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A double instrumental variable method for geophysical product error estimation

A double instrumental variable method for geophysical product error estimation
A double instrumental variable method for geophysical product error estimation

The global validation of remotely sensed and/or modeled geophysical products is often complicated by a lack of suitable ground observations for comparison. By cross-comparing three independent collocated observations, triple collocation (TC) can solve for geophysical product errors in error-prone systems. However, acquiring three independent products for a geophysical variable of interest can be challenging. Here, a double instrumental variable based algorithm (IVd) is proposed as an extension of the existing single instrumental variable (IVs) approach to estimate product error standard deviation (σ) and product-truth correlation (R) using only two independent products - an easier requirement to meet in practice. An analytical examination of the IVd method suggests that it is less prone to bias and has reduced sampling errors relative to IVs. Results from an example application of the IVd method to precipitation product error estimation show that IVd-based σ and R are good approximations of reference values obtained from TC at the global extent. In addition to their spatial consistency, IVd estimated error metrics also have only marginal (less than 5%) relative biases versus a TC baseline. Consistent with our earlier analytical analysis, these empirical results are shown to be superior to those obtained by IVs. However, several caveats for the IVd approach should be acknowledged. As with TC and IVs, IVd estimates are less robust when the signal-to-noise ratio of geophysical products is very low. Additionally, IVd may be significantly biased when geophysical products have strongly contrasting error auto-correlations.

Error estimation, Instrumental variable, Triple collocation
0034-4257
217-228
Dong, Jianzhi
4dddef5a-7f1b-4283-8ff1-7516648910cb
Crow, Wade T.
f2e76407-3e83-4733-a5a8-c887e0ae05db
Duan, Zheng
e706637d-3ab3-4125-9508-fcd8186adb5f
Wei, Lingna
0e6f2575-877a-4ad3-89f3-0cb4ce6e358b
Lu, Yang
6d9d9d4f-3177-4265-b03b-34d7129ec95c
Dong, Jianzhi
4dddef5a-7f1b-4283-8ff1-7516648910cb
Crow, Wade T.
f2e76407-3e83-4733-a5a8-c887e0ae05db
Duan, Zheng
e706637d-3ab3-4125-9508-fcd8186adb5f
Wei, Lingna
0e6f2575-877a-4ad3-89f3-0cb4ce6e358b
Lu, Yang
6d9d9d4f-3177-4265-b03b-34d7129ec95c

Dong, Jianzhi, Crow, Wade T., Duan, Zheng, Wei, Lingna and Lu, Yang (2019) A double instrumental variable method for geophysical product error estimation. Remote Sensing of Environment, 225, 217-228. (doi:10.1016/j.rse.2019.03.003).

Record type: Article

Abstract

The global validation of remotely sensed and/or modeled geophysical products is often complicated by a lack of suitable ground observations for comparison. By cross-comparing three independent collocated observations, triple collocation (TC) can solve for geophysical product errors in error-prone systems. However, acquiring three independent products for a geophysical variable of interest can be challenging. Here, a double instrumental variable based algorithm (IVd) is proposed as an extension of the existing single instrumental variable (IVs) approach to estimate product error standard deviation (σ) and product-truth correlation (R) using only two independent products - an easier requirement to meet in practice. An analytical examination of the IVd method suggests that it is less prone to bias and has reduced sampling errors relative to IVs. Results from an example application of the IVd method to precipitation product error estimation show that IVd-based σ and R are good approximations of reference values obtained from TC at the global extent. In addition to their spatial consistency, IVd estimated error metrics also have only marginal (less than 5%) relative biases versus a TC baseline. Consistent with our earlier analytical analysis, these empirical results are shown to be superior to those obtained by IVs. However, several caveats for the IVd approach should be acknowledged. As with TC and IVs, IVd estimates are less robust when the signal-to-noise ratio of geophysical products is very low. Additionally, IVd may be significantly biased when geophysical products have strongly contrasting error auto-correlations.

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More information

Accepted/In Press date: 4 March 2019
e-pub ahead of print date: 19 March 2019
Published date: May 2019
Keywords: Error estimation, Instrumental variable, Triple collocation

Identifiers

Local EPrints ID: 431939
URI: http://eprints.soton.ac.uk/id/eprint/431939
ISSN: 0034-4257
PURE UUID: 2ded4a58-4956-4fc2-975f-587255c03e62

Catalogue record

Date deposited: 21 Jun 2019 16:30
Last modified: 06 Oct 2020 21:04

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Contributors

Author: Jianzhi Dong
Author: Wade T. Crow
Author: Zheng Duan
Author: Lingna Wei
Author: Yang Lu

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