Current Search: Meteorological data (x)
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- Title
- Energy balance in a shallow seagrass flat for winter conditions.
- Creator
- Smith, Ned P.
- Date Issued
- 1981
- PURL
- http://purl.flvc.org/FCLA/DT/3343792
- Subject Headings
- Limnology, Meteorological data, Hydrography
- Format
- Document (PDF)
- Title
- ESTIMATING MISSING PRECIPITATION RECORDS USING TREE-BASED APPROACHES.
- Creator
- Nguyen, Thu, Teegavarapu, Ramesh S. V., Florida Atlantic University, Department of Civil, Environmental and Geomatics Engineering, College of Engineering and Computer Science
- Abstract/Description
-
Missing rainfall records happens frequently in many areas, and making precipitation estimation has been a challenge due to the spatial-temporal variability of the parameter. Model tree (MT), regression tree (RT), and ensemble approach models were developed and evaluated for estimating missing precipitation values in this research study. The selection of stations using correlation coefficient and similar distribution, and variation of data used to build the model were applied in this study....
Show moreMissing rainfall records happens frequently in many areas, and making precipitation estimation has been a challenge due to the spatial-temporal variability of the parameter. Model tree (MT), regression tree (RT), and ensemble approach models were developed and evaluated for estimating missing precipitation values in this research study. The selection of stations using correlation coefficient and similar distribution, and variation of data used to build the model were applied in this study. Proposed models were developed and tested using daily rainfall data from 1971 to 2016 at twenty-two stations in Kentucky, U.S.A. The model results were analyzed and evaluated using error and performance measures. The results indicated that MT-based and ensemble models produce a better estimation of missing rainfall than regression trees. The MT-based model was able to estimate missing rainfall accurately without needing objective selection of stations and using minimal calibration data to build the model.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014414
- Subject Headings
- Precipitation (Meteorology), Estimating techniques, Missing data (Statistics)
- Format
- Document (PDF)
- Title
- Computer simulation of air-estuary thermal energy fluxes.
- Creator
- Smith, Ned P.
- Date Issued
- 1980
- PURL
- http://purl.flvc.org/FCLA/DT/3353728
- Subject Headings
- Estuaries--Research, Computer simulation, Meteorological data, Thermal flux, Air
- Format
- Document (PDF)
- Title
- An analysis of historical meteorological data from the Florida Keys and current meter data from three tidal channels in lower Biscayne Bay.
- Creator
- Pitts, Patrick A., Smith, Ned P.
- Date Issued
- 1997-03-14
- PURL
- http://purl.flvc.org/fcla/dt/3359262
- Subject Headings
- Meteorological data, Biscayne Bay (Fla.), Winds, Tidal channels
- Format
- Document (PDF)
- Title
- REGULARIZATION MODELS FOR IMPUTATION OF MISSING PRECIPITATION DATA.
- Creator
- Azad, Anika, Teegavarapu, Ramesh S. V., Florida Atlantic University, Department of Civil, Environmental and Geomatics Engineering, College of Engineering and Computer Science
- Abstract/Description
-
This study focuses on developing optimization models to estimate missing precipitation data at twenty-two sites within Kentucky State. Various optimization formulations and regularization models are explored in this context. The performance of these models is evaluated using a range of performance measures and error metrics for handling missing records. The findings revealed that regularization models performed better than optimization models. This superiority is attributed to their ability...
Show moreThis study focuses on developing optimization models to estimate missing precipitation data at twenty-two sites within Kentucky State. Various optimization formulations and regularization models are explored in this context. The performance of these models is evaluated using a range of performance measures and error metrics for handling missing records. The findings revealed that regularization models performed better than optimization models. This superiority is attributed to their ability to reduce model complexity while enhancing overall performance. The study underscores the significance of regularization techniques in improving the accuracy and efficiency of precipitation data estimation.
Show less - Date Issued
- 2024
- PURL
- http://purl.flvc.org/fau/fd/FA00014432
- Subject Headings
- Rain and rainfall, Precipitation (Meteorology), Missing data (Statistics), Machine learning
- Format
- Document (PDF)
- Title
- Local energy exchanges in a shallow, coastal lagoon: summer conditions.
- Creator
- Smith, Ned P.
- Date Issued
- 1981
- PURL
- http://purl.flvc.org/FCLA/DT/3353738
- Subject Headings
- Indian River (Fla. : Lagoon), Heat flux, Meteorological data, Hydrography, Summer, Water temperature
- Format
- Document (PDF)
- Title
- An investigation of the heat budget of the Indian River lagoon, Florida, during winter months.
- Creator
- Smith, Ned P.
- Date Issued
- 1982
- PURL
- http://purl.flvc.org/fau/fd/FA00007145
- Subject Headings
- Indian River (Fla. : Lagoon), Heat budget (Geophysics), Meteorological data, Water temperature, Heat flux
- Format
- Document (PDF)
- Title
- Statistics preserving spatial interpolation methods for missing precipitation data.
- Creator
- El Sharif, Husayn., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
- Abstract/Description
-
Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of...
Show moreDeterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics.
Show less - Date Issued
- 2012
- PURL
- http://purl.flvc.org/FAU/3355568
- Subject Headings
- Numerical analysis, Meteorology, Statistical methods, Spatial analysis (Statistics), Data processing, Atmospheric physics, Statistical methods, Geographic information systems, Mathematical models
- Format
- Document (PDF)