National Oceanographic And Atmospheric Administration Research Articles

Assessing NOAA Rip-Current Hazard Likelihood Predictions: Comparison with Lifeguard Observations and Parameterizations of Bathymetric and Transient Rip-Current Types

Abstract Rip currents, fast offshore-directed flows, are the leading cause of death and rescues on surf beaches worldwide. The National Oceanic and Atmospheric Administration (NOAA) seeks to minimize this threat by providing rip-current hazard likelihood forecasts based on environmental conditions from the Nearshore Wave Prediction System. Rip currents come in several types, including bathymetric rip currents that form when waves break on sandbars interspersed with channels and transient rip currents that form when there are breaking waves coming from multiple directions. The NOAA model was developed and tested in an area where bathymetric rip currents may be the most prevalent type of rip current. Therefore, model performance in regions where other types of rip currents (e.g., transient rip currents) may be more ubiquitous remains unknown. To investigate the efficacy of the NOAA model guidance in the context of different rip-current types, we compared modeled rip-current probabilities with physical-based parameterizations of bathymetric and transient rip-current speeds. We also compared these probabilities to lifeguard observations of bathymetric and transient rip currents from Salt Creek Beach, California, in summer and fall 2021. We found that the NOAA model skillfully predicts a wide range of hazardous parameterized bathymetric speeds but generally underpredicts hazardous transient rip-current speeds and the hazardous rip currents observed at Salt Creek Beach. Our results demonstrate how wave parameters, including directional spread, may serve as environmental indicators of rip-current hazard. By evaluating factors that influence the skill of modeled rip-current predictions, we strive toward improved rip-current hazard forecasting. Significance Statement The purpose of this study is to evaluate how well the NOAA rip-current hazard model predicts different rip-current types. Accurate forecasting of rip currents is important because rip currents are the leading cause of death and rescues at surf beaches worldwide. By comparing the performance of the NOAA model to parameterized rip-current speed and lifeguard observations of rip-current strength, we highlighted the model’s decreased ability to predict hazardous transient rip currents compared to hazardous bathymetric rip currents. Because bathymetric and transient rip currents are driven by different environmental conditions, an improved hazard model must be sensitive to these different conditions to predict a greater range of hazardous rip currents.

Biologically Important Areas II for cetaceans within U.S. and adjacent waters - West Coast Region

Here we update U.S. West Coast Biologically Important Areas (BIAs) that were published in 2015 using new data and approaches. Additionally, BIAs were delineated for two species that were not delineated in the 2015 BIAs: fin whales and Southern Resident killer whales (SRKW). While harbor porpoise BIAs remained the same, substantial changes were made for other species including identifying both larger overall areas (parent BIAs) and smaller core areas (child BIAs). For blue, fin, and humpback whales we identified, delineated, and scored BIAs using the overlap between the distribution and relative density from three data sources, leveraging the strengths and weaknesses of these approaches: 1) habitat density models based on Southwest Fisheries Science Center (SWFSC) line-transect data from systematic ship surveys conducted through 2018, 2) satellite tag data from deployments conducted by three research groups, and 3) sightings of feeding behavior from non-systematic effort mostly associated with small-boat surveys for photo-identification conducted by Cascadia Research Collective. While the previous BIAs were based solely on a more subjective assignment from only the small boat sightings, here we incorporate the other two data sources and use a more rigorous, quantitative approach to identify higher density areas and integrate the data types. This resulted in larger, better-supported, objective BIAs compared to the previous effort. Our methods are also more consistent with the delineation of BIAs in other regions. For SRKWs, the parent BIA was based on a modification of the Critical Habitat boundaries defined by the National Oceanographic and Atmospheric Administration (NOAA) and the Department of Fisheries and Oceans (DFO) Canada; a core BIA highlighting areas of intensified use was identified using both NOAA’s Critical Habitat and kernel density analyses of satellite tag data. Gray whale BIAs were re-evaluated for the migratory corridor of Eastern North Pacific gray whales, for Pacific Coast Feeding Group feeding areas, and for gray whales that feed regularly in Puget Sound.

Bringing the Submarine Mariana Arc and Backarc Basin to Life for Undergraduates and the Public

ABSTRACTThis paper aims to better teach about submarine arc and backarc basin volcanic and hydrothermal activity using the ~1400 km long Mariana convergent margin as an example. Four US National Oceanographic and Atmospheric Administration (NOAA) expeditions (2004–2016) equipped with a remotely operated vehicle (ROV) have discovered and explored many of submarine volcanoes and associated hydrothermal fields and generated many short (~1 min long) videos about them. Some of these videos would be very useful for teaching about these processes if they were organized and context provided, which is done here. Eighteen short videos about nine sites generated by NOAA are presented and discussed here. These are organized into three categories: volcanic eruptions, magmatic degassing, and hydrothermal activity. Volcanic eruption videos include two about glassy pillow lavas erupted in 2013–2015 and a rare example of a submarine eruption. Four videos about magmatic degassing include an example of sulfur produced by disproportionation of magmatic sulfur dioxide associated with a submarine eruption, two rare examples of molten sulfur lakes, and liquid carbon dioxide venting. Four videos about hydrothermal activity are provided. Suggestions for how this material might be used in the classroom are also given.

A New Look on the Epidemiology of Slipped Capital Femoral Epiphysis: A Topic Revisited

Background: Slipped capital femoral epiphysis (SCFE) is a common hip pathology affecting adolescents mostly in the rapid growth phase. Previous studies have presented epidemiological data to inform practitioners on its etiology to improve diagnosis, treatment, and prevention. However, in recent years national databases have been redesigned, which may change previously published information on SCFEs. The purpose of this study is to evaluate SCFE epidemiology using the 2019 Kids' Inpatient Database (KID) and HCUPnet, Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality, in conjunction with U.S. Census Data.Methods: The Kids' Inpatient Database (KID) reflects data on 5.9 million pediatric discharges in 2019 and was combined with U.S. Census data to produce epidemiologic data regarding SCFEs in the pediatric population. KID regional data was then overlayed with National Oceanographic and Atmospheric Administration (NOAA) data to assess the associations between climate patterns and UV indices with SCFE incidence.Results: Overall incidence of SCFE in the U.S. was 2.66/100,000 children 9-16 years of age. The average age at presentation with SCFE was 12.3 years with males being older at presentation (12.8 vs. 11.6 years; P<.001; r=0.34). Males were significantly more likely to develop a SCFE than females (OR 1.73; 95% CI, 1.51-1.97). Black patients were significantly more likely to present with a SCFE than all other races (OR 1.66; 95% CI, 1.40-2.97). Obesity (23.2%) was the most common metabolic and endocrine comorbidity followed by severe obesity (7.5%). Geographical regions with colder temperatures and lower UV indexes had higher SCFE rates, while regions with higher temperatures and higher UV indexes had lower SCFE rates.Conclusion: This study determined a lower SCFE incidence rate than previously reported but shows similar distributions of SCFEs amongst different races. Age of onset was increased compared to previous studies. The rate of obesity also continues to increase while the incidence of SCFEs has experienced a gradual decrease over time. It is plausible that environmental factors and race (skin tone) may have a more influential effect on the development of this pathology.Level of Evidence: III - Cross-sectional study of non-consecutive patientsKey Concepts•SCFE incidence rates are lower than previously reported.•Obesity continues to increase while SCFEs have remained stable.•Cold climate regions (with lower UV-indexes) may be a risk factor for SCFEs, while areas with hot climate regions (with higher UV-indexes) could be protective.

Resource Equivalency Analysis (REA): Implication environmental of groundwater in Kupang East Nusa Tenggara

This article discusses the environmental assessment caused by the commercial use of groundwater by the community as landowners. In the future, this practice must receive direction and responsibility from the government as policymakers to prevent and repair environmental damage, especially habitat damage and species in strengthening the principle of "paying for commercial groundwater" with the REA methodology to assess and compensate for environmental damage. This method, developed by the National Oceanographic and Atmospheric Administration (NOAA), uses the scale of remediation required to compensate for past, current and future damage. The compensation approaches are the services approach (or the resources approach) and the valuation approach (the value-to-value and value-to-cost approach). The results show that the change in residential land is 0.16%, or 25 ha. The total area of changed settlement/land built up has decreased the function of land which was originally secondary/logged-over dry land forest to become settlement/land built up. Furthermore, there was a decrease in secondary/logged-over dry land forest to open field of 0.03% or 3.1 ha, so that the total area of secondary/logged-over dry land forest decreased by 0.19% or 28.1 ha.

Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles.

This work presents an open-source matlab software package for exploiting recent advances in extracting tonal signals from large acoustic data sets. A whistle extraction algorithm published by Li, Liu, Palmer, Fleishman, Gillespie, Nosal, Shiu, Klinck, Cholewiak, Helble, and Roch [(2020). Proceedings of the International Joint Conference on Neural Networks, July 19-24, Glasgow, Scotland, p. 10] is incorporated into silbido, an established software package for extraction of cetacean tonal calls. The precision and recall of the new system were over 96% and nearly 80%, respectively, when applied to a whistle extraction task on a challenging two-species subset of a conference-benchmark data set. A second data set was examined to assess whether the algorithm generalized to data that were collected across different recording devices and locations. These data included 487 h of weakly labeled, towed array data collected in the Pacific Ocean on two National Oceanographic and Atmospheric Administration (NOAA) cruises. Labels for these data consisted of regions of toothed whale presence for at least 15 species that were based on visual and acoustic observations and not limited to whistles. Although the lack of per whistle-level annotations prevented measurement of precision and recall, there was strong concurrence of automatic detections and the NOAA annotations, suggesting that the algorithm generalizes well to new data.

Assessment of Toxic Heavy Metals in Surface Water of the Meghna River Estuary: An Integrated Statistical Approach

Rapid industrial development and negligible waste disposal management are considered the driving factors for the major environmental crisis in developing countries like Bangladesh. In the present study, the surface water of Meghna River estuary was evaluated for the concentrations of five toxic heavy metals, namely chromium (Cr), lead (Pb), cadmium (Cd), arsenic (As), and mercury (Hg). All the heavy metals in question were found to be higher than the background value of natural surface water. The toxic heavy metals were in the descending order of Pb&gt;Cr&gt;Hg&gt;Cd&gt;As in the collected water samples. Pb and Hg were found to exceed the lowest biological chronic safety concentration limits recommended by the National Oceanographic and Atmospheric Administration (NOAA), whereas Cr, Cd, and As were under the admissible limits. Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Pearson’s correlation analysis suggested that the sources and distribution of those toxic heavy metals are similar. Anthropogenic activities such as industrial waste, agricultural runoff, and municipal solid waste disposal may be responsible for the increased concentration of those metals. Compared to China’s secondary seawater quality standard, the concentration of heavy metals in the Meghna estuary is considerably higher, except arsenic. When compared with previous studies, the heavy metals concentration in the Meghna estuary is significantly higher, which is alarming. From this integrated study, the Meghna estuary is under threatening conditions from ecological and human health perspectives. Further studies are required for temporal monitoring and assessment of the Meghna River estuary. The Dhaka University Journal of Earth and Environmental Sciences, Centennial Special Volume June 2022: 143-155

Detection of Snow Cover from Historical and Recent AVHHR Data—A Thematic TIMELINE Processor

Global snow cover forms the largest and most transient part of the cryosphere in terms of area. On the local and regional scale, small changes can have drastic effects such as floods and droughts, and on the global scale is the planetary albedo. Daily imagery of snow cover forms the basis of long-term observation and analysis, and only optical sensors offer the necessary spatial and temporal resolution to address decadal developments and the impact of climate change on snow availability. The MODIS sensors have been providing this daily information since 2000; before that, only the Advanced Very High-Resolution Radiometer (AVHRR) from the National Oceanographic and Atmospheric Administration (NOAA) was suitable. In the TIMELINE project of the German Aerospace Center, the historic AVHRR archive in HRPT (High Resolution Picture Transmission) format is processed for the European area and, among other processors, one output is the thematic product ‘snow cover’ that will be made available in 1 km resolution since 1981. The snow detection is based on the Normalized Difference Snow Index (NDSI), which enables a direct comparison with the MODIS snow product. In addition to the NDSI, ERA5 re-analysis data on the skin temperature and other level 2 TIMELINE products are included in the generation of the binary snow mask. The AVHRR orbit segments are projected from the swath projection into LAEA Europe, aggregated into daily coverages, and from this, the 10-day and monthly snow covers are finally calculated. In this publication, the snow cover algorithm is presented, as well as the results of the first validations and possible applications of the final product.

Three new species of pagurid hermit crabs (Decapoda: Anomura: Paguroidea) from the Northern Mariana Islands, Micronesia.

We describe three new species of hermit crab of the pagurid genera, Catapagurus A. Milne-Edwards, 1880, Nematopagurus A. Milne-Edwards Bouvier, 1892 and Pagurixus Melin, 1939, on the basis of material collected during the scientific cruise to the Northern Mariana Islands conducted by the U.S. National Oceanographic and Atmospheric Administration (NOAA) in 2015. Catapagurus tenuilamina n. sp., referred to the C. ensifer Henderson, 1893 species group, appears close to C. granulatus Edmondson, 1951, but differs from the latter in the more slender ultimate article of the antennular peduncle, more slender dactyli of pereopods 2 and 3, and the possession of two dorsal subdistal spines in the meri of the pereopods. Nematopagurus marianicus n. sp. resembles N. gardineri Alcock, 1905 and N. lewinsohni Trkay, 1986, but is distinguished from the latter two by the characteristic dense setation on the upper part of the left cheliped carpus and by the elongate dactyli of pereopods 2 and 3 that lack a row of bristle-like setae on the dorsal margins. Pagurixus eminens n. sp. is referred to the P. boninensis Melin, 1939 species group and appears closest to P. annulus Komai Poupin, 2013, but is differentiated from the latter in the shape and ornamentation of the right coxa of pereopod 5 in the male as well as details of the colour pattern on the chelipeds and ambulatory legs. Partial sequences of the mitochondrial 16S rRNA gene from the three new species were sequenced and deposited in the GenBank database for future genetic and phylogenetic study.

Trend analysis of heavy metals, Ni, Pb, Cd and As in marine sediments – A case study of ONGC Block (KG OSN 2009/2) in Krishna-Godavari Basin, Bay of Bengal

Heavy metals can be termed as conservative pollutants, introduce into the aquatic systems as a result of the weathering of soils and rocks, from under water volcanic eruption and other anthropogenic activities. Thereby it changes the natural concentration of metals in seawater resulting in a ten or even hundred fold increase near the source of an effluent discharge. While some metals like manganese (Mn), copper (Cu), iron (Fe) and zinc (Zn) are biologically important for marine life, others like Nickel (Ni), Lead (Pb), Cadmium (Cd), and Arsenic (As) are non-essential and become toxic at higher concentrations. Associated to particulate matters, heavy metals tends to stay in solution for a very long time, but they will end up in the sediments, Therefore concentrations in the sediments are often higher than those in solution. In the sediments, these particles may form an important secondary source of contamination, even after the primary source has disappeared. Therefore, there is a need for timescale monitoring of the levels of these metals in all the marine resources, so as to establish the trends that could be linked to anthropogenic activities. In this paper, the effect of E&amp;P activities of ONGC Block (KG OSN 2009/2) in Krishna-Godavari Basin, Bay of Bengal is studied, by carrying out a trend analysis of heavy metal concentration (60Ni, 208Pb, 111Cd, and 75As) in the sediments from this block. Sediments samples were collected from the ONGC Block (KG OSN 2009/2) using OSPAR commission guidelines and the heavy metal concentration values averaged out. These average values are used to analyze the trend for a period extending from 2015 up to 2019. In the years 2016, the pollution level recorded was minimum. Overall, from 2015 to 2019, 208Pb shows a decreasing trend line, but 60Ni, 111Cd, and 75As shows an increasing trend line. Albeit the increasing trend of 60Ni, 111Cd, and 75As concentration are a matter of concern, but all the values are below the ERL (effects range low) set by the National Oceanographic and Atmospheric Administration (NOAA), USA. Hence, it can be concluded that the oil field activity of ONGC in the Eastern Offshore has not made any significant impact on the marine environment, in terms of heavy metal pollution. A statistical analysis in terms of Relative Contamination Factors and Pollution Load Index has also been done in the paper.

A Review on Importance of Contingent Value in Pharma Sector

In comparison to other health economists' methods for benefit calculation, Contingent valuation (CV) was argued to theoretical benefits. However, in practice, as applicable to healthcare concerns, it seems that methodology has not analyzed benefits, as its impact on national decision making in medical sector has still not been exercised. This is not due to continued thriving methodological lack study in this field. It is product, somewhat unorganized and non-systematic, of such operations. To encourage analysts to reach beyond assessment of cost-effectiveness of offering a given degree of environmental products, there needs to be few ways of estimating benefit of supplying various degree of services compared to their costs. While other measures are feasible, such units are expressed more naturally in money terms. The major goal of pharmaceuticals is to enhance the economic value of pharmacy services. The contingent valuation (CV) provides a way to value importance of pharma services. The Contingent Valuation method provides benefit in terms of individual monetary amount provided by both product and services. The present paper provides a brief review about CV method, importance in raising economic value of pharmacy along with its implications. The review also provides some guidelines i.e. National Oceanographic and Atmospheric Administration (NOAA) that should be followed in order to raise the economic value.

A Probability-Based Daytime Algorithm for Sea Fog Detection Using GOES-16 Imagery

Fog is a hazardous weather event that can endanger navigation, aviation, and transportation. While human has several limitations in detecting and forecasting offshore fog, satellite remote sensing offers cost-effective images. In this study, a probability-based daytime sea fog detection algorithm, applied to geostationary operational environmental satellite (GOES) 16 satellite data over the Grand Banks offshore Eastern Canada, is presented and compared with the National Oceanographic and Atmospheric Administration (NOAA)'s Low Instrument Flight Rules (LIFR) probability map. Initially, clear-sky and ice cloud classes were delineated in the GOES-16 image and then the remaining pixels were assigned a fog probability by conducting small droplet proxy, spatial homogeneity, and temperature difference tests. Moreover, a green band was linearly interpolated using the first three bands of GOES-16 images to generate pseudotrue color composites. The resulting maps were evaluated both during an extended sea fog event and using several statistical measures. The average detection probability for the observed advection fog events was 66% for the proposed method, while that for NOAA's LIFR map was 38%. Furthermore, by thresholding the generated maps at the probability of 60%, the false alarm rate, probability of detection, hit rate, and Hanssen–Kuiper skill score were 0.09, 0.77, 0.83, and 0.68, respectively. The proposed method is operationally being used in this region to detect and monitor sea fog, facilitating safe navigation and aviation. This is the first study that uses GOES-16 for daytime fog detection and discusses a satellite-based solution for fog modeling in Grand Banks, NL.

Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions

Abstract. We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations for the Arctic during summer. The products are compared against SIC and net ice surface fraction (ISF) – SIC minus the per-grid-cell melt pond fraction (MPF) on sea ice – as derived from MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations and observed from ice-going vessels. Like in Kern et al. (2019), we group the 10 products based on the concept of the SIC retrieval used. Group I consists of products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms. Group II consists of products derived with the Comiso bootstrap algorithm and the National Oceanographic and Atmospheric Administration (NOAA) National Snow and Ice Data Center (NSIDC) SIC climate data record (CDR). Group III consists of Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) and National Aeronautics and Space Administration (NASA) Team (NT) algorithm products, and group IV consists of products of the enhanced NASA Team algorithm (NT2). We find widespread positive and negative differences between PMW and MODIS SIC with magnitudes frequently reaching up to 20 %–25 % for groups I and III and up to 30 %–35 % for groups II and IV. On a pan-Arctic scale these differences may cancel out: Arctic average SIC from group I products agrees with MODIS within 2 %–5 % accuracy during the entire melt period from May through September. Group II and IV products overestimate MODIS Arctic average SIC by 5 %–10 %. Out of group III, ASI is similar to group I products while NT SIC underestimates MODIS Arctic average SIC by 5 %–10 %. These differences, when translated into the impact computing Arctic sea-ice area (SIA), match well with the differences in SIA between the four groups reported for the summer months by Kern et al. (2019). MODIS ISF is systematically overestimated by all products; NT provides the smallest overestimations (up to 25 %) and group II and IV products the largest overestimations (up to 45 %). The spatial distribution of the observed overestimation of MODIS ISF agrees reasonably well with the spatial distribution of the MODIS MPF and we find a robust linear relationship between PMW SIC and MODIS ISF for group I and III products during peak melt, i.e. July and August. We discuss different cases taking into account the expected influence of ice surface properties other than melt ponds, i.e. wet snow and coarse-grained snow/refrozen surface, on brightness temperatures and their ratios used as input to the SIC retrieval algorithms. Based on this discussion we identify the mismatch between the actually observed surface properties and those represented by the ice tie points as the most likely reason for (i) the observed differences between PMW SIC and MODIS ISF and for (ii) the often surprisingly small difference between PMW and MODIS SIC in areas of high melt pond fraction. We conclude that all 10 SIC products are highly inaccurate during summer melt. We hypothesize that the unknown number of melt pond signatures likely included in the ice tie points plays an important role – particularly for groups I and II – and recommend conducting further research in this field.

The Second Wind Forecast Improvement Project (WFIP2): General Overview

AbstractIn 2015 the U.S. Department of Energy (DOE) initiated a 4-yr study, the Second Wind Forecast Improvement Project (WFIP2), to improve the representation of boundary layer physics and related processes in mesoscale models for better treatment of scales applicable to wind and wind power forecasts. This goal challenges numerical weather prediction (NWP) models in complex terrain in large part because of inherent assumptions underlying their boundary layer parameterizations. The WFIP2 effort involved the wind industry, universities, the National Oceanographic and Atmospheric Administration (NOAA), and the DOE’s national laboratories in an integrated observational and modeling study. Observations spanned 18 months to assure a full annual cycle of continuously recorded observations from remote sensing and in situ measurement systems. The study area comprised the Columbia basin of eastern Washington and Oregon, containing more than 6 GW of installed wind capacity. Nests of observational systems captured important atmospheric scales from mesoscale to NWP subgrid scale. Model improvements targeted NOAA’s High-Resolution Rapid Refresh (HRRR) model to facilitate transfer of improvements to National Weather Service (NWS) operational forecast models, and these modifications have already yielded quantitative improvements for the short-term operational forecasts. This paper describes the general WFIP2 scope and objectives, the particular scientific challenges of improving wind forecasts in complex terrain, early successes of the project, and an integrated approach to archiving observations and model output. It provides an introduction for a set of more detailedBAMSpapers addressing WFIP2 observational science, modeling challenges and solutions, incorporation of forecasting uncertainty into decision support tools for the wind industry, and advances in coupling improved mesoscale models to microscale models that can represent interactions between wind plants and the atmosphere.

The U.S. Integrated Ocean Observing System: Governance Milestones and Lessons From Two Decades of Growth

Reflecting on two decades of the U.S. Integrated Ocean Observing System (IOOS) is particularly timely during the OceanObs’19 meeting. Over the past twenty years since the first OceanObs meeting was convened, U.S. IOOS has advanced from regional proofs of concept to a national, sustained enterprise. U.S. IOOS has grown to include 17 Federal partners and 11 Regional Associations (RAs) that implement regional observing systems covering all U.S. coasts and Great Lakes with activities spanning from head of tide to the U.S. exclusive economic zone (EEZ). The National Oceanographic and Atmospheric Administration (NOAA), as lead agency, provides guidance and national-level coordination. An interagency body, the Integrated Ocean Observation Committee (IOOC), communicates across federal agencies and ensures IOOS maintains strong connections to the Global Ocean Observing System (GOOS). Additionally, a federal advisory committee, non-federal association, and various informal partnerships further inform and advance the IOOS enterprise. This governance structure fosters both national consistency, regional flexibility, and global contributions addressing the diverse needs of U.S. coastal and Great Lakes stakeholders.

Gridded Satellite (GridSat) GOES and CONUS data

Abstract. The Geostationary Operational Environmental Satellite (GOES) series is operated by the US National Oceanographic and Atmospheric Administration (NOAA). While in operation since the mid-1970s, the current series (GOES 8–15) has been operational since 1994. This document describes the Gridded Satellite (GridSat) data, which provide GOES data in a modern format. Four steps describe the conversion of original GOES data to GridSat data: (1) temporal resampling to produce files with evenly spaced time steps, (2) spatial remapping to produce evenly spaced gridded data (0.04∘ latitude), (3) calibrating the original data and storing brightness temperatures for infrared (IR) channels and reflectance for the visible channel, and (4) calculating spatial variability to provide extra information that can help identify clouds. The GridSat data are provided on two separate domains: GridSat-GOES provides hourly data for the Western Hemisphere (spanning the entire GOES domain) and GridSat-CONUS covers the contiguous US (CONUS) every 15 min (dataset reference: https://doi.org/10.7289/V5HM56GM).

Changes in Ugandan Climate Rainfall at the Village and Forest Level

In 2013, the US National Oceanographic and Atmospheric Administration (NOAA) refined the historical rainfall estimates over the African Continent and produced the African Rainfall Climate version 2.0 (ARC2) estimator. ARC2 offers a nearly complete record of daily rainfall estimates since 1983 at 0.1° × 0.1° resolution. Despite short-term anomalies, we identify an overall decrease in average rainfall of about 12% during the past 34 years in Uganda. Spatiotemporally, these decreases are greatest in agricultural regions of central and western Uganda, but similar rainfall decreases are also reflected in the gorilla habitat within the Bwindi Forest in Southwest Uganda. The findings carry significant implications for agriculture production, food security, wildlife habitat, and economic impact at the community and societal level.

Multidecadal Trends in Atmospheric and Ocean Conditions in Offshore Waters Near Cape Cod, Massachusetts

Abstract Climate change is influencing the ocean environment in myriad ways and many of its effects can directly or indirectly impact coastal ecosystems. In this study, I analyzed data for a number of variables describing atmospheric and ocean conditions (AOC) from a National Oceanographic and Atmospheric Administration (NOAA) data buoy located near the Cape Cod, MA, peninsula. The data suggest that a number of significant trends have occurred during the period of data collection spanning 1982–2015. Changes include up to a 2 °C and 3 °C warming of air and water temperatures in summer, reduced barometric pressure in the summer/fall, declining wind speeds in the spring, shorter average wave-periods in the winter and spring, a clockwise change in wind direction in the summer, and increased wave heights in the summer and fall. The AOC variables also exhibited a number of relationships with each other, which helped explain some mechanisms of change. With the exception of barometric pressure and fall wave-heigh...

Analysis of Rainfall in Tampa

Rainfall for a region is very important to define, because it affects an ecosystem health, wildlife, and even human behavior. Using data obtained from National Oceanographic and Atmospheric Administration (NOAA) at the Tampa Bay International Airport and graphing it, the total rainfall for a year was estimated by both a rough trapezoidal Riemann’s sum approximation and a definite integral generated by polynomial regression. It was determined that both approximations gave an underestimate of the total rainfall that was measured, but the polynomial integral gave a reasonable estimate with a small percent error. It was seen through the graphical representation of this data and the overall recorded total rainfall that indeed it did match the humid subtropical climate type of Tampa, with a spike in rainfall in the summer and precipitation amount that matched the Köppen climate classification system for this climate type. In guiding future measurements of rain it is useful to use a trendline to predict rainfall over a given period of time.

El Niño episodes coincide with California moray Gymnothorax mordax settlement around Santa Catalina Island, California.

The hypothesis that El Niño events influence the settlement patterns of the California moray Gymnothorax mordax is tested. The pelagic larval duration (PLD) of larval G. mordax is unknown, but studies on leptocephalus of related species suggest that larvae are long-lived, up to 2 years. Gymnothorax mordax, an elusive predatory species and the only muraenid off the coast of California, is considered abundant in the waters around Catalina Island. Thirty-three individuals were collected from Two Harbors, Catalina Island, and otoliths were taken to provide estimates of their age. Settlement year for each individual was backcalculated using estimated age from otolith measurements. These ages were then cross referenced with the Oceanic Niño Index (ONI) developed by the National Oceanographic and Atmospheric Administration (NOAA) to correlate estimated age of settlement with known El Niño years. Of the 33 individuals collected, 30 settled at Catalina Island during El Niño years. The oldest individual in the data-set was 22 years old, placing G. mordax as one of the longer-lived predatory fishes in the system. The present study represents the first account of wild G. mordax ages and suggests that El Niño events have an important role in driving the settlement of recruits towards the northern edge of their range.