Luan van Đại học bách khoa HN mba
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Luan van Đại học bách khoa HN mba
APPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbasatellite sea-surface measurements (TMI) and measurements from towers on the ground.A.l. TMI DataThe Tropical Rainfall Measuring Mission (TRMM) satellite carries a microwave imager known as TMI. The TMI images have been processed by Remote Sensing Systems into maps of mean wind speed using algontlun Luan van Đại học bách khoa HN mbas that have been calibrated against ocean buoy measurements ■ The TMI data represent the most comprehensive and reliable source of near-surface wind mLuan van Đại học bách khoa HN mba
easurements in Southeast Asia' The TMI produces 10 meter sea-surface wind speed estimates using radar reflectances recorded by satellites passing overAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbaurements from ocean buoys and the Q-Scat scatterometer The Illis difference against buoys is reported to be 0.84 Ill 's, while against Q-Scat it is reported to be 0.64 ms. The mean bias is much smaller.The main drawback of the TMI data is its relatively coarse spatial resolution of 25 km. Since the Luan van Đại học bách khoa HN mbasensor calibration is not valid near land, this resolution means that no wind speed data are available within about 25-50 km of any shoreline.Map A-lLuan van Đại học bách khoa HN mba
compares the predicted mean wind speed over the ocean from the MesoMap system with 25 km resolution TMI data averaged over 1998-2000. There IS a markeAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbahern coast of Vietnam. This is a zone of convergence generated by the interaction of the mountains and the prevailing monsoon winds. The convergence triggers convection in which warm an rises and releases its moisture as ram. The winds in both maps are comparatively weak in the Gulf of Thailand and Luan van Đại học bách khoa HN mbashow a similar geographical distribution Moving up the coast of Vietnam, the wind pattern again appears similar, with both model and data indicating aLuan van Đại học bách khoa HN mba
zone of high wind 111 the Gulf of Tonkin.However. MesoMap places the zone ill the center of the gulf whereas the TMI data show it closer to Hainan IsAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbaecial sensor microwave imager. Journal of Geophysical Research 102(C4):8703-8718.•' The TMI wind speed measurements arc less prone to error than the more widely known Special Sensor Microwave Imager (SSM1) measurements mainly because of the lower frequency of the TNI signal (11 GHz) The ims eiTor of Luan van Đại học bách khoa HN mba the SSMI measurements when compared against buoy data is repotted to be 1.4 m s. about 70% higher than the TM1 rms error against buoys of 0.84 m’s.WiLuan van Đại học bách khoa HN mba
nd Energy Resource Atlas of Southeast AsiaA-57Figure A-l. Comparison of mean wind speeds observed by the TMI (y axis) with those piedicted by the MesoAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbahich is a scatterplot of model and observed winds for each TMI grid cell On average, the simulated wind speed is lowei than the observed wind speed by about 0.3 Ill's. or 5%. This discrepancy does not necessarily indicate a flaw in the model but could be due to the sampling error of the simulations Luan van Đại học bách khoa HN mbaor measurements. The standaid deviation of the biases is 0.54 m/s. or about 8%. while the r is 72%. It appears likely that some of the outlying errorsLuan van Đại học bách khoa HN mba
aie due to contamination of the TMI data by offshore islands. The presence of land within a gild cell invalidates the relationship between the wave rAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbaartment of Energy Development and Promotion (DEDP), the US Ail Force DATSAV3 data base, the Vietnam Institute of Meteorology and Hydrology (IMH). and the Electricity Generating Authority of Thailand (EGAT). The data sets are described below.DATSAV3. The DATSAV3 surface database contains observations Luan van Đại học bách khoa HN mba from about 10.000 meteorological stations worldwide. The periods of record are generally from 1973 to the pl esent with data from some stations datinLuan van Đại học bách khoa HN mba
g back to 1930. Most of the stations in the database, however, have reported infrequently or have observed for a limited time period. The observationsAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbapoint, cloud data, pressure, present weather, visibility, precipitation amount, and snow depth.There are nearly 95 DATSAV3 stations in Southeast Asia. The list was narrowed to 40 based on data availability and regional representation, rhe majority of the '10 sites in this study reported the weather Luan van Đại học bách khoa HN mbaconditions even 3-11OU1S and measured wind, nominally, al 10m above ground.One of the main draw back of the DATSAV3 stations arc that most are locatedLuan van Đại học bách khoa HN mba
in cities and towns where wind measurements may be severely affected by nearby buildings and trees. We visited several such stations in Thailand and APPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mba 15111 confirm the same m that country.In addition, a number of stations show a trend of declining wind speed over time, indicating that trees and buildings have arisen around the stations and increasingly blocked the wind. As an example, see the data summary for the Phu Lien, Vietnam, meteorologica Luan van Đại học bách khoa HN mbal station in Appendix B.DF.DP The Thailand Department of Energy Development and Promotion (DEDP) provided hourly wind speed and direction data from 18Luan van Đại học bách khoa HN mba
w ind monitoring stations located throughout Thailand. The anemometer height for these stations was 10111. The periods of record vary from a few montAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mba the DATSAV3 stations and can be expected to provide more representative wind measurements. Nevertheless the low tower height is problematic, as It is difficult to extrapolate accurately to heights of interest for wind energy. In addition, several DEDP stations we did not visit - most located ill th Luan van Đại học bách khoa HN mbae northern part of Thailand, which were among the fust to be installed - report extremely low wind speeds, raising the suspicion that the measurementsLuan van Đại học bách khoa HN mba
may be obstructed or for some other reason they are not representative. For example, the mean speeds at Nakhon Phanom. Chang Mai. Chiang Rai. and UttAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbar, reports a mean speed of 2.9 ms; and the meteorological station al Chiang Mai reports a mean speed of 3.1 m/s. These latter two measurements are more likely to be reliable indicators of the wind resource in the region than the others.F.CtAT. We obtained three years of apparently good-quality data Luan van Đại học bách khoa HN mbafor one tall tower in Thailand operated by 1ĨGA1. Located near Phuket on the western coast of the Malay Peninsula, die lower w as instrumented al threLuan van Đại học bách khoa HN mba
e heights, 36 m. 20 m. and 10 m. We regard Illis data set as the most reliable land surface measurement available to US.TA Iff. Another usetill point APPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mbait this station, but the 1M11 indicated that the lower is located in fairly open cropland, with few trees, several kilometers from the coast. Unfortunately only 1 months of data spread over a single year were available, and only one level of measurement.Discussion The chart in Figure A.2 compares rh Luan van Đại học bách khoa HN mbae predicted and measured wind speeds at a sample of the stations. For rhe bulk of the stations, the recorded speed is well below that predicted by theLuan van Đại học bách khoa HN mba
model. However, the most reliable station. Phuket (EG AT), IS 111 goodWind Energy Resource Atlas of Southeast AsiaA-59Comparison With Surface MeasureAPPENDIX A. COMPARISONS W ITH SURFACE DATAA variety of surface wind data sets were evaluated for this project. They are divided into two categories: s Luan van Đại học bách khoa HN mba and Phuket), most of the DEDP stations, two Thai met stations (Bangkok and Chiang Mai), and five Vietnam met stations (Phu Lien. Vinli. Dong Hoi. Da Nang, and Qui Nhoil).agreement with the model: the mean observed speed is 5.2 1U'$ (at 36 m height), whereas MesoMap predicts 5.4 ms. Other measuremen Luan van Đại học bách khoa HN mbats that are reasonably consistent with the model are ill particularly well exposed locations, e.g.. Qui Nhon (tall tower). Bangkok and Chiang Mai airpLuan van Đại học bách khoa HN mba
orts. Prachuap Khiri Kan and Nakhon Si Thammarat DEDP stations along the eastern Malay coast., and Nonh Kai (DEDP) next to a reservoir.In most other cGọi ngay
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