Measuring Convective Organization

Giovanni Biagioli aDepartment of Mathematics and Geosciences, University of Trieste, Trieste, Italy
bEarth System Physics, ICTP, Trieste, Italy

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Adrian Mark Tompkins bEarth System Physics, ICTP, Trieste, Italy

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Abstract

Organized systems of deep convective clouds are often associated with high-impact weather and changes in such systems may have implications for climate sensitivity. This has motivated the derivation of many organization indices that attempt to measure the level of deep convective aggregation in models and observations. Here we conduct a comprehensive review of existing methodologies and highlight some of their drawbacks, such as only measuring organization in a relative sense, being biased toward particular spatial scales, or being very sensitive to the details of the calculation algorithm. One widely used metric, Iorg, uses statistics of nearest-neighbor distances between convective storms to address the first of these concerns, but we show here that it is insensitive to organization beyond the meso-β scale and very contingent on the details of the implementation. We thus introduce a new and complementary metric, Lorg, based on all-pair convective storm distances, which is also an absolute metric that can discern regular, random, and clustered cloud scenes. It is linearly sensitive to spatial scale in most applications and robust to the implementation methodology. We also derive a discrete form suited to gridded data and provide corrections to account for cyclic boundary conditions and finite, open boundary domains of nonequal aspect ratios. We demonstrate the use of the metric with idealized synthetic configurations, as well as model output and satellite rainfall retrievals in the tropics. We claim that this new metric usefully supplements the existing family of indices that can help to understand convective organization across spatial scales.

Significance Statement

The clustering and organization of convection is associated with high-impact weather and changes could impact climate sensitivity, but no consensus exists on how to best measure organization. Here we suggest a new metric that is robust to the calculation details and can classify scenes as random, clustered, or regular. This new metric can therefore account for spacing of organized convective systems and convective storms on scales spanning tens of kilometers to the entire tropics. We suggest that the new metric Lorg addresses many shortcomings of existing measures and can act as a useful additional tool to further understanding of convective organization.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Giovanni Biagioli, gbiagiol@ictp.it

Abstract

Organized systems of deep convective clouds are often associated with high-impact weather and changes in such systems may have implications for climate sensitivity. This has motivated the derivation of many organization indices that attempt to measure the level of deep convective aggregation in models and observations. Here we conduct a comprehensive review of existing methodologies and highlight some of their drawbacks, such as only measuring organization in a relative sense, being biased toward particular spatial scales, or being very sensitive to the details of the calculation algorithm. One widely used metric, Iorg, uses statistics of nearest-neighbor distances between convective storms to address the first of these concerns, but we show here that it is insensitive to organization beyond the meso-β scale and very contingent on the details of the implementation. We thus introduce a new and complementary metric, Lorg, based on all-pair convective storm distances, which is also an absolute metric that can discern regular, random, and clustered cloud scenes. It is linearly sensitive to spatial scale in most applications and robust to the implementation methodology. We also derive a discrete form suited to gridded data and provide corrections to account for cyclic boundary conditions and finite, open boundary domains of nonequal aspect ratios. We demonstrate the use of the metric with idealized synthetic configurations, as well as model output and satellite rainfall retrievals in the tropics. We claim that this new metric usefully supplements the existing family of indices that can help to understand convective organization across spatial scales.

Significance Statement

The clustering and organization of convection is associated with high-impact weather and changes could impact climate sensitivity, but no consensus exists on how to best measure organization. Here we suggest a new metric that is robust to the calculation details and can classify scenes as random, clustered, or regular. This new metric can therefore account for spacing of organized convective systems and convective storms on scales spanning tens of kilometers to the entire tropics. We suggest that the new metric Lorg addresses many shortcomings of existing measures and can act as a useful additional tool to further understanding of convective organization.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Giovanni Biagioli, gbiagiol@ictp.it

Supplementary Materials

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