@article{willett_brannock_dissen_keown_szura_brown_simonson_2023, title={NOAA Open Data Dissemination: Petabyte-scale Earth system data in the cloud}, volume={9}, ISSN={["2375-2548"]}, DOI={10.1126/sciadv.adh0032}, abstractNote={NOAA Open Data Dissemination (NODD) makes NOAA environmental data publicly and freely available on Amazon Web Services (AWS), Microsoft Azure (Azure), and Google Cloud Platform (GCP). These data can be accessed by anyone with an internet connection and span key datasets across the Earth system including satellite imagery, radar, weather models and observations, ocean databases, and climate data records. Since its inception, NODD has grown to provide public access to more than 24 PB of NOAA data and can support billions of requests and petabytes of access daily. Stakeholders routinely access more than 5 PB of NODD data every month. NODD continues to grow to support open petabyte-scale Earth system data science in the cloud by onboarding additional NOAA data and exploring performant data formats. Here, we document how this program works with a focus on provenance, key datasets, and use. We also highlight how to access these data with the goal of accelerating use of NOAA resources in the cloud.}, number={38}, journal={SCIENCE ADVANCES}, author={Willett, Denis S. and Brannock, Jonathan and Dissen, Jenny and Keown, Patrick and Szura, Katelyn and Brown, Otis B. and Simonson, Adrienne}, year={2023}, month={Sep} }
 @article{willett_white_augspurger_brannock_dissen_keown_brown_simonson_2022, title={Expanding Access to Open Environmental Data Advancements and Next Steps}, volume={103}, ISSN={["1520-0477"]}, DOI={10.1175/BAMS-D-22-0158.1}, abstractNote={Denis S. Willett,a Brian White,b Tom Augspurger,c Jonathan Brannock,a Jenny Dissen,a Patrick Keown,d Otis B. Brown,a and Adrienne Simonsond a Cooperative Institute for Satellite Earth Systems Studies (CISESS), North Carolina Institute of Climate Studies, North Carolina State University, Asheville, NC, USA b Terrafuse AI (Co-founder), Department of Earth, Marine and Environmental Sciences, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA c Planetary Computer, Microsoft, Redmond, WA, USA d NOAA Open Data Dissemination (NODD), National Oceanic and Atmospheric Administration, Asheville, NC, USA}, number={11}, journal={BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY}, author={Willett, Denis S. and White, Brian and Augspurger, Tom and Brannock, Jonathan and Dissen, Jenny and Keown, Patrick and Brown, Otis B. and Simonson, Adrienne}, year={2022}, month={Nov}, pages={E2579–E2583} }
 @article{waliser_gleckler_ferraro_taylor_ames_biard_bosilovich_brown_chepfer_cinquini_et al._2020, title={Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6}, volume={13}, ISSN={["1991-9603"]}, DOI={10.5194/gmd-13-2945-2020}, abstractNote={Abstract. The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O3), methane (CH4), and carbon dioxide (CO2) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO2). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP.}, number={7}, journal={GEOSCIENTIFIC MODEL DEVELOPMENT}, author={Waliser, Duane and Gleckler, Peter J. and Ferraro, Robert and Taylor, Karl E. and Ames, Sasha and Biard, James and Bosilovich, Michael G. and Brown, Otis and Chepfer, Helene and Cinquini, Luca and et al.}, year={2020}, month={Jul}, pages={2945–2958} }
 @article{matthews_peng_meier_brown_2020, title={Sensitivity of Arctic Sea Ice Extent to Sea Ice Concentration Threshold Choice and Its Implication to Ice Coverage Decadal Trends and Statistical Projections}, volume={12}, ISSN={["2072-4292"]}, url={https://doi.org/10.3390/rs12050807}, DOI={10.3390/rs12050807}, abstractNote={Arctic sea ice extent has been utilized to monitor sea ice changes since the late 1970s using remotely sensed sea ice data derived from passive microwave (PM) sensors. A 15% sea ice concentration threshold value has been used traditionally when computing sea ice extent (SIE), although other threshold values have been employed. Does the rapid depletion of Arctic sea ice potentially alter the basic characteristics of Arctic ice extent? In this paper, we explore whether and how the statistical characteristics of Arctic sea ice have changed during the satellite data record period of 1979–2017 and examine the sensitivity of sea ice extents and their decadal trends to sea ice concentration threshold values. Threshold choice can affect the timing of annual SIE minimums: a threshold choice as low as 30% can change the timing to August instead of September. Threshold choice impacts the value of annual SIE minimums: in particular, changing the threshold from 15% to 35% can change the annual SIE by more than 10% in magnitude. Monthly SIE data distributions are seasonally dependent. Although little impact was seen for threshold choice on data distributions during annual minimum times (August and September), there is a strong impact in May. Threshold choices were not found to impact the choice of optimal statistical models characterizing annual minimum SIE time series. However, the first ice-free Arctic summer year (FIASY) estimates are impacted; higher threshold values produce earlier FIASY estimates and, more notably, FIASY estimates amongst all considered models are more consistent. This analysis suggests that some of the threshold choice impacts to SIE trends may actually be the result of biased data due to surface melt. Given that the rapid Arctic sea ice depletion appears to have statistically changed SIE characteristics, particularly in the summer months, a more extensive investigation to verify surface melt impacts on this data set is warranted.}, number={5}, journal={REMOTE SENSING}, author={Matthews, Jessica L. and Peng, Ge and Meier, Walter N. and Brown, Otis}, year={2020}, month={Mar} }
 @article{beal_hummon_williams_brown_baringer_kearns_2008, title={Five years of Florida Current structure and transport from the Royal Caribbean Cruise ShipExplorer of the Seas}, volume={113}, ISSN={0148-0227}, url={http://dx.doi.org/10.1029/2007JC004154}, DOI={10.1029/2007JC004154}, abstractNote={[1] Using ship-of-opportunity platform Explorer of the Seas, five years of full-depth velocity data have been collected across the Florida Straits at 26°N. Between May 2001 and May 2006 the mean transport of the Florida Current was 31.0 ± 4.0 Sv. This compares to a mean transport of 32.4 ± 3.2 Sv inferred from cable voltages at 27°N over the same period, implying an average 1.4 Sv transport into the Straits through the Northwest Providence Channel. The climatological core of the Florida Current is 170 cms−1 and is positioned at 79.8°W, about 10 km east of the shelf break. The largest variability in velocity occurs over the shelf and shelf break and is likely related to shelf waves. A secondary maximum occurs across much of the Straits over the top 100 m of the water column and may be associated with wind events. The annual cycle of Florida Current transports has a range of 4.7 Sv, with a maximum in May–June–July and a minimum in January. The difference between the summer and winter current structure appears as a first baroclinic mode with zero crossing at 150 m. The maximum difference is about 15 cms−1 at the surface and is centered just offshore of the mean current core. On interannual timescales, low-pass filtered Explorer and cable transports show similar downward trends between 2002 and 2005, but diverge over the last year or so of the record.}, number={C6}, journal={Journal of Geophysical Research}, publisher={American Geophysical Union (AGU)}, author={Beal, Lisa M. and Hummon, Julia M. and Williams, Elizabeth and Brown, Otis B. and Baringer, Warner and Kearns, Edward J.}, year={2008}, month={Jun} }
 @article{framiñan_valle-levinson_sepúlveda_brown_2008, title={Tidal variations of flow convergence, shear, and stratification at the Rio de la Plata estuary turbidity front}, volume={113}, ISSN={0148-0227}, url={http://dx.doi.org/10.1029/2006JC004038}, DOI={10.1029/2006JC004038}, abstractNote={[1] Intratidal variability of density and velocity fields is investigated at the turbidity front of the Rio de la Plata Estuary, South America. Current velocity and temperature-salinity profiles collected in August 1999 along a repeated transect crossing the front are analyzed. Horizontal and vertical gradients, stability of the front, convergence zones, and transverse flow associated to the frontal boundary are described. Strong horizontal convergence of the across-front velocity and build up of along-front velocity shear were observed at the front. In the proximity of the front, enhanced transverse (or along-front) flow created jet-like structures at the surface and near the bottom flowing in opposite directions. These structures persisted throughout the tidal cycle and were advected upstream (downstream) by the flood (ebb) current through a distance of ∼10 km. During peak flood, the upper layer flow reversed from its predominant downstream direction and upstreamflow occupied the entire water column; outside the peak flood, two-layer estuarine circulation dominated. Changes in density field were observed in response to tidal straining, tidal advection, and wind-induced mixing, but stratification remained throughout the tidal cycle. This work demonstrates the large spatial variability of the velocity field at the turbidity front; it provides evidence of enhanced transverse circulation along the frontal boundary; and reveals the importance of advective and frictional intratidal processes in the dynamics of the central part of the estuary.}, number={C8}, journal={Journal of Geophysical Research}, publisher={American Geophysical Union (AGU)}, author={Framiñan, Mariana B. and Valle-Levinson, Arnoldo and Sepúlveda, Héctor H. and Brown, Otis B.}, year={2008}, month={Aug} }
 @article{donelan_haus_reul_plant_stiassnie_graber_brown_saltzman_2004, title={On the limiting aerodynamic roughness of the ocean in very strong winds}, volume={31}, ISSN={0094-8276}, url={http://dx.doi.org/10.1029/2004GL019460}, DOI={10.1029/2004GL019460}, abstractNote={The aerodynamic friction between air and sea is an important part of the momentum balance in the development of tropical cyclones. Measurements of the drag coefficient, relating the tangential stress (frictional drag) between wind and water to the wind speed and air density, have yielded reliable information in wind speeds less than 20 m/s (about 39 knots). In these moderate conditions it is generally accepted that the drag coefficient (or equivalently, the “aerodynamic roughness”) increases with the wind speed. Can one merely extrapolate this wind speed tendency to describe the aerodynamic roughness of the ocean in the extreme wind speeds that occur in hurricanes (wind speeds greater than 30 m/s)? This paper attempts to answer this question, guided by laboratory extreme wind experiments, and concludes that the aerodynamic roughness approaches a limiting value in high winds. A fluid mechanical explanation of this phenomenon is given.}, number={18}, journal={Geophysical Research Letters}, publisher={American Geophysical Union (AGU)}, author={Donelan, M. A. and Haus, B.K. and Reul, N. and Plant, W.J. and Stiassnie, M. and Graber, H.C. and Brown, O.B. and Saltzman, E.S.}, year={2004}, month={Sep} }
 @article{yang_parvin_mariano_ryan_evans_brown_2004, title={Seasonal and interannual studies of vortices in sea surface temperature data}, volume={25}, ISSN={0143-1161 1366-5901}, url={http://dx.doi.org/10.1080/01431160310001592319}, DOI={10.1080/01431160310001592319}, abstractNote={An algorithm for calculating feature displacement velocities and for detecting vortices has been applied to 13 years of sea surface temperature data derived from Advanced Very High Resolution Radiometer (AVHRR) data. A unique global event database for seasonal and interannual studies of the spatial distribution of oceanic vortices was created for the years 1986–1998. The results indicate that (1) the number of vortices in each season is fairly constant from year to year in each hemisphere—however, their preferred locations change on seasonal to interannual time-scales; (2) the maximum number of vortices were detected in the summer and in the winter in all oceans and the minimum number were detected in the autumn; and (3) the distribution of the spatial density function shows preferred localizations such as 40° S, the tropical instability region, marginal seas, western boundary and eastern boundary current regimes.}, number={7-8}, journal={International Journal of Remote Sensing}, publisher={Informa UK Limited}, author={Yang, Q., Correspond and Parvin, B. and Mariano, A. J. and Ryan, E. H. and Evans, R. and Brown, O. B.}, year={2004}, month={Apr}, pages={1371–1376} }