2001_2019_ERA5_MonthlyPrecipitation_FourierProcessed

<p>This is a set of images produced by temporal Fourier analysis of Monthly precipitation provided by the ERA5 dataset for 2001-2019 from the European Centre for Medium-Range Weather Forecasting. The imagery summarises a key environmental indicator, incorporating seasonal dynamics, for the MOOD study area.&nbsp;</p> <p><strong>Abstract: </strong></p> <p>Monthly precipitation values were extracted from ERA5 files for the years 2019 through 2020, and then processed by a temporal Fourier processing algorithm. A stepwise system of thresholds and interpolations screened erroneous values and bridged gaps in the time series. The smoothed series was sampled at 5-day intervals and transformed into a set of sine curves describing annual, bi-annual, and tri-annual fluctuations. For each of these curves, the Fourier algorithm generated images expressing the amplitude, phase, and variance. Other outputs recorded the mean, minimum, and maximum of the time series, and error measured during the Fourier transform. For a detailed description of the Fourier algorithm and its output, please see the article by Scharlemann et al., 2008 (https://doi.org/10.1371/journal.pone.0001408)<br>&nbsp;Sea pixels were masked with a MODIS land/sea layer and the images were projected from sinusoidal to geographic. The MOOD study region was a subset of global images. Idrisi rasters were converted to Geotiff format&nbsp; to give data users more flexibility<br>&nbsp;<br><strong>File naming scheme:</strong><br>&nbsp;The ER at the start of each file name indicates that the image covers the wider Europe and North Africa region included in the MOOD study area and is in geographic projection.<br>&nbsp;<br>&nbsp;The next two characters identify the channel:<br>&nbsp;20 for precipitation and 19&nbsp;refers to the year timeline of 2001-2019.<br>&nbsp;<br>&nbsp;The last two characters of each file name denote the output from Fourier processing:<br>&nbsp;a0 - mean<br>&nbsp;mn - minimum<br>&nbsp;mx - maximum<br>&nbsp;a1 - amplitude of annual cycle<br>&nbsp;a2 - amplitude of bi-annual cycle<br>&nbsp;a3 - amplitude of tri-annual cycle<br>&nbsp;p1 - phase of annual cycle<br>&nbsp;p2 - phase of bi-annual cycle<br>&nbsp;p3 - phase of tri-annual cycle<br>&nbsp;d1 - variance in annual cycle<br>&nbsp;d2 - variance in bi-annual cycle<br>&nbsp;d3 - variance in tri-annual cycle<br>&nbsp;da - combined variance in annual, bi-annual, and tri-annual cycles<br>&nbsp;vr - variance in raw data<br>&nbsp;<br>&nbsp;</p> <p>&nbsp;<br><strong>Projection + EPSG code:</strong><br>Latitude-Longitude/WGS84 (EPSG: 4326)<br><strong>Spatial extent:</strong><br>Extent &nbsp;-32.0000000000000000,10.0000000000000000 : 68.9999999999999574,81.9999999999999716<br><strong>Spatial resolution:</strong><br>0.0083333 deg (approx. 1000 m) &nbsp;<br><strong>Temporal resolution:</strong><br>2001-2019<br><strong>Pixel values:</strong></p> <p>Parameter Fourier Variable Image values are<br>&nbsp; A0, A1, A2, A3, Index Value * 10<br>&nbsp;ALL D1,D2,D3,Da Percentages<br>&nbsp;ALL E1,E2,E3 Percentages<br>&nbsp;ALL P1,P2.P3 Months*100. (Jan=100)</p> <p>&nbsp;</p> <p><br><strong>Source:&nbsp;</strong><br>&nbsp;Monthly Precipitation for ERA5 from the European Centre for Medium-Range Weather Forecasting (ECMWF)<br><strong>Software used:</strong><br>Codes for modelling are in Python and C++<br>The software used for map production is ESRI ArcMap 10.8</p> <p><strong>License: </strong>CC-BY-SA 4.0<br><strong>Processed by:</strong><br>ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project</p>