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Abstract: Wintertime surface ocean heat loss is the key process driving the formation of Subantarctic Mode Water (SAMW), but there are few direct observations of heat fluxes, particularly during winter. The Ocean Observatories Initiative (OOI) Southern Ocean mooring in the southeast Pacific Ocean and the Southern Ocean Flux Station (SOFS) in the southeast Indian Ocean provide the first concurrent, multiyear time series of air–sea fluxes in the Southern Ocean from two key SAMW formation regions. In this work we compare drivers of wintertime heat loss and SAMW formation by comparing air–sea fluxes and mixed layers at these two mooring locations. A gridded Argo product and the ERA5 reanalysis product provide temporal and spatial context for the mooring observations. Turbulent ocean heat loss is on average 1.5 times larger in the southeast Indian (SOFS) than in the southeast Pacific (OOI), with stronger extreme heat flux events in the southeast Indian leading to larger cumulative winter ocean heat loss. Turbulent heat loss events in the southeast Indian (SOFS) occur in two atmospheric regimes (cold air from the south or dry air circulating via the north), while heat loss events in the southeast Pacific (OOI) occur in a single atmospheric regime (cold air from the south). On interannual time scales, wintertime anomalies in net heat flux and mixed layer depth (MLD) are often correlated at the two sites, particularly when wintertime MLDs are anomalously deep. This relationship is part of a larger basin-scale zonal dipole in heat flux and MLD anomalies present in both the Indian and Pacific basins, associated with anomalous meridional atmospheric circulation.

This study uses the ECMWF ERA5 reanalysis and observationally constrained top-of-the-atmosphere radiative fluxes to infer net surface energy fluxes covering 1985–2018, which can be further adjusted to match the observed mean land heat uptake. Various diagnostics are applied to provide error estimates of inferred fluxes on different spatial scales. For this purpose, adjusted as well as unadjusted inferred surface fluxes are compared with other commonly used flux products. On a regional scale, the oceanic energy budget of the North Atlantic between the RAPID array at 26.5°N and moorings located farther north (e.g., at the Greenland–Scotland Ridge) is evaluated. On the station scale, a comprehensive comparison of inferred and buoy-based fluxes is presented. Results indicate that global land and ocean averages of unadjusted inferred surface fluxes agree with the observed heat uptake to within 1 W m−2, while satellite-derived and model-based fluxes show large global mean biases. Furthermore, the oceanic energy budget of the North Atlantic is closed to within 2.7 (−0.2) W m−2 for the period 2005–09 when unadjusted (adjusted) inferred surface fluxes are employed. Indirect estimates of the 2004–16 mean oceanic heat transport at 26.5°N are 1.09 PW (1.17 PW with adjusted fluxes), which agrees well with observed RAPID transports. On the station scale, inferred fluxes exhibit a mean bias of −20.1 W m−2 when using buoy-based fluxes as reference, which confirms expectations that biases increase from global to local scales. However, buoy-based fluxes as reference are debatable, and are likely positively biased, suggesting that the station-scale bias of inferred fluxes is more likely on the order of −10 W m−2. [ABSTRACT FROM AUTHOR]

Tropical convection regimes range from deep organized to shallow convective systems. Mesoscale processes such as cold pools within tropical convective systems can play a significant role in the evolution of convection over land and open ocean. Although cold pools are widely observed, their diurnal properties are not well understood over tropical oceans and land. The oceanic cold pool identification metric applied herein uses the gradient feature (GF) technique and is compared with diurnally resolved buoy-identified thermal cold pools. This study provides a first-ever diurnal climatology of GF number, area, and attributed TRMM 3B42 precipitation using a spaceborne scatterometer (RapidSCAT). Buoy data over the Pacific, Atlantic, and Indian Oceans have been used to validate and examine the RapidSCAT-identified diurnal cycle of GF number and precipitation. Buoy-observed cold pool duration, precipitation, temperature, and wind speed is analyzed to understand the in situ cold pool properties over tropical oceans. GF- and buoy-observed cold pool number and precipitation exhibits a similar bimodal diurnal variability with morning and afternoon maxima, thus establishing confidence in using GF as a proxy to observe cold pools over tropical oceans. The morning peak is attributed to cold pools associated with deep moist convection while the afternoon peak is related to shallower clouds in relatively drier environments resulting in smaller cold pools over global tropical oceans. Significance Statement: The global diurnal cycle of oceanic convectively generated cold pools (cool outflows from convection) is observed for the first time using the gradient feature method—revealing a bimodal distribution of cold pools organized by deep, organized convective systems in the early morning and afternoon cold pools predominated by shallower, more isolated convection. This analysis will provide a reference for high-resolution climate models to mimic in order to accurately represent key processes that organize convection and govern air–sea interactions. [ABSTRACT FROM AUTHOR]

The NOAA Daily Optimum Interpolation Sea Surface Temperature dataset (DOISST) has recently been updated to v2.1 (January 2016–present). Its accuracy may impact the climate assessment, monitoring and prediction, and environment-related applications. Its performance, together with those of seven other well-known sea surface temperature (SST) products, is assessed by comparison with buoy and Argo observations in the global oceans on daily 0.25° × 0.25° resolution from January 2016 to June 2020. These seven SST products are NASA MUR25, GHRSST GMPE, BoM GAMSSA, UKMO OSTIA, NOAA GPB, ESA CCI, and CMC. Our assessments indicate that biases and root-mean-square difference (RMSDs) in reference to all buoys and all Argo floats are low in DOISST. The bias in reference to the independent 10% of buoy SSTs remains low in DOISST, but the RMSD is slightly higher in DOISST than in OSTIA and CMC. The biases in reference to the independent 10% of Argo observations are low in CMC, DOISST, and GMPE; also, RMSDs are low in GMPE and CMC. The biases are similar in GAMSSA, OSTIA, GPB, and CCI whether they are compared against all buoys, all Argo, or the 10% of buoy or 10% of Argo observations, while the RMSDs against Argo observations are slightly smaller than those against buoy observations. These features indicate a good performance of DOISST v2.1 among the eight products, which may benefit from ingesting the Argo observations by expanding global and regional spatial coverage of in situ observations for effective bias correction of satellite data. [ABSTRACT FROM AUTHOR]

Six-month buoy-based heat flux observations from the poorly sampled tropical southeastern Indian Ocean are examined to document the extremes during three tropical cyclones (TCs) from December 2018 to May 2019. The most striking feature at the mooring site (16.9°S, 115.2°E) during the TCs is the extensively suppressed diurnal cycle of the net surface flux (Qnet), with a mean daytime (nighttime) reduction of 470 (131) W m−2, a peak decrease at approximately noon of 695 W m−2 and an extreme drop during TC Riley of 800 W m−2. The mean surface cooling in the daytime is primarily contributed by the 370 W m−2 decrease in shortwave radiation associated with the increased cloudiness. The air–sea turbulent heat fluxes increase by approximately 151 W m−2 in response to the enhanced wind speed under near-neutral boundary conditions. The daily mean rainfall-induced cooling is 8 W m−2, with a maximum magnitude of 90 W m−2. The mean values, seasonal variation, and synoptic variability of the characteristic heat fluxes are used to assess the new reanalysis data from ERA5 and MERRA2 and the analyzed OAFlux. The overall performance of the high-frequency net heat flux estimates at the synoptic scale is satisfactory, but the four flux components exhibit different quality levels. A serious error is that ERA5 and MERRA2 poorly represent TCs, and they show significant daily mean Qnet biases with opposite directions, −59 W m−2 (largely due to the overestimated latent heat with a bias of −76 W m−2) and 50 W m−2 (largely due to the overestimated shortwave radiation with a bias of 41 W m−2), respectively. [ABSTRACT FROM AUTHOR]

The relative roles of buoy and Argo observations in two sea surface temperature (SST) analyses are studied in the global ocean and tropical Pacific Ocean over 2000–16 using monthly Extended Reconstructed SST version 5 (ERSSTv5) and Daily Optimum Interpolation SST version 2 (DOISST). Experiments show an overall higher impact by buoys than Argo floats over the global oceans and an increasing impact by Argo floats. The impact by Argo floats is generally larger in the Southern Hemisphere than in the Northern Hemisphere. The impact on trends and anomalies of globally averaged SST by either one is small when the other is used. The warming trend over 2000–16 remains significant by including either buoys or Argo floats or both. In the tropical Pacific, the impact by buoys was large over 2000–05 when the number of Argo floats was low, and became smaller over 2010–16 when the number and area coverage of Argo floats increased. The magnitude of El Niño and La Niña events decreases when the observations from buoys, Argo floats, or both are excluded. The impact by the Tropical Atmosphere Ocean (TAO) and Triangle Trans-Ocean Buoy Network (TRITON) is small in normal years and during El Niño events. The impact by TAO/TRITON buoys on La Niña events is small when Argo floats are included in the analysis systems, and large when Argo floats are not included. The reason for the different impact on El Niño and La Niña events is that the drifting buoys are more dispersed from the equatorial Pacific region by stronger trade winds during La Niña events. [ABSTRACT FROM AUTHOR]

The difficulty in effectively evaluating sea surface temperature (SST) analyses is finding independent observations, since most available observations have been used in the SST analyses. In this study, the ocean profile measurements [from reverse thermometer, CTD, mechanical bathythermograph (MBT), and XBT] above 5-m depth over 1950–2016 from the World Ocean Database (WOD) are used (data labeled pSSTW). The biases of MBT and XBT are corrected based on currently available algorithms. The bias-corrected pSSTW over 1950–2016 and satellite-based SST from the European Space Agency (ESA) Climate Change Initiative (CCI) over 1992–2010 are used to evaluate commonly available SST analyses. These SST analyses are the Extended Reconstructed SST (ERSST), versions 5, 4, and 3b, the Met Office Hadley Centre Sea Ice and SST dataset (HadISST), and the Japan Meteorological Administration (JMA) Centennial In Situ Observation-Based Estimates of SST version 2.9.2 (COBE-SST2). Our comparisons show that the SST from COBE-SST2 is the closest to pSSTW and CCI in most of the Pacific, Atlantic, and Southern Oceans, which may result from its unique bias correction to ship observations. The SST from ERSST version 5 is more consistent with pSSTW than its previous versions over 1950–2016, and is more consistent with CCI than its previous versions over 1992–2010. The better performance of ERSST version 5 over its previous versions is attributed to its improved bias correction applied to ship observations with a baseline of buoy observations, and is seen in most of the Pacific and Atlantic. [ABSTRACT FROM AUTHOR]

The monthly global 2° × 2° Extended Reconstructed Sea Surface Temperature (ERSST) has been revised and updated from version 4 to version 5. This update incorporates a new release of ICOADS release 3.0 (R3.0), a decade of near-surface data from Argo floats, and a new estimate of centennial sea ice from HadISST2. A number of choices in aspects of quality control, bias adjustment, and interpolation have been substantively revised. The resulting ERSST estimates have more realistic spatiotemporal variations, better representation of high-latitude SSTs, and ship SST biases are now calculated relative to more accurate buoy measurements, while the global long-term trend remains about the same. Progressive experiments have been undertaken to highlight the effects of each change in data source and analysis technique upon the final product. The reconstructed SST is systematically decreased by 0.077°C, as the reference data source is switched from ship SST in ERSSTv4 to modern buoy SST in ERSSTv5. Furthermore, high-latitude SSTs are decreased by 0.1°-0.2°C by using sea ice concentration from HadISST2 over HadISST1. Changes arising from remaining innovations are mostly important at small space and time scales, primarily having an impact where and when input observations are sparse. Cross validations and verifications with independent modern observations show that the updates incorporated in ERSSTv5 have improved the representation of spatial variability over the global oceans, the magnitude of El Niño and La Niña events, and the decadal nature of SST changes over 1930s-40s when observation instruments changed rapidly. Both long- (1900-2015) and short-term (2000-15) SST trends in ERSSTv5 remain significant as in ERSSTv4. [ABSTRACT FROM AUTHOR]

By arguing that the surface pressure field over the Arctic Ocean can be treated as an isotropic, stationary, homogeneous, Gaussian random field, Thorndike estimated a number of covariance functions from two years of data (1979 and 1980). Given the active interest in changes of general circulation quantities and indices in the polar regions during the recent few decades, the spatial correlations in sea ice velocity fields are of particular interest. It is thus natural to ask, 'How persistent are these correlations?' To this end, a multifractal stochastic treatment is developed to analyze observed Arctic sea ice velocity fields from satellites and buoys for the period 1978-2015. Since it was previously found that the Arctic equivalent ice extent (EIE) has a white noise structure on annual to biannual time scales, the connection between EIE and ice motion is assessed. The long-term stationarity of the spatial correlation structure of the velocity fields and the robustness of their white noise structure on multiple time scales is demonstrated; these factors (i) combine to explain the white noise characteristics of the EIE on annual to biannual time scales and (ii) explain why the fluctuations in the ice velocity are proportional to fluctuations in the geostrophic winds on time scales of days to months. Moreover, it is shown that the statistical structure of these two quantities is commensurate from days to years, which may be related to the increasing prevalence of free drift in the ice pack. [ABSTRACT FROM AUTHOR]

The monthly Extended Reconstructed Sea Surface Temperature (ERSST) dataset, available on global 2° × 2° grids, has been revised herein to version 4 (v4) from v3b. Major revisions include updated and substantially more complete input data from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) release 2.5; revised empirical orthogonal teleconnections (EOTs) and EOT acceptance criterion; updated sea surface temperature (SST) quality control procedures; revised SST anomaly (SSTA) evaluation methods; updated bias adjustments of ship SSTs using the Hadley Centre Nighttime Marine Air Temperature dataset version 2 (HadNMAT2); and buoy SST bias adjustment not previously made in v3b. Tests show that the impacts of the revisions to ship SST bias adjustment in ERSST.v4 are dominant among all revisions and updates. The effect is to make SST 0.1°-0.2°C cooler north of 30°S but 0.1°-0.2°C warmer south of 30°S in ERSST.v4 than in ERSST.v3b before 1940. In comparison with the Met Office SST product [the Hadley Centre Sea Surface Temperature dataset, version 3 (HadSST3)], the ship SST bias adjustment in ERSST.v4 is 0.1°-0.2°C cooler in the tropics but 0.1°-0.2°C warmer in the midlatitude oceans both before 1940 and from 1945 to 1970. Comparisons highlight differences in long-term SST trends and SSTA variations at decadal time scales among ERSST.v4, ERSST.v3b, HadSST3, and Centennial Observation-Based Estimates of SST version 2 (COBE-SST2), which is largely associated with the difference of bias adjustments in these SST products. The tests also show that, when compared with v3b, SSTAs in ERSST.v4 can substantially better represent the El Niño/La Niña behavior when observations are sparse before 1940. Comparisons indicate that SSTs in ERSST.v4 are as close to satellite-based observations as other similar SST analyses. [ABSTRACT FROM AUTHOR]

The surface wind and stress responses to sea surface temperature (SST) are examined using collocated moored buoy and satellite observations in the Gulf Stream and the eastern equatorial Pacific. Using 17 buoy pairs, differences in the wind speed, 10-m equivalent neutral wind speed (ENW), and surface wind stress magnitude between two buoys separated by between 150 and 350 km were all found to be highly correlated to, and satisfy linear relations with, the SST difference on time scales longer than 10 days. This wind-SST coupling is consistent with previous analyses of spatially high-pass-filtered satellite ENW and SST fields. For all buoy pairs, the ENW and wind speed responses to SST differ by only 10%%-30%%, indicating that the ENW and stress responses to SST are attributable primarily to the response of the actual surface wind speed to SST rather than to stability. This result clarifies the dynamical pathway of the wind-SST coupling on the oceanic mesoscale. This buoy-pair methodology is used further to evaluate the ENW-SST coupling derived from collocated satellite observations of ENW by the Quick Scatterometer (QuikSCAT) and SST by the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) on board the Aqua satellite. Overall, the satellite and buoy ENW responses to SST compare well, with normalized mean differences (satellite minus buoy) of 17%% over the Gulf Stream and −31%% and 2%% over the southern and northern sides of the equatorial Pacific, respectively. Finally, seasonal variability of the large-scale ENW is shown to modulate the wind stress response to SST, whereby stronger winter wind enhances the stress response by a factor of ~2 relative to the ENW response. [ABSTRACT FROM AUTHOR]

Wintertime sea surface heat flux variability across the Kuroshio Extension (KE) front is analyzed using data from the Kuroshio Extension Observatory (KEO) buoy in the Kuroshio recirculation gyre south of the KE front and from the Japan Agency for Marine-Earth Science and Technology KEO (JKEO) buoy in the north of the front. The coincident data used are from periods during two winters (2007 and 2008), when both buoys had a complete suite of meteorological data. In these two winter periods, the focus of this research is on three types of typical weather patterns referred to here as the northerly wind condition, the monsoon wind condition, and the normal condition. During the northerly wind condition, latent and sensible heat fluxes were large and often varied simultaneously at both sites, whereas during the monsoon wind condition the latent heat flux at the KEO site was significantly larger than that at the JKEO site. The difference between these heat flux patterns is attributed to the different airmass transformations that occur when prevailing winds blow across the KE front versus along the front. Reanalysis products appear to reproduce these heat flux spatial patterns at synoptic scales. It is suggested that the relative frequencies of these different types of weather conditions result in anomalous spatial patterns in the heat fluxes on monthly time scales. [ABSTRACT FROM AUTHOR]

Six different SST analyses are compared with each other and with buoy data for the period 2007–08. All analyses used different combinations of satellite data [for example, infrared Advanced Very High Resolution Radiometer (AVHRR) and microwave Advanced Microwave Scanning Radiometer (AMSR) instruments] with different algorithms, spatial resolution, etc. The analyses considered are the National Climatic Data Center (NCDC) AVHRR-only and AMSR+AVHRR, the Navy Coupled Ocean Data Assimilation (NCODA), the Remote Sensing Systems (RSS), the Real-Time Global High-Resolution (RTG-HR), and the Operational SST and Sea Ice Analysis (OSTIA); the spatial grid sizes were , respectively. In addition, all analyses except RSS used in situ data. Most analysis procedures and weighting functions differed. Thus, differences among analyses could be large in high-gradient and data-sparse regions. An example off the coast of South Carolina showed winter SST differences that exceeded 5°C. To help quantify SST analysis differences, wavenumber spectra were computed at several locations. These results suggested that the RSS is much noisier and that the RTG-HR analysis is much smoother than the other analyses. Further comparisons made using collocated buoys showed that RSS was especially noisy in the tropics and that RTG-HR had winter biases near the Aleutians region during January and February 2007. The correlation results show that NCODA and, to a somewhat lesser extent, OSTIA are strongly tuned locally to buoy data. The results also show that grid spacing does not always correlate with analysis resolution. The AVHRR-only analysis is useful for climate studies because it is the only daily SST analysis that extends back to September 1981. Furthermore, comparisons of the AVHRR-only analysis and the AMSR+AVHRR analysis show that AMSR data can degrade the combined AMSR and AVHRR resolution in cloud-free regions while AMSR otherwise improves the resolution. These results indicate that changes in satellite instruments over time can impact SST analysis resolution. [ABSTRACT FROM AUTHOR]