Morocco, located at the southern margin of the Mediterranean climate-change hotspot, is exposed to a rapidly evolving precipitation regime whose national-scale characterization remains incomplete. This study delivers an integrated assessment of the spatio-temporal variability and trends of precipitation and its extremes over the country during the most recent World Meteorological Organization (WMO) climate-normal period (1991–2020), based on daily observations from 31 synoptic stations operated by the Direction Générale de la Météorologie (DGM). Trends in annual, seasonal and monthly precipitation were quantified using the non-parametric Mann–Kendall test combined with Sen’s slope estimator, while the structural transformation of the rainfall regime was characterized through three indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI): the Consecutive Dry Days (CDDs), the Simple Daily Intensity Index (SDII) and the amount of precipitation from very wet days (R95pTOT). The results reveal an apparent tendency toward a negative trend, with a predominance of negative precipitation trends in winter and early spring, most pronounced in February, that reach statistical significance at only a limited number of stations, partly offset by a spatially coherent wetting in November over central and eastern Morocco. The joint analysis of the three ETCCDI indices indicates a north–south contrasted reorganization: northern stations exhibit longer dry spells coexisting with intensified extreme rainfall, whereas southern stations show a generalized weakening of both intensity and extremes. These findings point to a structural shift toward more episodic and contrasted precipitation regimes, with the wet season starting later, ending earlier and concentrating rainfall into fewer but more intense events. The analysis provides an updated observational baseline for the validation of CMIP6 based regional projections and for the design of climate-resilient water and agricultural strategies in Morocco.

Marine renewable energies can be considered as the world’s largest untapped renewable energy resource. The demand for forecasting power generation at sub-seasonal to seasonal (S2S) timescales has been growing to aid in managing the production and storage of the offshore renewable energies. At these timescales, atmospheric circulation is predominantly governed by recurrent weather regimes (WRs). In this study, we investigated the impact of winter WRs on both wind and wave potential energies along the Ibero-Moroccan Atlantic region. An optimal number of 7 WRs based on 500-hPa geopotential height winter anomalies was selected via the Weighted Information Criterion, these regimes were specifically defined to distinguish their respective impacts on wind and wave power generation. Results show that the positive phase of the North Atlantic Oscillation is associated with the maximum of the wave and wind power, especially over the Iberian coasts and Bay of Biscay (up to + 100

General and regional climate models (GCMs/RCMs) exhibit many systematic biases, which affects the simulation accuracy of the real precipitation patterns and consequently the associated hydrological changes. The common approach used to reduce errors in the climate model output is to apply bias correction methods (BCMs) which attempt to adjust the climate simulation by its observation counterpart. In this study, we applied BCM on simulated rainfall over the Bouregrag basin (Morocco) from CanRCM4 CORDEX RCM using linear SCALING method (SCALING), gamma quantile mapping (GQM) and empirical quantile mapping (EQM). Owing to its high performance compared to the others, we applied the EQM method on climate projections under the RCP4.5 scenario. Results showed a decrease up to -50% in the monthly rainfall for the period 2041-2060 with the exception of August and December exhibiting an increase between +20% and +78%. This study supports the need to bias correct climate data before their use in hydrological models where the bias could be irreversible.

Waves generated by winds can transport a large amount of energy across the oceans with little loss. Many countries are currently developing promising technologies to harvest this energy by converting it into electricity. Studies dedicated to wave potential assessment are of primary importance for spotting the suitable locations to install wave energy converters as well as for designing wave energy devices. This paper presents an analysis of wave energy potential near Essaouira coast in Morocco, through the use of ocean wave hindcast data and high-resolution numerical modeling. The wave data were extracted from the European Integrated Ocean Waves for Geophysical and other Applications (IOWAGA) dataset for a period of 27 years. Results showed that the annual average power is about 23.72 kW/m which is equivalent to annual wave energy of 199.12 MWh/m. It was also found that the bulk of the wave energy is generated by waves with significant height between 1.5 and 3.0 m and mean wave energy periods between 10 and 12.5 s. The wave energy in the studied area exhibits a noticeable variability at different time scales. The numerical simulations enabled to identify three important locations suitable for wave energy exploitation. Among these potential sites, the one situated between Essaouira and Cape Sim presents many advantages and appears to be the most favorable.

The present study investigates aerosols distributions and a strong Sahara dust-storm event that occurred by early August 2018, in the South of Morocco. We used columnar aerosol optical depth (AOD), Angstrom Exponent (AE) and volume size distributions (VSD) as derived from ground-based observations by 2 AERONET (AErosol RObotic NETwork) sun-photometers at Saada (31.63°N, 8.16°W) and Ouarzazate (30.93°N, 6.91°W) sites, over the periods 2004–2019 and 2012–2015, respectively. The monthly seasonal distributions of AOD, AE, and VSD showed a seasonal trend dominated by the annual cycle, with a maximum aerosol load during summer (July–August) and a minimum in winter (December–January), characterized by a coarse mode near the radius of 2.59 μm and a fine mode at the radius of 0.16 μm, respectively. Indeed, this study showed that aerosol populations in southern Morocco are dominated by Saharan desert dust, especially during the summer season. The latter can sometimes be subject of dust-storm events. The case study presented in this paper reports on one of these events, which happened in early August 2018. The HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model was used to simulate air-mass back-trajectories during the event. In agreement with ground-based (AERONET sun-photometers) and satellite (CALIOP, MODIS and AIRS) observations, HYSPLIT back-trajectories showed that the dust air-mass at the 4-km layer, the average height of the dust plume, has crossed southern Morocco over the Saada site, with a westward direction towards the Atlantic Ocean, before it changed northward up to the Portuguese coasts.

K-means cluster analysis of wintertime 500-hPa geopotential height anomalies allowed identifying seven weather regimes (WRs) describing the atmospheric variability over the Euro-Mediterranean domain. The study of transitions between those WRs provided consistent results with the westward displacement of the blocking nearby northern Europe before the onset of the negative phase of the North Atlantic Oscillation (NAO-). The onset of the latter is, indeed, preceded by the North Atlantic blocking regime (NABl). In addition, we detected a preferred transition from the Scandinavian Blocking (ScBl) to NAO+ through the European Ridge regime (EuRG), which is modulated by active phases of the Madden-Julian Oscillation (MJO). The examination of the relationship between WRs and precipitation over Morocco showed that the NAO- (NAO+) regime is accompanied by more (less) rainy episodes. The investigation of the lagged relationships between the MJO and the WRs depicted the role of an active MJO in Phase 2 as a precursor of the ScBl and of an active MJO in Phase 6 as a precursor of the NABl. The exploration of the 10-15 days lagged impact of the MJO on Moroccan rainfall showed an increase (decrease) of wet (dry) conditions 10 to 15 days after the occurrence of an active MJO in Phases 6 and 8 (Phases 2-3-4). The MJO modulation of the WRs and rainfall patterns over Morocco constitutes an important source of predictability at the medium- and the extended-range (subseasonal) time scales, with potential use by decision makers in key socioeconomic sectors in the region.

The focus of this study is to assess the accuracy of four satellite-based rainfall estimations in Morocco. TRMM3B42V7, ARC2, RFE2.0 and PERSIANN-CDR are evaluated with observations from 19 meteorological stations, at daily and monthly time steps, over different seasons and different classes of topography for the period 2001-2014. Results show that, all satellite datasets reasonably reproduce the mean annual rainfall and the seasonal cycle. In terms of rainfall day statistics, ARC2 and RFE2.0 have performed the best while PERSIANN-CDR exhibited the worst performance. Categorical indices showed that the TRMM3B42V7 product outperforms others in both the boreal summer and the rain shadow area. For the total precipitation, all satellite products underestimate rainfall amount in low and mid elevation, whereas a marked overestimation is observed over the rain shadow area. In terms of rainfall intensity, TRMM3B42V7 exhibits good performance to reproduce high rainfall intensities.

Since the dawn of civilization, the Western Mediterranean region has been a unique path for encounters and exchanges. The stability of the general conditions prevailing in its surrounding was crucial to ensure this vital link between north and south and east and west. However, any imbalance would be the precursor of a harmful domino effect to these environments, where the natural vulnerabilities are combined to a worsening socioeconomic congestion. In both banks, efforts are made not to give way to the fragile balance of water availability and risks. Here, we show that the amount and recurrence of extreme rainfall events contradict with current management scenarios. Our pixel-based assessment of the rain components extracted from the African Rainfall Climatology product reveals an annual increase in the total amount of rainfall and extreme rainfall events. A spatial and a trend analysis of the studied rainfall components were carried out to determine their spatial patterns and magnitude. The cumulative annual rainfall alone will not mean if a year is dry or wet. A wet year can experience great periods of drought, which will have serious repercussions on the socioeconomic and ecological levels. In addition, the increased occurrence of extreme rains can produce floods, intensifying land degradation processes, loss of biodiversity, water availability and economic growth. Decision-makers should be aware that current models of territorial management will not be able to cope with this change and that interdisciplinary cohesion and cross-border actions are the most appropriate solution. Graphical abstract

Air temperature is an important meteorological variable in many fields of our life. However, the availability of air temperature measurements over large geographic areas is often limited by the weather stations spatial distribution inadequacy, their low density and difficulties of data quality and collection. In this context, this study consists to develop four simple models to estimate the three components of air temperature (Tmin, Tmax and Tmean) from remotely sensed land surface temperature (Ts) derived from NOAA-AVHRR images, and based on the international Köppen-Geiger climate classification of Morocco. The results confirmed the existence of good relationships between the three components of measured air temperatures and land surface temperature derived from NOAA-AVHRR images for the main four climate classes of Morocco. The coefficient of determination, R2, varied between 0.69 and 0.80 for Tmin versus Ts, between 0.62 and 0.74 for Tmax versus Ts, and between 0.69 and 0.79 for Tmean versus Ts. The root mean square error varied between 3.1 °C and 3.3 °C for Tmin versus Ts, between 3.2 and 4.1 °C for Tmax versus Ts and between 2.7 and 3.4 °C for Tmean versus Ts. K-fold cross validation method was performed to assess the accuracy and the stability of proposed models. The limited number of proposed models is a great advantage to carry further studies requiring air temperature’s components at larger scale.

The monitoring of drought statewide is a difficult issue especially when the national network of meteorological stations is sparse or do not cover the entire country. In this paper, rainfall satellite estimates derived from Tropical Rainfall Measuring Mission (TRMM) product have been used to evaluate the ability of remote sensing data to study the trends of annual precipitation in Morocco between 1998 and 2012. The standardized precipitation index, SPI, has been chosen to monitor meteorological drought in Morocco. Firstly, the accuracy of TRMM product to estimate annual rainfall was evaluated. Annual precipitations derived from 5113 daily TRMM data were compared to the corresponding rainfall measurements from 23 rain gauges. The results showed a general good linear relationship between TRMM and rain gauges data. When considering annual record, the Pearson correlation coefficient, R², was equal to 0.73 and the root mean square error, RMSE, was equal to 159.8mm/year. The correlation between rain gauge measurements and TRMM rainfall had been clearly improved when working with long-term annual average precipitation. The R² increased to 0.79 and the RMSE decreased to 115,2mm. Secondly, the Mann-kendall tau coefficient, the Theil Sen slope and the contextual Mann-Kendall significance were used to analyze the SPI trends over Morocco. This analysis showed that mainly two regions appeared to be subject of significant trends during the studied period: The extreme north eastern of Morocco manifests a positive SPI trends and is more and more subject of extreme rainfall while the extreme south of the country is suffering from a decrease of annual precipitation which could represent significant socio-economic risks in these areas.