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Jackie C. May, Clark Rowley, and Charlie N. Barron

Abstract

The Naval Research Laboratory (NRL) ocean surface flux (NFLUX) system provides near-real-time satellite-based gridded surface heat flux fields over the global ocean within hours of the observed satellite measurements. NFLUX can serve as an alternative to current numerical weather prediction models—in particular, the U. S. Navy Global Environmental Model (NAVGEM)—that provide surface forcing fields to operational ocean models. This study discusses the satellite-based shortwave and longwave global gridded analysis fields, which complete the full suite of NFLUX-provided ocean surface heat fluxes. A companion paper discusses the production of satellite swath-level surface shortwave radiation and longwave radiation estimates. The swath-level shortwave radiation estimates are converted into clearness-index values. Clearness index reduces the dependency on solar zenith angle, which allows for the assimilation of observations over a given time window. An automated quality-control process is applied to the swath-level estimates of clearness index and surface longwave radiation. Then 2D variational analyses of the quality-controlled satellite estimates with background atmospheric model fields form global gridded radiative heat flux fields. The clearness-index analysis fields are converted into shortwave analysis fields to be used in other applications. Three-hourly shortwave and longwave analysis fields are created from 1 May 2013 through 30 April 2014. These fields are validated against observations from research vessels and moored-buoy platforms and compared with NAVGEM. With the exception of the mean bias, the NFLUX fields have smaller errors when compared with those of NAVGEM.

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Jackie C. May, Clark Rowley, and Charlie N. Barron

Abstract

The Naval Research Laboratory (NRL) ocean surface flux (NFLUX) system originally provided operational near-real-time satellite-based surface state parameter and turbulent heat flux fields over the global ocean. This study extends the NFLUX system to include the production of swath-level shortwave and longwave radiative heat fluxes at the ocean surface. A companion paper presents the production of the satellite-based global gridded radiative heat flux analysis fields. The swath-level radiative heat fluxes are produced using the Rapid Radiative Transfer Model for Global Circulation Models (RRTMG), with the primary inputs of satellite-derived atmospheric temperature and moisture profiles and cloud information retrieved from the Microwave Integrated Retrieval System (MIRS). This study uses MIRS data provided for six polar-orbiting satellite platforms. Additional inputs to the RRTMG include sea surface temperature, aerosol optical depths, atmospheric gas concentrations, ocean surface albedo, and ocean surface emissivity. Swath-level shortwave flux estimates are converted into clearness index values, which are used in data assimilation because the clearness index values are less dependent on the solar zenith angle. The NFLUX swath-level shortwave flux, longwave flux, and clearness index estimates are produced for 1 May 2013–30 April 2014 and validated against observations from research vessel and moored buoy platforms. Each of the flux parameters compares well among the various satellites.

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Robert W. Helber, Jay F. Shriver, Charlie N. Barron, and Ole Martin Smedstad

Abstract

The impact of the number of satellite altimeters providing sea surface height anomaly (SSHA) information for a data assimilation system is evaluated using two comparison frameworks and two statistical methodologies. The Naval Research Laboratory (NRL) Layered Ocean Model (NLOM) dynamically interpolates satellite SSHA track data measured from space to produce high-resolution (eddy resolving) fields. The Modular Ocean Data Assimilation System (MODAS) uses the NLOM SSHA to produce synthetic three-dimensional fields of temperature and salinity over the global ocean. A series of case studies is defined where NLOM assimilates different combinations of data streams from zero to three altimeters. The resulting NLOM SSHA fields and the MODAS synthetic profiles are evaluated relative to independently observed ocean temperature and salinity profiles for the years 2001–03. The NLOM SSHA values are compared with the difference of the observed dynamic height from the climatological dynamic height. The synthetics are compared with observations using a measure of thermocline depth. Comparisons are done point for point and for 1° radius regions that are linearly fit over 2-month periods. To evaluate the impact of data outliers, statistical evaluations are done with traditional Gaussian statistics and also with robust nonparametric statistics. Significant error reduction is obtained, particularly in high SSHA variability regions, by including at least one altimeter. Given the limitation of these methods, the overall differences between one and three altimeters are significant only in bias. Data outliers increase Gaussian statistical error and error uncertainty compared to the same computations using nonparametric statistical methods.

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A. Birol Kara, Charlie N. Barron, Alan J. Wallcraft, and Temel Oguz

Abstract

Sea surface height (SSH) variability is presented over the Black Sea during 1993–2005. The 1/4° × 1/4° resolution daily SSH fields are formed using optimal interpolation of available altimeter data. SSH variability reveals distinct maxima in the eastern and western basins, reflecting variations in the corresponding gyres. A joint examination of SSH and sea surface temperature (SST) indicates strong relationship between the two only in winter, with correlations as high as 0.6 or more. This would reflect a steric change in sea surface height due to thermal expansion averaged over a relatively deep winter mixed layer. Newly developed SSH fields also demonstrate a switch to the positive mode of SSH starting from the end of 1996 lasting ≈4 yr. Such a climatic shift is found to be strongly related to large-scale teleconnection patterns. Finally, the daily SSH and SST anomaly fields presented in this paper can supplement various applications in the Black Sea, such as examination of biological production and mesoscale eddy dynamics.

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Charlie N. Barron, A. Birol Kara, Harley E. Hurlburt, C. Rowley, and Lucy F. Smedstad

Abstract

A ⅛° global version of the Navy Coastal Ocean Model (NCOM), operational at the Naval Oceanographic Office (NAVOCEANO), is used for prediction of sea surface height (SSH) on daily and monthly time scales during 1998–2001. Model simulations that use 3-hourly wind and thermal forcing obtained from the Navy Operational Global Atmospheric Prediction System (NOGAPS) are performed with/without data assimilation to examine indirect/direct effects of atmospheric forcing in predicting SSH. Model–data evaluations are performed using the extensive database of daily averaged SSH values from tide gauges in the Atlantic, Pacific, and Indian Oceans obtained from the Joint Archive for Sea Level (JASL) center during 1998–2001. Model–data comparisons are based on observations from 282 tide gauge locations. An inverse barometer correction was applied to SSH time series from tide gauges for model–data comparisons, and a sensitivity study is undertaken to assess the impact of the inverse barometer correction on the SSH validation. A set of statistical metrics that includes conditional bias (B cond), root-mean-square (rms) difference, correlation coefficient (R), and nondimensional skill score (SS) is used to evaluate the model performance. It is shown that global NCOM has skill in representing SSH even in a free-running simulation, with general improvement when SSH from satellite altimetry and sea surface temperature (SST) from satellite IR are assimilated via synthetic temperature and salinity profiles derived from climatological correlations. When the model was run from 1998 to 2001 with NOGAPS forcing, daily model SSH comparisons from 612 yearlong daily tide gauge time series gave a median rms difference of 5.98 cm (5.77 cm), an R value of 0.72 (0.76), and an SS value of 0.45 (0.51) for the ⅛° free-running (assimilative) NCOM. Similarly, error statistics based on the 30-day running averages of SSH time series for 591 yearlong daily tide gauge time series over the time frame 1998–2001 give a median rms difference of 3.63 cm (3.36 cm), an R value of 0.83 (0.85), and an SS value of 0.60 (0.64) for the ⅛° free-running (assimilated) NCOM. Model– data comparisons show that skill in 30-day running average SSH time series is as much as 30% higher than skill for daily SSH. Finally, SSH predictions from the free-running and assimilative ⅛° NCOM simulations are validated against sea level data from the tide gauges in two different ways: 1) using original detided sea level time series from tide gauges and 2) using the detided data with an inverse barometer correction derived using daily mean sea level pressure extracted from NOGAPS at each location. Based on comparisons with 612 yearlong daily tide gauge time series during 1998–2001, the inverse barometer correction lowered the median rms difference by about 1 cm (15%–20%). Results presented in this paper reveal that NCOM is able to predict SSH with reasonable accuracies, as evidenced by model simulations performed during 1998–2001. In an extension of the validation over broader ocean regions, the authors find good agreement in amplitude and distribution of SSH variability between NCOM and other operational model products.

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