Abstract

Approaches from metrology can assist earth observation (EO) practitioners to develop quantitative characterisation of uncertainty in EO data. This is necessary for the credibility of statements based on Earth observations in relation to topics of public concern, particularly climate and environmental change. This paper presents the application of metrological uncertainty analysis to historical Earth observations from satellites, and is intended to aid mutual understanding of metrology and EO. The nature of satellite observations is summarised for different EO data processing levels, and key metrological nomenclature and principles for uncertainty characterisation are reviewed. We then address metrological approaches to developing estimates of uncertainty that are traceable from the satellite sensor, through levels of data processing, to products describing the evolution of the geophysical state of the Earth. EO radiances have errors with complex error correlation structures that are significant when performing common higher-level transformations of EO imagery. Principles of measurement-function-centred uncertainty analysis are described that apply sequentially to each EO data processing level. Practical tools for organising and traceably documenting uncertainty analysis are presented. We illustrate these principles and tools with examples including some specific sources of error seen in EO satellite data as well as with an example of the estimation of sea surface temperature from satellite infra-red imagery. This includes a simulation-based estimate for the error distribution of clear-sky infra-red brightness temperature in which calibration uncertainty and digitisation are found to dominate. The propagation of these errors to sea surface temperature is then presented, illustrating the relevance of the approach to derivation of EO-based climate datasets. We conclude with a discussion arguing that there is broad scope and need for improvement in EO practice as a measurement science. EO practitioners and metrologists willing to extend and adapt their disciplinary knowledge to meet this need can make valuable contributions to EO.

Highlights

  • The environment and climate of the Earth have been explored from space for over 50 years

  • This paper presents the application of metrological uncertainty analysis to historical Earth observations from satellites, and is intended to aid mutual understanding of metrology and earth observation (EO)

  • To make the concepts and discussion in previous sections more concrete, we present an example tracing the uncertainty in estimating sea surface temperature (SST) data from observations taken from the advanced very high resolution radiometer (AVHRR)

Read more

Summary

Introduction

The environment and climate of the Earth have been explored from space for over 50 years. It presents the key ideas of this paper: a framework for metrological analysis of uncertainty in multi-decadal Earth observations through measurement-function centred analysis of EO levels of processing. This is an example where EO measurements intended for operational meteorology are of potential value to climate science, if measurement errors can be reduced, observational stability increased, and uncertainties can be rigorously quantified.

Measurands, sensors, orbits and variability
Data product levels
Additional remarks: processing chain, SI references
Introductory comments on metrology
Error, uncertainty, effect
Independent, structured and common errors, correlation
Common errors
Overview
Propagation of uncertainty: single measurand
Propagation of uncertainty: multiple measurands
Hierarchical structure of error effects
Correlation of effects
Calculation of error covariance for L1
The uncertainty analysis diagram
Effects tables
Uncertainty and sensitivity estimation
Uncertainty characterisation at higher product levels
Introductory context
The AVHRR instrument
C E a2 C E2
An uncertainty analysis diagram for the AVHRR
Space-view counts uncertainty
Internal calibration target thermal gradient effect
Calculating uncertainties
Uncertainties in the AVHRR brightness temperatures including digitisation
Uncertainties in sea surface temperature retrievals
A Monte-Carlo simulation of SST retrievals using optimal estimation
Remarks
Aims of EO metrology
Need for Collaboration and Communication
Limitations of this paper
Concluding remarks
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.