The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Alastair D Jenkins - One of the best experts on this subject based on the ideXlab platform.
-
computing cross isotherm volume transports from Ocean Temperature observations and surface heat fluxes with application to the barents sea inflow
Continental Shelf Research, 2010Co-Authors: Ole Henrik Segtnan, Tore Furevik, Alastair D JenkinsAbstract:A method for determining the cross-isotherm Ocean transport from surface heat flux and Ocean Temperature data is derived. By computing the volume flux through the isotherm that extend from 191E, 741N to the eastern part of the Kola Peninsula, the flow through the western entrance of the Barents Sea south of 741N is estimated. Using three different surface heat flux datasets, the inflow is found to range from 2.9 to 4.5Sv in winter (October‐March) and from 0.4 to 1.4Sv in summer (April‐ September; 1Sv! 10 6 m 3 s " 1 ). The seasonal variations are stronger than indicated by results from direct current measurements, probably because the seasonal cycle of the surface heat fluxes is overestimated along the considered isotherm. The annual mean inflow ranges from 1.9 to 2.2Sv during a cold period (1986‐1988), and from 2.4 to 3.0Sv during a warm period (1990‐1992), close to reported observations. & 2010 Elsevier Ltd. All rights reserved.
Carmen Boening - One of the best experts on this subject based on the ideXlab platform.
-
The impacts of cloud snow radiative effects on Pacific Ocean surface heat fluxes, surface wind stress, and Ocean Temperatures in coupled GCM simulations
Journal of Geophysical Research, 2015Co-Authors: J.-l. F. Li, Wei-liang Lee, Tong Lee, Terence L. Kubar, Jia-yuh Yu, Eric J Fetzer, Carmen BoeningAbstract:An accurate representation of the climatology of the coupled Ocean-atmosphere system in global climate models has strong implications for the reliability of projected climate change inferred by these models. Our previous efforts have identified substantial biases of Ocean surface wind stress that are fairly common in two generations of the Coupled Model Intercomparison Project (CMIP) models, relative to QuikSCAT climatology. One of the potential causes of the CMIP model biases is the missing representation of large frozen precipitating hydrometeors (i.e., cloud snow) in all CMIP3 and most CMIP5 models, which has not been investigated previously. We examine the impacts of cloud snow on the radiation and atmospheric circulation, air-sea fluxes, and explore the implications to common biases in CMIP models using the National Center for Atmospheric Research coupled Community Earth System Model (CESM) to perform sensitivity experiments with and without cloud snow radiative effects. This study focuses on the impacts of cloud snow in CESM on Ocean surface wind stress and air-sea heat fluxes, as well as their relationship with sea surface Temperature (SST) and subsurface Ocean Temperatures in the Pacific sector. It is found that inclusion of the cloud snow parameterization in CESM reduces the surface wind stress and upper Ocean Temperature (including SST) biases in the tropical and midlatitude Pacific. The differences in the upper Ocean Temperature with and without the cloud snow parameterization are consistent with the effect of different strength of vertical mixing due to Ocean surface wind stress differences but cannot be explained by the differences in net air-sea heat fluxes.
Tore Furevik - One of the best experts on this subject based on the ideXlab platform.
-
computing cross isotherm volume transports from Ocean Temperature observations and surface heat fluxes with application to the barents sea inflow
Continental Shelf Research, 2010Co-Authors: Ole Henrik Segtnan, Tore Furevik, Alastair D JenkinsAbstract:A method for determining the cross-isotherm Ocean transport from surface heat flux and Ocean Temperature data is derived. By computing the volume flux through the isotherm that extend from 191E, 741N to the eastern part of the Kola Peninsula, the flow through the western entrance of the Barents Sea south of 741N is estimated. Using three different surface heat flux datasets, the inflow is found to range from 2.9 to 4.5Sv in winter (October‐March) and from 0.4 to 1.4Sv in summer (April‐ September; 1Sv! 10 6 m 3 s " 1 ). The seasonal variations are stronger than indicated by results from direct current measurements, probably because the seasonal cycle of the surface heat fluxes is overestimated along the considered isotherm. The annual mean inflow ranges from 1.9 to 2.2Sv during a cold period (1986‐1988), and from 2.4 to 3.0Sv during a warm period (1990‐1992), close to reported observations. & 2010 Elsevier Ltd. All rights reserved.
Jinyi Yu - One of the best experts on this subject based on the ideXlab platform.
-
subsurface Ocean Temperature indices for central pacific and eastern pacific types of el nino and la nina events
Theoretical and Applied Climatology, 2011Co-Authors: Jinyi YuAbstract:Subsurface Ocean Temperature indices are developed to identify two distinct types of tropical Pacific warming (El Nino) and cooling (La Nina) events: the Eastern-Pacific (EP) type and the Central-Pacific (CP) type. Ocean Temperature anomalies in the upper 100 m are averaged over the eastern (80°W–90°W, 5°S–5°N) and central (160°E–150°W, 5°S–5°N) equatorial Pacific to construct the EP and CP subsurface indices, respectively. The analysis is performed for the period of 1958–2001 using an Ocean data assimilation product. It is found that the EP/CP subsurface indices are less correlated and show stronger skewness than the sea surface Temperature (SST)-based indices. In addition, while both quasi-biennial (∼2 years) and quasi-quadrennial (∼4 years) periodicities appear in the SST-based indices for these two types, the subsurface indices are dominated only by the quasi-biennial periodicity for the CP type and by the quasi-quadrennial (∼4 years) periodicity for the EP type. Low correlation, high skewness, and single leading periodicity are desirable properties for defining indices to separate the EP and CP types. Using the subsurface indices, major El Nino and La Nina events identified by the Nino-3.4 SST index are classified as the EP or CP types for the analysis period. It is found that most strong El Nino events are of the EP type while most strong La Nina events are of the CP type. It is also found that strong CP-type La Nina events tend to occur after strong EP-type El Nino events. The reversed subsequence (i.e., strong EP El Nino events follow strong CP La Nina events) does not appear to be typical. This study shows that subsurface Ocean indices are an effective way to identify the EP and CP types of Pacific El Nino and La Nina events.
-
subsurface Ocean Temperature indices for central pacific and eastern pacific types of el nino and la nina events
Theoretical and Applied Climatology, 2011Co-Authors: Jinyi YuAbstract:Subsurface Ocean Temperature indices are developed to identify two distinct types of tropical Pacific warming (El Nino) and cooling (La Nina) events: the Eastern-Pacific (EP) type and the Central-Pacific (CP) type. Ocean Temperature anomalies in the upper 100 m are averaged over the eastern (80°W–90°W, 5°S–5°N) and central (160°E–150°W, 5°S–5°N) equatorial Pacific to construct the EP and CP subsurface indices, respectively. The analysis is performed for the period of 1958–2001 using an Ocean data assimilation product. It is found that the EP/CP subsurface indices are less correlated and show stronger skewness than the sea surface Temperature (SST)-based indices. In addition, while both quasi-biennial (∼2 years) and quasi-quadrennial (∼4 years) periodicities appear in the SST-based indices for these two types, the subsurface indices are dominated only by the quasi-biennial periodicity for the CP type and by the quasi-quadrennial (∼4 years) periodicity for the EP type. Low correlation, high skewness, and single leading periodicity are desirable properties for defining indices to separate the EP and CP types. Using the subsurface indices, major El Nino and La Nina events identified by the Nino-3.4 SST index are classified as the EP or CP types for the analysis period. It is found that most strong El Nino events are of the EP type while most strong La Nina events are of the CP type. It is also found that strong CP-type La Nina events tend to occur after strong EP-type El Nino events. The reversed subsequence (i.e., strong EP El Nino events follow strong CP La Nina events) does not appear to be typical. This study shows that subsurface Ocean indices are an effective way to identify the EP and CP types of Pacific El Nino and La Nina events.
Tom Cowton - One of the best experts on this subject based on the ideXlab platform.
-
linear response of east greenland s tidewater glaciers to Ocean atmosphere warming
Proceedings of the National Academy of Sciences of the United States of America, 2018Co-Authors: Tom Cowton, Andrew Sole, Peter Nienow, Donald Slater, Poul ChristoffersenAbstract:Predicting the retreat of tidewater outlet glaciers forms a major obstacle to forecasting the rate of mass loss from the Greenland Ice Sheet. This reflects the challenges of modeling the highly dynamic, topographically complex, and data-poor environment of the glacier-fjord systems that link the ice sheet to the Ocean. To avoid these difficulties, we investigate the extent to which tidewater glacier retreat can be explained by simple variables: air Temperature, meltwater runoff, Ocean Temperature, and two simple parameterizations of "Ocean/atmosphere" forcing based on the combined influence of runoff and Ocean Temperature. Over a 20-y period at 10 large tidewater outlet glaciers along the east coast of Greenland, we find that Ocean/atmosphere forcing can explain up to 76% of the variability in terminus position at individual glaciers and 54% of variation in terminus position across all 10 glaciers. Our findings indicate that (i) the retreat of east Greenland's tidewater glaciers is best explained as a product of both Oceanic and atmospheric warming and (ii) despite the complexity of tidewater glacier behavior, over multiyear timescales a significant proportion of terminus position change can be explained as a simple function of this forcing. These findings thus demonstrate that simple parameterizations can play an important role in predicting the response of the ice sheet to future climate warming.