Articles | Volume 8, issue 9
https://doi.org/10.5194/acp-8-2341-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-8-2341-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Discriminating raining from non-raining clouds at mid-latitudes using meteosat second generation daytime data
B. Thies
Laboratory of Climatology and Remote Sensing, University of Marburg, Germany
T. Nauss
Laboratory of Climatology and Remote Sensing, University of Marburg, Germany
J. Bendix
Laboratory of Climatology and Remote Sensing, University of Marburg, Germany
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41 citations as recorded by crossref.
- Using the Gradient Boosting Decision Tree to Improve the Delineation of Hourly Rain Areas during the Summer from Advanced Himawari Imager Data L. Ma et al. 10.1175/JHM-D-17-0109.1
- Improving the accuracy of rainfall rates from optical satellite sensors with machine learning — A random forests-based approach applied to MSG SEVIRI M. Kühnlein et al. 10.1016/j.rse.2013.10.026
- Using cloud water path and cloud top temperature for estimating convective and stratiform rainfall from SEVIRI daytime data M. Lazri & S. Ameur 10.1007/s12517-016-2610-8
- Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG M. Lazri et al. 10.1016/j.asr.2013.07.036
- Daytime precipitation identification scheme based on multiple cloud parameters retrieved from visible and infrared measurements X. Liu et al. 10.1007/s11430-014-4870-z
- Improvement of rainfall estimation from MSG data using Random Forests classification and regression F. Ouallouche et al. 10.1016/j.atmosres.2018.05.001
- Rainfall estimation from MSG images using fuzzy association rules B. Bouaita et al. 10.3233/JIFS-182786
- PECA-FY4A: Precipitation Estimation using Chromatographic Analysis methodology for full-disc multispectral observations from FengYun-4A/AGRI S. Zhu & Z. Ma 10.1016/j.rse.2022.113234
- Precipitation Estimates from MSG SEVIRI Daytime, Nighttime, and Twilight Data with Random Forests M. Kühnlein et al. 10.1175/JAMC-D-14-0082.1
- Pattern recognition filtering and bidimensional FFT-based detection of storms in meteorological radar images O. Raaf & A. Adane 10.1016/j.dsp.2012.04.008
- A New Data Fusion Neural Network Scheme for Rainfall Retrieval Using Passive Microwave and Visible/Infrared Satellite Data M. Sist et al. 10.3390/app11104686
- Precipitation process and rainfall intensity differentiation using Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager data B. Thies et al. 10.1029/2008JD010464
- Precipitation Clouds Delineation Scheme in Tropical Cyclones and Its Validation Using Precipitation and Cloud Parameter Datasets from TRMM F. Chen et al. 10.1175/JAMC-D-17-0157.1
- Satellite-Based Rainfall Retrieval: From Generalized Linear Models to Artificial Neural Networks L. Beusch et al. 10.3390/rs10060939
- Comparison of Macro- and Microphysical Properties in Precipitating and Non-Precipitating Clouds over Central-Eastern China during Warm Season X. Zheng et al. 10.3390/rs14010152
- A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data M. Sehad & S. Ameur 10.1016/j.asr.2019.11.018
- Novel WkNN-based technique to improve instantaneous rainfall estimation over the north of Algeria using the multispectral MSG SEVIRI imagery N. Bensafi et al. 10.1016/j.jastp.2018.12.004
- Using naive Bayes classifier for classification of convective rainfall intensities based on spectral characteristics retrieved from SEVIRI S. HAMEG et al. 10.1007/s12040-016-0717-7
- Artificial intelligence systems for rainy areas detection and convective cells' delineation for the south shore of Mediterranean Sea during day and nighttime using MSG satellite images M. Tebbi & B. Haddad 10.1016/j.atmosres.2016.04.013
- A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI M. Lazri & S. Ameur 10.1016/j.jastp.2016.07.015
- Satellite based remote sensing of weather and climate: recent achievements and future perspectives B. Thies & J. Bendix 10.1002/met.288
- Las angiospermas epífitas del estado de Veracruz, México: diversidad y distribución T. Krömer et al. 10.22201/ib.20078706e.2020.91.3415
- An Artificial Neural Network Approach to Multispectral Rainfall Estimation over Africa R. Chadwick & D. Grimes 10.1175/JHM-D-11-081.1
- Combining MWL and MSG SEVIRI Satellite Signals for Rainfall Detection and Estimation K. Kumah et al. 10.3390/atmos11090884
- Species richness and vertical distribution of ferns and lycophytes along an elevational gradient in Los Tuxtlas, Veracruz, Mexico A. Acebey et al. 10.1016/j.flora.2017.08.003
- Triple Collocation of Summer Precipitation Retrievals from SEVIRI over Europe with Gridded Rain Gauge and Weather Radar Data R. Roebeling et al. 10.1175/JHM-D-11-089.1
- Revealing the potential of spectral and textural predictor variables in a neural network-based rainfall retrieval technique H. Meyer et al. 10.1080/2150704X.2017.1312026
- Optimization of One versus All-SVM using AdaBoost algorithm for rainfall classification and estimation from multispectral MSG data A. Belghit et al. 10.1016/j.asr.2022.08.075
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