Development and Testing of a Clear-Sky Data Selection Algorithm for FY-3C/D Microwave Temperature Sounder-2

The Fengyun (FY)-3C/D microwave temperature sounder-2 (MWTS-2) is similar to the Advanced Microwave Sounding Unit-A (AMSU-A), except it lacks two window channels located at 23.8 GHz and 31.4 GHz. This makes a clear-sky data determination challenging for the MWTS-2 due to the unavailability of cloud liquid water path (LWP) retrievable from the two window channels. The purpose of this study is to develop a clear-sky data selection algorithm for the FY-3C/D MWTS-2 based on the bias-removed differences between observations and model simulations of the MWTS-2 50.3-GHz channel 1 (or equivalently AMSU-A channel 3). First, a point is defined as a temporal clear-sky (cloudy) point if the bias-removed difference between observed and simulated brightness temperatures is smaller than or equal to (greater than) 2 K. Then, a temporal clear-sky (cloudy) point is defined as a final clear-sky (cloudy) point if all points within its 60-km (100-km) radial distance are temporal clear-sky (cloudy) points. Finally, if the mean value of the bias-removed differences between observations and simulations in the 100-km circle from a temporal cloudy point are smaller than or equal to (greater than) 2 K, all temporal clear-sky points within this circle are (not) taken as the final clear-sky points. Applications of this algorithm to FY-3C MWTS-2 and MetOp-B AMSU-A lead to the following conclusions: (i) more than 70% (95%) of the clear-sky (cloudy) data points are successfully identified from both AMSU-A and MWTS-2 observations; (ii) the algorithm-selected clear-sky data points were located in clear-sky areas in the GOES-15 imager, and (iii) the bias-removed differences between observations and model simulations of MWTS-2 channel 1 well reveals the eye, the eyewall, and the spiral rainband structure of Super Typhoon Halong (2014).

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The Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP)

Journal of Climate ◽

10.1175/jcli-d-16-0902.1 ◽

2017 ◽

Vol 30 (24) ◽

pp. 10193-10210 ◽

Cited By ~ 40

Author(s):

Gregory S. Elsaesser ◽

Christopher W. O’Dell ◽

Matthew D. Lebsock ◽

Ralf Bennartz ◽

Thomas J. Greenwald ◽

...

Keyword(s):

Liquid Water ◽

Microwave Emission ◽

Liquid Water Path ◽

Water Path ◽

Emission Signal ◽

Clear Sky ◽

University Of Wisconsin ◽

Remote Sensing Systems ◽

Cloud Liquid Water Path ◽

The University

The Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988–2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) intercalibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2, and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and the monthly mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, correcting for a CLWP bias (based on matchups to clear-sky MODIS scenes), and constructing a total (cloud + rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e., CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from −15% (e.g., global oceanic stratocumulus decks) to +5%–10% (e.g., portions of the higher latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Sciences Data and Information Services Center.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-12-00164.1 ◽

2013 ◽

Vol 30 (8) ◽

pp. 1704-1715 ◽

Cited By ~ 11

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.

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On the Consequences of Resampling Microwave Radiometer Observations for Use in Retrieval Algorithms

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2155.1 ◽

2009 ◽

Vol 48 (9) ◽

pp. 1981-1993 ◽

Cited By ~ 18

Author(s):

Anita D. Rapp ◽

M. Lebsock ◽

C. Kummerow

Keyword(s):

Wind Speed ◽

Liquid Water ◽

Microwave Radiometer ◽

Retrieval Algorithm ◽

Time Averaging ◽

Liquid Water Path ◽

Cloud Liquid Water ◽

Water Path ◽

Brightness Temperatures ◽

Cloud Liquid Water Path

Abstract How to deal with the different spatial resolutions of multifrequency satellite microwave radiometer measurements is a common problem in retrievals of cloud properties and rainfall. Data convolution and deconvolution is a common approach to resampling the measurements to a single resolution. Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) measurements are resampled to the resolution of the 19-GHz field of view for use in a multifrequency optimal estimation retrieval algorithm of cloud liquid water path, total precipitable water, and wind speed. Resampling the TMI measurements is found to have a strong influence on retrievals of cloud liquid water path and a slight influence on wind speed. Beam-filling effects in the resampled brightness temperatures are shown to be responsible for the large differences between the retrievals using the TMI native resolution and resampled brightness temperatures. Synthetic retrievals are performed to test the sensitivity of the retrieved parameters to beam-filling effects in the resampling of each of the different channels. Beam-filling effects due to the convolution of the 85-GHz channels are shown to be the largest contributor to differences in retrieved cloud liquid water path. Differences in retrieved wind speeds are found to be a combination of effects from deconvolving the 10-GHz brightness temperatures and compensation effects due to the lower liquid water path being retrieved by the high-frequency channels. The influence of beam-filling effects on daily and monthly averages of cloud liquid water path is also explored. Results show that space–time averaging of cloud liquid water path cannot fully compensate for the beam-filling effects and should be considered when using cloud liquid water path data for validation or in climate studies.

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Constraints on interactions between aerosols and clouds on a global scale from a combination of MODIS-CERES satellite data and climate simulations

Atmospheric Chemistry and Physics ◽

10.5194/acp-10-9851-2010 ◽

2010 ◽

Vol 10 (20) ◽

pp. 9851-9861 ◽

Cited By ~ 12

Author(s):

X. Ma ◽

K. von Salzen ◽

J. Cole

Keyword(s):

Liquid Water ◽

Negative Relationship ◽

Cloud Droplet ◽

Global Scale ◽

Effective Radius ◽

Liquid Water Path ◽

Cloud Droplets ◽

Cloud Liquid Water ◽

Albedo Effect ◽

Cloud Liquid Water Path

Abstract. Satellite-based cloud top effective radius retrieved by the CERES Science Team were combined with simulated aerosol concentrations from CCCma CanAM4 to examine relationships between aerosol and cloud that underlie the first aerosol indirect (cloud albedo) effect. Evidence of a strong negative relationship between sulphate, and organic aerosols, with cloud top effective radius was found for low clouds, indicating both aerosol types are contributing to the first indirect effect on a global scale. Furthermore, effects of aerosol on the cloud droplet effective radius are more pronounced for larger cloud liquid water paths. While CanAM4 broadly reproduces the observed relationship between sulphate aerosols and cloud droplets, it does not reproduce the dependency of cloud top droplet size on organic aerosol concentrations nor the dependency on cloud liquid water path. Simulations with a modified version of the model yield a more realistic dependency of cloud droplets on organic carbon. The robustness of the methods used in the study are investigated by repeating the analysis using aerosol simulated by the GOCART model and cloud top effective radii derived from the MODIS Science Team.

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Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part I: the retrieval algorithms

10.5194/amt-2020-387 ◽

2020 ◽

Author(s):

Anne Garnier ◽

Jacques Pelon ◽

Nicolas Pascal ◽

Mark A. Vaughan ◽

Philippe Dubuisson ◽

...

Keyword(s):

Liquid Water ◽

Cloud Base ◽

Transfer Model ◽

Effective Diameter ◽

Ice Clouds ◽

Clear Sky ◽

Brightness Temperatures ◽

Microphysical Properties ◽

Data Products ◽

Level 2

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear sky brightness temperatures over oceans has been updated and tuned for the simulations using MERRA-2 data to match IIR observations in clear sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5-km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ± 0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also aimed at improving retrievals in ice clouds having large optical depths by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and the CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3, and increases the number of retrievals in dense ice clouds. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 μm and 10.6 μm and at 12.05 μm and 08.65 μm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice crystal models from the recent TAMUice 2016 database, namely the single hexagonal column model and the 8-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 µm and 10.6 µm and effective diameter as derived from in situ measurements at tropical and mid-latitudes during the TC4 and SPARTICUS field experiments.

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Intercomparison of integrated IASI and AATSR calibrated radiances

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-8101-2009 ◽

2009 ◽

Vol 9 (2) ◽

pp. 8101-8119 ◽

Cited By ~ 1

Author(s):

S. M. Illingworth ◽

J. J. Remedios ◽

R. J. Parker

Keyword(s):

Weather Prediction ◽

Radiometric Calibration ◽

Spectral Filter ◽

Filter Function ◽

Brightness Temperatures ◽

Data Points ◽

Cross Calibration ◽

Sky Conditions ◽

Error Constraint

Abstract. The mission objectives of the Infrared Atmospheric Sounding Interferometer (IASI) are driven by the needs of the Numerical Weather Prediction (NWP) and climate monitoring communities. These objectives rely upon the IASI instrument being able to measure top of atmosphere radiances accurately. This paper presents a technique and results for the validation of the radiometric calibration of radiances for IASI, using a cross-calibration with the Advanced Along Track Scanning Radiometer (AATSR). The AATSR is able to measure Brightness Temperature (BT) to an accuracy of 30 mK, and by applying the AATSR spectral filter function to the IASI measured radiances we are able to compare AATSR and IASI Brightness Temperatures. By choosing coincidental data points that are over the sea and in clear sky conditions, a threshold of homogeneity is derived. It is found that in these homogenous conditions, the IASI BTs agree with those measured by the AATSR to within 0.5 K, with a precision of order 0.04 K. These results indicate that IASI is likely to be meeting its target objective of 0.5 K accuracy. It is believed that a refinement of the AATSR spectral filter function will hopefully permit a tighter error constraint on the quality of the IASI data and hence further assessment of the climate quality of the radiances.

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Observing the timescales of aerosol-cloud interactions in snapshot satellite images

10.5194/acp-2020-1030 ◽

2020 ◽

Author(s):

Edward Gryspeerdt ◽

Tom Goren ◽

Tristan W. P. Smith

Keyword(s):

Satellite Images ◽

Strong Impact ◽

Natural Experiments ◽

Liquid Water Path ◽

Clear Sky ◽

Cloud Properties ◽

Aerosol Cloud Interactions ◽

Aerosol Source ◽

Retrieval Bias ◽

Ship Emission

Abstract. The response of cloud processes to an aerosol perturbation is one of the largest uncertainties in the anthropogenic forcing of the climate. It occurs at a variety of timescales, from the near-instantaneous Twomey effect, to the longer timescales required for cloud adjustments. Understanding the temporal evolution of cloud properties following an aerosol perturbation is necessary to interpret the results of so-called "natural experiments" from a known aerosol source, such as a ship or industrial site. This work uses reanalysis windfields and ship emission information matched to observations of shiptracks to measure the timescales of cloud responses to aerosol in instantaneous (or "snapshot") images taken by polar-orbiting satellites. As found in previous studies, the local meteorological environment is shown to have a strong impact on the occurrence and properties of shiptracks, but there is a strong time dependence in their properties. The largest droplet number concentration (Nd) responses are found within three hours of emission, while cloud adjustments continue to evolve over periods of ten hours or more. Cloud fraction is increased within the early life of shiptracks, with the formation of shiptracks in otherwise clear skies indicating that around 5–10 % of clear-sky cases in this region may be aerosol-limited. The liquid water path (LWP) enhancement and the Nd-LWP sensitivity are also time dependent and strong functions of the background cloud and meteorological state. The near-instant response of the LWP within shiptracks may be evidence of a retrieval bias in previous estimates of the LWP response to aerosol derived from natural experiments. These results highlight the importance of temporal development and the background cloud field for quantifying the aerosol impact on clouds, even in situations where the aerosol perturbation is clear.

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Observing the timescales of aerosol–cloud interactions in snapshot satellite images

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-6093-2021 ◽

2021 ◽

Vol 21 (8) ◽

pp. 6093-6109

Author(s):

Edward Gryspeerdt ◽

Tom Goren ◽

Tristan W. P. Smith

Keyword(s):

Strong Impact ◽

Natural Experiments ◽

Wind Fields ◽

Liquid Water Path ◽

Clear Sky ◽

Cloud Properties ◽

Ship Tracks ◽

Aerosol Cloud Interactions ◽

Aerosol Source ◽

Ship Emission

Abstract. The response of cloud processes to an aerosol perturbation is one of the largest uncertainties in the anthropogenic forcing of the climate. It occurs at a variety of timescales, from the near-instantaneous Twomey effect to the longer timescales required for cloud adjustments. Understanding the temporal evolution of cloud properties following an aerosol perturbation is necessary to interpret the results of so-called “natural experiments” from a known aerosol source such as a ship or industrial site. This work uses reanalysis wind fields and ship emission information matched to observations of ship tracks to measure the timescales of cloud responses to aerosol in instantaneous (or“snapshot”) images taken by polar-orbiting satellites. As in previous studies, the local meteorological environment is shown to have a strong impact on the occurrence and properties of ship tracks, but there is a strong time dependence in their properties. The largest droplet number concentration (Nd) responses are found within 3 h of emission, while cloud adjustments continue to evolve over periods of 10 h or more. Cloud fraction is increased within the early life of ship tracks, with the formation of ship tracks in otherwise clear skies indicating that around 5 %–10 % of clear-sky cases in this region may be aerosol-limited. The liquid water path (LWP) enhancement and the Nd–LWP sensitivity are also time dependent and strong functions of the background cloud and meteorological state. The near-instant response of the LWP within ship tracks may be evidence of a bias in estimates of the LWP response to aerosol derived from natural experiments. These results highlight the importance of temporal development and the background cloud field for quantifying the aerosol impact on clouds, even in situations where the aerosol perturbation is clear.

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Observed Boundary Layer Controls on Shallow Cumulus at the ARM Southern Great Plains Site

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-17-0244.1 ◽

2018 ◽

Vol 75 (7) ◽

pp. 2235-2255 ◽

Cited By ~ 15

Author(s):

Neil P. Lareau ◽

Yunyan Zhang ◽

Stephen A. Klein

Keyword(s):

Boundary Layer ◽

Great Plains ◽

Vertical Velocity ◽

Mass Flux ◽

Cloud Base ◽

Liquid Water Path ◽

Southern Great Plains ◽

Clear Sky ◽

Shallow Cumulus ◽

In Situ Sensors

Abstract The boundary layer controls on shallow cumulus (ShCu) convection are examined using a suite of remote and in situ sensors at ARM Southern Great Plains (SGP). A key instrument in the study is a Doppler lidar that measures vertical velocity in the CBL and along cloud base. Using a sample of 138 ShCu days, the composite structure of the ShCu CBL is examined, revealing increased vertical velocity (VV) variance during periods of medium cloud cover and higher VV skewness on ShCu days than on clear-sky days. The subcloud circulations of 1791 individual cumuli are also examined. From these data, we show that cloud-base updrafts, normalized by convective velocity, vary as a function of updraft width normalized by CBL depth. It is also found that 63% of clouds have positive cloud-base mass flux and are linked to coherent updrafts extending over the depth of the CBL. In contrast, negative mass flux clouds lack coherent subcloud updrafts. Both sets of clouds possess narrow downdrafts extending from the cloud edges into the subcloud layer. These downdrafts are also present adjacent to cloud-free updrafts, suggesting they are mechanical in origin. The cloud-base updraft data are subsequently combined with observations of convective inhibition to form dimensionless “cloud inhibition” (CI) parameters. Updraft fraction and liquid water path are shown to vary inversely with CI, a finding consistent with CIN-based closures used in convective parameterizations. However, we also demonstrate a limited link between CBL vertical velocity variance and cloud-base updrafts, suggesting that additional factors, including updraft width, are necessary predictors for cloud-base updrafts.

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Validation of Hourly Global Horizontal Irradiance for Two Satellite-Derived Datasets in Northeast Iraq

Remote Sensing ◽

10.3390/rs10101651 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1651 ◽

Cited By ~ 4

Author(s):

Bikhtiyar Ameen ◽

Heiko Balzter ◽

Claire Jarvis ◽

Etienne Wey ◽

Claire Thomas ◽

...

Keyword(s):

Climate Data ◽

Clearness Index ◽

Clear Sky ◽

Station Data ◽

Data Points ◽

Recorded Data ◽

Monitoring Service ◽

Sky Conditions ◽

Station Location

Several sectors need global horizontal irradiance (GHI) data for various purposes. However, the availability of a long-term time series of high quality in situ GHI measurements is limited. Therefore, several studies have tried to estimate GHI by re-analysing climate data or satellite images. Validation is essential for the later use of GHI data in the regions with a scarcity of ground-recorded data. This study contributes to previous studies that have been carried out in the past to validate HelioClim-3 version 5 (HC3v5) and the Copernicus Atmosphere Monitoring Service, using radiation service version 3 (CRSv3) data of hourly GHI from satellite-derived datasets (SDD) with nine ground stations in northeast Iraq, which have not been used previously. The validation is carried out with station data at the pixel locations and two other data points in the vicinity of each station, which is something that is rarely seen in the literature. The temporal and spatial trends of the ground data are well captured by the two SDDs. Correlation ranges from 0.94 to 0.97 in all-sky and clear-sky conditions in most cases, while for cloudy-sky conditions, it is between 0.51–0.72 and 0.82–0.89 for the clearness index. The bias is negative for most of the cases, except for three positive cases. It ranges from −7% to 4%, and −8% to 3% for the all-sky and clear-sky conditions, respectively. For cloudy-sky conditions, the bias is positive, and differs from one station to another, from 16% to 85%. The root mean square error (RMSE) ranges between 12–20% and 8–12% for all-sky and clear-sky conditions, respectively. In contrast, the RMSE range is significantly higher in cloudy-sky conditions: above 56%. The bias and RMSE for the clearness index are nearly the same as those for the GHI for all-sky conditions. The spatial variability of hourly GHI SDD differs only by 2%, depending on the station location compared to the data points around each station. The variability of two SDDs is quite similar to the ground data, based on the mean and standard deviation of hourly GHI in a month. Having station data at different timescales and the small number of stations with GHI records in the region are the main limitations of this analysis.

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