scholarly journals Mechanisms Controlling Global Mean Sea Surface Temperature Determined From a State Estimate

2018 ◽  
Vol 45 (7) ◽  
pp. 3221-3227 ◽  
Author(s):  
R. M. Ponte ◽  
C. G. Piecuch
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
State Estimate ◽  
Mean Sea Surface ◽  
Global Mean

scholarly journals Centennial-Scale Sea Surface Temperature Analysis and Its Uncertainty

2014 ◽  
Vol 27 (1) ◽  
pp. 57-75 ◽  
Author(s):  
Shoji Hirahara ◽  
Masayoshi Ishii ◽  
Yoshikazu Fukuda
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Specific Area ◽  
Sea Surface ◽  
Sampling Errors ◽  
Sea Ice Concentration ◽  
Sst Variability ◽  
Analysis Errors ◽  
Global Mean

Abstract A new sea surface temperature (SST) analysis on a centennial time scale is presented. In this analysis, a daily SST field is constructed as a sum of a trend, interannual variations, and daily changes, using in situ SST and sea ice concentration observations. All SST values are accompanied with theory-based analysis errors as a measure of reliability. An improved equation is introduced to represent the ice–SST relationship, which is used to produce SST data from observed sea ice concentrations. Prior to the analysis, biases of individual SST measurement types are estimated for a homogenized long-term time series of global mean SST. Because metadata necessary for the bias correction are unavailable for many historical observational reports, the biases are determined so as to ensure consistency among existing SST and nighttime air temperature observations. The global mean SSTs with bias-corrected observations are in agreement with those of a previously published study, which adopted a different approach. Satellite observations are newly introduced for the purpose of reconstruction of SST variability over data-sparse regions. Moreover, uncertainty in areal means of the present and previous SST analyses is investigated using the theoretical analysis errors and estimated sampling errors. The result confirms the advantages of the present analysis, and it is helpful in understanding the reliability of SST for a specific area and time period.

scholarly journals Mean sea surface temperature changes influence ENSO-related precipitation changes in the mid-latitudes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Young-Min Yang ◽  
Jae-Heung Park ◽  
Soon-Il An ◽  
Bin Wang ◽  
Xiao Luo
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Sea Surface ◽  
Future Global Warming ◽  
Mean Sea Surface ◽  
El Niño Events ◽  
Precipitation Changes ◽  
El Nino Events

AbstractEl Niño profoundly impacts precipitation in high-population regions. This demands an advanced understanding of the changes in El Niño-induced precipitation under the future global warming scenario. However, thus far, consensus is lacking regarding future changes in mid-latitude precipitation influenced by El Niño. Here, by analyzing the Coupled Model Intercomparison Project simulations, we show that future precipitation changes are tightly linked to the response of each type of El Niño to the tropical Pacific mean sea surface temperature (SST) change. A La Niña-like mean SST change intensifies basin-wide El Niño events causing approximately 20% more precipitation over East Asia and North America via enhancing moisture transport. Meanwhile, an El Niño-like mean SST change generates more frequent eastern Pacific El Niño events, enhancing precipitation in North American. Our findings highlight the importance of the mean SST projection in selectively influencing the types of El Niño and their remote impact on precipitation.

scholarly journals Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4): Part II. Parametric and Structural Uncertainty Estimations

2015 ◽  
Vol 28 (3) ◽  
pp. 931-951 ◽  
Author(s):  
Wei Liu ◽  
Boyin Huang ◽  
Peter W. Thorne ◽  
Viva F. Banzon ◽  
Huai-Min Zhang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Spatial Scales ◽  
Parametric Uncertainty ◽  
Sea Surface ◽  
Parametric Uncertainties ◽  
Structural Uncertainty ◽  
Uncertainty Estimates ◽  
Global Mean

Abstract Described herein is the parametric and structural uncertainty quantification for the monthly Extended Reconstructed Sea Surface Temperature (ERSST) version 4 (v4). A Monte Carlo ensemble approach was adopted to characterize parametric uncertainty, because initial experiments indicate the existence of significant nonlinear interactions. Globally, the resulting ensemble exhibits a wider uncertainty range before 1900, as well as an uncertainty maximum around World War II. Changes at smaller spatial scales in many regions, or for important features such as Niño-3.4 variability, are found to be dominated by particular parameter choices. Substantial differences in parametric uncertainty estimates are found between ERSST.v4 and the independently derived Hadley Centre SST version 3 (HadSST3) product. The largest uncertainties are over the mid and high latitudes in ERSST.v4 but in the tropics in HadSST3. Overall, in comparison with HadSST3, ERSST.v4 has larger parametric uncertainties at smaller spatial and shorter time scales and smaller parametric uncertainties at longer time scales, which likely reflects the different sources of uncertainty quantified in the respective parametric analyses. ERSST.v4 exhibits a stronger globally averaged warming trend than HadSST3 during the period of 1910–2012, but with a smaller parametric uncertainty. These global-mean trend estimates and their uncertainties marginally overlap. Several additional SST datasets are used to infer the structural uncertainty inherent in SST estimates. For the global mean, the structural uncertainty, estimated as the spread between available SST products, is more often than not larger than the parametric uncertainty in ERSST.v4. Neither parametric nor structural uncertainties call into question that on the global-mean level and centennial time scale, SSTs have warmed notably.

A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model

2008 ◽  
Vol 21 (19) ◽  
pp. 5145-5153 ◽  
Author(s):  
James W. Hurrell ◽  
James J. Hack ◽  
Dennis Shea ◽  
Julie M. Caron ◽  
James Rosinski
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Surface Boundary ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Community Atmosphere Model ◽  
Mean Sea Surface ◽  
Atmosphere Model

Abstract A new surface boundary forcing dataset for uncoupled simulations with the Community Atmosphere Model is described. It is a merged product based on the monthly mean Hadley Centre sea ice and SST dataset version 1 (HadISST1) and version 2 of the National Oceanic and Atmospheric Administration (NOAA) weekly optimum interpolation (OI) SST analysis. These two source datasets were also used to supply ocean surface information to the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40). The merged product provides monthly mean sea surface temperature and sea ice concentration data from 1870 to the present: it is updated monthly, and it is freely available for community use. The merging procedure was designed to take full advantage of the higher-resolution SST information inherent in the NOAA OI.v2 analysis.

scholarly journals Diurnal Restratification Events in the Southeast Pacific Trade Wind Regime

2014 ◽  
Vol 44 (9) ◽  
pp. 2569-2587 ◽  
Author(s):  
Robert A. Weller ◽  
Sudip Majumder ◽  
Amit Tandon
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Trade Wind ◽  
Upper Ocean ◽  
Surface Mixed Layer ◽  
Wind Regime ◽  
Trade Winds ◽  
Near Surface ◽  
Mean Sea Surface

Abstract This paper describes the occurrence of diurnal restratification events found in the southeast trade wind regime off northern Chile. This is a region where persistent marine stratus clouds are found and where there is a less than complete understanding of the dynamics that govern the maintenance of the sea surface temperature. A surface mooring deployed in the region provides surface meteorological, air–sea flux, and upper-ocean temperature, salinity, and velocity data. In the presence of steady southeast trade winds and strong evaporation, a warm, salty surface mixed layer is found in the upper ocean. During the year, these trade winds, at times, drop dramatically and surface heating leads to the formation of shallow, warm diurnal mixed layers over one to several days. At the end of such a low wind period, mean sea surface temperature is warmer. Though magnitudes of the individual diurnal warming events are consistent with local forcing, as judged by running a one-dimensional model, the net warming at the end of a low wind event is more difficult to predict. This is found to stem from differences between the observed and predicted near-inertial shear and the depths over which the warmed water is distributed. As a result, the evolution of SST has a dependency on these diurnal restratification events and on near-surface processes that govern the depth over which the heat gained during such events is distributed.

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