The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project

Donlon, Craig; Robinson, I. S.; Casey, Kenneth S.; Vázquez-Cuervo, Jorge; Armstrong, E. M.; Arino, Olivier; Gentemann, Chelle; May, Douglas A.; Leborgne, P; Piollé, Jean-François; Barton, I. J.; Beggs, Helen; Poulter, David; Merchant, Christopher J.; Bingham, Andrew; Heinz, Steven R.; Harris, Andrew R.; Wick, Gary A.; Emery, Brian; Minnett, Peter J.; Evans, Robert H.; Llewellyn‐Jones, David; Mutlow, C. T.; Reynolds, Richard W.; Kawamura, Hiroshi; Rayner, Nick

doi:10.1175/bams-88-8-1197

Cited by 352 publications

(257 citation statements)

References 14 publications

Supporting

Mentioning

234

Contrasting

Unclassified

Order By: Relevance

“…To avoid confusion, several definitions of surface temperature have been proposed for the marine environment, depending on the depth of measurement (Donlon et al, 2007;Kawai and Wada, 2007). We adapt (and adopt) these definitions for the freshwater case:…”

Section: Definitions Of Surface Temperaturementioning

confidence: 99%

LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives

Prats¹,

Reynaud²,

Rebière³

et al. 2018

Earth Syst. Sci. Data

View full text Add to dashboard Cite

Abstract. The spatial and temporal coverage of the Landsat satellite imagery make it an ideal resource for the monitoring of water temperature over large territories at a moderate spatial and temporal scale at a low cost. We used Landsat 5 and Landsat 7 archive images to create the Lake Skin Surface Temperature (LakeSST) data set, which contains skin water surface temperature data for 442 French water bodies (natural lakes, reservoirs, ponds, gravel pit lakes and quarry lakes) for the period 1999-2016. We assessed the quality of the satellite temperature measurements by comparing them to in situ measurements and taking into account the cool skin and warm layer effects. To estimate these effects and to investigate the theoretical differences between the freshwater and seawater cases, we adapted the COARE 3.0 algorithm to the freshwater environment. We also estimated the warm layer effect using in situ data. At the reservoir of Bimont, the estimated cool skin effect was about −0.3 and −0.6 • C most of time, while the warm layer effect at 0.55 m was negligible on average, but could occasionally attain several degrees, and a cool layer was often observed in the night. The overall RMSE of the satellite-derived temperature measurements was about 1.2 • C, similar to other applications of satellite images to estimate freshwater surface temperatures. The LakeSST data can be used for studies on the temporal evolution of lake water temperature and for geographical studies of temperature patterns. The LakeSST data are available at https://doi.org/10.5281/zenodo.1193745.

show abstract

Section: Definitions Of Surface Temperaturementioning

confidence: 99%

LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives

Prats¹,

Reynaud²,

Rebière³

et al. 2018

Earth Syst. Sci. Data

View full text Add to dashboard Cite

show abstract

“…Parameterisations for short-and long-wave radiation, surface fluxes, cumulus convection, boundary layer turbulence (using a level 2.5 turbulence scheme), and moist processes (including microphysical quantities) are discussed in Hodur (1997) and Hodur and Doyle (1999). ERA-Interim reanalysis data were used as 6-hourly lateral boundary forcing fields, while the SST was updated every 24 hours, using the Global Ocean Data Assimilation Experiment (GODAE) high-resolution SST (GHRSST) data (Donlon et al, 2007). The domain configuration for the COAMPS † model simulation is shown in Fig.…”

Section: Data and The Model Setupmentioning

confidence: 99%

Structure and variability of the Oman coastal low-level jet

Ranjha¹,

Tjernström²,

Semedo³

et al. 2015

Tellus A: Dynamic Meteorology and Oceanography

View full text Add to dashboard Cite

A B S T R A C T In this study, reanalysis and regional atmospheric modelling was used to resolve the climatology and mesoscale structure, spatial variability and temporal characteristics of the Oman coastal low-level jet (CLLJ). The limited area model COAMPS † was used at a 6-km horizontal resolution for a 5-month period (MayÁSeptember) during 2009. Analysis of high-resolution model fields reveals the mesoscale structure of the Oman CLLJ, clearly distinguishing it from the large-scale South Asia monsoon circulation farther offshore, and from the previously identified Findlater (or Somali) jet, which occurs at a higher altitude. The Oman CLLJ is closer to the coast and spreads northeastward along the coast of Oman, clearly interacting with the coastal topography and headlands. It has a very strong annual cycle, related to the South Asia monsoon, with July exhibiting the highest CLLJ frequency of occurrence (around 80%) and highest wind speeds (around 27 ms (1 ), and May and September being the transition months. The southerly location of the Oman CLLJ, along with the very strong inland summer heating in the Arabian Peninsula, affects its diurnal cycle, with highest number of occurrences early in the morning, whereas the highest wind speeds occur during late afternoon, setting this CLLJ apart from other coastal jets in mid-latitude areas along eastern boundary currents.

show abstract

“…RA2 provides estimates of wind speed at 10 m height (U 10 ) and significant wave height (H S ) at the sub-satellite point. AATSR is a self-calibrating radiometer (Edwards et al, 1990) that provides estimates of surface skin temperatures (Donlon et al, 2007) and exhibits a very small standard deviation of error of 0.16 • C and a bias of +0.2 • C (O 'Carroll et al, 2008). RA2 provides estimates of U 10 with a standard deviation of 1.25 m s −1 and a bias of −0.28 m s −1 , and H S with a standard deviation of 0.15 m and no global bias (Queffeulou et al, 2010).…”

Section: Data Setsmentioning

confidence: 99%

Climate change impacts on sea–air fluxes of CO<sub>2</sub> in three Arctic seas: a sensitivity study using Earth observation

et al. 2013

View full text Add to dashboard Cite

Abstract. We applied coincident Earth observation data collected during 2008 and 2009 from multiple sensors (RA2, AATSR and MERIS, mounted on the European Space Agency satellite Envisat) to characterise environmental conditions and integrated sea-air fluxes of CO 2 in three Arctic seas (Greenland, Barents, Kara). We assessed net CO 2 sink sensitivity due to changes in temperature, salinity and sea ice duration arising from future climate scenarios. During the study period the Greenland and Barents seas were net sinks for atmospheric CO 2 , with integrated sea-air fluxes of −36 ± 14 and −11 ± 5 Tg C yr −1 , respectively, and the Kara Sea was a weak net CO 2 source with an integrated sea-air flux of +2.2 ± 1.4 Tg C yr −1 . The combined integrated CO 2 sea-air flux from all three was −45 ± 18 Tg C yr −1 . In a sensitivity analysis we varied temperature, salinity and sea ice duration. Variations in temperature and salinity led to modification of the transfer velocity, solubility and partial pressure of CO 2 taking into account the resultant variations in alkalinity and dissolved organic carbon (DOC). Our results showed that warming had a strong positive effect on the annual integrated sea-air flux of CO 2 (i.e. reducing the sink), freshening had a strong negative effect and reduced sea ice duration had a small but measurable positive effect. In the climate change scenario examined, the effects of warming in just over a decade of climate change up to 2020 outweighed the combined effects of freshening and reduced sea ice duration. Collectively these effects gave an integrated sea-air flux change of +4.0 Tg C in the Greenland Sea, +6.0 Tg C in the Barents Sea and +1.7 Tg C in the Kara Sea, reducing the Greenland and Barents sinks by 11 % and 53 %, respectively, and increasing the weak Kara Sea source by 81 %. Overall, the regional integrated flux changed by +11.7 Tg C, which is a 26 % reduction in the regional sink. In terms of CO 2 sink strength, we conclude that the Barents Sea is the most susceptible of the three regions to the climate changes examined. Our results imply that the region will cease to be a net CO 2 sink in the 2050s.

show abstract

The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project

Abstract: SST is an ocean variable that is readily measured by satellites and in situ sensors, and it is needed as a key input to forecasting systems to constrain the modeled upperocean circulation and thermal structure, and for the exchange of energy • AMERICAN METEOROLOGICAL SOCIETY

Cited by 352 publications

References 14 publications

LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives

LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives

Structure and variability of the Oman coastal low-level jet

Climate change impacts on sea–air fluxes of CO<sub>2</sub> in three Arctic seas: a sensitivity study using Earth observation

Contact Info

Product

Resources

About

The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project

Abstract: SST is an ocean variable that is readily measured by satellites and in situ sensors, and it is needed as a key input to forecasting systems to constrain the modeled upperocean circulation and thermal structure, and for the exchange of energy • AMERICAN METEOROLOGICAL SOCIETY

Cited by 352 publications

References 14 publications

LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives

LakeSST: Lake Skin Surface Temperature in French inland water bodies for 1999–2016 from Landsat archives

Structure and variability of the Oman coastal low-level jet

Climate change impacts on sea–air fluxes of CO&lt;sub&gt;2&lt;/sub&gt; in three Arctic seas: a sensitivity study using Earth observation

Contact Info

Product

Resources

About

Climate change impacts on sea–air fluxes of CO<sub>2</sub> in three Arctic seas: a sensitivity study using Earth observation