Global Aurora on Mars During the September 2017 Space Weather Event
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Models that try to forecast the detailed geographical distribution of oceanic and atmospheric variables affected by the ENSO cycle are briefly discussed. Combinations of singular-spectrum analysis and the maximum entropy method that hold promise for predicting the ENSO cycle 2-3 yrs in advance are addressed.
Empirical evidence from multiple sources show the Earth has been warming since the late 19th century. More recently, evidence for this warming trend is strongly supported by satellite data since the late 1970s from the cryosphere, atmosphere, oceans, and land that confirms increasing temperature trends and their consequences (e.g., reduced Arctic sea ice, rising sea level, ice sheet mass loss, etc.). At the same time, satellite observations of the Sun show remarkably stable solar cycles since the late 1970s, when direct observations of the Sun's total solar irradiance began. Numerical simulation models, driven in part by assimilated satellite data, suggest that future-warming trends will lead to not only a warmer planet, but also a wetter and drier climate depending upon location in a fashion consistent with large-scale atmospheric processes. Continued global warming poses new opportunities for the emergence and spread of fungal disease, as climate systems change at regional and global scales, and as animal and plant species move into new niches. Our contribution to this proceedings is organized thus: First, we review empirical evidence for a warming Earth. Second, we show the Sun is not responsible for the observed warming. Third, we review numerical simulation modeling results that project these trends into the future, describing the projected abiotic environment of our planet in the next 40 to 50 years. Fourth, we illustrate how Rift Valley fever outbreaks have been linked to climate, enabling a better understanding of the dynamics of these diseases, and how this has led to the development of an operational predictive outbreak model for this disease in Africa. Fifth, We project how this experience may be applicable to predicting outbreaks of fungal pathogens in a warming world. Lastly, we describe an example of changing species ranges due to climate change, resulting from recent warming in the Andes and associated glacier melt that has enabled amphibians to colonize higher elevation lakes, only to be followed shortly by the emergence of fungal disease in the new habitats.
We report on the level of solar activity during cycles 23 and 24 as the cycles build toward the corresponding solar maxima. The prolonged minimum period that followed solar cycle 23 and the weaker magnetic field at the poles seem to have resulted in a weaker level of activity during cycle 24. The double speak structure often observed in the maximum phases seems to be present during cycle 24, with the first peak having a sunspot number of only N90. large solar energetic particle (SEP) events, major geomagnetic storms, and radio-emitting interplanetary shocks have been observed in relatively sma:ier numbers. While the number of large SEP events during the rise phase of cycles 24 is not too different from that of cycle 23, they are generally less intense. Five ground level enhancement (GlE) events occurred up to the first activity peak in cycle 23, while a lone GlE event has been observed during the corresponding phase in cycle 24. There were 35 large (Dst S -100 nT) geomagnetic storms during the first 4.5 years of cycle 23, while only 5 occurred during cycle 24. The subdued activity during cycle 23 is consistent with the low numbers of type II radio bursts, full halo CMEs, and interplanetary shocks.
Hail scars are identifiable in MODIS satellite imagery based on NDVI change, which was dominantly negative. Hail damage spatially correlates with SPC hail reports and MESH. This study developed a proxy for quantifying crop loss at varying thresholds to address the gap between SPC damage estimates and insurance payouts.
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By developing and enhancing various services and tools, the GES DISC provides users with the capability to access and visualize data, and to make comparisons of data from multiple sensor and models via a number of cross-discipline projects. Discovering Data via Faceted Web Interface Web interface to data products and services Search and Download mechanisms Dataset Landing Pages Accessing Data through Interoperable Services: GDS – GrADS Data Server OPeNDAP - Open-source Project for a Network Data Access Protocol WMS – OGC service GIS connector – allowing IS tools to access data easier (coming soon) HTTPS -- direct online access Downloading Data Basics: Subset and egridding Service – Parameter, Spatial, Time, Vertical, Mean averaging, format conversion, and regridding for L3/L4 gridded data Swath Data Subsetter – Parameter, spatial subset of L2 /L1 data. Visualizing Data Online: Giovanni –Visualization and Analysis L3/L4 gridded data AIRS NRT Viewer – AIRS near-real-time DQVis – L2 data quality visualization
In this response, we address the three main comments by Tsurutani et al. (2018, http://doi.org/10.1002/2017JA024779) namely, unusually high plasma density, interplanetary magnetic field intensity, and fast storm recovery phase. The authors agree that there is room to improve the modeling by taking into account these comments and other aspects that were not fully explored during our initial work. We are already in the process of undertaking a more comprehensive modeling project.
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Uncoordinated management of hydropower dams during extreme and unexpected precipitation events in mountainous terrain can have disastrous consequences due to the competing nature of flood control and hydropower generation. Numerous cases of flooding events that have been exacerbated due to insufficient storage conditions in hydropower dams have been reported worldwide. There is a need for a scalable and publicly accessible monitoring framework that is capable of providing reliable, near-real time, and transparent reservoir operations data. A fully satellite-based framework is the most viable solution to build such capability. The Reservoir Assessment Tool (RAT 3.0), which utilizes high frequency remote sensing-based surface area and reservoir storage estimation alongside hydrological modelled inflow was applied here for the 2018 Kerala floods in India as a globally representative case for a mountainous river basin with high precipitation and hydropower dams. Application of satellite-based RAT 3.0 in monitoring the state of 19 reservoirs in Kerala during the flood event showed very promising results. In general, RAT 3.0, using satellite remote sensing, was found to be able to capture the temporal trend of the reservoir storage and pinpoint the sudden shift in filling or release decisions made by the dam operator. Inflow modelling in such regions was found to require careful calibration with identification of reservoirs that are heavily regulated being a critical aspect. The perennial high cloud cover in such regions necessitate and highlights the central role played by microwave and radar-based satellite sensors, such as the Surface Water and Ocean Topography (SWOT) mission, in tracking reservoir state. An operational version of RAT 3.0 for stakeholder agencies tailored for hydropower dams operating in high precipitation and mountainous environments is a real-world outcome of this study.
Catastrophic bushfires are becoming increasingly prevalent as climate change advances. Impacts extend beyond national borders. Multinational efforts can inform new science and management practices. Space-based sensors and integrated data facilities will play an important role. This paper describes a collaborative project between a consortium of Australian universities and NASA Centers to develop and implement a small satellite platform comprising highly integrated thermal and lightning sensors coupled with AI-based edge computing to help predict, detect, and track bushfires, supporting mitigation activities. This will fill an important capability gap since Australia does not currently have any sovereign Earth observation satellites. This program is enabled by and builds on Australia-NASA collaboration and will also support fire science and management activities in the broader global context.
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With climate change posing serious risks to crop production, solar PV has the potential to protect agriculture against extreme climate events. This concept has significant implications for agrivoltaics, but large gaps exist in the physical understanding of the climate resiliency that solar PV can bring to agriculture, and current studies focus on one-off designs ideal to protect against specific climate events. This study investigates key climate events that threaten agriculture throughout the year, including winter, spring, and summer climate threats.