# Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation
## 3 Results and Discussions
### Monitoring the Heatwave Impact on LAI and SSM Using Remote Sensing  
Time-series on Figure 1 illustrate monthly anomalies for CGLS products GEOV2 LAI (over 2000-2018, Figure 1a) and ASCAT SSM (over 2008-2018, Figure 1b) averaged over the domain of interest (presented by Figure 2). On both time-series, July is highlighted in red and the horizontal dashed lines represent the value of July 2018. As for LAI (Figure 1a), July 2018 exhibits a large negative anomaly, greater than twice standard deviations (stdv) on average. Such a low value is not observed in this 19-yr time-series for a month of July and only one month, in summer 2003: August 2003 presents an anomaly value below than that of July 2018. In 2003, large parts of Europe were affected by record-breaking temperature in summer (e.g., [74]). June to October 2018 presented negative LAI anomalies. Table 2 presents the fraction of the considered domain affected by negative anomalies greater than 2 stdv for all months of July over 2000-2018 for GEOV2 LAI and 2008-2018 for ASCAT SSM. In July 2018, it represents nearly 19% of the domain for LAI, the largest percentage observed in 19-year. Not only the 2018 summer heatwave lead to very large negative anomaly values in LAI but it has affected a large part of the domain. Figure 2a shows maps of anomaly for July 2018 for GEOV2 LAI.  
Figure 2a shows that most of the UK, Northern France, Belgium, Netherlands, Denmark, Germany and Czech-republic present anomaly values greater than -2 stdv. ASCAT SSM exhibits large negative anomalies for July 2018 (Figure 2b) with values greater than -1 standard deviation. Such low values were also observed in July 2008 and 2015, and it is worth noticing from Table 2 that in July 2018, 10% of the domain was affected by anomalies greater than -2 stdv, while only -2% and -3% for July 2008 and 2015. Figure 2b (maps on anomaly for July 2018 for ASCAT SSM) shows that the southern part of the domain presents large positive anomalies values (e.g., north of Spain, in the Balkans) and that  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c c} \hline  & July & July & July & July & July & July & July & July & July & July & July & July & July & July & July & July \\  & 2000 & 2001 & 2002 & 2003 & 2004 & 2005 & 2006 & 2007 & 2008 & 2009 & 2010 & 2011 & 2012 & 2013 & 2014 & 2015 & 2016 & 2017 & 2018 \\ \hline \hline \multicolumn{11}{c}{GEOV2 Leaf Area Index} & 5.0 & 0.4 & 0.2 & 5.0 & 0.6 & 0.8 & 1.8 & 1.1 & 0.2 & 0.03 & 0.7 & 0.7 & 0.3 & 0.7 & 0.2 & 2 & 0.1 & 0.6 & 19 \\ \hline ASCAT SWI & N/A & N/A & N/A & N/A & N/A & N/A & N/A & N/A & N/A & 2 & 0.04 & 1.7 & 0.2 & 1.5 & 0.5 & 0.06 & 3.0 & 0.01 & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Percentage of the domain with monthly anomalies lower than -2 stdv for satellite derived GEOV2 Leaf Area Index, ASCAT surface soil moisture. Only months of July are represented.  
Figure 1: Monthly Anomaly time-series (scaled by the standard deviation) of satellite derived (**a**) GEOV2 Leaf Area Index over 2000–2018 and (**b**) Surface Soil Moisture over 2008–2018 from the Copernicus Global Land Service averaged over the domain (presented by Figure 2). Months of July are highlighted in red, straight dashed lines represent values for July 2018.  
Figure 2: Monthly anomalies (scaled by standard deviation, expressed in units of standard deviation) maps for July 2018 for (**a**) GEOV2 Leaf Area Index with respect to 2000–2018 and (**b**) Surface Soil Moisture with respect to 2008–2018 from the Copernicus Global Land Service. Green/red colors represent positive/negative anomalies in units of standard deviation.  
good geographical agreement between GEOV2 LAI and ASCAT SSM anomalies is found. While some winter months show large negative anomalies in ASCAT SSM, e.g., December 2010, 2011, this might be related to frozen conditions not accounted for and interpreted as dry conditions.