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SpatialVx (version 1.0)

Spatial Forecast Verification

Description

Spatial forecast verification refers to verifying weather forecasts when the verification set (forecast and observations) is on a spatial field, usually a high-resolution gridded spatial field. Most of the functions here require the forecast and observed fields to be gridded and on the same grid. For a thorough review of most of the methods in this package, please see Gilleland et al. (2009) and for a tutorial on some of the main functions available here, see Gilleland (2022) .

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Version

Install

install.packages('SpatialVx')

Monthly Downloads

254

Version

1.0

License

GPL (>= 2)

Maintainer

Eric Gilleland

Last Published

July 19th, 2022

Functions in SpatialVx (1.0)

Forecast Verification with Cluster Analysis: The Variation

ExampleSpatialVxSet

Simulated Spatial Verification Set

Forecast Quality Index

Connectivity Index

CircleHistogram

Circular Histogram

Major and Minor Axes of a Feature

Elmore, Baldwin and Schultz Method for Field Significance for Spatial Bias Errors

FeatureMatchAnalyzer

Analyze Features of a Verification Set

Threshold-based Feature Finder

Force Merges in Matched Feature Objects

Spatial-Alignment Summary Measures

Feature-Based Contingency Table

Single Feature Properties

Raw Image Moments.

SpatialVx-internal

Internal functions for the SpatialVx package

Geographic Box Plot

Example Verification Set

The Spatial Alignment Summary Measure Called G

SpatialVx-package

Spatial Forecast Verification

2-d Interpolation

Optical Flow Verification

Combine Features/Matched Objects

Example Precipitation Rate Verification Set (NIMROD)

S1 Score, Anomaly Correlation

Loss functions for the spatial prediction comparison test (SPCT)

Bearing from One Spatial Location to Another

calculate_FSSvector_from_binary_fields

Calculate FSS Values

Temporal Block Bootstrap Keeping Locations in Space Constant

calculate_FSSwind

Calculate FSSwind Score Value

Create Binary Fields

Monte Carlo Degrees of Freedom

Spatial Forecast Verification Methods Inter-Comparison Project (ICP) Test Cases and other example verification sets

Cluster Analysis Verification

Centroid Distance Between Two Identified Objects

Create Composite Features

Create Several Graphics for List Objects Returned from hoods2d

Exponential Variogram

Identify Disjoint Sets of Connected Components

Calculate dFSS Score Value

Exponential Variogram

Centered on Square Domain Baddeley's Delta Metric

Variograms for a Gridded Verification Set

Spatial Forecast Verification Shape Analysis

Various Verification Statistics on Possibly Neighborhood-Smoothed Fields.

2-d Gaussian Mixture Models Verification

Minimum Boundary Separation Feature Matching

Binary Location Metric Proposed in Zhu et al. (2011)

Test for Equal Predictive Ability on Average Over a Regularly Gridded Space

Spatial Verification Sets -- SpatialVx Object

Quilt Plot and a Matrix Plot.

Neighborhood Verification Statistics for a Gridded Verification Set.

Image Warping By Hand

Merge and/or Match Identified Features Within Two Fields

Feature Interest

structurogram.matrix

Structure Function for Gridded Fields

Simulated Forecast and Verification Fields

Structure Function for Non-Gridded Spatial Fields.

Practically Perfect Hindcast Neighborhood Verification Method

Apply a Threshold to a Field

Create Surrogate Fields

Apply Traditional Forecast Verification After Wavelet Denoising

Intensity Scale (IS) Verification

Rigid Transformation

Localization Performance Measures

Feature-based Analysis of a Field (Image)

Binary Image Measures

Field Significance Method of Elmore et al. (2006)

High-Resolution Gridded Forecast Verification Using Discrete Wavelet Decomposition

Spatial Prediction Comparison Test

Some Common Traditional Forecast Verification Statistics.

Upscaling Neighborhood Verification on a 2-d Verification Set

Variography Score