Wind wave prediction in the Caspian Sea

In this thesis, wind wave prediction and analysis in the Southern Caspian Sea are surveyed. Because of very much importance and application of this matter in reducing vital and financial damages or marine activities, such as monitoring marine pollution, designing marine structure, shipping, fishing, offshore industry, tourism and etc, gave attention by some marine activities. In this study are used the Caspian Sea topography data that are extracted from the Caspian Sea Hydrography map of Iran Armed Forces Geographical Organization and the I 0 meter wind field data that are extracted from the transmitted GTS synoptic data of regional centers to Forecasting Center of Iran Meteorological Organization for wave prediction and is used the 20012 wave are recorded by the oil company's buoy that was located at distance 28 Kilometers from Neka shore for wave analysis. The results of this research are as follows: - Because of disagreement between the prediction results of SMB method in the Caspian sea and wave data of the Anzali and Neka buoys. The SMB method isn't able to Predict wave characteristics in the Southern Caspian Sea. - Because of good relativity agreement between the WAM model output in the Caspian Sea and wave data of the Anzali buoy. The WAM model is able to predict wave characteristics in the southern Caspian Sea with high relativity accuracy. The extreme wave height distribution function for fitting to the Southern Caspian Sea wave data is obtained by determining free parameters of Poisson-Gumbel function through moment method. These parameters are as below: A=2.41, B=0.33. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by above function with the wave data of Neka buoy is about %35. The 100-year return value of the Southern Caspian Sea significant height wave is about 4.97 meter. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by statistical model of peak over threshold with the wave data of Neka buoy is about %2.28. The parametric relation for fitting to the Southern Caspian Sea frequency spectra is obtained by determining free parameters of the Strekalov, Massel and Krylov etal_ multipeak spectra through mathematical method. These parameters are as below: A = 2.9 B=26.26, C=0.0016 m=0.19 and n=3.69. The maximum relative error between calculated free parameters of the Southern Caspian Sea multipeak spectrum with the proposed free parameters of double-peaked spectrum by Massel and Strekalov on the experimental data from the Caspian Sea is about 36.1 % in spectrum energetic part and is about 74M% in spectrum high frequency part. The peak over threshold waverose of the Southern Caspian Sea shows that maximum occurrence probability of wave height is relevant to waves with 2-2.5 meters wave fhe error sources in the statistical analysis are mainly due to: l) the missing wave data in 2 years duration through battery discharge of Neka buoy. 2) the deportation %15 of significant height annual mean in single year than long period average value that is caused by lack of adequate measurement on oceanic waves, and the error sources in the spectral analysis are mainly due to above- mentioned items and low accurate of the proposed free parameters of double-peaked spectrum on the experimental data from the Caspian Sea.

Nassau grouper (Epinephelus striatus) spawning aggregations: hydroacoustic surveys and geostatistical analysis

With the near extinction of many spawning aggregations of large grouper and snapper throughout the Caribbean, Gulf of Mexico, and tropical Atlantic, we need to provide baselines for their conservation. Thus, there is a critical need to develop techniques for rapidly assessing the remaining known (and unknown) aggregations. To this end we used mobile hydroacoustic surveys to estimate the density, spatial extent, and total abundance of a Nassau grouper spawning aggregation at Little Cayman Island, Cayman Islands, BWI. Hydroacoustic estimates of abundance, density, and spatial extent were similar on two sampling occasions. The location and approximate spatial extent of the Nassau grouper spawning aggregation near the shelf-break was corroborated by diver visual observations. Hydroacoustic density estimates were, overall, three-times higher than the average density observed by divers; however, we note that in some instances diver-estimated densities in localized areas were similar to hydroacoustic density estimates. The resolution of the hydroacoustic transects and geostatistical interpolation may have resulted in over-estimates in fish abundance, but still provided reasonable estimates of total spatial extent of the aggregation. Limitations in bottom time for scuba and visibility resulted in poor coverage of the entire Nassau grouper aggregation and low estimates of abundance when compared to hydroacoustic estimates. Although the majority of fish in the aggregation were well off bottom, fish that were sometimes in close proximity to the seafloor were not detected by the hydroacoustic survey. We conclude that diver observations of fish spawning aggregations are critical to interpretations of hydroacoustic surveys, and that hydroacoustic surveys provide a more accurate estimate of overall fish abundance and spatial extent than diver observations. Thus, hydroacoustics is an emerging technology that, when coupled with diver observations, provides a comprehensive survey method for monitoring spawning aggregations of fish.

Analysis of four decades of high elevation climate data

Four decades of instrumented climate records at D1 on Niwot Ridge suggest that high elevation data are an important - and even unique - part of the full climate picture. High elevation data provide information on changing lapse rates as well as model verification for global warming, which is predicted to occur earliest in high latitudes and at high elevations. The D1 records show climatic trends that arguably support global warming, assuming that greater planetary wave amplitude is verification of warming. Lapse rates reflect conditions of air mass stability, atmospheric moisture, and could [sic] cover, which contribute to feedback processes involving temperature, precipitation, and snowpack. The D1 record show a period, 1981-1985, when the lapse rate increased significantly, and this change was not detected by other data.

Distribution of wave heights in Phitti Creek during southwest monsoon

A waverider buoy was deployed in Phitti Creek (24°33'N; 67°03'E) for wave measurements during April-July 1986. Using Tucker's method wave records were calculated in terms of significant wave height (Hs) and Maximum Wave Height (Hmax). For each parameter weekly mean and standard deviation values were also computed for statistical analysis. For Hs the lowest mean value of 0.8m and for Hmax the lowest mean value of 1.51m were observed in the fourth week of April whereas the highest mean value observed for Hs was 3.02m and for Hmax was 4.94m in the fourth week of June, 1986.