A Strategic plan for a coastal forecast system.

"June 1993."

Die Wetterpropheten im Thierreich, oder, Musterung aller derjenigen Thiere, die eine Witterungsveränderung anzeigen oder anzeigen sollen /

Includes bibliographical references and index.

The sunspot.

Editor: J.S. Ricard.

Some statistical and mathematical approaches to meteorology : final report /

Final Report under Contract No.

Interpreting NWS radar displays as seen on television.

Mode of access: Internet.

Forecast Systems Laboratory, Boulder, Colorado.

Mode of access: Internet.

Severe storms [microform] : hearing before the Subcommittee on Natural Resources, Agriculture Research, and Environment of the Committee on Science and Technology, U.S. House of Representatives, Ninety-seventh Congress, first session, October 6, 1981.

"No. 177."

Mémoires composés au sujet d'une correspondance météorologique, ayant pour but de parvenir à prédire le temps beaucoup à l'avance sur un point donné de la terre /

"Premier mémoire."

Meeting of directors of meteorological services of western hemisphere countries : hearings before the Committee on Foreign Affairs, House of Representatives, Seventy-seventh Congress, first session, on R.J. res. 191, a joint resolution to authorize the President of the United States to invite the governments of the countries of the western hemisphere to participate in a meeting of the national directors of the meteorological services of those countries, to be held in the United States as soon as practicable in 1941 or 1942 : to invite regional commissions III and IV of the International Meteorological Organization to meet concurrently therewith, and to authorize an appropriation for the expenses of organizing and holding such meetings ..

Mode of access: Internet.

Program development plan : automation of field operations and services /

On spine: AFOS program development plan.

Climate diagnostics bulletin /

Mode of access: Internet.

Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

Seasonal changes of heat and moisture fluxes from the Caspian Sea surface and its effect on synoptic systems with heavy rainfalls in southern shores of the sea during 2005-2010

Caspian Sea with its unique characteristics is a significant source to supply required heat and moisture for passing weather systems over the north of Iran. Investigation of heat and moisture fluxes in the region and their effects on these systems that could lead to floods and major financial and human losses is essential in weather forecasting. Nowadays by improvement of numerical weather and climate prediction models and the increasing need to more accurate forecasting of heavy rainfall, the evaluation and verification of these models has been become much more important. In this study we have used the WRF model as a research-practical one with many valuable characteristics and flexibilities. In this research, the effects of heat and moisture fluxes of Caspian Sea on the synoptic and dynamical structure of 20 selective systems associated with heavy rainfall in the southern shores of Caspian Sea are investigated. These systems are selected based on the rainfall data gathered by three local stations named: Rasht, Babolsar and Gorgan in different seasons during a five-year period (2005-2010) with maximum amount of rainfall through the 24 hours of a day. In addition to synoptic analyses of these systems, the WRF model with and without surface flues was run using the two nested grids with the horizontal resolutions of 12 and 36 km. The results show that there are good consistencies between the predicted distribution of rainfall field, time of beginning and end of rainfall by the model and the observations. But the model underestimates the amounts of rainfall and the maximum difference with the observation is about 69%. Also, no significant changes in the results are seen when the domain and the resolution of computations are changed. The other noticeable point is that the systems are severely weakened by removing heat and moisture fluxes and thereby the amounts of large scale rainfall are decreased up to 77% and the convective rainfalls tend to zero.