Meteosat-Based Characterization of the Spatiotemporal Evolution of Warm Convective Cloud Fields over Central Europe

2016 ◽  
Vol 55 (10) ◽  
pp. 2181-2195 ◽  
Author(s):  
Sebastian Bley ◽  
Hartwig Deneke ◽  
Fabian Senf
Keyword(s):  
Time Series ◽  
Central Europe ◽  
Convective Cloud ◽  
Horizontal Wind ◽  
Small Scale ◽  
Liquid Water Path ◽  
Spatiotemporal Evolution ◽  
Cloud Optical Depth ◽  
Water Path ◽  
Time Lagged

AbstractThe spatiotemporal evolution of warm convective cloud fields over central Europe is investigated on the basis of 30 cases using observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the geostationary Meteosat platforms. Cloud fields are tracked in successive satellite images using cloud motion vectors. The time-lagged autocorrelation is calculated for spectral reflectance and cloud property fields using boxes of 16 × 16 pixels and adopting both Lagrangian and Eulerian perspectives. The 0.6-μm reflectance, cloud optical depth, and water path show a similar characteristic Lagrangian decorrelation time of about 30 min. In contrast, significantly lower decorrelation times are observed for the cloud effective radius and droplet density. It is shown that the Eulerian decorrelation time can be decomposed into an advective component and a convective component using the spatial autocorrelation function. In an Eulerian frame cloud fields generally decorrelate faster than in a Lagrangian one. The Eulerian decorrelation time contains contributions from the spatial decorrelation of the cloud field advected by the horizontal wind. A typical spatial decorrelation length of 7 km is observed, which suggests that sampling of SEVIRI observations is better in the temporal domain than in the spatial domain when investigating small-scale convective clouds. An along-track time series of box-averaged cloud liquid water path is derived and compared with the time series that would be measured at a fixed location. Supported by previous results, it is argued that this makes it possible to discriminate between local changes such as condensation and evaporation on the one hand and advective changes on the other hand.

scholarly journals Joint Cloud Water Path and Rain Water Path Retrievals from ORACLES Observations

2020 ◽  
Author(s):  
Andrew M. Dzambo ◽  
Tristan L'Ecuyer ◽  
Kenneth Sinclair ◽  
Bastiaan van Diedenhoven ◽  
Siddhant Gupta ◽  
...  
Keyword(s):  
Optical Depth ◽  
Liquid Water ◽  
Cloud Water ◽  
Retrieval Algorithm ◽  
Liquid Water Path ◽  
Cloud Optical Depth ◽  
Water Path ◽  
Surface Precipitation ◽  
Uncertainty Estimates ◽  
Cloud Water Path

Abstract. This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar-3rd generation (APR-3), passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ~ 10–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP) with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e. rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in-situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud-precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

scholarly journals Observations of Quasi-Stationary and Shallow Orographic Snow Clouds: Spatial Distributions of Supercooled Liquid Water and Snow Particles

2005 ◽  
Vol 133 (4) ◽  
pp. 743-751 ◽  
Author(s):  
Kenichi Kusunoki ◽  
Masataka Murakami ◽  
Narihiro Orikasa ◽  
Mizuho Hoshimoto ◽  
Yoshinobu Tanaka ◽  
...  
Keyword(s):  
Liquid Water ◽  
Microwave Radiometer ◽  
Indirect Evidence ◽  
Supercooled Liquid ◽  
Small Scale ◽  
Mountain Range ◽  
Spatial Distributions ◽  
Liquid Water Path ◽  
Cyclonic Storm ◽  
Water Path

On 25 February 1999, due to a winter monsoon after a cyclonic storm, orographic snow clouds formed under conditions of weak cold advection on the western side of the central mountain range of Japan. In this study, the Ka-band Doppler radar and vehicle-mounted microwave radiometer and 2D-Grey imaging probe were used to obtain unique datasets for analyzing the spatial distributions of microphysical structures of the snow clouds at the windward slope. The liquid water path, number concentration of snow particles (0.1–6.4 mm diameter), and precipitation rate were found to be correlated with altitude. The greater concentration of larger particles tended to appear up the slope. The echo top was at about 2.5 km (−30 dBZ), and the relatively strong echo region (>−3 dBZ) appeared at 5 km up the slope and extended nearly parallel to the slope. According to the echo pattern, the ice water path increased with terrain height and reached the maximum intensity at about 14 km up the slope. These observations provide indirect evidence that terrain-induced updrafts lead to the generation and growth of supercooled cloud droplets and indicate that the riming process plays an important role in the growth of snow particles at higher altitudes. In this paper, it is confirmed that the abundance of supercooled liquid water (SLW) during intensified monsoon flow is due to larger water production rates caused by higher vertical velocities induced by topography. Furthermore, it can be shown that small-scale terrains enhance localized updrafts embedded within the larger-scale flow and have noticeable impact on SLW cloud distribution.

scholarly journals LamaH | <i>La</i>rge-Sa<i>m</i>ple D<i>a</i>ta for <i>H</i>ydrology and Environmental Sciences for Central Europe

2021 ◽  
Author(s):  
Christoph Klingler ◽  
Karsten Schulz ◽  
Mathew Herrnegger
Keyword(s):  
Time Series ◽  
Central Europe ◽  
Hydrological Cycle ◽  
Human Impacts ◽  
Small Scale ◽  
High Temporal Resolution ◽  
Large Sample ◽  
Potential Applications ◽  
The Individual ◽  
Headwater Basins

Abstract. Very large and comprehensive datasets are increasingly used in the field of hydrology. Large-sample studies provide insights into the hydrological cycle that might not be available with small-scale studies. LamaH (Large-Sample Data for Hydrology) is a new dataset for large-sample studies and comparative hydrology in Central Europe. It covers the entire upper Danube to the state border Austria/Slovakia, as well as all other Austrian catchments including their foreign upstream areas. LamaH covers an area of 170 000 km2 in 9 different countries, ranging from lowland regions characterized by a continental climate to high alpine zones dominated by snow and ice. Consequently, a wide diversity of properties is present in the individual catchments. We represent this variability in 859 observed catchments with over 60 catchment attributes, covering topography, climatology, hydrology, land cover, vegetation, soil and geological properties. LamaH further contains a collection of runoff time series as well as meteorological time series. These time series are provided with daily and also hourly resolution. All meteorological and the majority of runoff time series cover a span of over 35 years, which enables long-term analyses, also with a high temporal resolution. The runoff time series are classified by over 20 different attributes including information about human impacts and indicators for data quality and completeness. The structure of LamaH is based on the well-known CAMELS datasets. In contrast, however, LamaH does not only consider headwater basins. Intermediate catchments are also covered, allowing, for the first time within a hydrological large sample dataset, to consider the hydrological network and river topology in applications. We discuss not only the data basis and the methodology of data preparation, but also focus on possible limitations and uncertainties. Potential applications of LamaH are also outlined, since it is intended to serve as a uniform basis for further research. LamaH is available at https://doi.org/10.5281/zenodo.4525244 (Klingler et al., 2021).

scholarly journals LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe

2021 ◽  
Vol 13 (9) ◽  
pp. 4529-4565
Author(s):  
Christoph Klingler ◽  
Karsten Schulz ◽  
Mathew Herrnegger
Keyword(s):  
Time Series ◽  
Central Europe ◽  
Hydrological Cycle ◽  
Human Impacts ◽  
Small Scale ◽  
High Temporal Resolution ◽  
Environmental Sciences ◽  
Large Sample ◽  
Sample Data ◽  
The Individual

Abstract. Very large and comprehensive datasets are increasingly used in the field of hydrology. Large-sample studies provide insights into the hydrological cycle that might not be available with small-scale studies. LamaH-CE (LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe, LamaH for short; the geographical extension “-CE” is omitted in the text and the dataset) is a new dataset for large-sample studies and comparative hydrology in Central Europe. It covers the entire upper Danube to the state border of Austria–Slovakia, as well as all other Austrian catchments including their foreign upstream areas. LamaH covers an area of about 170 000 km2 in nine countries, ranging from lowland regions characterized by a continental climate to high alpine zones dominated by snow and ice. Consequently, a wide diversity of properties is present in the individual catchments. We represent this variability in 859 gauged catchments with over 60 catchment attributes, covering topography, climatology, hydrology, land cover, vegetation, soil and geological properties. LamaH further contains a collection of runoff time series as well as meteorological time series. These time series are provided with a daily and hourly resolution. All meteorological and the majority of runoff time series cover a span of over 35 years, which enables long-term analyses with a high temporal resolution. The runoff time series are classified by over 20 attributes including information about human impacts and indicators for data quality and completeness. The structure of LamaH is based on the well-known CAMELS (Catchment Attributes and MEteorology for Large-sample Studies) datasets. In contrast, however, LamaH does not only consider independent basins, covering the full upstream area. Intermediate catchments are covered as well, which allows together with novel attributes the considering of the hydrological network and river topology in applications. We not only describe the basic datasets used and methodology of data preparation but also focus on possible limitations and uncertainties. LamaH contains additionally results of a conceptual hydrological baseline model for checking plausibility of the inputs as well as benchmarking. Potential applications of LamaH are outlined as well, since it is intended to serve as a uniform data basis for further research. LamaH is available at https://doi.org/10.5281/zenodo.4525244 (Klingler et al., 2021).

scholarly journals Comparison of Macro- and Microphysical Properties in Precipitating and Non-Precipitating Clouds over Central-Eastern China during Warm Season

2021 ◽  
Vol 14 (1) ◽  
pp. 152
Author(s):  
Xiaoyi Zheng ◽  
Yuanjian Yang ◽  
Ye Yuan ◽  
Yanan Cao ◽  
Jinlan Gao
Keyword(s):  
Eastern China ◽  
Low Frequency ◽  
Warm Season ◽  
Physical Structure ◽  
Liquid Water Path ◽  
Cloud Optical Depth ◽  
Water Path ◽  
Microphysical Properties ◽  
Central Eastern ◽  
Precipitating Clouds

The macro- and microphysical properties of clouds can reflect their vertical physical structure and evolution and are important indications of the formation and development of precipitation. We used four-year merged CloudSat-CALIPSO-MODIS products to distinguish the macro- and microphysical properties of precipitating and non-precipitating clouds over central-eastern China during the warm season (May–September). Our results showed that the clouds were dominated by single- and double-layer forms with occurrence frequencies > 85%. Clouds with a low probability of precipitation (POP) were usually geometrically thin. The POP showed an increasing trend with increases in the cloud optical depth, liquid water path, and ice water path, reaching maxima of 50%, 60%, and 75%, respectively. However, as cloud effective radius (CER) increased, the POP changed from an increasing to a decreasing trend for a CER > 22 μm, in contrast with our perception that large particles fall more easily against updrafts, but this shift can be attributed to the transition of the cloud phase from mixed clouds to ice clouds. A high POP > 60% usually occurred in mixed clouds with vigorous ice-phase processes. There were clear differences in the microphysical properties of non-precipitating and precipitating clouds. In contrast with the vertical evolution of non-precipitating clouds with weaker reflectivity, precipitating clouds were present above 0 dBZ with a significant downward increase in reflectivity, suggesting inherent differences in cloud dynamical and microphysical processes. Our findings highlight the differences in the POP of warm and mixed clouds, suggesting that the low frequency of precipitation from water clouds should be the focus of future studies.

Design of a Shadowband Spectral Radiometer for the Retrieval of Thin Cloud Optical Depth, Liquid Water Path, and the Effective Radius

2011 ◽  
Vol 28 (11) ◽  
pp. 1458-1465 ◽  
Author(s):  
M. J. Bartholomew ◽  
R. M. Reynolds ◽  
A. M. Vogelmann ◽  
Q. Min ◽  
R. Edwards ◽  
...  
Keyword(s):  
Optical Depth ◽  
Liquid Water ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Optical Depth ◽  
Water Path ◽  
Cloud Properties ◽  
Radiative Intensity ◽  
Thin Cloud ◽  
Aerosol Properties

Abstract The design and operation of a Thin-Cloud Rotating Shadowband Radiometer (TCRSR) described here was used to measure the radiative intensity of the solar aureole and enable the simultaneous retrieval of cloud optical depth, drop effective radius, and liquid water path. The instrument consists of photodiode sensors positioned beneath two narrow metal bands that occult the sun by moving alternately from horizon to horizon. Measurements from the narrowband 415-nm channel were used to demonstrate a retrieval of the cloud properties of interest. With the proven operation of the relatively inexpensive TCRSR instrument, its usefulness for retrieving aerosol properties under cloud-free skies and for ship-based observations is discussed.

scholarly journals Joint cloud water path and rainwater path retrievals from airborne ORACLES observations

2021 ◽  
Vol 21 (7) ◽  
pp. 5513-5532
Author(s):  
Andrew M. Dzambo ◽  
Tristan L'Ecuyer ◽  
Kenneth Sinclair ◽  
Bastiaan van Diedenhoven ◽  
Siddhant Gupta ◽  
...  
Keyword(s):  
Optical Depth ◽  
Liquid Water ◽  
Cloud Water ◽  
Retrieval Algorithm ◽  
Liquid Water Path ◽  
Cloud Optical Depth ◽  
Water Path ◽  
Surface Precipitation ◽  
Uncertainty Estimates ◽  
Cloud Water Path

Abstract. This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ∼10 %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

scholarly journals The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004–2019

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
A. M. S. M. C. M. Aththanayake ◽  
Kamalanath Samarakoon ◽  
H. M. Arjuna Thilakarathna
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Southern Oscillation ◽  
Population Data ◽  
Enso Modoki ◽  
Cross Correlation Analysis ◽  
Teleconnection Indices ◽  
Weather Parameters ◽  
Time Lagged

Abstract Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI. Methods We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected. Results Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods. Conclusions Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

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