Present and Past Sea Surface Temperatures: A Recipe for Better Seasonal Climate Forecasts

2020 ◽  
Vol 35 (4) ◽  
pp. 1221-1234
Author(s):  
Matthew B. Switanek ◽  
Joseph J. Barsugli ◽  
Michael Scheuerer ◽  
Thomas M. Hamill
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
The United States ◽  
Cold Season ◽  
Sea Surface ◽  
Precipitation Forecast ◽  
The North ◽  
Model Ensembles ◽  
Tropical Sea

AbstractMonthly tropical sea surface temperature (SST) data are used as predictors to make statistical forecasts of cold season (November–March) precipitation and temperature for the contiguous United States. Through the use of the combined-lead sea surface temperature (CLSST) model, predictive information is discovered not just in recent SSTs but also from SSTs up to 18 months prior. We find that CLSST cold season forecast anomaly correlation skill is higher than that of the North American Multimodel Ensemble (NMME) and the SEAS5 model from the European Centre for Medium-Range Weather Forecasts (ECMWF) when averaged over the United States for both precipitation and 2-m air temperature. The precipitation forecast skill obtained by CLSST in parts of the Intermountain West is of particular interest because of its implications for water resources. In those regions, CLSST dramatically improves the skill over that of the dynamical model ensembles, which can be attributed to a robust statistical response of precipitation in this region to SST anomalies from the previous year in the tropical Pacific.

scholarly journals Are paleoclimate model ensembles consistent with the MARGO data synthesis?

2011 ◽  
Vol 7 (2) ◽  
pp. 775-807 ◽  
Author(s):  
J. C. Hargreaves ◽  
A. Paul ◽  
R. Ohgaito ◽  
A. Abe-Ouchi ◽  
J. D. Annan
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temperature Data ◽  
Sea Surface ◽  
Data Synthesis ◽  
The North ◽  
Weak Evidence ◽  
Observational Uncertainty ◽  
Model Ensembles ◽  
Surface Temperature Data

Abstract. We investigate the consistency of various ensembles of model simulations with the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) sea surface temperature data synthesis. We discover that while two multi-model ensembles, created through the Paleoclimate Model Intercomparison Projects (PMIP and PMIP2), pass our simple tests of reliability, an ensemble based on parameter variation in a single model does not perform so well. We show that accounting for observational uncertainty in the MARGO database is of prime importance for correctly evaluating the ensembles. Perhaps surprisingly, the inclusion of a coupled dynamical ocean (compared to the use of a slab ocean) does not appear to cause a wider spread in the sea surface temperature anomalies, but rather causes systematic changes with more heat transported north in the Atlantic. There is weak evidence that the sea surface temperature data may be more consistent with meridional overturning in the North Atlantic being similar for the LGM and the present day, however, the small size of the PMIP2 ensemble prevents any statistically significant results from being obtained.

scholarly journals Summer aridity in the United States: Response to mid-Holocene changes in insolation and sea surface temperature

2006 ◽  
Vol 33 (22) ◽  
Author(s):  
Noah S. Diffenbaugh ◽  
Moetasim Ashfaq ◽  
Bryan Shuman ◽  
John W. Williams ◽  
Patrick J. Bartlein
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
The United States ◽  
Sea Surface

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.

Effects of tropical sea surface temperature variability on Northern Hemisphere tropical cyclone genesis

2021 ◽  
pp. 1-66
Author(s):  
Shuo Li ◽  
Wei Mei ◽  
Shang-Ping Xie
Keyword(s):  
Tropical Cyclone ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Northern Hemisphere ◽  
Sea Surface ◽  
Tropical Cyclone Genesis ◽  
The North ◽  
Meridional Mode ◽  
Cyclone Genesis ◽  
Tropical Sea

AbstractThis study quantifies the contributions of tropical sea surface temperature (SST) variations during the boreal warm season to the interannual-to-decadal variability in tropical cyclone genesis frequency (TCGF) over the Northern Hemisphere ocean basins. The first seven leading modes of tropical SST variability are found to affect basin-wide TCGF in one or more basins, and are related to canonical El Niño–Southern Oscillation (ENSO), global warming (GW), the Pacific Meridional Mode (PMM), Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Mode (AMM). These modes account for approximately 58%, 50% and 56% of the variance in basin-wide TCGF during 1969–2018 over the North Atlantic (NA), Northeast Pacific (NEP) and Northwest Pacific (NWP), respectively. The SST effect is weak on TCGF variability in the North Indian Ocean. The dominant SST modes differ among the basins: ENSO, the AMO, AMM and GW for the NA; ENSO and the AMO for the NEP; and the PMM, interannual AMO and GW for the NWP. A specific mode may have opposite effects on TCGF in different basins, particularly between the NA and NEP. Sliding-window multiple linear regression analyses show that the SST effects on basin-wide TCGF are stable in time in the NA and NWP, but strengthen after the mid-1970s in the NEP. The SST effects on local TC genesis and occurrence frequency are also explored, and the underlying physical mechanisms are examined by diagnosing a genesis potential index and its components.

scholarly journals Are paleoclimate model ensembles consistent with the MARGO data synthesis?

2011 ◽  
Vol 7 (3) ◽  
pp. 917-933 ◽  
Author(s):  
J. C. Hargreaves ◽  
A. Paul ◽  
R. Ohgaito ◽  
A. Abe-Ouchi ◽  
J. D. Annan
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Model ◽  
Temperature Data ◽  
Sea Surface ◽  
Data Synthesis ◽  
The North ◽  
Observational Uncertainty ◽  
Model Ensembles ◽  
Surface Temperature Data

Abstract. We investigate the consistency of various ensembles of climate model simulations with the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) sea surface temperature data synthesis. We discover that while two multi-model ensembles, created through the Paleoclimate Model Intercomparison Projects (PMIP and PMIP2), pass our simple tests of reliability, an ensemble based on parameter variation in a single model does not perform so well. We show that accounting for observational uncertainty in the MARGO database is of prime importance for correctly evaluating the ensembles. Perhaps surprisingly, the inclusion of a coupled dynamical ocean (compared to the use of a slab ocean) does not appear to cause a wider spread in the sea surface temperature anomalies, but rather causes systematic changes with more heat transported north in the Atlantic. There is weak evidence that the sea surface temperature data may be more consistent with meridional overturning in the North Atlantic being similar for the LGM and the present day. However, the small size of the PMIP2 ensemble prevents any statistically significant results from being obtained.

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