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Alfred J. Kalyanapu
,
A. K. M. Azad Hossain
,
Jinwoo Kim
,
Wondmagegn Yigzaw
,
Faisal Hossain
, and
C. K. Shum

objective, a two-dimensional numerical flood model, the Flood in Two Dimensions–Graphics Processing Unit (Flood2D-GPU), is calibrated and used to simulate flood depths and velocities for various PMF simulations. These flood model outputs are compiled into quantifiable downstream flood hazard potential to population using existing flood depth–velocity hazard relationships. 2. Case study 2.1. Folsom Dam and American River watershed The study uses Folsom Dam and reservoir, which is located in the ARW near

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Shane D. Mayor
,
Jennifer P. Lowe
, and
Christopher F. Mauzey

–180 ms to complete. The GPU version of BVM using CUDA C completed filtering in ~90 ms, making it almost twice as fast as the CPU version. 2) Polar-to-rectangular projection The projection of the scan data onto a rectangular grid begins by converting the grid’s coordinates from a Cartesian system to a polar system with its origin at the location of the lidar. The polar coordinates are then used to compute interpolants of the scan data using bilinear interpolation. The backscatter samples in a scan are

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Christoph Schär
,
Oliver Fuhrer
,
Andrea Arteaga
,
Nikolina Ban
,
Christophe Charpilloz
,
Salvatore Di Girolamo
,
Laureline Hentgen
,
Torsten Hoefler
,
Xavier Lapillonne
,
David Leutwyler
,
Katherine Osterried
,
Davide Panosetti
,
Stefan Rüdisühli
,
Linda Schlemmer
,
Thomas C. Schulthess
,
Michael Sprenger
,
Stefano Ubbiali
, and
Heini Wernli

of the NIM weather model on CPU, GPU, and MIC processors . Bull. Amer. Meteor. Soc. , 98 , 2201 – 2213 , https://doi.org/10.1175/BAMS-D-15-00278.1 . Gregory , J. M. , R. Stouffer , S. Raper , P. Stott , and N. Rayner , 2002 : An observationally based estimate of the climate sensitivity . J. Climate , 15 , 3117 – 3121 , https://doi.org/10.1175/1520-0442(2002)015<3117:AOBEOT>2.0.CO;2 . Gross , M. , and Coauthors , 2018 : Physics–dynamics coupling in weather, climate, and

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Ibrahim Demir
,
Helen Conover
,
Witold F. Krajewski
,
Bong-Chul Seo
,
Radosław Goska
,
Yubin He
,
Michael F. McEniry
,
Sara J. Graves
, and
Walter Petersen

which instruments are working nominally. Figure 1 shows the portal home screen, including the instrument status report list (right center). Color blocks around the instrument names indicate that the 2D video disdrometer and X-band polarimetric radar 2 (XPOL-2) have questionable statuses, while all other instruments are shown to be operating nominally. A red status code would indicate a completely inoperable instrument. Instrument teams provided status details in the full report, which can be

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Matthias Steiner

atmospheric process representation, increase the efficiency of computer code, and/or utilize emerging computational resources such as graphical processing units (GPUs) to decrease computational time for finescale urban predictions. To support eVTOL flight operations in urban environments, it is necessary to provide timely and actionable weather guidance ( Fig. 2 ). This may require a reduction of model complexity (and thus computational time) to the minimum needed to capture a given weather situation. In

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David Leutwyler
,
Adel Imamovic
, and
Christoph Schär

. Segal , R. C. Kessler , and R. A. Pielke , 1984 : Evaluation of soil moisture effects on the generation and modification of mesoscale circulations . Mon. Wea. Rev. , 112 , 2281 – 2292 , https://doi.org/10.1175/1520-0493(1984)112<2281:EOSMEO>2.0.CO;2 . 10.1175/1520-0493(1984)112<2281:EOSMEO>2.0.CO;2 Owens , J. , M. Houston , D. Luebke , S. Green , J. Stone , and J. Phillips , 2008 : GPU computing . Proc. IEEE , 96 , 879 – 899 , https://doi.org/10.1109/JPROC.2008

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Gökhan Sever
and
Yuh-Lang Lin

favorable conditions for heavy precipitation. However, the dynamics for this extremely large Froude number flow is still not well explored. Based on idealized simulations using the Advanced Regional Prediction System (ARPS) ( Xue et al. 2000 ), CL00 identified three moist flow regimes for a conditionally unstable flow over an idealized two-dimensional (2D) mesoscale mountain: (i) an upstream-propagating convective precipitation system, (ii) a quasi-stationary convective system over the mountain, and

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Charlotte Cambier van Nooten
,
Koert Schreurs
,
Jasper S. Wijnands
,
Hidde Leijnse
,
Maurice Schmeits
,
Kirien Whan
, and
Yuliya Shapovalova

model to use radar data from multiple resolutions ( Choi and Kim 2021 ; Ravuri et al. 2021 ) and is based on residual blocks and spectrally normalized convolutional 2D layers (SNConv2D) ( Miyato et al. 2018 ). Subsequently, the sampler generates several predictions (i.e., future radar images). The sampler consists of multiple modules, including a latent conditioning stack and convolutional gated recurrent unit (ConvGRU) layers. Two discriminator models check whether generated images are realistic

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Akshara Kaginalkar
,
Sachin D. Ghude
,
U. C. Mohanty
,
Pradeep Mujumdar
,
Sudheer Bhakare
,
Hemant Darbari
,
Arun K. Dwivedi
,
Pallavi Gavali
,
Srujan Gavhale
,
Sahidul Islam
,
Gouri Kadam
,
Sumita Kedia
,
Manoj Khare
,
Neelesh Kharkar
,
Santosh H. Kulkarni
,
Sri Sai Meher
,
A. K. Nath
,
Mohamed Niyaz
,
Sagar Pokale
,
Vineeth Krishnan Valappil
,
Sreyashi Debnath
,
Chinmay Jena
,
Raghu Nadimpalli
,
Madhusmita Swain
,
Saimy Davis
,
Shubha Avinash
,
C. Kishtawal
,
Prashant Gargava
,
S. D. Attri
, and
Dev Niyogi

and case studies (pollution mitigation, flood mapping, extreme events); (iv) design of interactive DSS with big data, 3D visualization, GIS, and end-user data dissemination and web and mobile app services; (v) scientific cloud services for urban environment IaaS, DaaS, MaaS, and SaaS with workflows; and (vi) capacity building (training and outreach). The development mechanism of UES2S has an agile research approach, building on existing knowledge, data, and methods in a participative manner

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Xi Liu
,
Yu Zheng
,
Xiaoran Zhuang
,
Yaqiang Wang
,
Xin Li
,
Zhang Bei
, and
Wenhua Zhang

RTX A6000 GPUs. a. The PredRNNv2 model for rainfall prediction The main schematic illustration of our model architecture is shown in Fig. 2 . Here, we design a PredRNNv2 model with four spatiotemporal long short-term memory (ST-LSTM) layers, which are typically used in spatiotemporal predictions (e.g., Wu et al. 2022 ; Wang et al. 2023 ). This four-layer structure can strike a balance between prediction quality and training efficiency ( Wang et al. 2023 ). Each ST-LSTM layer has 128

Open access