PPT-Relationships Between Deep Convection and Tropospheric Layers Using Polarimetric Radio

2 nd PAZ Polarimetric Radio Occultations User Workshop Terence Kubar 21 Manuel de la Torre Ju rez 1 Jonas Katona 1 F Joseph Turk 1 Ramon Padull s 34   1 Jet Propulsion Laboratory California Institute of Technology Pasadena CA. Naiyan. Wang. Outline. Non-NN Approaches. Deep Convex Net. Extreme Learning Machine. PCAnet. Deep Fisher Net (Already . presented before). Discussion. Deep convex net. Each module is a two- layer convex network.. atmospheric convection. Brian Mapes. Rosenstiel School of Marine and Atmospheric Sciences, U. of Miami. with. Zhiming Kuang, Harvard University. Physical importance of convection. v. ertical flux of . On Monday and Tuesday…. We found the density of liquids and rocks. . We learned that denser materials sink, and lighter materials float.. We learned that granite is lighter than basalt and that iron is denser than both.. boundary . layer and . orographic. circulation . with . locally-triggered deep convection around the Santa Catalina Mountains in Arizona. Bart Geerts . (geerts@uwyo.edu) . . J. Robert A. Houze, Jr.. University of Washington. with: K. L. Rasmussen, M. D. Zuluaga, and S. R. Brodzik. European Geosciences Union General Assembly, Vienna, Austria 17 April 2015 . The TRMM Satellite. Part 2 – Modes of Isolated Organization. AOS 453 – Spring 2014. 4/3/. 2014. Structure Of DMC Lectures This Week. Tuesday. DMC (Convective/Convection) Initiation. Chapter 7 in MR09. Isolated DMC Organization (Part 1). Robert A. Houze, Jr.. University of Washington. with: K. L. Rasmussen, M. D. Zuluaga, and S. R. Brodzik. Presented at:. AGU Fall Meeting, San Francisco, 18 December 2015 . The TRMM Satellite. 1997-2014. deep, moist convection. Bogdan Antonescu. University of Manchester. (some slides courtesy of C. . Doswell. ). Mesoscale. Ingredients for deep, moist convection. Instability. . – conditional instability: (lapse rate) needed to develop . of . Jyotirvidya Parisanstha, Pune . India. by . S.Gurjar. Jyotirvidya. . Parisanstha. (JVP) . , Pune India Oldest association of Amateur Astronomers of India. Established in 1944. Presently active in Serious Astronomy observations. effects of terrain on . precipitation. The wind began to blow steadily out of the west and pour the water of the distant seas on the dark heads of the hills . … . J.R.R. Tolkien, The Lord of the Rings. 1. Outline. Introduction. Scope . Weather Radar. Polarimetric Weather Radar . Operation. Case Study. POLDIRAD. Analysis: Benefits of Polarimetric Weather Radar. Rain Rate estimates. Errors. Conclusion. in vivo. measurements. Angelo Pierangelo. 1. Jérémy . Vizet. 1. , . Jean . Rehbinder. 1. , . Stanislas . Deby. 1. , . Stéphane . Roussel. 1. , . Tatiana . Novikova. 1. , . Ranya. Soufan. 2. , . Catherine . Topics: 1. st. lecture wrap-up, difficulty training deep networks,. image classification problem, using convolutions,. tricks to train deep networks . . Resources: http://www.cs.utah.edu/~rajeev/cs7960/notes/ . networks with many layers . (vs. shallow nets with just a couple of layers). Multiple layers work to build an improved feature space. First layer learns 1. st. order features (e.g. edges…). 2. nd.