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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Quantifying the Early Snowmelt Event of 2015 in the Cascade Mountains, USA by Developing and Validating MODIS-Based Snowmelt Timing Maps

Spring snowmelt serves as the major hydrological contribution to many watersheds of the US West. Since the 1970s the conterminous western USA has seen an earlier arrival of spring snowmelt. The extremely low snowpack and early melt of 2015 in the Cascade Mountains may be a harbinger of winters to come, underscoring the interest in advancements in spring snowmelt monitoring. Target-of-opportunity and point measurements of snowmelt using meteorological stations or stream gauges are common sources of these data, however, there have been few attempts to identify snowmelt timing using remote sensing. In this study, we describe the creation of snowmelt timing maps (STMs) which identify the day of year that each pixel of a remotely sensed image transitions from "snow-covered" to "no snow" during the spring melt season, controlling for cloud coverage and ephemeral spring snow storms. Derived from the 500 meter MODerate-resolution Imaging Spectroradiometer (MODIS) standard snow map, MOD10A2, this new dataset provides annual maps of snowmelt timing, with corresponding maps of cloud interference and interannual variability in snow coverage from 2001-2015. We first show that the STMs agree strongly with in-situ snow telemetry (SNOTEL) meteorological station measurements in terms of snowmelt timing. We then use the STMs to investigate the early snowmelt event of 2015 in the Cascade Mountains, USA, highlighting the protected areas of Mt. Rainier, Crater Lake, and Lassen Volcanic National Parks. In 2015 the Cascade Mountains experienced snowmelt 41 days earlier than the 2001-2015 average, with 25 percent of its land area melting more than 65 days earlier than average. The upper elevations of the Cascade Mountains experienced the greatest snowmelt anomaly. Our results are relevant to land managers and biologists as they plan adaptation strategies for mitigating the effects of climate change throughout temperate mountains.

snowmelt timing↗
NASA NTRS2018

Extreme Air Pollution Events in Hokkaido, Japan Traced Back to Early Snowmelt and Large-Scale Wildfires Over East Eurasia: Case Studies

To identify the unusual climate conditions and their connections to air pollutions in a remote area due to wildfires, we examine three anomalous large-scale wildfires in May 2003, April 2008, and July 2014 over East Eurasia, as well as how products of those wildfires reached an urban city, Sapporo, in the northern part of Japan (Hokkaido), significantly affecting the air quality. NASA's MERRA-2 (the Modern-Era Retrospective analysis for Research and Applications, Version 2) aerosol re-analysis data closely reproduced the PM2.5 variations in Sapporo for the case of smoke arrival inJuly 2014. Results show that all three cases featured unusually early snowmelt in East Eurasia, accompanied by warmer and drier surface conditions in the months leading to the fires, inducing long-lasting soil dryness and producing environmental conditions conductive to active wildfires. Due to prevailing anomalous synoptic-scale atmospheric motions, smoke from those fires eventually reached a remote area, Hokkaido, and worsened the air quality in Sapporo. In futurestudies, continuous monitoring of the timing of Eurasian snowmelt and the air quality from the source regions to remote regions, coupled with the analysis of atmospheric and surface conditions, may be essential in more accurately predicting the effects of wildfires on air quality.

MERRA-2↗
NASA NTRS2016

Impacts of Snow Darkening by Absorbing Aerosols on Eurasian Climate

The deposition of absorbing aerosols on snow surfaces reduces snow-albedo and allows snowpack to absorb more sunlight. This so-called snow darkening effect (SDE) accelerates snow melting and leads to surface warming in spring. To examine the impact of SDE on weather and climate during late spring and early summer, two sets of NASA GEOS-5 model simulations with and without SDE are conducted. Results show that SDE-induced surface heating is particularly pronounced in Eurasian regions where significant depositions of dust transported from the North African deserts, and black carbon from biomass burning from Asia and Europe occur. In these regions, the surface heating due to SDE increases surface skin temperature by 3-6 degrees Kelvin near the snowline in spring. Surface energy budget analysis indicates that SDE-induced excess heating is associated with a large increase in surface evaporation, subsequently leading to a significant reduction in soil moisture, and increased risks of drought and heat waves in late spring to early summer. Overall, we find that rainfall deficit combined with SDE-induced dry soil in spring provide favorable condition for summertime heat waves over large regions of Eurasia. Increased frequency of summer heat waves with SDE and the region of maximum increase in heat-wave frequency are found along the snow line, providing evidence that early snowmelt by SDE may increase the risks of extreme summer heat wave. Our results suggest that climate models that do not include SDE may significantly underestimate the effect of global warming over extra-tropical continental regions.

GEOS-5↗
NASA NTRS1975

Operational water management applications of snowcovered area observations

An effort was made to evaluate the utility of satellite snowcover observations for seasonal streamflow prediction. On a representative, large watershed(10 to the 5th power to 10 to the sixth power sq km) it was found, based on six years of data, that meteorological satellite observations of snow cover early in the snowmelt season exhibit a relationship to seasonal runoff having a statistically significant coefficient of determination of 0.92. Analyses of LANDSAT-1 snow-cover observations over the Wind River Mountains of Wyoming reveals that for areas with infrequent cloud cover the extent of snowcover and its change with time can be monitored on watersheds as small as 10 sq km in areal extent. The change in the snow cover with time as observed from LANDSAT-1 is found to reflect major differences in seasonal runoff from high altitude (mean altitude 3 km) and low altitude ( 3 km) watersheds. There are quantitative indications that LANDSAT observations over small watersheds could be used in a manner similar to that employed for meteorological satellite observations to relate the percent of a basin snowcovered on a given data to seasonal runoff.

Rango, A.↗
NASA NTRS2019

Possible Impacts of Snow Darkening Effects on the Hydrological Cycle over Western Eurasia and East Asia

In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW Impurity Module (GOSWIM) for the land surface. Two sets of ten-member ensemble experiments for 10 years were carried out forced by prescribed sea surface temperature (2002–2011) with different atmospheric initial conditions, with and without SDE, respectively. Results show that SDE can exert a significant regional influence in partitioning the contributions of evaporative and advective processes on the hydrological cycle, during spring and summer season. Over western Eurasia, SDE-induced rainfall increase during early spring can be largely explained by the increased evaporation from snowmelt. Rainfall, however, decreases in early summer due to the reduced evaporation as well as moisture divergence and atmospheric subsidence associated with the development of an anomalous mid- to upper-tropospheric anticyclonic circulation. On the other hand, in the East Asian monsoon region, moisture advection from the adjacent ocean is a main contributor to rainfall increase in the melting season. A warmer land-surface caused by earlier snowmelt and subsequent drying further increases moisture transport and convergence significantly enhancing rainfall over the region. Our findings suggest that the SDE may play an important role in leading to hotter and drier summers over western Eurasia, through coupled land-atmosphere interaction, while enhancing East Asian summer monsoonal precipitation via enhanced land-ocean thermal contrast and moisture transport due to the SDE-induced warmer Eurasian continent.

snow darkening effect↗
NASA NTRS2018

Impacts of Snow Darkening Effects by Light Absorbing Aerosols on Hydroclimate of Eurasia During Boreal Spring and Summer

In this study, we used the NASA GEOS-5 climate model to investigate the impact of snow darkening by light-absorbing aerosols on the hydro-climate if Eurasia during boreal spring and summer. Two sets of 10-member ensemble model integrations with prescribed sea surface temperature were carried out for 10 simulated years (2002-2011); one includes snow-darkening effects (SDE) by light-absorbing aerosols, and one does not (NSDE). Differences between the two experiments in the hydro-climates over Eurasia were evaluated. Results show that SDE warming is most pronounced during the melting season due to strong snow-albedo feedback in the vicinity of the retreating seasonal snowline. SDE spurs a Wet-First-Dry-Later (WFDL) modulation of the surface energy and water balances, characterized by an accelerated (days-to-weeks) snowmelt along with excessive runoff and a warming and wetting of the land during the early part of the melting season. The fast snowmelt is followed by a prolonged (> months) warming and desiccation of the land, stemming from a deficit of late-season snowmelt water and increased surface evaporation. The prolonged warming and drying of the land atmosphere system persist through the summer, sustained by atmospheric conditions favorable for the development of atmospheric blocking, i.e., higher mid-to-upper tropospheric geopotential height, lower relative humidity, reduced cloudiness and enhanced atmospheric subsidence. Overall, SDE by light absorbing aerosols leads to a warmer and drier boreal summer hydro-climate, increasing the frequency of the top 5% and 1% extreme hot days (as defined by NSDE statistics) over western and northern Eurasia by approximately three-fold and tenfold, respectively.

Snow darkening↗
NASA NTRS2015

Climate-Induced Larch Growth Response Within the Central Siberian Permafrost Zone

Aim: estimation of larch (Larix gmelinii) growth response to current climate changes. Location: permafrost area within the northern part of Central Siberia (approximately 65.8 deg N, 98.5 deg E). Method: analysis of dendrochronological data, climate variables, drought index SPEI, GPP (gross primary production) and EVI vegetation index (both Aqua/MODIS satellite derived), and soil water content anomalies (GRACE satellite measurements of equivalent water thickness anomalies, EWTA). Results: larch tree ring width (TRW) correlated with previous year August precipitation (r = 0.63), snow accumulation (r = 0.61), soil water anomalies (r = 0.79), early summer temperatures and water vapor pressure (r = 0.73 and r = 0.69, respectively), May and June drought index (r = 0.68-0.82). There are significant positive trends of TRW since late 1980s and GPP since the year 2000. Mean TRW increased by about 50%, which is similar to post-Little Ice Age warming. TRW correlated with GPP and EVI of larch stands (r = 0.68-0.69). Main conclusions: within the permafrost zone of central Siberia larch TRW growth is limited by early summer temperatures, available water from snowmelt, water accumulated within soil in the previous year, and permafrost thaw water. Water stress is one of the limiting factors of larch growth. Larch TRW growth and GPP increased during recent decades.

permafrost thaw↗
NASA NTRS1978

HCMM energy budget data as a model input for assessing regions of high potential groundwater pollution

The author has identified the following significant results. In early April 1978, heavy spring runoff from snowmelt caused significant flooding along a portion of the Big Sioux River Basin in southeastern South Dakota. The flooded area was visible from surrounding areas on a May 15 HCMM IR test image. On May 15, the flood waters had receded but an area of anomalous residual high soil moisture remained. The high soil moisture area was not visible on a HCMM day visible test image of the same scene, or on LANDSAT imagery. To evaluate the effect of water table depth on surface temperatures, thermal scanner data collected on September 5 and 6, 1978 at approximate HCMM overpass times at an altitude of 3650 m were analyzed. Apparent surface temperatures measured by the scanner included emittance contributions from soil surface and the land cover. Results indicated that the shallow water tables produced a damping of the amplitude of the diurnal surface temperature wave.

Moore, D. G.↗
NASA NTRS2015

Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

Growing↗
NASA NTRS2020

Montana Water Resources: Developing a Composite Moisture Index Utilizing NASA Earth Observations for Drought Monitoring in the Missouri River Basin

The Missouri River Basin provides irrigation water for a substantial part of the domestic agricultural sector within the United States. Drought events pose a significant threat to the economic livelihoods of dependent individuals, industries, and ecosystems (e.g. farmers, local tribes, hydroelectric power, wildlife). In 2017 alone, the Missouri River Basin experienced a severe drought that resulted in a $2.6 billion loss to the U.S. Northern Plains. In response to such events, organizations throughout the basin, such as the Montana Climate Office, have dedicated efforts for drought monitoring and communicating relevant information to local stakeholders. In an effort to aid regional decision-making capabilities, the project team partnered with the Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, and NOAA Regional Climate Services, Central Region to create a monthly Composite Moisture Index (CMI) that relies on NASA Earth observations from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Soil Moisture Active Passive (SMAP) mission. From these satellites, as well as the NOAA NWS National Operational Hydrologic Remote Sensing Center’s Snow Data Assimilation System (SNODAS), our team aggregated climate datasets including soil moisture, snow cover, snow depth, and snow water equivalent to compute a CMI that indicates regional moisture conditions during the winter months. The March CMI values produced over the Missouri River headwater subbasin strongly correlate (r = 0.75) with spring and early summer stream discharge, demonstrating the use of this metric to indicate moisture conditions for the snowmelt and growing seasons.

DEVELOP Project Summary↗
NASA NTRS2021

Montana Water Resources: Developing a Composite Moisture Index Utilizing NASA Earth Observations for Drought Monitoring in Montana and the Missouri River Basin

The Missouri River Basin provides irrigation water for a substantial part of the domestic agricultural sector within the United States. Drought events pose a significant threat to economic livelihoods of dependent individuals, industries, and ecosystems (e.g., farmers, local tribes, hydroelectric power, wildlife). In 2017 alone, the Missouri River Basin experienced a severe drought that resulted in a $2.6 billion loss to the U.S. Northern Plains. In response to such events, organizations throughout the basin, such as the Montana Climate Office, have dedicated efforts for drought monitoring and communicating relevant information to local stakeholders. In an effort to aid regional decision-making capabilities, the project team partnered with the Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, and NOAA Regional Climate Services, Central Region to create a monthly Composite Moisture Index (CMI) that relies on NASA Earth observations from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Soil Moisture Active Passive (SMAP) mission. From these satellites, as well as the NOAA NWS National Operational Hydrologic Remote Sensing Center Snow Data Assimilation System (SNODAS), our team aggregated climate datasets including soil moisture, snow cover, snow depth, and snow water equivalent to compute a CMI that indicates regional moisture conditions during the winter months. The March CMI values produced over the Missouri River headwater subbasin strongly correlate (r = 0.75) with spring and early summer stream discharge, demonstrating the use of this metric to indicate moisture conditions for the snowmelt and growing seasons.

DEVELOP Tech Paper↗
NASA NTRS2019

Definition of a Technology Validation Mission for P-band Reflectometry using Signals of Opportunity

Root-Zone Soil Moisture (RZSM) (moisture profile in the top meter of soil) and Snow Water Equivalent (SWE) (total snow pack water content) are identified as priority target variables in the ESAS 2017 decadal survey [1] with critical roles in hydrology and water management. RZSM estimates are vital for understanding multiple Earth system processes and forecasting (for example, droughts [2]). Simultaneous knowledge of surface and RZSM could enable a breakthrough in estimating key unobserved hydrologic fluxes and reduce uncertainty in net ecosystem exchange (NEE), carbon balance [3] discharge estimates, and crop yield forecasts [4] .With the high albedo and insulating properties of snow, monitoring, SWE accumulation would provide a key constraint on the potential runoff during spring ablation while monitoring SWE disappearance rates would provide a key constraint on SWE partition into runoff vs. infiltration/recharge. [5] demonstrated that knowledge of early-spring SWE generally contributes most to streamflow forecast skill in the Western U.S. SWE is also a source of water storage that provides the water resources during spring snowmelt. Despite such potentially transformative contributions, accurate RZSM and SWE measurements are unattainable with current technology. While active/passive L-band methods (e.g. SMAP, SMOS) can reliably retrieve surface soil moisture in the top 5 cm of soil [6], [7]. RZSM estimates are only available through model assimilation of brightness temperatures with a radiative transfer and land surface models [8]. SWE estimation uses multi-frequency passive microwave techniques (e.g. [9]-[11]), which have significant problems with deeper snow and in forested and mountainous environments [12]. Signals of opportunity (SoOp) in P-band (200-400 MHz) is a new remote sensing technique with the capability of estimating both essential hydrologic variables, RZSM and SWE, circumventing many of the aforementioned limitations under all weather conditions day and night. SoOp is the re-utilization of existing powerful satellite transmissions within bands allocated for communications or navigation. P-band SoOp sensitivity to soil moisture has been demonstrated in an airborne experiment over Oklahoma in 2016 [13]. Recent theory [14] and experiments [15] have also confirmed that the reflection coefficient phase is proportional to SWE.

Garrison, J. L.↗
NASA NTRS1997

Sensitivity of Spruce/Moss Boreal Forest Net Ecosystem Productivity to Seasonal Anomalies in Weather

Abstract. A process-oriented, daily time step model of a spruce/moss boreal ecosystem simulated 1994 and 1995 productivity for a Boreal Ecosystem-Atmosphere Study site near Thompson, Manitoba. Simulated black spruce net primary productivity (NPP) was 139 g C m(exp -2) in 1994 and 112 in 1995; feathermoss NPP was 13.0 g C m(exp -2) in 1994 and 9.7 in 1995; decomposition was 126 g C m(exp -2) in 1994 and 130 in 1995; net ecosystem productivity (NEP) was an uptake of 26.3 g C m(exp -2)in 1994 and 2.5 in 1995. A very dry period for the first half of the 1995 summer was the major cause of that year's lower productivity. Sensitivity simulations explored the impact of 2-month long warmer, cooler, wetter, and drier spells on ecosystem productivity. Warmer summers decreased spruce NPP, moss NPP, and NEP; cooler summers had the opposite effect. Earlier snowmelt (due to either warmer spring temperatures or reduced winter precipitation) increased moss and spruce NPP; later snowmelt had the opposite effect. The largest effect on decomposition was a 5% reduction due to a drier summer. One-month droughts (April through October) were also imposed on 1975 base year weather. Early summer droughts reduced moss annual NPP by -30-40%; summer droughts reduced spruce annual NPP by 10%; late summer droughts increased moss NPP by about 20% due to reduced respiration; May to September monthly droughts reduced heterotrophic respiration by about 10%. Variability in NEP was up to roughly +/- 35%. Finally, 1975 growing season precipitation was redistributed into frequent, small rainstorms and infrequent, large rainstorms. These changes had no effect on spruce NPP. Frequent rainstorms increased decomposition by a few percent, moss NPP by 50%, and NEP by 20%. Infrequent rainstorms decreased decomposition by 5%, moss NPP by 50% and NEP by 15%. The impact of anomalous weather patterns on productivity of this ecosystem depended on their timing during the year. Multiyear data sets are necessary to understand this behavior and test these types of models.

Frolking, Steve↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Mars: Hydrology, Drainage, and Valley Systems

The titles in this section include: 1) Analysis of Orientation Dependence of Martian Gullies; 2) A Preliminary Relationship between the Depth of Martian Gullies and the Abundance of Hydrogen on Near-Surface Mars; 3) Water Indicators in Sirenum Terra and around the Argyre Impact Basin, Mars; 4) The Distribution of Gullies and Tounge-shaped Ridges and Their Role in the Degradation of Martian Craters; 5) A Critical Evaluation of Crater Lake Systems in Memnonia Quadrangle, Mars; 6) Impact-generated Hydrothermal Activity at Gusev Crater: Implications for the Spirit Mission; 7) Characterization of the Distributary Fan in Holden NE Crater using Stereo Analysis; 8) Computational Analysis of Drainage Basins on Mars: Appraising the Drainage Density; 9) Hypsometric Analyses of Martian Basins: A Comparison to Terrestrial, Lunar, and Venusian Hypsometry; 10) Morphologic Development of Harmakhis Vallis, Mars; 11) Mangala Valles, Mars: Investigations of the source of Flood Water and Early Stages of Flooding; 12) The Formation of Aromatum Chaos and the Water Discharge Rate at Ravi Vallis; 13) Inferring Hydraulics from Geomorphology for Athabasca Valles, Mars; 14) The Origin and Evolution of Dao Vallis: Formation and Modification of Martian Channels by Structural Collapse and Glaciation; 15) Snowmelt and the Formation of Valley Networks on Martian Volcanoes; 16) Extent of Floating Ice in an Ancient Echus Chasma/Kasei Valley System, Mars.

Source record↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability – the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA’s Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

Drought monitoring↗
NASA NTRS2020

How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

Socially and economically costly extreme weather events have become more prevalent in the last decade. Monitoring and early warning systems could help mitigate the impact of such events by allowing people to better prepare themselves to manage their responses to these events. One significant element of an effective warning system is soil moisture because it is a key determinant of the exchange of water and heat energy between the land and atmosphere, the partitioning of precipitation between infiltration and runoff, and therefore has an influence on weather patterns and streamflow. In addition, soil moisture governs plant water availability - the key to crop yield forecasting. For these reasons, a wide range of organizations use soil moisture information to better predict and monitor climate and weather phenomena such as floods and droughts. By improving soil moisture estimates, it may be possible to improve the monitoring and early warning systems upon which these organizations rely, and hence better mitigate the impacts of extreme weather events. Through case studies, this article discusses several uses of soil moisture data products from NASA's Soil Moisture Active Passive (SMAP) mission to help improve soil moisture-related monitoring and early warning systems.

agriculture↗
NASA NTRS1975

Employment of satellite snowcover observations for improving seasonal runoff estimates

Low resolution meteorological satellite and high resolution earth resources satellite data were used to map snowcovered area over the upper Indus River and the Wind River Mountains of Wyoming, respectively. For the Indus River, early Spring snowcovered area was extracted and related to April through June streamflow from 1967-1971 using a regression equation. Composited results from two years of data over seven Wind River Mountain watersheds indicated that LANDSAT-1 snowcover observations, separated on the basis of watershed elevation, could also be related to runoff in significant regression equations. It appears that earth resources satellite data will be useful in assisting in the prediction of seasonal streamflow for various water resources applications, nonhazardous collection of snow data from restricted-access areas, and in hydrologic modeling of snowmelt runoff.

Rango, A.↗
NASA NTRS2021

A Dusty Atmospheric River Brings Floods to the Middle East

Torrential rainfall and rapid snowmelt in April 2017 caused deadly floods in northwestern Iran. An atmospheric river (AR), propagating across the Middle East and North Africa, was found responsible for this extreme event. The snowmelt was triggered by precipitation and warm advection associated with the AR. Total satellite-based rainfall for April 2017 was moderately below normal, suggesting that a heavy flood can happen during dry years. The AR was fed by moisture from the Mediterranean and Red Seas. Despite its adverse societal consequences, this event was beneficial to the recovery of the desiccating Lake Urmia. The impacts of this AR were not limited to flooding; it also facilitated dust transport to the region. This distinct characteristic of the ARs in the Middle East is attributed to major mineral dust sources located along their pathways. This event was reasonably predicted at 7-day lead time, crucially important for successful early warning systems.

Atmospheric river↗