On the Variability of the Barometric Effect and Its Relation to Cosmic-Ray Neutron Sensing

Accurate estimation of the barometric coefficient (β) is important for correcting pressure effects in soil moisture data from cosmic-ray neutron sensing (CRNS) due to the barometric effect. To evaluate estimation strategies for β, we compared analytical and empirical approaches using 71 CRNS and 46 neutron monitor (NM) stations across the United States, Europe, and globally. Our results show spatio-temporal variation in the barometric effect, with β ranging from 0.66 to 0.82 %hPa for NM and from 0.63 to 0.80 %hPa for CRNS. These coefficients exhibit higher variability than previously published semi-analytical models. In addition, we found that the analytically determined β values were systematically lower compared with empirical estimates, with stronger agreement between the two empirical methods (r≈0.67) than between empirical and analytical approaches. Furthermore, NM stations produced higher β values than CRNS, indicating that differences in detector energy sensitivity affected the values of β. Principal Component Analysis (PCA) further showed that the analytical and empirical β estimates clustered together, reflecting shared sensitivity to elevation. In contrast, soil moisture and atmospheric humidity projected nearly orthogonally to the β vectors, indicating negligible influence, while cut-off rigidity contributed to a separate, inverse gradient. Analytical β estimates were fully orthogonal to AH, while empirical methods showed only slight deviations beyond orthogonality. The barometric coefficient (β), therefore, varies with location, altitude, atmospheric conditions, and sensor type, highlighting the necessity of station-specific values for precise correction. Overall, our study emphasizes the need for atmospheric correction in CRNS measurements and introduces a method for deriving site- and sensor-specific β values for accurate soil moisture estimation.

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Publication Details

Journal
Sensors
Published
2026-02-01
DOI
https://doi.org/10.3390/s26030925
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

On the Variability of the Barometric Effect and Its Relation to Cosmic-Ray Neutron Sensing

Leonard K. Amekudzi, Roland Baatz, Patrick Davies, Emmanuel Quansah et al.
Sensors
Soil Moisture and Remote Sensing
article

On the Variability of the Barometric Effect and Its Relation to Cosmic-Ray Neutron Sensing

Leonard K. Amekudzi, Roland Baatz, Patrick Davies, Emmanuel Quansah, Paul Schattan, Heye Reemt Bogena
article en

Abstract

Accurate estimation of the barometric coefficient (β) is important for correcting pressure effects in soil moisture data from cosmic-ray neutron sensing (CRNS) due to the barometric effect. To evaluate estimation strategies for β, we compared analytical and empirical approaches using 71 CRNS and 46 neutron monitor (NM) stations across the United States, Europe, and globally. Our results show spatio-temporal variation in the barometric effect, with β ranging from 0.66 to 0.82 %hPa for NM and from 0.63 to 0.80 %hPa for CRNS. These coefficients exhibit higher variability than previously published semi-analytical models. In addition, we found that the analytically determined β values were systematically lower compared with empirical estimates, with stronger agreement between the two empirical methods (r≈0.67) than between empirical and analytical approaches. Furthermore, NM stations produced higher β values than CRNS, indicating that differences in detector energy sensitivity affected the values of β. Principal Component Analysis (PCA) further showed that the analytical and empirical β estimates clustered together, reflecting shared sensitivity to elevation. In contrast, soil moisture and atmospheric humidity projected nearly orthogonally to the β vectors, indicating negligible influence, while cut-off rigidity contributed to a separate, inverse gradient. Analytical β estimates were fully orthogonal to AH, while empirical methods showed only slight deviations beyond orthogonality. The barometric coefficient (β), therefore, varies with location, altitude, atmospheric conditions, and sensor type, highlighting the necessity of station-specific values for precise correction. Overall, our study emphasizes the need for atmospheric correction in CRNS measurements and introduces a method for deriving site- and sensor-specific β values for accurate soil moisture estimation.

SensorsVol. 26(3)
Forschungszentrum Jülich (DE), Universität Innsbruck (AT), Kwame Nkrumah University of Science and Technology (GH), Leibniz Centre for Agricultural Landscape Research (DE), CDM Smith (United States) (US), BOKU University (AT)
European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Austrian Science Fund, West African Science Service Centre on Climate Change and Adapted Land Use
Openalex Percentile: Top 75%
Soil Moisture and Remote Sensing
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