# Monthly Precipitation over Northern Middle Atlas, Eastern Morocco: Homogenization and Trends
###### Abstract  
The lack of a complete and reliable data series often represents the main difficulty in carrying out climate studies. Diverse causes, such as human and instrumental errors, false and incomplete records, and the use of obsolete equipment in some meteorological stations, give rise to inhomogeneities that do not represent climatic reality. This work in the northern part of the Moroccan Middle Atlas used 22 meteorological stations with sometimes-incomplete monthly precipitation data from 1970 to 2019. The homogenization and estimation of the missing data were carried out with the R software package Climatol version 3.1.1. The trends in the series were quantified by the Mann-Kendall nonparametric test. The results obtained show a low root mean square error (RMSE), between the original and homogenized data, of between 0.5 and 38.7 mm per month, with an average of 8.5 mm. Rainfall trends for the months of December through June are generally downward. These negative trends are significantly stronger in the southern and eastern parts of the study area, especially during the month of April (the wettest month). On the other hand, July shows positive trends, with 71% of stations having an increasing precipitation tendency, although only five (or 1/3) of these are statistically significant. From August to November, generally positive trends were also observed. For these months, the percentage of series with a positive and significant trend varied between 55 and 77%. monthly precipitation; homogenization; Climatol; trend analysis; northern Middle Atlas; Morocco +
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studies have been carried out on the spatio-temporal evolution of climatic parameters as an indicator of these variations [9; 10; 11; 12]. However, unlike temperatures which exhibit consistently large changes coherent with global warming conditions, precipitation exhibits high temporal variability and inconsistent spatial patterns in terms of trends [13; 14]. Yet, precipitation is of great importance in various climatic settings, especially in semi-arid and arid regions where it is the main source of surface water [15]. It is necessary to study the variability of precipitation on a small scale, in order to deepen our knowledge of rainfall patterns and therefore on the availability of water resources in the different territorial units in a given region [16]. Here, we focus on the northern Middle Atlas region. Such work is very interesting for decision-makers and actors in several regions, given that this area is considered a water tower for Morocco, feeding most wadis and rivers. Particularly in semi-arid areas, rainfall is the most important element of the climate, both for populations and natural environments [17]. The occurrence and variability of rainfall largely determine the availability of water resources, the species that can live and the crops that can grow in different regions of the world. The study of rainfall variability, in the context of climate change, draws its importance from water and food security concerns that are strongly raised today. However, direct analysis of the raw data can be misleading due to non-climatic disturbances (such as errors in the observations or in their transmission) and changes in the instrument used both in the location of the observatory, and in its immediate environment [16; 18; 19]. Therefore, quality control and the assessment of the homogeneity of climate data are necessary before undertaking climate research [20]. Moreover, series of climatic data may contain gaps, which requires a reconstitution of the missing values. To avoid erroneous conclusions about the detected changes, the best way to deal with heterogeneity in climatic data series is to examine each station's metadata for accurate information about the historical context of the station, such as changes in measuring device type and observation site, and other relevant documented information [21].