scholarly journals Long-range persistence in sea surface temperature off the coast of central California

2019 ◽  
Vol 9 ◽  
pp. 175931311879111 ◽  
Author(s):  
Laurence C Breaker
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Long Range ◽  
Time Scales ◽  
Sea Surface ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Scaling Exponents ◽  
Central California ◽  
Pacific Grove

We estimate long-range persistence in ocean surface temperature off the coast of central California, a region where similar observations have not been made. The database consists of 20-year records of daily sea surface temperature from three locations: Pacific Grove and Granite Canyon along the coast, and Southeast Farallon Island located 40 km off the coast and slightly further north. Long-range persistence is important for a number of reasons: on the negative side, it can have serious detrimental effects for statistical inference and on the positive side, it provides access to the ocean’s memory which can lead to a greater understanding of the processes involved and thus to better prediction. Long-range persistence also provides important insights into the relationship between the scaling that is obtained and the time scales employed. The first step in the analysis was to remove the annual cycle from the data at each location because of its detrimental effect on estimating long-range persistence. Then detrended fluctuation analysis was used to calculate long-range persistence where a single scaling exponent is obtained that relates the magnitudes of the fluctuations in the data to the time scales involved. Similar scaling exponents were obtained for Granite Canyon and Pacific Grove with values of 1.04 and 1.05, respectively. At Southeast Farallon Island, a value of 1.16 was obtained. The increase in the scaling exponent at Southeast Farallon Island is consistent with observations made elsewhere and model results, which indicate that as coastal influence decreases further offshore, the scaling exponents for sea surface temperature tend to increase. Because Southeast Farallon Island is exposed to subarctic waters offshore, whereas Pacific Grove and Granite Canyon are exposed to warmer waters from the California Undercurrent along the coast, these exposures to different water masses may contribute to the observed change in scaling behavior.

scholarly journals Environmental Factors Affecting Tropical Cyclone Power Dissipation

2007 ◽  
Vol 20 (22) ◽  
pp. 5497-5509 ◽  
Author(s):  
Kerry Emanuel
Keyword(s):  
Tropical Cyclone ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
North Pacific ◽  
Wind Shear ◽  
Western North Pacific ◽  
Vertical Wind Shear ◽  
Sea Surface ◽  
Strongly Correlated

Abstract Revised estimates of kinetic energy production by tropical cyclones in the Atlantic and western North Pacific are presented. These show considerable variability on interannual-to-multidecadal time scales. In the Atlantic, variability on time scales of a few years and more is strongly correlated with tropical Atlantic sea surface temperature, while in the western North Pacific, this correlation, while still present, is considerably weaker. Using a combination of basic theory and empirical statistical analysis, it is shown that much of the variability in both ocean basins can be explained by variations in potential intensity, low-level vorticity, and vertical wind shear. Potential intensity variations are in turn factored into components related to variations in net surface radiation, thermodynamic efficiency, and average surface wind speed. In the Atlantic, potential intensity, low-level vorticity, and vertical wind shear strongly covary and are also highly correlated with sea surface temperature, at least during the period in which reanalysis products are considered reliable. In the Pacific, the three factors are not strongly correlated. The relative contributions of the three factors are quantified, and implications for future trends and variability of tropical cyclone activity are discussed.

Sea Surface Temperature–Precipitation Relationship in Different Reanalyses

2013 ◽  
Vol 141 (3) ◽  
pp. 1118-1123 ◽  
Author(s):  
Arun Kumar ◽  
Li Zhang ◽  
Wanqiu Wang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Department Of Energy ◽  
Sea Surface ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Temperature And Precipitation ◽  
The Relationship ◽  
Modern Era

Abstract The focus of this investigation is how the relationship at intraseasonal time scales between sea surface temperature and precipitation (SST–P) varies among different reanalyses. The motivation for this work was spurred by a recent report that documented that the SST–P relationship in Climate Forecast System Reanalysis (CFSR) was much closer to that in the observation than it was for the older generation of reanalyses [i.e., NCEP–NCAR reanalysis (R1) and NCEP–Department of Energy (DOE) reanalysis (R2)]. Further, the reason was attributed either to the fact that the CFSR is a partially coupled reanalysis, while R1 and R2 are atmospheric-alone reanalyses, or that R1 and R2 use the observed weekly-averaged SST. The authors repeated the comparison of the SST–P relationship among R1, R2, and CFSR, as well as two recent generations of atmosphere-alone reanalyses, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the ECMWF Re-Analysis Interim (ERA-Interim). The results clearly demonstrate that the differences in the SST–P relationship at intraseasonal time scales across different reanalyses are not due to whether the reanalysis system is coupled or atmosphere alone, but are due to the specification of different SSTs. The SST–P relationship in different reanalyses, when computed against a single SST for the benchmark, demonstrates a relationship that is common across all of the reanalyses and observations.

Progress in Monthly Climate Forecasting with a Physical Model

1981 ◽  
Vol 62 (12) ◽  
pp. 1666-1675 ◽  
Author(s):  
Julian Adem ◽  
William L. Donn
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Physical Model ◽  
Long Range ◽  
Surface Albedo ◽  
Sea Surface ◽  
Climate Forecasting ◽  
Temperature And Precipitation ◽  
Ice Conditions

A long-range forecasting technique, based on a physical model that emphasizes thermodynamics, is applied to the prediction of anomalies of temperature and precipitation for the Northern Hemisphere. Monthly forecasts are initialized with the sea surface temperature, 700 mb temperature and surface albedo, including variable snow-ice conditions. Application to the hot spell and drought in the summer of 1980 for the contiguous United States shows very encouraging skill when verified for the standard 100-station NOAA grid.

scholarly journals An Analysis of the Nonstationarity in the Bias of Sea Surface Temperature Forecasts for the NCEP Climate Forecast System (CFS) Version 2

2012 ◽  
Vol 140 (9) ◽  
pp. 3003-3016 ◽  
Author(s):  
A. Kumar ◽  
M. Chen ◽  
L. Zhang ◽  
W. Wang ◽  
Y. Xue ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Long Range ◽  
Initial Conditions ◽  
Sea Surface ◽  
Climate Forecast ◽  
Prediction System ◽  
Forecast System ◽  
Climate Forecast System ◽  
Forecast Bias

Abstract For long-range predictions (e.g., seasonal), it is a common practice for retrospective forecasts (also referred to as the hindcasts) to accompany real-time predictions. The necessity for the hindcasts stems from the fact that real-time predictions need to be calibrated in an attempt to remove the influence of model biases on the predicted anomalies. A fundamental assumption behind forecast calibration is the long-term stationarity of forecast bias that is derived based on hindcasts. Hindcasts require specification of initial conditions for various components of the prediction system (e.g., ocean, atmosphere) that are generally taken from a long reanalysis. Trends and discontinuities in the reanalysis that are either real or spurious can arise due to several reasons, for example, the changing observing system. If changes in initial conditions were to persist during the forecast, there is a potential for forecast bias to depend over the period it is computed, making calibration even more of a challenging task. In this study such a case is discussed for the recently implemented seasonal prediction system at the National Centers for Environmental Prediction (NCEP), the Climate Forecast System version 2 (CFS.v2). Based on the analysis of the CFS.v2 for 1981–2009, it is demonstrated that the characteristics of the forecast bias for sea surface temperature (SST) in the equatorial Pacific had a dramatic change around 1999. Furthermore, change in the SST forecast bias, and its relationship to changes in the ocean reanalysis from which the ocean initial conditions for hindcasts are taken is described. Implications for seasonal and other long-range predictions are discussed.

scholarly journals Mean Biases, Variability, and Trends in Air–Sea Fluxes and Sea Surface Temperature in the CCSM4

2012 ◽  
Vol 25 (22) ◽  
pp. 7781-7801 ◽  
Author(s):  
Susan C. Bates ◽  
Baylor Fox-Kemper ◽  
Steven R. Jayne ◽  
William G. Large ◽  
Samantha Stevenson ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Hydrological Cycle ◽  
Sea Surface ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
Climate System Model ◽  
Frequency Bands

Abstract Air–sea fluxes from the Community Climate System Model version 4 (CCSM4) are compared with the Coordinated Ocean-Ice Reference Experiment (CORE) dataset to assess present-day mean biases, variability errors, and late twentieth-century trend differences. CCSM4 is improved over the previous version, CCSM3, in both air–sea heat and freshwater fluxes in some regions; however, a large increase in net shortwave radiation into the ocean may contribute to an enhanced hydrological cycle. The authors provide a new baseline for assessment of flux variance at annual and interannual frequency bands in future model versions and contribute a new metric for assessing the coupling between the atmospheric and oceanic planetary boundary layer (PBL) schemes of any climate model. Maps of the ratio of CCSM4 variance to CORE reveal that variance on annual time scales has larger error than on interannual time scales and that different processes cause errors in mean, annual, and interannual frequency bands. Air temperature and specific humidity in the CCSM4 atmospheric boundary layer (ABL) follow the sea surface conditions much more closely than is found in CORE. Sensible and latent heat fluxes are less of a negative feedback to sea surface temperature warming in the CCSM4 than in the CORE data with the model’s PBL allowing for more heating of the ocean’s surface.

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