Observing The Mediterranean Sea from space: 21 years of Pathfinder-AVHRR Sea Surface Temperatures (1985 to 2005). Re-analysis and validation

S., Marullo,; Nardelli, Bruno Buongiorno; Guarracino, M.; R., Santoleri,

doi:10.5194/osd-3-1191-2006

Cited by 56 publications

(71 citation statements)

References 10 publications

(14 reference statements)

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“…The 1985-2008 spatiotemporal dataset for the Aegean Sea consists of optimally interpolated declouded monthly SST maps at a 1/16 resolution-grid ($6 km), provided by the Gruppo Oceanografia da Satellite (GOS) of the CNR-ISAC (Istituto di Scienze dell'Atmosfera e del Clima) (http://gos.ifa.rm.cnr.it). Marullo et al [26] validated the optimally interpolated Pathfinder SST dataset for the Mediterranean Sea using in situ data from 1985 to 2005, and they found a mean bias of less than 0.1 K with a root mean square error of about 0.5 K, whilst they showed that errors were weakly dependent upon season and did not drift with time. Moreover the spatial distribution of the in situ and satellite-derived temperature difference and its standard deviation was found to be quite uniform in the Mediterranean…”

Section: Methodsmentioning

confidence: 99%

“…Nykjaer [11] found a high observation density of the Pathfinder SST dataset for the Mediterranean Sea with the monthly mean number of highest quality SST observations per 4 km pixel varying from about 10 in winter to about 30 in summer. The construction of the satellite-derived SST data for the Aegean Sea considered herein is based on a re-analysis of the AVHRR Pathfinder (version 5.0) SST timeseries of the Mediterranean Sea [26]. The 1985-2008 spatiotemporal dataset for the Aegean Sea consists of optimally interpolated declouded monthly SST maps at a 1/16 resolution-grid ($6 km), provided by the Gruppo Oceanografia da Satellite (GOS) of the CNR-ISAC (Istituto di Scienze dell'Atmosfera e del Clima) (http://gos.ifa.rm.cnr.it).…”

Section: Methodsmentioning

confidence: 99%

“…Sea with few hot spots greater than 0.5 K mostly located near the coasts [26]. Basinaverage seasonal and yearly mean timeseries are constructed from the monthly time-series in order to investigate the SST inter-annual/decadal scale variability, the long-term linear trends and their seasonality.…”

Section: Advances In Oceanography and Limnology 127mentioning

confidence: 99%

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Long-term sea surface temperature variability in the Aegean Sea

Skliris

Sofianos

Γκανάσος

et al. 2011

Advances in Oceanography and Limnology

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The inter-annual/decadal scale variability of the Aegean Sea Surface Temperature (SST) is investigated by means of long-term series of satellite-derived and in situ data. Monthly mean declouded SST maps are constructed over the period, based on a re-analysis of AVHRR Oceans Pathfinder optimally interpolated data over the Aegean Sea. Basin-average SST time series are also constructed using the ICOADS in situ data over . Results indicate a small SST decreasing trend until the early nineties, and then a rapid surface warming consistent with the acceleration of the SST rise observed on the global ocean scale. Decadal-scale SST anomalies were found to be negatively correlated with the winter North Atlantic Oscillation (NAO) index over the last 60 years suggesting that along with global warming effects on the regional scale, a part of the long-term SST variability in the Aegean Sea is driven by large scale atmospheric natural variability patterns. In particular, the acceleration of surface warming in the Aegean Sea began nearly simultaneously with the NAO index abrupt shift in the mid-nineties from strongly positive values to weakly positive/ negative values.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Long-term sea surface temperature variability in the Aegean Sea

Skliris

Sofianos

Γκανάσος

et al. 2011

Advances in Oceanography and Limnology

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“…The optimally interpolated SST product finally covers the Mediterranean basin at 1°/16° resolution, dating back to 1985, and accurately represents the Mediterranean SST when compared to in-situ measurements on board buoys, drifters or voluntary observing ships, and to ARGO profilers. The satellite data, the optimal interpolation scheme and the validation of the MFSTEP optimally interpolated SST product are fully described in Marullo et al (2007). For the P1 period, Fig.…”

Section: Sst Analysis In the Ctl And Cpl Regional Climate Simulationsmentioning

confidence: 99%

North-western Mediterranean sea-breeze circulation in a regional climate system model

et al. 2017

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regional climate model (AORCM) coupling WRF and NEMO-MED12 in the frame of HyMeX/MED-CORDEX are compared. One result of this study is that these simulations reproduce remarkably well the intensity, direction and inland penetration of the sea breeze and even the existence of the shallow sea breeze despite the overestimate of temperature over land in both simulations. The coupled simulation provides a more realistic representation of the evolution of the SST field at fine scale than the atmosphereonly one. Temperature and moisture anomalies are created in direct response to the SST anomaly and are advected by the sea breeze over land. However, the SST anomalies are not of sufficient magnitude to affect the large-scale seabreeze circulation. The temperature anomalies are quickly damped by strong surface heating over land, whereas the water vapor mixing ratio anomalies are transported further inland. The inland limit of significance is imposed by the vertical dilution in a deeper continental boundary-layer.

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“…Also, Hayes et al (2005) analyzed the annual average of the SST in the last glacier period, and pointed out a variation in the SST from 9 ºC to 19 ºC in the Mediterranean sub-basins. Marullo et al (2007) investigated the correlation of remote sensed SST (i.e., AVHRR Pathfinder version 5.0) and measured SST in the Mediterranean Sea for a 21-year time period. The results of the study pointed to a very high correlation (i.e., ca.…”

Section: Introductionmentioning

confidence: 99%

Sea Surface Temperature Change in the Mediterranean Sea Under Climate Change: A Linear Model for Simulation of the Sea Surface Temperature Up to 2100

Sakallı¹

2017

Appl Ecol Env Res

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Abstract. The warming in the inner seas could not be more important and time is certainly running out for it. This study highlights important results about the detectable and predictable warming of the sea surface temperature (SST) in the Mediterranean Sea. The featured analysis of the SST is based on the remote sensed and corrected SST data for the period 1986-2015, and predicted data by using a linear black box model for period -2100 . The 30-year (1986 SST analysis shows an increase of about 0.4 ºC per decade. The most fluctuation in the monthly SST was generally detected at the beginning of the summer period. In the last 30 years of this century (2071-2100), the relative increase in average SST is predicted to be about 5.8 ºC in the Mediterranean Sea by the model. The analysis and prediction of the recent studies showed a perceptible warming in the sea surface during the last decades, and the warming will also continue to increase under the present environmental condition.

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Observing The Mediterranean Sea from space: 21 years of Pathfinder-AVHRR Sea Surface Temperatures (1985 to 2005). Re-analysis and validation

Cited by 56 publications

References 10 publications

Long-term sea surface temperature variability in the Aegean Sea

Long-term sea surface temperature variability in the Aegean Sea

North-western Mediterranean sea-breeze circulation in a regional climate system model

Sea Surface Temperature Change in the Mediterranean Sea Under Climate Change: A Linear Model for Simulation of the Sea Surface Temperature Up to 2100

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