Meteorological Network Expansion Using Information Decay Concept

Husain, Tahir; Ukayli, M. A.; Khan, Hasin U.

doi:10.1175/1520-0426(1986)003<0027:mneuid>2.0.co;2

Cited by 6 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Identifying the optimal locations for stations for wildland fire applications has been of interest for many years (Fujioka 1986). More generally, there are many needs for improved selection of surface observing sites for a variety of weather and climate applications (Husain et al 1986;Vose and Menne 2004;Paimazumder and Molders 2009;National Research Council 2009). Siting new stations as well as maintaining existing ones requires consideration of a broad range of factors including access, security, obstructions, and the representativeness of the site compared to the surrounding area.…”

Section: Discussionmentioning

confidence: 99%

An Evaluation of the Distribution of Remote Automated Weather Stations (RAWS)

Horel

Dong

2010

Journal of Applied Meteorology and Climatology

View full text Add to dashboard Cite

This study estimates whether surface observations of temperature, moisture, and wind at some stations in the continental United States are less critical than others for specifying weather conditions in the vicinity of those stations. Two-dimensional variational analyses of temperature, relative humidity, and wind were created for selected midday hours during summer 2008. This set of 8925 control analyses was derived from 5-km-resolution background fields and Remote Automated Weather Station (RAWS) and National Weather Service (NWS) observations within roughly 4° × 4° latitude–longitude domains. Over 570 000 cross-validation experiments were completed to assess the impact of removing each RAWS and NWS station. The presence of observational assets within relatively close proximity to one another is relatively common. The sensitivity to removing temperature, relative humidity, or wind observations varies regionally and depends on the complexity of the surrounding terrain and the representativeness of the observations. Cost savings for the national RAWS program by removing a few stations may be possible. However, nearly all regions of the country remain undersampled, especially mountainous regions of the western United States frequently affected by wildfires.

show abstract

Section: Discussionmentioning

confidence: 99%

An Evaluation of the Distribution of Remote Automated Weather Stations (RAWS)

Horel

Dong

2010

Journal of Applied Meteorology and Climatology

View full text Add to dashboard Cite

show abstract

“…The net information term in the above equations is a function of distance from the station. The variation of the net information term with distance was correlated for a set of station pairs, and it was found that such a relationship can best be expressed by an exponential function as follows [Husain, Ukayli and Khan, 1986]: Y1 = 14 where y, is the net information ordinate at a distance d1 ( a) from the station 'i'; c is the net information ordinate at '14b' the station location; and b is the coefficient of expo-' nential decay curve which is determined as:…”

mentioning

confidence: 99%

HYDROLOGIC UNCERTAINTY MEASURE AND NETWORK DESIGN¹

Husain

1989

J American Water Resour Assoc

Self Cite

View full text Add to dashboard Cite

This paper presents a simple methodology, using the entropy concept, to estimate regional hydro logic uncertainty and information at both gaged and ungaged grids in a basin. The methodology described in this paper is applicable for (a) the selection of the optimum station from a dense network, using maximization of information transmission criteria, and (b) expansion of a network using data from an existing sparse network by means of the information interpolation concept and identification of the zones from minimum hydrologic information. The computation of single and joint entropy terms used in the above two cases depends upon single and multivariable probability density functions. In this paper, these terms are derived for the gamma distribution. The derived formulation for optimum hydrologic network design was tested using the data from a network of 29 rain gages on Sleeper River Experimental Watershed. For the purpose of network reduction, the watershed was divided into three subregions, and the optimum stations and their locations in each subregion were identified. To apply the network expansion methodology, only the network consisting of 13 stations was used, and feasible triangular elements were formed by joining the stations. Hydrologic information was calculated at various points on the line segments, and critical information zones were identified by plotting information contours. The entropy concept used in this paper, although derived for single and bivaviate gamma distribution, is general in type and can easily be modified for other distributions by a simple variable transformation criterion.

show abstract