Diabatic initialization of cloud-resolving forecast models such as MM5, RAMS, ARPS, and WRF allows these models to prognose the future of precipitating cloud systems such as snowstorms and thunderstorms that are present at the initial time. This is a solution to one of the most long-standing problems in NWP: the 1to 3-h spin-up of cloud systems caused by the use of traditional dry initialization.

Abstract The Chinese Meteorology Administration chemistry model Unified Atmospheric Chemistry Environment (CUACE) is online integrated into the mesoscale operational numerical weather prediction (NWP) (GRAPES_Meso5.1) and aerosol‐cloud‐radiation interaction achieved to establish first version (V1) of chemistry‐weather (CW) interacted GRAPES‐Meso5.1/CUACE CW V1. most polluted winter 2016–2017 se...

Fengyun-3E (FY-3E), the world’s first early-morning-orbit meteorological satellite for civil use, was launched successfully at Jiuquan Satellite Launch Center on 5 July 2021. The FY-3E will fill vacancy of global observation, working together with FY-3C and FY-3D satellites to achieve data coverage early morning, afternoon orbits. combination these three provide numerical weather prediction (NW...

Deep learning-based super-resolution (SR) methods have been widely used in natural images; however, their applications satellite-derived sea surface temperature (SST) not yet fully discussed. Hence, it is necessary to analyze the validity of deep SR SST reconstruction. In this study, an model, including multiscale feature extraction and multireceptive field mapping, was first proposed. Then, pr...

As the wind power penetration increases, short-term prediction accuracy of is great importance for safe and cost-effective operation grid in which integrated. Traditional farm uses numerical weather (NWP) information as an important input but does not consider correlation characteristics NWP from different farms. In this study, a convolutional neural network–long memory based model clusters pro...

Meteorology satellite visible-light images are critical for meteorologists. However, there no channels data at night, so we propose a method based on deep learning to create synthetic during night. Specifically, produce realistic-looking products, trained generative adversarial network (GAN) model. The model can generate from corresponding infrared (IR) and numerical weather prediction (NWP) pr...

As the spatial, temporal and spectral resolution of visible infrared radiance observations from space has improved, their utility for estimating atmospheric motion, and, in particular, benefit to Numerical Weather Prediction (NWP) increased. The these data also been aided by increased computer power, improved NWP models use improving assimilation techniques.
 
 This review provides a ...

Abstract This study quantifies the contributions of tropical sea surface temperature (SST) variations during boreal warm season to interannual-to-decadal variability in cyclone genesis frequency (TCGF) over Northern Hemisphere ocean basins. The first seven leading modes SST are found affect basinwide TCGF one or more basins, and related canonical El Niño–Southern Oscillation (ENSO), global warm...

A model intercomparison between two atmospheric models, the non–hydrostatic Lokal Modell (LM) and the hydrostatic HIgh Resolution Limited Area Model (HIRLAM) is carried out for a one-week period, including a case of cyclogeneis leading to heavy precipitation over Northern Italy. The two models, very different in terms of data-assimilation and numerics, provide different results in terms of fore...

Abstract We report about a new third-party observation, namely, wind measurements derived from hot-air balloon (HAB) tracks. first compare the HAB winds with meteorological tower and radio acoustic profiler, both situated at topographically flat observatory near Cabauw, Netherlands. To explore potential of this type observation in other topographies, we present an intriguing flight Austria spec...