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98 records · Page 6

Diurnal urban rainfall anomalies across different landscapes

Urbanization influences regional climates and extreme weather. While previous research has documented urban-induced precipitation for specific cities or storm cases, diurnal urban precipitation anomalies across different landscapes remain poorly understood. Analyzing diurnal and seasonal variations of urban precipitation anomalies across 175 US cities, we found strong urban effects on precipitation especially during summer afternoons. Large, inland cities can receive 10% more summer afternoon rainfall, and the pattern varies with urban heat islands and wind conditions. Coastal cities, under the influence of sea-land breeze, experience three times amplified daily urban precipitation enhancements than inland cities. Urban impacts are also noted for mountain cities, affecting their topography-dominated precipitation patterns. With increasing thresholds of extreme precipitation, most US cities experience more intense rainfall compared to their rural backgrounds. This study enhances our understanding of hitherto poorly documented diurnal aspects of urban rainfall through geographically distributed, landscape-specific rainfall anomalies.

Science & Technology - Other Topics↗

Evaluation of NASA SPoRT's Pseudo-Geostationary Lightning Mapper Products in the 2011 Spring Program

NASA's Short-term Prediction Research and Transition (SPoRT) program is a contributing partner with the GOES-R Proving Ground (PG) preparing forecasters to understand and utilize the unique products that will be available in the GOES-R era. This presentation emphasizes SPoRT s actions to prepare the end user community for the Geostationary Lightning Mapper (GLM). This preparation is a collaborative effort with SPoRT's National Weather Service partners, the National Severe Storms Laboratory (NSSL), and the Hazardous Weather Testbed s Spring Program. SPoRT continues to use its effective paradigm of matching capabilities to forecast problems through collaborations with our end users and working with the developers at NSSL to create effective evaluations and visualizations. Furthermore, SPoRT continues to develop software plug-ins so that these products will be available to forecasters in their own decision support system, AWIPS and eventually AWIPS II. In 2009, the SPoRT program developed the original pseudo geostationary lightning mapper (PGLM) flash extent product to demonstrate what forecasters may see with GLM. The PGLM replaced the previous GLM product and serves as a stepping-stone until the AWG s official GLM proxy is ready. The PGLM algorithm is simple and can be applied to any ground-based total lightning network. For 2011, the PGLM used observations from four ground-based networks (North Alabama, Kennedy Space Center, Oklahoma, and Washington D.C.). While the PGLM is not a true proxy product, it is intended as a tool to train forecasters about total lightning as well as foster discussions on product visualizations and incorporating GLM-resolution data into forecast operations. The PGLM has been used in 2010 and 2011 and is likely to remain the primary lightning training tool for the GOES-R program for the near future. This presentation will emphasize the feedback received during the 2011 Spring Program. This will discuss several topics. Based on feedback from the 2010 Spring Program, SPoRT created two variant PGLM products, which NSSL produced locally and provided in real-time within AWIPS for 2011. The first is the flash initiation density (FID) product, which creates a gridded display showing the number of flashes that originated in each 8 8 km grid box. The second product is the maximum flash density (MFD). This shows the highest PGLM value for each grid point over a specific period of time, ranging from 30 to 120 minutes. In addition to the evaluation of these two new products, the evaluation of the PGLM itself will be covered. The presentation will conclude with forecaster feedback for additional improvements requested for future evaluations, such as within the 2012 Spring Program.

Stano, Geoffrey T.↗

NASA Activity Update for the 2013 Unmanned Vehicle Systems International (UVSI) Yearbook

This year s report offers a high level perspective on some of the UAS related activities in which NASA is involved, both internal and external to the agency. Internally, NASA issued UAS operational policy on certification of NASA UAS and aircrew. A team of NASA UAS experts and operators analyzed all current procedures and best practices to design the policy. An update to the agencies Aircraft Operations Management Manual incorporated a new chapter to address UAS planning, preflight operations, flight operations, flight crew requirements, airworthiness and flight safety reviews. NASA UAS are classified into three categories based on weight and airspeed. Aircrews, including observers, are classified by how they interface with the UAS, and the policy defines qualifications, training, and currency. The NASA flight readiness approval process identifies risks and mitigations in order to reduce the likelihood and/or consequence of the risk to an acceptable level. The UAS operations process incorporates all aspects of airworthiness, flight standards and range safety exactly the same processes used for NASA manned aircraft operations. NASA has two internal organizations that routinely operate UAS. The Science Mission Directorate utilizes UAS as part of its Airborne Science Program and is the most frequent operator of NASA UAS in both national and international airspace. The Aeronautics Research Mission Directorate conducts UAS flight operations in addition to conducting research important to the UAS community. This past year the Science Mission Directorate supported the Hurricane and Severe Storm Sentimental (HS3) Mission with two NASA Global Hawk platforms. HS3 is a five-year mission specifically targeted to investigate the processes that underlie hurricane formation. During the 2012 portion of this mission the Global Hawk overflew hurricanes Leslie and Nadine in the Atlantic Ocean completing 6 flights and accumulating more than 148 flight hours. Another multi-year mission was initiated last year when the Sensor Integrated Environmental Remote Research Aircraft (SIERRA) UAS began surveying faults in California s Surprise Valley. A team of scientists and engineers from the United States Geological Survey (USGS), NASA Ames Research Center, Central Washington University, and Carnegie Mellon University will measure magnetic fields using ground surveys and the SIERRA to map the geophysics below the surface of Surprise Valley. The data collected will be used to generate 3D maps of the geophysical data of the area. The Aeronautics Mission Directorate continues its collaboration with Boeing to conduct UAS flight operations of the X-48C, a modified version of the X-48B originally built by Cranfield Aerospace, United Kingdom. The Aeronautics Mission Directorate utilizes vehicles of this size for a wide variety of research studies. Most of these operations are conducted within restricted airspace. The Aeronautics Research Mission Directorate also sponsors the UAS in the National Airspace System (NAS) Project, which is working in close cooperation with the Federal Aviation Administration (FAA) to address critical challenges associated with routine UAS operations in civil airspace. The project is focused on separation assurance and collision avoidance systems and algorithms, command and control for non-military operations including spectrum allocation requirements, human system interaction issues, and safety and certification topics.

Bauer, Jeffrey E.↗

The International Space Station Lightning Imaging Sensor: Performance, Applications, and Cross-Platform Science

The Lightning Imaging Sensor (LIS), an optically based lightning detector developed at NASA Marshall Space Flight Center, was launched to the International Space Station (ISS) in February 2017, detecting optical signatures of lightning with storm-scale horizontal resolution (4-km) during both day and night. ISS LIS data are available 1 March 2017 to present. Millisecond timing allows detailed intercalibration and validation with other spaceborne and ground-based lightning sensors. Initial comparisons with those other sensors suggest flash detection efficiency around 60% (diurnal variability of 51-75%), false alarm rate under 5%, timing accuracy better than 2 ms, and horizontal location accuracy around 3 km. The spatially uniform flash detection capability of ISS LIS from low-Earth orbit allows assessment of spatially varying flash detection efficiency for other sensors and networks, particularly the Geostationary Lightning Mappers (GLMs). ISS LIS provides research data suitable for investigations of lightning physics, climatology, thunderstorm processes, and atmospheric composition, as well as realtime lightning data for operational forecasting and aviation weather interests. ISS LIS enables enrichment and extension of the long-term global climatology of lightning from space, and is the only recent platform that extends the global record to higher latitudes (± 55°). The global spatial distribution of lightning from ISS LIS is broadly similar to previous datasets, with globally averaged seasonal/annual flash rates (3-year average: ~44 s) about 5-10% lower. This difference is likely due to reduced flash detection efficiency that will be mitigated in future ISS LIS data processing, as well as the shorter ISS LIS period of record. The expected land/ocean contrast in the diurnal variability of global lightning is also observed. The near-realtime ISS LIS data make the instrument important to operational weather forecasting and related applications, including public safety. Finally, ISS LIS is demonstrating utility as part (or potential part) of cross-platform studies examining a diverse array of topics, including lightning physics, thunderstorm processes, convective precipitation, and atmospheric composition.

Timothy Lang↗

Exploring Ecological, Morphological, and Environmental Controls on Coastal Foredune Evolution at Annual Scales Using a Process-Based Model

Coastal communities commonly rely upon foredunes as the first line of defense against sea-level rise and storms, thus requiring management guidance to optimize their protective services. Here, we use the AeoLiS model to simulate wind-driven accretion and wave-driven erosion patterns on foredunes with different morphologies and ecological properties under modern-day conditions. Additional sets of model runs mimic potential future climate changes to inform how both morphological and ecological properties may have differing contributions to net dune changes under evolving environmental forcing. This exploratory study, applied to represent the morphological, environmental, and ecological conditions of the northern Outer Banks, North Carolina, USA, finds that dunes experiencing minimal wave collision have similar net volumetric growth rates regardless of beach morphology, though the location and density of vegetation influence sediment deposition patterns across the dune profile. The model indicates that high-density, uniform planting strategies trap sediment close to the dune toe, whereas low-density plantings may allow for accretion across a broader extent of the dune face. The initial beach and dune shape generally plays a larger role in annual-scale dune evolution than vegetation cover. For steeper beach slopes and/or low dune toe elevations, the model generally predicts wave-driven dune erosion at the annual scale.

Environmental Sciences & Ecology↗

Implicit learning of convective organization explains precipitation stochasticity

Accurate prediction of precipitation intensity is crucial for both human and natural systems, especially in a warming climate more prone to extreme precipitation. Yet, climate models fail to accurately predict precipitation intensity, particularly extremes. One missing piece of information in traditional climate model parameterizations is subgrid-scale cloud structure and organization, which affects precipitation intensity and stochasticity at coarse resolution. Here, using global storm-resolving simulations and machine learning, we show that, by implicitly learning subgrid organization, we can accurately predict precipitation variability and stochasticity with a low-dimensional set of latent variables. Using a neural network to parameterize coarse-grained precipitation, we find that the overall behavior of precipitation is reasonably predictable using large-scale quantities only; however, the neural network cannot predict the variability of precipitation (R 2 ~ 0.45) and underestimates precipitation extremes. The performance is significantly improved when the network is informed by our organization metric, correctly predicting precipitation extremes and spatial variability (R 2 ~ 0.9). The organization metric is implicitly learned by training the algorithm on a high-resolution precipitable water field, encoding the degree of subgrid organization. The organization metric shows large hysteresis, emphasizing the role of memory created by subgrid-scale structures. We demonstrate that this organization metric can be predicted as a simple memory process from information available at the previous time steps. These findings stress the role of organization and memory in accurate prediction of precipitation intensity and extremes and the necessity of parameterizing subgrid-scale convective organization in climate models to better project future changes of water cycle and extremes.

54 ENVIRONMENTAL SCIENCES↗

The dynamic atmospheric and aeolian environment of Jezero crater, Mars

Despite the importance of sand and dust to Mars geomorphology, weather, and exploration, the processes that move sand and that raise dust to maintain Mars’ ubiquitous dust haze and to produce dust storms have not been well quantified in situ, with missions lacking either the necessary sensors or a sufficiently active aeolian environment. Perseverance rover’s novel environmental sensors and Jezero crater’s dusty environment remedy this. In Perseverance’s first 216 sols, four convective vortices raised dust locally, while, on average, four passed the rover daily, over 25% of which were significantly dusty (“dust devils”). More rarely, dust lifting by nonvortex wind gusts was produced by daytime convection cells advected over the crater by strong regional daytime upslope winds, which also control aeolian surface features. One such event covered 10 times more area than the largest dust devil, suggesting that dust devils and wind gusts could raise equal amounts of dust under nonstorm conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

STREAMS guidelines: standards for technical reporting in environmental and host-associated microbiome studies

The interdisciplinary nature of microbiome research, coupled with the generation of complex multi-omics data, makes knowledge sharing challenging. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines provide a checklist for the reporting of study information, experimental design and analytical methods within a scientific manuscript on human microbiome research. Here, in this Consensus Statement, we present the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines. The guidelines expand on STORMS and include 67 items to support the reporting and review of environmental (for example, terrestrial, aquatic, atmospheric and engineered), synthetic and non-human host-associated microbiome studies in a standardized and machine-actionable manner. Based on input from 248 researchers spanning 28 countries, we provide detailed guidance, including comparisons with STORMS, and case studies that demonstrate the usage of the STREAMS guidelines. In conclusion, STREAMS, like STORMS, will be a living community resource updated by the Consortium with consensus-building input of the broader community.

59 BASIC BIOLOGICAL SCIENCES↗