar Prototype in the Green Spectral Region for Atmospheric Boundary Layer Observations Songhua Wu *, Xiaoquan Song and Bingyi Liu Ocean Remote Sensing Institute, Ocean University of China, 238 Songling Road, Qingdao 266100, China; E-Mails: [email protected] (X.S.); [email protected] (B.L.) * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +86-532-6678-2573. Received: 8 October 2013; in revised form: 27 October 2013 / Accepted: 13 November 2013 / Published: 18 November 2013 Abstract: A lidar detects atmospheric parameters by transmitting laser pulse to the atmosphere and receiving the backscattering signals from molecules and aerosol particles. Because of the small backscattering cross section, a lidar usually uses the high sensitive photomultiplier and avalanche photodiode as detector and uses photon counting technology for collection of weak backscatter signals. Photon Counting enables the capturing of extremely weak lidar return from long distance, throughout dark background, by a long time accumulation. Because of the strong solar background, the signal-to-noise ratio of lidar during daytime could be greatly restricted, especially for the lidar operating at visible wavelengths where solar background is prominent. Narrow band-pass filters must therefore be installed in order to isolate solar background noise at wavelengths close to that of the lidar receiving channel, whereas the background light in superposition with signal spectrum, limits an effective margin for signal-to-noise ratio (SNR) improvement. This work describes a lidar prototype operating at the Fraunhofer lines, the invisible band of solar spectrum, to achieve photon counting under intense solar background. -
Observations of Atmospheric Aerosol and Cloud Using a Polarized Micropulse Lidar in Xi’An, China
atmosphere Article Observations of Atmospheric Aerosol and Cloud Using a Polarized Micropulse Lidar in Xi’an, China Chao Chen 1,2,3,4, Xiaoquan Song 1,* , Zhangjun Wang 1,2,3,4,*, Wenyan Wang 5, Xiufen Wang 2,3,4, Quanfeng Zhuang 2,3,4, Xiaoyan Liu 1,2,3,4 , Hui Li 2,3,4, Kuntai Ma 1, Xianxin Li 2,3,4, Xin Pan 2,3,4, Feng Zhang 2,3,4, Boyang Xue 2,3,4 and Yang Yu 2,3,4 1 College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China; [email protected] (C.C.); [email protected] (X.L.); [email protected] (K.M.) 2 Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266100, China; [email protected] (X.W.); [email protected] (Q.Z.); [email protected] (H.L.); [email protected] (X.L.); [email protected] (X.P.); [email protected] (F.Z.); [email protected] (B.X.); [email protected] (Y.Y.) 3 Shandong Provincial Key Laboratory of Marine Monitoring Instrument Equipment Technology, Qingdao 266100, China 4 National Engineering and Technological Research Center of Marine Monitoring Equipment, Qingdao 266100, China 5 Xi’an Meteorological Bureau of Shanxi Province, Xi’an 710016, China; [email protected] * Correspondence: [email protected] (X.S.); [email protected] (Z.W.) Abstract: A polarized micropulse lidar (P-MPL) employing a pulsed laser at 532 nm was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy Citation: Chen, C.; Song, X.; Wang, of Sciences). -
Meteorological Monitoring Guidance for Regulatory Modeling Applications
United States Office of Air Quality EPA-454/R-99-005 Environmental Protection Planning and Standards Agency Research Triangle Park, NC 27711 February 2000 Air EPA Meteorological Monitoring Guidance for Regulatory Modeling Applications Air Q of ua ice li ff ty O Clean Air Pla s nn ard in nd g and Sta EPA-454/R-99-005 Meteorological Monitoring Guidance for Regulatory Modeling Applications U.S. ENVIRONMENTAL PROTECTION AGENCY Office of Air and Radiation Office of Air Quality Planning and Standards Research Triangle Park, NC 27711 February 2000 DISCLAIMER This report has been reviewed by the U.S. Environmental Protection Agency (EPA) and has been approved for publication as an EPA document. Any mention of trade names or commercial products does not constitute endorsement or recommendation for use. ii PREFACE This document updates the June 1987 EPA document, "On-Site Meteorological Program Guidance for Regulatory Modeling Applications", EPA-450/4-87-013. The most significant change is the replacement of Section 9 with more comprehensive guidance on remote sensing and conventional radiosonde technologies for use in upper-air meteorological monitoring; previously this section provided guidance on the use of sodar technology. The other significant change is the addition to Section 8 (Quality Assurance) of material covering data validation for upper-air meteorological measurements. These changes incorporate guidance developed during the workshop on upper-air meteorological monitoring in July 1998. Editorial changes include the deletion of the “on-site” qualifier from the title and its selective replacement in the text with “site specific”; this provides consistency with recent changes in Appendix W to 40 CFR Part 51. -
Sea Surface Wind Speed Estimation from Space-Based Lidar Measurements Y
Sea surface wind speed estimation from space-based lidar measurements Y. Hu, K. Stamnes, M. Vaughan, Jacques Pelon, C. Weimer, D. Wu, M. Cisewski, W. Sun, P. Yang, B. Lin, et al. To cite this version: Y. Hu, K. Stamnes, M. Vaughan, Jacques Pelon, C. Weimer, et al.. Sea surface wind speed estimation from space-based lidar measurements. Atmospheric Chemistry and Physics, European Geosciences Union, 2008, 8, pp.3593-3601. hal-00328304v2 HAL Id: hal-00328304 https://hal.archives-ouvertes.fr/hal-00328304v2 Submitted on 20 May 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Atmos. Chem. Phys., 8, 3593–3601, 2008 www.atmos-chem-phys.net/8/3593/2008/ Atmospheric © Author(s) 2008. This work is distributed under Chemistry the Creative Commons Attribution 3.0 License. and Physics Sea surface wind speed estimation from space-based lidar measurements Y. Hu1, K. Stamnes2, M. Vaughan1, J. Pelon3, C. Weimer4, D. Wu5, M. Cisewski1, W. Sun1, P. Yang6, B. Lin1, A. Omar1, D. Flittner1, C. Hostetler1, C. Trepte1, D. Winker1, G. Gibson1, and M. Santa-Maria1 1Climate Science Branch, NASA Langley Research Center, Hampton, VA, USA 2Dept. -
Processing Jump Point of Lidar Detection Data and Inversing the Aerosol Extinction Coefficient
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W9, 2019 ISPRS Workshop on Remote Sensing and Synergic Analysis on Atmospheric Environment (RSAE), 25–27 October 2019, Nanjing, China PROCESSING JUMP POINT OF LIDAR DETECTION DATA AND INVERSING THE AEROSOL EXTINCTION COEFFICIENT Hailun Zhang1, Hu Zhao1,﹡, Yapeng Liu2, Xingkai Wang2, Chang Shu2 1School of Electrical and Information Engineering, North MinZu University Yinchuan 750021, China - [email protected], [email protected] 2School of computer science and engineering, North MinZu University Yinchuan 750021, China - [email protected], [email protected], [email protected] Commission Ⅲ, WG Ⅲ/8 KEY WORDS:Extinction Coefficient, Jump Point, Fitting, Interpolation, Invention Method ABSTRACT: For a long time, the research of the optical properties of atmospheric aerosols has aroused a wide concern in the field of atmospheric and environmental. Many scholars commonly use the Klett method to invert the lidar return signal of Mie scattering. However, there are always some negative values in the detection data of lidar, which have no actual meaning,and which are jump points. The jump points are also called wild value points and abnormal points. The jump points are refered to the detecting points that are significantly different from the surrounding detection points, and which are not consistent with the actual situation. As a result, when the far end point is selected as the boundary value, the inversion error is too large to successfully invert the extinction coefficient profile. These negative points are jump points, which must be removed in the inversion process. In order to solve the problem, a method of processing jump points of detection data of lidar and the inversion method of aerosol extinction coefficient is proposed in this paper. -
Development of Lidar Techniques to Estimate
DEVELOPMENT OF LIDAR TECHNIQUES TO ESTIMATE ATMOSPHERIC OPTICAL PROPERTIES by Mariana Adam A dissertation submitted to the Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland October, 2005 © Mariana Adam 2005 All rights reserved DEVELOPMENT OF LIDAR TECHNIQUES TO ESTIMATE ATMOSPHERIC OPTICAL PROPERTIES by Mariana Adam ABSTRACT The modified methodologies for one-directional and multiangle measurements, which were used to invert the data of the JHU elastic lidar obtained in clear and polluted atmospheres, are presented. The vertical profiles of the backscatter lidar signals at the wavelength 1064 nm were recorded in Baltimore during PM Supersite experiment. The profiles of the aerosol extinction coefficient over a broad range of atmospheric turbidity, which includes a strong haze event which occurred due to the smoke transport from Canadian forest fires in 2002, were obtained with the near-end solution, in which the boundary condition was determined at the beginning of the complete overlap zone. This was done using an extrapolation from the ground level of the aerosol extinction coefficient, calculated with the Mie theory. For such calculations the data of the ground-based in-situ instrumentation, the nephelometer and two particle size analyzers were used. An analysis of relative errors in the retrieved extinction profiles ii due to the uncertainties in the established boundary conditions was performed using two methods to determine the ground-level extinction coefficient, which in turn, imply two methods to determine aerosol index of refraction (using the nephelometer data and chemical species measurements). The comparison of the three analytical methods used to solve lidar equation (near-end, far-end and optical-depth solutions) is presented. -
Meteorological Monitoring Plan
Meteorological Monitoring at Los Alamos LA-UR-03-8097 November 2003 Los Alamos National Laboratory is operated by the University of California for the United States Department of Energy under contract W-7405-ENG-36 Cover: (Top) Net radiation (shortwave and longwave) measurements at Technical Area (TA) 6. (Middle) Multiple measurement levels on the TA-6 tower. (Bottom) Typical tower instrumentation including a horizontal vane/propeller, a vertical propeller, and an aspirated thermometer with a solar radiation shield. An Affirmative Action/Equal Opportunity Employer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither The Regents of the University of California, the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by The Regents of the University of California, the United States Government, or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of The Regents of the University of California, the United States Government, or any agency thereof. The Los Alamos National Laboratory strongly supports academic freedom and a researcher’s right to publish; as an institution, however, the Laboratory does not endorse the viewpoint of a publication or guarantee its technical correctness. -
Sodar Observation of the ABL Structure and Waves Over the Black Sea Offshore Site
atmosphere Article Sodar Observation of the ABL Structure and Waves over the Black Sea Offshore Site Vasily Lyulyukin 1,* , Margarita Kallistratova 1 , Daria Zaitseva 1, Dmitry Kuznetsov 1, Arseniy Artamonov 1 , Irina Repina 1,2 , Igor Petenko 1,3 and Rostislav Kouznetsov 1,4 and Artem Pashkin 1,2 1 A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017 Moscow, Russia; [email protected] (M.K.); [email protected] (D.Z.); [email protected] (D.K.); [email protected] (A.A.); [email protected] (I.R.); [email protected] (I.P.); rostislav.kouznetsov@fmi.fi (R.K.); [email protected] (A.P.) 2 Research Computer Center, M.V. Lomonosov Moscow State University, 119991 Moscow, Russia 3 Institute of Atmospheric Sciences and Climate, National Research Council, 00133 Rome, Italy 4 Finnish Meteorological Institute, FI-00101 Helsinki, Finland * Correspondence: [email protected] Received: 19 October 2019; Accepted: 11 December 2019; Published: 14 December 2019 Abstract: Sodar investigations of the breeze circulation and vertical structure of the atmospheric boundary layer (ABL) were carried out in the coastal zone of the Black Sea for ten days in June 2015. The measurements were preformed at a stationary oceanographic platform located 450 m from the southern coast of the Crimean Peninsula. Complex measurements of the ABL vertical structure were performed using the three-axis Doppler minisodar Latan-3m. Auxiliary measurements were provided by a temperature profiler and two automatic weather stations. During the campaign, the weather was mostly fair with a pronounced daily cycle. Characteristic features of breeze circulation in the studied area, primarily determined by the adjacent mountains, were revealed. -
West Texas Mesonet Overview
www.mesonet.ttu.edu National Wind Institute www.depts.ttu.edu/nwi Atmospheric Science Group www.atmo.ttu.edu West Texas Mesonet – Map 111 Completed Stations – January 2018 Site Photo CROWELL 1E – Foard County Site Photo Bootleg 11WNW - Deaf Smith County Site Photo ENDEE 2SW – Quay County, New Mexico Instrumentation ❖ The following data are collected at each mesonet station every one to five minutes depending on the datalogger at each station: ❖ 10-meter wind speed and direction (average and 3-second peak wind speed) ❖ 9-meter temperature ❖ 20-ft wind speed (fire weather) and 2-meter wind speed ❖ 2-meter temperature ❖ 1.5-meter temperature and relative humidity (including dewpoint calculation) ❖ barometric pressure (using digital barometer: calculations include station pressure and altimeter) ❖ rainfall (total for the 5-minute period and an hourly summation product) ❖ 2-meter solar radiation (Kipp and Zonen SP-Lite2 and CM-3) Instrumentation ❖The following data are collected at most mesonet stations every 15 minutes: ❖Soil Temperature at 5cm (~2 inches) under sod-covered ground ❖Soil Temperature at 10cm (~4 inches) under sod-covered ground ❖Soil Temperature at 20cm (~8 inches) under sod-covered ground ❖Soil Temperature at 5cm (~2 inches) for bare ground ❖Soil Temperature at 20cm (~8 inches) for bare ground ❖Soil Moisture at 5cm (~2 inches) (all of these are sod-covered ground) ❖Soil Moisture at 20cm (~8 inches) ❖Soil Moisture at 60cm (~24 inches) ❖Soil Moisture at 75cm (~30 inches) ❖Leaf Wetness Instrumentation Fluvanna 3W WTM Station Users/Importance ❖ Users: ❖ Agriculture ❖ Schools ❖ Wind Power Industry ❖ Community Leaders ❖ National Weather Service ❖ Emergency Management ❖ NOAA Weather Radio ❖ Media Outlets ❖ General Public ❖ And Many More….