Global monthly sea surface temperature and sea ice reconstruction for historical simulations

2020 ◽  
Author(s):  
Eric Samakinwa ◽  
Stefan Brönnimann
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Sea Surface ◽  
Annual Variability ◽  
Instrumental Records

<p>Variability in Sea Surface Temperature (SST) is one of the prime sources of intra-annual variability, and also an important boundary condition for Atmospheric General Circulation Models (AGCMs). In many AGCM simulations, SST and Sea Ice Concentration (SIC) are prescribed. While SSTs are specified according to observations available in recent period of instrumental records (1850 – present), SIC depends on climatological averages with less variability prior to the inception of satellite measurements. This limits our understanding of large-scale climate variations in the past.</p><p>In this study, we augment multi-proxy reconstructed annual mean temperature of Neukom et al. (2019) with intra-annual variability from HadISST (v2.0), for 850 years (1000 – 1849). Intra-seasonal variability, such as the phase-locking of El-Nino Southern Oscillation, Indian Ocean Dipole and Tropical Atlantic SST indices to annual-cycle, are utilized. The intra-annual component of HadISST and SST indices estimated from the multi-proxy reconstructed annual mean, are used to develop grid-based multivariate linear regression models using the Frisch-Waugh-Lovell theorem, in a monthly stratified approach. Furthermore, we introduce a scaling technique to ensure homogeneous mean and variance, similar to that of the target. SST observations obtained from ship measurements by ICOADS before 1850, will be integrated in an off-line data assimilation approach.</p><p>Similarly, we reconstruct SIC via analogue resampling of HadISST SIC (1941 – 2000), for both hemispheres. We pool our analogues in four seasons, comprising of 3 months each, such that for each month within a season, there are 180 possible analogues. The best analogues are selected based on correlation coefficients between reconstructed SST and its target.</p>

scholarly journals Assessing bias corrections of oceanic surface conditions for atmospheric models

2019 ◽  
Vol 12 (1) ◽  
pp. 321-342 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
General Circulation Models ◽  
Substantial Improvement ◽  
Sea Surface ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Analogue Method

Abstract. Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC.

scholarly journals Assessing bias-corrections of oceanic surface conditions for atmospheric models

2017 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
General Circulation Models ◽  
Substantial Improvement ◽  
Sea Surface ◽  
Analog Method ◽  
Sea Ice Concentration ◽  
Ice Concentration

Abstract. Future sea–surface temperature and sea–ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcing for the downscaling of future climate experiment. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea–ice concentration (SIC) are presented. For SIC, we also propose a new analog method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiment and some real-case applications using observations. With respect to other previously existing methods for SIC, the analog method is a substantial improvement for the bias correction of future sea–ice concentrations.

scholarly journals North American April tornado occurrences linked to global sea surface temperature anomalies

2019 ◽  
Vol 5 (8) ◽  
pp. eaaw9950 ◽  
Author(s):  
J.-E. Chu ◽  
A. Timmermann ◽  
J.-Y. Lee
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North American ◽  
General Circulation ◽  
Large Scale ◽  
Moisture Flux ◽  
General Circulation Models ◽  
The United States ◽  
Sea Surface

Annual tornado occurrences over North America display large interannual variability and a statistical linkage to sea surface temperature (SST) anomalies. However, the underlying physical mechanisms for this connection and its modulation in a rapidly varying seasonal environment still remain elusive. Using tornado data over the United States from 1954 to 2016 in combination with SST-forced atmospheric general circulation models, we show a robust dynamical linkage between global SST conditions in April, the emergence of the Pacific-North American teleconnection pattern (PNA), and the year-to-year tornado activity in the Southern Great Plains (SGP) region of the United States. Contrasting previous studies, we find that only in April SST-driven atmospheric circulation anomalies can effectively control the northward moisture-laden flow from the Gulf of Mexico, boosting low-level moisture flux convergence over the SGP. These strong large-scale connections are absent in other months because of the strong seasonality of the PNA and background moisture conditions.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals An objective tropical Atlantic sea surface temperature gradient index for studies of south Amazon dry-season climate variability and change

2008 ◽  
Vol 363 (1498) ◽  
pp. 1761-1766 ◽  
Author(s):  
Peter Good ◽  
Jason A Lowe ◽  
Mat Collins ◽  
Wilfran Moufouma-Okia
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Dry Season ◽  
Sea Surface ◽  
Tropical Atlantic ◽  
Sst Gradient

Future changes in meridional sea surface temperature (SST) gradients in the tropical Atlantic could influence Amazon dry-season precipitation by shifting the patterns of moisture convergence and vertical motion. Unlike for the El Niño-Southern Oscillation, there are no standard indices for quantifying this gradient. Here we describe a method for identifying the SST gradient that is most closely associated with June–August precipitation over the south Amazon. We use an ensemble of atmospheric general circulation model (AGCM) integrations forced by observed SST from 1949 to 2005. A large number of tropical Atlantic SST gradient indices are generated randomly and temporal correlations are examined between these indices and June–August precipitation averaged over the Amazon Basin south of the equator. The indices correlating most strongly with June–August southern Amazon precipitation form a cluster of near-meridional orientation centred near the equator. The location of the southern component of the gradient is particularly well defined in a region off the Brazilian tropical coast, consistent with known physical mechanisms. The chosen index appears to capture much of the Atlantic SST influence on simulated southern Amazon dry-season precipitation, and is significantly correlated with observed southern Amazon precipitation. We examine the index in 36 different coupled atmosphere–ocean model projections of climate change under a simple compound 1% increase in CO 2 . Within the large spread of responses, we find a relationship between the projected trend in the index and the Amazon dry-season precipitation trends. Furthermore, the magnitude of the trend relationship is consistent with the inter-annual variability relationship found in the AGCM simulations. This suggests that the index would be of use in quantifying uncertainties in climate change in the region.

scholarly journals Can oceanic paleothermometers reconstruct the Atlantic Multidecadal Oscillation?

2011 ◽  
Vol 7 (1) ◽  
pp. 151-159 ◽  
Author(s):  
D. Heslop ◽  
A. Paul
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Climate Model ◽  
Low Frequency ◽  
Atlantic Multidecadal Oscillation ◽  
Sea Surface ◽  
Prediction Errors ◽  
The Past ◽  
Instrumental Records

Abstract. Instrumental records of the North Atlantic sea surface temperature reveal a large-scale low frequency mode of variability that has become known as the Atlantic Multidecadal Oscillation (AMO). Proxy and modelling studies have demonstrated the important consequences of the AMO on other components of the climate system both within and outside the Atlantic region. Over longer time scales, the past behavior of the AMO is predominantly constrained by terrestrial proxies and only a limited number of records are available from the marine realm itself. Here we use an Earth System-Climate Model of intermediate complexity to simulate AMO-type behavior in the Atlantic with a specific focus placed on the ability of ocean paleothermometers to capture the associated surface and subsurface temperature variability. Given their lower prediction errors and annual resolution, coral-based proxies of sea surface temperature appear to be capable of reconstructing the temperature variations associated with the past AMO with an adequate signal-to-noise ratio. In contrast, the relatively high prediction error and low temporal resolution of sediment-based proxies, such as the composition of foraminiferal calcite, limits their ability to produce interpretable records of past temperature anomalies corresponding to AMO activity. Whilst the presented results will inevitably be model-dependent to some degree, the statistical framework is model-independent and can be applied to a wide variety of scenarios.

scholarly journals Using an AGCM to Diagnose Historical Effective Radiative Forcing and Mechanisms of Recent Decadal Climate Change

2014 ◽  
Vol 27 (3) ◽  
pp. 1193-1209 ◽  
Author(s):  
Timothy Andrews
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Radiative Forcing ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Aerosol Forcing ◽  
Effective Radiative Forcing

Abstract An atmospheric general circulation model is forced with observed monthly sea surface temperature and sea ice boundary conditions, as well as forcing agents that vary in time, for the period 1979–2008. The simulations are then repeated with various forcing agents, individually and in combination, fixed at preindustrial levels. The simple experimental design allows the diagnosis of the model’s global and regional time-varying effective radiative forcing from 1979 to 2008 relative to preindustrial levels. Furthermore the design can be used to (i) calculate the atmospheric model’s feedback/sensitivity parameters to observed changes in sea surface temperature and (ii) separate those aspects of climate change that are directly driven by the forcing from those driven by large-scale changes in sea surface temperature. It is shown that the atmospheric response to increased radiative forcing over the last 3 decades has halved the global precipitation response to surface warming. Trends in sea surface temperature and sea ice are found to contribute only ~60% of the global land, Northern Hemisphere, and summer land warming trends. Global effective radiative forcing is ~1.5 W m−2 in this model, with anthropogenic and natural contributions of ~1.3 and ~0.2 W m−2, respectively. Forcing increases by ~0.5 W m−2 decade−1 over the period 1979–2008 or ~0.4 W m−2 decade−1 if years strongly influenced by volcanic forcings—which are nonlinear with time—are excluded from the trend analysis. Aerosol forcing shows little global decadal trend due to offsetting regional trends whereby negative aerosol forcing weakens in Europe and North America but continues to strengthen in Southeast Asia.

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