ALBERT

Description: The Arabian Peninsula has experienced pronounced interannual to decadal variability in dust activity, including an abrupt regime shift around 2006 from an inactive dust period during 1998–2005 to an active period during 2007–2013. Corresponding in time to the onset of this regime shift, the climate state transitioned into a combined La Niña and negative phase of the Pacific Decadal Oscillation, which incited a hiatus in global warming in the 2000s (Kosaka and Xie, 2013; Trenberth and Fasullo, 2013). Superimposed upon a long-term regional drying trend, synergistic interactions between these teleconnection modes triggered the establishment of a devastating and prolonged drought, which engulfed the Fertile Crescent, namely Iraq and Syria, and led to crop failure and civil unrest [Kelley et al., 2015]. Dried soils and diminished vegetation cover in the Fertile Crescent, as evident through remotely-sensed Enhanced Vegetation Indices, supported greater dust generation and transport to the Arabian Peninsula in 2007–2013, as identified both in increased dust days observed at weather stations and enhanced remotely-sensed aerosol optical depth. According to backward trajectory analysis of dust days on the Arabian Peninsula, increased dust lifting and atmospheric dust concentration in the Fertile Crescent during this recent, prolonged drought episode supported a greater frequency of dust events across the peninsula with associated northerly trajectories and led to the dust regime shift. These findings are particularly concerning, considering projections of warming and drying for the eastern Mediterranean region and potential collapse of the Fertile Crescent during this century [Kitoh et al., 2008].

Description: The Middle Eastern Shamal is a strong north-northwesterly wind, capable of lifting dust from the Tigris-Euphrates basin and transporting it to the Persian Gulf and Arabian Peninsula. The present study explores the poorly understood spatial and temporal variability of summer Shamal on the diurnal, seasonal, and interannual time scales, along with its influence on dust storm activity and sensitivity to global patterns of sea-surface temperature using a comprehensive set of observational data. Statistics of the summer Shamal season are quantified for the first time, including its onset, termination, duration, and the occurrence of distinct break periods. Based on a multi-station criteria, the mean onset and termination of the Shamal season occur on 30 May ± 16 days (one standard deviation) and 16 Aug ± 22 days, respectively. Anomalously early (late) onset and termination of the Shamal season is typically associated with La Niña (El Niño) conditions, which favor (inhibit) the development of the Iranian heat low in spring and inhibit (favor) its persistence into late summer. Dust source regions in the Tigris-Euphrates basin and Kuwait, as well as southeastward dust transport during the summer Shamal, which cannot be detected by satellite aerosol products alone, are identified, for the first time, from the Multiangle Imaging SpectroRadiometer (MISR) plume motion vector products, and confirmed by surface observations and lidar data. A close interrelationship has been revealed among summertime dust activity across the eastern Arabian Peninsula, frequency of Shamal days, and duration of the Shamal season on the interannual time scales.

Description: Abstract Deposition of mineral dust into ocean fertilizes ecosystems and influences biogeochemical cycles and climate. In situ observations of dust deposition are scarce, and model simulations depend on the highly parameterized representations of dust processes with few constraints. By taking advantage of satellites' routine sampling on global and decadal scales, we estimate African dust deposition flux and loss frequency (a ratio of deposition flux to mass loading) along the trans‐Atlantic transit using the three‐dimensional distributions of aerosol retrieved by spaceborne lidar (Cloud‐Aerosol Lidar with Orthogonal Polarization [CALIOP]) and radiometers (Moderate Resolution Imaging Spectroradiometer [MODIS], Multiangle Imaging Spectroradiometer [MISR], and Infrared Atmospheric Sounding Interferometer [IASI]). On the basis of a 10‐year (2007‐2016) and basin‐scale average, the amount of dust deposition into the tropical Atlantic Ocean is estimated at 136‐222 Tg/year. The 65‐83% of satellite‐based estimates agree with the in situ climatology within a factor of 2. The magnitudes of dust deposition are highest in boreal summer and lowest in fall, whereas the interannual variability as measured by the normalized standard deviation with mean is largest in spring (28‐41%) and smallest (7‐15%) in summer. The dust deposition displays high spatial heterogeneity, revealing that the meridional shifts of major dust deposition belts are modulated by the seasonal migration of the intertropical convergence zone. On the basis of the annual and basin mean, the dust loss frequency derived from the satellite observations ranges from 0.078 to 0.100 day‐1, which is lower than model simulations by up to factors of 2 to 5. The most efficient loss of dust occurs in winter, consistent with the higher possibility of low‐altitude transported dust in southern trajectories being intercepted by rainfall associated with the intertropical convergence zone. The satellite‐based estimates of dust deposition can be used to fill the geographical gaps and extend time span of in situ measurements, study the dust‐ocean interactions, and evaluate model simulations of dust processes.

Description: The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 11 km and is typically observed from 9 viewing angles between ±66° off nadir. For a simultaneous retrieval of aerosol properties and surface reflection using AirMSPI, an efficient and flexible retrieval algorithm has been developed. It imposes multiple types of physical constraints on spectral and spatial variations of aerosol properties as well as spectral and temporal variations of surface reflection. Retrieval uncertainty is formulated by accounting for both instrumental errors and physical constraints. A hybrid Markov-chain/adding-doubling radiative transfer (RT) model is developed to combine the computational strengths of these two methods in modeling polarized RT in vertically inhomogeneous and homogeneous media, respectively. Our retrieval approach is tested using 27 AirMSPI datasets with low to moderately high aerosol loadings, acquired during four NASA field campaigns plus one AirMSPI pre-engineering test flight. The retrieval results including aerosol optical depth, single scattering albedo, aerosol size and refractive index are compared with AERONET aerosol reference data. We identify the best angular combinations for 2-, 3-, 5-, 7-angle observations from the retrieval quality assessment of various angular combinations. We also explore the benefits of polarimetric and multiangular measurements, and target revisits in constraining aerosol property and surface reflection retrieval.

Description: Aerosol plumes from wildfires affect the Earth's climate system through regulation of the radiative budget and clouds. However, optical properties of aerosols from individual wildfire smoke plumes and their resultant impact on regional climate are highly variable. Therefore, there is a critical need for observations that can constrain the partitioning between different types of aerosols. Here we present the apparent influence of regional ecosystem types on optical properties of wildfire-induced aerosols based on remote sensing observations from two satellite instruments and three ground stations. The independent observations commonly show that the ratio of the absorbing aerosols is significantly lower in smoke plumes from the Maritime Continent than those from Central Africa, so that their impacts on regional climate are different. The observed light-absorbing properties of wildfire-induced aerosols are explained by dominant ecosystem types such as wet peatlands for the Maritime Continent and dry savannah for Central Africa respectively. These results suggest that the wildfire-aerosol-climate feedback processes largely depend on the terrestrial environments from which the fires originate. These feedbacks also interact with climate under greenhouse warming. Our analysis shows that aerosol optical properties retrieved based on satellite observations are critical in assessing wildfire-induced aerosols forcing in climate models. The optical properties of carbonaceous aerosol mixtures used by state-of-art chemistry climate models may overestimate emissions for absorbing aerosols from wildfires over the Maritime Continent.

Description: This study refines the method for calibrating a glacio-hydrological model based on Hydrograph Partitioning Curves (HPCs), and evaluates its value in comparison to multi-dataset optimization approaches which use glacier mass balance, satellite snow cover images and discharge. The HPCs are extracted from the observed flow hydrograph using catchment precipitation and temperature gradients. They indicate the periods when the various runoff processes, such as glacier melt or snow melt, dominate the basin hydrograph. The annual cumulative curve of the difference between average daily temperature and melt threshold temperature over the basin, as well as the annual cumulative curve of average daily snowfall on the glacierized areas are used to identify the starting and end dates of snow and glacier ablation periods. Model parameters characterizing different runoff processes are calibrated on different HPCs in a stepwise and iterative way. Results show that the HPC-based method (1) delivers model-internal consistency comparably to the tri-dataset calibration methods; (2) improves the stability of calibrated parameter values across various calibration periods; and (3) estimates the contributions of runoff components similarly to the tri-dataset calibration method. Our findings indicate the potential of the HPC-based approach as an alternative for hydrological model calibration in glacierized basins where other calibration datasets than discharge are often not available or very costly to obtain.

Description: It is well established that smoke particles modify clouds, which in turn affects climate. However, no studies have quantified the temporal dynamics of aerosol-cloud interactions with direct observations. Here, for the first time, we use temporally-offset satellite observations from northern Africa between 2006 and 2010 to quantitatively measure the effect of fire aerosols on convective cloud dynamics. We attribute a reduction in cloud fraction during periods of high aerosol optical depths to a smoke-driven inhibition of convection. We find that higher smoke burdens limit upward vertical motion, increase surface pressure, and increase low-level divergence—meteorological indicators of convective suppression. These results are corroborated by climate simulations that show a smoke-driven increase in regionally averaged shortwave tropospheric heating and decrease in convective precipitation during the fire season. Our results suggest that, in tropical regions, anthropogenic fire initiates a positive feedback loop where increased aerosol emissions limit convection, dry the surface and enable increased fire activity via human ignition.