The sensitivity of numerical forecasts to convective parameterization during the warm period and the use of lightning data as an indicator for convective occurrence

Mazarakis, N.; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Argiriou, Athanassios A.

doi:10.1016/j.atmosres.2009.03.002

Cited by 32 publications

(24 citation statements)

References 23 publications

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“…The calculation of the statistical scores (Table 1) revealed a decreasing trend of the Prob- ability of Detection (POD) with increasing rain threshold, with a POD of 0.42 for the highest precipitation amounts. This result is in agreement with the verification results of similar activities of high-resolution rain forecasts in the Mediterranean area [44][45][46]. On the other hand, the calculated False Alarm Ratio (FAR) was very low (lower than 0.17) for all rain thresholds, indicating that the model has no tendency to provide false alarms.…”

Section: Discussionsupporting

confidence: 79%

FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas

et al. 2016

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A web-based Decision Support System, named FLIRE DSS, for combined forest fire control and planning as well as flood risk management, has been developed and is presented in this paper. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of the web based DSS without the need of local installation of complex software and their maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in such a way plan its efficient elimination. Also, during dry periods, agencies can implement "what-if " scenarios for areas that are prone to fire and thus have available plans for forest fire management in case such scenarios occur. Flood services include flood maps and flood-related warnings and become available to relevant authorities for visualization and further analysis on a daily basis. When flood warnings are issued, relevant authorities may proceed to efficient evacuation planning for the areas that are likely to flood and thus save human lives. Real-time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real-time, and a high resolution weather forecast grid supports flood modeling as well as the development of "what-if " scenarios for the fire modeling. All these can be accessed by various computer sources including PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. All these methods and tools provide the end users with the necessary information to design an operational plan for the elimination of the fire events and the efficient management of the flood events in almost real time. Concluding, the FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility.

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Section: Discussionsupporting

confidence: 79%

FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas

et al. 2016

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“…With this data, a 2x2 contingency table (Martin et al, 2010) is then constructed for some precipitation thresholds. The values selected are those used by Bartzokas et al (2010) contingency tables generated, categorical statistical scores are computed in order to describe particular aspects of precipitation forecast performance (Mazarakis et al, 2009). The categorical statistics include the accuracy (AC), bias score (BIAS), probability of detection (POD), false alarm ratio (FAR), threat score (CSI) and the Heidke skill score (HSS).…”

Section: Verification Proceduresmentioning

confidence: 99%

Real-time weather forecasting in the Western Mediterranean Basin: An application of the RAMS model

Gómez

Caselles

Estrela

2014

Atmospheric Research

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Moreover, due to the physical complexity of the area of study, the model presents different degree of accuracy between coastal and inland stations. Precipitation has also been verified by means of yes/no contingency tables as well as scatter plots. These tables have been built using 4 specific thresholds that have permitted to compute some categorical statistics. From the results found, it is shown that the precipitation forecast in the area of study is in general over-predicted, but with marked differences between the seasons of the year. Finally, dividing the available data by season of the year, has permitted us to analyse differences in the observed patterns for the magnitudes mentioned above. These results have been used to better understand the behaviour of the RAMS model within the Valencia Region.

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“…In general, the implementation of the KF CPS during the warm period of the year over Greece suffers from small values of Frequency Bias (see Sect. 4.2 for the definition of Frequency Bias), especially for moderate and large amounts of rain (Mazarakis et al, 2009). To alleviate this effect, the coefficient (a) 0.5 (EASYTRIG1) and (b) 1.0 (EASYTRIG2) has been added to the left-hand side of the trigger function, forcing the scheme to be triggered more easily.…”

Section: Changes To the Trigger Function (Easytrig1 Easytrig2)mentioning

confidence: 99%

“…Other problems are the erroneous placement of the convective activity and the failure of the representation of propagating convection (Davis et al, 2003). In particular, the quantitative precipitation forecast (QPF) above the Greek peninsula mainly suffers from N. Mazarakis et al: Precipitation forecast sensitivity to modifications of Kain-Fritsch scheme the two aforementioned problems (Kotroni and Lagouvardos, 2004;Mazarakis et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Convection cannot be explicitly resolved at the resolution used by operational mesoscale models when the resolution is greater than 4 km, and thus it is parameterized using one of the various convective parameterization schemes (CPS). Many studies have shown that among the various CPS used in the numerical weather prediction (NWP), the KainFritsch (KF) scheme (Kain andFritsch, 1990, 1992) performs well in forecasts of convective systems (Kuo et al, 1996;Wang and Seaman, 1997;Lagouvardos, 2001, 2004;Ferrier, 2004;Mazarakis et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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The sensitivity of warm period precipitation forecasts to various modifications of the Kain-Fritsch Convective Parameterization scheme

Mazarakis

Kotroni

Lagouvardos

et al. 2011

Nat. Hazards Earth Syst. Sci.

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Abstract. The sensitivity of quantitative precipitation forecasts to various modifications of the Kain-Fritsch (KF) convective parameterization scheme (CPS) is examined for twenty selected cases characterized by intense convective activity and widespread precipitation over Greece, during the warm period of [2005][2006][2007]. The study is conducted using the MM5 model with a two nested domains strategy, with horizontal grid increments of 24 and 8 km, respectively. Five modifications to the KF CPS, each designed to test the sensitivity of the model to the convective scheme formulation, are discussed. The modifications include: (i) the maximization of the convective scheme precipitation efficiency, (ii) the change of the convective time step, (iii) the forcing of the convective scheme to produce more/less cloud material, (iv) changes to the trigger function and (v) the alteration of the vertical profile of updraft mass flux detrainment.The simulated precipitation from the 8-km grid is verified against raingauge measurements. Although skill scores vary widely among the cases and the precipitation thresholds, model results using the modifications of the convective scheme show improvements in 6-h precipitation totals compared to simulations generated using the unmodified convective scheme. In general, forcing the model to produce less cloud material improves the precipitation forecast for the moderate and high precipitation amounts, while the same modification and the change of the convective time step to 1 min has the same result for the high precipitation thresholds. The increase of convective time step to 15 min, the maximization of precipitation efficiency and the changes to the trigger function give similar results for medium and high precipitation. On the other hand, the forecast for the light Correspondence to: N. Mazarakis (nickmaz@meteo.noa.gr) precipitation is improved by forcing the model to produce more cloud material as well as by the alteration of the vertical profile of updraft mass flux detrainment.

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The sensitivity of numerical forecasts to convective parameterization during the warm period and the use of lightning data as an indicator for convective occurrence

Cited by 32 publications

References 23 publications

FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas

FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas

Real-time weather forecasting in the Western Mediterranean Basin: An application of the RAMS model

The sensitivity of warm period precipitation forecasts to various modifications of the Kain-Fritsch Convective Parameterization scheme

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