The NOAA NCEI marine microplastics database.

Microplastics (<5 mm) pollution is a growing problem affecting coastal communities, marine ecosystems, aquatic life, and human health. The widespread occurrence of marine microplastics, and the need to curb its threats, require expansive, and continuous monitoring. While microplastic research has increased in recent years and generated significant volumes of data, there is a lack of a robust, open access, and long-term aggregation of this data. The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) now provides a global open access to marine microplastics data on an easily discoverable and accessible GIS web map and data portal ( https://www.ncei.noaa.gov/products/microplastics ). The objective of this data portal is to develop a repository where microplastics data are aggregated, archived, and served in a user friendly, consistent, and reliable manner. This work contributes to NCEI's efforts towards data standardization, integration, harmonization, and interoperability among national and international collaborators for monitoring global marine microplastics. This paper describes the NOAA NCEI global marine microplastics database, its creation, quality control procedures, and future directions.

The Ocean Carbon and Acidification Data System.

The Ocean Carbon and Acidification Data System (OCADS) is a data management system at the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI). It manages a wide range of ocean carbon and acidification data, including chemical, physical, and biological observations collected from research vessels, ships of opportunity, and uncrewed platforms, as well as laboratory experiment results, and model outputs. Additionally, OCADS serves as a repository for related Global Ocean Observing System (GOOS) biogeochemistry Essential Ocean Variables (EOVs), e.g., oxygen, nutrients, transient tracers, and stable isotopes. OCADS endeavors to be one of the world's leading providers of ocean carbon and acidification data, information, products, and services. To provide the best data management services to the ocean carbon and acidification research community, OCADS prioritizes adopting a customer-centric approach and gathering knowledge and expertise from the research community to improve its data management practices. OCADS aims to make all ocean carbon and acidification data accessible via a single portal, and welcomes submissions from around the world: https://www.ncei.noaa.gov/products/ocean-carbon-acidification-data-system/.

Another Year of Record Heat for the Oceans.

Changes in ocean heat content (OHC), salinity, and stratification provide critical indicators for changes in Earth's energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth's climate system. In 2022, the world's oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum. According to IAP/CAS data, the 0-2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ (1 Zetta Joules = 1021 Joules); and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins (the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the "salty gets saltier-fresh gets fresher" pattern, also reached its highest level on record in 2022, implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Niña event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.

Another Record: Ocean Warming Continues through 2021 despite La Niña Conditions.

The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate system and increases ocean heat content (OHC). Here, we provide the first analysis of recent OHC changes through 2021 from two international groups. The world ocean, in 2021, was the hottest ever recorded by humans, and the 2021 annual OHC value is even higher than last year's record value by 14 ± 11 ZJ (1 zetta J = 1021 J) using the IAP/CAS dataset and by 16 ± 10 ZJ using NCEI/NOAA dataset. The long-term ocean warming is larger in the Atlantic and Southern Oceans than in other regions and is mainly attributed, via climate model simulations, to an increase in anthropogenic greenhouse gas concentrations. The year-to-year variation of OHC is primarily tied to the El Niño-Southern Oscillation (ENSO). In the seven maritime domains of the Indian, Tropical Atlantic, North Atlantic, Northwest Pacific, North Pacific, Southern oceans, and the Mediterranean Sea, robust warming is observed but with distinct inter-annual to decadal variability. Four out of seven domains showed record-high heat content in 2021. The anomalous global and regional ocean warming established in this study should be incorporated into climate risk assessments, adaptation, and mitigation.

Water Vapor Transfer and Near-Surface Salinity Contrasts in the North Atlantic Ocean.

Maintaining North Atlantic (NA) intra-basin near-surface salinity (NSS) contrast between the high NSS (>37.0) in the subtropical NA (STNA) and low NSS (<35.0) in the subpolar NA (SPNA) has been shown to be important in sustaining the strength of the Atlantic Meridional Overturning Circulation. Evaporation (E) exceeding precipitation (P) in the STNA is primarily responsible for the high NSS there, whereas P dominating E in the SPNA contributes to its low NSS. With a basic understanding of NA intra-basin moisture transport, a correlation analysis was conducted between E-P/NSS over the NA subpolar gyre (SPG) and E-P across the rest of the NA over the 1985-2012 time period. Significant anti-correlations exist between E-P/NSS over the NA SPG and E-P over the central/northern STNA. This suggests that during times of high E over the central/northern STNA there is high (low) precipitation (NSS) over the SPG demonstrating a relationship likely exists between E over the STNA and NSS over the SPG. The maximum anti-correlated area is poleward of the maximum E-P location in the STNA, which is examined. These results provide a first step to ultimately utilizing NSS in the NA as a proxy for estimating changes in the hydrological cycle.

Improved estimates of ocean heat content from 1960 to 2015.

Earth's energy imbalance (EEI) drives the ongoing global warming and can best be assessed across the historical record (that is, since 1960) from ocean heat content (OHC) changes. An accurate assessment of OHC is a challenge, mainly because of insufficient and irregular data coverage. We provide updated OHC estimates with the goal of minimizing associated sampling error. We performed a subsample test, in which subsets of data during the data-rich Argo era are colocated with locations of earlier ocean observations, to quantify this error. Our results provide a new OHC estimate with an unbiased mean sampling error and with variability on decadal and multidecadal time scales (signal) that can be reliably distinguished from sampling error (noise) with signal-to-noise ratios higher than 3. The inferred integrated EEI is greater than that reported in previous assessments and is consistent with a reconstruction of the radiative imbalance at the top of atmosphere starting in 1985. We found that changes in OHC are relatively small before about 1980; since then, OHC has increased fairly steadily and, since 1990, has increasingly involved deeper layers of the ocean. In addition, OHC changes in six major oceans are reliable on decadal time scales. All ocean basins examined have experienced significant warming since 1998, with the greatest warming in the southern oceans, the tropical/subtropical Pacific Ocean, and the tropical/subtropical Atlantic Ocean. This new look at OHC and EEI changes over time provides greater confidence than previously possible, and the data sets produced are a valuable resource for further study.

Electrical conductivity of the global ocean.

The electrical conductivity of the ocean is a fundamental parameter in the electrodynamics of the Earth System. This parameter is involved in a number of applications ranging from the calibration of in situ ocean flow meters, through extensions of traditional induction studies, and into quite new opportunities involving the remote sensing of ocean flow and properties from space-borne magnetometers such as carried aboard the three satellites of the Swarm mission launched in 2013. Here, the first ocean conductivity data set calculated directly from observed temperature and salinity measurements is provided. These data describe the globally gridded, three-dimensional mean conductivity as well as seasonal variations, and the statistics of spatial and seasonal variations are shown. This "climatology" data set of ocean conductivity is offered as a standard reference similar to the ocean temperature and salinity climatologies that have long been available.

The global warming hiatus: Slowdown or redistribution?

Global mean surface temperatures (GMST) exhibited a smaller rate of warming during 1998-2013, compared to the warming in the latter half of the 20th Century. Although, not a "true" hiatus in the strict definition of the word, this has been termed the "global warming hiatus" by IPCC (2013). There have been other periods that have also been defined as the "hiatus" depending on the analysis. There are a number of uncertainties and knowledge gaps regarding the "hiatus." This report reviews these issues and also posits insights from a collective set of diverse information that helps us understand what we do and do not know. One salient insight is that the GMST phenomenon is a surface characteristic that does not represent a slowdown in warming of the climate system but rather is an energy redistribution within the oceans. Improved understanding of the ocean distribution and redistribution of heat will help better monitor Earth's energy budget and its consequences. A review of recent scientific publications on the "hiatus" shows the difficulty and complexities in pinpointing the oceanic sink of the "missing heat" from the atmosphere and the upper layer of the oceans, which defines the "hiatus." Advances in "hiatus" research and outlooks (recommendations) are given in this report.

Estimation of low quantity genes: a hierarchical model for analyzing censored quantitative real-time PCR data.

Analysis of gene quantities measured by quantitative real-time PCR (qPCR) can be complicated by observations that are below the limit of quantification (LOQ) of the assay. A hierarchical model estimated using MCMC methods was developed to analyze qPCR data of genes with observations that fall below the LOQ (censored observations). Simulated datasets with moderate to very high levels of censoring were used to assess the performance of the model; model results were compared to approaches that replace censored observations with a value on the log scale approximating zero or with values ranging from one to the LOQ of ten gene copies. The model was also compared to a Tobit regression model. Finally, all approaches for handling censored observations were evaluated with DNA extracted from samples that were spiked with known quantities of the antibiotic resistance gene tetL. For the simulated datasets, the model outperformed substitution of all values from 1-10 under all censoring scenarios in terms of bias, mean square error, and coverage of 95% confidence intervals for regression parameters. The model performed as well or better than substitution of a value approximating zero under two censoring scenarios (approximately 57% and 79% censored values). The model also performed as well or better than Tobit regression in two of three censoring scenarios (approximately 79% and 93% censored values). Under the levels of censoring present in the three scenarios of this study, substitution of any values greater than 0 produced the least accurate results. When applied to data produced from spiked samples, the model produced the lowest mean square error of the three approaches. This model provides a good alternative for analyzing large amounts of left-censored qPCR data when the goal is estimation of population parameters. The flexibility of this approach can accommodate complex study designs such as longitudinal studies.

Quantitative measurement of blaCMY-2 in a longitudinal observational study of dairy cattle treated with ceftiofur.

There is concern that a relationship exists between antibiotic use in livestock production and the emergence, spread, and persistence of antibiotic resistance. It is important to understand the impact that therapeutic doses of antibiotics for treatment of disease have on resistance because disease treatment typically involves higher doses of antibiotic over short time spans. Absolute quantities of the antibiotic resistance gene bla(CMY-2) were measured by real-time quantitative polymerase chain reaction (qPCR) in the bacterial community DNA of fecal samples from dairy cattle that were given a 5-day course of ceftiofur and untreated cattle during a longitudinal, observational study. A hierarchical linear model that accounts for left-censored data and repeated measures was used to estimate group means of bla(CMY-2) from the qPCR data. Ceftiofur-treated animals had significantly higher mean quantities of bla(CMY-2) than untreated animals during treatment. On the first day post-treatment, mean quantities of bla(CMY-2) returned to pre-treatment levels and remained low in both groups for the remainder of the study. The use of qPCR to measure bla(CMY-2) quantities provided evidence that the burden of resistance in treated animals may have increased temporarily, a result that was not evident when using only cultivation-based methods of testing for resistance.

Climate, landscape, and the risk of orbivirus exposure in cattle in Illinois and western Indiana.

Climate and environmental data were used to estimate the risk of testing positive for antibodies to bluetongue (BTV) and epizootic hemorrhagic disease viruses (EHDV) in cattle in Illinois and western Indiana over three transmission seasons (2000-2002). The risks of BTV and EHDV seropositivity were positively associated with temperature during every year of the study. The EHDV seropositivity was also positively associated with forest patchiness in two of the years. During 2002, a year with unusually high spring rainfall, forest patchiness was not significantly associated with EHDV but spring rainfall did have a moderating effect on temperature. Maps of predicted probability of exposure to BTV or EHDV were created using these best-fitting models and show distinctly different spatial patterns within the same cattle population.

Exploratory spatial data analysis of regional seroprevalence of antibodies against epizootic hemorrhagic disease virus in cattle from Illinois and Indiana.

OBJECTIVE: To estimate seroprevalence of antibodies against the serogroup of epizootic hemorrhagic disease viruses (EHDVs) and describe spatial distribution of antibodies against EHDV among cattle herds in Illinois and western Indiana. SAMPLE POPULATION: 9,414 serum samples collected from cattle in 60 herds over 3 transmission seasons. PROCEDURES: Serum samples were tested for antibodies against EHDV by use of an ELISA. Seroprevalence for 4 zones covering the length of Illinois and parts of Indiana were estimated. A multivariable mixed-effects logistic regression model with a random effect for herd was used to estimate seropositive risk for zone (1 through 4), age (yearling, adult), herd type (beef, dairy), transmission season (2000 to 2002), and zone by year interaction. Isopleth maps of seroprevalence at the herd level were produced. RESULTS: Antibodies against EHDV were detected in 1,110 (11.8%) samples. Estimated seroprevalence in 2000, 2001, and 2002 was 15.3%, 13.4%, and 5.2%, respectively. Seroprevalence was highest in the southernmost zone and lowest in the northernmost zone, but risk of seropositivity for EHDV among and within zones varied by year. Clusters of high seroprevalence in the south, low seroprevalence in the north, and outliers of high and low seroprevalence were detected. Risk mapping revealed areas of higher seroprevalence extending northward along the western and eastern ends of the study region. CONCLUSIONS: Seroprevalence of antibodies against EHDV in cattle was higher in the south than north; however, local complexities existed that were not observed in a serosurvey of antibodies against bluetongue virus from the same cattle population.

Regional seroprevalence of bluetongue virus in cattle in Illinois and western Indiana.

OBJECTIVE: To estimate seroprevalence of bluetongue virus (BTV) and the geographic distribution of seropositive cattle herds in Illinois and western Indiana. SAMPLE POPULATION: 10,585 serum samples obtained from cattle in 60 herds during 3 transmission seasons (2000 through 2002). PROCEDURES: In a longitudinal study, serum samples were tested for BTV antibodies by use of a competitive ELISA. Four geographic zones were created by use of mean minimum January temperature. A multivariable mixed-effects logistic regression model with a random effect for herd was used to estimate seropositive risk for zone, age of cattle, herd type, and transmission season. RESULTS: Overall, BTV antibodies were detected in 156 (1.5%) samples. Estimated seroprevalence in 2000, 2001, and 2002 was 1.49%, 0.97%, and 2.18%, respectively. Risk of being seropositive for BTV was associated with geographic zone and age. Seroprevalence increased progressively from northern to southern zones, with no evidence of BTV infection in the northernmost zone. In the southernmost zone, annual seroprevalence ranged from 8.65% to 11.00%. Adult cattle were 2.35 times as likely as juvenile cattle to be seropositive. CONCLUSIONS AND CLINICAL RELEVANCE: Overall seroprevalence was lower than has been reported for Illinois cattle. Bluetongue virus antibodies were distributed heterogeneously in this region. Only in the southernmost zone was seroprevalence consistently > 2%. Regionalization of BTV risk based on state borders does not account for such variability. Serologic data could be combined with landscape, climate, and vector data to develop predictive models of BTV risk within transitional regions of the United States.