scholarly journals Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high–resolution visible channel: Evaluation of candidate approaches with MODIS observations

2019 ◽  
Author(s):  
Frank Werner ◽  
Hartwig Deneke
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
High Frequency ◽  
Cloud Droplet ◽  
Horizontal Resolution ◽  
Droplet Radius ◽  
Liquid Water Path ◽  
Cloud Property ◽  
Standard Resolution ◽  
Narrowband Channels

Abstract. This study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native 3 × 3 km2 spatial resolution of the narrowband channels to 1 × 1 km2. These methods make use of SEVIRI’s coincident broadband high–resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1 × 1 km2 MODIS radiances, which are re-projected to the horizontal grid of the HRV channel, and serve as reference for the evaluation. By using these radiances smoothed with the spatial response function of the native SEVIRI channels as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈ 14 and ≈ 6 μm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈ 89 g m−2 and ≈ 177 cm−3, respectively. For τ, these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint, and by applying most of the presented downscaling schemes. For the accuracy of reff,the choice of downscaling scheme however is important: deviations are generally of similar magnitude or larger than those for retrievals at the SEVIRI standard resolution, indicative of their limited skill at predicting high–frequency spatial variability in reff. A strong degradation of accuracy of reff is observed for some of the approaches, which also affects subsequent WL and ND estimates. As a result, an approach which constrains the reff to the lower–resolution results is recommended. Overall, this study demonstrates that an increase in horizontal resolution of SEVIRI cloud property retrievals can be reliably achieved by use of its HRV channel, yielding cloud properties which are preferable in terms of accuracy to those obtained from SEVIRI’s standard-resolution. This work advances efforts to mitigate impacts of scale mismatches among channels of multi–resolution instruments on cloud retrievals.

scholarly journals Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: evaluation of candidate approaches with MODIS observations

2020 ◽  
Vol 13 (3) ◽  
pp. 1089-1111
Author(s):  
Frank Werner ◽  
Hartwig Deneke
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Cloud Droplet ◽  
Horizontal Resolution ◽  
Droplet Radius ◽  
Modulation Transfer ◽  
Liquid Water Path ◽  
Standard Resolution ◽  
Narrowband Channels ◽  
The Right

Abstract. This study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native ≈3km×3km spatial resolution of the narrowband channels to ≈1km×1km. These methods make use of SEVIRI's coincident broadband high-resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1 km×1 km MODIS radiances, which are reprojected to the horizontal grid of the HRV channel and serve as reference for the evaluation. By using these radiances, smoothed with the modulation transfer function of the native SEVIRI channels, as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈14 and ≈6 µm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈89gm-2 and ≈177cm-3, respectively. For τ, these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint and by applying most of the presented downscaling schemes. Uncertainties in retrieved reff at the native SEVIRI resolution are smaller, and the improvements from downscaling the observations are less obvious than for τ. Nonetheless, the right choice of downscaling scheme yields noticeable improvements in the retrieved reff. Furthermore, the improved reliability in retrieved cloud products results in significantly reduced uncertainties in derived WL and ND. In particular, one downscaling approach provides clear improvements for all cloud products compared to those obtained from SEVIRI's standard resolution and is recommended for future downscaling endeavors. This work advances efforts to mitigate impacts of scale mismatches among channels of multiresolution instruments on cloud retrievals.

scholarly journals Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples

2021 ◽  
Vol 14 (7) ◽  
pp. 5107-5126
Author(s):  
Hartwig Deneke ◽  
Carola Barrientos-Velasco ◽  
Sebastian Bley ◽  
Anja Hünerbein ◽  
Stephan Lenk ◽  
...  
Keyword(s):  
High Resolution ◽  
Optical Depth ◽  
Spatial Resolution ◽  
High Frequency ◽  
Spatiotemporal Variability ◽  
High Frequency Component ◽  
Cloud Optical Depth ◽  
Cloud Property ◽  
Cloud Properties ◽  
Narrowband Channels

Abstract. The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1 km2 compared to the standard 3×3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 µm, 0.8 µm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 µm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 µm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

scholarly journals Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples

2020 ◽  
Author(s):  
Hartwig Deneke ◽  
Carola Barrientos-Velasco ◽  
Sebastian Bley ◽  
Anja Hünerbein ◽  
Stephan Lenk ◽  
...  
Keyword(s):  
High Resolution ◽  
Optical Depth ◽  
Spatial Resolution ◽  
High Frequency ◽  
Convective Cloud ◽  
High Frequency Component ◽  
Cloud Optical Depth ◽  
Cloud Property ◽  
Cloud Properties ◽  
Narrowband Channels

Abstract. The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument onboard the geostationary METEOSAT satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1 × 1 km2, compared to the standard 3 × 3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 μm, 0.8 μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved; (ii) the temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel; (iii) an example of surface solar irradiance, determined from the retrieved cloud properties, is shown, where the HRV channel helps to better capture the large spatio-temporal variability induced by convective clouds. These results suggest that incorporating the HRV channel in the retrieval has potential for improving METEOSAT-based cloud products for several application domains.

scholarly journals MBL drizzle properties and their impact on cloud property retrievals

2015 ◽  
Vol 8 (4) ◽  
pp. 4307-4323
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Property ◽  
Annual Means ◽  
Mean Differences ◽  
The Impact

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrievals from ground-based measurements at the ARM Azores site from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6% with a maximum of 55.8% in winter and a minimum of 35.6% in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 5.48 (1.29) g m−2, 68.7 (39.5) μm, and 0.14 (0.38) cm−3. The seasonal mean LWPd values are less than 4% of the MWR-retrieved LWP values. The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.12 and 0.38 μm, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle on cloud property retrievals is insignificant at the ARM Azores site.

scholarly journals Resolution Dependence of European Precipitation in a State-of-the-Art Atmospheric General Circulation Model

2015 ◽  
Vol 28 (13) ◽  
pp. 5134-5149 ◽  
Author(s):  
Ronald van Haren ◽  
Reindert J. Haarsma ◽  
Geert Jan Van Oldenborgh ◽  
Wilco Hazeleger
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Vertical Velocity ◽  
Moisture Transport ◽  
State Of The Art ◽  
Horizontal Resolution ◽  
Accurate Representation ◽  
Medium Resolution ◽  
Resolution Model ◽  
High Resolution Model

Abstract In this study, the authors investigate the effect of GCM spatial resolution on modeled precipitation over Europe. The objectives of the analysis are to determine whether climate models have sufficient spatial resolution to have an accurate representation of the storm tracks that affect precipitation. They investigate if there is a significant statistical difference in modeled precipitation between a medium-resolution (~112-km horizontal resolution) and a high-resolution (~25-km horizontal resolution) version of a state-of-the-art AGCM (EC-EARTH), if either model resolution gives a better representation of precipitation in the current climate, and what processes are responsible for the differences in modeled precipitation. The authors find that the high-resolution model gives a more accurate representation of northern and central European winter precipitation. The medium-resolution model has a larger positive bias in precipitation in most of the northern half of Europe. Storm tracks are better simulated in the high-resolution model, providing for a more accurate horizontal moisture transport and moisture convergence. Using a decomposition of the precipitation difference between the medium- and high-resolution model in a part related and a part unrelated to a difference in the distribution of vertical atmospheric velocity, the authors find that the smaller precipitation bias in central and northern Europe is largely unrelated to a difference in vertical velocity distribution. The smaller precipitation amount in these areas is in agreement with less moisture transport over this area in the high-resolution model. In areas with orography the change in vertical velocity distribution is found to be more important.

scholarly journals Effects of wintertime polluted aerosol on cloud over the Yangtze River Delta: case study

2016 ◽  
Author(s):  
Chen Xu ◽  
Junyan Duan ◽  
Yanyu Wang ◽  
Yifan Wang ◽  
Hailin Zhu ◽  
...  
Keyword(s):  
Yangtze River ◽  
Cloud Droplet ◽  
Yangtze River Delta ◽  
River Delta ◽  
Droplet Radius ◽  
The Yangtze River ◽  
Liquid Water Path ◽  
Cloud Parameters ◽  
Low Clouds ◽  
The Yangtze River Delta

Abstract. The effects of polluted aerosol on cloud are examined over the Yangtze River Delta (YRD) using three-month satellite data during wintertime from December 2013 to January 2014. The relationships between aerosol properties and cloud parameters are analyzed in detail to clarify the differences of cloud development under varying aerosol and meteorology conditions. Complex relationships between aerosol optical depth (AOD) and cloud droplet radius (CDR), liquid water path (LWP) and cloud optical thickness (COT) exists in four sub-regions. High aerosol loading (AOD) does not obviously affect the distributions of cloud LWP and COT. In fact, an inhibiting effect of aerosol occurs in coastal area for low- and medium-low clouds, more pronounced in low clouds (

scholarly journals REVIEW OF METHODS FOR DETERMINING THE SPATIAL RESOLUTION OF UAV SENSORS

2015 ◽  
Vol XL-1/W4 ◽  
pp. 391-395 ◽  
Author(s):  
A. Orych
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Quality Assessment ◽  
Spatial Resolution ◽  
High Frequency ◽  
Frame Size ◽  
Flight Stability ◽  
Amount Of Information ◽  
Imaging Sensor

The ground resolved distance (GRD) of an imaging sensor, i.e. the size of the smallest element distinguishable on acquired imagery, is one of the most important sensor quality assessment factors, as it is directly linked to the amount of information that can be derived from the end product. The paper is a review of a wide variety of calibration targets used for determining the spatial resolution of remote sensing sensors. The author provides a description of calibration targets used historically and then moves on to high-frequency targets used for high-resolution remote sensing imaging equipment. As analysis is made which of these types of targets are best suited for UAV sensors, taking into account parameters very specific to UAVs: frame size, small GSD values and low flight stability.

scholarly journals Marine boundary layer drizzle properties and their impact on cloud property retrieval

2015 ◽  
Vol 8 (9) ◽  
pp. 3555-3562 ◽  
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Marine Boundary Layer ◽  
Microwave Radiometer ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Cloud Property ◽  
Annual Means ◽  
Mean Differences ◽  
The Impact

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrieval in Dong et al. (2014a) from ground-based measurements at the ARM Azores facility from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6 %, with a maximum of 55.8 % in winter and a minimum of 35.6 % in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 4.73 (1.25) g m−2, 61.5 (36.4) μm, and 0.38 (0.79) cm−3. The seasonal mean LWPd values are less than 3 % of the LWP values retrieved by the microwave radiometer (MWR). The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.75 and 2.35 %, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle below the cloud base on cloud property retrieval is insignificant for a solar-transmission-based method, but significant for any retrievals using radar reflectivity.

scholarly journals The semianalytical cloud retrieval algorithm for SCIAMACHY II. The application to MERIS and SCIAMACHY data

2006 ◽  
Vol 6 (2) ◽  
pp. 1813-1840 ◽  
Author(s):  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
V. V. Rozanov ◽  
S. Noël ◽  
K. Gerilowski ◽  
...  
Keyword(s):  
Cloud Droplet ◽  
Droplet Radius ◽  
Retrieval Algorithm ◽  
Liquid Water Path ◽  
Imaging Spectrometer ◽  
Medium Resolution ◽  
Resolution Imaging ◽  
Cloud Optical Thickness ◽  
Scanning Imaging ◽  
First Time

Abstract. The Semianalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, for the first time we derive simultaneously cloud optical thickness (COT), liquid water path (LWP), cloud top height (CTH), and cloud droplet radius (CDR) using SCIAMACHY measurements in the visible (442 nm, COT), in the oxygen A-band (755–775 nm, CTH) and in the infrared (1550 nm, CDR). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observe almost the same scene as SCIAMACHY.

scholarly journals Magnetic Temporal Interference For Noninvasive, High-resolution, and Localized Deep Brain Stimulation: Concept Validation

2020 ◽  
Author(s):  
Mohsen Zaeimbashi ◽  
Adam Khalifa ◽  
Cunzheng Dong ◽  
Yuyi Wei ◽  
Sydney Cash ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
High Resolution ◽  
Magnetic Fields ◽  
Spatial Resolution ◽  
Brain Stimulation ◽  
High Frequency ◽  
Brain Area ◽  
Large Area ◽  
The Brain ◽  
Deep Brain

AbstractNon-invasive deep brain stimulation has been a major challenge in the field of neuroscience and brain stimulation in the past three decades. Current brain stimulation technologies suffer from such hurdles as the inability to do deep brain stimulation, poor spatial resolution, and invasiveness. Transcranial magnetic stimulation (TMS) technique, for instance, cannot target brain regions deeper than ∼2cm and has a poor spatial resolution, impacting a large area of the peripheral region and leading to various side effects. Implantable electrodes, even though effective for deep brain stimulation, are invasive and carry various drawbacks related to the surgery and site infection. In this paper, we propose a new concept that relies on temporal interference of two high- frequency magnetic fields generated by two electromagnetic coils. The neural system does not respond to each of these high-frequency magnetic fields alone because of the intrinsic low-pass filtering properties of the neural membrane. The peripheral areas of the brain are impacted only by the high-frequency magnetic fields that cannot stimulate the nerves, while the deep brain area where the two fields interfere experiences a magnetic field that contains a low-frequency envelope and therefore the nerves can be stimulated. This technique can noninvasively focus a magnetic or electric beam at any depth inside the brain with a high resolution, without impacting the peripheral regions.

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