Search Results

You are looking at 1 - 10 of 45,057 items for :

  • Data processing/distribution x
  • Refine by Access: All Content x
Clear All
Yuan-Zheng Lu
,
Xian-Rong Cen
,
Shuang-Xi Guo
,
Ling Qu
,
Peng-Qi Huang
,
Xiao-Dong Shang
, and
Sheng-Qi Zhou

(100–500 m) and deep (500–1500 m) layers In the upper layer (100–500 m), lateral distributions of turbulent properties, the buoyancy frequency N , dissipation rate ε , and diffusivity K z , are shown in Figs. 5a–c , respectively, where the geometric averages were taken vertically. To clearly demonstrate the global pattern, the data were further averaged into 1° × 1° bins, as respectively shown in Figs. 5d–f . The same process was applied to the deep layer (500–1500 m), as shown in Fig. 6

Full access
Chunying Liu
,
Eric Freeman
,
Elizabeth C. Kent
,
David I. Berry
,
Steven J. Worley
,
Shawn R. Smith
,
Boyin Huang
,
Huai-min Zhang
,
Thomas Cram
,
Zaihua Ji
,
Mathieu Ouellet
,
Isabelle Gaboury
,
Frank Oliva
,
Axel Andersson
,
William E. Angel
,
Angela R. Sallis
, and
Adedoja Adeyeye

have moved, or are currently in the process of moving, to the BUFR format in transmitting NRT marine observational data. BUFR is designed for efficient exchange and storage of meteorological and oceanographic data. BUFR’s table-driven structure provides greater flexibility compared to the TAC format; BUFR can easily be extended and is self-describing. These table-driven and self-descriptive features in BUFR allow for greater reporting precision and more metadata (e.g., Pelletier 2008 ). In TAC

Open access
Duncan C. Wheeler
and
Sarah N. Giddings

1. Introduction In recent years, acoustic Doppler velocimeters (ADVs) have proven valuable tools for measuring turbulent statistics in various environments. With their fast sample rates, relatively accurate measurements, and ability to measure in shallow water, ADVs have led to improvements in our understanding of surf zone and shallow estuarine turbulence (e.g., Feddersen 2012 ; Jones and Monismith 2008 ). Key to this success has been the development of reliable data processing

Restricted access
Christopher Daly
,
Matthew K. Doggett
,
Joseph I. Smith
,
Keith V. Olson
,
Michael D. Halbleib
,
Zlatko Dimcovic
,
Dylan Keon
,
Rebecca A. Loiselle
,
Ben Steinberg
,
Adam D. Ryan
,
Cherri M. Pancake
, and
Eileen M. Kaspar

section 3 for details). We follow four steps when adding a new network or data source: 1) set up data delivery methods with the provider, 2) obtain historical data, 3) write ingest scripts to process data and insert into a database, and 4) operationalize data delivery and ingest systems. Developing and maintaining station ingest systems for so many disparate data sources requires significant ongoing resources. Each data source has its own data access protocols, data formats, units, and metadata

Open access
Maruti K. Mudunuru
,
James Ang
,
Mahantesh Halappanavar
,
Simon D. Hammond
,
Maya B. Gokhale
,
James C. Hoe
,
Tushar Krishna
,
Sarat Sreepathi
,
Matthew R. Norman
,
Ivy B. Peng
, and
Philip W. Jones

a previously unimaginable quantity and diversity of data, but the computing and network load for processing, transmitting, and subsequent storage of this volume will be orders of magnitude higher than any system available today. Data movement costs in terms of energy and latency motivate the interest in the federation and distribution of computing across the AI4ESP scientific ecosystem. AI/ML technologies could help reduce such volumes by identifying patterns and anomalies and summarizing

Open access
Imke Durre
,
Anthony Arguez
,
Carl J. Schreck III
,
Michael F. Squires
, and
Russell S. Vose

distributions of precipitation days to corresponding estimated distributions at the respective nearest grid points. Additionally, a qualitative visual comparison of the masked Prcp fields during a few significant storms to the spatial patterns indicated by the input data, radar observations, and PRISM. Table 3 Steps involved in the process of masking an initially interpolated field of Prcp values in an effort to remove spurious nonzero values introduced by the smoothing effect of TPSS. The

Free access
Bernard Campistron
,
Gilbert Despaux
, and
Jean-Pierre Lacaux

536 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME4A Microcomputer Data-Acquisition System for Real-Time Processing of Raindrop Size Distribution Measured with the RD69 Distrometer BERNARD CAMPISTRON, GILBERT DESPAUX AND JEAN-PIERRE LACAUXLaboratoire d~t~rologie, Centre de Recherches Atmosphdriques (O.P.M.T.), Campistrous 65300, Lannemezan, France17 September 1986 and 9 January 1987 The disdrometer is an instrument

Full access
Ryan M. May
,
Kevin H. Goebbert
,
Jonathan E. Thielen
,
John R. Leeman
,
M. Drew Camron
,
Zachary Bruick
,
Eric C. Bruning
,
Russell P. Manser
,
Sean C. Arms
, and
Patrick T. Marsh

Meteorology and atmospheric science have long had a strong reliance on data visualization and especially map analysis. From the mid 1980s through the early 2000s, this meant widespread use of software tools like Read Interpolate Plot version 4 (RIP4; Stoelinga 2018 ), NCAR Command Language (NCL; NCAR 2019 ), General Meteorology Package (GEMPAK; Unidata 2019 ), and Grid Analysis and Display System (GrADS; George Mason University 2018 ). Tools like these achieved favor because they promoted

Full access
Guoqiang Tang
,
Martyn P. Clark
, and
Simon Michael Papalexiou

distributions. For precipitation, one more parameter (i.e., the probability of precipitation) is needed to determine if an event occurs. These parameters can be obtained from meteorological estimates and estimation uncertainties, which are produced by optimally merging station and reanalysis data. The detailed steps are introduced as follows. Deterministic estimation. S tation-based estimates . Locally weighted linear regression is used as a spatial interpolation method: the topographic

Full access
Taylor A. Gowan
,
John D. Horel
,
Alexander A. Jacques
, and
Adair Kovac

large amount of storage and compute power are needed to efficiently process thousands of GRIB2 data files. To illustrate accessing large amounts of data from the HRRR-Zarr store, we generated empirical cumulative distributions for selected atmospheric parameters using a single high-performance compute node. This use case motivated the later analysis in section 2d to evaluate the additional speedup that might result using an AWS dask cluster. To assess the anomalous nature of the downslope wind

Open access