Spatial patterns of intraseasonal variability of chlorophyll and sea surface temperature in the California Current

Abstract. Marine sediments have greatly improved our understanding of the climate system, but their interpretation often assumes that certain climate mechanisms operate consistently over all timescales of interest and that variability at one or a few sample sites is representative of an oceanographic province. In this study, we test these assumptions using modern observations in an idealized manner mimicking paleo-reconstruction to investigate whether sea surface temperature and productivity proxy records in the Southern California Current System can be used to reconstruct Ekman upwelling. The method uses extended empirical orthogonal function (EEOF) analysis of the covariation of alongshore wind stress, chlorophyll, and sea surface temperature as measured by satellites from 2002 to 2009. We find that EEOF1 does not reflect an Ekman upwelling pattern but instead much broader California Current processes. EEOF2 and 3 reflect upwelling patterns, but these patterns are timescale dependent and regional. Thus, the skill of using one site to reconstruct the large-scale dominant patterns is spatially dependent. Lastly, we show that using multiple sites and/or multiple variables generally improves field reconstruction. These results together suggest that caution is needed when attempting to extrapolate mechanisms that may be important on seasonal timescales (e.g., Ekman upwelling) to deeper time but also the advantage of having multiple proxy records.

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Effect of Atlantic Sea Surface Temperature in May on Intraseasonal Variability of Eurasian NDVI in Summer

Journal of Geophysical Research Atmospheres ◽

10.1029/2019jd031991 ◽

2020 ◽

Vol 125 (9) ◽

Author(s):

Liuqing Ji ◽

Ke Fan

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Intraseasonal Variability ◽

Sea Surface

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Intraseasonal Sea Surface Temperature Variability across the Indonesian Seas*

Journal of Climate ◽

10.1175/jcli-d-14-00758.1 ◽

2015 ◽

Vol 28 (22) ◽

pp. 8710-8727 ◽

Cited By ~ 14

Author(s):

Asmi M. Napitu ◽

Arnold L. Gordon ◽

Kandaga Pujiana

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Intraseasonal Variability ◽

Longwave Radiation ◽

Active Phase ◽

Ocean Model ◽

Sea Surface ◽

Indonesian Seas ◽

Sst Variability ◽

Slab Ocean

Abstract Sea surface temperature (SST) variability at intraseasonal time scales across the Indonesian Seas during January 1998–mid-2012 is examined. The intraseasonal variability is most energetic in the Banda and Timor Seas, with a standard deviation of 0.4°–0.5°C, representing 55%–60% of total nonseasonal SST variance. A slab ocean model demonstrates that intraseasonal air–sea heat flux variability, largely attributed to the Madden–Julian oscillation (MJO), accounts for 69%–78% intraseasonal SST variability in the Banda and Timor Seas. While the slab ocean model accurately reproduces the observed intraseasonal SST variations during the northern winter months, it underestimates the summer variability. The authors posit that this is a consequence of a more vigorous cooling effect induced by ocean processes during the summer. Two strong MJO cycles occurred in late 2007–early 2008, and their imprints were clearly evident in the SST of the Banda and Timor Seas. The passive phase of the MJO [enhanced outgoing longwave radiation (OLR) and weak zonal wind stress) projects on SST as a warming period, while the active phase (suppressed OLR and westerly wind bursts) projects on SST as a cooling phase. SST also displays significant intraseasonal variations in the Sulawesi Sea, but these differ in characteristics from those of the Banda and Timor Seas and are attributed to ocean eddies and atmospheric processes independent from the MJO.

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Intraseasonal Variability of Surface Fluxes and Sea Surface Temperature in the Tropical Western Pacific and Indian Oceans

Journal of Climate ◽

10.1175/1520-0442(1998)011<1685:ivosfa>2.0.co;2 ◽

1998 ◽

Vol 11 (7) ◽

pp. 1685-1702 ◽

Cited By ~ 200

Author(s):

Toshiaki Shinoda ◽

Harry H. Hendon ◽

John Glick

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Intraseasonal Variability ◽

Surface Fluxes ◽

Western Pacific ◽

Sea Surface ◽

Tropical Western Pacific

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Using Saildrones to Validate Satellite-Derived Sea Surface Salinity and Sea Surface Temperature along the California/Baja Coast

Remote Sensing ◽

10.3390/rs11171964 ◽

2019 ◽

Vol 11 (17) ◽

pp. 1964 ◽

Cited By ~ 11

Author(s):

Jorge Vazquez-Cuervo ◽

Jose Gomez-Valdes ◽

Marouan Bouali ◽

Luis Miranda ◽

Tom Van der Stocken ◽

...

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Current System ◽

California Current ◽

Sea Surface ◽

Sea Surface Salinity ◽

Surface Salinity ◽

California Current System ◽

The Impact ◽

Buoy Measurements

Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products by comparing with buoy measurements, do not allow for evaluating the impact of mesoscale-to-submesoscale variability. We present the validation of remotely sensed SST and SSS data against the unmanned surface vehicle (USV)—called Saildrone—measurements from the 60 day 2018 Baja California campaign. More specifically, biases and root mean square differences (RMSDs) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero, while MUR showed a bias of 0.3 °C. The OSTIA showed the smallest RMSD of 0.39 °C, while DMI had the largest RMSD of 0.5 °C. An RMSD of 0.4 °C between Saildrone SST and the satellite-derived products could be explained by the diurnal and sub-daily variability in USV SST, which currently cannot be resolved by remote sensing measurements. SSS showed fresh biases of 0.1 PSU for JPLSMAP and 0.2 PSU and 0.3 PSU for RMSS40 and RSS70 respectively. SST and SSS showed peaks in coherence at 100 km, most likely associated with the variability of the California Current System.

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