Subseasonal-to-Seasonal Predictability Assessment of an Early Heat Wave in the Eastern Mediterranean in May 2020 ^†

The data used are summarized in Table 1. The WRF simulations were produced using the analyses and forecasts of the Climate Forecast System version 2 (CFSv2) from the National Centers for Environmental Prediction (NCEP). This dataset was selected because it provides all the required meteorological fields (i.e., air temperature, dew point, geopotential heights, winds, etc.) across multiple vertical levels to the stratopause (1 hPa) and, most importantly, the forecast window of this dataset covers an adequate time-range of lateral boundary data for the S2S forecasts. The data are provided by NCEP every 6 h with a spatial resolution of 1° × 1°.

Furthermore, for the predictability estimation of the simulation forecasts, the S2S Prediction Project Database [3] was used (s2s.ecmwf.int and s2s.cma.cn, accessed on 1 March 2021), which provides S2S forecasts from various meteorological centers globally. The real-time data are provided twice per week, daily or weekly (depending on the provider center), with a spatial resolution of 1.5° × 1.5°.

The analysis was based on datasets of reanalysis data, gridded observations, and observations of weather stations from major Greek cities. The reanalysis data were obtained from the ERA5 Copernicus Climate Change Service database (ECMWF—climate.copernicus.eu, accessed on 15 February 2021). ERA5’s spatial resolution is 0.25° × 0.25°, and the gridded data are provided hourly across multiple vertical levels to 1 hPa pressure level (37 pressure levels in total). The gridded observations refer to the E-OBS, which is a daily gridded land-only observational dataset over Europe from the station network of the European Climate Assessment & Dataset (ECA&D) project (ecad.eu, accessed on 10 March 2021). This dataset has a spatial resolution of 0.1° × 0.1° with daily surface variables such as maximum air temperature. The E-OBS surface dataset was also used because of its higher spatial resolution and smaller errors compared to ERA5, in order to produce 95th percentiles of maximum daily air temperature. The weather station observations were obtained from the National Observatory of Athens (NOA) and the database of the National Climatic Data Center of the National Oceanic and Atmospheric Administration (NOAA) (ncdc.noaa.gov, accessed on 15 February 2021). In total, 48 weather stations, including numerous stations in Greece and the surrounding countries, were taken into consideration.

The early heat wave for various major cities in Greece (Athens, Thessaloniki, Heraklion, Larisa, and Patra) according to EHF, based on E-OBS, started at different dates (from 11 to 13 May), but the end of the event occurred simultaneously on 20 May with the passing of a cold front. The heat wave for the area of Thessaloniki, according to EHF (E-OBS), started on 13 May and ended on the 20th, lasting 8 days (Figure 1). According to Nairn et al. [4], it is categorized as a heat wave because the EHF was above zero for at least 3 consecutive days. The EHF based on ERA5 data locates the start of the heat wave on 16 May and the end on the 19th (duration: 4 days). In comparison with the E-OBS, ERA5 shows the peak of the heat wave to be weaker by 30 °C² (Figure 1) and to occur a day later (17th May). This difference is mainly due to the different spatial resolutions of the two datasets and their different production methodologies, as E-OBS consists of gridded observations and ERA5 is a reanalysis dataset.

As mentioned previously, the peak of the heat wave is found at different dates, but the most robust results are provided by EHF with the E-OBS data. EHF (E-OBS) identifies the peak intensity as being on 16th May, which agrees with the maximum air temperatures measured from the weather stations of the National Observatory of Athens (NOA) and the Hellenic National Meteorological Service (HΝMS) across Greece and the surrounding countries (not shown). This day includes the highest maximum air temperatures recorded in Greece during the heat wave. The highest temperature (40 °C) was recorded in Kalamata, and it was approximately 17 °C above the 95th percentile of the maximum air temperature value for the specific date. The highest temperature (41.7 °C) in the whole region was recorded in Aydin, Turkey. Additionally, all stations exceeded their T₉₅max by 4 °C to 17 °C for the 16th of May. Possible reasons for this strong heating are the prolonged low soil moisture accompanied by a blocking high-pressure system. Additionally, a wedge of warm air coming from the Sahara Desert raised the temperature of the lower troposphere and the position of the jet stream northwest of Greece resulted in downward atmospheric movement that led to the amplification of the warming due to thermal compression of the air.

According to the synoptic systems in the vicinity of Greece, at the beginning of the heat wave in the region of Greece, there were stable conditions, with the sea level pressure being approximately 1013 hPa, no fronts were apparent, and surface winds were calm, coming from the SSW and SW. At the end of the heat wave, a cold front approached from the west, bringing cold air masses and lowering the mean daily air temperature across the Eastern Mediterranean. Again, the end of the heat wave fits accordingly to EHF index with the E-OBS data.

The extreme temperatures are also prominent at the lower troposphere. As shown in Figure 2, at an 850 hPa level, the ERA5 data indicate air temperatures higher by 10 standard deviations, or 14 °C higher than the climatological value above the Aegean Sea. The main reason for the severe warming is the strong thermal advection (maximum value: 1.5 °C/h—Western Greece and Albania, not shown) from the southwest for the duration of the event, especially in the western part of Greece. TIhe source of the warm air masses is southeastern Algeria and southwestern Libya, while their path extends north and northeast, affecting southern Italy, Greece and western Turkey.

This study assesses the 850 hPa air temperature forecasts of the global models of ECMWF, UKMO, NCEP, CMA, KMA, and HMCR, as well as the regional WRF predictions produced using CFSv2 data (NCEP) for the period of 8–23 May 2020. The predictability skill of each model is tested for its initializations from 23 to 29 April 2020. In Figure 3, the ROC curves of all forecasts are presented. It appears that most models present a minor ability to forecast the heat wave, with no exceptional performances. Two of the models (UKMO and HMCR) present no skill, as they are very close to the no-skill line (dashed black line).

The three models (from the S2S database) with the highest skill in this case are CMA, KMA and ECMWF. This is quantitatively justified by their AUC scores (Figure 3), which are all above 0.59. The WRF simulations, which include 14 ensemble members for the period of 23–29 April, show relatively high skill scores compared to the six previously mentioned models, with the second highest AUC score.

The comparison between the NCEP model and the WRF model is more robust since WRF uses NCEP data (CFSv2) as the initial and boundary conditions for its simulations. The AUC score of NCEP is 0.57, while the WRF AUC score is 0.61, which shows that the dynamical downscaling to a spatial resolution of 25 km × 25 km yields more skillful predictions of extreme temperatures at 850 hPa at subseasonal timescales. Furthermore, the hit rate for a probability threshold of 17% is twice as high in WRF (HR = 0.75) than in NCEP (HR = 0.37). It is noted from Figure 3 that the skill of NCEP with a forecasting probability of 17% has the same approximate skill as WRF with a probability of 33%. This means that WRF shows higher predictability skill than NCEP due to its higher spatiotemporal resolution and its different parameterization schemes that have been selected.