Results 161 to 170 of about 70,613 (293)

The characteristics of squall lines in the Southeast Asia region

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Squall lines over the Maritime Continent were analysed using 20 years of IMERG GPM data and classified into four regional clusters. Significant regional differences were found in their size, intensity, lifespan, and propagation. Nighttime squall lines are primarily driven by the convergence of opposing offshore flows and the convergence of monsoonal ...
Jeong‐Yik Diong, Prince Xavier, Muhammad Firdaus Ammar Abdullah, Juliane Schwendike   +3 more
wiley   +1 more source

HR-Mamba: Building Footprint Segmentation with Geometry-Driven Boundary Regularization. [PDF]

Sensors (Basel)
Su B, Yin D, Yi P, Wu W, Liu J, Yang F, Mu H, Xiong J.   +7 more
europepmc   +1 more source

Preprocessing of Meteorological Data for Training an Artificial Intelligence Model

Information and control systems at railway transport
Прогнозування метеоумов за допомогою сучасних моделей штучного інтелекту потребує попередьої обробки великої кількості даних різних типів. Перед використанням метеоданих для навчання моделей, метеодані мають бути зібрані, об’єднані та структуровані. У статті розглянута підготовка метеоданих для подальшого використання при навчанні графових нейронних ...
openaire   +1 more source

Parameter investigation for urban surface‐energy balance: A large‐eddy simulation study

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Large eddy simulation modelling is used to investigate the variation in surface‐energy balance (SEB) across an ensemble of morphometrically identical urban geometries. The geometries have the same plan‐area fraction, vegetated fraction, and frontal‐area index, but are unique in terms of building and green‐space layout.
Christopher E. Wilson, Jonathan K. P. Shonk, Sylvia I. Bohnenstengel, Athanasios Paschalis, Maarten van Reeuwijk   +4 more
wiley   +1 more source

Trends in rainfall and temperature extremes during 1954-2019 in Addis Ababa, Ethiopia

Journal of Agrometeorology
ELIAS FISEHA MEKONNEN, MUHAMMED ABERA ASSEFA, AJEBUSH GOCHAW AYELE   +2 more
doaj   +1 more source

Assimilation of machine‐learning‐predicted nitrate to improve the quality of phytoplankton forecasting in the shelf‐sea environment

Quarterly Journal of the Royal Meteorological Society, EarlyView.
This article demonstrates that assimilating machine‐learning‐derived surface nitrate can improve five‐day phytoplankton forecast substantially within the Met Office operational system for the Northwest European Shelf. We explain the reasons behind this improvement and propose that an online system where machine learning and data assimilation are cycled
Deep S. Banerjee, Jozef Skákala, David Ford   +2 more
wiley   +1 more source

Precipitation nowcasting with radar data for evaluating multiple horizons using U-Net-based algorithm in Eastern Amazon. [PDF]

PLoS One
Rocha R, Ferreira D, Oliveira E, Arruda H, Viademonte S, Paes AP, Jesus E, Costa C, Franco V, Saraiva I, Tedeschi R, Nogueira A, Alves R, Carvalho E.   +13 more
europepmc   +1 more source

Polar‐low track prediction using machine‐learning methods

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang, Rune Grand Graversen, Filippo Maria Bianchi, Jiping Liu, Ruibo Lei   +4 more
wiley   +1 more source

Using machine learning algorithms to study the relationship between meteorological conditions and air quality parameters. [PDF]

Sci Rep
Tawabini B.
europepmc   +1 more source

NowPrecip 2: Precipitation nowcasting in the complex terrain of Switzerland. Part I: Methods

Quarterly Journal of the Royal Meteorological Society, EarlyView.
In this work we present the methods of the areal precipitation nowcasting system NowPrecip version 2. In this version a new methodology is introduced, which, although it shares philosophy and techniques with the original methodology of NowPrecip version 1, can be considered as distinct from that.
I. V. Sideris, A. Ntoumos, A. Berne, A. Hering, P. Juda, M. Boscacci, L. Clementi, U. Germann   +7 more
wiley   +1 more source