start-ver=1.4
cd-journal=joma
no-vol=122
cd-vols=
no-issue=1
article-no=
start-page=158
end-page=171
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2017
dt-pub=20170114
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Pressure dependence of electrical conductivity in forsterite
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract= Electrical conductivity of dry forsterite has been measured in muli-anvil apparatus to investigate the pressure dependence of ionic conduction in forsterite. The starting materials for the conductivity experiments were a synthetic forsterite single crystal and a sintered forsterite aggregate synthesized from oxide mixture. Electrical conductivities were measured at 3.5, 6.7, 9.6, 12.1, and 14.9 GPa between 1300 and 2100 K. In the measured temperature range, the conductivity of single crystal forsterite decreases in the order of [001], [010], and [100]. In all cases, the conductivity decreases with increasing pressure and then becomes nearly constant for [100] and [001] and slightly increases above 7 GPa for [010] orientations and a polycrystalline forsterite sample. Pressure dependence of forsterite conductivity was considered as a change of the dominant conduction mechanism composed of migration of both magnesium and oxygen vacancies in forsterite. The activation energy (ΔE) and activation volume (ΔV) for ionic conduction due to migration of Mg vacancy were 1.8–2.7 eV and 5–19 cm3/mol, respectively, and for that due to O vacancy were 2.2–3.1 eV and −1.1 to 0.3 cm3/mol, respectively. The olivine conductivity model combined with small polaron conduction suggests that the most part of the upper mantle is controlled by ionic conduction rather than small polaron conduction. The previously observed negative pressure dependence of the conductivity of olivine with low iron content (Fo90) can be explained by ionic conduction due to migration of Mg vacancies, which has a large positive activation volume.
en-copyright=
kn-copyright=

en-aut-name=YoshinoTakashi
en-aut-sei=Yoshino
en-aut-mei=Takashi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=ZhangBaohua
en-aut-sei=Zhang
en-aut-mei=Baohua
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=RhymerBrandon
en-aut-sei=Rhymer
en-aut-mei=Brandon
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

en-aut-name=ZhaoChengcheng
en-aut-sei=Zhao
en-aut-mei=Chengcheng
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=

en-aut-name=FeiHongzhan
en-aut-sei=Fei
en-aut-mei=Hongzhan
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=

affil-num=1
en-affil=Institute for Planetary Materials, Okayama University
kn-affil=

affil-num=2
en-affil=Key Laboratory for High-Temperature and High-Pressure Study of the Earth’s Interior, Institute of Geochemistry, Chinese Academy of Sciences
kn-affil=

affil-num=3
en-affil=Department of Geosciences, State University of New York at Stony Brook
kn-affil=

affil-num=4
en-affil=Institute for Planetary Materials, Okayama University
kn-affil=

affil-num=5
en-affil=Bayerisches Geoinstitut, University of Bayreuth
kn-affil=
END

start-ver=1.4
cd-journal=joma
no-vol=14
cd-vols=
no-issue=12
article-no=
start-page=e2022MS003046
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2022
dt-pub=202212
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Too Frequent and Too Light Arctic Snowfall With Incorrect Precipitation Phase Partitioning in the MIROC6 GCM
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Cloud-phase partitioning has been studied in the context of cloud feedback and climate sensitivity; however, precipitation-phase partitioning also has a significant role in controlling the energy budget and sea ice extent. Although some global models have introduced a more sophisticated precipitation parameterization to reproduce realistic cloud and precipitation processes, the effects on the process representation of mixed- and ice-phase precipitation are poorly understood. Here, we evaluate how different precipitation modeling (i.e., diagnostic [DIAG] vs. prognostic [PROG] schemes) affects the simulated precipitation phase and occurrence frequency. Two versions of MIROC6 were used with the satellite simulator COSP2. Although the PROG scheme significantly improves the simulated cloud amount and snowfall rates, the phase partitioning, frequency, and intensity of precipitation with the PROG scheme are still biased, and are even worse than with the DIAG scheme. We found a "too frequent and too light" Arctic snowfall bias in the PROG, which cannot be eliminated by model tuning. The cloud-phase partitioning is also affected by the different approaches used to consider precipitation. The ratio of supercooled liquid water is underrepresented by switching from the DIAG to PROG scheme, because some snowflakes are regarded to be cloud ice. Given that the PROG precipitation retains more snow in the atmosphere, the underestimation becomes apparent when other models incorporate the PROG scheme. This depends on how much precipitation is within the clouds in the model. Our findings emphasize the importance of correctly reproducing the phase partitioning of cloud and precipitation, which ultimately affects the simulated climate sensitivity. Plain Language Summary This study examined cloud and precipitation phase partitioning (i.e., the ratio between liquid and ice) in the Arctic using the MIROC6 global climate model (GCM). Despite recent advances in precipitation modeling by GCMs, the associations between the macrostructures (i.e., cloud coverage and precipitation rate) and phase partitioning have been little studied. Prognostic treatment of precipitation, which is a more sophisticated parameterization, yields seasonal and annual cloud cover and snowfall that are in better agreement with satellite observations. However, it tends to generate snowfall too frequently and too lightly, resulting in the misrepresentation of precipitation phase partitioning. In addition, there is a risk of overestimating the ratio of cloud ice to cloud liquid by including prognostic precipitation. The bias is difficult to remove by model tuning alone. If the models misrepresent the precipitation phase partitioning, then the bias will further influence feedback processes in a future warming scenario through the snow-to-rain phase change, similar to the cloud phase feedback. Our findings emphasize the importance of conducting process-oriented model evaluations on a regional scale.
en-copyright=
kn-copyright=

en-aut-name=ImuraYuki
en-aut-sei=Imura
en-aut-mei=Yuki
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=MichibataTakuro
en-aut-sei=Michibata
en-aut-mei=Takuro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

affil-num=1
en-affil=Department of Earth Sciences, Okayama University
kn-affil=

affil-num=2
en-affil=Department of Earth Sciences, Okayama University
kn-affil=
en-keyword=cloud phase partitioning
kn-keyword=cloud phase partitioning
en-keyword=precipitation microphysics
kn-keyword=precipitation microphysics
en-keyword=climate
kn-keyword=climate
END

start-ver=1.4
cd-journal=joma
no-vol=128
cd-vols=
no-issue=5
article-no=
start-page=e2022JB025670
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2023
dt-pub=20230425
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Lithium Isotope Constraints on Slab and Mantle Contribution to Arc Magmas
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=Dehydration of subducting oceanic lithosphere (slab) induces Li-isotope fractionation between the fluid and the slab, suggested by the δ7Li variation (∼10‰) in exhumed subduction complexes. Given that arc magmas represent melt of the supraslab mantle, a large δ7Li variation is anticipated for arc volcanic rocks. However, the δ7Li values in these rocks are mostly homogeneous within the range of mid-ocean ridge basalts (+1.6 to +5.6‰). The lack of a subduction-related δ7Li signature has been explained by (1) homogenization by mixing of different magma sources, (2) loss of Li from the slab via dehydration, or (3) homogenization by diffusive exchange of slab-derived Li and the mantle. The Chugoku district in SW Japan is an ideal place to study the process responsible for Li-isotope variation in arc magmas, since the Chugoku volcanic rocks show large δ7Li variation (–1.9 to +7.4‰). High δ7Li values (+6.3 to +7.4‰) are found in some high-Sr andesites and dacites (adakites) whereas low δ7Li values (–1.0 to –0.1‰) are found in high-Mg andesites. The parental magmas of these rocks have been sourced from subducted oceanic crust and sediments, respectively, with various extents of the interaction with wedge mantle. The limited extents of Li isotope modification are indicated by the similarity of the δ7Li values of these rocks and their supposed sources. The models for a slab dehydration and a diffusive exchange between slab-derived melt and mantle demonstrate that the δ7Li signatures of the sources can be preserved in the adakites if they ascent rapidly in mantle.
en-copyright=
kn-copyright=

en-aut-name=ZhangWei
en-aut-sei=Zhang
en-aut-mei=Wei
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=KitagawaHiroshi
en-aut-sei=Kitagawa
en-aut-mei=Hiroshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=NakamuraEizo
en-aut-sei=Nakamura
en-aut-mei=Eizo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

affil-num=1
en-affil=The Pheasant Memorial Laboratory for Geochemistry and Cosmochemistry, Institute for Planetary Materials, Okayama University
kn-affil=

affil-num=2
en-affil=The Pheasant Memorial Laboratory for Geochemistry and Cosmochemistry, Institute for Planetary Materials, Okayama University
kn-affil=

affil-num=3
en-affil=The Pheasant Memorial Laboratory for Geochemistry and Cosmochemistry, Institute for Planetary Materials, Okayama University
kn-affil=
en-keyword=SW Japan
kn-keyword=SW Japan
en-keyword=slab
kn-keyword=slab
en-keyword=lithium isotope
kn-keyword=lithium isotope
en-keyword=arc magma
kn-keyword=arc magma
en-keyword=melt transport
kn-keyword=melt transport
END