scholarly journals Comment on ``The heavy precipitation event of 14–15 October 2018 in the Aude catchment: A meteorological study based on operational numerical weather prediction systems and standard and personal observations´´

2020 ◽  
Author(s):  
Anonymous
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Precipitation Event ◽  
Heavy Precipitation Event ◽  
Numerical Weather ◽  
Prediction Systems

scholarly journals The heavy precipitation event of 14–15 October 2018 in the Aude catchment: a meteorological study based on operational numerical weather prediction systems and standard and personal observations

2021 ◽  
Vol 21 (3) ◽  
pp. 1135-1157
Author(s):  
Olivier Caumont ◽  
Marc Mandement ◽  
François Bouttier ◽  
Judith Eeckman ◽  
Cindy Lebeaupin Brossier ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Precipitation Event ◽  
Synoptic Situation ◽  
Heavy Precipitation Event ◽  
Cold Air ◽  
Numerical Weather ◽  
Prediction Systems

Abstract. The case of the heavy precipitation event on 14 and 15 October 2018 which has led to severe flash flooding in the Aude watershed in south-western France is studied from a meteorological point of view using deterministic and probabilistic numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. This case features typical characteristics of Mediterranean heavy precipitation events such as its classic synoptic situation and its quasi-stationary convective precipitation that regenerates continuously, as well as some peculiarities such as the presence of a former hurricane and a pre-existing cold air mass close to the ground. Mediterranean Sea surface temperature and soil moisture anomalies are briefly reviewed, as they are known to play a role in this type of hydrometeorological events. A study of rainfall forecasts shows that the event had limited predictability, in particular given the small size of the watersheds involved. It is shown that the stationarity of precipitation, whose estimation benefits from data from personal stations, is linked to the presence near the ground of a trough and a strong potential virtual temperature gradient, the stationarity of both of which is highlighted by a combination of observations from standard and personal stations. The forecast that comes closest to the rainfall observations contains the warmest, wettest, and fastest low-level jet and also simulates near the ground a trough and a marked boundary between cold air in the west and warm air in the east, both of which are stationary.

scholarly journals The heavy precipitation event of 14–15 October 2018 in the Aude catchment: A meteorological study based on operational numerical weather prediction systems and standard and personal observations

2020 ◽  
Author(s):  
Olivier Caumont ◽  
Marc Mandement ◽  
François Bouttier ◽  
Judith Eeckman ◽  
Cindy Lebeaupin Brossier ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Precipitation Event ◽  
Synoptic Situation ◽  
Heavy Precipitation Event ◽  
Cold Air ◽  
Numerical Weather ◽  
Prediction Systems

Abstract. The case of the heavy precipitation event on 14 and 15 October 2018 which has led to severe flash flooding in the Aude watershed in south-western France is studied from a meteorological point of view using deterministic and probabilistic numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. This case is typical of Mediterranean heavy precipitation events due to its classic synoptic situation and its quasi-stationary convective precipitation that regenerates continuously, but with some peculiarities such as the presence of a former hurricane and a pre-existing cold air mass close to the ground. It is shown that the positive Mediterranean sea surface temperature anomaly may have played an aggravating role in the amount of precipitation that poured into the Aude basin. On the other hand, soil moisture does not seem to have played a significant role. A study of rainfall forecasts shows that the event had limited predictability, in particular given the small size of the watersheds involved. It is shown that the stationarity of precipitation, whose estimation benefits from data from personal stations, is linked to the presence near the ground of a trough and a strong potential virtual temperature gradient, the stationarity of both of which is highlighted by a combination of observations from standard and personal stations. The forecast that comes closest to the rainfall observations contains the warmest, wettest and fastest low-level jet and also simulates near the ground a trough and a marked boundary between cold air in the west and warm air in the east, both of which are stationary.

scholarly journals Short-Range Numerical Weather Prediction of Extreme Precipitation Events Using Enhanced Surface Data Assimilation

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 587
Author(s):  
Magnus Lindskog ◽  
Tomas Landelius
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Short Range ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Numerical Weather ◽  
Extreme Precipitation Events ◽  
Surface Data ◽  
Enhanced Surface ◽  
Precipitation Events

A limited-area kilometre scale numerical weather prediction system is applied to evaluate the effect of refined surface data assimilation on short-range heavy precipitation forecasts. The refinements include a spatially dependent background error representation, use of a flow-dependent data assimilation technique, and use of data from a satellite-based scatterometer instrument. The effect of the enhancements on short-term prediction of intense precipitation events is confirmed through a number of case studies. Verification scores and subjective evaluation of one particular case points at a clear impact of the enhanced surface data assimilation on short-range heavy precipitation forecasts and suggest that it also tends to slightly improve them. Although this is not strictly statistically demonstrated, it is consistent with the expectation that a better surface state should improve rainfall forecasts.

scholarly journals A Diagram Depicting Forecast Skill and Predictability

1984 ◽  
Vol 65 (7) ◽  
pp. 701-703 ◽  
Author(s):  
Richard A. Anthes ◽  
David P. Baumhefner
Keyword(s):  
Numerical Weather Prediction ◽  
Numerical Models ◽  
Weather Prediction ◽  
Current Level ◽  
Forecast Skill ◽  
Numerical Weather ◽  
Prediction Systems ◽  
Atmospheric Phenomena

In operational numerical weather prediction systems, both observations and numerical models contribute to the skill of the forecast. A simple diagram representing the relative contributions of observations and models to the current level of forecast skill and to the ultimate predictability of atmospheric phenomena is interpreted in this note. The forecast skill of 500 mb heights and an estimate of the ultimate predictability of this variable are used in a quantitative illustration of the diagram.

scholarly journals Processing and quality control with FY-3C/GNOS data used in numerical weather prediction applications

2018 ◽  
Author(s):  
Mi Liao ◽  
Sean Healy ◽  
Peng Zhang
Keyword(s):  
Quality Control ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Noise Estimate ◽  
Ionosphere Model ◽  
Angle Space ◽  
Prediction Systems ◽  
L1 And L2

Abstract. The Chinese radio occultation sounder GNOS (Global Navigation Occultation Sounder) is on the FY-3C satellite, which was launched on September 23, 2013. Currently, GNOS data is transmitted via the Global Telecommunications System (GTS) providing 450–500 profiles per day for numerical weather prediction applications. This paper describes the processing for the GNOS profiles with large biases, related to L2 signal degradation. A new extrapolation procedure in bending angle space corrects the L2 bending angles, using a thin ionosphere model, and the fitting relationship between L1 and L2. We apply the approach to improve the L2 extrapolation of GNOS. The new method can effectively eliminate about 90 % of the large departures. In addition to the procedure for the L2 degradation, this paper also describes our quality control (QC) for FY-3C/GNOS. A noise estimate for the new L2 extrapolation can be used as a QC parameter to evaluate the performance of the extrapolation. Mean phase delays of L1 and L2 in the tangent height interval of 60 to 80 km are analysed and applied in the QC as well. A statistical comparison between GNOS and ECMWF (European Centre for Medium-Range Weather Forecasts) forecast data demonstrates that GNOS performs almost as well as GRAS, especially in the core region from around 10 to 35 km. The GNOS data with the new L2 extrapolation is suitable for assimilation into numerical weather prediction systems.

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