WRF-Chem modeling of sulfur dioxide emissions from the 2008 Kasatochi Volcano

We use the Weather Research Forecasting with Chemistry (WRF-Chem) model to simulate the evolution, dispersion and conversion of the sulfur dioxide (SO2) plume generated by the 2008 eruption of Kasatochi Volcano in Alaska, USA. About 1.7 Tg of SO2 were dispersed into the atmosphere during three distinct explosive events. Stratospheric sulfur dioxide conversion chemistry is detailed and model output is compared to remote sensing retrievals from the Ozone Monitoring Instrument (OMI). WRF-Chem generated SO2 column densities and plume locations similar to those from OMI retrievals as the plume traveled from the North Pacific through the continental United States and Canada. Analysis of SO2 conversion established an eight day lifetime of SO2 for the Kastaochi plume, which is a slightly shorter lifetime than derived by other modeling methods.

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The Use of Satellite Remote Sensing Data in Numerical Modeling of The North Pacific Circulation

Integrated Technologies for Environmental Monitoring and Information Production ◽

10.1007/978-94-010-0231-8_27 ◽

2003 ◽

pp. 351-368

Author(s):

V. Kuzin ◽

V. Moiseev ◽

A. Martynov

Keyword(s):

Remote Sensing ◽

Numerical Modeling ◽

North Pacific ◽

Satellite Remote Sensing ◽

Remote Sensing Data ◽

Sensing Data ◽

The North ◽

The North Pacific

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Statistical Characteristics of Cyclonic Warm-Core Eddies and Anticyclonic Cold-Core Eddies in the North Pacific Based on Remote Sensing Data

Remote Sensing ◽

10.3390/rs11020208 ◽

2019 ◽

Vol 11 (2) ◽

pp. 208 ◽

Cited By ~ 10

Author(s):

Wenjin Sun ◽

Changming Dong ◽

Wei Tan ◽

Yijun He

Keyword(s):

Remote Sensing ◽

North Pacific ◽

Kuroshio Extension ◽

Remote Sensing Data ◽

Statistical Characteristics ◽

The North ◽

Warm Core ◽

Spatio Temporal ◽

Cold Core ◽

The North Pacific

A (an) cyclonic (anticyclonic) eddy is usually associated with a cold (warm) core caused by the eddy-induced divergence (convergence) motion. However, there are also some cyclonic (anticyclonic) eddies with warm (cold) cores in the North Pacific, named cyclonic warm-core eddies (CWEs) and anticyclonic cold-core eddies (ACEs) in this study, respectively. Their spatio-temporal characteristics and regional dependence are analyzed using the multi-satellite merged remote sensing datasets. The CWEs are mainly concentrated in the northwestern and southeastern North Pacific. However, besides these two areas, the ACEs are also concentrated in the northeastern Pacific. The annual mean number decreases year by year for both CWEs and ACEs, and the decreasing rate of the CWEs is about two times as large as that of the ACEs. Moreover, the CWEs and ACEs also exhibit a significant seasonal variation, which are intense in summer and weak in winter. Based on the statistics of dynamic characteristics in seven subregions, the Kuroshio Extension region could be considered as the most active area for the CWEs and ACEs. Two possible mechanisms for CW-ACEs generation are discussed by analyzing two cases.

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Oceanographic characteristics of biological hot spots in the North Pacific: A remote sensing perspective

Deep Sea Research Part II Topical Studies in Oceanography ◽

10.1016/j.dsr2.2006.03.004 ◽

2006 ◽

Vol 53 (3-4) ◽

pp. 250-269 ◽

Cited By ~ 109

Author(s):

Daniel M. Palacios ◽

Steven J. Bograd ◽

David G. Foley ◽

Franklin B. Schwing

Keyword(s):

Remote Sensing ◽

North Pacific ◽

Hot Spots ◽

The North ◽

The North Pacific

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Acoustic remote sensing of large-scale temperature variability in the North Pacific Ocean

Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600) ◽

10.1109/oceans.2004.1406343 ◽

2005 ◽

Cited By ~ 2

Author(s):

B.M. Howe ◽

B.D. Cornuelle ◽

B.D. Dushaw ◽

M.A. Dzieciuch ◽

D. Menemenlis ◽

...

Keyword(s):

Remote Sensing ◽

Pacific Ocean ◽

North Pacific ◽

Large Scale ◽

North Pacific Ocean ◽

Temperature Variability ◽

The North ◽

Scale Temperature ◽

Acoustic Remote Sensing ◽

The North Pacific

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Reemergence Mechanisms for North Pacific Sea Ice Revealed through Nonlinear Laplacian Spectral Analysis*

Journal of Climate ◽

10.1175/jcli-d-13-00256.1 ◽

2014 ◽

Vol 27 (16) ◽

pp. 6265-6287 ◽

Cited By ~ 22

Author(s):

Mitchell Bushuk ◽

Dimitrios Giannakis ◽

Andrew J. Majda

Keyword(s):

Spectral Analysis ◽

Sea Ice ◽

North Pacific ◽

North Pacific Ocean ◽

Coupled Analysis ◽

Model Output ◽

The North ◽

Multiple Variables ◽

The North Pacific ◽

Sst Anomalies

Abstract This paper studies spatiotemporal modes of variability of sea ice concentration and sea surface temperature (SST) in the North Pacific sector in a comprehensive climate model and observations. These modes are obtained via nonlinear Laplacian spectral analysis (NLSA), a recently developed data analysis technique for high-dimensional nonlinear datasets. The existing NLSA algorithm is modified to allow for a scale-invariant coupled analysis of multiple variables in different physical units. The coupled NLSA modes are utilized to investigate North Pacific sea ice reemergence: a process in which sea ice anomalies originating in the melt season (spring) are positively correlated with anomalies in the growth season (fall) despite a loss of correlation in the intervening summer months. It is found that a low-dimensional family of NLSA modes is able to reproduce the lagged correlations observed in sea ice data from the North Pacific Ocean. This mode family exists in both model output and observations and is closely related to the North Pacific gyre oscillation (NPGO), a low-frequency pattern of North Pacific SST variability. Moreover, this mode family provides a mechanism for sea ice reemergence in which summer SST anomalies store the memory of spring sea ice anomalies, allowing for sea ice anomalies of the same sign to appear in the fall season. Lagged correlations in model output and observations are significantly strengthened by conditioning on the NPGO mode being active, in either positive or negative phase. Another family of NLSA modes, related to the Pacific decadal oscillation (PDO), is found to capture a winter-to-winter reemergence of SST anomalies.

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