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  • Annual summaries dataset of Heatwaves in Europe, as defined by the Excess Heat Factor
    Publication . Oliveira, Ana; Lopes, António; Correia, Ezequiel
    The dataset includes six yearly time series of six Heatwave (HW) aspects/metrics (or statistical summaries) calculated from the E-OBS dataset (v19eHOM, available in https://www.ecad.eu/download/ensembles/downloadversion19.0eHOM.php) following the Excess Heat Factor (EHF) methodology implemented in the ClimPACT tool, in compliance with the guidelines established by the Expert Team on Climate Change Detection and Indices (ET-SCI). These aspects correspond to annual summaries of HW frequency, duration and intensity, considering solely the events occurring during the extended summer season (from June to September). Input Daily Maximum (TX) and Minimum (TN) near-surface air temperature data were retrieved from a European gridded dataset (E-OBS) – the ensemble homogenized version ‘19.0eHOM’, at 0.1° × 0.1° spatial resolution, covering the European region, and retrieved from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service. The E-OBS dataset is based on station observations, provided by the European Climate Assessment & Dataset. The here-presented HW aspects/summaries outputs of the ClimPACT tool correspond to the gridded annual statistical summaries of HW – these are detected based on the positive Excess Heat Factor (EHF) days, an HW index based on the human health response to heat extremes. The summaries include: (i) annual Number of Heatwaves (HWN); (ii) annual Heatwave Days Frequency (HWF); (iii) annual Maximum Heatwave Duration (HWD); (iv) annual Mean Heatwave Magnitude (HWM); and (v) annual Maximum Heatwave Amplitude (HWA). In addition, the annual maximum Heatwave Severity (HWS) was calculated, by dividing HWA by the 85th percentile of the positive EHF days. These annual time series can be used in HW-related studies focusing on the European region, particularly those focusing on climatology, trends, and impacts on human health.
  • Heatwaves and summer urban heat islands: a daily cycle approach to unveil the urban thermal signal changes in Lisbon, Portugal
    Publication . Oliveira, Ana; Lopes, António; Correia, Ezequiel; Niza, Samuel; Soares, Amílcar
    Lisbon is a European Mediterranean city, greatly exposed to heatwaves (HW), according to recent trends and climate change prospects. Considering the Atlantic influence, air temperature observations from Lisbon’s mesoscale network are used to investigate the interactions between background weather and the urban thermal signal (UTS) in summer. Days are classified according to the prevailing regional wind direction, and hourly UTS is compared between HW and non‐HW conditions. Northern‐wind days predominate, revealing greater maximum air temperatures (up to 40 °C) and greater thermal amplitudes (approximately 10 °C), and account for 37 out of 49 HW days; southern‐wind days have milder temperatures, and no HWs occur. Results show that the wind direction groups are significantly different. While southern‐wind days have minor UTS variations, northern‐wind days have a consistent UTS daily cycle: a diurnal urban cooling island (UCI) (often lower than –1.0 °C), a late afternoon peak urban heat island (UHI) (occasionally surpassing 4.0 °C), and a stable nocturnal UHI (1.5 °C median intensity). UHI/UCI intensities are not significantly different between HW and non‐HW conditions, although the synoptic influence is noted. Results indicate that, in Lisbon, the UHI intensity does not increase during HW events, although it is significantly affected by wind. As such, local climate change adaptation strategies must be based on scenarios that account for the synergies between potential changes in regional air temperature and wind.
  • An urban climate-based empirical model to predict present and future patterns of the Urban Thermal Signal
    Publication . Oliveira, Ana; Lopes, António; Correia, Ezequiel; Niza, Samuel; Soares, Amílcar
    Air temperature is a key aspect of urban environmental health, especially considering population and climate change prospects. While the urban heat island (UHI) effect may aggravate thermal exposure, city-level UHI regression studies are generally restricted to temporal-aggregated intensities (e.g., seasonal), as a function of time-fixed factors (e.g., urban density). Hence, such approaches do not disclose daily urban-rural air temperature changes, such as during heatwaves (HW). Here, summer data from Lisbon's air temperature urban network (June to September 2005-2014), is used to develop a linear mixed-effects model (LMM) to predict the daily median and maximum Urban Thermal Signal (UTS) intensities, as a response to the interactions between the time-varying background weather variables (i.e., the regional/non-urban air temperature, 2-hours air temperature change, and wind speed), and time-fixed urban and geographic factors (local climate zones and directional topographic exposure). Results show that, in Lisbon, greatest temperatures and UTS intensities are found in 'Compact' areas of the city are proportional to the background air temperature change. In leeward locations, the UTS can be enhanced by the topographic shelter effect, depending on wind speed - i.e., as wind speed augments, the UTS intensity increases in leeward sites, even where sparsely built. The UTS response to a future urban densification scenario, considering climate change HW conditions (RCP8.5, 2081-2100 period), was also assessed, its results showing an UTS increase of circa 1.0 °C, in critical areas of the city, despite their upwind location. This LMM empirical approach provides a straightforward tool for local authorities to: (i) identify the short-term critical areas of the city, to prioritise public health measures, especially during HW events; and (ii) test the urban thermal performance, in response to climate change and urban planning scenarios. While the model coefficient estimates are case-specific, the approach can be efficiently replicated in other locations with similar biogeographic conditions.