scholarly journals Verification of precipitation forecasts by the DWD limited area model LME over Cyprus

2007 ◽  
Vol 10 ◽  
pp. 133-138 ◽  
Author(s):  
K. Savvidou ◽  
S. C. Michaelides ◽  
A. Orphanou ◽  
P. Constantinides ◽  
J.-P. Schulz ◽  
...  
Keyword(s):  
Precipitation Amount ◽  
Probability Of Detection ◽  
Local Network ◽  
Precipitation Event ◽  
Limited Area ◽  
Monthly Precipitation ◽  
Limited Area Model ◽  
Area Model ◽  
Rain Gauges ◽  
Verification Model

Abstract. A comparison is made between the precipitation forecasts by the non-hydrostatic limited area model LME of the German Weather Service (DWD) and observations from a network of rain gauges in Cyprus. This is a first attempt to carry out a preliminary verification and evaluation of the LME precipitation forecasts over the area of Cyprus. For the verification, model forecasts and observations were used covering an eleven month period, from 1/2/2005 till 31/12/2005. The observations were made by three Automatic Weather Observing Systems (AWOS) located at Larnaka and Paphos airports and at Athalassa synoptic station, as well as at 6, 6 and 8 rain gauges within a radius of about 30 km around these stations, respectively. The observations were compared with the model outputs, separately for each of the three forecast days. The "probability of detection" (POD) of a precipitation event and the "false alarm rate" (FAR) were calculated. From the selected cases of the forecast precipitation events, the average forecast precipitation amounts in the area around the three stations were compared with the measured ones. An attempt was also made to evaluate the model's skill in predicting the spatial distribution of precipitation and, in this respect, the geographical position of the maximum forecast precipitation amount was contrasted to the position of the corresponding observed maximum. Maps with monthly precipitation totals observed by a local network of 150 rain gauges were compared with the corresponding forecast precipitation maps.

27 Years of Regional Cooperation for Limited Area Modelling in Central Europe

2018 ◽  
Vol 99 (7) ◽  
pp. 1415-1432 ◽  
Author(s):  
Yong Wang ◽  
Martin Belluš ◽  
Andrea Ehrlich ◽  
Máté Mile ◽  
Neva Pristov ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Central Europe ◽  
Regional Cooperation ◽  
Weather Prediction ◽  
Ensemble Forecasting ◽  
Limited Area ◽  
Member States ◽  
Limited Area Model ◽  
Area Model ◽  
Common System

AbstractThis paper describes 27 years of scientific and operational achievement of Regional Cooperation for Limited Area Modelling in Central Europe (RC LACE), which is supported by the national (hydro-) meteorological services of Austria, Croatia, the Czech Republic, Hungary, Romania, Slovakia, and Slovenia. The principal objectives of RC LACE are to 1) develop and operate the state-of-the-art limited-area model and data assimilation system in the member states and 2) conduct joint scientific and technical research to improve the quality of the forecasts.In the last 27 years, RC LACE has contributed to the limited-area Aire Limitée Adaptation Dynamique Développement International (ALADIN) system in the areas of preprocessing of observations, data assimilation, model dynamics, physical parameterizations, mesoscale and convection-permitting ensemble forecasting, and verification. It has developed strong collaborations with numerical weather prediction (NWP) consortia ALADIN, the High Resolution Limited Area Model (HIRLAM) group, and the European Centre for Medium-Range Weather Forecasts (ECMWF). RC LACE member states exchange their national observations in real time and operate a common system that provides member states with the preprocessed observations for data assimilation and verification. RC LACE runs operationally a common mesoscale ensemble system, ALADIN–Limited Area Ensemble Forecasting (ALADIN-LAEF), over all of Europe for early warning of severe weather.RC LACE has established an extensive regional scientific and technical collaboration in the field of operational NWP for weather research, forecasting, and applications. Its 27 years of experience have demonstrated the value of regional cooperation among small- and medium-sized countries for success in the development of a modern forecasting system, knowledge transfer, and capacity building.

scholarly journals Intercomparison of snowfall estimates derived from the CloudSat Cloud Profiling Radar and the ground based weather radar network over Sweden

2015 ◽  
Vol 8 (8) ◽  
pp. 8157-8189
Author(s):  
L. Norin ◽  
A. Devasthale ◽  
T. S. L'Ecuyer ◽  
N. B. Wood ◽  
M. Smalley
Keyword(s):  
High Latitude ◽  
Precipitation Amount ◽  
Weather Radar ◽  
Probability Of Detection ◽  
Polar Regions ◽  
Rain Gauges ◽  
Radar Network ◽  
Skill Scores ◽  
Satellite Sensors ◽  
Observing Systems

Abstract. To be able to estimate snowfall accurately is important for both weather and climate applications. Ground-based weather radars and space-based satellite sensors are often used as viable alternatives to rain-gauges to estimate precipitation in this context. The Cloud Profiling Radar (CPR) onboard CloudSat is especially proving to be a useful tool to map snowfall globally, in part due to its high sensitivity to light precipitation and ability to provide near-global vertical structure. The importance of having snowfall estimates from CloudSat/CPR further increases in the high latitude regions as other ground-based observations become sparse and passive satellite sensors suffer from inherent limitations. Here we intercompared snowfall estimates from two observing systems, CloudSat and Swerad, the Swedish national weather radar network. Swerad offers one of the best calibrated data sets of precipitation amount at very high latitudes that are anchored to rain-gauges and that can be exploited to evaluate usefulness of CloudSat/CPR snowfall estimates in the polar regions. In total 7.2×105 matchups of CloudSat and Swerad over Sweden were inter-compared covering all but summer months (October to May) from 2008 to 2010. The intercomparison shows encouraging agreement between these two observing systems despite their different sensitivities and user applications. The best agreement is observed when CloudSat passes close to a Swerad station (46–82 km), when the observational conditions for both systems are comparable. Larger disagreements outside this range suggest that both platforms have difficulty with shallow snow but for different reasons. The correlation between Swerad and CloudSat degrades with increasing distance from the nearest Swerad station as Swerad's sensitivity decreases as a function of distance and Swerad also tends to overshoots low level precipitating systems further away from the station, leading to underestimation of snowfall rate and occasionally missing the precipitation altogether. Further investigations of various statistical metrics, such as the probability of detection, false alarm rate, hit rate, and the Hanssen–Kuipers skill scores, and the sensitivity of these metrics to snowfall rate and the distance from the radar station, were carried out. The results of these investigations highlight the strengths and the limitations of both observing systems at the lower and upper ends of snowfall distributions and the range of uncertainties that could be expected from these systems in the high latitude regions.

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