scholarly journals A study of the chilean vertical network through global geopotential models and the cnes cls 2011 global mean sea surface

2014 ◽  
Vol 20 (2) ◽  
pp. 300-316 ◽  
Author(s):  
Henry Montecino Castro ◽  
Aharon Cuevas Cordero ◽  
Sílvio Rogério Correia de Freitas
Keyword(s):  
Vertical Component ◽  
Sea Surface ◽  
Tide Gauges ◽  
Satellite Mission ◽  
Geopotential Models ◽  
Mean Sea Surface ◽  
The Mean ◽  
Combining Information ◽  
Global Mean ◽  
Goce Satellite

Most aspects related to the horizontal component of the Geocentric Reference System for the Americas (SIRGAS) have been solved. However, in the case of the vertical component there are still aspects of definition, national realizations and continental unification still not accomplished. Chile is no exception; due to its particular geographic characteristics, a number of tide gauges (TG) had to be installed in the coast from which the leveling lines that compose the Chilean Vertical Network (CHVN) were established. This study explored the offsets of the CHVN by two different approaches; one geodetic and one oceanographic. In the first approach, the offsets were obtained in relation to the following Global Geopotential Models (GGM): the satellite-only model (unbiased) GO_CONS_gcf_2_tim_r3 derived from GOCE satellite mission; EGM2008 (combined-biased); and GOEGM08, combining information from the GO_CONS_gcf_2_tim_r3 in long wavelengths (n max~200) with the mean/short wavelengths of EGM2008 (n>200). In the oceanographic method, we used the CNES CLS 2011 Global Mean Sea surface and EIGEN_GRACE_5C GGM to obtain the values of MDT at the different TG. We also evaluated the CHVN in relation to different GGMs. The results showed consistency between the values obtained by the two methods at the TG of Valparaíso and Puerto Chacabuco. In terms of the evaluation of the GGM, GOEGM08 produced the best results.

scholarly journals Analysis of the Model Climate Sensitivity Spread Forced by Mean Sea Surface Temperature Biases

2012 ◽  
Vol 25 (20) ◽  
pp. 7147-7162 ◽  
Author(s):  
Dietmar Dommenget
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Response Amplitude ◽  
Sea Surface ◽  
Model Simulations ◽  
Large Spread ◽  
Mean Sea Surface ◽  
The Mean ◽  
Global Mean ◽  
Mean State

Abstract Uncertainties in the numerical realization of the physical climate system in coarse-resolution climate models in the Coupled Model Intercomparison Project phase 3 (CMIP3) cause large spread in the global mean and regional response amplitude to a given anthropogenic forcing scenario, and they cause the climate models to have mean state climates different from the observed and different from each other. In a series of sensitivity simulations with an atmospheric general circulation model coupled to a Slab Ocean Model, the role of differences in the control mean sea surface temperature (SST) in simulating the global mean and regional response amplitude is explored. The model simulations are forced into the control mean state SST of 24 CMIP3 climate models, and 2xCO2 forcing experiments are started from the different control states. The differences in the SST mean state cause large differences in other climate variables, but they do not reproduce most of the large spread in the mean state climate over land and ice-covered regions found in the CMIP3 model simulations. The spread in the mean SST climatology leads to a spread in the global mean and regional response amplitude of about 10%, which is about half as much as the spread in the response of the CMIP3 climate models and is therefore of considerable size. Since the SST climatology biases are only a small part of the models’ mean state climate biases, it is likely that the climate model’s mean state climate biases are accounting for a large part of the model’s climate sensitivity spread.

scholarly journals Lessons from a high CO2 world: an ocean view from ~3 million years ago

2020 ◽  
Author(s):  
Erin McClymont ◽  
Heather Ford ◽  
Sze Ling Ho ◽  
Julia Tindall ◽  
Alan Haywood ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
North Atlantic ◽  
Spatial Scales ◽  
Climate System ◽  
Sea Surface ◽  
System Response ◽  
Emission Scenarios ◽  
Proxy Data ◽  
Mean Sea Surface ◽  
Global Mean

<p>A range of future climate scenarios are projected for high atmospheric CO<sub>2</sub> concentrations, given uncertainties over future human actions as well as potential environmental and climatic feedbacks. The geological record offers an opportunity to understand climate system response to a range of forcings and feedbacks which operate over multiple temporal and spatial scales. Here, we examine a single interglacial during the late Pliocene (KM5c, ca. 3.205 +/- 0.01 Ma) when atmospheric CO<sub>2</sub> concentrations were higher than pre-industrial, but similar to today and to the lowest emission scenarios for this century. As orbital forcing and continental configurations were almost identical to today, we are able to focus on equilibrium climate system response to modern and near-future CO<sub>2</sub>. Using proxy data from 32 sites, we demonstrate that global mean sea-surface temperatures were warmer than pre-industrial, by ~2.3 ºC for the combined proxy data (foraminifera Mg/Ca and alkenones), or by ~3.2ºC (alkenones only). Compared to the pre-industrial, reduced meridional gradients and enhanced warming in the North Atlantic are consistently reconstructed. There is broad agreement between data and models at the global scale, with regional differences reflecting ocean circulation and/or proxy signals. An uneven distribution of proxy data in time and space does, however, add uncertainty to our anomaly calculations. The reconstructed global mean sea-surface temperature anomaly for KM5c is warmer than all but three of the PlioMIP2 model outputs, and the reconstructed North Atlantic data tend to align with the warmest KM5c model values.  Our results demonstrate that even under low CO<sub>2</sub> emission scenarios, surface ocean warming may be expected to exceed model projections, and will be accentuated in the higher latitudes.</p>

scholarly journals Impacts of mean dynamic topography on a regional ocean assimilation system

Ocean Science ◽  
2015 ◽  
Vol 11 (5) ◽  
pp. 829-837 ◽  
Author(s):  
C. Yan ◽  
J. Zhu ◽  
C. A. S. Tanajura
Keyword(s):  
Data Assimilation ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Dynamic Topography ◽  
Altimetry Data ◽  
Mean Dynamic Topography ◽  
Mean Sea Surface ◽  
The Mean

Abstract. An ocean data assimilation system was developed for the Pacific–Indian oceans with the aim of assimilating altimetry data, sea surface temperature, and in situ measurements from Argo (Array for Real-time Geostrophic Oceanography), XBT (expendable bathythermographs), CTD (conductivity temperature depth), and TAO (Tropical Atmosphere Ocean). The altimetry data assimilation requires the addition of the mean dynamic topography to the altimetric sea level anomaly to match the model sea surface height. The mean dynamic topography is usually computed from the model long-term mean sea surface height, and is also available from gravimetric satellite data. In this study, the impact of different mean dynamic topographies on the sea level anomaly assimilation is examined. Results show that impacts of the mean dynamic topography cannot be neglected. The mean dynamic topography from the model long-term mean sea surface height without assimilating in situ observations results in worsened subsurface temperature and salinity estimates. Even if all available observations including in situ measurements, sea surface temperature measurements, and altimetry data are assimilated, the estimates are still not improved. This proves the significant impact of the MDT (mean dynamic topography) on the analysis system, as the other types of observations do not compensate for the shortcoming due to the altimetry data assimilation. The gravimeter-based mean dynamic topography results in a good estimate compared with that of the experiment without assimilation. The mean dynamic topography computed from the model long-term mean sea surface height after assimilating in situ observations presents better results.

A global mean sea surface based upon GEOS 3 and Seasat altimeter data

1992 ◽  
Vol 97 (B4) ◽  
pp. 4915 ◽  
Author(s):  
J. G. Marsh ◽  
C. J. Koblinsky ◽  
H. J. Zwally ◽  
A. C. Brenner ◽  
B. D. Beckley
Keyword(s):  
Sea Surface ◽  
Altimeter Data ◽  
Mean Sea Surface ◽  
Global Mean

High-resolution numerical modelling of the altimetry-derived gravity disturbances and disturbing gradients

2020 ◽  
Author(s):  
Róbert Čunderlík ◽  
Marek Macák ◽  
Michal Kollár ◽  
Karol Mikula
Keyword(s):  
High Resolution ◽  
Numerical Solution ◽  
Finite Volume ◽  
Sea Surface ◽  
Computational Domain ◽  
Disturbing Potential ◽  
Gravity Disturbances ◽  
Mean Sea Surface ◽  
Upper Boundary ◽  
Goce Satellite

<p>Recent high-resolution mean sea surface models obtained from satellite altimetry in a combination with the GRACE/GOCE-based global geopotential models provide valuable information for detailed modelling of the altimetry-derived gravity data. Our approach is based on a numerical solution of the altimetry-gravimetry boundary-value problem using the finite volume method (FVM). FVM discretizes the 3D computational domain between an ellipsoidal approximation of the Earth's surface and an upper boundary chosen at a mean altitude of the GOCE satellite orbits. A parallel implementation of the finite volume numerical scheme and large-scale parallel computations on clusters with distributed memory allow to get a high-resolution numerical solution in the whole 3D computational domain. Our numerical experiment presents the altimetry-derived gravity disturbances and disturbing gradients determined with the high-resolution 1 x 1 arc min at two altitude levels; on the reference ellipsoid and at the altitude of 10 km above the ellipsoid. As input data, the Dirichlet boundary conditions over oceans/seas are considered in the form of the disturbing potential. It is obtained from the geopotential evaluated on the DTU18 mean sea surface model from the GO_CONS_GCF_2_TIM_R5 geopotential model and then filtered using the nonlinear diffusion filtering. On the upper boundary, the FVM solution is fixed to the disturbing potential generated from the GO_CONS_GCF_2_DIR_R5 model while exploiting information from the GRACE and GOCE satellite missions.</p>

scholarly journals Pre-industrial and mid-Pliocene simulations with NorESM-L

2012 ◽  
Vol 5 (2) ◽  
pp. 523-533 ◽  
Author(s):  
Z. S. Zhang ◽  
K. Nisancioglu ◽  
M. Bentsen ◽  
J. Tjiputra ◽  
I. Bethke ◽  
...  
Keyword(s):  
Surface Air Temperature ◽  
Sea Surface ◽  
System Model ◽  
Test Case ◽  
Earth System ◽  
Warm Climate ◽  
Mean Sea Surface ◽  
Global Mean ◽  
Term Response

Abstract. The mid-Pliocene period (3.3 to 3.0 Ma) is known as a warm climate with atmospheric greenhouse gas levels similar to the present. As the climate at this time was in equilibrium with the greenhouse forcing, it is a valuable test case to better understand the long-term response to high levels of atmospheric greenhouse gases. In this study, we use the low resolution version of the Norwegian Earth System Model (NorESM-L) to simulate the pre-industrial and the mid-Pliocene climate. Comparison of the simulation with observations demonstrates that NorESM-L simulates a realistic pre-industrial climate. The simulated mid-Pliocene global mean surface air temperature is 16.7 °C, which is 3.2 °C warmer than the pre-industrial. The simulated mid-Pliocene global mean sea surface temperature is 19.1 °C, which is 2.0 °C warmer than the pre-industrial. The warming is relatively uniform globally, except for a strong amplification at high latitudes.

scholarly journals An Oceanographer's Guide to GOCE and the Geoid

Ocean Science ◽  
2008 ◽  
Vol 4 (1) ◽  
pp. 15-29 ◽  
Author(s):  
C. W. Hughes ◽  
R. J. Bingham
Keyword(s):  
Gravitational Field ◽  
Spherical Harmonic ◽  
Gravity Data ◽  
Reference Ellipsoid ◽  
Sea Surface ◽  
Dynamic Topography ◽  
Satellite Mission ◽  
Satellite Gravity ◽  
Ocean Models ◽  
Goce Satellite

Abstract. A review is given of the geodetic concepts necessary for oceanographers to make use of satellite gravity data to define the geoid, and to interpret the resulting product. The geoid is defined, with particular attention to subtleties related to the representation of the permanent tide, and the way in which the geoid is represented in ocean models. The usual spherical harmonic description of the gravitational field is described, together with the concepts required to calculate a geoid from the spherical harmonic coefficients. A brief description is given of the measurement system in the GOCE satellite mission, scheduled for launch shortly. Finally, a recipe is given for calculation of the ocean dynamic topography, given a map of sea surface height above a reference ellipsoid, a set of spherical harmonic coefficients for the gravitational field, and defining constants.

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