Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges

By Juanzhen Sun, Ming Xue, James W. Wilson, I. Zawadzki, Susan P. Ballard, Jeanette onvlee-hooiMeyer, P. Joe, D. Barker, Ping-Wah Li, B. Golding and 2 more. 2014

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting (2015, methodology): “Existing methods for precipitation nowcasting can roughly be categorized into two classes [22], namely, NWP based methods and radar echo 1 extrapolation based methods.”
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model (2017, background): “In addition to the inherent complexities of the atmosphere and relevant dynamical processes, the ever-growing need for real-time, large-scale, and fine-grained precipitation nowcasting poses extra challenges to the meteorological community and has aroused research interest in the machine learning co”
On the interaction of observation and prior error correlations in data assimilation (2018, unknown): “Therefore, accounting for OECs correctly could allow for denser observations to be assimilated, which could be important for high-resolution weather forecasting (Browne et al., 2014; Sun et al., 2014).”
Convection‐permitting models: a step‐change in rainfall forecasting (2016, methodology): “An experimental 1.5 km ‘Nowcasting Demonstration Project’ (NDP) was run during 2012–2013 over the southern half of the UK using hourly cycling, 4D-Variational (4D-Var) (Golding et al., 2014; Sun et al., 2014; Ballard et al., 2015) and UKV boundary conditions.”