Validation of satellite-based sea surface temperature products against in situ observations off the western coast of Sumatra

This study validated the sea surface temperature (SST) datasets from the Group for High-Resolution SST Multi Product Ensemble (GMPE), National Oceanic and Atmospheric Administration (NOAA) Optimal Interpolation (OI) SST version 2 and 2.1 (OIv2 and OIv2.1), and Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) in the area off the western coast of Sumatra against in situ observations. Furthermore, the root mean square differences (RMSDs) of OIv2, OIv2.1, and ECCO2 were investigated with respect to GMPE, whose small RMSD < 0.2 K against in situ observations confirmed its suitability as a reference. Although OIv2 showed a large RMSD (1–1.5 K) with a significant negative bias, OIv2.1 (RMSD < 0.4 K) improved remarkably. In the average SST distributions for December 2017, the differences among the 4 datasets were significant in the areas off the western coast of Sumatra, along the southern coast of Java, and in the Indonesian inland sea. These results were consistent with the ensemble spread distribution obtained with GMPE. The large RMSDs of OIv2 corresponded to high clouds, and it was suggested that the change in the satellites used for SST estimation contributed to the improvement in OIv2.1.

Immense variability in the sea surface temperature near macro tidal flat revealed by high-resolution satellite data (Landsat 8)

Sea surface temperature (SST) is crucial for understanding the physical characteristics and ecosystems of coastal seas. SST varies near the tidal flat, where exposure and flood recur according to the tidal cycle. However, the variability of SST near the tidal flat is poorly understood owing to difficulties in making in-situ observations. The high resolution of Landsat 8 enabled us to determine the variability of SST near the macro tidal flat. The spatial distribution of the SST extracted from Landsat 8 changed drastically. The seasonal SST range was higher near the tidal flat than in the open sea. The maximum seasonal range of coastal SST exceeded 23 °C, whereas the range in the open ocean was approximately 18 °C. The minimum and maximum horizontal SST gradients near the tidal flat were approximately − 0.76 °C/10 km in December and 1.31 °C/10 km in June, respectively. The heating of sea water by tidal flats in spring and summer, and cooling in the fall and winter might result in a large horizontal SST gradient. The estimated heat flux from the tidal flat to the seawater based on the SST distribution shows seasonal change ranging from − 4.85 to 6.72 W/m2.

In Situ Observations of the Occlusion of a Clay-Sugar Compound within Calcite

The stability of soil organic matter (SOM) plays a key role in controlling global climate change as soil stores a large amount of organic carbon, compared with other ecological systems....

SEA-LEVEL PRESSURE TRENDS IN THE SOUTHERN OCEAN AND ANTARCTICA FROM REANALYSIS AND IN SITU DATA

Trends in the mean sea-level pressure (SLP) in Antarctica in the last four decades (1980– 2020) have been examined using in situ observations and reanalysis data. The analysis involved time series of monthly mean, season-mean and yearly-mean values of the SLP derived from four reanalysis datasets, NCEP/NCAR, ERA5, JRA55, MERRA2, and from surface observations acquired from the Reference Antarctic Data for Environmental Research (READER) dataset. With this data we have evaluated the trends, characterized their seasonal peculiarities and variation across the high-latitude region of the Southern Hemisphere. The results of the analysis confirmed the dominance of decreasing trends in the annual mean SLP in Antarctica. Larger negative trends were found in the Western Antarctica with the most pronounced pressure drop in the South Pacific. The long-term decrease in the annual mean SLP in Antarctica was due to strong negative pressure trends in the austral summer and fall season whereas in winter and in spring the trends turn to mixed and mostly positive. The comparison of multiyear time series of SLP reanalysis data with in situ observations at Antarctic stations revealed a considerable overestimate of negative SLP trends in the NCEP/NCAR dataset. Among the four examined reanalysis datasets, ERA5 provided the best agreement with the station data on the annual mean and monthly mean SLP trend values.

Comparing the runoff decompositions of small testbed catchments: end-member mixing analysis against hydrological modelling

This study is focused on the comparison of catchment streamflow composition simulated with three well-known rainfall-runoff (RR) models (ECOMAG, HBV, SWAT) against hydrograph decomposition onto the principal constituents evaluated from End-Member Mixing Analysis (EMMA). There used the data provided by the short-term in-situ observations at two small mountain-taiga experimental catchments located in the south of Pacific Russia. All used RR models demonstrate that two neighboring small catchments disagree significantly in mutual dynamics of the runoff fractions due to geological and landscape structure differences. The geochemical analysis confirmed the differences in runoff generation processes at both studied catchments. The assessment of proximity of the runoff constituents to the hydrograph decomposition with the EMMA that makes a basis for the RR models benchmark analysis. We applied three data aggregation intervals (season, month and pentad) to find a reasonable data generalization period ensuring results clarity. In terms of runoff composition, the most conformable RR model to EMMA is found to be ECOMAG, HBV gets close to reflect specific runoff events well enough, SWAT gives distinctive behavior against other models. The study shows that along with using the standard efficiency criteria reflected proximity of simulated and modelling values of runoff, compliance with the EMMA results might give useful auxiliary information for hydrological modelling results validation.