Offshore Wind Resources Assessment from Multiple Satellite Data and WRF Modeling over South China Sea

Assessment of wind resources in two parts of Northeast Brazil with the use of numerical models

In October 2010, typhoon Megi induced a profound cold wake of size 800 km by 500 km with sea surface temperature cooling of 8°C in the South China Sea (SCS). More interestingly, the cold wake shifted from the often rightward bias to both sides of the typhoon track and moved to left in a few days. Using satellite data, in situ measurements and numerical modeling based on the East Asian Seas Nowcast/Forecast System (EASNFS), we performed detailed investigations. To obtain realistic typhoon‐strength atmospheric forcing, the EASNFS applied typhoon‐resolving Weather Research and Forecasting (WRF) model wind field blended with global weather forecast winds from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS). In addition to the already known impacts from the slow typhoon translation speed and shallow pre‐exiting ocean thermocline, we found the importance of the unique geographical setting of the SCS and the NE monsoon. As the event happened in late October, NE monsoon already started and contributed to the southwestward ambient surface current. Together with the topographicβ effect, the cold wake shifted westward to the left of Megi's track. It was also found that Megi expelled waters away from the SCS and manifested as a gush of internal Kelvin wave exporting waters through the Luzon Strait. The consequential sea level depression lasted and presented a favorable condition for cold dome development. Fission of the north‐south elongated cold dome resulted afterward and produced two cold eddies that dissipated slowly thereafter.

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

The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.

Starting from 2003, a new typhoon surveillance program, Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR), was launched. During 2004, 10 missions for eight typhoons were conducted successfully with 155 dropwindsondes deployed. In this study, the impact of these dropwindsonde data on tropical cyclone track forecasts has been evaluated with five models (four operational and one research models). All models, except the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model, show the positive impact that the dropwindsonde data have on tropical cyclone track forecasts. During the first 72 h, the mean track error reductions in the National Centers for Environmental Prediction’s (NCEP) Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS) of the Fleet Numerical Meteorology and Oceanography Center (FNMOC), and the Japanese Meteorological Agency (JMA) Global Spectral Model (GSM) are 14%, 14%, and 19%, respectively. The track error reduction in the Weather Research and Forecasting (WRF) model, in which the initial conditions are directly interpolated from the operational GFS forecast, is 16%. However, the mean track improvement in the GFDL model is a statistically insignificant 3%. The 72-h-average track error reduction from the ensemble mean of the above three global models is 22%, which is consistent with the track forecast improvement in Atlantic tropical cyclones from surveillance missions. In all, despite the fact that the impact of the dropwindsonde data is not statistically significant due to the limited number of DOTSTAR cases in 2004, the overall added value of the dropwindsonde data in improving typhoon track forecasts over the western North Pacific is encouraging. Further progress in the targeted observations of the dropwindsonde surveillances and satellite data, and in the modeling and data assimilation system, is expected to lead to even greater improvement in tropical cyclone track forecasts.

A set of criteria is developed to identify tropical cyclone (TC) formations in the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecast fields. Then the NOGAPS forecasts of TC formations from 1997 to 1999 are verified relative to a formation time defined to be the first warning issued by the Joint Typhoon Warning Center. During these three years, the spatial distributions of TC formations were strongly affected by an El Nino–Southern Oscillation event. The successful NOGAPS predictions of formation within a maximum separation threshold of 4° latitude are about 70%–80% for 24-h forecasts, and drop to about 20%–30% for 120-h forecasts. The success rate is higher for formations in the South China Sea and between 160°E and 180° but is generally lower between 120° and 160°E. The composite 850-hPa large-scale flow for the formations between 120° and 160°E is similar to a monsoon confluence region with marked cross-equatorial flow. Therefore, it is concluded that the skil...

: 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-degrees and 2-degrees, depending on the availability. Monthly means of heat budget components are computed on the basis of monthly means of atmospheric variables during 1984-2000.

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).

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.

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 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.

Satellite-borne synthetic aperture radar (SAR) offers the potential for remotely sensing surface wind speed both over the open sea and in close proximity to the coast. The resolution improvement of SAR over scatterometers is of particular advantage near coasts. Thus, there is a need to verify the performance of SAR wind speed retrieval in coastal environments adjacent to very complex terrain and subject to strong synoptic forcing. Mountainous coasts present a challenge because the wind direction values required for SAR wind speed retrieval algorithms cannot be obtained from global model analyses with as much accuracy there as over the open ocean or adjacent to gentle coasts where most previous SAR accuracy studies have been conducted. The performance of SAR wind speed retrieval in this challenging environment is tested using a 7-yr dataset from the mountainous coast of the Gulf of Alaska. SAR-derived wind speeds are compared with direct measurements from three U.S. Navy Oceanographic Meteorological Automatic Device (NOMAD) buoys. Both of the commonly used SAR wind speed retrieval models, CMOD4 and CMOD5, were tested, as was the impact of correcting the buoy-derived wind speed profile for surface-layer stability. Both SAR wind speed retrieval models performed well although there was some wind speed–dependent bias. This may be either a SAR wind speed retrieval issue or a buoy issue because buoys can underestimate winds as wind speed and thus sea state increase. The full set of tests is performed twice, once using wind directions from the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model analyses and once using wind direction observations from the buoys themselves. It is concluded that useful wind speeds can be derived from SAR backscatter and global model wind directions even in proximity to mountainous coastlines.

In this paper, we perform a comparison of wind speed measurements from the ENVISAT Advanced Synthetic Aperture Radar (ASAR), the MetOp-A Advanced Scatterometer (ASCAT), the U.S. National Data Buoy Center's moored buoys, and the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model. These comparisons were made in near U.S. coast regions over a 17-month period from March 2009 to July 2010. The ASAR wind speed retrieval agreed well with the scatterometer and model estimates, with mean differences ranging from -0.69 to 0.85 m/s and standard deviations between 1.16 and 1.77 m/s, depending upon the ASAR beam mode type. The results indicate that ASAR-derived ocean surface wind speeds are as accurate as the ASCAT and NOGAPS wind products. Comparisons between ASCAT winds and synthetic aperture radar (SAR) winds averaged at different spatial resolutions show very little change. This demonstrates that it is suitable that the scatterometer wind retrieval geophysical model function, i.e., CMOD5, is used for SAR wind retrieval. The impact of C-band VV polarization SAR calibration error on wind retrieval is also discussed.

The convective parameterization of Emanuel has been employed in the forecast model of the Navy Operational Global Atmospheric Prediction System (NOGAPS) since 2000, when it replaced a version of the relaxed Arakawa–Schubert scheme. Although in long-period data assimilation forecast tests the Emanuel scheme has been found to perform quite well in NOGAPS, particularly for tropical cyclones, some weaknesses have also become apparent. These weaknesses include underprediction of heavy-precipitation events, too much light precipitation, and unrealistic heating at upper levels. Recent research efforts have resulted in modifications of the scheme that are designed to reduce such problems. One change described here involves the partitioning of the cloud-base mass flux into mixing cloud mass flux at individual levels. The new treatment significantly reduces a heating anomaly near the tropopause that is associated with a large amount of mixing cloud mass flux ascribed to that region in the original Emanuel ...

A high-order accurate radiative transfer (RT) model developed by Fu and Liou has been implemented into the Navy Operational Global Atmospheric Prediction System (NOGAPS) to improve the energy budget and forecast skill. The Fu–Liou RT model is a four-stream algorithm (with a two-stream option) integrating over 6 shortwave bands and 12 longwave bands. The experimental 10-day forecasts and analyses from data assimilation cycles are compared with the operational output, which uses a two-stream RT model of three shortwave and five longwave bands, for both winter and summer periods. The verifications against observations of radiosonde and surface data show that the new RT model increases temperature accuracy in both forecasts and analyses by reducing mean bias and root-mean-square errors globally. In addition, the forecast errors also grow more slowly in time than those of the operational NOGAPS because of accumulated effects of more accurate cloud–radiation interactions. The impact of parameterized cloud effective radius in estimating liquid and ice water optical properties is also investigated through a sensitivity test by comparing with the cases using constant cloud effective radius to examine the temperature changes in response to cloud scattering and absorption. The parameterization approach is demonstrated to outperform that of constant radius by showing smaller errors and better matches to observations. This suggests the superiority of the new RT model relative to its operational counterpart, which does not use cloud effective radius. An effort has also been made to improve the computational efficiency of the new RT model for operational applications.