Articles | Volume 11, issue 5
https://doi.org/10.5194/amt-11-3177-2018
https://doi.org/10.5194/amt-11-3177-2018
Research article
 | 
01 Jun 2018
Research article |  | 01 Jun 2018

Neural network cloud top pressure and height for MODIS

Nina Håkansson, Claudia Adok, Anke Thoss, Ronald Scheirer, and Sara Hörnquist

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Cited articles

Ackerman, S., Menzel, P., and Frey, R.: MODIS Atmosphere L2 Cloud Product (06_L2), https://doi.org/10.5067/MODIS/MYD06_L2.006, 2015. a, b
Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E., Ackerman, S. A., Heidinger, A. K., and Yang, P.: MODIS Cloud-Top Property Refinements for Collection 6, J. Appl. Meteorol. Clim., 51, 1145–1163, https://doi.org/10.1175/JAMC-D-11-0203.1, 2012. a, b, c
Bickel, D. R.: Robust Estimators of the Mode and Skewness of Continuous Data, Comput. Stat. Data Anal., 39, 153–163, https://doi.org/10.1016/S0167-9473(01)00057-3, 2002. a
Cotter, A., Shamir, O., Srebro, N., and Sridharan, K.: Better Mini-Batch Algorithms via Accelerated Gradient Methods, in: Advances in Neural Information Processing Systems 24, edited by: Shawe-Taylor, J., Zemel, R. S., Bartlett, P. L., Pereira, F., and Weinberger, K. Q., 1647–1655, Curran Associates, Inc., available at: http://papers.nips.cc/paper/4432-better-mini-batch-algorithms-via-accelerated-gradient-methods.pdf, 2011. a
Derrien, M., Lavanant, L., and Le Gleau, H.: Retrieval of the cloud top temperature of semi-transparent clouds with AVHRR, in: Proceedings of the IRS'88, 199–202, Deepak Publ., Hampton, Lille, France, 1988. a
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Short summary
In this paper a new algorithm for cloud top height retrieval from imager instruments like MODIS is presented. It uses artificial neural networks and reduces the mean absolute error by 32 % compared to two other operational cloud height algorithms. This means that improved cloud height retrieval for nowcasting, as input to models and in cloud climatologies is possible.
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