ALBERT

Description: We identify eleven megafans (partial cones of fluvial sediment, 〉80 km radius) in the northern Kalahari Basin, using several criteria based on VIS and IR remotely sensed data and SRTM-based surface morphology reconstructions. Two other features meet fewer criteria of the form which we class as possible megafans. The northern Kalahari megafans are located in a 1700 km arc around the southern and eastern flanks of the Angola's Bi Plateau, from northern Namibia through northwest Botswana to western Zambia. Three lie in the Owambo subbasin centered on the Etosha Pan, three in the relatively small Okavango rift depression, and five in the Upper Zambezi basin. The population includes the well-known Okavango megafan (150 km), Namibia's Cubango megafan, the largest megafan in the region (350 km long), and the largest nested group (the five major contiguous megafans on the west slopes of the upper Zambezi Valley). We use new, SRTM-based topographic roughness data to discriminate various depositional surfaces within the flat N. Kalahari landscapes. We introduce the concepts of divide megafans, derived megafans, and fan-margin rivers. Conclusions. (i) Eleven megafan cones total an area of ~190,000 sq km. (ii) Different controls on megafan size operate in the three component basins: in the Okavango rift structural controls become the prime constraint on megafan length by controlling basin dimensions. Megafans in the other les constricted basins appear to conform to classic relationships fan area, slope, and feeder-basin area. (iii) Active fans occupy the Okavango rift depression with one in the Owambo basin. The rest of the population are relict but recently active fans (surfaces are relict with respect to activity by the feeder river). (iv) Avulsive behavior of the formative river-axiomatic for the evolution of megafans-has resulted in repeated rearrangements of regional drainage, with likely effects in the study area well back into the Neogene. Divide megafans comprise the majority of the identified features, some of which have delivered water and sediment alternately to neighboring basins in the course of normal avulsion activity, likely resulting in significant changes in the hydrologies of two of the study-area subbasins. (v) Paleoclimatic inferences extracted from fluvial and lacustrine sediments therefore need to take account of avulsion-driven drainage configurations, especially where these are autogenically controlled.

Description: No abstract available

Description: The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study designed to provide a comprehensive data set that can be used to investigate a number of important climate science questions, including those related to aerosol mixing state and aerosol radiative forcing. The study was designed to sample the atmosphere be tween and within two atmospheric columns; one fixed near the coast of North America (over Cape Cod, MA) and a second moveable column over the Atlantic Ocean several hundred kilometers from the coast. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was deployed at the base of the Cape Cod column, and the ARM Aerial Facility was utilized for the summer and winter intensive observation periods. One important finding from TCAP is that four of six nearly cloud-free flight days had aerosol layers aloft in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA high-spectral resolution lidar (HSRL-2).These layer s contributed up to 60 of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. In addition, while there was a great deal of spatial and day-to-day variability in the aerosol chemical composition and optical properties, no systematic differences between the two columns were observed.

Description: Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Description: We present the development of a deep learning model for objective estimation of tropical cyclone intensity at a higher temporal frequency, deployment of the model in production, design and implementation of the tropical cyclone monitoring and intensity estimation system and development of an interactive portal for situational awareness and evaluation of intensity estimation.

Description: We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static reference case. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/sq m or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than 70% ground spot overlap between the satellites is possible with 0.5deg of pointing accuracy, 2 Km of GPS accuracy and commands uplinked once a day. The formations can be maintained at less than 1 m/s of monthly (Delta)V per satellite.

Description: No abstract available

Description: No abstract available

Description: Clearsky contamination is a challenging and longlasting problem for cloud optical thickness () and effective droplet radius (r(sub eff)) retrievals using passive satellite sensors. This study explores the feasibility of improving both and r(sub eff) retrievals for partly cloudy (PCL) pixels by using available subpixel samples in a visible to nearinfrared band, which many satellite sensors offer. Data are provided by highresolution reflectance (R) observations and cloud property retrievals by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at horizontal resolutions between 30960m. For partly cloudy 960m observations, the clearsky component of the pixels induces significant underestimations of up to 58% for , while overestimations in r(sub eff) can exceed 41%. This yields underestimations in the derived liquid water path and cloud droplet number concentration of up to 68% and 72%, respectively. By means of three different assumptions it is shown that subpixel R observations in the visible to nearinfrared band can be used to estimate higherresolution R for the second band in the retrieval scheme, as well as the subpixel cloud cover. The estimated values compare well to actually observed ASTER results and are used to retrieve cloud properties, which are unbiased by the clearsky component of PCL pixels. While the presented retrieval approach is only evaluated for marine boundary layer clouds, it is computationally efficient and can be easily applied to observations from different imagers. As an example, the PCL retrieval scheme is applied to data by the Moderate Resolution Imaging Spectroradiometer, where similar biases for PCL pixels are observed.

Description: Dependence on rainfed agriculture in a highly variable climate, renders crop and livestock production vulnerable to impacts of drought in Kenya. Stakeholders in the region have highlighted the need for timely and actionable detailed early warning information on drought and its implication on crop productivity. Here we apply the Regional Hydrological Extremes Assessment System (RHEAS) to estimate current and future drought conditions onset, severity, recovery, and duration) and expected productivity outlooks.