DESA1002 'Nine Quarter City' - <Jiajia Shi>

Dubrovnik is an old city on the Adriatic Sea coast in the extreme south of Croatia. It is one of the most prominent tourist resorts of the Mediterranean, a seaport and the center of the Dubrovnik-Neretva county. Its population was 43,770 in 2001. Dubrovnik is nicknamed "Pearl of the Adriatic" and is listed as a UNESCO World Heritage Site. Dubrovnik enjoys a pleasant Mediterranean climate that sees many sunny days, even during winter. Generally the winters are quite mild with average days fluctuating between 10°C (50°F) and 5°C (41°F), and minimal rainfall occuring on around half the days of the winter months. Summers are drier, with average temperatures hovering just below 30°C (86°F). My design starts here------such a beautiful place. The project is a primary school. It is not really big, but it has everything, like assembling hall, food court, basketball court------ Harmonious is the word to describe my design, students are able to walk everywhere in building thoroughly. it is a comfortable place for study

Improving the precipitation accumulation analysis using lightning measurements and different integration periods

The focus of this article is to improve the precipitation accumulation analysis, with special focus on the intense precipitation events. Two main objectives are addressed: (i) the assimilation of lightning observations together with radar and gauge measurements, and (ii) the analysis of the impact of different integration periods in the radar–gauge correction method. The article is a continuation of previous work by Gregow et al. (2013) in the same research field. <br><br> A new lightning data assimilation method has been implemented and validated within the Finnish Meteorological Institute – Local Analysis and Prediction System. Lightning data do improve the analysis when no radars are available, and even with radar data, lightning data have a positive impact on the results. <br><br> The radar–gauge assimilation method is highly dependent on statistical relationships between radar and gauges, when performing the correction to the precipitation accumulation field. Here, we investigate the usage of different time integration intervals: 1, 6, 12, 24 h and 7 days. This will change the amount of data used and affect the statistical calculation of the radar–gauge relations. Verification shows that the real-time analysis using the 1 h integration time length gives the best results

Precipitation accumulation analysis &ndash; assimilation of radar-gauge measurements and validation of different methods

We investigate the appropriateness of four different methods to produce precipitation accumulation fields using radar data alone or combined with precipitation gauge data. These methods were validated for high-latitude weather conditions of Finland. The reference method uses radar reflectivity only, while three assimilation methods are used to blend radar and surface observations together, namely the linear analysis regression, the Barnes objective analysis and a new method based on a combination of the regression and Barnes techniques (RandB). The Local Analysis and Prediction System (LAPS) is used as a platform to calculate the four different hourly accumulation products over a 6-month period covering summer 2011. The performance of each method is verified against both dependent and independent observations (i.e. observations that are or are not included, respectively, into the precipitation accumulation analysis). The newly developed RandB method performs best according to our results. Applying the regression or Barnes assimilation analysis separately still yields better results for the accumulation products compared to precipitation accumulation derived from radar data alone