Central Europe heavy rain event

By Sheldon J. Kusselson (NOAA NESDIS)

Rainfall events almost always occur with some combination of lift, instability and moisture. High impact heavy rainfall events that can result in flooding almost always occur with equally high amounts of these variables. Satellite imagery is very helpful in showing these variables, at the very least in a subjective manner. Using satellite imagery/products with other types of observational and numerical computer model data can be very helpful in building forecaster confidence in predicting these types of events before they occur or at least as they are evolving.

The Mediterranean case presented below is the first significant rainfall event in Greece in 2012, after the dry summer months (see time series of Kerkira station, source: Wetteronline). According to YouTube, "a squall line of thunderstorms hit NW Greece with great amounts of precipitation, strong gusts and lightning" (see YouTube videos: Igoumenitsa 13/9/12 — HERMINE Cyclone and Hermine cyclone — West Greece Sept 2012). An analysis of this case is shown in the following presentation (source: S. Kusselson).

Slide 1 shows the 00:00 UTC 14 September 2012 500hPa heights overlaid on the Airmass RGB product for the same time to help us get a sense of the instability parameters that were setting up for this multi-day heavy rainfall event. The Airmass RGB is designed and tuned to monitor the evolution of cyclones, in particular rapid cyclogenesis, jet streaks and PV (potential vorticity) anomalies, which appear red in the image. Included as an insert at the lower right corner of the image was the same time initial analysis NOAA Global Forecast System (GFS) 500hPa standardised deviation height anomalies.

The Airmass RGB was matched with model 500hPa height anomalies to get a sense of the forcing mechanisms and anomalous heights that would drive the efficient squeezing of moisture from the atmosphere to the ground to increase the heavy rainfall and flooding potential. This could further boost forecaster confidence in the coming potential high impact event.

Slide 2 shows the 850hPa heights for 00:00 UTC 14 September as this is usually helpful for determining the low level flow and subsequent moisture transport when using satellite products of total atmospheric moisture.

Slide 3 is the SEVIRI Physical Retrieval (SPhR) Total Precipitable Water (TPW) product for 00:00 UTC 14 September. The algorithm retrieves the atmospheric temperature and moisture profiles as well as surface skin temperature for one clear sky SEVIRI pixel, or a Field-Of-Regard (FOR) which contains M x M pixels. The central aim of the SPhR is to provide information on the water vapour contained in a vertical column of unit cross-section area in several layers in the troposphere and to provide some instability indices.

These parameters are calculated from the retrieved profiles of temperature and humidity. Total Precipitable Water (TPW) is the amount of liquid water, in mm, if all the atmospheric water vapour in the column were condensed. High values of TPW in clear air often become antecedent conditions prior to the development of heavy precipitation and flash floods. When high TPW values areas present a lifting mechanism and warm advection in low levels, heavy precipitation often occurs. This data provides forecasters with an important tool for short and even some cases medium range forecasting. The SPhR TPW product only provides information in clear areas.

Slide 4 is the NOAA/NESDIS Operational Blended or Merged Total Precipitable Water product that merges microwave total precipitable water retrievals from polar orbiting satellites to provide additional total column moisture information especially in areas of clouds and over a larger area than what is available with the SEVIRI product. Because of the 2–4 hour time-lag in receiving the polar orbiting data that goes into producing the Blended TPW product, the SEVIRI product is more timely. But each product can complement and supplement the other with information on total atmospheric moisture.

On slide 4, there is annotation of 850hPa flow across the highest moisture that is intended to give the forecaster the sense of where the greatest transport of that high moisture is at low levels. Since most of the Total Precipitable Water in the atmosphere is situated below 700hPa or 3km (Kusselson, 1993), we use a compromising 850hPa level flow to overlay on the Blended TPW product. Low level wind flow through or parallel to the highest moisture or moisture plume/atmospheric river is a good indicator of the potential for heavy rain and subsequent flooding just downstream.

Slide 5 shows the merged TPW Percent of Normal product for the same 00:00 UTC time and one can see within the red oval that the moisture maximum was nearly 175 % of normal (normal for this product is from the NASA Water Vapour project period of 1988 to 1999 that will be extended in the next few years). To complement this product, inserted into the lower right was the GFS computer model initial analysis standardised anomalies that clearly confirmed the maximum moisture being three to four standard deviations above normal. Quite clearly from satellite and other meteorological information, the event evolving on the evening of 13–14 September 2012 over Central Europe was going to be a long heavy rainfall event and a potentially high impact event that could result in flooding.

Slide 6 is the Multi-sensor Precipitation Estimate for around 00:00 UTC on the 14th. The Multi-sensor Precipitation Estimate (MPE) is an instantaneous rain rate product that is derived from the IR-data of the geostationary EUMETSAT satellites by continuous re-calibration of the algorithm with rain-rate data from polar orbiting microwave sensors, and can confirm the beginning of the heavy rain heading into western Greece. Rainfall results for the next several days that confirmed our suspicions of a high impact heavy rain event are shown in slides 7 and 8.

Slide 7 shows the more timely NOAA/NESDIS geostationary-IR only Global Hydro-Estimator (H-E) multiday rainfall totals from 12:00 UTC 13 September through 12:00 UTC 17 September when most of the rain fell over the maximum (close to 200mm) rainfall area.

Slide 8 shows a confirmation of the H-E rainfall estimates with the less timely NASA TRMM-based precipitation estimates that are provided on a global 0.25°x0.25° grid over the latitude band 50° N-S. In this case the rainfall that covers a seven-day period is based on a TRMM-calibrated merger of all available TMI, SSMIS, and AMSU-B/MHS precipitation estimates along with geosynchronous infrared estimates calibrated by the merged-microwave data.

Reference

Kusselson, S.J., 1993: The operational use of passive microwave data to enhance precipitation forecasts. Preprints: 13th Conference on Weather Analysis and Forecasting, Vienna, VA, Amer. Meteor. Soc. 434-438.