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2- https://doi.org/10.1029/2008jc004760
Comment on “Seasonal heat budgets of the Red and Black seas” by Matsoukas et al.
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Take Notes [1] Matsoukas et al. [2007] present a monthly analysis of heat fluxes in relation to heat budget in the Red and Black Seas to provide further insight for air-sea exchange processes in the small ocean basins. Components of net surface heat flux are illustrated during 1984–1995. In computing latent and sensible heat fluxes, Matsoukas et al. [2007] apply traditional bulk formulations. A heat balance method that is based on the available energy for evaporation flux is also presented to compare latent heat fluxes with those from the bulk formulations. All near-surface atmospheric variables, including wind speed at 10 m, used in the heat balance method are obtained from reanalysis of a numerical weather product (NWP). Initial input data for radiation flux calculations are at resolutions of 1.0° and 2.5°, depending on the availability. Monthly means of heat budget components are computed on the basis of monthly means of atmospheric variables during 1984–2000. [2] Concerning heat fluxes in the Red and Black Seas, all computations and their details are generally properly presented by Matsoukas et al. [2007]. We worry, however, about one major concern (section 3 and 4). We also identify two other potentially important issues and suggest how these might alter results (section 5). Here our major focus is that Matsoukas et al. [2007] do not consider the representativeness errors inherent in using input data from a coarse resolution NWP product in studying air-sea exchange processes in small ocean basins, such as the Red and Black Seas. This neglection poses serious errors in heat budget computations. For example, the Red Sea is a narrow inland water body which has relatively shallow water depths (Figure 1). It is roughly 1900 km long and, at its widest point, over 300 km wide. Oceanic features are greatly influenced by seasonally reversing winds in this small region so interactions between the ocean shelf and the adjacent continent are of great interest. Therefore, wind speed at 10 m is expected have great influence on latent and sensible heat fluxes especially near coastlines. Use of improper winds for heat flux computations can thus misleadingly influence heat budget estimates as will be described in section 3. In addition, the 2.5° resolution study used in their data cannot accurately represent sea-only radiative fluxes for the small Red and Black Seas. [3] The data for surface atmospheric variables in calculating sensible and latent heat fluxes in the paper by Matsoukas et al. [2007] are obtained from a NWP product, namely, European Centre for Medium-Range Weather Forecasts. Unfortunately, the gridded global fields provided by the NWP centers are generally at a spatial scale too coarse to appropriately define the contrast between water and land grid points for small ocean basins, such as the Red and Black Seas. Such NWP products are given in Table 1. [4] Our focus will be on quantifying the accuracy of the wind speed at 10 m from coarse resolution NWP products, including European Centre for Medium-Range Weather Forecasts 40-year Reanalysis (ERA-40) as used by Matsoukas et al. [2007]. We particularly use wind speed at 10 m for such evaluations since accuracy of latent and sensible heat flux computations strongly depends on accuracy of winds in the bulk parameterizations. For validations of NWP winds a relatively finer gridded wind product, Quick Scatterometer (QSCAT), is formed from satellite measurements (Table 1). In particular, twice-daily QSCAT wind measurements are obtained from Remote Sensor Systems (RSS), http://www.remss.com, and monthly means of rain-free winds are formed. Data for NWP products are obtained from the National Center for Atmospheric Research (NCAR) data support section (http://dss.ucar.edu/datasets/), and monthly means are constructed using 6 hourly values. [5] Several problems arise when using wind speed from the 1.125° × 1.125° resolution (≈125 km) ERA-40 product in computing latent and sensible heat fluxes in the Red Sea especially near the coastal boundaries. At best there can be no more than two grid points in the horizontal direction (Figure 1). Matsoukas et al. [2007] use a 1° grid resolution, and for a specific latitude, the longitude span was between 1 and 3 grid points for the Red Sea. In any case, winds at most grid points near the land-sea boundaries over the sea are contaminated by land values due to relatively coarse resolution, i.e., a grid point includes wind values from both land and ocean, affecting the accuracy of the computed latent and sensible heat fluxes. [6] The land-sea mask values from all NWP products, including the 1.125° resolution ERA-40 on the Gaussian grid, are interpolated to a finer grid of 1/12° (Figure 2a). This is done in order to demonstrate land contamination of winds near the coastal regions and also their accuracies in the interior. The ocean and land areas in NWP products are typically defined by a land-sea mask of zeros and ones, indicating that a grid cell is treated as all sea or all land, respectively. A percentage land-sea mask value of 40 (100), for example, in Figure 2 explains that wind speed at 10 m over the sea are 40% (100%) contaminated by winds over land. [7] The land-sea mask for QSCAT has a different meaning since all satellite measurements are over the sea, and thus there is no land contamination. We describe the satellite-based QSCAT mask as 1.0 for data void areas and 0.0 for regions with valid QSCAT winds. On a month by month basis the mask could vary depending on the orbital pattern. A land-sea mask value of 1.0 for QSCAT winds indicates that there are no valid measurements in that region, in that particular month; this most commonly occurs near the coast. Note that the scatterometer cannot make reliable measurements within 35 km of the coast. [8] In Figure 2a, the most obvious feature of the land-sea mask values is that the land contamination from NWP products exists near all coastal boundaries of the Red Sea. This is especially seen from National Centers for Environmental Prediction (NCEP), which has the coarsest grid resolution. The land-sea mask from ERA-40 also reveals lots of land contamination near the coastal boundaries with only a small white region in the interior where there is no land contamination. This indicates that sensible and latent heat flux computations presented in the paper by Matsoukas et al. [2007] are all based on land-contaminated wind speed values. It is emphasized that in grid cells near the coastline ERA-40 provides both land values and sea values with the final cell-averaged value based on the fraction of land. ERA-40 only has true sea-only values where its land-sea mask is exactly zero, which is far away from the coast. For all products, also including QSCAT, there is no confidence in the accuracy of wind in the northernmost end of the Red Sea on the basis of the land-sea masks because of their insufficient grid resolution. [9] Spatial variations of wind speed at 10 m from QSCAT are compared to those from NWP products during February and August of 2001 (Figures 2b, 2c, 2d, and 2e). These two months are chosen for illustrative purposes. Figure 2b is identical to Figure 2c except that the former also includes winds over land. Winds from QSCAT are available starting from July 1999 onward, but winds from the ERA-40 reanalysis are not available beyond September 2002. For comparison purposes, we therefore choose the year 2001. Satellite-based QSCAT winds are taken as truth, justified because there is no land contamination in the QSCAT winds and they are more reliable than NWP winds near the land-sea boundaries over the global ocean [Kara et al., 2008a]. [10] For NWP winds in February, the consequences from land contamination are severe especially for Navy Operational Global Atmospheric Prediction System (NOGAPS) and ERA-40 (Figure 2b). Since wind speeds over land are low (e.g., <3 m s-1), land contamination makes wind speed weaker over the sea near the coastal boundaries. Wind speed estimates over coastal waters are relatively weaker than those in the interior. NCEP winds over land near the coastal boundary are weak as well, but they are stronger than those from NOGAPS and ERA-40. Thus, relatively coarse resolution NCEP winds have low contrast between land and sea points. This low contrast diminishes the impact from the land contamination in NCEP. Similar features are also evident in August (Figure 2d). [11] Winds from all products are generally uniform over the Red Sea during February (Figure 2c) and August (Figure 2e) of 2001. The common feature of NWP winds is that they are all weaker than the satellite-based QSCAT winds not only near the coastal boundaries but also in the interior, especially in the northern part of the region where QSCAT winds are much stronger (>2 m s−1). Weaker winds from NWP products also exist in other months (not shown). [12] Differences between NWP and QSCAT winds are computed to examine typical biases for the fields shown in Figures 2b and 2c. Winds from NWP products are almost always weaker than those from QSCAT over the Red Sea with some exceptions (Figure 3). Differences in the interior are ≈1 m s−1 and can even be larger in the case of ERA-40 during both February and August of 2001. Near the coastal boundaries of the Red Sea, differences from QSCAT are >3–4 m s−1, particularly for ERA-40 winds, because of the relatively large land contamination of winds over the sea. [13] As demonstrated above, winds from QSCAT are stronger than those from ERA-40. Here, we have a demonstration of what percentage of this is due to the resolution/land mask issue (and other regional effects) and how much is due to the fact that QSCAT winds are normally stronger the ERA-40 winds. Using a 1° × 1° uniform grid over the Red Sea, basin average of the QSCAT wind speeds is 6.4 m s−1 in February of 2001. Because all QSCAT wind measurements are only over water, they are not affected by land contamination. Basin average of original wind speeds from ERA-40 is 3.9 m s−1, and this includes the effects of land contamination. The original ERA-40 winds have a 39% (1-(3.9 m s−1/6.4 m s−1)) low bias relative to QSCAT. [14] If one tries to exclude land contamination by using the sea-fill methodology [Kara et al., 2007a], basin average of the ERA-40 wind speeds becomes 5.3 m s−1, a 17% low bias relative to QSCAT. Note that the creeping sea-fill technique makes use of only over-sea values of any given scalar atmospheric variable (e.g., wind speed here) and replaces the value associated with each land-masked point by one using only nearby sea values [see also Kara et al., 2008a]. In other words, wind speeds shown in the white regions of the land-sea mask of ERA-40 (see Figure 2a) are interpolated to the coastal boundaries. The program for the creeping sea-fill methodology is available online at http://www7320.nrlssc.navy.mil/nasec/. Thus, 56% (1-(17%/39%)) of the original ERA-40 low wind speed bias is due to land contamination that is remedied by the application of the creeping sea-fill in February of 2001. The remainder of the low bias is not attributable to the land contamination as it is evident in the interior of the Red Sea, i.e., even away from land, ERA-40 winds are 17% weaker than QSCAT. [15] One of the most important variables in determining the heat budgets in the Red and Black Seas is latent heat flux. As discussed in the preceding section (Figure 3), in comparison to fine resolution QSCAT, there are large errors in winds from NWP products near the coastal boundaries of the Red Sea. Because latent heat flux is a direct function of wind speed at 10 m in the bulk formulation, we examine whether the resulting heat budget can be significantly affected by ignoring the land contamination, as was done by Matsoukas et al. [2007]. On the basis of new calculations, updated values for the heat budget components are also provided for the Red and Black Seas. [16] To demonstrate the impact of land contamination on latent heat flux, we compute climatological monthly means on the basis of 6 hourly outputs from ERA-40 reanalysis from 1 September 1978 to 1 September 2002 (25 years). We started from 1978 rather than 1957, when the original ERA-40 analysis started, because most of the satellite data used in the assimilation procedure became available around 1979. Climatological means are computed at two grid resolutions: 1° × 1° grids to be consistent with Matsoukas et al. [2007] and 1/12° × 1/12° grids to further include coastal regions of the Red Sea. [17] As an example, climatological mean of latent heat flux is examined in February. In addition to original values directly obtained from ERA-40 at 1° and 1/12° resolutions (Figures 4a and 4c), we also show sea-filled latent heat fluxes for the corresponding fields (Figures 4b and 4d) after the creeping sea-fill methodology described earlier is applied. The land contamination is so severe near the coastal boundaries of the Red Sea that values of latent heat fluxes that had been exceedingly low (e.g., 50 W m−2) become very high (e.g., 200 W m−2) after the creeping sea-fill, especially in the northernmost areas. Excessively low latent heat fluxes from the original ERA-40 reanalysis can easily be attributed to unrealistically weak winds from ERA-40 (Figure 3a). The creeping sea-fill reduces land contamination from latent heat fluxes at both grid resolutions (Figures 4b and 4d). [18] The importance of using a fine resolution ocean grid of 1/12° as opposed to a coarse grid of 1° in obtaining basin-averaged latent heat fluxes is evident in Table 2. Although original ERA-40 values can be quite different, sea-filled values agree with each other quite well. Annually, differences between original and and sea-filled latent heat flux values can be as large as 50 W m−2. Matsoukas et al. [2007] do not have any specific consideration for the land contamination. As expected, such contamination from the 1° gridded field is relatively large. While it is not shown here, land contamination of radiation fluxes is less severe (<30 W m−2). [19] One may notice that the sea-filled latent heat climatologies look different from original fields calculated from ERA-40 (Figure 4). This can be explained as follows. On the basis of the land-sea mask of ERA-40 (Figure 2a) there is essentially one single ERA-40 sea value for each of its latitude bands in the Red Sea, and a few bands have two values). This means that the across the sea variation in ERA-40 is entirely from land/sea differences. Using the sea-fill approach, we assume the land is like the closest sea point. Therefore, there is no across the sea variation in this case. This is clearly seen in the plot south of 22°N. North of 22°N, one sees some across the sea variation (where ERA-40 has two grid points over sea). However, the sea grid points are also much more consistent (blue) and significantly different from the nearby land points. The blue values are in the all-values plots, but swamped by other color contours from land. The impact of land contamination due to coarse grid resolutions of NWP products is also discussed in the Black Sea [Kara et al., 2008b]. [20] Finally, for completeness we present net heat budgets for the Red and Black Seas (Table 3). For each component of the net heat budget, sea-filled values are first produced on the basis of the land-sea mask of ERA-40 (Figure 2a). Climatological means are then computed on the basis of 6 hourly values during 1978–2002. It is quite remarkable that when using the sea-filled ERA-40 data, the heat budget is successfully closed in the Black Sea with a net value of 0 W m−2. The heat budget in the Red Sea is also almost closed with a net value of −8 W m−2. [21] In this commentary, so far our major focus has been on the land contamination issues, resulting in improper estimates of the heat budget in the Red and Black Seas. There are two more additional points. First important isssue is that all results presented in the paper by Matsoukas et al. [2007] are derived using monthly means of atmospheric variables to compute monthly mean latent and sensible heat fluxes. In traditional climate studies [e.g., Josey et al., 1999; Boyer et al., 2006], high-frequency observations of wind speed and other atmospheric variables are used to make estimates of heat flux which are then averaged to compute monthly means. Matsoukas et al. [2007] could have used the 6 hourly NWP products to estimate 6 hourly latent and sensible heats fluxes from which monthly means could be calculated. Using monthly mean atmospheric variables in computing “monthly” fluxes can result in ≈20% difference depending on the time and location [e.g., Lee et al., 2005; Gulev, 1997]. [22] Another fundamental problem in the paper by Matsoukas et al. [2007] is that in computing latent and sensible heat fluxes they use outdated parameterizations for exchange coefficients [Vardavas, 1987]. Their study assumes neutral atmospheric conditions for each month, and the above mentioned monthly winds are preferred in these calculations. However, there has been significant progress in determining exchange coefficients since 1987. For example, the well-known and commonly used Couped Ocean-Atmosphere Response Experiment (COARE) algorithm (v3.0) provides up-to-date exchange coefficient parameterizations for computing latent and sensible heat fluxes [Fairall et al., 2003]. Results based on the COARE algorithm clearly reveal that ignoring the effects of vapor mixing ratio in the parameterization of exchange coefficient can give a flux value that is ≈3–5 times less than its actual value at very low wind speeds [Kara et al., 2005]. This is further illustrated at the web page http://www7320.nrlssc.navy.mil/nasec/. Using only wind speed and ignoring air-sea stratification (i.e., neutral case) can also cause errors as large as 20% or more in the wind stress exchange coefficient even on monthly means [Kara et al., 2007b]. [23] Results presented by Matsoukas et al. [2007] ignore land contamination in obtaining the heat budget for the Red and Black Seas. We demonstrate that near coastal boundaries, the spatially coarse NWP products have errors not only in the wind fields. Because of large errors (>3 m s−1) in ERA-40 winds, corrections to winds are essential in the heat budget computations. Postprocessing of winds and other NWP fields can reduce errors in latent and sensible heat fluxes near the land-sea boundaries. We found that ignoring the land contamination on latent heat fluxes could result in basin-averaged errors as high as 50 W m−2, significantly changing the heat budget. The errors near the coastline can often be >100 W m−2. As it is demonstrated in this paper, sea-filled shortwave and longwave radiation values processed from ERA-40 and interpolated to fine resolution ocean grids (1/12°) are sufficiently accurate since the net surface heat budget is almost closed in both regions. [24] One of the main goals of their study is to demonstrate that the energy balance method disagrees with the bulk aerodynamic approach. However, the wind errors in their application of the bulk formulation make it difficult to justify comparison between the two methodologies. Specifically, some values of heat budget components presented by Matsoukas et al. [2007] are somewhat consistent with ours shown in Table 3 but this appears to result from a cancellation of errors. For example, by using improper exchange coefficients they may have obtained relatively higher latent and sensible heat fluxes. The use of land-contaminated winds will lead to low estimates of latent heat flux. Errors in other terms would have to compensate by inflating the latent heat flux. In addition, monthly mean winds used for computing monthly mean heat fluxes would lead to additional errors in the resulting heat budget. Our estimates are also based on slightly longer time period of 1978–2001. [25] Satellite-based QSCAT winds can be used for estimating heat budgets in the future. While the available time period of 1999 onward for QSCAT winds may not be long enough for climatological studies, such a fine resolution gridded (0.25°) product would provide spatial resolution more appropriate for the narrow Red and Black Seas. In addition, land contamination in atmospheric variables needs to be taken into consideration whenever NWP products are used for computing heat budgets over sea-only locations. [26] A. Wallcraft of NRL is greatly appreciated for his helpful comments. The authors acknowledge the invaluable suggestions provided by the reviewer. Additional thanks go to C. Matsoukas for numerous discussions. This work is funded by the Office of Naval Research (ONR) under the 6.2 project, Improved Synthetic Ocean Profiles (ISOP). The paper is contribution NRL/JA/7320/08/8084 and has been approved for public release. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
- Research Article
- 52
- 10.1175/jpo2984.1
- Apr 1, 2007
- Journal of Physical Oceanography
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).
- Research Article
- 43
- 10.1029/2008jd011696
- Aug 27, 2009
- Journal of Geophysical Research: Atmospheres
The accuracy of wind speed at 10 m above the sea surface from two satellite and three numerical weather prediction (NWP) products is investigated over the global ocean. Rain‐free equivalent neutral winds from the Quick Scatterometer (QuikSCAT) are converted to stability‐dependent winds to be consistent with those from NWP products and are taken as truth in comparisons to winds from other products. Quantitative statistical analyses presented at each grid point over the global ocean reveal that monthly winds from NWP products have almost perfect skill relative to those from QuikSCAT winds during the 3‐year common period (September 1999 to August 2002). Exceptions occur in tropical regions and high southern latitudes. Wind speeds adjusted to 10 m at many moored buoys located in different regions of the global ocean further confirm the accuracy of monthly NWP winds, giving RMS difference of 1.0 m s−1 based on 1281 monthlong time series. The satellite‐based QuikSCAT winds agree with buoy winds relatively better than NWP products. While there is good agreement among wind products on monthly timescales, large differences (>3 m s−1 and more) in NWP winds are found in comparison to QuikSCAT winds on shorter time intervals at high latitudes. Daily means of sensible and latent heat fluxes based on NWP winds can therefore differ as much as 100 W m−2 in comparison to those based on QuikSCAT winds. In general, NWP wind‐based sensible and latent heat fluxes are more similar to their QuikSCAT wind‐based counterparts in tropical regions and midlatitudes.
- Research Article
- 13
- 10.1029/2006jc003849
- Oct 1, 2007
- Journal of Geophysical Research: Oceans
In this study we calculate the monthly heat budget of the Red and Black Seas and its components: the net solar and net terrestrial fluxes, the sensible and latent heat fluxes, and the monthly heat content change. A radiation transfer model is employed for the estimation of the net solar and terrestrial energy fluxes, instead of commonly used parameterizations. The agreement with radiation fluxes measured at surface stations is within 10 W m−2. The Red Sea net solar flux estimate is lower than past studies, while the Black Sea heat budget components are comparable to some past results. The monthly heat content of both seas is estimated from water temperature and salinity profiles and is found to dominate the seasonal energy exchange between the water and the atmosphere, as for the Mediterranean Sea. The latent heat flux is calculated using two methodologies: the bulk aerodynamic and the energy balance method. Our annual results for the Red and Black seas show solar heating of 238 and 139 W m−2, respectively. The evaporation rates are 2120 and 960 mm yr−1, respectively. The annual aerosol direct forcing on the net solar flux is −10 W m−2 and −3 W m−2.
- Research Article
- 58
- 10.1175/mwr3283.1
- Feb 1, 2007
- Monthly Weather Review
Three observational datasets of Hurricane Isidore (in 2002) were analyzed and compared: the Special Sensor Microwave Imager (SSM/I), the Quick Scatterometer (QuikSCAT) winds, and dropsonde winds. SSM/I and QuikSCAT winds were on average about 1.9 and 0.3 m s−1 stronger, respectively, than dropsonde winds. With more than 20 000 points of data, SSM/I wind speed was about 2.2 m s−1 stronger than QuikSCAT. Comparison of the wind direction observed by QuikSCAT with those from the dropsondes showed that the quality of QuikSCAT data is good. The effect of assimilating SSM/I wind speeds and/or QuikSCAT wind vectors for the analysis of Hurricane Isidore was assessed using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and its three-dimensional variational data assimilation system. For the Hurricane Isidore case study, it was found that the assimilation of either satellite winds strengthened the cyclonic circulation in the analysis. However, the increment of the QuikSCAT wind analysis is more complicated than that from the SSM/I analysis due to the correction of the storm location, a positive result from the assimilation of wind vectors. The increase in low-level wind speeds enhanced the air–sea interaction processes and improved the simulated intensity for Isidore. In addition, the storm structure was better simulated. Assimilation of QuikSCAT wind vectors clearly improved simulation of the storm track, in particular during the later period of the simulation, but lack of information about the wind direction from SSM/I data prevented it from having much of an effect. Assessing the assimilation of QuikSCAT wind speed versus wind vector data confirmed this hypothesis. The track improvement partially resulted from the relocation of the storm’s initial position after assimilation of the wind vectors. For this case study, it was found that the assimilation of SSM/I or QuikSCAT data had the greatest impact on the Hurricane Isidore simulation during the first 2 days.
- Research Article
- 34
- 10.1029/2007jc004516
- Oct 1, 2008
- Journal of Geophysical Research: Oceans
Through a comprehensive analysis, reliability of 10 m wind speeds is presented near the land‐sea boundaries over the global ocean. Winds from three numerical weather prediction (NWP) centers and two satellite‐based products are analyzed. NWP products are 1.875° × 1.875° National Center Environmental Prediction reanalyses, 1.125° × 1.125° European Centre for Medium‐Range Weather Forecasts 40‐year Reanalysis (ERA‐40), and 1.0° × 1.0° Navy Operational Global Atmospheric Prediction System (NOGAPS) operational product. These are compared to much finer resolution (0.25° × 0.25°) satellite winds, Quick Scatterometer (QSCAT) and Special Sensor Microwave/Imager. Large biases (e.g., >3 m s−1) may exist in NWP products near the land‐sea boundaries, because wind speeds from the uniformly gridded global fields are generally at a spatial scale too coarse to appropriately define the contrast between water and land grid points. This so‐called land contamination of ocean‐only winds varies, and typically depends on the extent of the land‐sea mask. A creeping sea‐fill methodology is introduced to reduce errors in winds. It is based on the elimination of land‐corrupted NWP grid points and replacement by adjacent, purely over‐ocean values. In comparison to winds from many moored buoys, the methodology diminishes RMS errors (from >4 m s−1to <1 m s−1) for NOGAPS and ERA‐40. The creeping sea‐fill is not advised for NCEP winds which have low contrast between land and sea points, thereby resulting in little impact from the land contamination.
- Research Article
- 60
- 10.1175/jpo-2656.1
- Jan 1, 2005
- Journal of Physical Oceanography
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.
- Research Article
- 53
- 10.1175/waf934.1
- Aug 1, 2006
- Weather and Forecasting
The NASA Quick Scatterometer (QuikSCAT) has revolutionized the analysis and short-term forecasting of winds over the oceans at the NOAA Ocean Prediction Center (OPC). The success of QuikSCAT in OPC operations is due to the wide 1800-km swath width, large retrievable wind speed range (0 to in excess of 30 m s−1), ability to view QuikSCAT winds in a comprehensive form in operational workstations, and reliable near-real-time delivery of data. Prior to QuikSCAT, marine forecasters at the OPC made warning and forecast decisions over vast ocean areas based on a limited number of conventional observations or on the satellite presentation of a storm system. Today, QuikSCAT winds are a heavily used tool by OPC forecasters. Approximately 10% of all short-term wind warning decisions by the OPC are based on QuikSCAT winds. When QuikSCAT is available, 50%–68% of all weather features on OPC surface analyses are placed using QuikSCAT. QuikSCAT is the first remote sensing instrument that can consistently distinguish extreme hurricane force conditions from less dangerous storm force conditions in extratropical cyclones. During each winter season (October–April) from 2001 to 2004, 15–23 extratropical cyclones reached hurricane force intensity over both the North Atlantic and North Pacific Oceans. Due to QuikSCAT, OPC forecasters are now more likely to anticipate the onset of hurricane force conditions. QuikSCAT has also revealed significant wind speed gradients in the vicinity of strong sea surface temperature (SST) differences near the Gulf Stream and shelfbreak front of the western North Atlantic. These wind speed gradients are most likely due to changes in low-level stability of the boundary layer across the SST gradients. OPC forecasters now use a variety of numerical guidance based tools to help predict boundary layer stability and the resultant near-surface winds.
- Research Article
- 1
- 10.1007/s13131-017-1108-x
- Sep 1, 2017
- Acta Oceanologica Sinica
New satellite-derived latent and sensible heat fluxes are performed by using WindSat wind speed, WindSat sea surface temperature, the European Centre for Medium-range Weather Forecasting (ECMWF) air humidity, and ECMWF air temperature from 2004 to 2014. The 55 moored buoys are used to validate them by using the 30 min and 25 km collocation window. Furthermore, the objectively analyzed air-sea heat fluxes (OAFlux) products and the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis 2 (NCEP2) products are also used for global comparisons. The mean biases of sensible and latent heat fluxes between WindSat flux results and buoy flux data are–0.39 and–8.09 W/m2, respectively. In addition, the root-mean-square (RMS) errors of the sensible and latent heat fluxes between them are 5.53 and 24.69 W/m2, respectively. The RMS errors of sensible and latent heat fluxes are observed to gradually increase with an increasing buoy wind speed. The difference shows different characteristics with an increasing sea surface temperature, air humidity, and air temperature. The zonal average latent fluxes have some high regions which are mainly located in the trade wind zones where strong winds carry dry air in January, and the maximum value centers are found in the eastern waters of Japan and on the US east coast. Overall, the seasonal variability is pronounced in the Indian Ocean, the Pacific Ocean, and the Atlantic Ocean. The three sensible and latent heat fluxes have similar latitudinal dependencies; however, some differences are found in some local regions.
- Research Article
- 39
- 10.1016/s0168-1923(00)00097-6
- Apr 7, 2000
- Agricultural and Forest Meteorology
Turbulent exchange processes within and above a straw mulch.: Part II: Thermal and moisture regimes
- Research Article
- 41
- 10.1175/jcli3573r2.1
- Dec 15, 2005
- Journal of Climate
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 &gt;0.7). Three of the observation-based climatologies generally yield unrealistic circulation features and currents that are too weak.
- Research Article
- 10.1175/mwr-d-24-0003.1
- May 1, 2024
- Monthly Weather Review
Based on data collected from 14 buoys in the Gulf Stream, this study examines how hourly air–sea turbulent heat fluxes vary on subdaily time scales under different boundary layer stability conditions. The annual mean magnitudes of the subdaily variations in latent and sensible heat fluxes at all stations are 40 and 15 W m−2, respectively. Under near-neutral conditions, hourly fluctuations in air–sea humidity and temperature differences are the major drivers of subdaily variations in latent and sensible heat fluxes, respectively. When the boundary layer is stable, on the other hand, wind anomalies play a dominant role in shaping the subdaily variations in latent and sensible heat fluxes. In the context of a convectively unstable boundary layer, wind anomalies exert a strong controlling influence on subdaily variations in latent heat fluxes, whereas subdaily variations in sensible heat fluxes are equally determined by air–sea temperature difference and wind anomalies. The relative contributions by all physical quantities that affect subdaily variations in turbulent heat fluxes are further documented. For near-neutral and unstable boundary layers, the subdaily contributions are O(2) and O(1) W m−2 for latent and sensible heat fluxes, respectively, and they are less than O(1) W m−2 for turbulent heat fluxes under stable conditions. Significance Statement High-resolution buoy observations of air–sea variables in the Gulf Stream provide the opportunity to investigate the physical factors that determine subdaily variations in air–sea turbulent heat fluxes. This study addresses two key points. First, the observed subdaily amplitudes of heat fluxes are related to various processes, including wind fields and air–sea thermal effect differences. Second, the global sea surface heat budget is known to not be in near-zero balance and it ranges from several to tens of watts per square meter. Therefore, consideration of the relatively strong influence of subdaily variability in air–sea turbulent heat fluxes could provide a new strategy for solving the global heat budget balance problem.
- Research Article
- 2
- 10.18307/2019.0425
- Jan 1, 2019
- Journal of Lake Sciences
作为冷季主要的天气事件，冷空气过境会改变湖泊上方的气团性质，对湖泊的水热通量产生影响，进而影响湖泊的生物物理和化学过程.以亚热带大型浅水湖泊——太湖为研究对象，基于2012-2017年5个冷季（11月-翌年3月）的太湖中尺度通量网观测数据，量化不同强度冷空气（寒潮、强冷空气和较强冷空气）对太湖水热通量的影响.结果表明：在5个冷季中，寒潮、强冷空气和较强冷空气发生的总次数分别为4、11和33次，累积持续天数分别为14、31和78天.冷空气过境显著增强太湖的水热通量，3种冷空气过境使太湖的感热通量分别增至无冷空气时的10.3、6.0和4.3倍，潜热通量分别增至无冷空气时的4.0、2.1和2.7倍.虽然冷空气影响天数仅占冷季天数的16.4%，但对整个冷季的潜热和感热通量贡献分别为34.9%和51.7%，以较强冷空气贡献最大.冷空气影响时，水-气界面的温度梯度是太湖感热通量的主控因子，而潜热通量的主控因子为风速.与深水湖泊相比，太湖等浅水湖泊对冷空气过境的响应更快，寒潮过境时尤为明显.;As the major synoptic system, cold air events influence the water vapor and heat exchanges between lake and atmosphere by changing the meteorological conditions of air masses over the lake. Then biophysical and biogeochemical cycles in the lake ecosystem would be moderated by cold air passage. Based on dataset of the Taihu Eddy Flux Network observed during the five cool seasons (2012-2017), the effects of different cold air events (cold wave, severe cold air events and strong cold air events) on latent and sensible heat fluxes were quantified on the large subtropical shallow Lake Taihu. The results showed that cold wave, severe cold air events and strong cold air events totally happened 4, 11 and 33 times, and lasted for 14, 31 and 78 days, respectively. The sensible and latent heat exchanges between lake and atmosphere were accelerated significantly by the passage of cold air. The sensible heat flux increased by 10.3, 6.0 and 4.3 times during cold wave, severe cold air events and strong cold air events, respectively. The latent heat flux was increased by 4.0, 2.1 and 2.7 times, respectively. Although cold air passage only occupied 16.4% of entire cool season, the cold air events contributed 34.9% and 51.7% of the total latent and sensible heat fluxes, respectively. Moreover, the strong cold air events were the biggest contributor. During cold air events, the temperature gradient between the air and water is the most significant factor governing the sensible heat exchange rate. While, the latent heat flux is mostly dominated by wind speed. Compared to deep lakes, shallow lakes response faster to cold air activities. Therefore, the latent and sensible heat fluxes of shallow lakes increase much more, especially during cold waves.
- Research Article
- 314
- 10.1175/jcli-d-11-00004.1
- Mar 14, 2012
- Journal of Climate
Reanalysis products produced at the various centers around the globe are utilized for many different scientific endeavors, including forcing land surface models and creating surface flux estimates. Here, flux tower observations of temperature, wind speed, precipitation, downward shortwave radiation, net surface radiation, and latent and sensible heat fluxes are used to evaluate the performance of various reanalysis products [NCEP–NCAR reanalysis and Climate Forecast System Reanalysis (CFSR) from NCEP; 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and ECMWF Interim Re-Analysis (ERA-Interim) from ECMWF; and Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Global Land Data Assimilation System (GLDAS) from the Goddard Space Flight Center (GSFC)]. To combine the biases and standard deviation of errors from the separate stations, a ranking system is utilized. It is found that ERA-Interim has the lowest overall bias in 6-hourly air temperature, followed closely by MERRA and GLDAS. The variability in 6-hourly air temperature is again most accurate in ERA-Interim. ERA-40 is found to have the lowest overall bias in latent heat flux, followed closely by CFSR, while ERA-40 also has the lowest 6-hourly sensible heat bias. MERRA has the second lowest and is close to ERA-40. The variability in 6-hourly precipitation is best captured by GLDAS and ERA-Interim, and ERA-40 has the lowest precipitation bias. It is also found that at monthly time scales, the bias term in the reanalysis products are the dominant cause of the mean square errors, while at 6-hourly and daily time scales the dominant contributor to the mean square errors is the correlation term. Also, it is found that the hourly CFSR data have discontinuities present due to the assimilation cycle, while the hourly MERRA data do not contain these jumps.
- Research Article
- 16
- 10.3402/polar.v30i0.10167
- Jan 1, 2011
- Polar Research
The latent heat fluxes (LHF) and sensible heat fluxes (SHF) over the Southern Ocean from six different data sets are inter-compared for the period 1988- 2000. The six data sets include three satellite-based products, namely, the second version of the Goddard Satellite-Based Surface Turbulent Fluxes data set (GSSTF-2), the third version of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS-3) and the Japanese Ocean Fluxes Data Sets with Use of Remote Sensing Observations (J-OFURO); two global reanalysis products, namely, the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 data set (NCEP-2) and the European Centre for Medium-Range Weather Forecasts 40 Year Re-analysis data set (ERA-40); and the Objectively Analyzed Air-Sea Fluxes for the Global Oceans data set (OAFlux). All these products reveal a similar pattern in the averaged flux fields. The zonal mean LHF fields all exhibit a continuous increase equatorward. With an exception of HOAPS-3, the zonal mean SHF fields display a minimum value near 50°S, increasing both pole- and equatorward. The differences in the standard deviation for LHF are larger among the six data products than the differences for SHF. Over the regions where the surface fluxes are significantly influenced by the Antarctic Oscillation and the Pacific-South American teleconnection, the values and distributions of both LHF and SHF are consistent among the six products. It was found that the spatial patterns of the standard deviations and trends of LHF and SHF can be explained primarily by sea-air specific humidity and temperature differences; wind speed plays a minor role. Keywords: Latent heat flux; sensible heat flux; Southern Ocean (Published: 17 November 2011) Citation: Polar Research 2011, 30 , 10167, DOI: 10.3402/polar.v30i0.10167
- Research Article
- 34
- 10.1080/1755876x.2021.1911126
- Apr 6, 2021
- Journal of Operational Oceanography
This study aims to investigate the quality of ERA5, a recent reanalysis wind product, and its contribution to wave modelling performance in a semi-closed sea, the Black Sea. This investigation includes a comparison of ERA5 surface wind fields with the ones from the CFSR to assess if this latest reanalysis improved the representation of the surface winds. Wind speeds from both reanalyses were validated with measurements at Gloria, the only sea wind measurement station on the Black Sea. Validations were also conducted using altimeter and scatterometer satellite data after which results were later compared against each other. The second aim of this study investigates whether a wave hindcast model forced with the ERA5 wind fields has improved prediction of wave parameters. A SWAN model with default settings was used to compare the results under the same conditions. Performance analyzes of the default SWAN wave estimates with both ERA5 and CFSR winds were conducted using three offshore buoy measurements and altimeter data of satellites over the Black Sea. Results show that ERA5 winds are more biased compared to CFSR winds at Gloria location. Both CFSR and ERA5 underestimate wind speeds. ERA5 performs better than the CFSR in lower wind speeds and worse in higher wind speeds. However, ERA5 winds have less bias and are more scattered than the CFSR winds against the satellite data. SWAN driven by CFSR winds performs better than the one driven by ERA5 winds against both buoy and satellite data.
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