scholarly journals Integrated water vapor above Ny Ålesund, Spitsbergen: a multi-sensor intercomparison

2010 ◽  
Vol 10 (3) ◽  
pp. 1215-1226 ◽  
Author(s):  
M. Pałm ◽  
C. Melsheimer ◽  
S. Noël ◽  
S. Heise ◽  
J. Notholt ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Microwave Radiometer ◽  
Radiative Properties ◽  
Radiation Budget ◽  
Major Influence ◽  
Path Delay ◽  
Zenith Path Delay ◽  
Satellite Sensors ◽  
Highly Correlated

Abstract. Water vapor is an important constituent of the atmosphere. Because of its abundance and its radiative properties it plays an important role for the radiation budget of the atmosphere and has major influence on weather and climate. In this work integrated water vapor (IWV) derived from the measurements of three satellite sensors, GOME, SCIAMACHY and AMSU-B, two ground based sensors, a Fourier-transform spectrometer (FTIR), a microwave radiometer for O3 (RAM) and IWV inferred from GPS zenith path delay (ZPD) measurements, are compared to radio-sonde measurements above Ny Ålesund, 79° N. All six remote sensors exploit different principles and work in different wavelength regions. All remote sensing instruments reproduce the sonde measurements very well and are highly correlated when compared with the radio-sonde measurements. The ground-based FTIR shows very little scatter of about 10%. The GPS performs similar to the FTIR at all times except for very low IWV, where the scatter exceeds 50% of the measured IWV. The other remote sensing instruments show scatter of about 20% (standard deviation). The ground-based RAM performs similar to the satellite instruments, despite the fact that the retrieval of IWV is just a by-product of this ozone sensor.

scholarly journals Integrated water vapor above Ny Ålesund, Spitsbergen: a multisensor intercomparison

2008 ◽  
Vol 8 (6) ◽  
pp. 21171-21199 ◽  
Author(s):  
M. Palm ◽  
C. Melsheimer ◽  
S. Noël ◽  
J. Notholt ◽  
J. Burrows ◽  
...  
Keyword(s):  
Water Vapor ◽  
The Other ◽  
Radiation Budget ◽  
Major Influence ◽  
Fourier Transform Spectrometer ◽  
Remote Sensors ◽  
Weather And Climate ◽  
Comprehensive Picture ◽  
Satellite Sensors ◽  
Important Constituent

Abstract. Water vapor is an important constituent of the atmosphere. Because of its abundance it plays an important role for the radiation budget of the atmosphere and has major influence on weather and climate. In this work the integrated water vapor (IWV) measurements derived from the measurements of two satellite sensors, SCIAMACHY and AMSU-B, and two ground-based sensors, a Fourier-transform spectrometer (FTIR) and an O3 microwave ozone sensor (RAM), are compared to radio-sonde measurements in Ny Ålesund, 79° N. All four remote sensors exploit different principles and work in different wavelength regions. Combined they deliver a comprehensive picture of the IWV above Ny Ålesund. The ground-based FTIR reproduces the radio-sonde measurements very well and also shows a high correlation and very little scatter of about 10%. The other remote sensing instruments show a good correlation with the coincident radio-sonde measurements but show high scatter of about 20% (standard deviation). The ground-based RAM performs similar to the satellite instruments, which is somewhat surprising, because measuring IWV is only a by-product for this sensor. The RAM sensor records a measurement every hour and is therefore suited to observe the diurnal variation. As measured by the RAM and FTIR the variance within 4 h is often in excess of 50% (minimum – maximum of the measured IWV). This large variance in the integrated water vapor renders the comparison of different sensors a difficult task. The derived variance of the instruments when compared to radio-sonde measurements can be explained by the high natural variability of IWV.

Comparison of Arctic cloud properties over sea ice and open ocean based on airborne spectral solar remote sensing

2021 ◽  
Author(s):  
Marcus Klingebiel ◽  
André Ehrlich ◽  
Elena Ruiz-Donoso ◽  
Manfred Wendisch
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Open Water ◽  
Open Ocean ◽  
Arctic Sea Ice ◽  
Radiative Properties ◽  
Radiation Budget ◽  
The Arctic ◽  
Liquid Water Path ◽  
Cloud Properties

<p>Over the last decades, the Arctic has experienced an enhanced warming, which is known as Arctic amplification. This process leads to a decrease in the amount of Arctic sea ice, which is linked by different feedback mechanisms to clouds and the related radiative properties. To analyze how the properties of these Arctic clouds could change in a future sea ice free Arctic, we completed three airborne campaigns in the marginal sea ice zone between 2017 and 2020 covering summer and winter conditions. During these campaigns we performed in-situ and remote sensing measurements to study cloud micro- and macrophysical properties and analyzed how these clouds affect the radiation budget. In this study we use the passive remote sensing measurements from these airborne observations to retrieve cloud top effective radius, liquid water path and cloud optical thickness. We found that these cloud properties differ between a sea ice surface and over open water. The airborne observations are supported by an analysis of the cloud product from the MODIS satellite. The systematic differences of clouds over sea ice and the open ocean suggests that clouds may change in a future warming Arctic environment.</p>

scholarly journals Trend and Variability of the Atmospheric Water Vapor: A Mean Sea Level Issue

2014 ◽  
Vol 31 (9) ◽  
pp. 1881-1901 ◽  
Author(s):  
Soulivanh Thao ◽  
Laurence Eymard ◽  
Estelle Obligis ◽  
Bruno Picard
Keyword(s):  
Water Vapor ◽  
Sea Level ◽  
Microwave Radiometer ◽  
Temporal Distribution ◽  
Quantitative Agreement ◽  
Atmospheric Water Vapor ◽  
Path Delay ◽  
Atmospheric Water ◽  
Mean Sea Level ◽  
The Mean

Abstract The wet tropospheric path delay is presently the main source of error in the estimation of the mean sea level by satellite altimetry. This correction on altimetric measurements, provided by a dedicated radiometer aboard the satellite, directly depends on the atmospheric water vapor content. Nowadays, water vapor products from microwave radiometers are rather consistent but important discrepancies remain. Understanding these differences can help improve the retrieval of water vapor and reduce at the same time the error on the mean sea level. Three radiometers are compared: the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), Jason-1 microwave radiometer (JMR), and Envisat microwave radiometer (MWR). Water vapor products are analyzed both in terms of spatial and temporal distribution over the period 2004–10, using AMSR-E as a reference. The Interim ECMWF Re-Analysis (ERA-Interim) data are also included in the study as an additional point of comparison. Overall, the study confirms the general good agreement between the radiometers: similar patterns are observed for the spatial distribution of water vapor and the correlation of the times series is better than 0.90. However, regional discrepancies are observed and a quantitative agreement on the trend is not obtained. Regional discrepancies are driven by the annual cycle. The JMR product shows discrepancies are highly dependent on water vapor, which might be related to calibration issues. Furthermore, triple collocation analysis suggests a possible drift of JMR. MWR discrepancies are located in coastal regions and follow a seasonal dynamic with stronger differences in summer. It may result from processing of the brightness temperatures.

scholarly journals Assessment and reduction of zenith path delay biases due to day boundary effect

2021 ◽  
Author(s):  
Lau Nguyen Ngoc ◽  
Richard Coleman
Keyword(s):  
Water Vapor ◽  
Boundary Effect ◽  
Critical Factor ◽  
Satellite Orbit ◽  
New Product ◽  
Path Delay ◽  
Initial Value ◽  
International Gnss Service ◽  
Zenith Path Delay ◽  
The Impact

The troposphere consists of dry air and water vapor, delaying the GNSS signal by about 2.4 m in the zenith direction. The water vapor only causes an error of about 0.2 m in distance measurement, but it is challenging to model and overcome. From 2003 the International GNSS Service (IGS) started to provide the new product of zenith path delay (ZPD) with an accuracy of 1.5-5 mm. However, we found an error in these products up to 30 mm at epochs between 2 days due to the day boundary effect and an average of 16mm RMS for nine days. Our research shows that for reducing the impact, the most critical factor is selecting the initial value for the ZPD, followed by satellite orbit/clock and, finally, the station coordinate values. By choosing an appropriate initial value for ZPD and employing a 3 days orbit/clock, the ZPD error due to the day boundary effect can be reduced to negligible. Meanwhile, the change in the station coordinate value in cm level does not impact the effect.

scholarly journals Retrieval Models of Water Vapor and Wet Tropospheric Path Delay for the HY-2A Calibration Microwave Radiometer

2014 ◽  
Vol 31 (7) ◽  
pp. 1516-1528 ◽  
Author(s):  
Gang Zheng ◽  
Jingsong Yang ◽  
Lin Ren
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Dynamic Environment ◽  
Validation Dataset ◽  
Path Delay ◽  
Crossover Point ◽  
Retrieval Models ◽  
Point Distribution ◽  
Along Track ◽  
Temporal Inhomogeneity

Abstract This paper focuses on the development and validation of retrieval models of water vapor (WV) and wet tropospheric path delay (PD) for the calibration microwave radiometer (CMR) on board the first ocean dynamic environment satellite of China—Haiyang-2A (HY-2A). The reference data are those of Jason-1 microwave radiometer (JMR) and Jason-2 advanced microwave radiometer (AMR). The crossover points of the HY-2A and Jason-1/2 satellite tracks are extracted, and the data pairs at these points are divided into fitting and validation datasets. The retrieval models of WV and PD are built for the CMR using the fitting dataset and genetic algorithm, and validated using the validation dataset. The validation shows that the results of the retrieval models are consistent with the JMR and AMR data, and the root-mean-square differences of WV and PD are 1.86 kg m−2 and 11.4 mm, respectively. Finally, the retrieved results from the CMR brightness temperature along-track data using the retrieval models and the AMR along-track data are gridded by the inverse distance weighted method. Their monthly-mean spatial distributions are compared in order to investigate the applicability of the retrieval models globally, namely, beyond locations of the data pairs in the validation dataset. The comparison shows that the retrieval models are applicable in most open ocean areas, and that the latitude and temporal inhomogeneity of the crossover point distribution in the fitting dataset does not lead to obvious latitude and temporal inhomogeneity in the gridded data.

scholarly journals Fog Analysis during SOFOG3D Experiment

2021 ◽  
Author(s):  
Pragya Vishwakarma ◽  
Julien Delanoë ◽  
Christophe Le Gac ◽  
Fabrice Bertrand ◽  
Jean-Charles Dupont ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Microwave Radiometer ◽  
3D Structure ◽  
In Situ Measurements ◽  
Radiation Budget ◽  
Radar Signal ◽  
Cloud Radar ◽  
Microphysical Properties ◽  
South West

<p>Transportation especially aviation sector all around the world is severely hindered due to Fog and hence observations and specific research for fog is necessary. The SOFOG3D (SOuth west FOGs 3D) experiment took place in South-West of France which is particularly prone to fog occurrence, during the period between November 2019 to March 2020 with primary objective to advance our understanding of fog processes and to improve fog forecast. Simultaneous measurements from various remote sensing instruments like BASTA: a 95 GHz cloud radar with scanning capability, HATPRO Microwave radiometer (MWR), doppler lidar, and balloon-borne in-situ measurements were collected to characterize the spatio-temporal evolution of Fog. On the supersite, detailed measurements of meteorological conditions, aerosol properties, fog microphysics, water deposition, radiation budget, heat, and momentum fluxes are collected to provide 3D structure of the boundary layer during fog events. The improvement in the retrieval of fog parameters and understanding of fog dynamics based on cloud radar and microwave (MWR) synergy will be addressed. We will present our work on the retrieval of key fog parameters like dynamics and microphysics using a combination of cloud radar and MWR observations. The retrievals will be validated with the tethered-balloon and radio-sounding observations. In-situ measurements and remote-sensing retrievals of fog microphysical properties will be compared. We will show a detailed analysis of retrieved LWP derived from BASTA radar only with LWP derived from HATPRO microwave radiometer, considering instrumental uncertainty and sensitivity. A closer analysis of the in-situ data (measured by granulometer) will be presented in order to assess and improve the retrieval derived with cloud radar in vertically pointing mode. Radar attenuation will be quantified by measuring the backscattered radar signal on well-known calibrated reflectivity metallic targets installed at the top of 20 m mast. The integrated attenuation along the radar beam path will be measured by the cloud radar and used as a new constraint to improve the microphysical properties.</p>

scholarly journals Remote sensing of water cloud droplet size distributions using the backscatter glory: a case study

2004 ◽  
Vol 4 (5) ◽  
pp. 1255-1263 ◽  
Author(s):  
B. Mayer ◽  
M. Schröder ◽  
R. Preusker ◽  
L. Schüller
Keyword(s):  
Remote Sensing ◽  
Size Distribution ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Single Scattering ◽  
Effective Radius ◽  
Radiative Properties ◽  
High Angular Resolution ◽  
Size Distributions

Abstract. Cloud single scattering properties are mainly determined by the effective radius of the droplet size distribution. There are only few exceptions where the shape of the size distribution affects the optical properties, in particular the rainbow and the glory directions of the scattering phase function. Using observations by the Compact Airborne Spectrographic Imager (CASI) in 180° backscatter geometry, we found that high angular resolution aircraft observations of the glory provide unique new information which is not available from traditional remote sensing techniques: Using only one single wavelength, 753nm, we were able to determine not only optical thickness and effective radius, but also the width of the size distribution at cloud top. Applying this novel technique to the ACE-2 CLOUDYCOLUMN experiment, we found that the size distributions were much narrower than usually assumed in radiation calculations which is in agreement with in-situ observations during this campaign. While the shape of the size distribution has only little relevance for the radiative properties of clouds, it is extremely important for understanding their formation and evolution.

scholarly journals New Gridded Product for the Total Columnar Atmospheric Water Vapor over Ocean Surface Constructed from Microwave Radiometer Satellite Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2402
Author(s):  
Weifu Sun ◽  
Jin Wang ◽  
Yuheng Li ◽  
Junmin Meng ◽  
Yujia Zhao ◽  
...  
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Global Ocean ◽  
Optimal Interpolation ◽  
Fusion Product ◽  
Mean Deviation ◽  
Atmospheric Water ◽  
Absolute Deviation ◽  
Better Than

Based on the optimal interpolation (OI) algorithm, a daily fusion product of high-resolution global ocean columnar atmospheric water vapor with a resolution of 0.25° was generated in this study from multisource remote sensing observations. The product covers the period from 2003 to 2018, and the data represent a fusion of microwave radiometer observations, including those from the Special Sensor Microwave Imager Sounder (SSMIS), WindSat, Advanced Microwave Scanning Radiometer for Earth Observing System sensor (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), and HY-2A microwave radiometer (MR). The accuracy of this water vapor fusion product was validated using radiosonde water vapor observations. The comparative results show that the overall mean deviation (Bias) is smaller than 0.6 mm; the root mean square error (RMSE) and standard deviation (SD) are better than 3 mm, and the mean absolute deviation (MAD) and correlation coefficient (R) are better than 2 mm and 0.98, respectively.

Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors

2014 ◽  
Vol 53 (15) ◽  
pp. 3301 ◽  
Author(s):  
Zhongping Lee ◽  
Shaoling Shang ◽  
Chuanmin Hu ◽  
Giuseppe Zibordi
Keyword(s):  
Remote Sensing ◽  
Ocean Color ◽  
Remote Sensing Reflectance ◽  
Satellite Sensors

scholarly journals Water vapor transport in the lower mesosphere of the subtropics: a trajectory analysis

2008 ◽  
Vol 8 (23) ◽  
pp. 7273-7280 ◽  
Author(s):  
T. Flury ◽  
S. C. Müller ◽  
K. Hocke ◽  
N. Kämpfer
Keyword(s):  
Water Vapor ◽  
Trajectory Analysis ◽  
Microwave Radiometer ◽  
Rotational Transition ◽  
Transport Processes ◽  
Water Vapor Transport ◽  
Transition Line ◽  
Wind Fields ◽  
Large Variability ◽  
Northern India

Abstract. The Institute of Applied Physics operates an airborne microwave radiometer AMSOS that measures the rotational transition line of water vapor at 183.3 GHz. Water vapor profiles are retrieved for the altitude range from 15 to 75 km along the flight track. We report on a water vapor enhancement in the lower mesosphere above India and the Arabian Sea. The measurements took place on our flight from Switzerland to Australia and back in November 2005 conducted during EC- project SCOUT-O3. We find an enhancement of up to 25% in the lower mesospheric H2O volume mixing ratio measured on the return flight one week after the outward flight. The origin of the air is traced back by means of a trajectory model in the lower mesosphere and wind fields from ECMWF. During the outward flight the air came from the Atlantic Ocean around 25 N and 40 W. On the return flight the air came from northern India and Nepal around 25 N and 90 E. Mesospheric H2O measurements from Aura/MLS confirm the transport processes of H2O derived by trajectory analysis of the AMSOS data. Thus the large variability of H2O VMR during our flight is explained by a change of the winds in the lower mesosphere. This study shows that trajectory analysis can be applied in the mesosphere and is a powerful tool to understand the large variability in mesospheric H2O.

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