<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The study presents a compatibility analysis of gravimetric observations with passive microwave observations. Monitoring the variability of soil water content is one of the essential issues in climate-related research. Total water storage changes (ΔTWS) observed by Gravity Recovery and Climate Experiment (GRACE), enables the creation of many applications in hydrological monitoring. Soil moisture (SM) is a critical variable in hydrological studies. Advanced Microwave Scanning Radiometer (AMSR-E) satellite products provided unique observations on this variable in near-daily time resolutions. The study used maximum covariance analysis (MCA) to extract principal components for ΔTWS and SM signals. The analysis was carried out for the global area, dividing the discussion into individual continents. The amplitudes of gravimetric and microwave signals were computed via the complex empirical orthogonal function (EOF) and the complex conjugate EOF* to determine the regions for detailed comparison. Similarities and differences in signal convergence results were compared with land cover data describing soil conditions, vegetation cover, urbanization status, and cultivated land. Convergence was determined using Pearson correlation coefficients and cross-correlation. In order to compare ΔTWS and SM in individual seasons, ΔTWS observations were normalized. Results show that naturally forested areas and large open spaces used for agriculture support the compatibility between GRACE and AMSRE observations and are characterized by a good Pearson correlation coefficient >0.8. Subpolar regions with permafrost present constraints for AMSR-E observations and have little convergence with GRACE observations.</p>
</abstract>

The study presents a compatibility analysis of gravimetric observations with passive microwave observations. Monitoring the variability of soil water content is one of the essential issues in climate-related research. Total water storage changes (ΔTWS) observed by Gravity Recovery and Climate Experiment (GRACE), enables the creation of many applications in hydrological monitoring. Soil moisture (SM) is a critical variable in hydrological studies. Advanced Microwave Scanning Radiometer (AMSR-E) satellite products provided unique observations on this variable in near-daily time resolutions. The study used maximum covariance analysis (MCA) to extract principal components for ΔTWS and SM signals. The analysis was carried out for the global area, dividing the discussion into individual continents. The amplitudes of gravimetric and microwave signals were computed via the complex empirical orthogonal function (EOF) and the complex conjugate EOF* to determine the regions for detailed comparison. Similarities and differences in signal convergence results were compared with land cover data describing soil conditions, vegetation cover, urbanization status, and cultivated land. Convergence was determined using Pearson correlation coefficients and cross-correlation. In order to compare ΔTWS and SM in individual seasons, ΔTWS observations were normalized. Results show that naturally forested areas and large open spaces used for agriculture support the compatibility between GRACE and AMSRE observations and are characterized by a good Pearson correlation coefficient >0.8. Subpolar regions with permafrost present constraints for AMSR-E observations and have little convergence with GRACE observations.

Similarities and Differences in the Earth’s Water Variations Signal Provided by Grace and AMSR-E Observations Using Maximum Covariance Analysis at Various Land Cover Data Backgrounds

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This work is licensed under the Creative Commons Attribution 4.0 International License.

The study presents a compatibility analysis of gravimetric observations with passive microwave observations. Monitoring the variability of soil water content...

Similarities and Differences in the Earth’s Water Variations Signal Provided by Grace and AMSR-E Observations Using Maximum Covariance Analysis at Various Land Cover Data Backgrounds

Publicado en línea: 18 jul 2023

Páginas: 63 - 87

Recibido: 22 mar 2023

Aceptado: 16 jun 2023

DOI: https://doi.org/10.2478/arsa-2023-0006

Palabras clave
GRACE, AMSR-E, total water storage anomalies, soil moisture, remote sensors

© 2023 Viktor Szabó et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Similarities and Differences in the Earth’s Water Variations Signal Provided by Grace and AMSR-E Observations Using Maximum Covariance Analysis at Various Land Cover Data Backgrounds

Publicado en línea: 18 jul 2023

Páginas: 63 - 87

Recibido: 22 mar 2023

Aceptado: 16 jun 2023

DOI: https://doi.org/10.2478/arsa-2023-0006

Palabras claveGRACE, AMSR-E, total water storage anomalies, soil moisture, remote sensors

© 2023 Viktor Szabó et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
GRACE, AMSR-E, total water storage anomalies, soil moisture, remote sensors