scholarly journals Mobile water vapor Raman lidar for heavy rain forecasting: system description and validation

2018 ◽  
Author(s):  
Tetsu Sakai ◽  
Tomohiro Nagai ◽  
Toshiharu Izumi ◽  
Satoru Yoshida ◽  
Yoshinori Shoji
Keyword(s):  
Water Vapor ◽  
Urban Areas ◽  
Lower Troposphere ◽  
Precipitable Water ◽  
Heavy Rain ◽  
Analysis Data ◽  
Local Analysis ◽  
Maximum Height ◽  
Raman Lidar ◽  
Comparison Results

Abstract. To improve the lead time and accuracy of predictions of localized heavy rainfall, which can cause extensive damage in urban areas in Japan, we developed a mobile Raman lidar (RL) system for measuring the vertical distribution of the water vapor mixing ratio (w) in the lower troposphere. The RL was installed in a small trailer for easy deployment to the upwind side of potential rainfall areas to monitor the inflow of moist air before rainfall events. We describe the lidar system and present validation results obtained by comparing the RL-measured data with collocated radiosonde, Global Navigation Satellite System (GNSS), and high-resolution objective analysis data. The comparison results showed that RL-derived w agreed within 10 % with values obtained by radiosonde at altitude ranges between 0.14 and 1.5 km in the daytime and between 0.14 and 5–6 km at night in the absence of low clouds; the vertical resolution of the RL measurements was 75–150 m, their temporal resolution was less than 20 min, and the measurement uncertainty was less than 30 %. RL-derived precipitable water vapor values were similar to or slightly lower than those obtained by GNSS at night, when the maximum height of RL measurements exceeded 5 km. The RL-derived w values were at most 1 g/kg (25 %) larger than local analysis data. Four months of continuous operation of the RL system demonstrated its utility for monitoring water vapor distributions for heavy rain forecasting.

scholarly journals Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis

2019 ◽  
Vol 12 (1) ◽  
pp. 313-326 ◽  
Author(s):  
Tetsu Sakai ◽  
Tomohiro Nagai ◽  
Toshiharu Izumi ◽  
Satoru Yoshida ◽  
Yoshinori Shoji
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Lower Troposphere ◽  
Measurement Instrument ◽  
Analysis Data ◽  
Objective Analysis ◽  
Local Analysis ◽  
Maximum Height ◽  
Raman Lidar ◽  
Comparison Results

Abstract. We developed an automated compact mobile Raman lidar (MRL) system for measuring the vertical distribution of the water vapor mixing ratio (w) in the lower troposphere, which has an affordable cost and is easy to operate. The MRL was installed in a small trailer for easy deployment and can start measurement in a few hours, and it is capable of unattended operation for several months. We describe the MRL system and present validation results obtained by comparing the MRL-measured data with collocated radiosonde, Global Navigation Satellite System (GNSS), and high-resolution objective analysis data. The comparison results showed that MRL-derived w agreed within 10 % (root-mean-square difference of 1.05 g kg−1) with values obtained by radiosonde at altitude ranges between 0.14 and 1.5 km in the daytime and between 0.14 and 5–6 km at night in the absence of low clouds; the vertical resolution of the MRL measurements was 75–150 m, their temporal resolution was less than 20 min, and the measurement uncertainty was less than 30 %. MRL-derived precipitable water vapor values were similar to or slightly lower than those obtained by GNSS at night, when the maximum height of MRL measurements exceeded 5 km. The MRL-derived w values were at most 1 g kg−1 (25 %) larger than local analysis data. A total of 4 months of continuous operation of the MRL system demonstrated its utility for monitoring water vapor distributions in the lower troposphere.

Topographic amplification of crustal subsidence by the rainwater load of the 2018 heavy rain in SW Japan

2021 ◽  
Author(s):  
Syachrul Arief
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Heavy Rain ◽  
Satellite System ◽  
Rain Gauge ◽  
Precipitable Water Vapor ◽  
Surface Load ◽  
Rain Area ◽  
Movement Data ◽  
Sw Japan

<p>The huge amount of water vapor in the atmosphere caused disastrous heavy rain and floods in early July 2018 in SW Japan. Here I present a comprehensive space geodetic study of water brought by this heavy rain done by using a dense network of Global Navigation Satellite System (GNSS) receivers. </p><p>First, I reconstruct sea level precipitable water vapor above land region on the heavy rain. The total amount of water vapor derived by spatially integrating precipitable water vapor on land was ~25.8 Gt, which corresponds to the bucket size to carry water from ocean to land. I then compiled the precipitation measured with a rain radar network. The data showed the total precipitation by this heavy rain as ~22.11 Gt.</p><p>Next, I studied the crustal subsidence caused by the rainwater as the surface load. The GNSS stations located under the heavy rain area temporarily subsided 1-2 centimeters and the subsidence mostly recovered in a day. Using such vertical crustal movement data, I estimated the distribution of surface water in SW Japan. </p><p>The total amount of the estimated water load on 6 July 2018 was ~68.2 Gt, which significantly exceeds the cumulative on-land rainfalls of the heavy rain day from radar rain gauge analyzed precipitation data. I consider that such an amplification of subsidence originates from the selective deployment of GNSS stations in the concave places, e.g. along valleys and within basins, in the mountainous Japanese Islands.</p>

scholarly journals Study and mitigation of calibration factor instabilities in a water vapor Raman lidar

2017 ◽  
Vol 10 (7) ◽  
pp. 2745-2758 ◽  
Author(s):  
Leslie David ◽  
Olivier Bock ◽  
Christian Thom ◽  
Pierre Bosser ◽  
Jacques Pelon
Keyword(s):  
Water Vapor ◽  
Lower Troposphere ◽  
Satellite System ◽  
Calibration Factor ◽  
Raman Lidar ◽  
Lidar System ◽  
Short Term ◽  
Term Stability ◽  
Water Vapor Mixing Ratio

Abstract. We have investigated calibration variations in the Rameau water vapor Raman lidar. This lidar system was developed by the Institut National de l'Information Géographique et Forestière (IGN) together with the Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS). It aims at calibrating Global Navigation Satellite System (GNSS) measurements for tropospheric wet delays and sounding the water vapor variability in the lower troposphere. The Rameau system demonstrated good capacity in retrieving water vapor mixing ratio (WVMR) profiles accurately in several campaigns. However, systematic short-term and long-term variations in the lidar calibration factor pointed to persistent instabilities. A careful testing of each subsystem independently revealed that these instabilities are mainly induced by mode fluctuations in the optic fiber used to couple the telescope to the detection subsystem and by the spatial nonuniformity of the photomultiplier photocathodes. Laboratory tests that replicate and quantify these instability sources are presented. A redesign of the detection subsystem is presented, which, combined with careful alignment procedures, is shown to significantly reduce the instabilities. Outdoor measurements were performed over a period of 5 months to check the stability of the modified lidar system. The calibration changes in the detection subsystem were monitored with lidar profile measurements using a common nitrogen filter in both Raman channels. A short-term stability of 2–3 % and a long-term drift of 2–3 % per month are demonstrated. Compared to the earlier Development of Methodologies for Water Vapour Measurement (DEMEVAP) campaign, this is a 3-fold improvement in the long-term stability of the detection subsystem. The overall water vapor calibration factors were determined and monitored with capacitive humidity sensor measurements and with GPS zenith wet delay (ZWD) data. The changes in the water vapor calibration factors are shown to be fairly consistent with the changes in the nitrogen calibration factors. The nitrogen calibration results can be used to correct the overall calibration factors without the need for additional water vapor measurements to within 1 % per month.

scholarly journals Ground-based water vapor raman lidar measurements up to the upper troposphere and lower stratosphere for long-term monitoring

2012 ◽  
Vol 5 (1) ◽  
pp. 17-36 ◽  
Author(s):  
T. Leblanc ◽  
I. S. McDermid ◽  
T. D. Walsh
Keyword(s):  
Water Vapor ◽  
Lower Stratosphere ◽  
Lower Troposphere ◽  
Atmospheric Composition ◽  
Raman Lidar ◽  
Upper Troposphere ◽  
Lidar Measurements ◽  
Development Data ◽  
Instrumental Development

Abstract. Recognizing the importance of water vapor in the upper troposphere and lower stratosphere (UTLS) and the scarcity of high-quality, long-term measurements, JPL began the development of a powerful Raman lidar in 2005 to try to meet these needs. This development was endorsed by the Network for the Detection of Atmospheric Composition Change (NDACC) and the validation program for the EOS-Aura satellite. In this paper we review the stages in the instrumental development, data acquisition and analysis, profile retrieval and calibration procedures of the lidar, as well as selected results from three validation campaigns: MOHAVE (Measurements of Humidity in the Atmosphere and Validation Experiments), MOHAVE-II, and MOHAVE 2009. In particular, one critical result from this latest campaign is the very good agreement (well below the reported uncertainties) observed between the lidar and the Cryogenic Frost-Point Hygrometer in the entire lidar range 3–20 km, with a mean bias not exceeding 2% (lidar dry) in the lower troposphere, and 3% (lidar moist) in the UTLS. Ultimately the lidar has demonstrated capability to measure water vapor profiles from ∼1 km above the ground to the lower stratosphere with a precision of 10% or better near 13 km and below, and an estimated accuracy of 5%. Since 2005, nearly 1000 profiles have been routinely measured, and since 2009, the profiles have typically reached 14 km for one-hour integration times and 1.5 km vertical resolution, and can reach 21 km for 6-h integration times using degraded vertical resolutions. These performance figures show that, with our present target of routinely running our lidar two hours per night, 4 nights per week, we can achieve measurements with a precision in the UTLS equivalent to that achieved if launching one CFH per month.

scholarly journals Validation of INSAT-3D sounder data with in-situ measurements and other similar satellite observations over Indian region

2016 ◽  
Author(s):  
M. Venkat Ratnam ◽  
A. Hemanth Kumar ◽  
A. Jayaraman
Keyword(s):  
Water Vapor ◽  
Lower Troposphere ◽  
India Meteorological Department ◽  
Analysis Data ◽  
Infrared Region ◽  
In Situ Measurements ◽  
Indian Region ◽  
Positive Bias ◽  
3D Data

Abstract. To date, several satellites measurements are available which can provide profiles of temperature and water vapor with reasonable accuracies. However, temporal resolution remained poor, particularly over topics, as most of them are polar orbiting. At this juncture, launch of INSAT-3D (Indian National Satellite) by the Indian Space Research Organization (ISRO) on 26 July 2013 carrying multi-spectral imager covering visible to long wave infrared region made it possible to obtain profiles of temperature and water vapor over Indian region with higher temporal and vertical resolutions and altitude coverage besides the other parameters. The initial validation of INSAT-3D data is made with the high temporal (3 h) resolution radiosonde observations launched over Gadanki (13.5° N, 79.2° E) during a special campaign and routine evening soundings obtained at 12 UTC. We also compared INSAT-3D data with the radiosonde observations obtained from 34 India Meteorological Department stations. Comparisons were also made over Indian region with data from other satellites like AIRS, MLS and SAPHIR and ERA-Interim and NCEP re-analysis datasets. INSAT-3D is able to show a better coverage over Indian region with high spatial and temporal resolutions as expected. Good correlation in temperature between INSAT-3D and in-situ measurements is noticed except in the upper troposphere and lower stratospheric region (positive bias of 2–3 K). There exists mean dry bias of 10–25 % in relative humidity. Similar biases are also noticed when compared to other satellites and re-analysis data sets. INSAT-3D shows large positive bias in temperature above 25° N in the lower troposphere. Thus, caution is advised in using this data at those places for tropospheric studies. Finally it is concluded that temperature data from INSAT-3D is of high quality that can be directly assimilated for better forecast over Indian region.

scholarly journals Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data

2018 ◽  
Vol 11 (5) ◽  
pp. 2735-2748 ◽  
Author(s):  
Guangyao Dai ◽  
Dietrich Althausen ◽  
Julian Hofer ◽  
Ronny Engelmann ◽  
Patric Seifert ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
The Sun ◽  
Mixing Ratio ◽  
Raman Lidar ◽  
Pressure Profiles ◽  
Sun Photometer ◽  
Water Vapor Mixing Ratio ◽  
Lidar Observations

Abstract. We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.

scholarly journals Retrievals of precipitable water vapor using star photometry: Assessment with Raman lidar and link to sun photometry

2012 ◽  
Vol 117 (D5) ◽  
pp. n/a-n/a ◽  
Author(s):  
D. Pérez-Ramírez ◽  
F. Navas-Guzmán ◽  
H. Lyamani ◽  
J. Fernández-Gálvez ◽  
F. J. Olmo ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Raman Lidar
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