Search

Snow provides critical water resources for billions of people, making the remote sensing of snow water equivalent (SWE) a highly prioritized endeavor, particularly given ongoing climate change impacts. Synthetic aperture radar (SAR) is a promising method for remote sensing of SWE because radar penetrates snow, and SAR interferometry (InSAR) can be used to estimate changes in SWE (ΔSWE) between SAR acquisitions. We calculated ΔSWE retrievals from 10 NASA L-band (1–2 GHz, ∼25 cm wavelength) uninhabited aerial vehicle SAR (UAVSAR) acquisitions covering a ∼640 km2 swath in northern Colorado during the winters of 2020 and 2021. UAVSAR acquisitions coincided with ∼117 mm of accumulation in 2020 and ∼282 mm of accumulation in 2021. ΔSWE retrievals were evaluated against measurements of SWE from repeat ground-penetrating radar (GPR) and terrestrial lidar scans (TLSs) collected during the NASA SnowEx time series campaigns at two field sites (total area =∼0.2 km2) as well as SWE measurements from seven automated stations distributed throughout the UAVSAR swath. For single InSAR pairs, UAVSAR ΔSWE retrievals yielded an overall r of 0.72–0.79 and an RMSE of 19–22 mm when compared with TLS and GPR ΔSWE retrievals. UAVSAR ΔSWE showed some scatter with ΔSWE measured at automated stations for both study years, but cumulative UAVSAR SWE yielded a r of 0.92 and an RMSE of 42 mm when compared to total SWE measured by the stations. Further, UAVSAR ΔSWE RMSEs differed by mm for coherences (i.e., the complex interferometric coherence) of 0.10 to 0.90, suggesting that coherence has only a small influence on the ΔSWE retrieval accuracy. Given the evaluations presented here and in other recent studies, the upcoming NASA-ISRO SAR (NISAR) satellite mission, with a 12 d revisit period, offers an exciting opportunity to apply this methodology globally.

Marine sediments are excellent archives for reconstructing past changes in climate and ocean circulation. Overlapping with instrumental records, they hold the potential to elucidate natural variability and contextualize current changes. Yet, dating uncertainties of traditional approaches (e.g., up to ± 30–50 years for the last 2 centuries) pose major challenges for integrating the shorter instrumental records with these extended marine archives. Hence, robust sediment chronologies are crucial, and most existing age model constraints do not provide sufficient age control, particularly for the 20th century, which is the most critical period for comparing proxy records to historical changes. Here we propose a novel chronostratigraphic approach that uses anthropogenic signals such as the oceanic 13C Suess effect and spheroidal carbonaceous fly-ash particles to reduce age model uncertainties in high-resolution marine archives. As a test, we apply this new approach to a marine sediment core located at the Gardar Drift, in the subpolar North Atlantic, and revise the previously published age model for this site. We further provide a refined estimate of regional reservoir corrections and uncertainties for Gardar Drift.

Abstract Background Acquired brain injury (ABI) often leads to persisting somatic, cognitive, and social impairments. Cognitive impairments of processing speed, sustained attention, and working memory are frequently reported and may negatively affect activities of daily living and quality of life. Rehabilitation efforts aiming to retrain these cognitive functions have often consisted of computerized training programs. However, few studies have demonstrated effects that transfer beyond the trained tasks. There is a growing optimism regarding the potential usefulness of virtual reality (VR) in cognitive rehabilitation. The research literature is sparse, and existing studies are characterized by considerable methodological weaknesses. There is also a lack of knowledge about the acceptance and tolerability of VR as an intervention method for people with ABI. The present study aims to investigate whether playing a commercially available VR game is effective in training cognitive functions after ABI and to explore if the possible effects transfer into everyday functioning. Methods One hundred participants (18–65 years), with a verified ABI, impairments of processing speed/attention, and/or working memory, and a minimum of 12 months post injury will be recruited. Participants with severe aphasia, apraxia, visual neglect, epilepsy, and severe mental illness will be excluded. Participants will be randomized into two parallel groups: (1) an intervention group playing a commercial VR game taxing processing speed, working memory, and sustained attention; (2) an active control group receiving psychoeducation regarding compensatory strategies, and general cognitive training tasks such as crossword puzzles or sudoku. The intervention period is 5 weeks. The VR group will be asked to train at home for 30 min 5 days per week. Each participant will be assessed at baseline with neuropsychological tests and questionnaires, after the end of the intervention (5 weeks), and 16 weeks after baseline. After the end of the intervention period, focus group interviews will be conducted with 10 of the participants in the intervention group, in order to investigate acceptance and tolerability of VR as a training method. Discussion This study will contribute to improve understanding of how VR is tolerated and experienced by the ABI population. If proven effective, the study can contribute to new rehabilitation methods that persons with ABI can utilize in a home setting, after the post-acute rehabilitation has ended.

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2), chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA National Centers for Environmental Information (NCEI), which also provides access to the merged data product. This is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/zyrq-ht66 (Lauvset et al., 2023). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2023 methods and provides a broad overview of the secondary quality control procedures and results.

Abstract Aim Eating disorders have a serious impact on quality of life, especially when combined with Type 1 diabetes. We investigated eating disorders in relation to factors early in life with some focus on Type 1 diabetes. Methods Out of 21,700 children born 1st of Oct 1997–1st of Oct 1999 17,055 (78.6%) were included in ABIS (All Babies in southeast Sweden) and 16,415 had adequate questionnaires. ICD-10 diagnosis from The National Patient Register was merged with the ABIS data. Results In total 247 individuals, 19 boys (7.7%) and 219 girls (92.3%) out of 16,415 (1.5%) developed eating disorders (EDs), 167 (1.0%) Type 1 diabetes of whom 7 (4.2%) also got eating disorders (ED) (OR 3.25 (1.47–7.28); p = 0.04), all of them years after diagnosis of Type 1 diabetes. EDs was associated with high parental education especially in fathers (OR 1.65 (1.09–2.50); p = 0.02) and to at birth anxiety, and depression among mothers. There was no association with the duration of breastfeeding. Conclusions Eating disorders are common in girls, with increased risk in high-educated but psychologically vulnerable families. Prevalence is increased in type 1 diabetes. Even modern diabetes treatment needs to be completed with psychological support. Level of evidence Level III: Evidence obtained from well-designed cohort or case–control analytic studies.

Abstract The oceanic uptake and resulting storage of the anthropogenic CO2 (Cant) that humans have emitted into the atmosphere moderates climate change. Yet our knowledge about how this uptake and storage has progressed in time remained limited. Here, we determine decadal trends in the storage of Cant by applying the eMLR(C*) regression method to ocean interior observations collected repeatedly since the 1990s. We find that the global ocean storage of Cant grew from 1994 to 2004 by 29 ± 3 Pg C dec−1 and from 2004 to 2014 by 27 ± 3 Pg C dec−1 (±1σ). The storage change in the second decade is about 15 ± 11% lower than one would expect from the first decade and assuming proportional increase with atmospheric CO2. We attribute this reduction in sensitivity to a decrease of the ocean buffer capacity and changes in ocean circulation. In the Atlantic Ocean, the maximum storage rate shifted from the Northern to the Southern Hemisphere, plausibly caused by a weaker formation rate of North Atlantic Deep Waters and an intensified ventilation of mode and intermediate waters in the Southern Hemisphere. Our estimates of the Cant accumulation differ from cumulative net air‐sea flux estimates by several Pg C dec−1, suggesting a substantial and variable, but uncertain net loss of natural carbon from the ocean. Our findings indicate a considerable vulnerability of the ocean carbon sink to climate variability and change.

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulfur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured on board the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using certified reference material (CRM) measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality-controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA NCEI (https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/GLODAPv2_2022/, last access: 15 August 2022). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/1f4w-0t92 (Lauvset et al., 2022). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2022 methods and provides a broad overview of the secondary quality control procedures and results.

Due to low calcium carbonate saturation states, and winter mixing that brings anthropogenic carbon to the deep ocean, the Nordic Seas and their cold-water corals are vulnerable to ocean acidification. Here, we present a detailed investigation of the changes in pH and aragonite saturation in the Nordic Seas from preindustrial times to 2100, by using in situ observations, gridded climatological data, and projections for three different future scenarios with the Norwegian Earth System Model (NorESM1-ME). During the period of regular ocean biogeochemistry observations from 1981–2019, the pH decreased with rates of 2–3 × 10−3 yr−1 in the upper 200 m of the Nordic Seas. In some regions, the pH decrease can be detected down to 2000 m depth. This resulted in a decrease in the aragonite saturation state, which is now close to undersaturation in the depth layer of 1000–2000 m. The model simulations suggest that the pH of the Nordic Seas will decrease at an overall faster rate than the global ocean from the preindustrial era to 2100, bringing the Nordic Seas' pH closer to the global average. In the esmRCP8.5 scenario, the whole water column is projected to be undersaturated with respect to aragonite at the end of the 21st century, thereby endangering all cold-water corals of the Nordic Seas. In the esmRCP4.5 scenario, the deepest cold-water coral reefs are projected to be exposed to undersaturation. Exposure of all cold-water corals to corrosive waters can only be avoided with marginal under the esmRCP2.6 scenario. Over all timescales, the main driver of the pH drop is the increase in dissolved inorganic carbon (CT) caused by the raising anthropogenic CO2, followed by the temperature increase. Thermodynamic salinity effects are of secondary importance. We find substantial changes in total alkalinity (AT) and CT as a result of the salinification, or decreased freshwater content, of the Atlantic water during all time periods, and as a result of an increased freshwater export in polar waters in past and future scenarios. However, the net impact of this decrease (increase) in freshwater content on pH is negligible, as the effects of a concentration (dilution) of CT and AT are canceling.

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2021 is an update of the previous version, GLODAPv2.2020 (Olsen et al., 2020). The major changes are as follows: data from 43 new cruises were added, data coverage was extended until 2020, all data with missing temperatures were removed, and a digital object identifier (DOI) was included for each cruise in the product files. In addition, a number of minor corrections to GLODAPv2.2020 data were performed. GLODAPv2.2021 includes measurements from more than 1.3 million water samples from the global oceans collected on 989 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For this annual update, adjustments for the 43 new cruises were derived by comparing those data with the data from the 946 quality controlled cruises in the GLODAPv2.2020 data product using crossover analysis. Comparisons to estimates of nutrients and ocean CO2 chemistry based on empirical algorithms provided additional context for adjustment decisions in this version. The adjustments are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent with to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon Data System of NOAA NCEI (https://www.ncei.noaa.gov/access/ocean-carbon-data-system/oceans/GLODAPv2_2021/, last access: 7 July 2021). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/ttgq-n825 (Lauvset et al., 2021). These bias-adjusted product files also include significant ancillary and approximated data and can be accessed via https://www.glodap.info (last access: 29 June 2021). These were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2021 methods and provides a broad overview of the secondary quality control procedures and results.

Educators in Belize are charged with ensuring that all Belizeans are given an opportunity to acquire a quality education that promotes personal development and productive citizenship. Consequently, Belizean law now requires all children from ages five through fourteen to attend at least eight years of primary school. Students with special needs have historically not received accommodations in the education system, so many teachers struggle with meeting the needs of students with learning disabilities in these inclusive settings. This qualitative case study explored teaching strategies and contextual factors in inclusive primary classrooms in Belize and was conducted in the form of Community Engaged Research in partnership with the Ministry of Education, Youth, Sports, and Culture (MOE). Findings suggest consistent approaches for differentiating instruction, teacher passion for teaching and commitment to meeting student needs, a need for additional resources and training, and a disconnect between families and schools. Interpretation of these findings through Hornby's (2015) theory of inclusive education suggests that Belize is primarily following inclusivity as students with disabilities are integrated into the mainstream educational system. However, while some principles and practices of inclusion are followed, other features are absent. Adding a special education component could enhance student learning as individualization and standardization of instruction, expectations, and assessment could occur between teachers, across grade levels, and in communication with families. A special education component with associated teacher training could support teacher desire for additional resources and meet the needs of an increasingly diverse population of students.

Early childhood teachers play a critical role in the kindergarten readiness of preschool age children. Yet, they often receive little and insufficient training in the use of evidence-based practices that can increase academic success and prevent undesired behaviors. As a result, preschool teachers tend to use more exclusionary practices when disciplining students. A promising strategy for developing the skills of preschool teachers is the use of bug-in-ear coaching, a coaching strategy where a trained individual provides in-the-moment support to a teacher from a location outside of the classroom. This study examined bug-in-ear coaching to support preschool teachers in using opportunities to respond during explicit math instruction. A multiple baseline design across teachers was used to assess the impact of the intervention on the teachers' rates of implementation of opportunities to respond. Bug-in-ear coaching was associated with an increased rate of opportunities to respond for all teachers during the intervention with a functional relation for two out of four teachers. All teachers' rates of opportunities to respond were below their intervention rates during maintenance. Further, teachers reported enjoying the intervention and the opportunity given to improve their practices. Teachers also expressed their desire to have this level of coaching in their centers.

We developed a simple method to refine existing open-ocean maps and extend them towards different coastal seas. Using a multi-linear regression we produced monthly maps of surface ocean fCO2 in the northern European coastal seas (the North Sea, the Baltic Sea, the Norwegian Coast and the Barents Sea) covering a time period from 1998 to 2016. A comparison with gridded Surface Ocean CO2 Atlas (SOCAT) v5 data revealed mean biases and standard deviations of 0 ± 26 µatm in the North Sea, 0 ± 16 µatm along the Norwegian Coast, 0 ± 19 µatm in the Barents Sea and 2 ± 42 µatm in the Baltic Sea. We used these maps to investigate trends in fCO2, pH and air–sea CO2 flux. The surface ocean fCO2 trends are smaller than the atmospheric trend in most of the studied regions. The only exception to this is the western part of the North Sea, where sea surface fCO2 increases by 2 µatm yr−1, which is similar to the atmospheric trend. The Baltic Sea does not show a significant trend. Here, the variability was much larger than the expected trends. Consistently, the pH trends were smaller than expected for an increase in fCO2 in pace with the rise of atmospheric CO2 levels. The calculated air–sea CO2 fluxes revealed that most regions were net sinks for CO2. Only the southern North Sea and the Baltic Sea emitted CO2 to the atmosphere. Especially in the northern regions the sink strength increased during the studied period.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.6 ± 0.7 GtC yr−1. For the same decade, GATM was 5.1 ± 0.02 GtC yr−1 (2.4 ± 0.01 ppm yr−1), SOCEAN 2.5 ±  0.6 GtC yr−1, and SLAND 3.4 ± 0.9 GtC yr−1, with a budget imbalance BIM of −0.1 GtC yr−1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr−1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr−1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr−1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.6 ± 0.6 GtC yr−1, and SLAND was 3.1 ± 1.2 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about −7 % (median estimate) based on individual estimates from four studies of −6 %, −7 %, −7 % (−3 % to −11 %), and −13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2020 (Friedlingstein et al., 2020).

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2020 is an update of the previous version, GLODAPv2.2019. The major changes are data from 106 new cruises added, extension of time coverage to 2019, and the inclusion of available (also for historical cruises) discrete fugacity of CO2 (fCO2) values in the merged product files. GLODAPv2.2020 now includes measurements from more than 1.2 million water samples from the global oceans collected on 946 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to WOCE exchange format and (ii) as a merged data product with adjustments applied to minimize bias. These adjustments were derived by comparing the data from the 106 new cruises with the data from the 840 quality-controlled cruises of the GLODAPv2.2019 data product using crossover analysis. Comparisons to empirical algorithm estimates provided additional context for adjustment decisions; this is new to this version. The adjustments are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete fCO2, were not subjected to bias comparison or adjustments. The original data and their documentation and DOI codes are available at the Ocean Carbon Data System of NOAA NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2_2020/, last access: 20 June 2020). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/2c8h-sa89 (Olsen et al., 2020). These bias-adjusted product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2020 methods and provides a broad overview of the secondary quality control procedures and results.

Anthropogenic emissions of CO2 to the atmosphere have modified the carbon cycle for more than 2 centuries. As the ocean stores most of the carbon on our planet, there is an important task in unraveling the natural and anthropogenic processes that drive the carbon cycle at different spatial and temporal scales. We contribute to this by designing a global monthly climatology of total dissolved inorganic carbon (TCO2), which offers a robust basis in carbon cycle modeling but also for other studies related to this cycle. A feedforward neural network (dubbed NNGv2LDEO) was configured to extract from the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2.2019) and the Lamont–Doherty Earth Observatory (LDEO) datasets the relations between TCO2 and a set of variables related to the former's variability. The global root mean square error (RMSE) of mapping TCO2 is relatively low for the two datasets (GLODAPv2.2019: 7.2 µmol kg−1; LDEO: 11.4 µmol kg−1) and also for independent data, suggesting that the network does not overfit possible errors in data. The ability of NNGv2LDEO to capture the monthly variability of TCO2 was testified through the good reproduction of the seasonal cycle in 10 time series stations spread over different regions of the ocean (RMSE: 3.6 to 13.2 µmol kg−1). The climatology was obtained by passing through NNGv2LDEO the monthly climatological fields of temperature, salinity, and oxygen from the World Ocean Atlas 2013 and phosphate, nitrate, and silicate computed from a neural network fed with the previous fields. The resolution is 1∘×1∘ in the horizontal, 102 depth levels (0–5500 m), and monthly (0–1500 m) to annual (1550–5500 m) temporal resolution, and it is centered around the year 1995. The uncertainty of the climatology is low when compared with climatological values derived from measured TCO2 in the largest time series stations. Furthermore, a computed climatology of partial pressure of CO2 (pCO2) from a previous climatology of total alkalinity and the present one of TCO2 supports the robustness of this product through the good correlation with a widely used pCO2 climatology (Landschützer et al., 2017). Our TCO2 climatology is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/10551, Broullón et al., 2020).

As elsewhere in the world, academic misconduct is a serious problem in Aotearoa. Yet, beyond the occasional newspaper headline, we know relatively little about the extent of the problem here or the factors associated with it. Consequently, our educational leaders and practitioners are left under-informed as they seek to address the problem and promote academic integrity. To help provide the knowledge and insights needed to craft good policy and best practice, the Research on Academic Integrity in New Zealand (RAINZ) Project--a research collaboration involving eight tertiary institutions--was founded in 2021. In the second semester of 2022, the RAINZ Project launched the first-ever nationwide survey of undergraduate students' perceptions, attitudes, and behaviours related to academic integrity. Results from this survey, which was completed by undergraduates (N = 4493), indicate that most students (approximately two-thirds) reported engaging in at least one form of academic misconduct in the past year. As hypothesised, students' perceptions (of the institutional climate and peer norms) and moral attitudes (related to cheating) were significantly associated with their engagement in academic misconduct. Details of these results as well as their implications for policy and practice are discussed.

Background: Studies have found that presence of challenging behaviours and mental health problems limits employment for people with intellectual disabilities. This study investigates the associations between age, gender, living condition, level of intellectual disability, diagnoses, behaviour, mental health, and employment in adults with intellectual disabilities in Norway. Method: A cross-sectional community-based survey including 214 adult participants (56% men) with intellectual disabilities. Results: In our sample, 25% had no organised day activity, 27% attended non-work day care, 19% attended sheltered employment, or day care with production, without pay and 29% worked in paid sheltered employment. One participant attended mainstream employment. Moderate and severe/profound level of intellectual disability, possible organic condition and irritability significantly reduced the odds of employment (paid and unpaid). Conclusion: Findings suggest unequal access to the sheltered employment that was meant to be inclusive. More individualised evaluation of prerequisites is suggested to further facilitate employment for this group.

The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of water samples. This update of GLODAPv2, v2.2019, adds data from 116 cruises to the previous version, extending its coverage in time from 2013 to 2017, while also adding some data from prior years. GLODAPv2.2019 includes measurements from more than 1.1 million water samples from the global oceans collected on 840 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have undergone extensive quality control, especially systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to WOCE exchange format and (ii) as a merged data product with adjustments applied to minimize bias. These adjustments were derived by comparing the data from the 116 new cruises with the data from the 724 quality-controlled cruises of the GLODAPv2 data product. They correct for errors related to measurement, calibration, and data handling practices, taking into account any known or likely time trends or variations. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH, and 5 % in the halogenated transient tracers. The compilation also includes data for several other variables, such as isotopic tracers. These were not subjected to bias comparison or adjustments. The original data, their documentation and DOI codes are available in the Ocean Carbon Data System of NOAA NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2_2019/, last access: 17 September 2019). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/xnme-wr20 (Olsen et al., 2019). The product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This paper documents the GLODAPv2.2019 methods and provides a broad overview of the secondary quality control procedures and results.

Global climatologies of the seawater CO2 chemistry variables are necessary to assess the marine carbon cycle in depth. The climatologies should adequately capture seasonal variability to properly address ocean acidification and similar issues related to the carbon cycle. Total alkalinity (AT) is one variable of the seawater CO2 chemistry system involved in ocean acidification and frequently measured. We used the Global Ocean Data Analysis Project version 2.2019 (GLODAPv2) to extract relationships among the drivers of the AT variability and AT concentration using a neural network (NNGv2) to generate a monthly climatology. The GLODAPv2 quality-controlled dataset used was modeled by the NNGv2 with a root-mean-squared error (RMSE) of 5.3 µmol kg−1. Validation tests with independent datasets revealed the good generalization of the network. Data from five ocean time-series stations showed an acceptable RMSE range of 3–6.2 µmol kg−1. Successful modeling of the monthly AT variability in the time series suggests that the NNGv2 is a good candidate to generate a monthly climatology. The climatological fields of AT were obtained passing through the NNGv2 the World Ocean Atlas 2013 (WOA13) monthly climatologies of temperature, salinity, and oxygen and the computed climatologies of nutrients from the previous ones with a neural network. The spatiotemporal resolution is set by WOA13: 1∘ × 1∘ in the horizontal, 102 depth levels (0–5500 m) in the vertical and monthly (0–1500 m) to annual (1550–5500 m) temporal resolution. The product is distributed through the data repository of the Spanish National Research Council (CSIC; https://doi.org/10.20350/digitalCSIC/8644, Broullón et al., 2019).

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018.