Geophysical Research Letters

Journal Information
ISSN / EISSN : 00948276 / 19448007
Current Publisher: American Geophysical Union (AGU) (10.1029)
Former Publisher: Wiley (10.1002)
Total articles ≅ 40,779
Google Scholar h5-index: 87
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Latest articles in this journal

Xingying Huang, Samantha Stevenson, Alex D. Hall
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088679

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Cesar R. Castillo, Inci Güneralp, Billy Hales, Burak Güneralp
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088378

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Yalei You, S. Joseph Munchak, Ralph Ferraro, Karen Mohr, Christa Peters‐Lidard, Catherine Prigent, Sarah Ringerud, Scott Rudlosky, Heshun Wang, Hamidreza Norouzi, et al.
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088656

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Shih‐Wei Fang, Jin‐Yi Yu
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088926

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Hitoshi Matsui, Nobuhiro Moteki
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088978

Abstract:
The representation of aerosol activation into cloud droplets in climate models is important for accurate understanding of aerosol radiative impacts on the Arctic climate, but it remains highly uncertain. Here we show that the uncertainty range of subgrid vertical velocity (SVV) and maximum supersaturation (SSmax) in aerosol activation produces fourfold to fivefold differences in the direct radiative effect of black carbon (BC) in the Arctic (0.091–0.40 W m–2) because SVV and SSmax determine the activated fraction and wet removal efficiency of aerosols. Aerosols are particularly sensitive to SVV in remote regions, but not near their sources because many aerosols near sources are not yet influenced by wet removal processes. Our results demonstrate that SVV treatment is a major source of uncertainty in Arctic aerosol simulations and may be key for reducing the large discrepancies among global models in estimates of BC and its radiative effects in the Arctic.
Zachary W. Murphy, David A. Dicarlo, Peter B. Flemings, Hugh Daigle
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl089289

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Sizhuang Deng, Alan Levander
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl089630

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Vu A. Nguyen, Oleguer Nogues‐Correig, Takayuki Yuasa, Dallas Masters, Vladimir Irisov
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088308

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Tianjun Zhou, Jingwen Lu, Wenxia Zhang, Ziming Chen
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl088415

Abstract:
Policy‐makers need reliable future climate projection for adaptation purposes. A clear separation of sources of uncertainty also helps narrow the projection uncertainty. However, it remains unclear for monsoon precipitation projections. Here we quantified the contributions of internal variability, model uncertainty and scenario uncertainty to the ensemble spread of global land monsoon precipitation projections using Coupled Model Intercomparison Project Phase 5 (CMIP5) models and single‐model initial‐condition large ensembles (SMILEs). For mean precipitation, model uncertainty (contributing ~90%) dominates the projection uncertainty, while the contribution of internal variability (scenario uncertainty) decreases (increases) with time. The source of uncertainty for extreme precipitation differs from that of mean precipitation mainly in long‐term projection, with the contribution of scenario uncertainty comparable to model uncertainty. Reducing model uncertainty can effectively narrow the monsoon precipitation projection. The internal variability estimates differ slightly among models and methods, the uncertainty partitioning is robust in mid‐long term.
Yunjiao Pu, Steven A. Cummer, Anjing Huang, Michael Briggs, Bagrat Mailyan, Stephen Lesage
Geophysical Research Letters, Volume 47; doi:10.1029/2020gl089427

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