The meteorological department of Bangladesh collects monthly wind speed data with the help of vertical axis cup type anemometers at 20 m height. These wind data for different stations were taken manually form the logbook, and monthly and yearly average speeds were computed for all the stations. Then these data and wind data from different sources were compared, analyzed and a new data set is prepared for making corrections with the logarithmic law; and these corrected data were used in mapping of wind velocity. The wind velocity for different stations are not same due to geographical situation, surface level, crisscrossing land by hundred of rivers, flooding, various crop cultivation and plantation with respect of soil fertility etc; which has several effects on climate. The climate of Bangladesh has two major seasonal variations: mild winter and hot-humid summer. The dry-winter season lasts for about 5 months (November-March) and gentle northeasterly land breeze blows over the terrain during this period. The summer spans from April to October with frequent small-scale storms occurring almost every day. Monsoon rains cause a large quantity of precipitation at June-October. Strong southwesterly sea breeze blows over the land during the summer season.Wind has primary, secondary and tertiary classes of origin (Manwell et al. 2002). The primary origin is accounted for pressure differences across the earth's surface, gravitational forces, inertia of the air, the earth's rotation and friction with the surface. ln a simpler form, four atmospheric forces: pressure force, Coriolis force, inertial force and frictional forces determine global perspective of wind motion. Secondary sources of wind include hurricanes, monsoon circulation, and cyclones. Thirdly, diurnal variations, thunderstorms, tornadoes etc. determine short-term, small-scale wind variations. The Tropic of Cancer passes through the middle of Bangladesh and the terrain is subjected to the northeast trade winds (primary origin). During the summer, wind blows from the southwest direction bringing moisture from the Bay of Bengal and causing significant monsoon effect throughout the country (secondary origin). Tropical cyclones are also common at the beginning of the summer season. All the studies such as Wind Energy Study (WEST), Solar and Wind Energy Resource Assessment (SWERA) and Technical Expertise for Renewable Application OERNA) show that, wind speed is generally lower in the winter and higher in thd summer. Wind also exhibits a diurnal cycle, generally having a peak at noon and a dip at evening (tertiary origin).The first steps for harnessing energy from the wind is to make extensive assessment of wind energy potential and cost analysis for a site of interest. A suitable location could then be identifled from several candidate sites. All of these analyses need a reliable and accurate wind map. However, when data is inadequate or inaccurate several other alternatives could also be explored (Landberg et al. 2003). A microscale wind map considers the effects of near-by obstacle, terrain roughness, orography and thermal flow with a scale of 1-10 km. On the other hand, a mesoscale map has a grid size of the order of 10-100 km (Petersen et al. 1997). Large-scale climatological data is regionalized in order to develope meso-map, where, local effects defined above are not considered. Various software tools, such as WASP, KAMM could be used to model high-resolution wind resource maps. Wind energy mapping requires local knowledge, regional surface measurements, global climatological databases, computational fluid dynamies (CFD) analysis, and correlation analysis. (Landberg et al. 2003). ln this paper two aspects (global database and surface measurement correlation) are considered for generating a wind map that essentially incorporates microscale features embedded in a mesoscale map. Bangladesh Meteorological Department had been collecting wind speed data for a long period (1961 onward) from many weather stations spread throughout the country. But these were usually meant for weather forecasting and were unsuitable for wind energy assessment purposes owing to three major reasons. Firstly, measurement tower height was too low (5-10 m), whereas wind turbines generally had higher hub heights (10-30 m). Secondly, obstacles such as, near-by buildings, houses and plantation, surround much weather stations. Thirdly, data recording mechanisms in many stations were not automated and were subject to erroneous processing. However, since these were averaged over a very long period (more than 30 years), use of these data with proper adjustments for elevation and terrain conditions are still worth consideration. Wind data measured in a place surrounded by near-by obstacles such as hills, tall trees, house etc. were characterized by lower magnitude, higher turbulence and lower power concentration.The Climate Diagnoslic Center (CDC) derived NCEP reanalysis based wind model for Bangladesh, and considered a suitable map compared with other global data based models. However, it also needs some height and terrain modifications to take into account for the land profile and elevations attributed to Bangladesh. The plot of CDC derived NCEp reanalysis was gridded into a 13 x 13 matrix (with 169 data ooints representing 0:50 x 0:50 resolution). Then the power law (Eq.2) was used to modify the modelto elevate it to 30 m. Necessary height adjustments were introduced to the gridded data for the hillf districts in the southeast and eroded highlands in the north. The value of the power law exponent o, for most parts of the country was found to be 0.15 when Eq. (3) is used with land profile index of 4.5 (Zo = 0.07 m, equivalent to cropland with occasional trees).