Satellite Wind Data Research Articles

Wave Hindcast and Extreme Value Analysis for the Southern Part of the Caspian Sea

This paper describes the eleven years (1992–2002) of wave simulation in the Caspian Sea to achieve the wave climate atlas of this basin. The latest version of a 3rd generation wave hindcast model was used to predict wind wave characteristics during this period. The 10 meters wind field of the European Center for Medium Range Weather Forecasts (ECMWF) and the bathymetric map of the basin were employed as the input data of the model. In situ and satellite wind and wave data sets were used to evaluate the accuracy of the input wind field and the simulated wave field. Extreme Value Analysis (EVA) was the next stage in which the wave characteristics were calculated for different return periods and finally a user-friendly engineering and management tool was developed and verified to extract the required wind & wave characteristics in the basin.

Subtleties in forcing eddy resolving ocean models with satellite wind data

Using new global satellite remote sensing data, we show that ignoring the ocean current dependence in the wind stress artificially increases global wind power input to the oceanic general circulation by about 32%, and more than doubles the input in the regions of strong ocean current systems. Scatterometer-derived wind stress naturally accounts for the moving ocean that is not included in traditional wind stress products. However, forcing an ocean model with a scatterometer-derived wind stress cannot actually account for the ocean current effect on the wind power input. The difference between the real and modeled surface eddy fields can reduce the damping associated with the ocean current dependence in wind stress, leading to a positive bias in global wind power input of about 23%. Most of this spurious energy flux goes directly to the fluctuation eddy field and is several times larger than the energy flux to real ocean eddies.

Seasonal variations in pCO 2 and its controlling factors in surface seawater of the northern East China Sea

Surface partial pressure of CO 2 ( pCO 2), temperature, salinity, nutrients, and chlorophyll a were measured in the East China Sea (ECS; 31°30′–34°00′N to 124°00′–127°30′E) in August 2003 (summer), May 2004 (spring), October 2004 (early fall), and November 2005 (fall). The warm and saline Tsushima Warm Current was observed in the eastern part of the survey area during four cruises, and relatively low salinity waters due to outflow from the Changjiang (Yangtze River) were observed over the western part of the survey area. Surface pCO 2 ranged from 236 to 445 μatm in spring and summer, and from 326 to 517 μatm in fall. Large pCO 2 (values >400 μatm) occurred in the western part of the study area in spring and fall, and in the eastern part in summer. A positive linear correlation existed between surface pCO 2 and temperature in the eastern part of the study area, where the Tsushima Warm Current dominates; this correlation suggests that temperature is the major factor controlling surface pCO 2 distribution in that area. In the western part of the study area, however, the main controlling factor is different and seasonally complex. There is large transport in this region of Changjiang Diluted Water in summer, causing low salinity and low pCO 2 values. The relationship between surface pCO 2 and water stability suggests that the amount of mixing and/or upwelling of CO 2-rich water might be the important process controlling surface pCO 2 levels during spring and fall in this shallow region. Sea–air CO 2 flux, based on the application of a Wanninkhof [1992. Relationship between wind speed and gas exchange over the ocean. Journal of Geophysical Research 97, 7373–7382] formula for gas transfer velocity and a set of monthly averaged satellite wind data, were −5.04±1.59, −2.52±1.81, 1.71±2.87, and 0.39±0.18 mmol m −2 d −1 in spring, summer, early fall, and fall, respectively, in the northern ECS. The ocean in this study area is therefore a carbon sink in spring and summer, but a weak source or in equilibrium with the atmosphere in fall. If the winter flux value is assumed to have been the mean of autumnal and vernal values, then the northern ECS absorbs about 0.013 Pg C annually. That result suggests that the northern ECS is a net sink for atmospheric CO 2, a result consistent with previous studies.

Properties of Ellipticity Correlation with Atmospheric Structure from Gemini South

Cosmic shear holds great promise for a precision independent measurement of Ωm, the mass density of the universe relative to the critical density. The signal is expected to be weak, so a thorough understanding of systematic effects is crucial. An important systematic effect is the atmosphere: shear power introduced by the atmosphere is larger than the expected signal. Algorithms exist to extract the cosmic shear from the atmospheric component, although a measure of their success applied to a range of seeing conditions is lacking. To gain insight into atmospheric shear, Gemini South imaging, in conjunction with ground condition and satellite wind data, was obtained. We find that under good seeing conditions point-spread function (PSF) correlations persist well beyond the separation typical of high-latitude stars. Under these conditions, ellipticity residuals based on a simple PSF interpolation can be reduced to within a factor of a few of the shot noise induced ellipticity floor. We also find that the ellipticity residuals are highly correlated with wind direction. Finally, we correct stellar shapes using a more sophisticated procedure and generate shear statistics from stars. Under all seeing conditions in our data set the residual correlations lie everywhere below the target signal level. For good seeing we find that the systematic error attributable to atmospheric turbulence is comparable in magnitude to the statistical error (shape noise) over angular scales relevant to present lensing surveys.

On the annual cycle of coastal and open ocean satellite chlorophyll off Chile (18°–40°S)

High resolution SeaWiFS (Sea‐viewing Wide Field‐of‐view Sensor) chlorophyll and satellite wind data (1997–2004) are used to analyze the coastal and oceanic behavior of sea surface chlorophyll (CHL) concentration in the eastern boundary current system off Chile (18°–40°S). Two contrasting regimes are evident; a coastal regime, where CHL maximum occurs during summer, coinciding with the maximum upwelling‐favorable wind stress and an offshore regime, where the CHL maximum is in winter and is not related to the maximum wind (stress, curl). Moreover, our analysis reveals that the annual coastal CHL cycle is strong along the entire latitudinal extension, contrary to previous observations that showed a weak seasonal cycle off northern Chile. Averaging ocean‐color data across spatial domains where different forcings and processes operate will lead to unreliable retrieval of pigment biomass. Proper characterization of biological processes in upwelling and coastal regions requires deriving statistics over the relevant spatial scales.

Impact of special observations on the numerical simulation of a heavy rainfall event during ARMEX-Phase I

The heavy rainfall event over west coast of India during 26 - 28 June 2002 (ARMEX Phase - I) is simulated using a high-resolution mesoscale model-NCAR MM5. Two experiments were made with and without the inclusion of special observations of ARMEX – Phase I along with Quickscat and SSM/I surface winds. NCAR MM5, with four nested domains of 81, 27, 9 and 3 km resolutions, is integrated for 72 hr from 0000 UTC of 25 June 2002. The initial and boundary conditions are derived from NCEP analysis at 1 - degree resolution. Quantitative precipitation estimates and the wind fields from MM5 output are analysed. The model results indicate the formation of a mesoscale convective system and associated heavy rainfall on 27 and 28 June 2002. The model could predict heavy rainfall upto about 30 cm/day though some observations at isolated locations are up to 50 cm/day. Experiment with the inclusion of ARMEX observations and satellite wind data seem to improve the prediction of the location of the maxima and the movement of the rain band but with a slight decrease in the intensity of the heavy rainfall.

Coastal upwelling fluxes of O<sub>2</sub>, N<sub>2</sub>O, and CO<sub>2</sub> assessed from continuous atmospheric observations at Trinidad, California

Abstract. Continuous atmospheric records of O2/N2, CO2 and N2O obtained at Trinidad, California document the effects of air-sea exchange during coastal upwelling and plankton bloom events. The atmospheric records provide continuous observations of air-sea fluxes related to synoptic scale upwelling events over several upwelling seasons. Combined with satellite, buoy and local meteorology data, calculated anomalies in O2/N2 and N2O were utilized in a simple atmospheric transport model to compute air-sea fluxes during coastal upwelling. CO2 fluxes were linked to the oceanic component of the O2 fluxes through local hydrographic data and estimated as a function of upwelling intensity (surface ocean temperature and wind speed). Regional air-sea fluxes of O2/N2, N2O, and CO2 during coastal upwelling were estimated with the aid of satellite wind and SST data. Upwelling CO2 fluxes were found to represent ~10% of export production along the northwest coast of North America. Synoptic scale upwelling events impact the net exchange of atmospheric CO2 along the coastal margin, and will vary in response to the frequency and duration of alongshore winds that are subject to climate change.

Estimation of observation impact using the NRL atmospheric variational data assimilation adjoint system

An adjoint-based procedure for assessing the impact of observations on the short-range forecast error in numerical weather prediction is described. The method is computationally inexpensive and allows observation impact to be partitioned for any set or subset of observations, by instrument type, observed variable, geographic region, vertical level or other category. The cost function is the difference between measures of 24-h and 30-h global forecast error in the Navy Operational Global Atmospheric Prediction System (NOGAPS) during June and December 2002. Observations are assimilated at 00UTC in the Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS). The largest error reductions in the Northern Hemisphere are produced by rawinsondes, satellite wind data, and aircraft observations. In the Southern Hemisphere, the largest error reductions are produced by Advanced TIROS Operational Vertical Sounder (ATOVS) temperature retrievals, satellite wind data and rawinsondes. Approximately 60% (40%) of global observation impact is attributed to observations below (above) 500 hPa. A significant correlation is found between observation impact and cloud cover at the observation location. Currently, without consideration of moisture observations and moist processes in the forecast model adjoint, the observation impact procedure accounts for about 75% of the actual reduction in 24-h forecast error.

Tropical Pacific control of intraseasonal oscillations off Chile by way of oceanic and atmospheric pathways

Sea level, current, satellite wind data and a simple model of wind‐forced, low frequency waves are used to study the origins of strong, observed intraseasonal variability in the ocean and atmosphere off Chile. There intraseasonal wind fluctuations are correlated to wind fluctuations in the equatorial Pacific, associated with the Madden‐Julian Oscillation. Results suggest intraseasonal teleconnections via two distinct atmospheric pathways. Very simple model simulations forced by satellite winds from the equator and the South American coast compare well with observed fluctuations of currents and sea level off central Chile. There most of this intraseasonal variability, particularly during summer and during El Niño events, arrives as free, oceanic, coastal trapped waves via oceanic, equatorial Kelvin waves, forced by tropical Pacific winds. South of 20°S, some oceanic intraseasonal variability is forced by local winds associated with the atmospheric teleconnections.

Impact ofGMS-5andGOES-9Satellite-Derived Winds on the Prediction of a NORPEX Extratropical Cyclone

Abstract The impact of satellite-derived wind observations on the prediction of a mid–Pacific Ocean cyclone during the North Pacific Experiment (NORPEX, 14 Jan–27 Feb 1998) is assessed using a four-dimensional variational (4DVAR) approach in which a nonhydrostatic version of the Pennsylvania State University–National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) serves as a strong constraint. The satellite-derived wind observations are retrieved through an automated tracking algorithm using water vapor visible, and infrared imagery from the operational Geostationary Meteorological Satellite-5 (GMS-5) and Geostationary Operational Environmental Satellite-9 (GOES-9) over the North Pacific basin. For the case studied, it is found that the amount of satellite wind data is much greater in the upper troposphere than in the lower troposphere. The 4DVAR assimilation of the satellite wind observations is carried out on a single domain with 90-km horizontal resolution. Incorporation of sate...

Marine wind analysis from remotely sensed measurements

A primary objective of this study is to demonstrate a methodology that can potentially be used to generate high spatial resolution gridded vector wind fields for the northwest Atlantic on synoptic time scales. This task is accomplished using optimal interpolation (OI) to blend satellite wind data from European remote sensing (ERS-2) satellite scatterometers, National Aeronautics and Space Administration (NASA) scatterometers (NSCAT), and TOPEX/Poseidon and ERS-2 altimeters with numerical weather prediction (NWP) model wind estimates. The NWP model wind fields are produced using the MC2 atmospheric model (Canadian mesoscale compressible community atmospheric model). The grid for these fields is 0.25°. OI correlation functions and variances are derived from remotely sensed data. A second objective of the study is to provide a methodology for validation of synthetic aperture radar (SAR) derived vector winds from RADARSAT-1 images collected during the 1997 Labrador Sea Deep Convection Experiment (LSDCE). These winds are derived from the observed radar cross section and a scatterometer wind retrieval model. The validation of the SAR-derived winds is based on the OI winds and in situ ship-based winds.

Ocean currents evident in satellite wind data

Satellite‐mounted radar scatterometers designed to quantify surface winds over the ocean actually measure the relative motion between the air and the ocean surface. Estimates of the wind stress from conventional surface wind measurements are usually derived neglecting ocean currents. However, when the relative motion is used, the differences in the estimated stress can be as large as 50% near the equator and may even reverse sign during an El Niño. This assertion is supported by the strong relationship between the surface currents measured by the Tropical Atmosphere‐Ocean (TAO) array in the Pacific Ocean and the differences between the winds estimated from scatterometer data and those measured by TAO anemometers. The fact that the scatterometer measures relative motion, and not wind alone, makes scatterometer‐derived stress a more accurate representation of the boundary condition needed for both atmospheric and oceanic models than stress fields derived neglecting ocean currents.

A global wave hindcast over the period 1958–1997: Validation and climate assessment

This study describes the first 40 year global wave simulation derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NRA) surface wind fields. The NRA 10 m wind fields were input into a deep water version of a proven spectral ocean wave model adapted onto a global grid of spacing 1.25° in latitude by 2.5° in longitude. In situ and satellite wind and wave data sets were used to evaluate the hindcast skill. The validation showed excellent agreement not only in terms of bias and scatter but over the entire frequency distribution out to 99th percentiles of both winds and waves. A global trend analysis showed statistically significant areas of both increasing and decreasing winds and waves. The increasing trend in the northeast Atlantic and decreasing trend in the central North Atlantic are particularly well defined and consistent with changes reported in previous studies, which were linked to changes in the North Atlantic Oscillation. The trend analysis highlighted the difficulty in separating creeping inhomogeneities in the NRA winds from real climate change, illustrating the need to use homogeneous in situ measured data to confirm trends derived from model output. The trends derived from the hindcast seem reasonable in the Northern Hemisphere and may provide a good upper bound to true trends in the wind and wave climate.

Recent developments in the continuous assimilation of satellite wind data for tropical cyclone track forecasting

Tropical cyclone track forecasting remains a vexing problem. Here, we have examined nine forecasts in the Australian Region which were generally deemed difficult. The forecast problem has been addressed in three ways. First, modelling and data assimilation have been performed at very high (15 km) resolution. Second, a newly developed data source, namely, high spatial and temporal resolution cloud drift winds, has been used to augment the often quite poor data base upon which forecasts are based and, in one case, these winds have been augmented with scatterometer-based surface winds. Finally, a range of continuous assimilation techniques, including recently developed 4-D variational assimilation and hourly nudging have been tested. In these cases, where often, conventional forecast guidance and CLIPER (Morison, 1993) were poor, continuous assimilation procedures, i.e. 1-hourly nudging and 4-D variational assimilation, took best advantage of the high resolution winds and provided much improved forecasts. Worthy of note was, for the case examined, scatterometer winds were able to reduce the initial position error of the cyclone. Overall, it would appear continuous assimilation, combined with a substantial high resolution data base and high resolution modelling have the potential to greatly improve the accuracy of tropical cyclone track forecasts.

Targeted observations in FASTEX: Adjoint‐based targeting procedures and data impact experiments in IOP17 and IOP18

AbstractThe Fronts and Atlantic Storm‐Track EXperiment (FASTEX) provided an opportunity for testing targeted‐observing procedures in a real‐time framework during January and February 1997. This study describes the use of singular vectors (SVs) for objective targeting during FASTEX, and the evaluation of the impact obtained from targeted dropsonde data, satellite wind data, and other observations on 1‐2 day forecast skill in intensive observation periods (IOPs) 17 and 18.In IOP17, targeted dropsondes improve a 42 h forecast of L41 (Low 41; cyclones were numbered in sequence throughout FASTEX) in terms of sea‐level pressure, but the forecast skill is degraded in the upper troposphere. It is suggested that the degraded forecast may be caused by an incomplete survey of the SV target area, that improved the analysis in one region, but made the analysis less accurate in an adjacent part of the target area where no dropsonde data were provided. In a series of experiments, the best 42 h forecast of L41 is obtained by the addition of a few radiosonde profiles provided specially for FASTEX at off‐times, that provide observational data in the most sensitive part of the SV target area. the analysis differences introduced by the radiosonde profiles are much smaller in magnitude than those from the dropsonde data, but have a larger forecast impact, because they occur in an area that has larger error growth rates in this forecast.In a series of experiments for IOP18, the best 24 h forecast of L44 is obtained using a combination of targeted‐dropsonde data and satellite wind data. Both data types can also be used separately to improve this forecast. the assimilation of satellite wind data and ship‐based soundings in areas of weak initial‐condition sensitivity (‘null’ areas) is shown to have minimal impact on the forecast error. the target areas identified by SVs in these two IOPs occur in strongly baroclinic regions, tending to favour the right‐entrance and left‐exit regions of the upper‐level jet, but with greatest sensitivity near 600 hPa.

Improved Hurricane Track Forecasting from the Continuous Assimilation of High Quality Satellite Wind Data

Abstract Despite recent improvements in the accuracy of hurricane track forecasts, mean position errors still remain unacceptably large. For example, recurvature is captured poorly by forecast models and can produce excessively large position errors. This study addresses the problem of hurricane track forecasting in three ways. First, the initial conditions for the forecast model are augmented by a dense coverage of high spatial and temporal resolution satellite-derived wind vectors. Second, to gauge the extent to which this additional four-dimensional detail of the atmospheric structure can be exploited, three distinct types of data assimilation methods are examined. These are 1) conventional (intermittent, cycled) 6-h assimilation, 2) nudging over a 12- or 24-h period up to the initial time, and 3) recently developed barotropic and four-dimensional variational assimilation schemes, also over a 12- or 24-h period. The nudging and variational methods are continuous assimilation procedures and incorporate ...

An optimal interpolation scheme for the assimilation of spectral wave data

An optimal interpolation scheme for assimilating two‐dimensional wave spectra is presented which is based on a decomposition of the spectrum into principal wave systems. Each wave system is represented by three characteristic parameters: significant wave height, mean propagation direction, and mean frequency. The spectrum is thereby reduced to a manageable number of parameters. From the correction of the wind‐sea system a correction of the local wind is derived. A 2‐month test of the system using wave spectra retrieved from ERS 1 synthetic aperture radar wave mode data in the Atlantic yielded consistent corrections of winds and waves. However, the corrected wind data alone, although valuable in identifying wind errors in critical high wind speed regions, are too sparsely distributed in space and time to be used in isolation and need to be combined with other data in an atmospheric data assimilation scheme. This emphasizes the need for the development of combined wind and wave data assimilation schemes for the optimal use of satellite wind and wave data.

Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

Abstract. The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale) experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period). Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies), and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The classical momentum flux bulk parameterization was found to fail in low wind and unstable conditions. Finally, the sea surface was investigated using airborne and satellite radars and wave buoys. A wave model, operationally used, was found to get better results compared with radar and wave-buoy measurements, when initialized using an improved wind field, obtained by assimilating satellite and buoy wind data in a meteorological model. A detailed analysis of a 2-day period showed that the swell component, propagating from a far source area, is underestimated in the wave model. A data base has been created, containing all experimental measurements. It will allow us to pursue the interpretation of observations and to test model simulations in the ocean, at the surface and in the atmospheric boundary layer, and to investigate the ocean-atmosphere coupling at the local and mesoscales.

Lidar-Measured Winds from Space: A Key Component for Weather and Climate Prediction

The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate. This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds. Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.

Validation and assimilation of Seasat altimeter wave heights using the WAM wave model

The mutual consistency of the Seasat global data sets of scatterometer winds and altimeter wave heights is investigated for the complete Seasat period using the third‐generation wave model WAM. The wave model was driven by surface (1000 hPa) wind and surface stress fields constructed by the Goddard Laboratory for Atmospheres (GLA) by assimilation of the scatterometer winds in an atmospheric model. For the 10‐day period September 7–17 the intercomparison was extended to two further scatterometer wind fields: a 1000‐hPa assimilated wind field from the European Centre for Medium‐Range Weather Forecasts and a subjectively analyzed 19.5‐m‐height surface wind field from the Jet Propulsion Laboratory. On the global average, the modeled and observed wave heights agree reasonably well. Regional differences, however, can be large and sometimes exceed 40%. The errors are attributed mainly to deficiencies in the forcing wind fields. Low wind speeds are found to be overestimated and high wind speeds underestimated by the Seasat scatterometer algorithm. The friction velocities of the GLA model are found to be significantly underestimated in the high‐wind belt of the southern hemisphere. The analysis demonstrates the diagnostic advantages of applying a wave model for the quality assessment of satellite wind and wave data. A preliminary wave data assimilation scheme is presented in which the wave field is updated without changing the forcing wind field. A considerable improvement of the computed wave field is achieved, particularly in regions in which the wave energy is dominated by swell. However, a more general assimilation scheme including modifications of the wind field is needed to upgrade wind sea forecasts.