scholarly journals Improved simulation of 19th- and 20th-century North Atlantic hurricane frequency after correcting historical sea surface temperatures

2021 ◽  
Vol 7 (26) ◽  
pp. eabg6931
Author(s):  
Duo Chan ◽  
Gabriel A. Vecchi ◽  
Wenchang Yang ◽  
Peter Huybers
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
20Th Century ◽  
North Atlantic ◽  
Sea Surface ◽  
Model Data ◽  
Atmospheric Models ◽  
Decadal Variations ◽  
Hurricane Prediction ◽  
19Th And 20Th Century

Confidence in dynamical and statistical hurricane prediction is rooted in the skillful reproduction of hurricane frequency using sea surface temperature (SST) patterns, but an ensemble of high-resolution atmospheric simulation extending to the 1880s indicates model-data disagreements that exceed those expected from documented uncertainties. We apply recently developed corrections for biases in historical SSTs that lead to revisions in tropical to subtropical SST gradients by ±0.1°C. Revised atmospheric simulations have 20% adjustments in the decadal variations of hurricane frequency and become more consistent with observations. The improved simulation skill from revised SST estimates not only supports the utility of high-resolution atmospheric models for hurricane projections but also highlights the need for accurate estimates of past and future patterns of SST changes.

Optimizing COSMO_REA6 reanalysis radiation flux for a high resolution coastal ocean model

2020 ◽  
Author(s):  
Martin Vodopivec ◽  
Matjaž Ličer
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Atmospheric Model ◽  
Short Wave ◽  
Ocean Model ◽  
Sea Surface ◽  
Atmospheric Models ◽  
Fine Grid ◽  
Wave Flux

<p>When modelling coastal areas in high spatial resolution, it is also essential to obtain atmospheric forcing with suitably fine grid. The complex coastline and coastal orography exert strong influence on atmospheric fields, wind in particular, and the east Adriatic coast with numerous islands and coastal mountain ridges is a fine example. We decided to use a high resolution COSMO atmospheric reanalysis for our long term ROMS_AGRIF hindcasts, but in our initial experiments we found out that the atmospheric model significantly underestimates the short wave flux over the Mediterranean Sea, probably due to overestimation of high clouds formation and erroneous sea surface temperature used as a boundary condition. We explore different atmospheric models and different combinations of fluxes - direct, diffuse and clear sky solar radiation and combinations of fluxes from different atmospheric models (eg. ERA5). We compare them with solar irradiance observations at a coastal meteorological station and run year-long simulations to compare model sea surface temperature (SST) with satellite observations obtained from Coprenicus Marine Environment Monitoring Service.</p>

scholarly journals Decadal Variations of North Atlantic Sea Surface Temperature in Observations and CMIP3 Simulations*

2010 ◽  
Vol 23 (17) ◽  
pp. 4619-4636 ◽  
Author(s):  
Nathan Jamison ◽  
Sergey Kravtsov
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
North Atlantic ◽  
Climate Models ◽  
Decadal Variability ◽  
Singular Spectrum Analysis ◽  
Global Climate Models ◽  
Sea Surface ◽  
Decadal Variations

Abstract This study evaluates the ability of the global climate models that compose phase 3 of the Coupled Model Intercomparison Project (CMIP3) to simulate intrinsic decadal variations detected in the observed North Atlantic sea surface temperature (SST) record via multichannel singular spectrum analysis (M-SSA). M-SSA identifies statistically significant signals in the observed SSTs, with time scales of 5–10, 10–15, and 15–30 yr; all of these signals have distinctive spatiotemporal characteristics and are consistent with previous studies. Many of the CMIP3 twentieth-century simulations are characterized by quasi-oscillatory behavior within one or more of the three observationally motivated frequency bands specified above; however, only a fraction of these models also capture the spatial patterns of the observed signals. The models best reproduce the observed quasi-regular SST variations in the high-frequency, 5–10-yr band, while the observed signals in the intermediate, 10–15-yr band have turned out to be most difficult to capture. A handful of models capture the patterns and, sometimes, the spectral character of the observed variability in the two or three bands simultaneously. These results imply that the decadal prediction skill of the models considered—to be estimated within the CMIP5 framework—would be stratified according to the models’ performance in capturing the time scales and patterns of the observed decadal SST variations. They also warrant further research into the dynamical causes of the observed and simulated decadal variability, as well as into apparent differences in the representation of these variations by individual CMIP3 models.

scholarly journals A spatiotemporal reconstruction of sea-surface temperatures in the North Atlantic during Dansgaard–Oeschger events 5–8

2018 ◽  
Vol 14 (6) ◽  
pp. 901-922 ◽  
Author(s):  
Mari F. Jensen ◽  
Aleksi Nummelin ◽  
Søren B. Nielsen ◽  
Henrik Sadatzki ◽  
Evangeline Sessford ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
General Circulation ◽  
Sea Surface ◽  
Reconstruction Method ◽  
Sea Surface Temperatures ◽  
Proxy Data ◽  
Surface Temperatures ◽  
Temperature Reconstructions

Abstract. Here, we establish a spatiotemporal evolution of the sea-surface temperatures in the North Atlantic over Dansgaard–Oeschger (DO) events 5–8 (approximately 30–40 kyr) using the proxy surrogate reconstruction method. Proxy data suggest a large variability in North Atlantic sea-surface temperatures during the DO events of the last glacial period. However, proxy data availability is limited and cannot provide a full spatial picture of the oceanic changes. Therefore, we combine fully coupled, general circulation model simulations with planktic foraminifera based sea-surface temperature reconstructions to obtain a broader spatial picture of the ocean state during DO events 5–8. The resulting spatial sea-surface temperature patterns agree over a number of different general circulation models and simulations. We find that sea-surface temperature variability over the DO events is characterized by colder conditions in the subpolar North Atlantic during stadials than during interstadials, and the variability is linked to changes in the Atlantic Meridional Overturning circulation and in the sea-ice cover. Forced simulations are needed to capture the strength of the temperature variability and to reconstruct the variability in other climatic records not directly linked to the sea-surface temperature reconstructions. This is the first time the proxy surrogate reconstruction method has been applied to oceanic variability during MIS3. Our results remain robust, even when age uncertainties of proxy data, the number of available temperature reconstructions, and different climate models are considered. However, we also highlight shortcomings of the methodology that should be addressed in future implementations.

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