scholarly journals A quality control procedure for Fengyun-3A microwave temperature sounder with emphasis on a new cloud detection algorithm

2016 ◽  
Vol 66 (1) ◽  
pp. 19
Author(s):  
Xiang Wang ◽  
Yifang Ren ◽  
Gang Li
Keyword(s):  
Quality Control ◽  
Liquid Water ◽  
Detection Algorithm ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Control Procedure ◽  
Cloud Detection ◽  
Liquid Water Path ◽  
Model Simulations ◽  
Water Path

A cloud detection algorithm for satellite radiance from the microwave temperature sounder (MWTS) on board the first satellite of the Chinese polar-orbiting Fengyun-three series (FY-3A) is proposed based on the measurements at the frequencies of 50.3 and 53.6 GHz. The cloud liquid water path index (LWP index) is calculated using the brightness temperature at these two channels. Analysis of one case carried out in January2010shows the great consistency be-tween this new algorithm result and the available liquid water path product from the Meteorological Operational satellite A (MetOp-A).In general, about 60% of the global MWTS data are considered to be contaminated by cloud by virtue of the new cloud detection algorithm. A quality control (QC) procedure is applied to MWTS measurements with emphasis on the cloud detection. The QC steps are composed of (i) channel 2 over sea ice, land and coastal field of views (FOVs); (ii) channels 2 and 3 over cloudy FOVs; and (iii) outliers with large differences between observations and model simulations. After QC, MWTS measurements of channels 2–4 agree very well with the model simulations using the National Centres for Environmental Prediction (NCEP) forecast data as radiative transfer model input; the scan biases are reduced significantly, especially at the edges of the swath; and the frequency distributions of the differences between observations and model simulations become more Gaussian-like.

A Quality Control Procedure for FY-3A MWTS Measurements with Emphasis on Cloud Detection Using VIRR Cloud Fraction

2013 ◽  
Vol 30 (8) ◽  
pp. 1704-1715 ◽  
Author(s):  
Juan Li ◽  
Xiaolei Zou
Keyword(s):  
Quality Control ◽  
Detection Algorithm ◽  
Cloud Fraction ◽  
Control Procedure ◽  
Test Results ◽  
Cloud Detection ◽  
Liquid Water Path ◽  
Model Simulations ◽  
Cloud Liquid Water Path ◽  
Environmental Prediction

Abstract A quality control (QC) procedure for satellite radiance assimilation is proposed and applied to radiance observations from the Microwave Temperature Sounder (MWTS) on board the first satellite of the Chinese polar-orbiting Fengyun-3 series (FY-3A). A cloud detection algorithm is incorporated based on the cloud fraction product provided by the Visible and Infrared Radiometer (VIRR) on board FY-3A. Analysis of the test results conducted in July 2011 indicates that most clouds are identifiable by applying an FY-3A VIRR cloud fraction threshold of 37%. This result is verified with the cloud liquid water path data from the Meteorological Operational Satellite A (MetOp-A). On average, 56.1% of the global MWTS data are identified as cloudy by the VIRR-based cloud detection method. Other QC steps include the following: (i) two outmost field of views (FOVs), (ii) use of channel 3 if the terrain altitude is greater than 500 m, (iii) channel 2 over sea ice and land, (iv) coastal FOVs, and (v) outliers with large differences between model simulations and observations. About 82%, 74%, and 29% of the MWTS observations are removed by the proposed QC for channels 2–4, respectively. An approximate 0.5-K scan bias improvement is achieved with QC, with a large impact at edges of the field of regard for channels 2–4. After QC, FY-3A MWTS global data more closely resemble the National Centers for Environmental Prediction (NCEP) forecast data, the global biases and standard deviations are reduced significantly, and the frequency distribution of the differences between observations and model simulations become more Gaussian.

scholarly journals Characteristic Atmospheric Radiative Heating Rate Profiles in Arctic Clouds as Observed at Barrow, Alaska

2018 ◽  
Vol 57 (4) ◽  
pp. 953-968 ◽  
Author(s):  
D. D. Turner ◽  
M. D. Shupe ◽  
A. B. Zwink
Keyword(s):  
Heating Rate ◽  
Liquid Water ◽  
Single Layer ◽  
Radiative Heating ◽  
Radiative Transfer Model ◽  
Radiative Cooling ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Water Path ◽  
Order Of Magnitude

AbstractA 2-yr cloud microphysical property dataset derived from ground-based remote sensors at the Atmospheric Radiation Measurement site near Barrow, Alaska, was used as input into a radiative transfer model to compute radiative heating rate (RHR) profiles in the atmosphere. Both the longwave (LW; 5–100 μm) and shortwave (SW; 0.2–5 μm) RHR profiles show significant month-to-month variability because of seasonal dependence in the vertical profiles of cloud liquid and ice water contents, with additional contributions from the seasonal dependencies of solar zenith angle, water vapor amount, and temperature. The LW and SW RHR profiles were binned to provide characteristic profiles as a function of cloud type and liquid water path (LWP). Single-layer liquid-only clouds are shown to have larger (10–30 K day−1) LW radiative cooling rates at the top of the cloud layer than single-layer mixed-phase clouds; this is due primarily to differences in the vertical distribution of liquid water between the two classes. However, differences in SW RHR profiles at the top of these two classes of clouds are less than 3 K day−1. The absolute value of the RHR in single-layer ice-only clouds is an order of magnitude smaller than in liquid-bearing clouds. Furthermore, for double-layer cloud systems, the phase and condensed water path of the upper cloud strongly modulate the radiative cooling both at the top and within the lower-level cloud. While sensitivity to cloud overlap and phase has been shown previously, the characteristic RHR profiles are markedly different between the different cloud classifications.

Exploring the Assimilation of ATMS Cloud Retrieval Products and its Benefits for CrIS All-sky Radiance Simulations

2021 ◽  
Author(s):  
Xin Li ◽  
Xiaolei Zou ◽  
Mingjian Zeng ◽  
Ning Wang ◽  
Fei Tang
Keyword(s):  
Advanced Technology ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Water Path ◽  
Sky Radiance ◽  
Cloud Liquid Water Path ◽  
Cross Track ◽  
Ice Water ◽  
Statistical Interpolation

AbstractAimed at improving all-sky Cross-track Infrared Sounder (CrIS) radiance assimilation, this study explores the benefits for CrIS all-sky radiance simulations, focusing on the accuracy of background cloud information, through assimilating cloud liquid water path (LWP), ice water path (IWP), and rain water path (RWP) data retrieved from the Advanced Technology Microwave Sounder (ATMS). The Community Radiative Transfer Model (CRTM), which considers cloud scattering and absorption processes, is applied to simulate CrIS radiances. The Gridpoint Statistical Interpolation ensemble-variational data assimilation (DA) is updated by incorporating ensemble covariances of hydrometeor variables and observation operators of LWP, IWP, and RWP. First, two DA experiments named DActrl and DAcwp are conducted with (DAcwp) and without (DActrl) assimilating ATMS LWP, IWP, and RWP data. Assimilating ATMS cloud retrieval data results in better spatial distributions of hydrometers for both a Meiyu rainfall case and a typhoon case. Analyses of DActrl and DAcwp are then used as input to the CRTM to generate CrIS all-sky radiance simulations SMallsky_DActrl and SMallsky_DAcwp, respectively. Improvements in the DAcwp analyses of hydrometeor variables are found to benefit CrIS radiance simulations, especially in cloudy regions. A long period of statistics reveals that the biases and standard deviations of all-sky observations minus simulations from SMallsky_DAcwp are notably smaller than those from SMallsky_DActrl. This pilot study suggests the potential benefit of combining the use of microwave cloud retrieval products for all-sky infrared DA.

scholarly journals A MODIS-Derived Value-Added Climatology of Maritime Cloud Liquid Water Path That Conserves Solar Reflectance

2017 ◽  
Vol 56 (6) ◽  
pp. 1767-1781
Author(s):  
Amanda Gumber ◽  
Michael J. Foster
Keyword(s):  
Monte Carlo ◽  
Radiative Transfer ◽  
Liquid Water ◽  
Value Added ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Cloud Liquid Water Path ◽  
Visible Reflectance

AbstractA dataset is generated from a method to retrieve distributions of cloud liquid water path over partially cloudy scenes. The method was introduced in a 2011 paper by Foster and coauthors that described the theory and provided test cases. Here it has been applied to Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 and collection-6 cloud products, resulting in a value-added dataset that contains adjusted distributions of cloud liquid water path for more than 10 years for marine liquid cloud for both Aqua and Terra. This method adjusts horizontal distributions of cloud optical properties to be more consistent with observed visible reflectance and is especially useful in areas where cloud optical retrievals fail or are considered to be of low quality. Potential uses of this dataset include validation of climate and radiative transfer models and facilitation of studies that intercompare satellite records. Results show that the fit method is able to reduce bias between observed visible reflectance and that derived from optical retrievals by up to an average improvement of 3%. The level of improvement is dependent on several factors, including seasonality, viewing geometry, cloud fraction, and cloud heterogeneity. Applications of this dataset are explored through a satellite intercomparison with PATMOS-x and Global Change Observation Mission–First Water (GCOM-W1; “SHIZUKU”) AMSR-2 and use of a Monte Carlo radiative transfer model. From the 3D Monte Carlo model simulations, albedo biases are found when the method is applied, with seasonal averages that range over 0.02–0.06.

AMSU-B Observations of Mixed-Phase Clouds over Land

2005 ◽  
Vol 44 (1) ◽  
pp. 72-85 ◽  
Author(s):  
M. N. Deeter ◽  
J. Vivekanandan
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Mixed Phase ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effects ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Properties ◽  
Mixed Phase Clouds

Abstract Measurements from passive microwave satellite instruments such as the Advanced Microwave Sounding Unit B (AMSU-B) are sensitive to both liquid and ice cloud particles. Radiative transfer modeling is exploited to simulate the response of the AMSU-B instrument to mixed-phase clouds over land. The plane-parallel radiative transfer model employed for the study accounts for scattering and absorption from cloud ice as well as absorption and emission from trace gases and cloud liquid. The radiative effects of mixed-phase clouds on AMSU-B window channels (i.e., 89 and 150 GHz) and water vapor line channels (i.e., 183 ± 1, 3, and 7 GHz) are studied. Sensitivities to noncloud parameters, including surface temperature, surface emissivity, and atmospheric temperature and water vapor profiles, are also quantified. Modeling results indicate that both cloud phases generally have significant radiative effects and that the 150- and 183 ± 7-GHz channels are typically the most sensitive channels to integrated cloud properties (i.e., liquid water path and ice water path). However, results also indicate that AMSU-B measurements alone are probably insufficient for retrieving all mixed-phase cloud properties of interest. These results are supported by comparisons of AMSU-B observations of a mixed-phase cloud over the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site with corresponding calculated clear-sky values.

scholarly journals Cloud<i>_</i>cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties

2020 ◽  
Vol 12 (3) ◽  
pp. 2121-2135
Author(s):  
Caroline A. Poulsen ◽  
Gregory R. McGarragh ◽  
Gareth E. Thomas ◽  
Martin Stengel ◽  
Matthew W. Christensen ◽  
...  
Keyword(s):  
Liquid Water ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Data Set ◽  
Water Path ◽  
Cloud Properties ◽  
Wide Range ◽  
Good Agreement

Abstract. We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

Cloud detection methods for a stand-alone ground based microwave radiometer

2021 ◽  
Author(s):  
Moritz Löffler ◽  
Christine Knist ◽  
Jasmin Vural ◽  
Annika Schomburg ◽  
Volker Lehmann ◽  
...  
Keyword(s):  
Microwave Radiometer ◽  
Data Availability ◽  
Detection Methods ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Detection ◽  
Test Bed ◽  
Secondary Products ◽  
Liquid Water Path ◽  
Scientific Publications

&lt;p&gt;The project &amp;#8220;Pilotstation&amp;#8221; at DWD employs a test bed setup to assess data availability, quality, observation impact and operational sustainability for five different ground based remote sensing instruments. The instruments in question, also referred to as &amp;#8220;profilers&amp;#8221;, are designed to continuously measure vertical profiles of thermodynamic and cloud/aerosol related variables.&lt;/p&gt; &lt;p&gt;A ground based microwave radiometer (MWR) is one of the instruments evaluated in the project &amp;#8220;Pilotstation&amp;#8221;. MWR primarily measure downwelling radiation in the K-band and V-band in the form of brightness temperatures (TB). All-sky temperature and low-resolution humidity profiles as well as high-accuracy liquid water path (LWP, &amp;#916;LWP: &amp;#177; 10-20 gm&lt;sup&gt;-2&lt;/sup&gt;) and integrated water vapour (IWV, &amp;#916;IWV: ~ &amp;#177; 0.5 kgm&lt;sup&gt;-2&lt;/sup&gt;) are secondary products, which can be derived from the TB.&lt;/p&gt; &lt;p&gt;The adaptation of the fast radiative transfer model RTTOV for ground based instruments enabled weather services to go forward with directly assimilating MWR TB rather than secondary products. First assimilation experiments of MWR TB at DWD were successful. Alongside other quality checks, the data assimilation (DA) relies on a cloud detection beforehand. The most frequent reason for rejecting data from DA is the suspected presence of clouds, consequently reliably identifying clouds without excessively rejecting clear-sky data is especially important for a high availability of suitable data.&lt;/p&gt; &lt;p&gt;The study presented focuses on the requirements of operational DA and a stand-alone setup of an MWR. The work compares the performance of cloud detection algorithms used in scientific publications based on MWR observations. The comparisons include methods using TB, LWP and their variability. For this the CloudNet classification time series at Lindenberg and observation minus model background statistics serve as references. The presentation will also include progress made on refining the cloud detection schemes at hand in order to achieve a higher precision and to better meet the requirements of DA.&lt;/p&gt;

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