ARCEME Drought followed by Heavy Precipitation Database

Events are defined based on time series of ERA5-Land [1] variables, aggregated daily by time zone. Daily indicators of evaporative balance Input data are daily aggregates of ERA5-Land [1] total precipitation and reference evapotranspiration (from Singer et al. 2020 [2]). $PE = Precipitation - ReferenceEvapotranspiration$ Accumulation period $p$: 30, 90, 180, 360 days At time $t$ (in local time): $PE_{p,t} = \frac{\sum_{i=0}^{p-1} PE_{t-i}}{p}$ Daily indicator of heavy precipitation For the detection of heavy precipitation, we use the daily maximum of a moving sum over 24h (MP) instead of the total daily precipitation (TP) to ensure that heavy precipitation spreading over two days is flagged as extreme and that the detected event starts on the day in which the heavy precipitation effectively starts. Quantiles Drought For each grid cell $(x,y)$, day-of-year (as Month-Day) quantiles are computed for a reference period (1991-2020), with 31 days sliding windows centered on day-of-year $d$. $q_{d,x,y,p,i}$ for $i \in \left\{0.01, 0.05, 0.1, 0.15, 0.25, 0.5, 0.75, 0.85, 0.9, 0.95, 0.99\right\}$ For February 29, less values are used to compute the quantiles. Heavy precipitation For precipitation, we do not deseasonalize the time series. The quantiles are computed on all values of daily total precipitation ($TP$) greater than 0.0001 meter (rain days) over the reference period (1991-2020). $q_{x,y,TP,i}$ for $i \in \left\{0.01, 0.05, 0.1, 0.15, 0.25, 0.5, 0.75, 0.85, 0.9, 0.95, 0.99\right\}$ Event detection Drought A 0.05 threshold is applied: all $PE$ values below the threshold are flagged as extreme. $DEO_{t,x,y,p} = $ \begin{cases} 1 & \text{if } PE_{t,x,y,p} < q_{d,x,y,p,0.05}\\ 0 & \text{otherwise} \end{cases}To ensure that current conditions are dry, we set an additional condition for $PE_{30}$ in the previous 5 days. $DEO_{t,x,y,30} = $ \begin{cases} 1 & \text{if } PE_{t-i,x,y,30} < q_{d-i,x,y,30,0.05} \text{ for } i \in [1,5]\\ 0 & \text{otherwise} \end{cases} The Discrete Event Occurrences (DEO) are saved in a data cube, encoding the different indicators on different bits. Heavy precipitation We use a local threshold (daily total precipitation greater than 95th percentile of daily total precipitaion of raindays over reference period) combined it with a global threshold. The global threshold is the latitude weighted mean of the 75th percentile of daily total precipitation for all land grid cells. $DEO_{t,x,y,TP} =$ \begin{cases} 1 & \text{if } MP_{t,x,y} > q_{x,y,TP,0.95} \text{ AND } MP_{t,x,y} > q_{0.75,TP|\text{land}}\\ 0 & \text{otherwise} \end{cases} Events labelling DEOs are combined and labelled as individual events through a connected component analysis. The current combination follows the rule: any $DEO_{t,x,y,p}$ for $p \in \{90,180,360\}$ AND $DEO_{t,x,y, 30}$ AND $DEO_{t,x,y,TP} $. Database The database consists of- a zarr Event Cube storing the individual indicators of drought and heavy precipitation from 1991 to 2023 - a zarr Label Cube, with the labelled connected events from 2015 to 2023, obtained from a connected component analysis.- a csv summary table with statistics describing the labelled events. Checksum 7e0d40779e908ebf1f38c0c8ddf28d8b5003a89adaad6dcc6d7ad4855aaedafe labelcube_dhp_era5land_qdoy0.05_ref1991_2020.zarr.zip6cc4616645e6e157c091680245495e5e5191ee03ba3bcbfa316bd35ac01fbbef dhp_era5land_eventcube_qdoy0.05_ref1991_2020.zarr.zip76cbf56199426241ea625d69fd9b31e8defff715ce5e692177858c3bad6a9410 dhpEventStats_2015_2023_qdoy0.05_ref1991_2020.csv.zip References [1] Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., & Thépaut, J.-N. (2021). ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13(9), 4349–4383. https://doi.org/10.5194/essd-13-4349-2021 [2] Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G., MacLeod, D., Quichimbo, E. A., & Michaelides, K. (2021). Hourly potential evapotranspiration at 0.1° resolution for the global land surface from 1981-present. Scientific Data, 8(1), 224. https://doi.org/10.1038/s41597-021-01003-9 Citation Melanie Weynants, Khalil Teber, Miguel D. Mahecha, Fabian Gans. 2025. ARCEME Drought followed by Heavy Precipitation Database. https://doi.org/10.5281/zenodo.15705050 Funding This work was funded by the European Space Agency.