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Article

Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)

by
Elias Massoud
1,*,
Theresa Massoud
2,
Bin Guan
1,3,
Agniv Sengupta
1,
Vicky Espinoza
4,
Michelle De Luna
5,
Colin Raymond
1 and
Duane Waliser
1,3
1
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
2
Department of Chemistry, Faculty of Arts and Science, University of Balamand Dubai, Dubai, UAE
3
Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, USA
4
School of Engineering, University of California Merced, Merced, CA 95343, USA
5
Geosciences and Environment, California State University, Los Angeles, CA 90032, USA
*
Author to whom correspondence should be addressed.
Water 2020, 12(10), 2863; https://doi.org/10.3390/w12102863
Submission received: 17 August 2020 / Revised: 9 October 2020 / Accepted: 12 October 2020 / Published: 14 October 2020
(This article belongs to the Section Hydrology)
Browse Figures
Versions Notes

Abstract

:
This study investigates the historical climatology and future projected change of atmospheric rivers (ARs) and precipitation for the Middle East and North Africa (MENA) region. We use a suite of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5, historical and RCP8.5 scenarios) and other observations to estimate AR frequency and mean daily precipitation. Despite its arid-to-semi-arid climate, parts of the MENA region experience strong ARs, which contribute a large fraction of the annual precipitation, such as in the mountainous areas of Turkey and Iran. This study shows that by the end of this century, AR frequency is projected to increase (~20–40%) for the North Africa and Mediterranean areas (including any region with higher latitudes than 35 N). However, for these regions, mean daily precipitation (i.e., regardless of the presence of ARs) is projected to decrease (~15–30%). For the rest of the MENA region, including the Arabian Peninsula and the Horn of Africa, minor changes in AR frequency (±10%) are expected, yet mean precipitation is projected to increase (~50%) for these regions. Overall, the projected sign of change in AR frequency is opposite to the projected sign of change in mean daily precipitation for most areas within the MENA region.

1. Introduction

The Middle East and North Africa (MENA) region lies at the interface of the subtropics and mid-latitudes, and future changes in precipitation in this region are subject to influences from various factors, such as the Hadley circulation and winter storms [1]. These storms can manifest as atmospheric rivers (ARs), which are long and narrow filaments of water vapor transport that release precipitation in the form of rain or snow upon making landfall or encountering uplift [2]. Recent events have shown that ARs in MENA can produce extremely heavy precipitation, and they can provide both significant benefits as well as major costs to water resources management in the region. Given this recent awareness of the significance of ARs in the region, we investigate in this study the importance of ARs for MENA precipitation, and we estimate how ARs and precipitation will change in the future in MENA.
Changes in precipitation in a warmer climate are governed by many factors. A primary physical mechanism for increases in precipitation is the enhanced water vapor content in a warmer atmosphere, which enhances moisture convergence into storms [3]. Projecting regional changes in precipitation is difficult because of uncertainty in projecting changes in the large-scale circulation [4], and because of the chaotic nature of the Earth system [5,6], which makes it very difficult to accurately predict weather and climate past a few weeks. For MENA, observed changes in precipitation have included a mix of increases, decreases, or little change, depending on location and season [7,8,9]. Across the globe, high-latitude regions are generally projected to become wetter, whereas the subtropical regions are projected to become drier [10]. Since the MENA region lies between these two areas, there is significant uncertainty about the sign and magnitude of future changes to precipitation in much of the region. However, since atmospheric water vapor will increase with increasing temperatures, confidence is high that precipitation extremes will increase in frequency and intensity in the future throughout the MENA region and the rest of the globe [11,12]. This study investigates the impact of a warmer climate on mean and extreme precipitation in the MENA region where the impact of ARs is starting to get recognized.
We examine extreme precipitation in this study by focusing on ARs, which can have a significant impact on hydrologic events, such as droughts or floods, in many regions of the world, including western North America [13,14,15,16,17], Europe [18,19], western South America [20], and other regions [21,22]. ARs play an important role for regional precipitation, which can include rain or snow [14,23,24,25]. They can also cause large flooding events [15,16,17,26,27,28] and extreme winds [29], as well as mitigating droughts [30]. This large impact has motivated an increasing number of studies on ARs related to climate change (as reviewed in [31]), with many studies focusing on Europe [18,32,33,34] and Western North America [23,35,36,37,38,39,40,41,42,43]. Espinoza et al. (2018) [11] and Massoud et al. (2019) [12] provided a global view of AR frequency and strength in future climates, and showed that increases in both frequency and strength of ARs is expected to occur globally by roughly 25–50%, depending on the area of interest.
Various studies have included the MENA region as part of their study domain, such as the International Coordinated Regional Climate Downscaling Experiment (CORDEX-MENA) initiative. This program has published numerous studies about climate, such as temperature and precipitation analyses, in the MENA region [7,44,45,46,47]. Regarding ARs in the MENA region, studies have just started to populate the literature. Akbary et al. (2019) [48] analyzed the historical spatio-temporal changes of ARs and their pathways in the MENA region, finding a decrease in frequency over the period of 1984–2013. Esfandiari and Lashkari (2020ab) [49,50], investigated ARs in Iran, looking at the effect of ARs on cold-season heavy precipitation events, as well as their pathways and landfall locations. Dezfuli (2020) [51] reviewed a rare atmospheric river event that happened in March 2019, named AR Dena, which caused recorded floods across Iran and the Arabian Peninsula. AR activity in the MENA region is noted in the context of the global analysis of ARs in Guan and Waliser (2019) [52].
Through the Coupled Model Intercomparison Project, or CMIP, the climate modeling community provides a suite of model simulations and projections (e.g., CMIP5, [53]) to characterize uncertainty arising from model differences and greenhouse-gas concentration pathways, as well as to characterize uncertainty inherent in the climate system due to internal variability [54,55]. These ensembles provide an important resource for examining the uncertainties in future AR and precipitation projections. The climate model (CMIP5) historical simulations and the future (RCP8.5) scenario simulations are processed through an AR detection algorithm [56,57] in our study, to catalogue AR conditions with various metrics accounted for, such as AR frequency and intensity.
This study is set up as follows. First, we introduce the study domain and highlight various individual AR events that stand out in the historic record, including one of the longest regional ARs on record which occurred in January 1994, and another event named AR Dena, which occurred in March 2019, notable for its very heavy precipitation. Then, we calculate the fraction of precipitation that comes from ARs for this region, showcasing how ARs can account for nearly half of the total precipitation for some local areas. We then show historical estimates of AR dynamics and mean daily precipitation over the MENA region, along with mean wind vector fields and sea level pressure, both seasonally and annually. Finally, we use the CMIP suite of models to conduct a novel investigation of historical and future changes in ARs and precipitation for the MENA region. Although studies have performed similar analyses on global scales [11,12], this is the first study to investigate future changes in ARs and precipitation for the MENA region using the CMIP multi-model ensemble.

2. Materials and Methods

2.1. MENA Domain

ARs ordinarily require some type of lifting mechanism for condensation to occur and to produce precipitation, and in many cases, this mechanism comes in the form of orographic (mountain) lifting. In the MENA region, the areas of Turkey and Iran (see Figure 1) are rich with mountain ranges that absorb the impact of ARs and where local precipitation from ARs is generally very heavy. However, climatological mean precipitation is generally low for most of this region, where the domain is mostly covered by the Sahara and Arabian deserts, which are home to the largest stretch of desert in the world.
We show a topographic map of the MENA region in Figure 1. This plot utilizes topographic, bathymetric and shoreline data from the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center’s ETOPO1 Global Relief Model [58]. This is a 1 arc-minute model of the Earth’s surface, which was developed from diverse global and regional digital datasets and then shifted to a common horizontal and vertical datum. In general, 1 arc-minute equates to 1/60th of 1 degree. So, depending on the region of the globe, 1 arc-minute is equal to ~2 km. The map in Figure 1 shows the elevation (m) for the MENA domain, and 3 arbitrary transects that intersect the region are shown with red dashed lines and are highlighted in the subpanels on the right. The high elevation in certain areas are highlighted here, such as the mountain terrains in Turkey and Iran, which causes orographic lifting of ARs and creates favorable conditions to greatly enhance precipitation.

2.2. Observed Precipitation, Winds, and Mean Sea Level Pressure

Monthly precipitation is obtained from the German Meteorological Service’s (Deutscher Wetterdienst, DWD, in Offenbach am Main, Germany) Global Precipitation Climatology Centre (GPCC; [59]) version 8 dataset on a 0.5° continental grid (provided online by the Physical Sciences Division of the NOAA Earth System Research Laboratory; https://www.esrl.noaa.gov/psd/data/gridded/data.gpcc.html). This is a quality-controlled gridded dataset obtained from worldwide station data for the period 1891 to 2016.
This analysis also uses the National Centers for Environmental Prediction (NCEP) reanalysis [60] to characterize the circulation field, in particular the 925-hPa winds and the mean sea level pressure (MSLP). This retrospective analysis product of atmospheric fields is available on a 2.5° × 2.5° global grid, for the period January 1949 to the present. On seasonal and annual timescales like the ones we show, Carvalho (2019) [61] shows that the National Aeronautics and Space Administration’s (NASA) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2; [62]) and NCEP are very similar.

2.3. Integrated Water Vapor Transport (IVT)

This study uses specific humidity and wind fields from MERRA-2 reanalysis in its computation of the IVT field. The MERRA-2 reanalysis product, available on a 0.5° latitude by 0.625° longitude grid for the period 1980–present, assimilates satellite observations not available to its predecessor, MERRA, with additional updates to the Goddard Earth Observing System (GEOS) model and its analysis scheme.

2.4. AR Detection Algorithm

Guan and Waliser (2015) [56] developed a global AR detection algorithm, which was updated and validated later with in situ and dropsonde data [57]. This algorithm is employed for our study, which is based on a combination of the IVT magnitude, direction, and geometry characteristics, to objectively identify ARs. Contiguous regions of enhanced IVT transport are first identified from magnitude thresholding (i.e., grid cells with IVT above the seasonally and regionally dependent 85th percentile) and further filtered using directional and geometry criteria requirements. The detection algorithm was applied to both reanalysis data and the CMIP5 models in their native resolution. For the CMIP5 models, once the AR dynamics are estimated, results are re-gridded using a bi-linear function and ensuring that sharp gradients were not a problem in the interpolating scheme, as was done in Espinoza et al. (2018) [11] and Massoud et al. (2019) [12]. This global algorithm had over ~90% agreement in detected AR landfall dates with regional algorithms that focused on regions with different climatologies, such as western North America [63], Britain [28], and East Antarctica [64], which provides us with confidence in using this algorithm for our MENA region application. Note, these algorithms are best viewed as complementary to one another, and the agreement rate should not be interpreted in terms of “hits” and “misses”. The agreement rate mentioned above for other regions gives us confidence that the results we investigate in our current study would not heavily change if another detection algorithm was to be developed or used. In that regard, it is noted that the Iran-focused study in Esfandiari and Lashkari (2020ab) [49,50] used AR IVT percentile and geometry criteria largely following our global algorithm used here. We direct readers to Guan and Waliser (2015) for more information on the AR detection algorithm used in our study.

2.5. Climate Model Simulations of Atmospheric Rivers and Precipitation

The historical simulations and future projections under the representative concentration pathway RCP8.5 warming scenario [65,66,67] informing the Fifth Assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) are used in the present analysis. All model outputs are re-gridded on a common grid using bi-linear interpolation when needed. Then, all the metrics investigated in this study are computed (see below). The coarse resolution of GCMs means that our analysis reflects regional-scale processes, and not finer-resolution ones such as the effects of small topographic variations, and that our results should be interpreted with this caveat in mind. However, we would not expect that a higher-resolution model would meaningfully affect the broad patterns we see, such as the latitudinal shifts of ARs due to climate change. All CMIP5 models used in this study are the ‘r1i1p1’ version of the model simulations; the ‘precipitation flux (pr)’ variable was analyzed for these simulations. Similar to Espinoza et al. (2018) [11] and Massoud et al. (2019) [12], we define ARs using integrated vapor transport (IVT) values constructed from daily values of 3-D wind and water vapor model outputs at four pressure levels between 500 and 1000 hPa (data described in Lavers et al. 2015 [68]; their Table S1). IVT values are calculated at native model resolutions ranging from 1.125° to 2.813°. The climate model (CMIP5) historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096, following Lavers et al. (2015) [68], Espinoza et al. (2018) [11], and Massoud et al. (2019) [12]. This time frame is determined as the period that contains the maximum number of overlapping years among all models, with 24 years for both the historical and future runs.
The AR frequency in a given period for each grid cell is calculated as the percentage of time steps where an AR is detected, ranging from 0% (no ARs) to 100% (an AR at every time step). A typical value around the globe is around 10%, which translates to AR conditions being present 10% of the time steps, or around 36 days per year.

3. Results

3.1. Individual AR Events in MENA

We begin by using our comprehensive dataset to survey some of the most notable MENA ARs documented in previous literature. This comparison facilitates a uniform perspective on AR extremes in this region. Akbary et al. (2020) [48] highlighted several AR events, and showed that about 13 ARs occur each year on average (range of 6–25 ARs per year) in the MENA region, and the majority of them occur in the fall and winter seasons. They showed that most ARs for the MENA region originate over the North Atlantic Ocean and enter Africa from Mauritania and Senegal, then pass Egypt, Saudi Arabia and Iran before dissipating in Afghanistan and Pakistan (e.g., Figure 1). They also showed that the Red Sea is a major source of moisture that feeds ARs on their path in this region. Here, we survey the diversity of ARs in MENA by examining the pathways and intensities of notable observed events (Figure 2).
We show in Figure 2 (top left panel) the longest AR storm documented in the literature for the MENA region which occurred in January 1994, and stretched from western North Africa to the Himalayan Mountains with a length of 12,000 km. This AR event is also shown in Akbary et al. (2020) [48], in their Figure 3h. Note, this AR is the longest on record up to 2013, however it is not the longest in the AR database used here.
The next AR event we document here is shown in Figure 2 (top right panel), which displays an AR that occurred in December 2008. This AR originated from a similar location in the Atlantic, however the pathway led towards Europe and resulted in extreme rainfall over Italy. The AR is also documented in Akbary et al. (2020) [48], in their Figure 3. Moreover, an individual AR event that occurred in December 2016 is shown here in Figure 2 (bottom left panel). Similar to the previous AR, this event originated from the Atlantic and the pathway led towards Europe, with even heavier extreme rainfall than the previous AR. To the best of our knowledge, this AR is not documented in any other study in the literature.
Another significant AR event that occurred in the MENA region was AR Dena, which happened in March 2019, had a maximum length of 9000 km, and produced extreme precipitation, as shown in Figure 2 (bottom right panel). Dezfuli (2020) [51] highlighted this event and showed how during March 2019, record floods across the Middle East were driven largely by moisture transported from the North Atlantic Ocean. Iran, in particular, was substantially affected by the floods (c.f. [69]), with widespread damage to infrastructure and a death toll of at least 76. The nearly 9000-km-long AR propagated across the MENA region, and was fed by additional moisture from several other sources on its pathway. The simultaneous presence of a midlatitude system and a subtropical jet facilitated the moisture supply and convergence, while the orographic forcing of the Zagros Mountains induced record rainfall. According to Dezfuli (2020) [51], this event presented a compelling example of rapid shifts from prolonged drought to frequent floods and, potentially, the notion that “extremes become more extreme” in a changing climate [30,70].

3.2. Climatology of ARs and Precipitation in the MENA Region

The Middle East does not often appear in surveys of previous AR literature (although c.f. [71]), highlighting the novel aspects of studying ARs there. However, several well-documented examples exist [72,73]. In our results, we find that the MENA region is one of the few locations around the globe in which precipitation from ARs can account for a significant portion of the total annual precipitation (Figure 3). Figure 3 shows the fraction of precipitation associated with ARs for the MENA region. The darker shades of red contours indicate the regions where ARs account for more than 30% of the total rainfall, with some areas having nearly half of their precipitation coming from ARs, especially in Iran. This indicates that ARs are not only very significant for water resource management in the area, and that ARs can help this region escape drought conditions, but that ARs can also provide enough rainfall to produce deadly floods. This highlights the importance of studying ARs in this region.
Figure 4 shows the AR IVT (kg/m/s) and frequency (% of time steps) for the MENA region, shown annually as well as for each season, over the analysis period of 1981–2018. ARs in the MENA region are mostly a cool-season phenomenon (Figure 4a–c,e), with the summer months being absent of ARs due to high-pressure systems induced by the downwelling branches of the Hadley Cell and South Asian summer monsoon (Figure 4d). One of the most accurate ways to represent the possibility of storms (and their precipitation, if they do happen) is mid-tropospheric relative humidity, which is less than 20% over the entire Middle East in the summer (JJA), versus 30–50% in the winter (DJF), and for comparison, it is 60–70% in summer over central India [74]. These low values are due to large-scale descent through most of the free troposphere, induced by the South Asian summer monsoon. Figure 5 displays the seasonal and annual precipitation and wind dynamics for MENA. Comparing the AR climatology with the overall mean precipitation and wind climatologies for the region (Figure 4 and Figure 5) shows similar dynamics, with some minor variants.
Figure 6 shows the CMIP5 simulations for ARs and precipitation for this region. Based on the CMIP5 multi-model ensemble on historical AR frequency (Figure 6, top panel), some regions of MENA experience up to 8% AR frequency on average. The CMIP5 multi-model ensemble on historical mean daily precipitation (Figure 6, bottom panel) demonstrates that, although ARs play an active role in the region, the majority of the area has a desert landscape, with very little to no rainfall. However, some regions in the mountains of Turkey and Iran show a higher mean daily precipitation rate, with up to 5 mm/day for certain areas, where a large fraction of this rainfall comes from ARs (as shown in Figure 3). A previous back-trajectory analysis confirms this conclusion [75].

3.3. Projected Future AR Frequency and Precipitation in MENA

The CMIP5 model ensemble is simulated to 2100, and we investigate the RCP8.5 scenario, which represents a high-emissions future. Figure 7 (top panel) shows the projected future AR frequency for the MENA region, represented as the percent of timesteps that show AR conditions. Figure 7 (bottom panel) shows the projected future mean daily precipitation, represented in mm/day. To investigate the values of the projected changes for AR frequency and mean daily precipitation for the MENA region, we subtract the historical values in Figure 6 from the future values in Figure 7. This gives us the raw values for projected future changes, which are shown in Figure 8 and discussed in the next paragraph.
The top panel of Figure 8 shows the raw projected changes for AR frequency in the MENA region, and the saturated red colors in this plot indicate the large region (mostly in mid-latitude Eurasia) that is expected to see increases in AR frequency (up to +3% of timesteps). This is seen as far south as the North African coast of the Mediterranean Sea, as well as in Turkey and Iran. The rest of the region, however, is not expected to see any significant change in AR frequency. For the raw values of projected future changes in mean daily precipitation (bottom panel of Figure 8), we see different signs of change depending on the area. For the Mediterranean Sea and countries that border it, decreases in precipitation are expected (−0.3 mm/day), and for the Arabian Peninsula, there is an expected increase in precipitation (+0.3 mm/day), in line with previous studies [76,77]. In Figure 8, the significance of these results is highlighted using a paired-sample t-test with p = 0.05, and grids indicating regions where the projected change in AR frequency or precipitation are statistically significant are marked with black dots.
To further elucidate these changes, we take a look at the relative future changes where we ‘normalize’ the future change values shown in Figure 8 by the historical values shown in Figure 6, to get a relative sense of how much the change compares to the historical climatology. In other words, we take the raw change values shown in Figure 8 and we divide by the historical values shown in Figure 6. These relative change values are shown in Figure 9. Again, Eurasia is expected to see increases in AR frequency of up to 50% from historical values. Through these relative changes, new regions emerge in importance (left panel of Figure 9), such as the Arabian Peninsula (up to +20% from historical values). For the relative values of projected future changes in mean daily precipitation (right panel of Figure 9), we see different signs of change depending on the area. Similar to the raw expected changes, the Mediterranean basin should expect decreases in precipitation (down −30% from historical values). However, for the Arabian Peninsula, there is an expected increase in precipitation (up +50% from historical values). Therefore, the stretch of countries from the Horn of Africa to the United Arab Emirates should expect an increase in precipitation, which will have some contributions from ARs (left panel of Figure 9), but also from other sources of precipitation (right panel of Figure 9).
Overall, we calculated two metrics to show future changes in AR frequency and precipitation. The first (shown in Figure 8) shows the direct change and provides insight on how much the future changes are (in magnitude). The second metric (shown in Figure 9) shows relative changes (in percentage values) compared to the historical climatology. Again, the maps showing black dots in Figure 8 indicate where the future change estimates are statistically significant for the metrics and values shown in Figure 7, Figure 8 and Figure 9.

3.4. Statistical Significance of Expected Changes

The usefulness of climate simulations for understanding significant future changes hinges on a proper accounting of their uncertainties [78]. For example, if the model spread is large enough, then the expected change, as reported by a multi-model ensemble mean, may not be meaningful. Different models can present very different results, and the spread of the multi-model ensemble can inform the significance of the future change results [79,80]. To this end, we show in Figure 10 the spread of the multi-model ensemble for the CMIP5 simulations of AR frequency and mean daily precipitation for the historical (blue), RCP8.5 (red), and the projected differences (green), presented as latitudinal averages. The green bars surrounding the difference curve indicate 95% significance, which is determined using 2 times the standard deviation of the multi-model ensemble spread.
For initial investigation of statistical significance of future changes in AR frequency, we refer to the black dots in the top panel of Figure 8, which indicate where the future change estimates are statistically significant at the p = 0.05 level based on a paired-sample t-test. For an additional investigation of statistical significance, the left panel in Figure 10 shows that areas with higher latitude than 35 N are expected to see significant increases in AR frequency in the future. Comparing the values in the future change curves of Figure 10 (red, RCP8.5) with the historical values (blue, historical), we see that projected changes (green, difference) in AR frequency are significant for regions at higher latitudes than 35 N. Furthermore, Massoud et al. (2019) showed the natural variability of atmospheric rivers around the globe (c.f. their Figure 9), and reported that, for the MENA region, the natural variability of AR frequency can range from 1–2 [% of time steps], which is lower than the expected changes reported here for areas higher than 35 N showing an increase of +3 [% of time steps].
For an initial investigation of statistical significance of future changes in precipitation, we refer to the black dots in the bottom panel of Figure 8, which indicate where the future change estimates are statistically significant at the p = 0.05 level based on a paired-sample t-test. For an additional investigation of statistical significance, the right panel of Figure 10 shows the spread of precipitation simulations based on latitudinal averages. This panel shows an expected increase in precipitation from 5–20 N, and a projected decrease in precipitation around 40 N (black ‘x’ marks indicate latitudes with statistical significance). These results coincide with the regions highlighted in Figure 8 and Figure 9, which show how the Mediterranean basin and Europe should expect a decrease in precipitation, and for the Arabian Peninsula, an increase in precipitation. For much of the region from 5–20 N, the results are shown to be statistically significant (e.g., Figure 8), however for much of the rest of the region, it is difficult to distinguish changes in future precipitation around MENA, and Figure 8, Figure 9 and Figure 10 show that that there is little to no projected changes for most of the area. This is not surprising for a variable like precipitation, whose projections of future changes are usually uncertain compared to the multi-model ensemble spread or the natural variability of precipitation for many regions of the globe, especially for arid and semi-arid locations [70,81,82].

4. Summary and Discussion

In this study, we investigated the historical climatology and future projected change of atmospheric rivers (ARs) and precipitation for the Middle East and North Africa (MENA) region using a suite of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5 historical and RCP8.5). We showed (Figure 3) the subregions where ARs account for more than 30% of the total rainfall, with some areas having nearly half of their rain coming from ARs, which signified the importance of studying ARs in this region. We highlighted various individual AR events (Figure 2), showing one of the longest AR events in recorded history for the MENA region, which occurred on January 1994, and AR Dena which happened in March 2019 and caused widespread damage. These events presented a compelling example of shifts from prolonged drought to frequent floods and potentially the notion of “extremes become more extreme” in a changing climate [30,51,70]. In essence, the absence of ARs in these regions can cause droughts over a multi-year period, and the emergence of extreme AR activity following a drought can be beneficial for water resource management, but can also cause widespread destruction through extreme winds and flooding.
We found in Figure 8 and Figure 9 that increases in AR frequency are projected for much of the region (~+50% from historical values). For changes in mean precipitation, much of the region surrounding the Mediterranean Sea showed an expected decrease (down −30% from historical values), yet for the Arabian Peninsula, there is an expected increase in precipitation (up +50% from historical values). The stretch of countries from the Horn of Africa to the United Arab Emirates should expect an increase in precipitation, which will have some contributions from ARs (left panel of Figure 9, and Figure 3), but also from non-AR sources of precipitation (right panel of Figure 9). We showed where the future change estimates have significance (Figure 8), based on a paired-sample t-test with p = 0.05. We found that projected changes in AR frequency are statistically significant, with the mean projected change being several times larger than the standard deviation of the model ensemble spread, especially for mid-latitude regions with higher latitude than 35 N (Figure 10). For precipitation, the projected changes are significant only for certain areas, and for much of the region, there are little to no projected changes in future precipitation (Figure 10).
Our results indicate that the projected change in AR frequency is opposite in sign to the projected change of mean precipitation for most areas within the MENA region. Together with the large fraction of precipitation associated with ARs, this finding underscores the importance of ARs to the MENA region and thus of understanding the thermodynamic and dynamic drivers of the changes we describe here. Understanding these changes can be beneficial for policy makers and water resources managers in the region. This paper presented the first case study to use CMIP model simulations to investigate historical and future changes in ARs and precipitation for the MENA region.

Author Contributions

Conceptualization, E.M., T.M., and D.W.; Data curation, E.M., B.G., A.S., V.E., and M.D.L.; Formal analysis, E.M., T.M., B.G., A.S., C.R. and D.W.; Funding acquisition, D.W.; Methodology, E.M., T.M., and D.W.; Project administration, E.M., and D.W.; Resources, E.M., B.G., A.S., V.E., and D.W.; Supervision, E.M. and D.W.; writing—original draft preparation, E.M. and T.M.; writing—review and editing, E.M., T.M., B.G., A.S., V.E., M.D.L., C.R. and D.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research and the APC was partly funded by RCMES award 104967 281945.02.03.03.67.

Acknowledgments

The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2020. All data used in this study are publicly available. The CMIP5 model output data are available via https://cmip.llnl.gov/cmip5/data_portal.html. The derived data used for estimating the historical and future AR frequencies are available at https://figshare.com/articles/Global_Atmospheric_Rivers_Historic_and_Future_/8317079. The AR catalogue is available at https://ucla.app.box.com/v/ARcatalog.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Topographical map of the Middle East and North Africa (MENA) using the NOAA National Geophysical Data Center’s ETOPO1 Global Relief Model. The map shows the elevation (m) for the MENA domain. The three transects that intersect the region are shown with red dashed lines and are highlighted in the subpanels on the right. The high elevation in certain areas are highlighted here, such as the mountain terrains in Turkey and Iran.
Figure 1. Topographical map of the Middle East and North Africa (MENA) using the NOAA National Geophysical Data Center’s ETOPO1 Global Relief Model. The map shows the elevation (m) for the MENA domain. The three transects that intersect the region are shown with red dashed lines and are highlighted in the subpanels on the right. The high elevation in certain areas are highlighted here, such as the mountain terrains in Turkey and Iran.
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Figure 2. Individual AR cases: (Top left) AR event in January 1994. (Top Right) AR event in December 2008. (Bottom Left) AR event in December 2016. (Bottom Right) AR event Dena in March 2019. (Legend) Green: AR shape from the AR detection algorithm. Arrows: integrated water vapor transport (IVT) vectors (not shown if magnitude smaller than 100 kg/m/s). Shading: IVT magnitude (kg/m/s). Blue: 2-day cumulative precipitation (in mm) centered on the time step shown in the panel title.
Figure 2. Individual AR cases: (Top left) AR event in January 1994. (Top Right) AR event in December 2008. (Bottom Left) AR event in December 2016. (Bottom Right) AR event Dena in March 2019. (Legend) Green: AR shape from the AR detection algorithm. Arrows: integrated water vapor transport (IVT) vectors (not shown if magnitude smaller than 100 kg/m/s). Shading: IVT magnitude (kg/m/s). Blue: 2-day cumulative precipitation (in mm) centered on the time step shown in the panel title.
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Figure 3. A representation of the fraction of annual precipitation that is associated with atmospheric rivers. The darker shades of red contours indicate areas where ARs account for more than 30% of the total rainfall, with central Iran having nearly half of its precipitation coming from ARs.
Figure 3. A representation of the fraction of annual precipitation that is associated with atmospheric rivers. The darker shades of red contours indicate areas where ARs account for more than 30% of the total rainfall, with central Iran having nearly half of its precipitation coming from ARs.
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Figure 4. AR frequency (% of time steps) and IVT (kg/m/s) plots for the MENA region, shown (a) annually and (b–e) for each season. Figures show the AR occurrence frequency at 6-hourly time steps over the analysis period of 1981–2018.
Figure 4. AR frequency (% of time steps) and IVT (kg/m/s) plots for the MENA region, shown (a) annually and (b–e) for each season. Figures show the AR occurrence frequency at 6-hourly time steps over the analysis period of 1981–2018.
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Figure 5. The climatological precipitation (in green contours, mm/day) from Global Precipitation Climatology Centre (GPCC) ver. 8, the mean wind vector field at 925-hPa (black arrows, m/s) and the mean sea level pressure (blue contours, hPa) from NCEP Reanalysis, shown (a) annually, and (b–e) for each individual season. The period of analysis is 1951–2015.
Figure 5. The climatological precipitation (in green contours, mm/day) from Global Precipitation Climatology Centre (GPCC) ver. 8, the mean wind vector field at 925-hPa (black arrows, m/s) and the mean sea level pressure (blue contours, hPa) from NCEP Reanalysis, shown (a) annually, and (b–e) for each individual season. The period of analysis is 1951–2015.
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Figure 6. (Top) Historical AR frequency (% of timesteps) for the MENA region, as represented by CMIP5 models. Similar to Figure 4a, the top panel of this figure represents the annual historical AR frequency, but shown here for CMIP5 models. (Bottom) Historical mean daily precipitation (mm/day) for the MENA region as represented by CMIP5 models. Similar to Figure 5a, the bottom panel of this figure represents the annual historical mean daily precipitation, but shown here for CMIP5 models. The CMIP5 historical simulations range from 1979–2002.
Figure 6. (Top) Historical AR frequency (% of timesteps) for the MENA region, as represented by CMIP5 models. Similar to Figure 4a, the top panel of this figure represents the annual historical AR frequency, but shown here for CMIP5 models. (Bottom) Historical mean daily precipitation (mm/day) for the MENA region as represented by CMIP5 models. Similar to Figure 5a, the bottom panel of this figure represents the annual historical mean daily precipitation, but shown here for CMIP5 models. The CMIP5 historical simulations range from 1979–2002.
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Figure 7. (Top) Projected future AR frequency (% of timesteps) for the MENA region obtained from CMIP5 models (RCP85). This figure represents the same process as the AR frequency shown in Figure 6 (top), but for the future simulations. (Bottom) Projected future mean daily precipitation (mm/day) for the MENA region obtained from CMIP5 models (RCP85). This figure represents the same process as the mean daily precipitation shown in Figure 6 (bottom), but for the future simulations. The CMIP5 future (RCP8.5) scenario simulations range from 2073–2096.
Figure 7. (Top) Projected future AR frequency (% of timesteps) for the MENA region obtained from CMIP5 models (RCP85). This figure represents the same process as the AR frequency shown in Figure 6 (top), but for the future simulations. (Bottom) Projected future mean daily precipitation (mm/day) for the MENA region obtained from CMIP5 models (RCP85). This figure represents the same process as the mean daily precipitation shown in Figure 6 (bottom), but for the future simulations. The CMIP5 future (RCP8.5) scenario simulations range from 2073–2096.
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Figure 8. (Top) Raw values for the projected change in future AR frequency [% of timesteps], calculated as the difference between projected future values and historic climatology for the MENA region. (Bottom) Raw values for the projected change in future mean daily precipitation [mm/day] for the MENA region. The CMIP5 historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096. Grids with a black dot indicate where the projected change in AR frequency or precipitation is statistically significant, based on a paired-sample t-test with p = 0.05.
Figure 8. (Top) Raw values for the projected change in future AR frequency [% of timesteps], calculated as the difference between projected future values and historic climatology for the MENA region. (Bottom) Raw values for the projected change in future mean daily precipitation [mm/day] for the MENA region. The CMIP5 historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096. Grids with a black dot indicate where the projected change in AR frequency or precipitation is statistically significant, based on a paired-sample t-test with p = 0.05.
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Figure 9. (Left) Relative values for the projected change in future AR frequency, calculated as the percent change in projected future values compared to historic climatology (%) for the MENA region. (Right) Relative values for the projected change in future mean daily precipitation (%) for the MENA region. The CMIP5 historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096.
Figure 9. (Left) Relative values for the projected change in future AR frequency, calculated as the percent change in projected future values compared to historic climatology (%) for the MENA region. (Right) Relative values for the projected change in future mean daily precipitation (%) for the MENA region. The CMIP5 historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096.
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Figure 10. Multi-model ensemble for the CMIP5 historical simulations (blue), the RCP85 simulations (red), and the difference bars showing 95% significance range for the projected differences (green), and latitudes with statistical significance marked with a black ‘x’. The 95% bounds are determined using 2 times the standard deviation of the multi-model ensemble spread. These plots are shown as latitudinal averages. (Left) This panel shows the AR frequency plots, and areas with higher latitudes than 35 N are expected to see significant increases in AR frequency in the future. (Right) This panel shows the precipitation plots, showing an expected increase in precipitation from 5–20 N, and slight decrease in precipitation around 40 N. These results coincide with the regions highlighted in Figure 9. The CMIP5 historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096.
Figure 10. Multi-model ensemble for the CMIP5 historical simulations (blue), the RCP85 simulations (red), and the difference bars showing 95% significance range for the projected differences (green), and latitudes with statistical significance marked with a black ‘x’. The 95% bounds are determined using 2 times the standard deviation of the multi-model ensemble spread. These plots are shown as latitudinal averages. (Left) This panel shows the AR frequency plots, and areas with higher latitudes than 35 N are expected to see significant increases in AR frequency in the future. (Right) This panel shows the precipitation plots, showing an expected increase in precipitation from 5–20 N, and slight decrease in precipitation around 40 N. These results coincide with the regions highlighted in Figure 9. The CMIP5 historical simulations range from 1979–2002 and the future (RCP8.5) scenario simulations range from 2073–2096.
Water 12 02863 g010

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MDPI and ACS Style

Massoud, E.; Massoud, T.; Guan, B.; Sengupta, A.; Espinoza, V.; De Luna, M.; Raymond, C.; Waliser, D. Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA). Water 2020, 12, 2863. https://doi.org/10.3390/w12102863

AMA Style

Massoud E, Massoud T, Guan B, Sengupta A, Espinoza V, De Luna M, Raymond C, Waliser D. Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA). Water. 2020; 12(10):2863. https://doi.org/10.3390/w12102863

Chicago/Turabian Style

Massoud, Elias, Theresa Massoud, Bin Guan, Agniv Sengupta, Vicky Espinoza, Michelle De Luna, Colin Raymond, and Duane Waliser. 2020. "Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA)" Water 12, no. 10: 2863. https://doi.org/10.3390/w12102863

APA Style

Massoud, E., Massoud, T., Guan, B., Sengupta, A., Espinoza, V., De Luna, M., Raymond, C., & Waliser, D. (2020). Atmospheric Rivers and Precipitation in the Middle East and North Africa (MENA). Water, 12(10), 2863. https://doi.org/10.3390/w12102863

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