CN110031868A - A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height - Google Patents
A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height Download PDFInfo
- Publication number
- CN110031868A CN110031868A CN201910407004.4A CN201910407004A CN110031868A CN 110031868 A CN110031868 A CN 110031868A CN 201910407004 A CN201910407004 A CN 201910407004A CN 110031868 A CN110031868 A CN 110031868A
- Authority
- CN
- China
- Prior art keywords
- laser radar
- boundary layer
- noise ratio
- cloud
- height
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/95—Lidar systems specially adapted for specific applications for meteorological use
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Electromagnetism (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Optical Radar Systems And Details Thereof (AREA)
Abstract
The invention discloses a kind of methods based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height.Its basic principle are as follows: utilize a coherent wind laser radar, obtain carrier-to-noise ratio Vertical Profile;After signal normalization, wavelet covariance conversion process signal is utilized;Find out height of the corresponding height of maximum as atmospheric boundary layer top after wavelet transformation.Compared with existing algorithm, the statics atmospheric boundary layer height of high time resolution can be also obtained using only coherent wind laser radar, in conjunction with the dynamics atmospheric boundary layer height that Wind-field Retrieval obtains, facilitates climate model, Forecast Model For Weather, Air Pollution Diffusion Model precision and further increase.
Description
Technical field
The present invention relates to Atmospheric Survey fields, more particularly to one kind to be based on coherent wind laser radar carrier-to-noise ratio inverting boundary
The method of layer height.
Background technique
Recent decades, with the high speed development of social economy, air pollution is more serious.Especially with aerosol fine grained
Haze weather caused by the suspended particulate substances such as object (PM2.5) has huge threat to human health safety and environment.And
The spatial and temporal distributions of PM2.5 are then mainly influenced by atmospheric boundary layer.Atmospheric boundary layer, also referred to as planetary boundary layer are big
Gas contamination control, numerical weather forecast, city and agricultural weather, the key area in aeronautical meteorology and hydrology field.Atmosphere
Boundary Layer Height, also referred to as atmospheric boundary layer thickness are the height at the top of boundary layer, are the basic ginsengs for characterizing atmospheric boundary layer
Number, is widely used in global atmosphere climatic model and Air Pollution Diffusion Model.Thus to the anti-of atmospheric boundary layer height
It drills, to Air Quality Forecast and Air Pollution Control important role.
Within atmospheric boundary layer, atmosphere is vertically uniformly mixed due to turbulent flow.Aerosol density is thereby resulted in, greatly
Gas trace gas, humidity, the significant changes in boundary layer near top such as mild turbulent flow in position.It can be finally inversed by atmospheric boundary accordingly
Layer height.It mainly include traditionally using detection modes such as sounding balloons to the detection of atmospheric boundary layer height.But sounding balloon
It can not uninterruptedly be measured, temporal resolution is low, it is difficult to meet increasingly increased forecast precision requirement.In recent years, it is concerned with and surveys
Wind laser radar is widely used in the ground such as airport, weather station atmospheric boundary layer Wind measurement.
The present inventor has found after study: coherent wind laser radar carries out the carrier-to-noise ratio provided when Wind measurement
The distribution that (carrier to noise ratio, CNR) reflects atmospheric aerosol to a certain extent, can be used for quiet
The inverting of mechanics atmospheric boundary layer height is different from big using the dynamics of the progress such as vertical velocity variance and turbulence dissipation rate
The inverting of gas Boundary Layer Height.Tradition has variance method and threshold value using the method for coherent laser radar CNR inversion boundary layer height
Method.Variance method is to solve Boundary Layer Height, but the method temporal resolution phase according to the variation of the variance of CNR in given time window
To lower, the high time resolution of laser radar cannot be made full use of.Threshold method is the threshold determination side according to CNR Vertical Profile
Interlayer height, under different weather state, error is larger.
Summary of the invention
In consideration of it, the present invention proposes a kind of method based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height,
So that can be achieved with spy while atmospheric wind and Boundary Layer Height on the basis of a coherent wind laser radar is used only
It surveys, has potential significance for contamination modeling and Air Quality Forecast.
The purpose of the present invention is to provide a kind of sides based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height
Method, it is intended to provide the Boundary Layer Height inversion result of high time resolution when solving to only have coherent wind laser radar detection.
To achieve the above object, the invention provides the following technical scheme:
A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height, the coherent wind laser thunder
Up to including: continuous wave laser, beam splitter, acousto-optic modulator, fiber amplifier, circulator, telescope, coupler, balance detection
Device, analog acquisition card, computer;
The output end of continuous wave laser and the input terminal of beam splitter connect, the first output end and acousto-optic modulator of beam splitter
Input terminal connection, the first input end of the second output terminal of beam splitter and coupler connects, the output end of acousto-optic modulator with
The input terminal of fiber amplifier connects, and the output end of fiber amplifier and the input terminal of circulator connect, the sending and receiving end of circulator
It is connect with telescope, the output end of circulator and the second input terminal of coupler connect, and the output end and detector of coupler connect
It connects, the output end of detector is connect with analog acquisition card, and analog acquisition card is connect with computer;
The described method includes:
Step 1: coherent wind Laser Radar Observation obtains the carrier-to-noise ratio CNR profile for the vertical direction that measurement obtains;
Step 2: the CNR profile normalized of acquisition is obtained into normalized CNR profile f (z);
Step 3: wavelet covariance is carried out to the CNR profile f (z) after normalization and converts to obtain covariance function Wf(a,
b);
Step 4: covariance function W is found outfHeight corresponding to (a, b) maximum value obtains the height on atmospheric boundary layer top
Degree.
Further, in step 1, coherent wind Laser Radar Observation obtains the carrier-to-noise ratio for the vertical direction that measurement obtains
CNR profile;Include:
Coherent wind laser radar carries out vertical sounding and obtains carrier-to-noise ratio Vertical Profile or oblique incidence souding acquisition carrier-to-noise ratio
The vertical component of profile.
Further, in step 3, wavelet covariance is carried out to the CNR profile f (z) after normalization and converts to obtain covariance
Function Wf(a, b), comprising:
Covariance function is
Wavelet basis uses Haar function:
In formula, ztAnd zbThe coboundary of computer capacity and lower boundary respectively in the inverting of boundary layer, a are Haar small echo scaling
Coefficient, b are Haar function center.
Further, in step 4, covariance function W is found outfBefore height corresponding to (a, b) maximum value, further includes:
Cloud layer recognition is carried out, cloud layer signal is removed.
Further, the method for cloud layer recognition includes threshold method, the threshold method are as follows: dissipates f (z) and preset cloud layer by force
It penetrates signal threshold value to compare, if f (z) is greater than or equal to the cloud layer strong scattering signal threshold value, determines the signal for cloud layer signal.
Further, the method for cloud layer recognition includes cloud base cloud top gradient combination criterion, the cloud base cloud top gradient knot
Close criterion are as follows: the gradient for calculating f (z) judges that the space interval between the gradient positive maximum of f (z) and negative maximum is less than
Preset interval threshold then determines between the gradient positive maximum of f (z) and negative maximum for cloud layer signal.
A kind of method based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height provided by the invention has such as
It is lower the utility model has the advantages that
(1) statics atmospheric boundary layer height inverting can be carried out by coherent wind laser radar carrier-to-noise ratio being used only, and be realized
Separate unit coherent wind laser radar eliminates aerosol laser for measuring while atmospheric wind and atmospheric boundary layer height
The use of radar or ceilometer, reduces costs, operation and maintenance of being more convenient for.
(2) wavelet algorithm that the present invention uses has time-space resolution compared to traditional thresholding algorithm or variance algorithm
The features such as rate is high, and precision is high.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below Detailed description of the invention will be carried out to the present invention.
Fig. 1 is the coherent wind laser radar schematic diagram that the present invention uses.
Fig. 2 is the process of the method proposed by the present invention based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height
Figure.
Fig. 3 be atmospheric boundary layer height solving result provided in an embodiment of the present invention and its with aerosol LIDAR result
The schematic diagram compared.Corresponding data is one group of data that coherent wind laser radar and aerosol LIDAR are surveyed.
Specific embodiment
With reference to the attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete
Ground description.Obviously, described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on this
The embodiment of invention, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, belongs to protection scope of the present invention.
Embodiment
The invention discloses a kind of methods based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height.
As shown in Figure 1, the coherent wind laser radar includes: continuous wave laser 1, beam splitter 2, acousto-optic modulator 3, light
Fiber amplifier 4, circulator 5, telescope 6, coupler 7, balanced detector 8, analog acquisition card 9, computer 10;
The output end of continuous wave laser 1 is connect with the input terminal of beam splitter 2, the first output end and acousto-optic tune of beam splitter 2
The input terminal of device 3 processed connects, and the second output terminal of beam splitter 2 is connect with the first input end of coupler 7, acousto-optic modulator 3
Output end is connect with the input terminal of fiber amplifier 4, and the output end of fiber amplifier 4 is connect with the input terminal of circulator 5, annular
The sending and receiving end of device 5 is connect with telescope 6, and the output end of circulator 5 is connect with the second input terminal of coupler 7, coupler 7 it is defeated
Outlet is connect with detector 8, and the output end of detector 8 is connect with analog acquisition card 9, and analog acquisition card 9 is connect with computer 10.
Basic principle of the invention are as follows: coherent wind laser radar carrier-to-noise ratio is related to aerosol extinction, carrier-to-noise ratio profile
It can reduce suddenly near the top of boundary layer, find out the height that carrier-to-noise ratio reduces suddenly using wavelet covariance transformation, be corresponding
Boundary Layer Height.
In conjunction with Fig. 2, the present invention is based on the methods of coherent wind laser radar carrier-to-noise ratio inversion boundary layer height, comprising:
Step 1: coherent wind Laser Radar Observation obtains the carrier-to-noise ratio CNR profile for the vertical direction that measurement obtains.
Particularly, in the above method, observation includes continuous uninterrupted observation and continued observations.
Optionally, the observation time of every group of profile is determined according to user demand, 2 seconds to 1 hour.In order to meet simultaneously
High time resolution demand and the influence for removing turbulent flow and noise are excellent with minute magnitude.
Optionally, in the above-mentioned methods, the oblique observation of the elevation angle sufficiently large (being greater than 45 degree) can be carried out.It will be apart from conversion
It, can be by it according to Vertical Observation equivalent processes after height.
Step 2: the CNR profile normalized of acquisition is obtained into normalized CNR profile f (z).
Normalization refers to, to the signal in presumptive area, after subtracting minimum value, divided by new maximum value, to make letter
Number value is located at [0,1] section.
It is more concerned about the trend that boundary layer top gas sol content reduces rapidly after normalization, it in subsequent processing can be to avoid
Different aerosol environment are such as used and can remove different strong and weak letters when threshold determination because strong and weak difference is influencing caused by inversion result
Number influence.
Step 3: wavelet covariance is carried out to the CNR profile f (z) after normalization and converts to obtain covariance function Wf(a,
b);
Specifically, wherein covariance function is
Wavelet basis uses Haar function:
In formula, ztAnd zbThe coboundary of computer capacity and lower boundary respectively in the inverting of boundary layer, a are Haar small echo scaling
Coefficient, b are Haar function center.
Optionally, zoom factor a according to the geographical feature of laser radar vertical resolution and local aerosol extinction and
Seasonal characteristic determines.It is usually taken to be fixed value, as embodiment hereof takes 250 meters;Also it can be taken as following the function of height change.
Optionally, Haar wavelet basis can also be substituted with other wavelet basis, such as Mexican Hat wavelet function.Wherein,
Mexican Hat wavelet function are as follows:
Step 4: covariance function W is found outfHeight corresponding to (a, b) maximum value obtains the height on atmospheric boundary layer top
Degree.
Optionally, covariance function W is found outfBefore height corresponding to (a, b) maximum value, further includes: carry out cloud layer knowledge
Not, cloud layer signal is removed.
That is, cloud recognizer can be added in step 4 to remove cloud layer signal.
Specifically, the method for cloud layer recognition includes threshold method, the threshold method are as follows: by f (z) and preset cloud layer strong scattering
Signal threshold value compares, if f (z) is greater than or equal to the cloud layer strong scattering signal threshold value, determines the signal for cloud layer signal.
Alternatively, the method for cloud layer recognition includes cloud base cloud top gradient combination criterion, the cloud base cloud top gradient knot
Close criterion are as follows: the gradient for calculating f (z) judges that the space interval between the gradient positive maximum of f (z) and negative maximum is less than
Preset interval threshold then determines between the gradient positive maximum of f (z) and negative maximum for cloud layer signal.
Method of the invention is explained with a specific measurement data below.
S1 obtains the actual measurement carrier-to-noise ratio Vertical Profile of one group of coherent wind laser radar, the sample number as the present embodiment
According to.Aerosol LIDAR distance correction photon counting as a control group is obtained simultaneously.
S2, by corresponding Vertical Profile normalized, as shown in Fig. 3 left figure.
S3 carries out wavelet covariance variation to corresponding profile, and the present embodiment uses Haar wavelet function, such as Fig. 3 right figure institute
Show.
S4 finds the position that carrier-to-noise ratio declines rapidly by covariance result after excluding cloud noise by cloud layer recognition,
That is the corresponding height of Haar wavelet covariance maximum value, such as red and Blue circles mark height, as atmospheric boundary layer in Fig. 3
Height value.Wherein cloud layer recognition includes using threshold method, and cloud base cloud top gradient combination criterion etc. is based on cloud layer strong scattering signal
Threshold determination or acute variation (i.e. gradient is very big at cloud base, minimum at cloud top) based on cloud base cloud top scattered signal from
And determine the method for cloud layer.
Fig. 3 is to be utilized respectively coherent wind laser radar and aerosol LIDAR inverting atmospheric boundary layer height the same time
Spend schematic diagram.It can be seen that although the aerosol vertical structure details that coherent wind laser radar is shown is not so good as aerosol laser
Radar demeanour, but the atmospheric boundary layer height and aerosol LIDAR distance being finally inversed by by coherent wind laser radar carrier-to-noise ratio
The atmospheric boundary layer height numerical value that amendment photon counting is finally inversed by is suitable, has good consistency.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Within the technical scope of the present disclosure, any changes or substitutions that can be easily thought of by anyone skilled in the art,
It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claims
Subject to enclosing.
Claims (6)
1. a kind of method based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height, it is characterised in that:
The coherent wind laser radar includes: continuous wave laser (1), beam splitter (2), acousto-optic modulator (3), fiber amplifier
(4), circulator (5), telescope (6), coupler (7), balanced detector (8), analog acquisition card (9), computer (10);
The output end of continuous wave laser (1) is connect with the input terminal of beam splitter (2), the first output end and acousto-optic of beam splitter (2)
The input terminal of modulator (3) connects, and the second output terminal of beam splitter (2) is connect with the first input end of coupler (7), acousto-optic tune
The output end of device (3) processed is connect with the input terminal of fiber amplifier (4), output end and circulator (5) of fiber amplifier (4)
Input terminal connection, the sending and receiving end of circulator (5) connect with telescope, and the second of the output end of circulator (5) and coupler (7) is defeated
Enter end connection, the output end of coupler (7) is connect with detector (8), and the output end of detector (8) and analog acquisition card (9) are even
It connects, analog acquisition card (9) is connect with computer (10);
The described method includes:
Step 1: coherent wind Laser Radar Observation obtains the carrier-to-noise ratio CNR profile for the vertical direction that measurement obtains;
Step 2: the CNR profile normalized of acquisition is obtained into normalized CNR profile f (z);
Step 3: wavelet covariance is carried out to the CNR profile f (z) after normalization and converts to obtain covariance function Wf(a, b);
Step 4: covariance function W is found outfHeight corresponding to (a, b) maximum value obtains the height on atmospheric boundary layer top.
2. the method according to claim 1, wherein in step 1, coherent wind Laser Radar Observation is obtained and is surveyed
The carrier-to-noise ratio CNR profile of the vertical direction measured;Include:
Coherent wind laser radar carries out vertical sounding and obtains carrier-to-noise ratio Vertical Profile or oblique incidence souding acquisition carrier-to-noise ratio profile
Vertical component.
3. the method according to claim 1, wherein being carried out in step 3 to the CNR profile f (z) after normalization
Wavelet covariance converts to obtain covariance function Wf(a, b), comprising:
Covariance function is
Wavelet basis uses Haar function:
In formula, ztAnd zbThe coboundary of computer capacity and lower boundary respectively in the inverting of boundary layer, a are Haar small echo zoom factor,
B is Haar function center.
4. the method according to claim 1, wherein finding out covariance function W in step 4f(a, b) maximum value
Before corresponding height, further includes:
Cloud layer recognition is carried out, cloud layer signal is removed.
5. the method according to claim 1, wherein the method for cloud layer recognition includes threshold method, the threshold method
Are as follows: by f (z) compared with preset cloud layer strong scattering signal threshold value, if f (z) is greater than or equal to the cloud layer strong scattering signal threshold
Value, then determine the signal for cloud layer signal.
6. the method according to claim 1, wherein the method for cloud layer recognition includes that gradient combination in cloud base cloud top is sentenced
Determine method, the cloud base cloud top gradient combination criterion are as follows: the gradient for calculating f (z) judges the gradient positive maximum and cathode of f (z)
Space interval between big value is less than preset interval threshold, then determine be between the gradient positive maximum of f (z) and negative maximum
Cloud layer signal.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910407004.4A CN110031868A (en) | 2019-05-15 | 2019-05-15 | A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910407004.4A CN110031868A (en) | 2019-05-15 | 2019-05-15 | A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height |
Publications (1)
Publication Number | Publication Date |
---|---|
CN110031868A true CN110031868A (en) | 2019-07-19 |
Family
ID=67242341
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910407004.4A Pending CN110031868A (en) | 2019-05-15 | 2019-05-15 | A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110031868A (en) |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110687547A (en) * | 2019-09-27 | 2020-01-14 | 北京航天环境工程有限公司 | Toxic and harmful gas environment risk early warning and monitoring method based on remote sensing radar |
CN112526547A (en) * | 2020-11-18 | 2021-03-19 | 董晶晶 | Atmospheric boundary layer classification method and device based on wind lidar |
CN112698359A (en) * | 2020-12-21 | 2021-04-23 | 山东国耀量子雷达科技有限公司 | Coherent wind lidar based on quantum up-conversion principle and wind field detection method |
CN112946629A (en) * | 2021-01-29 | 2021-06-11 | 西安理工大学 | Remote sensing detection system and detection method for condensable water amount of aerial cloud system |
CN113189616A (en) * | 2021-05-10 | 2021-07-30 | 北京城市气象研究院 | Method for determining height of boundary layer of atmosphere and related equipment |
CN114296050A (en) * | 2022-03-07 | 2022-04-08 | 南京鼐云信息技术有限责任公司 | Photovoltaic power station short-term power generation power prediction method based on laser radar cloud picture detection |
CN115390093A (en) * | 2022-09-22 | 2022-11-25 | 北京环拓科技有限公司 | Method for detecting atmospheric boundary layer by using ozone radar |
CN115453574A (en) * | 2022-10-27 | 2022-12-09 | 南京信息工程大学 | Multifunctional laser radar for atmospheric multi-parameter detection |
RU2799037C1 (en) * | 2019-09-20 | 2023-07-03 | Оффис Насьональ Д'Этюд Э Де Решерш Аэроспасьяль | Lidar system for anemometric measurements |
CN116500649A (en) * | 2023-06-28 | 2023-07-28 | 中国科学技术大学 | Inversion method and device for boundary layer height |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014165266A1 (en) * | 2013-03-12 | 2014-10-09 | LogLinear Group, LLC | Single beam wind speed and direction determination |
CN107045130A (en) * | 2017-03-07 | 2017-08-15 | 北京理工大学 | A kind of Portable type full-automatic micropulse anemometry laser radar system |
CN107561555A (en) * | 2017-08-31 | 2018-01-09 | 兰州大学 | Method, apparatus, computer equipment and the storage medium of inversion boundary layer height |
CN108256546A (en) * | 2017-11-30 | 2018-07-06 | 中国人民解放军国防科技大学 | Method and system for detecting height of atmospheric boundary layer under non-precipitation condition |
-
2019
- 2019-05-15 CN CN201910407004.4A patent/CN110031868A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014165266A1 (en) * | 2013-03-12 | 2014-10-09 | LogLinear Group, LLC | Single beam wind speed and direction determination |
CN107045130A (en) * | 2017-03-07 | 2017-08-15 | 北京理工大学 | A kind of Portable type full-automatic micropulse anemometry laser radar system |
CN107561555A (en) * | 2017-08-31 | 2018-01-09 | 兰州大学 | Method, apparatus, computer equipment and the storage medium of inversion boundary layer height |
CN108256546A (en) * | 2017-11-30 | 2018-07-06 | 中国人民解放军国防科技大学 | Method and system for detecting height of atmospheric boundary layer under non-precipitation condition |
Non-Patent Citations (5)
Title |
---|
FEIYUE MAO ETC.: "Determination of the boundary layer top from lidar backscatter profiles using a Haar wavelet method over Wuhan,China", 《OPTICS & LASER TECHNOLOGY》 * |
侍茂崇 等: "《海洋调查方法》", 31 March 2018 * |
姜杰 等: "南京上空大气边界层的激光雷达观测研究", 《环境科学与技术》 * |
李红 等: "基于激光雷达资料的小波变换法反演边界层高度的方法", 《干旱气象》 * |
魏浩 等: "小波变换在风廓线雷达探测大气边界层高度中的应用研究", 《热带气象学报》 * |
Cited By (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
RU2799037C1 (en) * | 2019-09-20 | 2023-07-03 | Оффис Насьональ Д'Этюд Э Де Решерш Аэроспасьяль | Lidar system for anemometric measurements |
CN110687547A (en) * | 2019-09-27 | 2020-01-14 | 北京航天环境工程有限公司 | Toxic and harmful gas environment risk early warning and monitoring method based on remote sensing radar |
CN112526547A (en) * | 2020-11-18 | 2021-03-19 | 董晶晶 | Atmospheric boundary layer classification method and device based on wind lidar |
CN112526547B (en) * | 2020-11-18 | 2024-02-23 | 南京泰爱信科技有限公司 | Atmospheric boundary layer classification method and device based on wind-measuring laser radar |
CN112698359A (en) * | 2020-12-21 | 2021-04-23 | 山东国耀量子雷达科技有限公司 | Coherent wind lidar based on quantum up-conversion principle and wind field detection method |
CN112946629A (en) * | 2021-01-29 | 2021-06-11 | 西安理工大学 | Remote sensing detection system and detection method for condensable water amount of aerial cloud system |
CN112946629B (en) * | 2021-01-29 | 2024-05-14 | 西安理工大学 | Remote sensing detection system and detection method for air cloud system condensable water |
CN113189616B (en) * | 2021-05-10 | 2023-05-02 | 北京城市气象研究院 | Method for determining boundary layer height of atmosphere and related equipment |
CN113189616A (en) * | 2021-05-10 | 2021-07-30 | 北京城市气象研究院 | Method for determining height of boundary layer of atmosphere and related equipment |
CN114296050A (en) * | 2022-03-07 | 2022-04-08 | 南京鼐云信息技术有限责任公司 | Photovoltaic power station short-term power generation power prediction method based on laser radar cloud picture detection |
CN115390093A (en) * | 2022-09-22 | 2022-11-25 | 北京环拓科技有限公司 | Method for detecting atmospheric boundary layer by using ozone radar |
CN115453574A (en) * | 2022-10-27 | 2022-12-09 | 南京信息工程大学 | Multifunctional laser radar for atmospheric multi-parameter detection |
CN116500649A (en) * | 2023-06-28 | 2023-07-28 | 中国科学技术大学 | Inversion method and device for boundary layer height |
CN116500649B (en) * | 2023-06-28 | 2023-10-20 | 中国科学技术大学 | Inversion method and device for boundary layer height |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110031868A (en) | A method of based on coherent wind laser radar carrier-to-noise ratio inversion boundary layer height | |
Haeffelin et al. | Evaluation of mixing-height retrievals from automatic profiling lidars and ceilometers in view of future integrated networks in Europe | |
CN110058258B (en) | Atmospheric boundary layer detection method based on hybrid laser radar | |
Morille et al. | STRAT: An automated algorithm to retrieve the vertical structure of the atmosphere from single-channel lidar data | |
CN110411927B (en) | Atmospheric fine particle AOD and earth surface polarization reflectivity collaborative inversion method | |
CN108490451B (en) | Method for inverting slope visibility by utilizing atmospheric extinction coefficient | |
CN107255806B (en) | A method of fitting inverting sea level horizontal air extinction coefficient | |
Mao et al. | Determination of the boundary layer top from lidar backscatter profiles using a Haar wavelet method over Wuhan, China | |
CN107561554A (en) | Inversion method with multi-wavelength laser radar data is counted based on solar luminosity | |
CN107870336B (en) | A kind of satellite-bone laser radar penetrates bottom iteration detection method layer by layer | |
Jiang et al. | Analysis of differences between thermodynamic and material boundary layer structure: Comparison of detection by ceilometer and microwave radiometer | |
Berg et al. | Lidar-observed stress vectors and veer in the atmospheric boundary layer | |
Wang et al. | Measuring boundary-layer height under clear and cloudy conditions using three instruments | |
Zeng et al. | Statistical characteristics of raindrop size distribution during rainy seasons in Northwest China | |
Liu et al. | Graphics algorithm for deriving atmospheric boundary layer heights from CALIPSO data | |
CN106706566A (en) | Calculation method of atmosphere vertical visibility via laser radar detection | |
Kunz et al. | Lidar observations of atmospheric boundary layer structure and sea spray aerosol plumes generation and transport at Mace Head, Ireland (PARFORCE experiment) | |
Bumke et al. | Analysis of measured drop size spectra over land and sea | |
Cai et al. | Vertical distributions of aerosol and cloud microphysical properties and the aerosol impact on a continental cumulus cloud based on aircraft measurements from the loess plateau of China | |
Qi et al. | Improving WSR-88D radar QPE for orographic precipitation using profiler observations | |
Zhu et al. | Characteristics of the planetary boundary layer above Wuhan, China based on CALIPSO | |
Zinke et al. | Sea spray emissions from the Baltic Sea: comparison of aerosol eddy covariance fluxes and chamber-simulated sea spray emissions | |
Werner | Fast sector scan and pattern recognition for a cw laser Doppler anemometer | |
Wang et al. | Vertical-plane dual-Doppler radar observations of cumulus toroidal circulations | |
Carswell et al. | Lidar-derived distribution of cloud vertical location and extent |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
TA01 | Transfer of patent application right | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20210514 Address after: 250101 Room 501, building 5, 747 Shunhua Road, high tech Zone, Jinan City, Shandong Province Applicant after: Shandong Guoyao quantum Radar Technology Co.,Ltd. Address before: No.99, xiupu Road, Pudong New Area, Shanghai, 201315 Applicant before: GUOYAO QUANTUM RADAR TECHNOLOGY Co.,Ltd. |
|
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190719 |