【正文】 它一天兩次每小時(shí)對(duì)結(jié)冰的預(yù)測(cè)而到第21小時(shí)的時(shí)候，創(chuàng)建預(yù)測(cè)數(shù)值。四個(gè)不同的情況的分類，取決于不同類型的形成過程。它的目的是檢測(cè)和預(yù)測(cè)該地區(qū)的超級(jí)冷卻液體(SLD)和可能的結(jié)冰地區(qū)分別對(duì)飛機(jī)構(gòu)成的威脅。綜上所述，其派生的分析可以被壓縮到WWO示意圖，在圖1的右邊顯示作為一個(gè)黃色條狀。 我們的目的，一個(gè)冬天的天氣對(duì)象(WWO)在一個(gè)特定的有限區(qū)域，如機(jī)場(chǎng)或一個(gè)密集的高速公路網(wǎng)絡(luò)，可以定義通過以下參數(shù)來觀察:一個(gè)由幾層組成的垂直的大氣層發(fā)生時(shí)間持續(xù)時(shí)間下一次發(fā)生時(shí)間級(jí)別的描述，如：然而，為了緩解寒冷的天氣條件的影響，使得機(jī)場(chǎng)運(yùn)作更有效率,其系統(tǒng)建設(shè)的重點(diǎn)應(yīng)該放在短期預(yù)測(cè)(稱為“短時(shí)預(yù)測(cè)”)這個(gè)方面。冬天的天氣條件下一個(gè)人可以依靠操作數(shù)值預(yù)報(bào)模型，預(yù)測(cè)未來24小時(shí)或以上的天氣環(huán)境。交通參與者和交通管理中心在合適的時(shí)間預(yù)計(jì)不利條件通知大眾，為之作出明確的政策和準(zhǔn)確的氣象信息是必要的。道路交通尤其被不利的天氣如雪、冰、霧、雨、大風(fēng)所耽誤和影響。r Meteorologie und Geodynamik, Vienna, Austria, 60 pp. [Available online at ][2] Janjic, Z. I. and J. P. Gerrtty, 2001: An alternative approach to nonhydrostatic modelling. Mon. Wea. Rev., 129, 11641178.[3] Leifeld, C., 2004: Weiterentwicklung des Nowcastingsystems ADWICE zur Erkennung vereisungsgef228。 elevation angle are generated with SMC’s CDV operational Cband radar. The algorithm takes instantaneous scans corresponding to the forecast time (., 1 hour forecast) with 176。C based on NWP model outputs and observation? Volumetric radar reflectivity observation? Snow depth measurement ? Soundings from radiosonde and aircraft measurements or/and numerical weather prediction 2012, Helsinki, 2325 May 2012 5The Potential Snow Fall Area (PSA) algorithm is based on realtime hourly operational data, like regional model surface temperature, precipitation posite estimated from lowlevel radar scans, and surface observations. This allows that the output, a warning in terms of PSA, can be generated in realtime and at lowcost. Also, the output can be used in building more plicated algorithms of winter weather warnings based on various other sources (., the ADWICE introduced in the previous section). Data sourcesThe algorithm is constructed with data available over Catalu241。r Luft und Raumfahrt, Oberpfaffenhofen, Germany。2Hydrometeorological Innovate Solutions ., Barcelona, SpainEmail: ABSTRACTRecent developments are reported on techniques to determine the onset, duration, amount and type of precipitation as well as the snow and icing conditions at the surface. The algorithms, still under development, will be used to forecast the weather in short to medium lead times, . for the next 30 minutes up to a few hours (“nowcasting”). An algorithm aims at detecting potential areas of snow fall by bining reflectivity data of precipitation and surface temperature data from a numerical model as well as surface stations in high spatial resolution. Another approach bines profiling measurements with numerical weather forecast products. (., meteo data measured by aircraft and polarimetric radar data)Keywords: type and amount of precipitation, nowcast, anticipating the weather 1 INTRODUCTIONWeather phenomena contribute to congestions, accidents and delays in all traffic modes. The road traffic in particular is derogate by adverse weather like snow, ice, fog, rain, strong wind and wind gusts. Increasing traffic makes transportation even more vulnerable to adverse weather conditions. Today stakeholders and participants in transportation (be it airborne or groundbased) most of the time only react on adverse weather when the disruption has already happened or is just about to happen. Future road management systems should proactively anticipate disruptive weather elements and their time scales of minutes to days well in advance to avoid or to mitigate the impact upon the traffic flow. But “weather” is not a technical problem that can be simply solved. Predicting the weather is a difficult and plex task and only possible within certain limits. It is therefore necessary to observe and forecast the changing state of the atmosphere as precisely and as rapidly as possible. Moreover, measures are required that translate “weather” to “impact” and minimise those impacts on traffic flow and its management. To inform traffic participants and traffic management centres in due time on (expected) adverse conditions, tailored and accurate meteorological information is required on short notice. This information must be integrated in the process of information distribution and decision making to allow for tactical as well as strategic decisions. The Institute of Atmospheric Physics of the Deutsches Zentrum f252。a including 1) terrain height from DEM, 2) temperature from model, surface station, soundings, and 3) radar reflectivity. The deployment of the observational sources is shown in Figure 4 overlaid on orography. More detail on each source is provided in the following points. Figure 4. Data available around Barcelona over orography: Crosses indicate the location of CDVRadar and Airport Barcelona. Similarly, large diamond for AEMET surface stations, small diamond for SMC surface stations, and triangles for soundings.Digital elevation model (DEM) data used here are from ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model1) which has a horizontal resolution of 1 arcsecond, both in longitude and in latitude. This highresolution terrain height is remapped with a grid spacing of 176。 grid spacing.Numerical weather prediction model: The model output for the surface is generated over the Iberian Peninsula by meteoblue AG, a private pany that runs NMM (Nonhydrostatic Mesoscale Model [2]) in 13km