Related Experiment Video
Updated: Jul 6, 2026
07:05
A New Workflow for Sampling and Digitizing Increment Cores
Published on: September 27, 2024
Discrete representation and resampling in limb-sounding measurements
Applied Optics
|March 22, 2008
Summary
This study uses functional spaces to analyze data resampling for atmospheric profiles. A new method conserving the vertical column is presented, evaluating its impact on errors and resolution.
Area of Science:
- Atmospheric Science
- Data Analysis
- Functional Analysis
Background:
- Discretization, interpolation, and resampling are common data analysis techniques.
- Functional spaces offer a robust framework for understanding measurement and data processing operations.
Purpose of the Study:
- To apply functional space formalism to characterize measurement and resampling processes.
- To develop and evaluate a novel resampling method for atmospheric profiles from limb-sounding measurements.
Main Methods:
- Utilized functional space formalism for data analysis.
- Developed a resampling method incorporating vertical column conservation as a constraint.
- Compared the new method against existing resampling techniques.
Main Results:
- The functional space framework effectively describes measurement and resampling.
- The proposed resampling method, using vertical column conservation, was presented and compared.
- Evaluated the impact of resampling on error propagation and vertical resolution.
Conclusions:
- Functional space formalism provides a powerful framework for analyzing atmospheric data resampling.
- The vertical column conserving resampling method offers a valuable approach for processing limb-sounding data.
- Understanding error propagation and resolution loss is crucial for accurate atmospheric profile analysis.
Related Concept Videos
01:20Downsampling
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
01:06Sampling Methods: Overview
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling.
In analytical chemistry, the choice of sampling...
In analytical chemistry, the choice of sampling...
01:10Reconstruction of Signal using Interpolation
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...
01:15Sampling Theorem
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
01:11Sampling Continuous Time Signal
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
In the...
01:22Upsampling
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...