Diagnostic tools using a mesoscale NWP model for the early warning of convection

Transcription

1 Meteorol. Appl. 5, (1998) Diagnostic tools using a mesoscale NWP model for the early warning of convection Véronique Ducrocq, Diane Tzanos and Stéphane Sénési, GAME/CNRM, Météo-France, Toulouse Cedex, France A mesoscale numerical weather prediction model and its associated diagnostics are evaluated to gauge their ability to forecast convection and the convective environment for ten case-study days. The diagnostic indices and parameters evaluated are those used to assess atmospheric instability, mesoscale forcing, inhibition and low-level moisture supply. In addition, bulk Richardson number and helicity diagnostics are examined for convection organisation. Convection over mountainous regions is not considered. The case-study days are grouped according to their synoptic type in order to evaluate the usefulness of the forecast diagnostics. In the evaluation it is found that by combining the CAPE (convective available potential energy) and low-level relative humidity diagnostics one can delineate quite large areas where convective triggering is possible and outside which convection will not develop. Organisation of the mesoscale convective systems is also considered. It is found that forecast strong lowlevel shears tend to be well correlated with observed linear convective systems. A set of stability indices are evaluated quantitatively and qualitatively by comparing the forecast stability indices with observations at a sounding location. CAPE and a simple index based on a moist temperature difference between two layers (Adedokun 2 ) are identified as the most useful forecast stability indices for all of the cases. 1. Introduction The process of forecasting deep convection can be divided into four steps (Conway et al., 1996): the early warning of convection, the forecasting of convective initiation, (c) the detecting and identifying of convection, and (d) the forecasting of convective evolution. The first step, the early warning of convection, consists in determining the areas where convection is possible during the next 3- to 12-hour period and also the type and intensity of convection expected. The second step is to forecast more precisely the time and location of convective developments up to 3 hours. Once the convection has initiated, the third step is for the forecaster to identify the type of convection and to forecast the evolution of the convective systems (i.e., movement, intensification or dissipation, associated severe weather, etc.) During the early warning phase, the forecaster attempts to assess the degree of potential instability as well as the possibility of forcing mechanisms. The information available to perform this task is derived primarily from soundings, hourly surface observations and output from numerical weather prediction (NWP) models, with model output providing the main source of information for longer lead times. With higher and higher horizontal spatial resolutions in many NWP models, some operational models are now capable of providing detailed information about the forcing at not only the synoptic scale but also the mesoscale. Moreover, successful forecasts of severe convective events have been performed with research versions of NWP mesoscale models in the USA (Zhang et al., 1989; Bélair et al., 1994) as well as in Europe (Ducrocq & Bougeault, 1995; Sénési et al., 1996). Ducrocq & Bougeault (1995), for example, succeeded in simulating qualitatively an observed squall line over south-western France. Research versions of mesoscale models, however, must be tuned in order to simulate convective events; this is generally not the case for operational mesoscale models, which typically fail to simulate convective events properly. Nonetheless, even if operational mesoscale models cannot forecast convective systems suitably, they can still provide forecasters with some pertinent information concerning convection and its development. The main problem that arises when trying to use operational mesoscale models for the early warning stage of convection is to determine the most reliable information (or diagnostics) the models can provide regarding convection and how best to exploit it. The aim of the present investigation is to determine the most beneficial diagnostics derived from a mesoscale model that can help forecasters in predicting convection. The investigation is accomplished through case studies. In the investigation, however, we do not consider convective systems that are influenced strongly 329

2 V Ducrocq, D Tzanos and S Sénési by orography. The mesoscale model employed is the French ARPEGE/Aladin limited area model, which has been running in a pre-operational mode at Météo- France since winter 1996 at a horizontal resolution of approximately 10 km. The diagnostics used for study and the forecast experiments are described in section 2. An evaluation of the diagnostics is then presented in the subsequent sections from differing points of view. In section 3 a qualitative analysis is carried out by examining synoptic situation types. In section 4 we compare the organisation and motion of the observed convective systems with some forecast environmental parameters. Finally, in section 5, we conduct a quantitative evaluation of the forecast stability indices at a sounding location. Concluding remarks follow in section Diagnostics and forecast experiments This section defines the NWP-based diagnostic parameters used in the study and is followed by a description of the forecast experiments. The acronyms used for the diagnostics are summarised in Table 1. Table 1. Meaning of the parameters used in the study Parameter Meaning CAPE Convective available potential energy of the most unstable parcel of the lowest 300 hpa MOCON Surface moisture flux convergence MOCONI Surface moisture flux convergence integrated over a low-level layer PW Precipitable water ADTHE Equivalent potential temperature advection CIN Convective inhibition energy R ig Bulk Richardson number [ V/ z ]5km Mean wind shear over the lowest 5 km: difference between the 0 5 km densityweighted mean wind and the densityweighted mean wind over the lowest 500 m [ V/ z ]2.5km Mean shear over the lowest 2.5 km: difference between the km densityweighted mean wind and the densityweighted mean wind over the lowest 500 m SREH Storm relative environmental helicity GR Grid resolved rainfall CR Rain amount produced by the convective parameterisation scheme 2.1. Diagnostics for the synoptic environment Although the synoptic environment was determined primarily by the large-scale coupling model, the positions of key elements, such as the jet stream, the major upper-level trough and the short-wave trough, needed to be assessed. No refined diagnostics, however, such as quasi-geostrophic diagnostics (see, for example, Kurz, ), were used for this study since our purpose was principally to determine how to use the mesoscale information provided by a mesoscale model. Consequently, only classical diagnostic tools used operationally by forecasters were examined Diagnostics for the mesoscale environment The major elements required for convective activity are some degree of potential instability, a moisture source and a lifting mechanism. Convective instability Measuring the stability of the atmosphere can be accomplished following different methods, and the diagnostics can be divided into three main classes: (i) stability indices, (ii) parameters derived by the Lagrangian parcel method, and (iii) static frequencies. Many stability indices can be found in the literature (e.g., total totals, Showalter index, lifted index, etc.), but most of these were designed during the early stages of sounding analysis and were therefore designed to be easy to compute from temperature and moisture at two pressure levels in the low and middle troposphere, respectively. The convective available potential energy or CAPE (Miller, 1967) provides a more accurate measure of the degree of instability than the classical stability indices. It is based on the Lagrangian parcel method that is used to identify conditional instability. In many applications, the lifted parcel originates at the ground. In our case, however, as advocated by Doswell & Rasmussen (1994), we take the most unstable parcel of the lower troposphere (typically in the lowest 300 hpa). This has the advantage of being appropriate for even nocturnal convection. The other parameters supplied by the parcel method, such as the equilibrium levels and the cloud depth, can also be informative. Consequently, the number of possible stability indices and parameters is large. For example, Sénési & Thepenier (1997), who performed a complete climatological study on the relevance of stability indices from a single observed sounding, listed no fewer than 69 possible stability indices and parameters. Among them, however, many were found to be redundant, and finally the authors retained only 15 stability indices for the main part of their climatological study. Since their study was valid for a sounding representative of northern France, and the present study considers convection mainly over northern and western France (i.e., outside mountainous regions), the same stability indices were used here (with the exception of three that depend on a forecast maximum temperature) to perform a quantitative evaluation at the same sounding location as in the Sénési & Thepenier (1997) study. As regards the indices fields, only a subset of the indices was computed at each model column. The set of stability indices is described in the Appendix. From another

3 NWP and the early warning of convection point of view, vertical cross-sections of moist static frequencies, since convective developments over mountainous areas are not considered. N may be useful in diagnosing layers of potential instability. Mesoscale lifting g qe g = or Nw = q z q 2 2 e e qw z Lifting that leads to the release of convective instability can originate from various sources: frontal lifting, convective outflow boundaries, orographic effects, and land sea breeze circulations. Forecast vertical velocity can be used to identify some mesoscale lifting compatible with the grid mesh size of the model. In addition, the moisture flux convergence provides a measure of the low-level lifting together with the degree of humidity of the lifted air. Moisture flux convergence can be assessed at the surface or averaged over a layer above the ground surface (e.g. Beckman, 1993). In the following, we refer to the surface moisture flux convergence as MOCON and define it as MOCON =-Ñ H ( rv) =-Ñ r H V-VÑ H r ( 1) where r is the vapour mixing ratio at 2 m, V is the wind vector at 10 m and MOCONI is the moisture flux convergence integrated over a low-level layer of depth dp above the ground pressure p s : MOCONI( dp) =- ps-dp The term dp ranges typically between 50 and 150 hpa. In most cases, the moisture advection part of the moisture flux convergence (second term on the right-hand side of equation (1)) is negligible compared with the mass convergence part (first term on the right-hand side of equation (1)). In a fashion similar to the work presented here, mesoscale analyses of hourly observations of 10 m winds and 2 m relative humidities of a mesonet are used to compute MOCON instead of using mesoscale NWP forecasts; the relevance of such a diagnostic for the nowcasting of the convective initiation has been evaluated (Calas et al., 1997). Hence, one advantage of using moisture flux convergence in place of vertical velocity to identify forecast low-level lifting is that a direct comparison between these mesoscale analyses of surface mesonet data is possible (such comparisons are not described in the present paper). Diagnostics designed to assess the orographic lifting are not presented here ò ps ps-dp ps w Ñ H ( rv) dlnp. ò dln P (c) Moisture Although some moisture information is contained in the above stability indices, it is interesting in some cases to appreciate solely the degree of humidity of the atmosphere. The degree of moisture of an atmospheric column can be estimated through precipitable water (PW), but we must also consider the vertical distribution of moisture and, in particular, search out the moist low tropospheric layers and dry middle tropospheric layers. These dry middle layers favour evaporation of falling precipitation which reinforces the downdraft intensity (see e.g. Ducrocq & Bougeault, 1995). (d) Other factors influencing the convection Other parameters are also known to have an effect on the intensity, type and evolution of convection. The warm and moist air supply in the lower levels, for instance, which can be estimated through a positive equivalent potential temperature advection (ADTHE = V.Ñ p q e ) can be investigated and compared with the evolution of convective systems. In particular, the maintenance of low-level moisture plays an important role in the case of quasi-stationary convective systems. A large amount of inhibition convective energy (CIN) can prohibit or delay the convective initiation in which case, as for thunderstorms, the convection may become more vigorous since the convective energy above the inversion has time to grow before the release of the instability. It can also help to focus the convection in preferential areas. (e) Convection type As for convection type, Weisman & Klemp (1982, 1984) have shown that supercells are favoured in their numerical simulations when the bulk Richardson number R ig ranges from 5 to 50, and multicell storms are favoured when R ig is greater than 35. The definition of R ig used here is: R ig CAPE = 2, [ V/ z] 2 5 km where the mean shear [ V/ z ]5km is computed as the difference between the 0Ð5 km density-weighted mean wind and the density-weighted mean wind over the lowest 500 m. As above, the parcel with the maximum energy is used to compute CAPE. The R ig values are not considered here when CAPE is smaller than 1000 J kg 1 or in mountainous areas (Weisman and Klemp s 331

4 V Ducrocq, D Tzanos and S Sénési results were established from simulations with CAPE values in the 1500Ð3000 J kg 1 range). Droegemeier et al. (1993) found for their numerical simulations of convective systems that the rotational characteristics and the structure of the convection are connected to the storm-relative environmental helicity (SREH) and the bulk Richardson number. Rotunno et al. (1988) demonstrated that long-lived squall lines are favoured by strong low-level shears. In addition to a wind hodograph, we can use a mean shear diagnostic to quantify low-level shear intensity, which can be computed as the difference between the 0Ð2500 m density-weighted mean wind and the density-weighted mean wind over the lowest 500 m (i.e. [ V/ z ]2.5km ) Diagnostics for convection Model precipitation output was used to assess how convective precipitation systems are forecast by the mesoscale model. Model precipitation consists of two terms: the grid-resolved rain (GR) and the rain amount supplied by the convective parameterisation scheme (CR). Occasionally, no rain is forecast in connection with the observed convective systems, but one can find a trace of simulated convection in the relative or specific humidity fields or in the vertical velocity fields at low and mid-levels Forecast experiments The ALADIN model is the limited-area version of the French global ARPEGE model, and consequently it is a spectral model that employs double Fourier series (see Bubnova et al., 1995, or Caian & Geleyn, 1997, for a complete description). All the simulations have a horizontal resolution on the co-location grid of about 10 km, with 27 hybrid vertical levels. Considering that the non-hydrostatic effects of a 10-km grid mesh are negligible, the hydrostatic version of the model was selected to perform the experiments. The physical package is the same as in the global ARPEGE model (Geleyn et al., 1994; Courtier et al., 1991) and includes, in particular, the Bougeault (1985) convective mass flux scheme for the deep convection. The initial conditions were provided by the ARPEGE analyses except for the cases in 1992 and 1993 for which the ECMWF analyses were used since ARPEGE was either not operational or had a lower resolution at the time. When convection developed before 1400 UTC (or after 1500 UTC), simulations starting at 0000 UTC (or at 1200 UTC) were used. When convection began between 1400 and 1500 UTC, simulations starting both at 0000 UTC and 1200 UTC were considered. The initial times of the simulations are given in Table 2. Lateral boundary conditions are updated every six hours. 332 Table 2. Initial time of forecast experiments and time of first convective develoment, grouped by synoptic types Initiation time Convective Synoptic of experiments initiation time type Date Case (UTC) (UTC) I 10 June July July July (exp. A) 1430 (system a) 1200 (exp. B) 1630 (system b) II 8 June July III 4 August (exp. A) (exp. B) 5 August (4 Aug.) August (exp. A) (exp. B) 20 August Assessments of diagnostic fields arranged by synoptic type 3.1. Method Simulations were performed and the diagnostics were applied to the model outputs for ten case-study days. The cases were selected by choosing events for which at least six ground stations had verified reports of both observed thunderstorm activity and daily rain above 5 mm. The synoptic situations of the ten selected cases were classified into three synoptic types. Synoptic type I (1 July 1994, 27 July 1994, 24 July 1994, 10 June 1992). Convection developed with synoptic forcing and in the vicinity of a wellmarked frontal system. The convection was either generated in the warm sector ahead of the cold front or embedded in the cloudy frontal system. Synoptic type II (8 June 1993, 17 July 1994). Convective storms formed on the cyclonic side of an upper-level cold low-pressure region without any associated surface front. (c) Synoptic type III (4 August 1994, 5 August 1994, 7 August 1994, 20 August 1995). Convective developments were strongly connected with diurnal heating and/or existing convective systems. For each case-study day, the first step in the evaluation was to verify that at the synoptic scale the key elements were forecast accurately by the model at the main synoptic hours (details of this work are not described here). Overall, it was found that the model s accuracy for all the cases was quite good at the synoptic scale. The evaluation of the forecast diagnostics for the forecast convection and mesoscale environment was performed for each case at two times, namely before and

5 NWP and the early warning of convection after any observed convective initiation. Table 2 lists the times of initial convective developments outside mountainous regions (the model orography is displayed in Figure 1). The structure and intensity of the fields of the forecast diagnostics (i.e. CAPE, Adedokun 2 index, cloud depth, energy index, modified total totals, MOCON, MOCONI, 850 hpa relative humidity, PW, CIN, ADTHE, GR, CR) before the observed convective initiation were systematically compared with the location of the observed convective development for all the cases. Then the evolution of these forecast diagnostic fields was compared with the evolution of the observed convective systems. It should be noted, however, that comparisons such as these after the observed convective initiation are difficult to make because in most cases the forecast and observed convection (and their feedback on the environment) differ. In the following analysis, we summarise the results of the forecast mesoscale environment and convection with regard to each synoptic type. In general, we do not report here the individual characteristics arising from the detailed studies performed for each case. The examination of the diagnostics in connection with the convective organisation is conducted in section Synoptic type I The places where convection was initiated with respect to the surface fronts are shown in Figures 2, 3, 4 and 5. CAPE and low-level relative humidity diagnosed from model output just prior to the observed convective initiation and superimposed with lightning data are shown in Figures 2, 3, 4 and Figure 1. Model orography (interval of 500 metres) and crosssection axes used in Figure 6. Latitude and longitude lines have a 2 spacing. 5. For all of these cases, the convection begins in areas where CAPE values indicate potential instability. CAPE values range from 500 J kg 1 (for 27 July 1994) to 2600 J kg 1 (for 24 July 1994) in the areas of convective development. Although large CAPE values and convective initiation can be located in the same regions, as is the case for the 24 July 1994 simulation, this is not always true. A combination of a low-level humidity field and an instability field enables one to delineate a little more precisely the areas of possible convective formation. For example, in the 1 July 1994 case (Figure 3), we can exclude convective development in southern France where we find large CAPE but weak lowlevel humidity, and in the 10 June 1992 case (Figure 2) in southwestern France where we find large lowlevel humidity but weak CAPE values. Except for the 10 June 1992 case, there is some lowlevel moisture convergence (not shown) in the vicinity of the frontal system, i.e., often at the surface cold front and ahead of it in the warm, moist air. For 10 June 1992, the observed convective systems are smaller than in the other cases, and this suggests that for this case, if some low-level forcing does exist, it may be at a scale too small for the mesoscale model to simulate. For the other cases, moisture convergence maxima and observed convective initiation are not necessarily located in the same places. For some of the cases, the simulation failed to represent low-level winds properly in the areas of convective development, and this may explain the mismatch between the observed convection location and the forecast low-level convergence. As an example, in the 1 July 1994 case, the observed sea breezes which induced low-level convergence in the convective initiation area are not simulated by the model. Forecast vertical velocity fields also exhibit some upward motion in the vicinity of the frontal systems. Vertical cross-sections of wet bulb potential temperature are useful for providing a better description of the frontal systems by identifying certain elements, such as the warm conveyor belt and ana- or kata-front surfaces. For all the cases analysed, convection developed in the warm and moist air ahead of the front, where low and middle levels are potentially unstable (Figure 6). In the 27 July 1994 case (Figure 6(d)), we have a kata-like front structure and the convection first developed where cold, dry air hung over warm, moist low-level air. This forecast structure agrees with the results of the Browning & Roberts (1994) study of satellite imagery for the same case. For the other cases, vertical crosssections tend to exhibit a more classic ana-front with convective initiation located just ahead of the moist, warm low-level axis which can be quite far from the surface cold front, as in the 24 July 1994 case (Figure 6(c)). The observations of the convection illustrate that convective systems move with the forecast frontal system 333

6 V Ducrocq, D Tzanos and S Sénési Figure 2. Synoptic type I for 10 June UTC analyses of geopotential (solid lines, L for low centre) and temperature (dashed lines) at 500 hpa with surface fronts; crosses mark the places where convection was initiated and the the panel used in ( b) is indicated by the rectangle. ( b) Forecast of CAPE (solid contours above 300 J kg 1, interval of 300 J kg 1 ) and 850 hpa relative humidity (grey scale in %) at 1000 UTC; cloud to ground flashes between 1100 and 1130 UTC are indicated by crosses. Figure 3. Synoptic type I for 1 July As Figure 2 but for 1200 UTC on 1 July. ( b) As Figure 2( b) but for 1100 UTC on 1 July and with cloud to ground flashes between 1200 and 1300 UTC. 334

7 NWP and the early warning of convection Figure 4. Synoptic type I for 24 July As Figure 2 but for 1200 UTC on 24 July. ( b) As Figure 2( b) but for 1100 UTC on 24 July and with cloud to ground flashes between 1200 and 1230 UTC. Figure 5. Synoptic type I for 27 July As in Figure 2 but for 1200 UTC on 27 July. ( b) As in Figure 2( b) but for 1400 UTC on 27 July (Exp. A) and with cloud to ground flashes between 1500 and 1530 UTC. 335

8 V Ducrocq, D Tzanos and S Sénési while remaining inside the warm, moist tongue. This enables one to anticipate the overall motion to a certain extent. For the cases of 10 June 1992 and 1 July 1994, the convection tends to develop and shift with a well marked area of positive q e advection (not shown). For the 27 July 1994 and 24 July 1994 cases, no significant q e advection is found in the convective development area. The forecast convection was depicted unevenly by the model. For instance, the forecast daily rain areas for 10 June 1992 and 24 July 1994 agree quite well with the observed rainy areas (not shown); however, the times and hourly totals disagree with the observations. Moreover, in the 1 July 1994 case, the forecast daily rain is located to the east of the observed rainy area. For the 27 July 1994 case, no precipitation is forecast, only mid-level upward motions are forecast in the area of the convective systems Synoptic type II Figures 7 and 8 show the location of the convective initiation with respect to the cold cut-off. For these two cases of synoptic type II the CAPE and low-level humidity just prior to the convective initiation are in Figures 7 and 8; note that the convective systems form in areas where CAPE is high ( >1500 J kg -1 ). As in the synoptic type I situation, low-level relative humidity combined with CAPE enables one to delineate areas of possible convection a little more accurately. Surface and vertically integrated (through the lowest 50 and 150 hpa) moisture convergence fields exhibit convergence zones at the convective initiation location (Figures 7(c), 8(c)). For 8 June 1993, strong convergence not situated at the same location as the observed convective developments was also forecast in southwestern France (Figure 7(c)), which may be explained by the western surface winds being forecast too far inland. The other main strong convergence zones and associated surface winds do agree with the observed surface winds; the convergence is produced mainly by sea land breezes. The line organisation of the low-level moisture convergence areas for 17 July 1994 is very similar to that in the observed convective system (Figure 8(c), 8(d)). Since the model succeeded in representing both potential convective instability and low-level moisture convergence in the observed convective area, the convective parameterisation produces convective rain in this area. For 17 July 1994, the time of first CR agrees with the first observed precipitation time. The CR evolution during the subsequent 4 hours is quite well depicted, including a line organisation of the rain (Figure 8(d)). After that, the forecast convective rainy system moves more slowly and dissipates more rapidly than the observed convective system. No convective downdraft 336 parameterisation in the model can explain the rapid dissipation of the forecast system, since we know that convective downdrafts play an important role in the production and maintenance of the cold pool, which is a key element in the mechanisms of convective systems. For the 8 June 1993 case, the model succeeded in simulating a rainy system over Brittany with a line organisation matching the radar observation (Figure 7(d)). Another convective rainy system is also forecast in south-western France, but its location does not agree with the observations, which is most likely due, as mentioned above, to the incorrectly forecast winds for this area Synoptic type III Convective initiation places for the four cases are shown in Figures 9, 10, 11 and 12. Convective developments occur in forecast areas of high convective instability for diurnal convective events, with CAPE values ranging from 1000 to 2000 J kg -1 (Figures 9, 11, 12) and in forecast areas of weak instability for the nocturnal convective case (5 August 1994, Figure 10). For the 7 August 1994 and 20 August 1995 cases, convection forms in a forecast zone of low-level relative humidity above 60% (Figures 11, 12). In the 4 August 1994 case, convection appears just ahead of a forecast moist pocket (Figure 9); observed convection forms ahead of an observed cloudy band. On the other hand, the observed convection for 5 August 1994 develops at the leading edge of a dissipating cloudy system for which the model fails to simulate the associated high humidity. With the exception of 4 August 1994, forecast moisture convergence is weak in the convective development area (not shown). In the 4 August 1994 case, a line of convergence is forecast but to the west of the observed convergence line. Only for 20 August 1995 are large positive values of ADTHE found (not shown). The model fails to produce any convective rain (not shown) in the observed rainy area for the 4 and 5 August 1994 cases; and for the 7 and 20 August 1995 cases, some CR is forecast in the observed rainy area but the pattern is not properly forecast. Information about the evolution of the convective systems can be found in the forecast fields. For instance, in the 20 August 1995 event and for the beginning of the 7 August 1994 case, the horizontal structures of the CAPE and low-level humidity fields evolve little, with a CAPE amount following a diurnal cycle. This agrees with the observed slow-moving convection, which is linked mainly to diurnal heating. After 2200 UTC on 7 August 1994, a part of the forecast large low-level humidity area moves eastwards, as does the observed convective system. For the 4 August 1994 event, the

9 NWP and the early warning of convection (c) (d) Figure 6. Vertical cross-sections of wet bulb potential temperature (thick solid lines, interval of 1 C) and of moist static frequency N w2 (positive values in thin solid lines, negative values in thin dashed lines, interval of s 2 ) for 1000 UTC on 10 June 1992, ( b) 1100 UTC on 1 July 1994, (c) 1100 UTC on 24 July 1994 and (d) 1400 UTC on 27 July The double arrows indicate the observed initiation location and the single arrow shows the motion direction of the surface cold front. The cross-section axes are shown in Figure 1; the cross-sections have longitude as the horizontal coordinate and pressure as the vertical coordinate. eastward motion of the observed convergence line can be inferred from the forecast convergence line General remarks From the qualitative evaluation of the diagnostics used to describe the mesoscale environment and convection, we can denote three classes of diagnostics. The first class of diagnostics was found to be applicable for all the cases investigated here. The second class was useful for only some of the cases, and a third class was not shown to be useful for the cases investigated here. Among the first class of diagnostics, we find diagnostics designed to assess the potential convective instabil- 337

10 V Ducrocq, D Tzanos and S Sénési (d) (c) Figure 7. Synoptic type II for 8 June As in Figure 2 but for 1200 UTC on 8 June. ( b) As Figure 2( b) but for 1300 UTC on 8 June and with cloud to ground flashes between 1400 and 1500 UTC. (c) Forecast of MOCON at 1300 UTC on 8 June (interval of s 1, solid lines for convergence, dashed lines for divergence); cloud to ground flashes between 1330 and 1500 UTC are represented by crosses. (d) Forecast of one-hour convective rain accumulation (isolines: 0.5, 1, 2 mm) between 1800 and 1900 UTC on 8 June superimposed with radar echoes at 1830 UTC in grey scale. 338 ity and the low-level moisture. Indeed, these diagnostics are useful to delineate areas of possible convective development. A single low-level humidity field like the 850 hpa level relative humidity was found to be informative. Averaged humidity over some low-level layers did not provide, for our cases, any more information than a single-level field. Precipitable water fields exhibited the same moist area as low-level relative humidity

11 NWP and the early warning of convection (d) (c) Figure 8. Synoptic type II for 17 July As Figure 2 but for 1200 UTC on 17 July. ( b) As Figure 2( b) but for 1500 UTC on 17 July and with cloud to ground flashes between 1600 and 1700 UTC. (c) As Figure 7(c) but for 1500 UTC on 17 July 1994 and with cloud to ground flashes between 1530 and 1630 UTC. (d) As Figure 7(d) but for between 2000 and 2100 UTC on 17 July and with radar echoes at 2030 UTC. fields but with maxima not located in the same regions. Using CAPE seemed suitable for qualitatively estimating potential convective instability (which is confirmed later in section 5). In the second class of diagnostics, which were useful in some of the cases here, we find diagnostics that measure low-level convergence and low-level advection of the equivalent potential temperature. Except for the large 339

12 V Ducrocq, D Tzanos and S Sénési Figure 9. Synoptic type III for 4 August As Figure 2 but for 1200 UTC on 4 August. ( b) As Figure 2( b) but for 1400 UTC on 4 August 1994 (Exp. A) and with cloud to ground flashes between 1430 and 1500 UTC. Figure 10. Synoptic type III for 5 August As in Figure 2 but for 1200 UTC on 5 August. ( b) As Figure 2( b) but for 0000 UTC on 5 August and with cloud to ground flashes between 0030 and 0100 UTC and contours at 100, 300, 600, 900, 1200 J kg 1 for CAPE. 340 positive values of ADTHE for the three cases mentioned above, no strong link was found between the ADTHE fields and the observed convective developments for the other cases. MOCON was found relevant mainly for synoptic type II cases. For some of the cases, the mismatch between the convective initiation

13 NWP and the early warning of convection Figure 11. Synoptic type III for 7 August As in Figure 2 but for 1200 UTC on 7 August. ( b) As Figure 2( b) but for 1400 UTC on 7 August (Exp. A) and with cloud to ground flashes between 1430 and 1500 UTC. Figure 12. Synoptic type III for 20 August As Figure 2 but for 20 August. ( b) As Figure 2( b) but for 1200 UTC on 20 August 1995 and with cloud to ground flashes between 1300 and 1330 UTC. location and the strong low-level moisture convergence areas can be explained by the incorrectly forecast lowlevel winds. But in the other cases even the MOCON computed from mesoscale analyses indicated no strong convergence at the convective initiation locations. Clearly, more knowledge is needed about these diagnostics computed from the model forecasts as well as from the observations. 341

14 V Ducrocq, D Tzanos and S Sénési Convective inhibition energy just prior to the convective initiation was weak or zero for all the cases. Taking into account the sparse sounding data to assess this forecast diagnostic, it remains difficult to determine if this is also the case for the observations and to prove the relevance of this forecast diagnostic. 4. Convective organisation and storm motion It has been shown that environmental wind and convective instability may influence the organisation of the convective systems. Heretofore, investigations have been conducted primarily for convective systems over North America, and much has been learned about these systems, particularly about supercell organisation (e.g. Weisman & Klemp, 1982) and long-lived squall lines (e.g. Rotunno et al., 1988). While convective systems over France can have supercell or long-lived squall line organisations, they do not represent the most frequent type of organisation. The systems that prevail over France are the multicell and mesoscale convective systems (MCSs) of multicells. Although a few European studies have tried to relate environmental characteristics to MCS organisation (Schiesser et al., 1995), the parameters influencing the organisation of mesoscale convective systems over European have not yet been clearly identified. For most of the cases selected for this study, convection is organised in mesoscale convective systems. To characterise these MCSs, we employed the classification of Schiesser et al. (1995), which is based on radar echoes and established for systems over Switzerland; that is, the MCSs were arranged in a group of cell complexes, a broken line of cell complexes or a continuous line of cell complexes. Line structures may or may not exhibit a leading line-trailing stratiform organisation as defined originally by Houze et al. (1990). The Schiesser et al. (1995) thresholds were adapted for the French radar network, i.e. the thresholds were lowered by approximately 5 dbz. For a given case, several convective systems may form, but we focus on no more than one or two mesoscale convective systems. The organisations of the selected MCSs are listed in Table 3. It should be noted that one of the MCSs exhibits squall line features (system b, 27 July 1994). The other MCSs are organised in broken lines (six MCSs) or in groups of cell complexes (three MCSs). For each selected convective system, forecast diagnostics characterising the environmental wind and convective instability were compared to the observed convective organisation in order to evaluate whether the environmental conditions differ as a function of organisation type. The forecast diagnostics were computed at observed mature stage times and near convective area centres. The values are listed in Table 3. The densityweighted mean wind over the hpa layer was also compared with the observed storm motion. 342 Synoptic types I and III exhibited both line and group organisations. Within these synoptic types, the line organisations tended to be associated with larger [ V/ z ]2.5km. When all the systems are taken into consideration, regardless of synoptic type, larger values of [ V/ z ]2.5km were also found for line organisations and smaller values for groups or no MCS organisation, with the exception of the 8 June 1993 broken line system and the 24 July 1994 group organisation. When comparing the observed and the forecast values of [ V/ z ]2.5km at the nearest observed sounding (in time and location), forecast values tended to be overestimated for group organisations and underestimated for line organisations (near 1 m s -1 above the observed value for 7 August 1994, and near 2 m s -1 below the observed value for 8 June 1993 and 4 August 1994). Hence, if the nearest observed sounding is used to compute [ V/ z ]2.5km, line organisations with the largest values of low-level shear are found, independent of synoptic type. Larger forecast values of [ V/ z ]5km are also found for line organisations within a synoptic type. No relationship was uncovered between the forecast helicity values and MCS organisation type, whatever of the storm motion estimate used (i.e. with an estimated storm motion defined as 75% of the speed and 30 to the right of the mean wind which is estimated by the density-weighted mean wind over the hpa layer (V ) or with the observed storm motion). All the helicity values are below the thresholds determined by Davies-Jones et al. (1990) for mid-level mesocyclones in supercell thunderstorms, which is in agreement with the absence of any supercell observations for our selected cases. For systems where it is possible to compute R ig, the values of R ig are also outside the supercell domain established by Weisman & Klemp (1982). The three systems with a CAPE value below 1000 J kg 1 are all organised as lines, and the three systems organised as groups show intermediate CAPE values close to 1800 J kg 1. For all the convective systems, the storms move to the right of the density-weighted mean wind over the 850Ð200 hpa layer. For convective systems of synoptic type I and III, the deviation ranged from 0 to 40. The type II convective systems behave differently from the others and exhibit a large deviation from the mean wind, which is weak. Except for the squall line system, the convective systems move more slowly than the mean wind (from 40 to 100% of the mean wind). Clearly, the squall line motion is governed by its gust front with a speed larger than the mean wind. 5. Stability indices and parameters To complement the qualitative evaluation presented above, we present here findings of a quantitative evaluation of the forecast soundings. Rather than simply comparing temperature, humidity and wind of

15 NWP and the early warning of convection Table 3. Forecast diagnostics versus MCS organization. C obs /dir. is the speed and direction of the observed storm motion. See text for the definition of all forecast diagnostics Synoptic C obs /dir. V /dir. [ V/ z ]2.5km [ V/ z ]5km CAPE type Date MCS organization (m s 1 ) (m s 1 ) (m s 1 ) (m s 1 ) (J kg 1 ) R ig I 10 June 1992 no MCS 5/230 5/ July 1994 Group 8/45 10/ July 1994 Broken line 14/60 14/ July 1994 System a: broken line 9/55 15/ Ð System b: continuous line Leading line-trailing stratiform 21/75 12/ Ð II 8 June 1993 Broken line Leading line-trailing stratiform 3/70 7/ July 1994 Broken line 6/70 8/ III 20 August 1995 Group 4/225 6/ August 1994 Group 6/90 10/ August 1994 Broken line 11/60 16/ August 1994 Broken line 16/40 20/ Ð observed and forecast soundings, we chose to compare quantitatively the diagnostics dedicated to convection; that is, stability index values computed for a forecast sounding are compared with their observed counterparts. To take advantage of an existing climatology of many stability indices from an observed sounding (Sénési & Thepenier, 1997), the comparison was performed for the same sounding time and location. In addition to this quantitative comparison, we highlight the most valuable forecast stability indices from the set of stability indices. The Sénési & Thepenier (1997) climatological study dealt with stability indices computed on the 1200 UTC sounding at Trappes (near Paris). From the available simulations, it was possible to extract eight forecast vertical soundings at the same location and time (two cases had simulations only beginning at 1200 UTC). For the cases of 24 July 1994, 4 August 1994, 7 August 1994 and 20 August 1995, convection forms within 150 km of the sounding location between 1130 and 1430 UTC. The convection moves towards the sounding location near UTC in the 10 June 1992 and 1 July 1994 cases and around 1900 UTC in the 27 July 1994 case. No convection develops near or moves towards the sounding location in the 8 June 1993 case. Stability indices and parameter values computed both on observed and forecast soundings are presented in Figure 13. Also drawn in the figure are the stability thresholds proposed by Sénési & Thepenier (1997) from the observed soundings from April to October between 1987 and 1994, together with the uppermost and lowest fifths. Upper and lower limits of the graphics are the extreme values of the indices over the seven convective seasons. For five soundings, all the forecast indices agree with the observed indices (i.e. the values of the observed and forecast indices lay on the same side of the proposed threshold). The 24 July 1994 (3), 27 July 1994 (4) and 20 August 1995 (8) cases are noteworthy because the instability is indicated by all the indices for both the simulations and the observations. In the 8 June 1993 case (5), for which convection occurs far away from the sounding, the observed indices indicate stability, in general, except for energy and convective instability indices (the Adedokun 2 index is close to the stability threshold). When we examine only the observed indices, the parcel parameters (CAPE and cloud depth) and the Adedokun 2 index are the only indices that indicate instability for all the cases with convection around the sounding and are below or just at the proposed thresholds for the non-convective case (5). This agrees with the previous results of Sénési & Thepenier (1997) which found these indices pertinent for discriminating between cases with and without convection. For the forecast values of these indices, large errors were found for CAPE and cloud depth with respect to the climatological variation range; on the other hand, forecast Adedokun 2 values are remarkably close to the observed values. Errors in CAPE (and cloud depth) are strongly connected to errors in surface wet bulb potential temperature (the most unstable parcel being, at that time of day, the ground surface parcel). Although the surface wet bulb potential temperature is used by both CAPE and Adedokun 2, an error in q w results in a larger impact on CAPE than in Adedokun 2 owing to an amplification by the vertical integration. Errors in the CAPE value may also derive from errors in the vertical structure of the temperature and moisture, whereas Adedokun 2 is only sensitive to errors in the 500 hpa temperature. For most of the indices, the largest error between the observed and forecast values for a given index is found for the 8 June 1993 case. This error is linked mainly to 343

16 V Ducrocq, D Tzanos and S Sénési Figure 13. Observed (O) and forecast (+) stability indices at Trappes at 1200 UTC on 10 June 1992 (1), 1 July 1994 (2), 24 July 1994 (3), 27 July 1994 (4), 8 June 1993 (5), 4 August 1994 (6), 7 August 1994 (7), 20 August 1995 (8), where the number in brackets indicates the position along the x-axis. The continuous line indicates the stability threshold of Sénési & Thepenier (1997), the dashed line and the dotted lines represent, respectively, the lowest and the uppermost fifths of the stability index values from observed radiosondes at Trappes at 1200 UTC from April to October between 1987 and

17 NWP and the early warning of convection (c) Figure 14. Forecast stability indices for 1000 UTC on 10 June 1992 based on Adedokun 2 (interval of 0.5 C), Jefferson (interval of 1 C), and (c) modified total totals (interval of 1 C). Dashed lines represent values below the stability threshold of Sénési & Thepenier (1997). Flashes around the initiation time are indicated by crosses. the model s inability to represent a dry layer between 800 and 500 hpa and explains not only the error in the CAPE, cloud depth, modified Showalter, Faust, Jefferson, modified K and Telfer indices but also the accuracy of the modified total totals or Adedokun 2 indices. This kind of comparison between observed and forecast indices at 1200 UTC could be useful for realtime operations, since it allows one to choose between the appropriate forecast indices for afternoon and evening. One advantage of using forecast stability index fields is to gain information about the stability at each grid column. As shown previously in the discussion on synoptic type, the horizontal structure of the stability index fields can be very valuable and informative. Some forecast indices computed for 10 June 1992 are displayed in Figure 14. It is interesting to note the similar structure of the CAPE and Adedokun 2 fields (Figures 2 and 14), which is in fact strongly related to the horizontal structure of the ground surface wet bulb potential temperature. The unstable area delineated by the two indices is the same and the observed convection effectively develops in this area. This is not the case for the energy, Jefferson and convective instability indices (Figure 14 for Jefferson index), with the convective development beginning ahead of the surface cold front (labelled A in Figure 14) located outside the delineated unstable area. The structure of these index fields is governed by the wet bulb potential temperature in the lower troposphere, which is itself similar to the low-level moisture horizontal structure. These indices are mainly an indication of frontal system humidity. Similar behaviour is found for the modified total totals and modified K indices (Figure 14(c)) with a horizontal structure linked to the horizontal structure of the lowlevel humidity. For the rest of the cases, similar qualitative comparisons of the horizontal structure of the indices around midday to convection development in the subsequent hours tends to promote the CAPE and Adedokun 2 indices as the most informative ones, except for the 27 July 1994 case which exhibits a split-front structure with an initial mid-level convective unstable layer. Taking into account the high sensitivity of the CAPE 345

18 V Ducrocq, D Tzanos and S Sénési Figure 15. Forecast stability indices for 0000 UTC on 28 July 1994 (Exp. B) based on CAPE (contours at 100, 200, 300, 600, 900, 1200 J kg 1 ) and ( b) Adedokun 2 (intervals of 0.5 C above 0 C and of 1 C below 0 C ). Dashed lines represent values below the stability threshold of Sénési & Thepenier (1997). Flashes between 0130 and 0135 UTC are represented by crosses. parameter to low-level q w errors, the Adedokun 2 index appears to have an advantage over CAPE. However, since the Adedokun 2 index depends on the ground surface q w, it loses this advantage with respect to CAPE for nocturnal convection (Figure 15). A modified Adedokun 2 index using a maximum q w of a layer above the ground surface instead of the ground surface q w would certainly be better. On the other hand, it can be argued that information about the low-level humidity horizontal structure, as contained, for example, in index fields such as modified total totals or energy indices, can be supplied more simply by a low-level humidity field. 6. Conclusions 346 An evaluation of the quality of a mesoscale model and its associated diagnostics for predicting the convective environment and convection was performed for ten case-study days. Independent of the synoptic type examined, the forecast convective instability, together with the forecast low-level relative humidity, were found to be useful for delineating areas outside which convection will not form. While the forecast moisture convergence helped in determining more precisely the convective initiation location for the two synoptic type II situations (cold cut-off), this was generally not the case. This disagreement between the convective initiation location and the forecast moisture convergence areas might have derived in some cases from the inaccurate forecasting of low-level winds. For the other cases, this disagreement was obvious from the observations. The forecast equivalent potential temperature advection was found to be relevant for some of the synoptic type I cases (warm sector ahead of a cold front). Clearly, for these two diagnostics, MOCON and ADTHE, a better understanding of their connection to convective initiation and evolution must be gained from other observed and forecast cases. It is difficult to draw any conclusions about the evolution of convective systems because observed and forecast convection (and their feedback on the environment) differ in many cases, making any comparison delicate. Some information can be obtained, however, such as the fact that the convection travels with the warm sector in synoptic type I or with a line of convergence. For an optimal use of the mesoscale model forecast during convective evolution, we recommend monitoring the observations in real time to provide more confidence in the mesoscale model forecast as well as to help detect any model errors. The model failed to properly represent the convective rain associated with the observed convective systems, except for the synoptic type II cases in which both convective instability and moisture convergence were accurately forecast. Undertaking developments in the physical package, such as a downdraft parameterisation, may improve the convection forecast in the future. While the basic parameters governing the organisation of convective systems over Europe had not been clearly identified up to now, the cases considered here demonstrate that line organisations tend to be associated with larger observed low-level wind shear. This was also