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Shower advection
Non-advection inland of showers (equilibrium convection)
Fig9.6.21-1: This old example was with "equilibrium convection", that is no longer present in the IFS: 30h convective precipitation totals (mm) with mean sea level pressure verifying at 18UTC 29 Nov 2010, forecast data time 12UTC 28 Nov 2010. The convection scheme is diagnostic and works on a grid box column, so cannot produce large amounts of precipitation over the relatively dry and cold (stable) wintery land areas. Showers are shown as limited to the sea alone while in nature these showers penetrate inland on the brisk easterly wind.
Non-advection inland of showers (non-equilibrium convection)
Fig9.6.31-2: This newer example was with non-equilibrium convection, introduced into the IFS in 2013: precipitation fields when showers developed over the Great Lakes in very cold air on a westerly wind (mm rainfall equivalent). Significant showers are shown where strong convection is initiated over the relatively warm waters of the Great Lakes, but give very small amounts of showery precipitation down-wind where instability is weakly initiated or not initiated over the cold land. In reality the showers developing over the Great Lakes persisted long enough to be blown well inland as active convection. Note in particular the difference in precipitation east of Lake Michigan.
Inland penetration of wintertime maritime showers
Wintertime maritime convection can penetrate further inland than indicated by IFS forecasts.
Comparison of precipitation totals as forecast by IFS and as observed by radar illustrates systematic downstream precipitation biases in the CONTROL-10ensemble control/HRES forecast (Fig9.6.4A & B1-3 & Fig 9.6.1-4). This relates to the parametrisation of convection. Convective precipitation produced in the IFS is considered to fall out immediately at the grid point and is not advected laterally irrespective of the winds experienced during descent of the precipitation. This means that precipitation reaching the ground can extend further inland than CONTROL-10/HRES shows when:
- snow is falling (because in reality the snow flake drifts further in the wind than does rain), and/or
- there are strong steering winds (because in reality rain can be advected laterally during descent).
Fig9.6.4A1-3: Illustration of observed showery precipitation over NW England on 28 February 2017. Active wintry showers that developed over the Irish Sea (lower right frame, scale shows instantaneous rates in mm/hr) became organised into a line and the convective cells moved towards the SE or ESE, in line with steering being according to the 700mb wind direction, locally giving observed rainfall totals up to >10mm/12hr (top left frame, scale shows totals in mm/12h). IFS short range forecasts from data time 00Z 28 Feb are shown for comparison (top right (colours as scale) and lower left frames (probabilities as scale)) - note probability of showers is confined to coastal grid points and only relatively small rainfall totals 2-4mm/12hr are forecast inland with only a moderate probability. The red outline (top left frame) highlights where errors were particularly acute.
Fig9.6.4B1-4: Comparison of 12hr precipitation totals from maritime convection in a cold (sub 528dam thickness) westerly flow to 09UTC on 7 Jan 2022.
- Forecast CONTROL-10/HRES precipitation (brown land, smooth outlines of precipitation areas)
- Radar precipitation (white land/no precipitation, striated precipitation areas)
The schematic Fig9.6.4C 1-5 illustrates the biases in the IFS forecast precipitation totals, and how they would likely change with stronger winds, reflecting in particular the situation of wintry precipitation in the example over NW England and Wales.
Fig9.6.4C1-5: Schematic illustration of systematic precipitation biases in onshore maritime convection. Too much precipitation is forecast for windward coastal zones and too little precipitation is forecast for areas leeward of high ground. These areas expand and move downwind with stronger winds.
Convective Severity - CAPE and CAPE-shear
Fig9.6.5A(left): Forecast CAPE Extreme Forecast Index (EFI) in northern Italy and western Austria for 00UTC 12 to 00UTC 13 Dec 17, T+24 to 48 from data time 00UTC 11 Dec 17. The darker orange area over far North Italy and Tyrol (roughly shown by the pin) has EFI>0.8 denoting high probability of an out-of-the-ordinary significant event. EFIs are shown by colours - Yellow >0.5%, Dark Yellow >0.6%, Orange >0.7%, Dark Orange >0.8%, Red >0.9%.
Fig9.6.5B(right): Forecast CAPE-shear Extreme Forecast Index (EFI) in northern Italy and western Austria for 00UTC 12 to 00UTC 13 Dec 17, T+24 to 48 from data time 00UTC 11 Dec 17. The red area over far North Italy and Tyrol (roughly shown by the pin) with EFI>0.9 and is rather larger in extent than CAPE EFI owing to the influence of the bulk shear in the lower troposphere. EFIs are shown by colours - Yellow >0.5%, Dark Yellow >0.6%, Orange >0.7%, Dark Orange >0.8%, Red >0.9%.
Fig9.6.6A(left): Forecast probability of precipitation (>5mm/12hr) in northern Italy and western Austria for 12hr period ending 00UTC 13 Dec 17, T+36 to 48 from data time 00UTC 11 June 17. Higher probability of precipitation over Tyrol. Probabilities shown by colours - Light blue >5%, Blue >35%, Dark blue >65%, Purple >95%.
Fig9.6.6B(right): Forecast CAPE-shear EFI superimposed upon forecast probability of precipitation (>5mm/12hr) in northern Italy and western Austria ending 00UTC 13 Dec 17, T+48 from data time 00UTC 11 June 17 as figures shown above. High CAPE or high CAPE-shear alone show only the potential for active convection - if it can be released. It is also necessary to to identify where the atmospheric model is actually producing precipitation, and if this overlaps with high CAPE or CAPE-shear then severe convection may be forecast. In this example the area over far North Italy and Tyrol (roughly shown by the pin) has high CAPE-shear and high probability of precipitation and hence severe weather may be forecast in the area.
Unrealistic extreme convective precipitation focussed near coastlines
This effect can occur with onshore cyclonic flow of maritime air that is marginally unstable to sea surface temperatures. At certain times SSTs can be higher close to coastlines than offshore. In these cases the inshore sea surface temperature can be high enough for the convection scheme in IFS to trigger release of convection with high CAPE values. Just upstream the lower sea surface temperatures offshore cannot overcome convective inhibition at low or mid-tropospheric levels. The IFS convective scheme triggers Instantaneous shower development at each step but does not advect the showers down wind. This results in repeated convective rainfall over the same inshore locations which can add up to large or implausibly large record-breaking near-coast totals (Fig9.6.1-6).
Fig9.6.1-6: EFI for 24h precipitation for period 00UTC 6 Nov 2023 to 00UTC 7 Nov 2023, DT 00UTC 6 Nov 2023. Unrealistically large or extreme precipitation totals on coasts exposed to the northwest are caused by instantaneous shower development by the convection scheme over inshore waters that are slightly warmer than offshore.
Orographic and Rainshadow effects
Orographic and rain shadow effects can be strong in unstable onshore air flow, particularly when an unstable marine airmass meets coastal mountains. However, precipitation forecasts can be incorrectly represented.
This is because the forced uplift triggers immediate development of parametrised showers, with precipitation (snow in the illustrated case) falling immediately and vertically to the ground.
In reality the showers take time to grow while also being driven downwind. The snow that falls from them also drifts downwind as it falls. However, neither "drift" mechanism is represented in the IFS and the net effect is that the snow in reality is spread across a much larger distance downwind than in the raw model output .
Fig9.6.1-7: The diagram shows an area of NW Scandinavia with snow accumulation indicated by colours (large accumulations blues, small amounts, green). Topographically the area is complex, but the key feature are strong upslopes near the exposed NW coast of Norway, with a line of mountains reaching about 2000m but interspersed with lower lying gaps.
The top left diagram shows accumulated snow derived over a 15 day period ending 00UTC 1 May 2023. Forecast accumulation of snowfall is predominantly on the exposed NW-facing mountainous coastal areas but a strong indication of little or no snow accumulation to the lee of the mountain ranges (shown by dashed line).
The central diagram shows the ECMWF analysed accumulation of snow at 00UTC 1 May 2023 which uses observations supplied by the relevant meteorological service but also uses the predicted accumulations given in the top diagram. Thus there remains a bias towards the clearer area near the dotted line despite the observations.
The bottom diagram is the snow depth analysis by the Swedish meteorological service. There are more observations than are shown plotted, and the rain shadow effect is not as well marked as suggested by model forecast or analyses.
Convective Severity - CAPE and CAPE-shear
Fig9.6.1-8: Forecast CAPE Extreme Forecast Index (EFI) in northern Italy and western Austria Fig9.6.7A(left): Multi-parameter EFI CHART (a clickable chart) for 00UTC 12 to 00UTC 13 Dec 17 (, T+24 to T+ 48 ) from data time 00UTC 11 Dec 17. The dark green darker orange area over far North Italy and Tyrol (arrowed) indicates a high EFI for rainfall.
Fig9.6.7B(right): Cumulative Density Function (CDF) for far North Italy (derived from the clickable EFI chart in Fig9.6.7A) for period 00UTC 12 Dec 17 to 00UTC 13 Dec 17. Note the steep slope of rainfall and temperature CDFs which implies high confidence (low spread among recent ENS members). Latest precipitation forecast has not as many high rainfall totals as previous ENS members but retains a high EFI value.
In such a winter case the values of CAPE and CAPE-shear are unlikely (inland) to be dramatically large, particularly when compared to summertime values. But nevertheless, the EFI values for CAPE (Fig9.6.5A) and especially CAPE-shear (Fig9.6.5B) are high, indicating the forecast values are towards the high end of the M-climate distributions for these parameters, and are therefore worthy of further investigation. In particular, there is an enhanced likelihood that the convection scheme's totals may not be so representative and that much more extreme local totals are possible.
Observations available for this case suggested quite a lot of localised variability, though peak 24h totals were no more than 20mm. It may be that although the CAPE-shear EFI was anomalously large, the absolute values of CAPE-shear may not have been very high.
Impact of differing land surfaces
Land surface characteristics (soil moisture, leaf area index) have an impact upon land and temperature forecasts. Changes in land characteristics is especially important where there is a sharp discontinuity in ground type or vegetation cover. This can produce significant difference in temperatures or moisture content of the lower atmosphere over a short distance, and hence to air temperature and/or the development of convection. Users should inspect model information on land surface, soil moisture and leaf area index to identify areas where significant changes in precipitation or other weather phenomena over short distances may occur.
Fig 9.6.8: Illustration of the impact of differing land cover and type in the vicinity of Flagstaff, Arizona. Showers broke out over the vegetated west part of the area but not over the rocky region to the east. The central diagram shows the ensemble 98th percentile of "point rainfall", with tephigrams DT 00UTC 18 July 18 T+24 VT 00UTC July 19. The parcel curves have very different CAPE values - greater in the west and hence greater risk of very wet weather, but lesser in the east even though temperatures were higher over the bare surface. This illustrates high sensitivity to humidity mixing ratios and altitude. Humidity mixing ratios can reflect land surface processes related to evapotranspiration which control the moisture exchange with the lower troposphere. And in turn these relate to the soil moisture which controls moisture availability. Also of critical importance on the soundings are the light winds with shear. Here the land surface characteristics changed rapidly across a short distance (forest to rock), which is in fact reflected on the deep (1m) soil moisture plots from the IFS, and also in the leaf area index (LAI), which is a multiplying factor for evaporation.
Impact of low-level moisture
The release of convection is strongly dependent upon correct analysis and forecasting of boundary layer humidity and land surface characteristics. This can result in a mismatch, mainly in arid coastal regions, between the location and severity of forecasts of active convection and verifying observations. Showers may be forecast in the wrong location or not forecast at all. Users should consider the possible effects of more moist air feeding into the boundary layer, perhaps by considering the potential for moist marine air to spread inland in a more pronounced way than CONTROL-10/HRES forecasts suggest. Users should consider the possibility of an influx of low level air that is dissimilar to forecast values - i.e. moist air across coastal areas that might allow release of convection, or the converse if an influx from drier areas occurs. Daytime heating in upland locations and/or upslope flow over the mountains can also cause destabilisation that may not be captured by the forecast models.
Poorly forecast heavy showers in Oman
Fig9.6.9: Large and vigorous convection over eastern Oman 6 July 2018 bringing heavy showers.
Fig9.6.10: Observed (black) and forecast (red) vertical profiles at approximately the same time as the satellite picture (Fig9.6.9) for a radiosonde location (Seeb, WMO:41256) just northwest of Muscat. The lowest layers were observed to be quite moist while the forecast vertical profile indicated much drier conditions. The low level winds are shown as drifting air from the nearby sea on both observed and forecast profiles. Higher moisture at low levels would allow deep and active convection to be released with sufficient energy input to overcome the convective inhibition (CIN), either by surface heating or by uplift over the mountains. Heavy showers did develop but were not well forecast, if at all.
Poorly forecast heavy showers in SE England
roughly shown by the pin) has EFI>0.8 denoting high probability of an out-of-the-ordinary significant event. EFIs are shown by colours - Yellow >0.5%, Dark Yellow >0.6%, Orange >0.7%, Dark Orange >0.8%, Red >0.9%.
Fig9.6.1-9: Forecast CAPE-shear Extreme Forecast Index (EFI) in northern Italy and western Austria for 00UTC 12 to 00UTC 13 Dec 17, T+24 to 48 from data time 00UTC 11 Dec 17. The red area over far North Italy and Tyrol (roughly shown by the pin) with EFI>0.9 and is rather larger in extent than CAPE EFI owing to the influence of the bulk shear in the lower troposphere. EFIs are shown by colours - Yellow >0.5%, Dark Yellow >0.6%, Orange >0.7%, Dark Orange >0.8%, Red >0.9%.
Fig9.6.1-10: Forecast probability of precipitation (>5mm/12hr) in northern Italy and western Austria for 12hr period ending 00UTC 13 Dec 17, T+36 to 48 from data time 00UTC 11 June 17. Higher probability of precipitation over Tyrol. Probabilities shown by colours - Light blue >5%, Blue >35%, Dark blue >65%, Purple >95%.
Fig9.6.1-11: Forecast CAPE-shear EFI superimposed upon forecast probability of precipitation (>5mm/12hr) in northern Italy and western Austria ending 00UTC 13 Dec 17, T+48 from data time 00UTC 11 June 17 as figures shown above. High CAPE or high CAPE-shear alone show only the potential for active convection - if it can be released. It is also necessary to to identify where the atmospheric model is actually producing precipitation, and if this overlaps with high CAPE or CAPE-shear then severe convection may be forecast. In this example the area over far North Italy and Tyrol (roughly shown by the pin) has high CAPE-shear and high probability of precipitation and hence severe weather may be forecast in the area.
Fig9.6.1-12: Multi-parameter EFI CHART (a clickable chart) for 00UTC 12 to 00UTC 13 Dec 17 (T+24 to T+48) from data time 00UTC 11 Dec 17. The dark green area over far North Italy and Tyrol (arrowed) indicates a high EFI for rainfall.
Fig9.6.1-13: Cumulative Density Function (CDF) for far North Italy (derived from the clickable EFI chart in Fig9.6.1-8) for period 00UTC 12 Dec 17 to 00UTC 13 Dec 17. Note the steep slope of rainfall and temperature CDFs which implies high confidence (low spread among recent ENS members). Latest precipitation forecast has not as many high rainfall totals as previous ENS members but retains a high EFI value.
In such a winter case the values of CAPE and CAPE-shear are unlikely (inland) to be dramatically large, particularly when compared to summertime values. But nevertheless, the EFI values for CAPE (Fig9.6.1-8) and especially CAPE-shear (Fig9.6.1-8) are high, indicating the forecast values are towards the high end of the M-climate distributions for these parameters, and are therefore worthy of further investigation. In particular, there is an enhanced likelihood that the convection scheme's totals may not be so representative and that much more extreme local totals are possible.
Observations available for this case suggested quite a lot of localised variability, though peak 24h totals were no more than 20mm. It may be that although the CAPE-shear EFI was anomalously large, the absolute values of CAPE-shear may not have been very high.
Impact of differing land surfaces
Land surface characteristics (soil moisture, leaf area index) have an impact upon land and temperature forecasts. Changes in land characteristics is especially important where there is a sharp discontinuity in ground type or vegetation cover. This can produce significant difference in temperatures or moisture content of the lower atmosphere over a short distance, and hence to air temperature and/or the development of convection. Users should inspect model information on land surface, soil moisture and leaf area index to identify areas where significant changes in precipitation or other weather phenomena over short distances may occur.
Fig9.6.1-14: Illustration of the impact of differing land cover and type in the vicinity of Flagstaff, Arizona. Showers broke out over the vegetated west part of the area but not over the rocky region to the east. The central diagram shows the ensemble 98th percentile of "point rainfall", with tephigrams DT 00UTC 18 July 18 T+24 VT 00UTC July 19. The parcel curves have very different CAPE values - greater in the west and hence greater risk of very wet weather, but lesser in the east even though temperatures were higher over the bare surface. This illustrates high sensitivity to humidity mixing ratios and altitude. Humidity mixing ratios can reflect land surface processes related to evapotranspiration which control the moisture exchange with the lower troposphere. And in turn these relate to the soil moisture which controls moisture availability. Also of critical importance on the soundings are the light winds with shear. Here the land surface characteristics changed rapidly across a short distance (forest to rock), which is in fact reflected on the deep (1m) soil moisture plots from the IFS, and also in the leaf area index (LAI), which is a multiplying factor for evaporation.
Impact of low-level moisture
The release of convection is strongly dependent upon correct analysis and forecasting of boundary layer humidity and land surface characteristics. This can result in a mismatch, mainly in arid coastal regions, between the location and severity of forecasts of active convection and verifying observations. Showers may be forecast in the wrong location or not forecast at all. Users should consider the possible effects of more moist air feeding into the boundary layer, perhaps by considering the potential for moist marine air to spread inland in a more pronounced way than HRES forecasts suggest. Users should consider the possibility of an influx of low level air that is dissimilar to forecast values - i.e. moist air across coastal areas that might allow release of convection, or the converse if an influx from drier areas occurs. Daytime heating in upland locations and/or upslope flow over the mountains can also cause destabilisation that may not be captured by the forecast models.
Poorly forecast heavy showers in Oman
Fig9.6.1-15: Large and vigorous convection over eastern Oman 6 July 2018 bringing heavy showers.
Fig9.6.1-16: Observed (black) and forecast (red) vertical profiles at approximately the same time as the satellite picture (Fig9.6.1-15) for a radiosonde location (Seeb, WMO:41256) just northwest of Muscat. The lowest layers were observed to be quite moist while the forecast vertical profile indicated much drier conditions. The low level winds are shown as drifting air from the nearby sea on both observed and forecast profiles. Higher moisture at low levels would allow deep and active convection to be released with sufficient energy input to overcome the convective inhibition (CIN), either by surface heating or by uplift over the mountains. Heavy showers did develop but were not well forecast, if at all.
Poorly forecast heavy showers in SE England
Fig9.6.1-17: An example of the effect of under-representation of low-level temperature and dew point by the IFS near an urban heat island. Forecast values of near-surface temperature and dew point are about 3C cooler than observed. Modifying the forecast vertical profile using observed values results in significantly greater CAPE than forecast which, together with the forecast shear, would indicate much more active convection. Flash flooding and a tornado were observed near the urban heat island.
Precipitation over mountainous coasts and islands
Too much precipitation can be forecast over mountainous coasts and islands. At a location on a mountain the model height can be significantly lower than the true height of the of the land surface. See a schematic of model representation of orography and Tenerife as an example of a mountainous island. Thus temperatures at the location can be forecast to be too warm. This can then result in in a reduction of CIN from true values and the release of convection, possibly with large MUCAPE, over the mountains.
Higher forecast temperatures inland are likely to induce more onshore flow of moist air from nearby sea or lake. This can substantially alter the structure of the forecast airmass and possibly encourage release of convection.It is possible there is excess convergence in HRES and the ensemble. This would result in greater vertical velocity and moisture convergence that could lead to errors in forecast precipitation over steep or poorly resolved orography.
It is for the forecaster to assess critically the expected and changing structure and evolution of the airmass at a given upland location. Forecasters should not rely on a single model forecast, but view the ensemble of forecasts and a whole. Further, although precipitation could be heavy over the mountains, it might not be widespread nor extend to adjacent low-lying areas. Equally, dry zone underlying the altitude of the mountain convection may reduce precipitation penetrating to lower levels. Fig9.6.1: An example of the effect of under-representation of low-level temperature and dew point by the IFS near an urban heat island. Forecast values of near-surface temperature and dew point are about 3C cooler than observed. Modifying the forecast vertical profile using observed values results in significantly greater CAPE than forecast which, together with the forecast shear, would indicate much more active convection. Flash flooding and a tornado were observed near the urban heat island.
Medium level instability in drier areas
It is important that moist medium level instability is modelled sufficiently as even relatively small CAPE can produce precipitation. Users should check forecast vertical profiles against local observations and profiles.
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Where medium level instability is forecast above a dry lower atmosphere, users should use forecast lightning charts and forecast vertical profiles to extend and improve precipitation forecasts. Where medium level instability is forecast (even with only moderate CAPE), some additional showers should be forecast within the areas of forecast lightning. Owing to resolution issues, forecast intensity of lightning strikes gives only a rough idea of regions where there is more active medium level instability but it does not reliably indicate that showers will penetrate to the surface, nor their intensity if they do so. However, probability of precipitation should be increased.
Fig2Fig9.6.1.30-18: Forecast IFS data for central and northwest Australia 17 Jan 2019. Local time is about 10hrs ahead of European time zones. The circled triangle locates Alice Springs.
- Fig2Fig9.6.1.30a-18(a): Total 6hr precipitation from 9km resolution model DT 12UTC 16 Jan 2019, T+21 VT 09UTC 17 Jan 2019.
- Fig2Fig9.6.1.30b-18(b): Lightning density in 6hr (flashes 100km-2hr-1) DT 12UTC 16 Jan 2019, T+21 VT 09UTC 17 Jan 2019.
- Fig2Fig9.6.1.30c-18(c): ENS probability of total precipitation >1mm: DT 12UTC 16 Jan 2019, T+12 VT 00UTC 17 Jan 19 to T+36 00UTC 18 Jan 2019.
- Fig2Fig9.6.1.30d-18(d): Total 6hr precipitation from 9km resolution model DT 12UTC 16 Jan 2019, T+21 VT 09UTC 17 Jan 2019, and Observed lightning flashes VT 09UTC 17 Jan 2019.
- Fig2Fig9.6.1.30e-18(e): Forecast vertical profile at Alice Springs DT 12UTC 16 Jan 19, T+18 VT 06UTC 17 Jan 2019.
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In this example, medium level thunderstorms developed and extended well into central parts of Australia (Fig2Fig9.6.1.30d, -18(b), with observed lightning) but no underlying surface rainfall is forecast (Figs2Figs9.6.1.30a & 2.1.30d-18(a) & 9.6.1-18(d), nor any probability of rain (Fig2Fig9.6.1.30c-18(c)). Forecast lightning flashes (Fig2Fig9.6.1.30b-18(b)) is overly extensive in northwest Australia but although there is some indication in central parts it is under-indicated (compare with Fig2Fig9.6.1.30d-18(d)).
The model boundary layer was generally dry in central Australia but observations showed much higher dew points where showers have occurred. Near Alice Springs the model T2m dewpoint was 4.2C lower than the observed dew point, and at a location to the northwest the error was 11.8ºC. Both discrepancies were probably due to storms that the model didn't represent.
The forecast vertical profile for Alice Springs (Fig2Fig9.6.1.30e-18(e)) shows possible (surface-based) medium level instability with just moderate CAPE (e.g. cyan line construction). Note that some ensemble members have higher low-level dew points which means a lower CIN to initiate medium level convection with greater CAPE (e.g. red dashed line construction). Further, if the boundary layer is moistened after any medium level showers penetrate to the surface then there is a higher likelihood of more energetic convection being released afterwards with much greater CAPE (e.g. black dashed line construction).
In Central Australia, no precipitation is indicated; any precipitation in the model is being evaporated before reaching the ground. However, the lightning activity chart suggests that, though the deep moist convection isn't very well-organised, scattered thunderstorms appear likely. This was bourne out by observations. Note also that the model greatly over-predicted lightning activity over northwest Australia.
Use of available forecast data and derived products
CAPE and CAPE-shear don't tell the full story
Large values of CAPE lie in a zone across the Aegean Sea and parts of mid-Greece coincident with a belt of strong vertical wind shear resulting in very high values of CAPE-SHEAR (Figs 29.6.1.24 & 2.1.25-19(a) & 9.6.1-19(b)). In particular, high forecast values of CAPE and CAPE-SHEAR are indicated at Pilio while much lower forecast values are shown at Kavala. This might suggest at first sight that any instability that is released in the region of Pilio would be very active with the possibility of severe storms and rainfall. At the same time much less showery activity might be expected at Kavala on the northern flank of the CAPE and CAPE-SHEAR zone. Such a snap assessment would be incorrect.
Fig2Fig9.6.1.24a-19(a): Forecast CAPE (Blue high, Red low) and Fig2.
Fig9.6.1.24b-19(b): Bulk Wind Shear (Orange high, Yellow low). T+24 VT00UTC 11 July 2019, DT00UTC 10 July 2019.
Fig2Fig9.6.1.25a-20(a): Forecast CAPE-SHEAR (Purple high, Blue low).
Fig9.6Fig2.1.25b-20(b): Max CAPE-SHEAR (Red high, Blue low). T+24 VT00UTC 11 July 2019, DT00UTC 10 July 2019. Very high values are indicated in the vicinity of Pilio. More modest values are indicated in the vicinity of Kavala on the CAPE-SHEAR chart but note that the maximum CAPE-SHEAR chart shows there have been much higher values during the previous 6hrs.
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The forecast precipitation field (Fig2Fig9.6.1.26-20) shows a belt of rainfall across North Greece, Albania and Bulgaria. This indicates that, as a minimum, in this area there is sufficient moisture in the forecast atmosphere to provide precipitation. The area of forecast precipitation intersects the northern flank of the forecast CAPE and CAPE-SHEAR areas and thus it is this area that is more likely to see release of deep and active convection with availability of plenty of moisture. Little or no precipitation is indicated in mid-Greece but nevertheless these lie within the areas of very high CAPE and isolated but local very heavy showers are possible and, bearing bearing in mind the high bulk shear and CAPE-SHEAR values, local storms cannot be ruled out.
Fig2Fig9.6.1.26-21: Forecast precipitation (12hr). T+24 VT00UTC 11 July 2019, DT00UTC 10 July 2019.
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The corresponding diagnostic charts for the probability of high rainfall (>40mm/24hr) and Extreme Forecast Index (EFI) for precipitation (Fig2Fig9.6.1.27-21(a) & Fig9.6.1-21(b)) identify the areas at greatest risk of a major precipitation event.
Fig2Fig9.6.1.27a-22(a): Probability of total precipitation >40mm (24hr). Green shading represents 35-65% probability.
Fig9. Fig26.1.27b-22(b): Precipitation extreme forecast index (EFI). Red shading represents EFI>0.8, Dark red >0.9 EFI. T+24 VT00UTC 11 July 2019, DT00UTC 10 July 2019.
Forecast vertical profiles are very helpful in assessing the potential for severe events. The forecast vertical profile at Pilio shows large CAPE but with relatively dry convection, possibly released by high surface daytime temperatures. Very little moisture is indicated and precipitation looks very unlikely. However some moisture is available locally over mid-Greece (Fig 29.6.1.26-22(b)) mainly at medium levels producing possible local showery outbreaks given some form of dynamic uplift. The relevant wind shear to consider for this is probably between medium and upper tropospheric levels rather than between lower and medium levels (the bulk shear). Inspection of the hodograph suggests the upper tropospheric shear is not great, so shower organisation/activity would lack this element of support. Note, however, that heavy medium level showers can penetrate downwards through underlying dry layers more than IFS forecasts tend to suggest, even reaching down to the surface. CONTROL-10 Ensemble control/HRES show a very humid boundary layer at Pilio, but it would require large energy input at the surface (2m temperatures above about 35°C) to overcome the large CIN and to lift the low level moisture to release moist convective cells.
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Violent storms with local hail swept across northern Greece overnight 10/11 July 2019 causing seven deaths and widespread damage.
Fig2Fig9.6.1.28-23: Forecast vertical profiles for Kavala and Pilio, Greece. T+24 VT00UTC 11 July 2019, DT00UTC 10 July 2019.
Use of a sequence of data as early warning
A sequence of forecast EFI charts gives early indication of forthcoming severe weather potential (Fig2Fig9.6.1.29-23), and some idea of the confidence that may be placed on the forecast event. In this case, northern Greece is identified as being at moderately high risk of an extreme event (EFI ~ 0.6) four days before, rising steadily to a very high risk of an extreme event (EFI ~ 0.9) two days before the before the occurrence of the severe weather. Note how there is consistent indication of a very high risk of an extreme event (EFI ~ 0.9) over the Balkan states through the sequence of forecast runs. The consistency in the areas shown at risk leads to a higher confidence in forecasts of severe weather. Users should inspect forecast fields using ecCharts and vertical profiles as outlined above to assess forecast details, and also add in the influence of additional factors using local knowledge (e.g. regarding topographic influences) wherever possible.
Fig2Fig9.6.1.29-24: Sequence of EFI precipitation charts from four EFI runs at 24hr intervals (DT 12UTC on 6, 7, 8, 9 July 2019). Increasingly high EFI precipitation values identify the areas at greatest risk.
Model output associated with extreme convection
CONTROL-10/HRES tends to over-forecast extreme convection, especially in the maritime tropics. Spurious quasi-circular waves (sometimes rings) in convective precipitation fields can emanate from the forecast rapid uplift that is associated. These spread outwards. The gravity waves can even move well upwind, giving a false impression of an eastward-moving trough. The source of these false features should be recognised and their effects discarded from forecasts. Changes to the IFS moist physics in 2019 have mitigated but not entirely removed this effect.
Fig 9.6.111-25: An example of a forecast precipitation chart showing a very active convective area in the mid-Indian Ocean. The surrounding ring of forecast precipitation is associated with a spurious gravity wave (ripple effect) moving outward from the initial convective cell. These rings of precipitation are incorrect and should be ignored.
Fig9.6.12: CONTROL-101-26: Ensemble control/HRES forecast of precipitation associated with gravity waves propagating outward across central Africa from a pulse of very strong convection formed over the Gulf of Guinea (just to the southwest of the charts). Model precipitation rate are shown for one such feature at T+120, T+132, T+144, data time 00Z 3 Sept 2018. The apparent trough is propagating anomalously against the flow and the precipitation is not correct.
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