numerical experiment on the prediction of the northeast (winter) monsoon in Southeast Asia by Jones, Robert William

Cover of: numerical experiment on the prediction of the northeast (winter) monsoon in Southeast Asia | Jones, Robert William

Published by U.S. National Oceanic and Atmospheric Administration, Environmental Research Laboratories, for sale by the Supt. of Docs., U.S. Govt. Print. Off. in Boulder, Colo, Washington .

Written in English

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Subjects:

  • Numerical weather forecasting,
  • Meteorology -- Mathematical models,
  • Monsoons -- Southeast Asia

Edition Notes

Book details

StatementRobert W. Jones
SeriesNOAA technical report ERL -- 272, NOAA technical report ERL -- 3
The Physical Object
Paginationvii, 56 p. :
Number of Pages56
ID Numbers
Open LibraryOL15474487M

Download numerical experiment on the prediction of the northeast (winter) monsoon in Southeast Asia

Numerical experiment on the prediction of the northeast (winter) monsoon in Southeast Asia. Boulder, Colo.: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories ; Washington: For sale by the Supt.

of Docs., U.S. Govt. Print. Off., (OCoLC) Material Type. The integrated system is applied to the prediction of northeast Asian dust storms, from the perspective of dust emission and dust concentration of various particle size groups.

Two successive but different dust storm events that occurred on 6–7 and 9–10 April are studied and the predictions are compared qualitatively with Cited by: 1. Introduction [2] We are concerned with the quantitative prediction of dust storms in real time, with a focus on northeast Asia.

There are two motivations for this work: (1) The arid and semiarid regions of northeast Asia are major sources of mineral dust which plays Cited by: [1] This study is concerned with the quantitative prediction of dust storms in real time.

An integrated wind erosion modeling system is used for 24‐, 48‐, and 72‐hour forecasts of northeast Asian dust events for March and April Cited by:   Another candidate Shreya Goswami said that the questions on numerical ability were difficult to solve, and the general awareness sections comprised of uncommon questions.

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DRIVE THE MULTI-COLUMN 1D ENSEMBLE CLOUD-SEEDING MODEL. Ling Jin1,2*, Fanyou Kong2, Hengchi Lei1, Zhaoxia Hu1. 1Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China 2. Center for Analysis and Prediction of Storms, University of Oklahoma, Norman.

A fortunate opportunity for comparison arose from a recent experiment with a numerical model (ECHAM) conducted at the International Institute for Climate Prediction, Columbia University.

This used global SST information through February to predict the March–June rainfall at three grid points in the Nordeste. Energy Procedia 17 () – Published by Elsevier Ltd.

Selection and/or peer-review under responsibility of Hainan University. doi: / International Conference on Future Electrical Power and Energy Systems Numerical and Experiment Research for Soft Coal under Condition of Blending Lignite TaiLv a, QianWang a.

Numerical Methods in Weather Prediction focuses on the numerical methods for solving problems of weather prediction and explains the aspect of the general circulation of the atmosphere.

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This book tells the story of Richardson’s trial forecast, and the fulfilment of his. Abstract Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the U.

The forecast period (t = 0 to t = 24 h) represents a numerical prediction in the operational sense, except that the lateral boundary conditions reflect available observations.

All DI techniques in this study are applied during the h period prior to the t = 0 h start of the forecast. Numerical model prediction studies that heretofore have been conducted over Nordeste have either been performed in a psuedoforecast mode [where observed SST is prescribed to the atmospheric general circulation model (AGCM)] or in tiertype predictions where the AGCM is forced with forecast SST derived from an independent source.

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During September and Februarythe NR/V Alliance extensively sampled the waters of the Sea of Marmara within the framework of the Turkish Straits System (TSS) experiment coordinated by the NATO Undersea Research Centre. The observational effort provided an opportunity to set up realistic numerical experiments for modeling the observed variability of the Marmara Sea.

Books. Dynamics of The Tropical Atmosphere and Oceans wind speed profiles that revealed a peak wind speed at hPa in the northwest quadrant and at hPa in the northeast quadrant. Two experiments were then run for 54 hr using the Globe/Regional Assimilation and Prediction System model, one assimilating the dropsonde data (DROP) and one.

AN EXPERIMENT IN NUMERICAL PREDICTION IN EQUATORIAL LATITUDES T. Krishnamurti* Department of Meteorology and Oceanography Naval Postgraduate School Monterey, California Contract No: Project No.

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Earthquake prediction is a branch of the science of seismology concerned with the specification of the time, location, and magnitude of future earthquakes within stated limits, and particularly "the determination of parameters for the next strong earthquake to occur in a region.

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In summerabnormally high-temperature events and associated low soil moisture conditions were observed in Northeast Eurasia. In this study, two regional climate model experiments, one with and the other without soil moisture–atmosphere interaction, were conducted to investigate the role of soil moisture in surface air temperature and precipitation in Northeast Eurasia utilizing the.

In this study, a volcanic ash tracking model called “PUFF” is applied to the actual eruption of Usu volcano on 31 March in order to infer the movement of airborne ash clouds for aviation safety. The PUFF model was developed and operated by the Alaska Volcano Observatory since the eruption of Redoubt volcano in The performance of the PUFF model is examined in this study .This open access book focuses on investigating predicting precursor information and key points of rockburst in mining engineering through laboratory experiment, theoretical analysis, numerical simulation and case studies.

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