Inclusion of sea‐surface temperature variation in the U.S. Navy ensemble‐transform global ensemble prediction system

This paper examines the sensitivity of sea surface temperature (SST) to water turbidity in the Black Sea using the eddy-resolving (∼3.2-km resolution) Hybrid Coordinate Ocean Model (HYCOM), which includes a nonslab K-profile parameterization (KPP) mixed layer model. The KPP model uses a diffusive attenuation coefficient of photosynthetically active radiation (kPAR) processed from a remotely sensed dataset to take water turbidity into account. Six model experiments (expt) are performed with no assimilation of any ocean data and wind/thermal forcing from two sources: 1) European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA) and 2) Fleet Numerical Meteorology and Oceanography Center (FNMOC) Navy Operational Global Atmospheric Prediction System (NOGAPS). Forced with ECMWF, experiment 1 uses spatially and monthly varying kPAR values over the Black Sea, experiment 2 assumes all of the solar radiation is absorbed at the sea surface, and experiment 3 uses a constant kPAR value of 0.06 m−1, representing clear-water constant solar attenuation depth of 16.7 m. Experiments 4, 5, and 6 are twins of 1, 2, and 3 but forced with NOGAPS. The monthly averaged model SSTs resulting from all experiments are then compared with a fine-resolution (∼9 km) satellite-based monthly SST climatology (the Pathfinder climatology). Because of the high turbidity in the Black Sea, it is found that a clear-water constant attenuation depth (i.e., expts 3 and 6) results in SST bias as large as 3°C in comparison with standard simulations (expts 1 and 4) over most of the Black Sea in summer. In particular, when using the clear-water constant attenuation depth as opposed to using spatial and temporal kPAR, basin-averaged rms SST difference with respect to the Pathfinder SST climatology increases ∼46% (from 1.41°C in expt 1 to 2.06°C in expt 3) in the ECMWF forcing case. Similarly, basin-averaged rms SST difference increases ∼36% (from 1.39°C in expt 4 to 1.89°C in expt 6) in the NOGAPS forcing case. The standard HYCOM simulations (expts 1 and 4) have a very high basin-averaged skill score of 0.95, showing overall model success in predicting climatological SST, even with no assimilation of any SST data. In general, the use of spatially and temporally varying turbidity fields is necessary for the Black Sea OGCM studies because there is strong seasonal cycle and large spatial variation in the solar attenuation coefficient, and an additional simulation using a constant kPAR value of 0.19 m−1, the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) space–time mean for the Black Sea, did not yield as accurate SST results as experiments 1 and 4. Model–data comparisons also revealed that relatively large HYCOM SST errors close to the coastal boundaries can be attributed to the misrepresentation of land– sea mask in the ECMWF and NOGAPS products. With the relatively accurate mask used in NOGAPS, HYCOM demonstrated the ability to simulate accurate SSTs in shallow water over the broad northwest shelf in the Black Sea, a region of large errors using the inaccurate mask in ECMWF. A linear relationship is found between changes in SST and changes in heat flux below the mixed layer. Specifically, a change of ∼50 W m−2 in sub-mixed-layer heat flux results in a SST change of ∼3.0°C, a value that occurs when using clear-water constant attenuation depth rather than monthly varying kPAR in the model simulations, clearly demonstrating potential impact of penetrating solar radiation on SST simulations.

Ocean models need over-ocean atmospheric forcing. However, such forcing is not necessarily provided near the land–sea boundary because 1) the atmospheric model grid used for forcing is frequently much coarser than the ocean model grid, and 2) some of the atmospheric model grid over the ocean includes land values near coastal regions. This paper presents a creeping sea-fill methodology to reduce the improper representation of scalar atmospheric forcing variables near coastal regions, a problem that compromises the usefulness of the fields for ocean model simulations and other offshore applications. For demonstration, atmospheric forcing variables from archived coarse-resolution gridded products—the 1.125° × 1.125° 15-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-15) and 1.0° × 1.0° Navy Operational Global Atmospheric Prediction System (NOGAPS)—are used here. A fine-resolution [1/25° × 1/25° cos(lat)], (longitude × latitude) (∼3.2 km) eddy-resolving Black Sea Hybrid Coordinate Ocean Model (HYCOM) is then forced with/without sea-filled atmospheric variables from these gridded products to simulate monthly mean climatological sea surface temperature (SST). Using only over-ocean values from atmospheric forcing fields in the ocean model simulations significantly reduces the climatological mean SST bias (by ∼1°–3°C) and rms SST difference over the seasonal cycle (by ∼2°–3°C) in coastal regions. Performance of the creeping sea-fill methodology is also directly evaluated using measurements of wind speed at 10 m above the surface from the SeaWinds scatterometer on the NASA Quick Scatterometer (QuikSCAT) satellite. Comparisons of original monthly mean wind speeds from operational ECMWF and NOGAPS products with those from QuikSCAT give basin-averaged rms differences of 1.6 and 1.4 m s−1, respectively, during 2000–03. Similar comparisons performed with sea-filled monthly mean wind speeds result in a much lower rms difference (0.7 m s−1 for both products) during the same time period, clearly confirming the accuracy of the methodology even on interannual time scales. Most of the unrealistically low wind speeds from ECMWF and NOGAPS near coastal boundaries are appropriately corrected with the use of the creeping sea fill. Wind speed errors for ECWMF and NOGAPS (mean bias of ≥ 2.5 m s−1 with respect to QuikSCAT during 2000–03) are substantially eliminated (e.g., almost no bias) near most of the land–sea boundaries. Finally, ocean, atmosphere, and coupled atmospheric–oceanic modelers need to be aware that the creeping sea fill is a promising methodology in significantly reducing the land contamination resulting from an improper land–sea mask existing in gridded coarse-resolution atmospheric products (e.g., ECMWF).

The ensemble transform (ET) scheme changes forecast perturbations into analysis perturbations whose amplitudes and directions are consistent with a user-provided estimate of analysis error covariance. A practical demonstration of the ET scheme was undertaken using Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS) analysis error variance estimates and the Navy Operational Global Atmospheric Prediction System (NOGAPS) numerical weather prediction (NWP) model. It was found that the ET scheme produced forecast ensembles that were comparable to or better in a variety of measures than those produced by the Fleet Numerical and Oceanography Center (FNMOC) bred-growing modes (BGM) scheme. Also, the demonstration showed that the introduction of stochastic perturbations into the ET forecast ensembles led to a substantial improvement in the agreement between the ET and NAVDAS analysis error variances. This finding is strong evidence that even a small-sized ET ensemble is capable of obtaining good agreement between the ET and NAVDAS analysis error variances, provided that NWP model deficiencies are accounted for. Last, since the NAVDAS analysis error covariance estimate is diagonal and hence ignores multivariate correlations, it was of interest to examine the ET analysis perturbations’ spatial correlation. Tests showed that the ET analysis perturbations exhibited statistically significant, realistic multivariate correlations.

Diurnal Sea Surface Temperature (SST) variations and the near-surface thermal structure of the tropical hot event (HE) have been investigated using advanced in-situ equatorial observations with hourly temporal resolution. The information on the HE area defined by the satellite cloud-free SSTs is used to sample the in-situ observations. The in-situ SSTs sampled for the HE conditions show that a maximum (minimum) SST has a histogram mode at 30.8°C (29.0°C), and frequently appears at 15:00 (07:00) local time. The amplitude of the diurnal SST variation (DSST) is defined by the difference between the maximum and minimum SSTs. The mean DSST during HEs is greater than 0.5°C, and has a maximum of about 0.75°C at the HE peak. The time series of mean DSST gradually increases (rapidly decreases) before (after) the peak. The satellite SST has a systematic positive bias against the corresponding daytime SST measured by the Triangle Trans-Ocean buoy Network. This bias is enhanced under conditions of large in-situ DSST. One-dimensional numerical model simulation suggests that the systematic bias is caused by the sharp vertical temperature gradient in the surface layer of HE. The near-surface thermal structure is generated by conditions of high insolation and low wind speed, which is the typical HE condition.

Daily inter-annual simulations of SST and MLD using atmospherically forced OGCMs: Model evaluation in comparison to buoy time series

Optimizing surface winds using QuikSCAT measurements in the Mediterranean Sea during 2000–2006

This study describes atmospheric forcing parameters constructed from different global climatologies, applied to the Black Sea, and investigates the sensitivity of Hybrid Coordinate Ocean Model (HYCOM) simulations to these products. Significant discussion is devoted to construction of these parameters before using them in the eddy-resolving (≈3.2-km resolution) HYCOM simulations. The main goal is to answer how the model dynamics can be substantially affected by different atmospheric forcing products in the Black Sea. Eight wind forcing products are used: four obtained from observation-based climatologies, including one based on measurements from the SeaWinds scatterometer on the Quick Scatterometer (QuikSCAT) satellite, and the rest formed from operational model products. Thermal forcing parameters, including solar radiation, are formed from two operational models: the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Fleet Numerical Meteorology and Oceanography Center (FNMOC) Navy Operational Global Atmospheric Prediction System (NOGAPS). Climatologically forced Black Sea HYCOM simulations (without ocean data assimilation) are then performed to assess the accuracy and sensitivity of the model sea surface temperature (SST) and sea surface circulation to these wind and thermal forcing products. Results demonstrate that the model-simulated SST structure is quite sensitive to the wind and thermal forcing products, especially near coastal regions. Despite this sensitivity, several robust features are found in the model SST in comparison to a monthly 9.3-km-resolution satellite-based Pathfinder SST climatology. Annual mean HYCOM SST usually agreed to within ≈±0.2° of the climatology in the interior of the Black Sea for any of the wind and thermal forcing products used. The fine-resolution (0.25° × 0.25°) wind forcing from the scatterometer data along with thermal forcing from NOGAPS gave the best SST simulation with a basin-averaged rms difference value of 1.21°C, especially improving model results near coastal regions. Specifically, atmospherically forced model simulations with no assimilation of any ocean data suggest that the basin-averaged rms SST differences with respect to the Pathfinder SST climatology can vary from 1.21° to 2.15°C depending on the wind and thermal forcing product. The latter rms SST difference value is obtained when using wind forcing from the National Centers for Environmental Prediction (NCEP), a product that has a too-coarse grid resolution of 1.875° × 1.875° for a small ocean basin such as the Black Sea. This paper also highlights the importance of using high-frequency (hybrid) wind forcing as opposed to monthly mean wind forcing in the model simulations. Finally, there are large variations in the annual mean surface circulation simulated using the different wind sets, with general agreement between those forced by the model-based products (vector correlation is usually >0.7). Three of the observation-based climatologies generally yield unrealistic circulation features and currents that are too weak.

In June 1990, the assimilation of synthetic tropical cyclone observations into the Navy Operational Global Atmospheric Prediction System (NOGAPS) was initiated at Fleet Numerical Oceanography Center (FNOC). These observations are derived directly from the information contained in the tropical cyclone warnings issued by the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center. This paper describes these synthetic observations, the evolution of their use at FNOC, and the details of their assimilation into NOGAPS. The results of a comprehensive evaluation of the 1991 NOGAPS tropical cyclone forecast performance in the western North Pacific are presented. NOGAPS analysis and forecast position errors were determined for all tropical circulations of tropical storm strength or greater. It was found that, after the assimilation of synthetic observations, the NOGAPS spectral forecast model consistently maintained the tropical circulations as evidenced by detection percentages of 96%, 90% ...

The Wallops-2000 experiment took place in April and May 2000 in the vicinity of Wallops Island, Virginia, to collect high-resolution measurements of microwave propagation and coincident meteorological parameters in a complex coastal environment. These data are used in conjunction with a mesoscale numerical weather prediction model to examine the impact of sea surface temperature (SST) on microwave ducting. Analysis of time series of meteorological fields at the location of an instrumented buoy indicates reliable forecast skill. Statistics from vertical profiles and of derived ducting characteristics (duct frequency, duct strength, duct-base height, and duct thickness) show that the model reproduced observed duct characteristics with modest accuracy, allowing for a 3–6-h error in synoptic airmass transitions. In addition to the control run, two experiments are conducted to examine the impact of SST on ducting. In one experiment a climatological SST field is used, and in the other a diurnal variation in SST is imposed. The higher SST in the diurnally varying simulations promotes stronger turbulent mixing, deep boundary layers, and small vertical gradients in mixing ratio in comparison with the control, which lead to reduced duct frequency and strength in many cases. The study further reveals that, while advection of large-scale air masses (vertical and horizontal) plays a crucial role in determining whether an environment is favorable for microwave ducting, diurnal variations in SST can be influential in determining the onset of ducting and the frequency of surface-based ducting in coastal regions.

The paper evaluates the meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones. It is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The meterological characteristics of the NOGAPS tropical cyclone predictions are evaluated by examining the formation of low-level cyclone systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones.

The purpose of this paper is to discuss the major systematic errors of the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS), version 3.2, and to describe several tuning experiments of NOGAPS parameterizations. It is found that despite its overall good performance, major systematic errors exist in the forecast model. These errors lead to a warmer atmosphere with less precipitation and eddy kinetic energy than is observed. Some of the errors may be attributed to the lack of horizontal and vertical resolution, but most of the errors are due to inadequacies and incorrect assumptions in the physical parameterizations. We present a list of the systematic errors of the operational 5-day forecasts and results of a 1-yr integration with climatological sea surface temperatures. One of the prominent features of NOGAPS integrations is a large diurnal oscillation in the global mean averages. This oscillation is traced to large differences in total albedo over the land and sea areas. We pres...

This study investigates the characteristic differences of tropical disturbances that eventually develop into tropical cyclones (TCs) versus those that did not, using global daily analysis fields of the Navy Operational Global Atmospheric Prediction System (NOGAPS) from the years 2003 to 2008. Time filtering is applied to the data to extract tropical waves with different frequencies. Waves with a 3–8-day period represent the synoptic-scale disturbances that are representatives as precursors of TCs, and waves with periods greater than 20 days represent the large-scale background environmental flow. Composites are made for the developing and nondeveloping synoptic-scale disturbances in a Lagrangian frame following the disturbances. Similarities and differences between them are analyzed to understand the dynamics and thermodynamics of TC genesis. Part I of this study focuses on events in the North Atlantic, while Part II focuses on the western North Pacific. A box difference index (BDI), accounting for both the mean and variability of the individual sample, is introduced to subjectively and quantitatively identify controlling parameters measuring the differences between developing and nondeveloping disturbances. Larger amplitude of the BDI implies a greater possibility to differentiate the difference between two groups. Based on their BDI values, the following parameters are identified as the best predictors for cyclogenesis in the North Atlantic, in the order of importance: 1) water vapor content within 925 and 400 hPa, 2) rain rate, 3) sea surface temperature (SST), 4) 700-hPa maximum relative vorticity, 5) 1000–600-hPa vertical shear, 6) translational speed, and 7) vertically averaged horizontal shear. This list identifies thermodynamic variables as more important controlling parameters than dynamic variables for TC genesis in the North Atlantic. When the east and west (separated by 40°W) Atlantic are examined separately, the 925–400-hPa water vapor content remains as the most important parameter for both regions. The SST and maximum vorticity at 700 hPa have higher importance in the east Atlantic, while SST becomes less important and the vertically averaged horizontal shear and horizontal divergence become more important in the west Atlantic.

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 (Bcond), 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.

We present a description of the development of the spectral forecast components of the Navy Operational Global Atmospheric Prediction System (NOGAPS). The original system, called 3.0, was introduced in January 1988. New versions were introduced in March 1989 (3.1) and August 1989 (3.2). A brief description of each version of the forecast model is given. Each physical parameterization is also described. We discuss the large changes in 3.1 and the motivation behind the changes. Statistical results from forecast comparison tests are discussed. Figures showing the total monthly forecast performance in the Northern Hemisphere and the Southern Hemisphere are also given. A brief discussion is presented of computational details, running times, and memory requirements of the forecast model.

Sea surface temperature (SST) diurnal variation is an important part of air-sea energy exchange, and its response to the Madden–Julian Oscillation (MJO) also helps in studying the development mechanism of the MJO. This study investigates SST diurnal variation in the North Indian Ocean by employing hourly data from the FY-4A geostationary satellite, in conjunction with reanalysis products and the MJO index. Validation against in situ SST measurements shows a bias of –0.33°C, an absolute bias of 0.73°C, an RSD of 0.33°C, an RMSE of 0.94°C, and a correlation coefficient of 0.90. The results demonstrate consistent accuracy throughout the diurnal cycle. Diurnal warming is most pronounced in the northern Arabian Sea and northern Bay of Bengal, especially from March to May prior to the monsoon onset. Wind speed and shortwave flux emerge as key drivers, although wind speed exerts a stronger regional influence on diurnal warming. Furthermore, the SST diurnal variation responds to the MJO within 1–2 days, as its active phase increases cloud cover and intensifies wind, thereby suppressing daytime warming. Despite the high temporal resolution of FY-4A, which allows for detailed sub-daily observations, monsoonal circulation and cloud cover can reduce data availability, complicating quantitative studies of SST variability and MJO feedbacks. Therefore, integrating multiple data sources is crucial for comprehensive analyses. Overall, these findings underscore the potential of geostationary satellites for monitoring diurnal SST fluctuations and emphasize the necessity of accounting for complex atmospheric–oceanic interactions in the North Indian Ocean when examining the role of diurnal variation in broader climate processes.