Lidar Profiles Research Articles

A new lidar inversion method using a surface reference target applied to the backscattering coefficient and lidar ratio retrievals of a fog-oil plume at short range

Abstract. In this paper, a new elastic lidar inversion equation is presented. It is based on the backscattering signal from a surface reference target (SRT) rather than that from a volumetric layer of reference (Rayleigh molecular scatterer) as is usually done. The method presented can be used when the optical properties of such a layer are not available, e.g., in the case of airborne elastic lidar measurements or when the lidar–target line is horizontal Also, a new algorithm is described to retrieve the lidar ratio and the backscattering coefficient of an aerosol plume without any a priori assumptions about the plume. In addition, our algorithm allows a determination of the instrumental constant. This algorithm is theoretically tested, viz. by means of simulated lidar profiles and then using real measurements. Good agreement with available data in the literature has been found.

The Impact of Airborne Doppler Aerosol Wind (DAWN) Lidar Wind Profiles on Numerical Simulations of Tropical Convective Systems during the NASA Convective Processes Experiment (CPEX)

AbstractHigh-spatiotemporal-resolution airborne Doppler Aerosol Wind (DAWN) lidar profiles over the Caribbean Sea and Gulf of Mexico region were collected during the NASA Convective Processes Experiment (CPEX) field campaign from 27 May to 24 June 2017. This study examines the impact of assimilating these wind profiles on the numerical simulation of moist convective systems using an Advanced Research version of the Weather Research and Forecasting (WRF) Model (WRF-ARW). A mesoscale convective system and a tropical storm (Cindy) that occurred on 16 June 2017 in a strong shear environment and on 21 June 2017 in a weak shear environment, respectively, are selected as case studies. The DAWN wind profiles are assimilated with the NCEP Gridpoint Statistical Interpolation analysis system using a three-dimensional variational (3DVar) and a hybrid three-dimensional ensemble-variational (3DEnVar) data assimilation systems to provide the initial conditions for a short-range forecast. Results show that the assimilation of DAWN wind profiles has significant positive impacts on convective simulations with the two assimilation approaches. The assimilation of DAWN wind profiles creates notable adjustments in the analysis of the divergence field for WRF simulations with a good agreement of wind forecasts with radiosonde observations. The quantitative precipitation forecasting is also improved. In general, the 3DEnVar data assimilation method is deemed more promising for DAWN data assimilation. There are cases with Tropical Storm Cindy in which DAWN data have slight to neutral impact on rainfall forecasts with 3DVAR, implying complicated interactions between errors of retrieved wind data and background error covariance in the lower and upper troposphere.

Measuring line-of-sight sodium density structure using laser guide stars

ABSTRACT The performance of adaptive optics systems employing sodium laser guide stars can be improved by continuously monitoring the vertical density structure of mesospheric sodium along the line of sight. We demonstrate that sodium density profiles can be retrieved by amplitude modulation of continuous wave (CW) lasers. In an experiment conducted at the Large Zenith Telescope (LZT), ESO’s Wendelstein Raman-fibre laser was amplitude-modulated with a pseudo-random binary sequence and profiles were obtained by cross-correlation of the modulation pattern with the observed return signal from the laser guide star. For comparison, high-resolution profiles were obtained simultaneously using the lidar system of the LZT. The profiles obtained by the two techniques show noise contamination, but were found to agree to within the measurement error. As a further check, a comparison was also made between several lidar profiles and those obtained by simultaneous observations using a remote telescope to image the laser plume from the side. The modulated CW lidar technique could be implemented by diverting a small fraction of the returned laser light to a photon counting detector. Theoretical analysis and numerical simulations indicate that, for 50 per cent modulation strength, the sodium centroid altitude could be retrieved every 5 s from a single laser guide star, with an accuracy which would induce a corresponding wavefront error of 50 nm for the Extremely Large Telescope and less than 30 nm for the Thirty Meter Telescope and Giant Magellan Telescope. If multiple laser guide stars are employed, the required modulation amplitude will be smaller.

Possible Effects of Greenhouse Gases to Ozone Profiles and DNA Active UV-B Irradiance at Ground Level

In this paper, we compare model calculations of ozone profiles and their variability for the period 1998 to 2016 with satellite and lidar profiles at five ground-based stations. Under the investigation is the temporal impact of the stratospheric halogen reduction (chemical processes) and increase in greenhouse gases (i.e., global warming) on stratospheric ozone changes. Attention is given to the effect of greenhouse gases on ultraviolet-B radiation at ground level. Our chemistry transport and chemistry climate models (Oslo CTM3 and EMAC CCM) indicate that (a) the effect of halogen reduction is maximized in ozone recovery at 1–7 hPa and observed at all lidar stations; and (b) significant impact of greenhouse gases on stratospheric ozone recovery is predicted after the year 2050. Our study indicates that solar ultraviolet-B irradiance that produces DNA damage would increase after the year 2050 by +1.3% per decade. Such change in the model is driven by a significant decrease in cloud cover due to the evolution of greenhouse gases in the future and an insignificant trend in total ozone. If our estimates prove to be true, then it is likely that the process of climate change will overwhelm the effect of ozone recovery on UV-B irradiance in midlatitudes.

The potential of elastic and polarization lidars to retrieve extinction profiles

Abstract. A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem.

Quantification of long-range transported aeolian dust towards the Indian peninsular region using satellite and ground-based data - A case study during a dust storm over the Arabian Sea

The Arabian Sea is an enclosed basin surrounded by land and is prone to receive large amount of aeolian dust from the continent. This can significantly impact surface water biogeochemical processes. In this study, an attempt has been made to quantify the amount of dust transported from Middle East region to Indian subcontinent (sampling site is Goa; 15.45°N 73.80°E; located in the northeast Arabian Sea) via the Arabian Sea. We identified a dust storm episode (02–10 April 2015) in the Arabian Peninsula and its propagation to the study site (Goa) using satellite data (MODIS and CALIPSO). The impact of the dust storm at Goa has been computed using ambient particulate matter concentration and satellite retrieved optical parameter. These observations were further substantiated using ground-based micro-pulse lidar measurement. The daily averaged lidar profile shows relatively high depolarization ratio (0.1–0.25), as well as high daily average backscatter coefficient (up to 0.08 Sr−1 Km−1) and extinction coefficient (up to 0.9 Km−1) during the storm period compared to non-dusty days. During this period, a two-layer (rich in non-spherical particle) structure with significantly high linear depolarization ratio is observed, indicating the impact of the dust storm at the coastal region of India. Ambient mass concentration of dust estimated using CALIPSO profile are comparable with the gravimetric mass measured from high volume sample collection. The back-trajectory analysis further supports the advection of air-mass from the Middle East to Eastern Arabian Sea. This study highlight the significant role of long-range transport in impacting dust load at the remote/receptor sites.

Towards an Algorithm for Near Real Time Profiling of Aerosol Species, Trace Gases, and Clouds Based on the Synergy of Remote Sensing Instruments

In this manuscript we present the concept of a novel algorithmic chain that aims to a dataset of unprecedented detail in the vertical distribution of multiple atmospheric components in near real time conditions. The analysis will be based on the following remote sensing instruments: a depolarization Raman lidar, a visible and a thermal all-sky camera, a Brewer spectrophotometer, and up to three mini DOAS/MAX-DOAS systems. Based on both individual and synergistic processing of the data collected, novel products will be made available in near real time conditions to the end users. Columnar aerosol information from the spectrophotometers will be combined with lidar data to retrieve vertical profiles of individual aerosol species. Cloud layers will be detected and classified based mainly on the synergy of the lidar and the sky cameras and a realistic 3D representation of cloud conditions around the measurement site will be produced. Lidar profiles will be implemented as a priori information for radiative transfer purposes, that are necessary in order to obtain high quality trace gases profiles from the DOAS/MAX-DOAS spectrophotometer. Fast synergistic data processing will ensure that the algorithm can be applied for near real time public data dissemination in the future.

A New Airborne Doppler Lidar for Boundary Layer Research & LES-Based Simulation

Airborne Doppler lidar measurements are a valuable tool in meteorological research. A new airborne Doppler lidar system has been developed jointly by the Karlsruhe Institute of Technology (KIT) and the Technical University of Brunswick. The system is designed for use aboard a medium-range turboprop aircraft, thereby targeting meso-scale flow phenomena. In order to optimize system setup and retrieval strategy, as well as evaluate measurement quality under turbulent conditions, a first LES-based airborne Doppler lidar simulator has been developed. The results provide detailed insight into airborne Doppler lidar wind profiling characteristics.

Retrieval of Dust Microphysical Properties

An intense mineral dust event from the Saharan desert was observed over the Island of Barbados after a long-range transport over the Atlantic Ocean during SALTRACE Campaign in June 2014. We analyze data from a multi-wavelength Raman-lidar system of Leibniz Institute for Tropospheric Research (TROPOS) called BERTHA (Back- scatter Extinction lidar Ratio Temperature Humidity profiling Apparatus) to derive the aerosol microphysical properties of the inspected layer via regularization using the software SphInX (Spheroidal Inversion eXperiments). These parameters were found to be within credible ranges.

Potential of Raman Lidar for Profiling of Methane Mixing Ratio in the Lower Troposphere

The results of methane profiling in the lower troposphere by Raman lidar from Lille University observatory platform (France), are presented. The use of powerful DPSS tripled Nd:YAG laser allowed profiling of methane background mixing ratio of 2 ppm in the night time up to 4000 m with 100 m height and 1 hour temporal resolution. Enhancement of CH4 mixing ratio inside the boundary layer comparing to the free troposphere values was observed.

Ice-nucleating particle versus ice crystal number concentrationin altocumulus and cirrus layers embedded in Saharan dust:a closure study

Abstract. For the first time, a closure study of the relationship between the ice-nucleating particle concentration (INP; INPC) and ice crystal number concentration (ICNC) in altocumulus and cirrus layers, solely based on ground-based active remote sensing, is presented. Such aerosol–cloud closure experiments are required (a) to better understand aerosol–cloud interaction in the case of mixed-phase clouds, (b) to explore to what extent heterogeneous ice nucleation can contribute to cirrus formation, which is usually controlled by homogeneous freezing, and (c) to check the usefulness of available INPC parameterization schemes, applied to lidar profiles of aerosol optical and microphysical properties up to the tropopause level. The INPC–ICNC closure studies were conducted in Cyprus (Limassol and Nicosia) during a 6-week field campaign in March–April 2015 and during the 17-month CyCARE (Cyprus Clouds Aerosol and Rain Experiment) campaign. The focus was on altocumulus and cirrus layers which developed in pronounced Saharan dust layers at heights from 5 to 11 km. As a highlight, a long-lasting cirrus event was studied which was linked to the development of a very strong dust-infused baroclinic storm (DIBS) over Algeria. The DIBS was associated with strong convective cloud development and lifted large amounts of Saharan dust into the upper troposphere, where the dust influenced the evolution of an unusually large anvil cirrus shield and the subsequent transformation into an cirrus uncinus cloud system extending from the eastern Mediterranean to central Asia, and thus over more than 3500 km. Cloud top temperatures of the three discussed closure study cases ranged from −20 to −57 ∘C. The INPC was estimated from polarization/Raman lidar observations in combination with published INPC parameterization schemes, whereas the ICNC was retrieved from combined Doppler lidar, aerosol lidar, and cloud radar observations of the terminal velocity of falling ice crystals, radar reflectivity, and lidar backscatter in combination with the modeling of backscattering at the 532 and 8.5 mm wavelengths. A good-to-acceptable agreement between INPC (observed before and after the occurrence of the cloud layer under investigation) and ICNC values was found in the discussed three proof-of-concept closure experiments. In these case studies, INPC and ICNC values matched within an order of magnitude (i.e., within the uncertainty ranges of the INPC and ICNC estimates), and they ranged from 0.1 to 10 L−1 in the altocumulus layers and 1 to 50 L−1 in the cirrus layers observed between 8 and 11 km height. The successful closure experiments corroborate the important role of heterogeneous ice nucleation in atmospheric ice formation processes when mineral dust is present. The observed long-lasting cirrus event could be fully explained by the presence of dust, i.e., without the need for homogeneous ice nucleation processes.

Air pollution inputs to the Mojave Desert by fusing surface mobile and airborne in situ and airborne and satellite remote sensing: A case study of interbasin transport with numerical model validation

Deserts are fragile and highly sensitive ecosystems that increasingly are affected by upwind urban areas and industrial activities. The Los Angeles Basin (LAB) contributes to poor air quality in downwind deserts including the Mojave Desert. Few studies have investigated potential air pollution inputs to the Mojave, whose fragile ecosystem includes endangered plant and animal species.Data were collected on 19 August 2015 by a mobile air quality laboratory, AMOG (AutoMObile trace Gas) Surveyor, that observed inputs can arise from the LAB as well as the San Joaquin Valley (SJV), California. The campaign used a strong methane (CH4) plume as a tracer for the downwind fate of emissions from Bakersfield area petroleum production and also measured ozone (O3). Additional in situ concurrent airborne GHG and O3 data were collected by AJAX - Alpha Jet Atmospheric eXperiment. Both AMOG and AJAX measure winds.Mojave Desert air quality was very poor (visibility ~4 km). Based on the winds, an additional source was inferred beyond the LAB and SJV Basins. Numerical transport modeling and analysis of aerosol lidar data collected the same day by the Cloud Profiling LiDAR onboard the Earth Research-2 stratospheric airplane demonstrated that fires in Northern California were responsible, with prevailing winds transporting air southwards along the eastern Sierra Nevada Range (Bishop Valley) to the Mojave.Whereas the southern and eastern Mojave are impacted by SJV and LAB outflow, the north Mojave generally avoids these inputs. This study shows it can be affected by even distant wildfires, which likely will increase in occurrence and intensity from climate change. Thus, regulatory efforts to reduce air quality impacts on the endangered Mojave ecosystem must include wildfires and also account for the significant differences between different regions of the Mojave. Currently, there is a paucity of studies, highlighting the critical need for field research.

Growth Rate of Gravity Wave Amplitudes Observed in Sodium Lidar Density Profiles and Nightglow Image Data

Amplitude growth rates of quasi-monochromatic gravity waves were estimated and compared from multiple instrument measurements carried out in Brazil. Gravity wave parameters, such as the wave amplitude and growth rate in distinct altitudes, were derived from sodium lidar density and nightglow all-sky images. Lidar observations were carried out in São Jose dos Campos (23 ∘ S, 46 ∘ W) from 1994 to 2004, while all-sky imagery of multiple airglow layers was conducted in Cachoeira Paulista (23 ∘ S, 45 ∘ W) from 1999–2000 and 2004–2005. We have found that most of the measured amplitude growth rates indicate dissipative behavior for gravity waves identified in both lidar profiles and airglow image datasets. Only a small fraction of the observed wave events (4% imager; 9% lidar) are nondissipative (freely propagating waves). Our findings also show that imager waves are strongly dissipated within the mesosphere and lower thermosphere region (MLT), decaying in amplitude in short distances (<12 km), while lidar waves tend to maintain a constant amplitude within that region. Part of the observed waves (16% imager; 36% lidar) showed unchanging amplitude with altitude (saturated waves). About 51.6% of the imager waves present strong attenuation (overdamped waves) in contrast with 9% of lidar waves. The general saturated or damped behavior is consistent with diffusive filtering processes imposing limits to amplitude growth rates of the observed gravity waves.

Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2)

Abstract. During the second Wind Forecast Improvement Project (WFIP2; October 2015–March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR – 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST – 750 m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80 m wind speeds (wind turbine hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and three profiling lidars for comparison. Improvements due to the experimental physics (EXP vs. CNT runs) and those due to finer horizontal grid spacing (HRRRNEST vs. HRRR) and the combination of the two are compared, using standard bulk statistics such as mean absolute error (MAE) and mean bias error (bias). On average, the HRRR 80 m wind speed MAE is reduced by 3 %–4 % due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5 % on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80 m wind speed MAE, up to 7 %–8 %. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena. Causes of model weaknesses are identified. Finally, bias correction methods are applied to the 80 m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors.

Validation of the Water Vapor Profiles of the Raman Lidar at the Maïdo Observatory (Reunion Island) Calibrated with Global Navigation Satellite System Integrated Water Vapor

The Maïdo high-altitude observatory located in Reunion Island (21 ∘ S, 55.5 ∘ E) is equipped with the Lidar1200, an innovative Raman lidar designed to measure the water vapor mixing ratio in the troposphere and the lower stratosphere, to perform long-term survey and processes studies in the vicinity of the tropopause. The calibration methodology is based on a GNSS (Global Navigation Satellite System) IWV (Integrated Water Vapor) dataset. The lidar water vapor measurements from November 2013 to October 2015 have been calibrated according to this methodology and used to evaluate the performance of the lidar. The 2-year operation shows that the calibration uncertainty using the GNSS technique is in good agreement with the calibration derived using radiosondes. During the MORGANE (Maïdo ObservatoRy Gaz and Aerosols NDACC Experiment) campaign (Reunion Island, May 2015), CFH (Cryogenic Frost point Hygrometer) radiosonde and Raman lidar profiles are compared and show good agreement up to 22 km asl; no significant biases are detected and mean differences are smaller than 9% up to 22 km asl.

From small-scale forest structure to Amazon-wide carbon estimates

Tropical forests play an important role in the global carbon cycle. High-resolution remote sensing techniques, e.g., spaceborne lidar, can measure complex tropical forest structures, but it remains a challenge how to interpret such information for the assessment of forest biomass and productivity. Here, we develop an approach to estimate basal area, aboveground biomass and productivity within Amazonia by matching 770,000 GLAS lidar (ICESat) profiles with forest simulations considering spatial heterogeneous environmental and ecological conditions. This allows for deriving frequency distributions of key forest attributes for the entire Amazon. This detailed interpretation of remote sensing data improves estimates of forest attributes by 20–43% as compared to (conventional) estimates using mean canopy height. The inclusion of forest modeling has a high potential to close a missing link between remote sensing measurements and the 3D structure of forests, and may thereby improve continent-wide estimates of biomass and productivity.

Numerical and statistical modeling based investigation of the detection efficiency of high-spectral-resolution lidars at different laser radiation wavelengths

In the present work, a numerical and statistical modeling approach is developed for estimating the operation efficiency of high-spectral-resolution lidars (HSRLs), when determining the atmospheric aerosol extinction profiles along the lidar line of sight (LOS) at different sensing (laser) radiation wavelengths from the UV, VIS and NIR spectral ranges. The efficiency estimation is based on numerical modeling of the lidar signal profile along the LOS and the corresponding profile of the signal-to-noise ratio (SNR) of its measurement. The optimally efficient wavelength (at certain distances along the LOS) is that ensuring maximum signal strength and SNR and, consequently, brighter and clearer lidar images of specific aerosol objects and background. The results about the optimum wavelengths obtained under different atmospheric-turbidity conditions (clear or hazy atmosphere), in the presence of cirrus clouds, are proved by statistical modeling and processing of realistic (noisy) lidar profiles and recovering the atmospheric extinction profiles along the LOS. It is shown that up to certain characteristic altitudes (that are lower at higher turbidity) the UV wavelengths are advantageous in the above sense. Above the mentioned altitudes, successively, first the VIS and then the NIR wavelengths become more efficient compared to the UV wavelengths.

Modeling the performance of a diode laser-based (DLB) micro-pulse differential absorption lidar (MPD) for temperature profiling in the lower troposphere.

Ground-based, network-deployable remote sensing instruments for thermodynamic profiling in the lower troposphere are needed by the atmospheric science research community. The recent development of a low-cost diode-laser-based (DLB) micro-pulse differential absorption lidar (DIAL) has begun to address the need for ground-based remote sensing instruments for water vapor profiling in the lower troposphere. Now, taking advantage of the broad spectral coverage of the DLB architecture, an enhancement to the water vapor micro-pulse DIAL (MPD) instrument is proposed to enable atmospheric temperature profiling. The new instrument is based on measuring a temperature-dependent oxygen (O2) absorption coefficient and using this to retrieve the range-resolved temperature profile. In this paper, a retrieval method is proposed based on the recently developed perturbative solution to the DIAL equation that takes into account the Doppler broadening of the molecularly backscattered signal. This perturbative solution relies on an ancillary high spectral resolution lidar (HSRL) measurement of the backscatter ratio. Data from an operational water vapor MPD combined with a DLB-HSRL were used to create an atmosphere model, from which return signals for the O2-MPD were generated. The perturbative retrieval was then applied to these data and a comparison of the retrieved temperature and the model temperature profile allowed the efficacy of retrieval to be evaluated. The results indicate that the temperature profile may be retrieved from a theoretical O2-MPD instrument with a ±1K accuracy up to 2.5 km and ±3 K accuracy up to 4.5 km with a 150 m range resolution and 30-minute averaging time. Using data from a recently developed O2-MPD in combination with a WV-MPD, and a DLB-HSRL, an initial temperature retrieval is demonstrated. The results of this initial demonstration are consistent with the performance modeling.

Exploring the Feasibility of Using Commercially Available Vertically Pointing Wind Profiling Lidars to Acquire Thunderstorm Wind Profiles

While multiple types of remote sensing instruments have been used to investigate wind profiles associated with thunderstorms, the use of profiling Lidars (LIght Detection And Ranging) has been mostly limited to the wind energy sector. Using data from a wind energy company, this study explores the feasibility of profiling lidar data to obtain low-level (<150 m) wind profile information in and near thunderstorms. Two case studies were analyzed in which strong thunderstorms passed over the lidar while the remote sensor was operational and collecting wind speed, wind direction, and vertical velocity profiles at sub-minute resolution. Wind time histories at different levels of the wind profiles revealed that the lidar was able to collect data through the entirety of each event. The time histories also displayed a very typical thunderstorm outflow wind structure that has frequently been observed with in situ anemometry and radar remote sensing. As expected, vertical velocity data were mostly negative (indicating downdraft) during both events and exceeded – 6 m s-1 in one event. A comparison of the lidar data with in situ sonic and cup anemometers was also performed. While only 10-minute anemometer data were available, the limited comparison suggested a high degree of similarity in the mean sense, but standard deviations associated with the 10-minute lidar data were much lower than those of the anemometer data. Though this latter result was not entirely unexpected, it serves to demonstrate some of the issues that should be addressed prior to using profiling lidars in thunderstorms.

A comparison of micrometeorological methods for marine roughness estimation at a coastal area

Marine roughness length z0 is an essential parameter for the parameterization of momentum flux exchanges at sea-atmosphere interface. This paper aims to examine the performance of four widely adopted micrometeorological methods and four direct modeling methods, for estimating marine surface roughness at a coastal area. Comparative analyses are carried out based on four-year measurements from an offshore platform that was equipped with LiDAR profiler, meteorological mast and other hydrologic measurement devices. The analyzed results show that the marine roughness length scales estimated via the profile method and the gust-factor method are unrealistically small, generally one or two orders of magnitude smaller than those predicted via the direct modeling methods. By contrast, both the speed-variance and direction-variance methods can provide more reasonable estimation results that compares favorably with those predicted by the direct modeling methods. It is also observed from the results that the features of waves in this shallow-water area differ from those at deep waters, including the independence of significant wave period upon wind speed and the less correlation between wave and wind directions. Based on the collected wave records, a modified empirical model of marine roughness is presented.