Climate Forecast System Reanalysis Winds Research Articles

Climatology and variability of wind speeds along the southwest coast of India derived from Climate Forecast System Reanalysis winds

AbstractWind climate along the southwest coast of India (Kerala coast) has been analysed using 41 years of Climate Forecast System Reanalysis (CFSR) winds to delineate long‐term trends and variability. The study reveals significant decreasing trends in annual mean wind speeds, of the order of −2.0 to −2.5 cm·s−1·year−1, for the period 1979–2019. Southwest monsoon has contributed the highest weakening trends (−3.0 to −4.0 cm·s−1·year−1) due to significant decrease in the southwesterly/westerly wind speeds. The wind climate and trends during the northeast monsoon and premonsoon seasons have been characterized largely by the prevalence of sea breeze and shamal–makran wind systems. We find that the intensity of both sea breeze and shamal–makran wind systems reduces from north to south along the Kerala coast, which is in consistent with the earlier studies. Decadal oscillations in wind speeds, driven by the decadal variability in large‐scale atmosphere–ocean circulations, are evident. Recent changes in the frequency of occurrence of Indian Ocean Dipole in the Indian Ocean have determined the overturning trends since 2010, and resulted in increasing trends in the current decade along the central and northern coasts of Kerala. Furthermore, interannual variability in wind speeds has been linked to the El Niño–Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD).

Impacts of Climate Oscillation on Offshore Wind Resources in China Seas

The long-term stability and sustainability of offshore wind energy resources are very important for wind energy exploration. In this study, the Cyclostationary Empirical Orthogonal Function (CSEOF) method, which can determine the time varying spatial distributions and long-term fluctuations in the cyclostationary geophysical process, was adopted to investigate the geographical and temporal variability of offshore wind resources in China Seas. The CSEOF analysis was performed on wind speeds at 70 m height above the sea surface from a validated combined Quick Scatterometer (QuikSCAT) and Advanced Scatterometer (ASCAT) wind product (2000–2016) with high spatial resolution of 12.5 km, and Climate Forecast System Reanalysis (CFSR) wind data (1979–2016) with a grid size of 0.5° × 0.5°. The decomposition results of the two datasets indicate that the first CSEOF mode represents the variability of wind annual cycle signal and contributes 77.7% and 76.5% to the wind energy variability, respectively. The principal component time series (PCTS) shows an interannual variability of annual wind cycle with a period of 3–4 years. The second mode accounts for 4.3% and 4.7% of total wind speed variability, respectively, and captures the spatiotemporal contribution of El Niño Southern Oscillation (ENSO) on regional wind energy variability. The correlations between the mode-2 PCTS of scatterometer or CFSR winds and the Southern Oscillation Index (SOI) are greater than 0.7, illustrating that ENSO has a significant impact on China’s offshore wind resources. Moreover, the mode-1 or mode-2 spatial pattern of CFSR winds is basically consistent with that of scatterometer data, but CFSR underestimates the temporal variability of annual wind speed cycle and the spatial changes of wind speed related to ENSO. Compared with reanalysis data, scatterometer winds always demonstrate a finer structure of wind energy variability due to their higher spatial resolution. For ENSO events with different intensities, the impact of ENSO on regional wind resources varies with time and space. In general, El Niño has reduced wind energy in most regions of China Seas except for the Bohai Sea and Beibu Bay, while La Niña has strengthened the winds in most areas except for the Bohai Sea and southern South China Sea.

Assessing the Impact of Wave–Current Interactions on Storm Surges and Waves during Cold Air Outbreaks in the Northern East China Sea

Storm surges and disastrous waves induced by cold air outbreaks, a type of severe weather system, often impact the coastal economic development. Using the Climate Forecast System Reanalysis wind product and the Coupled Ocean–Atmosphere–Wave–Sediment Transport model, we developed a coupled numerical model and applied it to examine the interaction between surface gravity waves and ocean currents during cold air outbreaks in two case studies in the northern East China Sea. The results revealed that wave–current interactions improved the simulation accuracy, especially the water level, as verified by tidal station measurements. We conducted sensitivity experiments to explore the spatiotemporal variation of the impact of wave–current interactions on storm surges and waves in the northern East China Sea, away from the coastline. The wave-induced surge (up to 0.4 m) and the wave-induced current (up to 0.5 m/s) were found to be related to the difference between wave direction and current direction. The significant wave height difference (up to 0.5 m) was sensitive to the storm surge nearshore and sensitive to the current field offshore, while the mean wave direction change (up to 40°) was more sensitive to the current field than to the storm surge. Additionally, the wave–current interaction regulated the momentum balance and wave action balance, respectively. By comparison, the momentum residuals of pressure gradient, Coriolis force, Coriolis–Stokes force, and bottom stress, which were pronounced in different areas, were modulated more significantly by the wave effect than other terms. The dominant mechanisms of wave–current interactions on waves included the current-induced modification of energy generation caused by wind input, the current-induced modification of energy dissipation caused by whitecapping, and the current-induced wave advection.

Use of Oceanic Reanalysis to Improve Estimates of Extreme Storm Surge

AbstractA storm surge hindcast for the west coast of Canada was generated for the period 1980–2016 using a 2D nonlinear barotropic Princeton Ocean Model forced by hourly Climate Forecast System Reanalysis wind and sea level pressure. Validation of the modeled storm surges using tide gauge records has indicated that there are extensive areas of the British Columbia coast where the model does not capture the processes that determine the sea level variability on intraseasonal and interannual time scales. Some of the discrepancies are linked to large-scale fluctuations, such as those arising from major El Niño and La Niña events. By applying an adjustment to the hindcast using an ocean reanalysis product that incorporates large-scale sea level variability and steric effects, the variance of the error of the adjusted surges is significantly reduced (by up to 50%) compared to that of surges from the barotropic model. The importance of baroclinic dynamics and steric effects to accurate storm surge forecasting in this coastal region is demonstrated, as is the need to incorporate decadal-scale, basin-specific oceanic variability into the estimation of extreme coastal sea levels. The results improve long-term extreme water level estimates and allowances for the west coast of Canada in the absence of long-term tide gauge records data.

Sea State Trends and Variability: Consistency Between Models, Altimeters, Buoys, and Seismic Data (1979–2016)

AbstractWave hindcasts of long time series (>30 years) have been instrumental in understanding the wave climate. However, it is still difficult to have a consistent reanalysis suitable for study of trends and interannual variability. Here we explore the consistency of a wave hindcast with independent observations from moored buoys, satellite altimeters, and seismic data. We use the Climate Forecast System Reanalysis (CFSR) winds to drive a wave model since extreme events are generally well captured. Unfortunately, the original CFSR winds are not homogeneous in time. We systematically modify this wind field in time and space to produce a wave field that has homogeneous differences against the Globwave/SeaStateCCI altimeter wave height database. These corrections to the winds and resulting waves are validated using independent buoy and microseism data. We particularly use seismic data in the dominant double‐frequency band, around 5‐s period, that are generated by opposing waves of equal frequencies. The seismic data confirms that our correction of time‐varying biases is consistent, even in remote and undersampled region such as the Southern Ocean where the original CFSR biases are strongest. Our analysis is performed on monthly time series, and we expect the monthly statistics to be better suited for climate studies. Remaining issues with time consistency of reanalysis products and associated wave hindcasts are further discussed.

Development and validation of a regional-scale high-resolution unstructured model for wave energy resource characterization along the US East Coast

Leveraging the high-performance computing capability at one of the US Department of Energy’s (USDOE) National Laboratories, an ultra-high-resolution Simulating WAves Nearshore (SWAN) model suitable for wave energy project feasibility studies is developed for the US East Coast Region. This model uses an unstructured mesh with a coastal resolution of 200 m. It is forced by Climate Forecast System Reanalysis wind fields with spatial and temporal resolutions of 0.312° and 1 h at the surface, and by wave parameters from the global WAVEWATCH III model along the model’s open boundaries. It is the first USDOE regional wave hindcast model for the US East Coast developed according to International Electrotechnical Commission standards for wave energy resource assessment and characterization. The present study focuses on the development and validation of this ultra-high resolution large-scale model, including source model selection, sensitivity studies, and model performance evaluation for a wave energy resource characterization application.

How do uncertainties in NCEP R2 and CFSR surface fluxes impact tropical ocean simulations?

NCEP/DOE reanalysis (R2) and Climate Forecast System Reanalysis (CFSR) surface fluxes are widely used by the research community to understand surface flux climate variability, and to drive ocean models as surface forcings. However, large discrepancies exist between these two products, including (1) stronger trade winds in CFSR than in R2 over the tropical Pacific prior 2000; (2) excessive net surface heat fluxes into ocean in CFSR than in R2 with an increase in difference after 2000. The goals of this study are to examine the sensitivity of ocean simulations to discrepancies between CFSR and R2 surface fluxes, and to assess the fidelity of the two products. A set of experiments, where an ocean model was driven by a combination of surface flux components from R2 and CFSR, were carried out. The model simulations were contrasted to identify sensitivity to different component of the surface fluxes in R2 and CFSR. The accuracy of the model simulations was validated against the tropical moorings data, altimetry SSH and SST reanalysis products. Sensitivity of ocean simulations showed that temperature bias difference in the upper 100 m is mostly sensitive to the differences in surface heat fluxes, while depth of 20 °C (D20) bias difference is mainly determined by the discrepancies in momentum fluxes. D20 simulations with CFSR winds agree with observation well in the western equatorial Pacific prior 2000, but have large negative bias similar to those with R2 winds after 2000, partly because easterly winds over the central Pacific were underestimated in both CFSR and R2. On the other hand, the observed temperature variability is well reproduced in the tropical Pacific by simulations with both R2 and CFSR fluxes. Relative to the R2 fluxes, the CFSR fluxes improve simulation of interannual variability in all three tropical oceans to a varying degree. The improvement in the tropical Atlantic is most significant and is largely attributed to differences in surface winds.

Wind and wave characteristics in the Black Sea based on the SWAN wave model forced with the CFSR winds

Wind and wave characteristics and their long-term variability in the Black Sea over a period of 31 years are investigated in this study. The state-of-the art spectral wave model SWAN is implemented to perform a 31- year wave hindcast in the area of interest. The simulation results are used to assess the inter-annual variability and long-term changes in wind and wave climate in the Black Sea for the period 1979–2009. The SWAN model is forced with the Climate Forecast System Reanalysis (CFSR) winds. The model is calibrated and validated against available wave measurements at six offshore and near-shore locations spread over a large region in the Black Sea. The calibration was performed by tuning parameters in the white-capping and wind input formulations against available measurements for 1996 at three offshore locations (Gelendzhik, Hopa, and Sinop). The validation was carried out using measured data, at Gelendzhik, Hopa, and Sinop offshore locations, Gloria drilling platform and Karaburun and Filyos near-shore locations. From the 31-year simulation results, the long-term spatial distributions and changes of the mean wind and mean and maximum wave characteristics and their inter-annual variabilities were determined. The calibration improved SWAN model performance by 11.6% for Hm0 and 3.3% for Tm02 on average at three locations. The mean annual significant wave height (Hm0) and mean wind speed (WS) indicate the occurrence of higher wave heights and wind speeds in the western Black Sea compared to the south eastern coasts of the Black Sea. The coefficient of variation over the Black Sea for Hm0 and WS shows that the variability for Hm0 is higher than that of WS. It is also observed that the variability for Hm0 is higher in areas (such as offshore Gelendzhik, Russia) where the variability of WS is high. Besides, the storms mentioned in the previous studies (such as Galabov and Kortcheva, 2013; Tarakcioglu et al., 2015) are observed in four interesting characteristic areas with maximum Hm0 determined in this study over the Black Sea.

An assessment of the wind re-analyses in the modelling of an extreme sea state in the Black Sea

This study aims at an assessment of wind re-analyses for modelling storms in the Black Sea. A wind-wave modelling system (Simulating WAve Nearshore, SWAN) is applied to the Black Sea basin and calibrated with buoy data for three recent re-analysis wind sources, namely the European Centre for Medium-Range Weather Forecasts Reanalysis-Interim (ERA-Interim), Climate Forecast System Reanalysis (CFSR), and Modern Era Retrospective Analysis for Research and Applications (MERRA) during an extreme wave condition that occurred in the north eastern part of the Black Sea. The SWAN model simulations are carried out for default and tuning settings for deep water source terms, especially whitecapping. Performances of the best model configurations based on calibration with buoy data are discussed using data from the JASON2, TOPEX-Poseidon, ENVISAT and GFO satellites. The SWAN model calibration shows that the best configuration is obtained with Janssen and Komen formulations with whitecapping coefficient (Cds) equal to 1.8e−5 for wave generation by wind and whitecapping dissipation using ERA-Interim. In addition, from the collocated SWAN results against the satellite records, the best configuration is determined to be the SWAN using the CFSR winds. Numerical results, thus show that the accuracy of a wave forecast will depend on the quality of the wind field and the ability of the SWAN model to simulate the waves under extreme wind conditions in fetch limited wave conditions.

Wave energy resource assessment in Uruguay

Marine energy sources are an untapped resource able to make a significant contribution to renewable and clean energy generation. In Uruguay, investment in renewable energy has experienced strong growth in recent years. Because the country is located in a microtidal zone, wave energy is the most promising marine energy resource. An assessment of its potential was conducted from a 31-year wave hindcast performed with the Wavewatch III® third-generation wave model forced by CFSR (Climate Forecast System Reanalysis) winds. The model was calibrated and validated with altimeter data and in situ measurements. The spatial distribution of the resource and its variability at different timescales were analyzed, as well as the correlation between the variability of the directional wave spectrum and several climate indexes. The extreme conditions that a wave energy converter should withstand were analyzed, and a new figure was defined to quantify the impact of extreme conditions on WEC (Wave energy converter) design and optimization. The obtained results show that although wave energy potential is moderate, it is fairly steady throughout the year, and the extreme waves are relatively benign. Therefore, wave energy is an attractive resource for integration into the country energy mix, contributing to its diversification and sustainability.

Statistical estimation of extreme ocean waves over the eastern Canadian shelf from 30-year numerical wave simulation

Reliable estimation of extreme ocean surface gravity waves is important for many scientific and practical issues. In this study, WAVEWATCHIII is used to simulate wave conditions over the eastern Canadian shelf (ECS) for the 30-year period, 1979–2008. The wave model is forced by the 6-hourly winds and ice cover taken from the Climate Forecast System Reanalysis (CFSR). A parametric vortex is inserted into the CFSR winds to better represent surface winds associated with tropical storms or hurricanes. The model performance in simulating the bulk significant wave height is assessed by comparing model results with wave observations at 12 buoy stations over the ECS. The peaks-over-threshold method is used to estimate the extreme significant wave heights from 30-year wave simulations. The estimated extreme waves with the 50-year return period over the ECS feature large wave heights of more than 12 m in the offshore deep waters and about 8–12 m over the open shelf waters of the ECS. By comparison, the 50-year extreme waves are moderate and 7 m or less in the Gulf of St. Lawrence and inner Gulf of Maine.

Application of the spectral correction method to reanalysis data in south Africa

In connection with applying reanalysis data for extreme wind estimation, this study investigates the use of a simple approach that corrects the smoothing effect in numerical modeling through adding in missing spectral information for relatively high, mesoscale frequencies. This approach, called the spectral correction method, has been applied in the wind energy community for estimating the design winds. Two particular aspects are examined, firstly the diurnal spectral peak and then the meso-microscale interface. Both aspects provide challenges for the application of the method, and the purpose of this study is to evaluate the applicability of the method to the relevant region. The impacts from the two aspects are investigated for interior and coastal locations. Measurements from five stations from South Africa are used to evaluate the results from the spectral model S(f)=af−5/3 together with the hourly time series of the Climate Forecast System Reanalysis (CFSR) 10m wind at 38km resolution over South Africa. The results show that using the spectral correction method to the CFSR wind data produce extreme wind atlases in acceptable agreement with the atlas made from limited measurements across the country to a temporal resolution of 1h. However, the modeled data tend to underestimate the diurnal peaks in the coastal areas, with a resultant underestimation of the 1:50-year wind speed. Measurements, even of limited length, could improve the estimate. Lastly, the validity of using the spectral model into higher frequencies is limited by the spectral gap between the meso- and microscale.

Wave climate simulation for southern region of the South China Sea

This study investigates long-term variability and wave characteristic trends in the southern region of the South China Sea (SCS). We implemented the state-of-the art WAVEWATCH III spectral wave model to simulate a 31-year wave hindcast. The simulation results were used to assess the inter-annual variability and long-term changes in the SCS wave climate for the period 1979 to 2009. The model was forced with Climate Forecast System Reanalysis winds and validated against altimeter data and limited available measurements from an Acoustic Wave and Current recorder located offshore of Terengganu, Malaysia. The mean annual significant wave height and peak wave period indicate the occurrence of higher wave heights and wave periods in the central SCS and lower in the Sunda shelf region. Consistent with wind patterns, the wave direction also shows southeasterly (northwesterly) waves during the summer (winter) monsoon. This detailed hindcast demonstrates strong inter-annual variability of wave heights, especially during the winter months in the SCS. Significant wave height correlated negatively with Nino3.4 index during winter, spring and autumn seasons but became positive in the summer monsoon. Such correlations correspond well with surface wind anomalies over the SCS during El Nino events. During El Nino Modoki, the summer time positive correlation extends northeastwards to cover the entire domain. Although significant positive trends were found at 95 % confidence levels during May, July and September, there is significant negative trend in December covering the Sunda shelf region. However, the trend appears to be largely influenced by large El Nino signals.

Patterns and cycles in the Climate Forecast System Reanalysis wind and wave data

The Climate Forecast System Reanalysis and the corresponding WAVEWATCH III hindcast datasets allow climatic interpretation of winds as well as their impacts on waves. In this paper, we analyze the continuous 31years of global wind and wave data in terms of climate patterns and cycles. Quarterly averages and percentile plots of the wind speed and wave height illustrate the seasonal pattern and distributions of extreme events, while the annual and inter-annual variability demonstrates the wind and wave climate. The data is correlated with published indices of known atmospheric cycles. The datasets show good correspondence with the Arctic Oscillation, Antarctic Oscillation, El Nino Southern Oscillation, and the Madden-Julian Oscillation in both the wind and wave fields. The results compare well with published climate studies on regional scales and provide important linkage to the global wave climate characteristics.

Validation of a thirty year wave hindcast using the Climate Forecast System Reanalysis winds

A thirty one year wave hindcast (1979–2009) using NCEP’s latest high resolution Climate Forecast System Reanalysis (CFSR) wind and ice database has been developed and is presented here. The hindcast has been generated using the third generation wind wave model WAVEWATCH III® with a mosaic of 16 two-way nested grids. The resolution of the grids ranged from 1/2° to 1/15°. Validation results for bulk significant wave height Hs and 10m (above Mean Sea Level) wind speeds U10 have been presented using both altimeter records and NDBC buoys. In general the database does a good job of representing the wave climate. At most buoys there is excellent agreement between model and data out to the 99.9th percentile. The agreement at coastal buoys is not as good as the offshore buoys due to unresolved coastal features (topographic/bathymetric) as well as issues related to interpolating wind fields at the land-sea margins. There are some concerns about the wave climate in the Southern Hemisphere due to the over prediction of winds (early part of the database) as well as the lack of wave blocking due to icebergs (in the model).