In recent years, research related to the occurrence of marine heatwave (MHW) events worldwide has been increasing, reporting severe impacts on marine ecosystems which led to losses of marine biodiversity or changes in world fisheries. Many of these studies, based on regional and global coupled models, show relevant biases in the MHW properties when compared with observations. In this study, the MHW frequency of occurrence, the duration and mean intensity over the global oceans are characterized, taking advantage of the new global climate model (GCM) dataset, from the Coupled Model Project Intercomparison Phase 6 (CMIP6). The MHWs result for the historical period are compared with observations, and the future projected changes are characterized under three socioeconomic pathways (SSPs) (SSP1, SSP2 and SSP5), for the middle and end of century (2041–2070 and 2071–2100). The results show a reasonable agreement between the modeled and observed MHW property trends, indicating increases in the frequency, duration and intensity of MHWs along the historical period. For the period 1982–2014, both the ∼2 mean observed events per year and the mean intensity of 0.35 °C above the threshold are underestimated by the multi-model ensemble (MME) mean by 21% and 31%, respectively, while the observed duration of ∼12 d are overestimated by 100%. The future MHWs are expected to increase in duration and intensity, where a near permanent MHW occurs with reference to the historical climate conditions, mainly by the end of the 21st century. The future MHWs intensity, projected by the MME mean, increases in the range of 0.2 °C to 1.5 °C, from the least to the most severe pathways. The GCMs biases obtained with CMIP6 revealed to be in line with the CMIP5 biases, reinforcing the need to use high spatial resolution models to characterize MHW.

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

Tidal estuaries are regarded as highly important ecosystems, mostly due to their high primary productivity and associated role as carbon sinks. In these ecosystems, primary productivity is mainly due to the photosynthetic carbon fixation by phytoplankton and microphytobenthos. The productivity of the two communities has been mostly studied separately, and directly comparable estimates of their carbon fixation rates in the same estuary are relatively scarce. The present study aimed to characterize the spatio-temporal variability of the productivity of phytoplankton and microphytobenthos in a tidal estuary, the Ria de Aveiro (Portugal). The productivity of the two communities was determined using a common methodological approach, based on measurements of in vivo chlorophyll fluorescence, allowing the estimation of the annual ecosystem-level budget for carbon fixation by the two groups. Productivity rates were determined based on synoptic in situ measurements of absolute rates of electron transport rate of photosystem II, using Pulse Amplitude Modulation fluorometry. Chlorophyll fluorescence indices were accompanied by measurements of salinity, temperature, water turbidity, solar irradiance, and planktonic and benthic microalgal biomass. Measurements were carried out hourly, along four spring-neap tidal cycles distributed along 1 year, on three sites of the estuary. The most pronounced trends in the spatio-temporal variability of the photophysiology and productivity of the two communities were the following: (i) maximum biomass and productivity were reached later for microphytobenthos (summer-autumn) than for phytoplankton (spring-summer); (ii) the absorption cross-section of PSII was generally higher for phytoplankton; (iii) the two groups showed a similar photoacclimation state, but microphytobenthos appeared as high light-acclimated when compared to phytoplankton. Biomass-specific productivity was on average higher for phytoplankton than for microphytobenthos, averaging 68.0 and 19.1 mg C mg Chl a^–1 d^–1, respectively. However, areal depth-integrated production rates were generally higher for the microphytobenthos than for the phytoplankton, averaging 264.5 and 140.0 mg C m^–2 d^–1, respectively. On an annual basis, phytoplankton productivity averaged 49.9 g C m^–2 yr^–1 while the productivity of microphytobenthos averaged 105.2 g C m^–2 yr^–1. When upscaling to the whole estuary, annual primary production rates of phytoplankton and microphytobenthos reached 4894.3 and 7534.0 t C yr^–1, respectively, representing 39.4 and 60.6% of the combined total of 12428.3 t C yr^–1 determined for the two communities in the Ria de Aveiro.