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Related Concept Videos

Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
Graphs of Two-Variable Functions01:27

Graphs of Two-Variable Functions

A weather map provides a practical example of a function of two variables. Across a wide region such as the United States, temperatures vary from one location to another. Each location can be identified by two geographic coordinates: longitude and latitude. Since a single temperature value is assigned to each coordinate pair, the situation can be represented mathematically as a function with two inputs and one output.In mathematical notation, longitude and latitude can be labeled as x and y,...
What is Weather?01:07

What is Weather?

Overview
Precipitation Processes01:12

Precipitation Processes

The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
Precipitation Gravimetry01:03

Precipitation Gravimetry

Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...

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Related Experiment Video

Updated: Jun 12, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

[Comparison of spatial interpolation methods for daily meteorological elements].

Xiao-Jian Jiang1, Xiao-Jun Liu, Fen Huang

  • 1Jiangsu Province Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China. aspnetant@gmail.com

Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology
|June 22, 2010
PubMed
Summary

Thin Plate Spline (TPS) is the optimal method for interpolating meteorological data in China. TPS showed the smallest errors and highest accuracy for temperature, sunshine, and precipitation across seasons compared to Inverse Distance Weighting and co-kriging.

Related Experiment Videos

Last Updated: Jun 12, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Area of Science:

  • Geosciences
  • Environmental Science
  • Meteorology

Background:

  • Accurate spatial interpolation of meteorological data is crucial for climate analysis and environmental monitoring.
  • Traditional methods like Inverse Distance Weighting (IDW) and co-kriging (CK) have limitations in capturing complex spatial patterns.
  • Evaluating advanced interpolation techniques is necessary to improve the accuracy of meteorological data representation.

Purpose of the Study:

  • To comparatively evaluate the performance of Inverse Distance Weighting (IDW), co-kriging (CK), and Thin Plate Spline (TPS) for spatial interpolation of meteorological elements in China.
  • To determine the optimal interpolation method for average daily meteorological data (maximum/minimum temperature, sunshine hours, precipitation) across different seasons.
  • To assess the accuracy of these methods using comprehensive historical observation data.

Main Methods:

  • Utilized comprehensive meteorological observation data from 559 stations in China spanning 1951-2005.
  • Applied three spatial interpolation methods: Inverse Distance Weighting (IDW), co-kriging (CK), and Thin Plate Spline (TPS).
  • Analyzed interpolation accuracy using Root Mean Square Error (RMSE) and coefficient of determination (R2) for annual and seasonal data.

Main Results:

  • Thin Plate Spline (TPS) consistently yielded the smallest RMSE and highest R2 for annual maximum and minimum air temperature, sunshine hours, and precipitation.
  • TPS demonstrated superior performance in most seasonal analyses, particularly for temperature in autumn and summer.
  • While TPS excelled overall, IDW showed the smallest RMSE for summer precipitation, and CK had the highest R2 for winter precipitation, indicating method-specific strengths.

Conclusions:

  • Thin Plate Spline (TPS) is recommended as the optimal spatial interpolation method for meteorological elements in China.
  • TPS provides a more accurate and reliable method for interpolating and rasterizing daily meteorological data compared to IDW and CK.
  • The findings support the use of TPS for improving climate studies and environmental assessments in China.