The thermal air–sea interaction mechanism that modulates the atmospheric mixing due to sea-surface temperature (SST) variability is studied with long-…The thermal air–sea interaction mechanism that modulates the atmospheric mixing due to sea-surface temperature (SST) variability is studied with long-term consistent satellite records. Statistical analyses of daily and instantaneous wind and SST data are performed over the major western boundary currents (WBCs). This wind–SST coupling, which is mediated by atmospheric mixing, is found to be very relevant on daily, and even shorter, time scales. Co-located and simultaneous SST and surface wind fields (from Advanced Very High Resolution Radiometer and Advanced Scatterometer data) reveal that the atmosphere responds instantaneously to the presence of SST structures with a larger coupling coefficient with respect to daily and monthly time-averaged fields. The coupling strength varies seasonally over WBCs in the Northern Hemisphere, with wintertime coupling being the lowest. Reanalysis data show that this behaviour is related to the seasonality of the air–sea temperature difference over the region of interest. Over the Northern Hemisphere WBCs, dry and cold continental air masses drive very unstable conditions, associated with very weak thermal air–sea coupling.more
A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high…A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 x 1013 locations are processed, yielding 1.4 x 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km-2 yr-1 in 1980 to over 100 km-2 yr-1 after 2007. Data are provided at their native resolution, averaged on a global 0.05 degrees latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05 degrees. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods.more
The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned …The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned for launch in 2022, has a direct heritage from the successful advanced scatterometer (ASCAT) flown on the current EPS satellites. In addition, SCA will represent three major innovations with respect to ASCAT, namely: 1) Cross polarization and horizontal copolarization; 2) a nominal spatial resolution of 25 km; and 3) 20% greater spatial coverage than ASCAT. The associated expected science and application benefits that led the SCA design are discussed with respect to ocean, land, and sea ice applications for near-real time, climate monitoring, and research purposes. Moreover, an option to implement an ocean Doppler capability to retrieve the ocean motion vector is briefly discussed as well. In conclusion, the SCA instrument innovations are well set to provide timely benefits in all the main application areas of the scatterometer (winds, soil moisture, sea ice) and can be expected to contribute to new and more sophisticated meteorological, oceanographic, land, sea ice, and climate services in the forthcoming SCA era.more
The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known…The rapid decline of Arctic sea ice makes understanding sympagic (ice-associated) biology a particularly urgent task. Here we studied the poorly known seasonality of sea-ice protist and meiofauna community composition, abundance and biomass in the bottom 30 cm of sea ice in relation to ice properties and ice drift trajectories in the northwestern Barents Sea. We expected low abundances during the polar night and highest values during spring prior to ice melt. Sea ice conditions and Chlorophyll a concentrations varied strongly seasonally, while particulate organic carbon concentrations were fairly stable throughout the seasons. In December to May we sampled growing first-year ice, while in July and August melting older sea ice dominated. Low sea-ice biota abundances in March could be related to the late onset of ice formation and short time period for ice algae and uni- and multicellular grazers to establish themselves. Pennate diatoms, such as Navicula spp. and Nitzschia spp., dominated the bottom ice algal communities and were present during all seasons. Except for May, ciliates, dinoflagellates, particularly of the order Gymnodiales, and small-sized flagellates were co-dominant. Ice meiofauna (here including large ciliates and foraminifers) was comprised mainly of harpacticoid copepods, copepod nauplii, rotifers, large ciliates and occasionally acoels and foraminifers, with dominance of omnivore species throughout the seasons. Large ciliates comprised the most abundant meiofauna taxon at all ice stations and seasons (50–90 %) but did not necessarily dominate the biomass. While ice melt might have released and reduced ice algal biomass in July, meiofauna abundance remained high, indicating different annual cycles of protist versus meiofauna taxa. In May highest Chlorophyll a concentrations (29.4 mg m−2) and protist biomass (107 mg C m−2) occurred, while highest meiofauna abundance was found in August (23.9 × 103 Ind. m−2) and biomass in December (0.6 mg C m−2). The abundant December ice biota community further strengthens the emerging notion of an active biota during the dark Arctic winter. The data demonstrated a strong and partially unexpected seasonality in the Barents Sea ice biota, indicating that changes in ice formation, drift and decay will significantly impact the functioning of the ice-associated ecosystem.more
The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant bias…The ability of climate models to capture extreme precipitation events is crucially important, but most of the existing models contain significant biases for the simulation of extreme precipitation. To understand the causes of these biases, we used five different cumulus parameterization schemes in the regional Climate-Weather Research and Forecasting (CWRF) model to investigate its performance and biases in the simulation of extreme precipi-tation events in China. In general, the ensemble cumulus parameterization (ECP) scheme was the most skillful in reproducing the spatial distribution of the 95th percentile daily precipitation (P95) and the other four schemes either overestimated (the Kain-Fritsch Eta and Tiedtke schemes) or underestimated (the Betts-Miller-Janjic and New Simplified Arakawa-Schubert schemes) P95. Compared with the observational data, ECP scheme signifi-cantly improved the simulation of extreme precipitation in China and had the highest correlation and the smallest root-mean-square error in most areas and seasons. To clarify the underlying physical processes of P95 simulation biases, we established a regression model of extreme precipitation based on ECP scheme. This showed that P95 in North China is mainly affected by moisture convergence, planetary boundary layer height and lifting condensation level (relative importance 18-32%). In Central China, the vertical upward motion of water vapor, sensible heat flux and planetary boundary layer height (relative importance 18-30%) are main factors associated with P95. In South China, the vertical upward motion and horizontal transport of water vapor are predominant (relative importance 26-37%). In addition, the net surface energy, surface and atmospheric radiation flux, total precipitable water, convective available potential energy and cloud water path also have a high correlation with P95 (the second most important factor; relative importance 14-31%). The influence of each factor on the simulation of P95 is different when using different cumulus parameterization schemes and the interaction among the different factors determines the ability of CWRF model to simulate extreme precipitation. These results provide important references for future model evaluations and improvements.more