edu.ucar.opensky::articles:42968 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T17:55:12.040383 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7n01bxn https://doi.org/10.6075/J0P26ZF1 https Related Dataset #1 Data from: A new method for diagnosing effective radiative forcing from aerosol-cloud interactions in climate models https://doi.org/10.48550/arXiv.1711.03675 https Related Preprint #1 CLUBB-SILHS: A parameterization of subgrid variability in the atmosphere https://doi.org/10.5065/qx9a-pg09 https Related Service #1 Derecho: HPE Cray EX Cluster https://doi.org/10.5281/zenodo.13839356 https Related Software #1 brandonduran/modis_cloud_radiative_kernels: Sep 25, 2025 release https://doi.org/10.5281/zenodo.5514136 https Related Software #2 mzelinka/cloud-radiative-kernels: Sep 4, 2024 Release https://doi.org/10.5281/zenodo.5514141 https Related Software #3 mzelinka/aprp: Aug 1, 2023 Release A new method for diagnosing effective radiative forcing from aerosol-cloud interactions in climate models 2025-02-19T00:00:00Z publication https://n2t.net/ark:/85065/d7n01bxn https://doi.org/10.5194/acp-25-2123-2025 Duran, B. M. author Wall, C. author Lutsko, N. J. author Michibata, T. author Ma, P. author Qin, Y. author Duffy, Margaret author Medeiros, Brian author Debolskiy, M. author UCAR/NCAR - Library publisher Aerosol–cloud interactions (ACIs) are a leading source of uncertainty in estimates of the historical effective radiative forcing (ERF). One reason for this uncertainty is the difficulty in estimating the ERF from aerosol–cloud interactions (ERFaci) in climate models, which typically requires multiple calls to the radiation code. Most commonly used methods also cannot disentangle the contributions from different processes to ERFaci. Here, we develop a new, computationally efficient method for estimating the shortwave (SW) ERFaci from liquid clouds using histograms of monthly averaged cloud fraction partitioned by cloud droplet effective radius (re) and liquid water path (LWP). Multiplying the histograms with SW cloud radiative kernels gives the total SW ERFaci from liquid clouds, which can be decomposed into contributions from the Twomey effect, LWP adjustments, and cloud fraction (CF) adjustments. We test the method with data from five CMIP6-era models, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument simulator to generate the histograms. Our method gives similar total SW ERFaci estimates to other established methods in regions of prevalent liquid cloud and indicates that the Twomey effect, LWP adjustments, and CF adjustments have contributed −0.34 ± 0.23, −0.22 ± 0.13, and −0.09 ± 0.11 W m−2, respectively, to the effective radiative forcing of the climate since 1850 in the ensemble mean (95 % confidence). These results demonstrate that widespread adoption of a MODIS re–LWP joint histogram diagnostic would allow the SW ERFaci and its components to be quickly and accurately diagnosed from climate model outputs, a crucial step for reducing uncertainty in the historical ERF. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span> None eng geoscientificInformation