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Spatiotemporally Adaptive Compression for Scientific Dataset with Feature Preservation – A Case Study on Simulation Data with Extreme Climate Events Analysis
Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated over timesteps to accommodate storage and I/O limitations. In this paper, we propose a technique that addresses storage costs while improving post-analysis accuracy through spatiotemporal adaptive, error-controlled lossy compression. We investigate the trade-off between data precision and temporal output rates, revealing that reducing data precision and increasing timestep frequency lead to more accurate analysis outcomes. Additionally, we integrate spatiotemporal feature detection with data compression and demonstrate that performing adaptive error-bounded compression in higher dimensional space enables greater compression ratios, leveraging the error propagation theory of a transformation-based compressor. To evaluate our approach, we conduct experiments using the well-known E3SM climate simulation code and apply our method to compress variables used for cyclone tracking. Our results show a significant reduction in storage size while enhancing the quality of cyclone tracking analysis, both quantitatively and qualitatively, in comparison to the prevalent timestep decimation approach. Compared to three state-of-the-art lossy compressors lacking feature preservation capabilities, our adaptive compression framework improves perfectly matched cases in TC tracking by 26.4-51.3% at medium compression ratios and by 77.3-571.1% at large compression ratios, with a merely 5–11% computational overhead.
Characterization of extreme weather events during large-scale power outages.
Abstract not provided.
Developing Coupled Data Assimilation Strategy for Understanding Model Bias and Extreme Climate Events in E3SM
We have successfully developed the first working version of online ensemble coupled data assimilation (ECDA) on E3SM for both version 1 and version 2. Our schemes have also been tested successfully for assimilating SST data in both synthetic observations and real world observations, laying a foundation for future development.
ESD Ideas: Translating historical extreme weather events into a warmer world
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Extreme scattering events from axisymmetric plasma lenses
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The role of extreme rain events in Peninsular Florida’s seasonal hydroclimate variations
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Characteristics of extreme rainfall events in northwestern Peru during the 1982-1983 El Nino period
Histograms and contour maps describing the daily rainfall characteristics of a northwestern Peru area most severely affected by the 1982-1983 El Nino event were prepared from daily rainfall data obtained from 66 stations in this area during the El Nino event, and during the same 8-month intervals for the two years preceding and following the event. These data were analyzed, in conjunction with the anlysis of visible and IR satellite images, for cloud characteristics and structure. The results present a comparison of the rainfall characteristics as a function of elevation, geographic location, and the time of year for the El Nino and non-El Nino periods.
Extreme weather events
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.
Climate Change, Extreme Weather Events, and Fungal Disease Emergence and Spread
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.
The 2012 July 23 Backside Eruption: An Extreme Energetic Particle Event?
The backside coronal mass ejection (CME) of 2012 July 23 had a short Sun-to-Earth shock transit time (18.5 hr).The associated solar energetic particle (SEP) event had a greater than 10 MeV proton flux peaking at approximately 5000 pfu, and the energetic storm particle event was an order of magnitude larger, making it the most intense event in the space era at these energies. By a detailed analysis of the CME, shock, and SEP characteristics, we find that the July 23 event is consistent with a high-energy SEP event (accelerating particles to giga-electron volt energies). The times of maximum and fluence spectra in the range 10100 MeV were very hard, similar to those of ground-level enhancement (GLE) events. We found a hierarchical relationship between the CME initial speeds and the fluence spectral indices: CMEs with low initial speeds had SEP events with the softest spectra, while those with the highest initial speeds had SEP events with the hardest spectra. CMEs attaining intermediate speeds result in moderately hard spectra. The July 23 event was in the group of hard-spectrum events. During the July 23 event, the shock speed greater than (2000 km s(exp -1), the initial acceleration (approximately 1.70 km s(exp -2), and the shock-formation height (approximately 1.5 solar radii)were all typical of GLE events. The associated type II burst had emission components from meter to kilometer wavelengths, suggesting a strong shock. These observations confirm that the 2012 July 23 event is likely to be an extreme event in terms of the energetic particles it accelerated.
Restructuring Big Data to Improve Data Access and Performance in Analytic Services Making Research More Efficient for the Study of Extreme Weather Events and Application User Communities
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
July 2018 Mid-Atlantic Atmospheric River and Extreme Precipitation Event Captured by MERRA-2
Despite starting off the month with hardly any precipitation, July 2018 turned out to be one of the wettest on record in the Baltimore/Washington D.C. area. Daily rainfall records were demolished as an entire month's worth of precipitation fell in a matter of days and flash flood warnings covered the region. Beginning on July 21, 2018, an atmospheric river, or a narrow stream of enhanced water vapor transport, positioned itself over the region, bringing gray skies and precipitation for days. This was captured by GMAO's Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and given the nearly 40-year record of MERRA-2, can be placed in the context of past events and the overall climate for the region during July. Not only was the multi-day rainfall out of character, but large-scale features throughout July differed from climatology and there were even bigger differences in the state of the atmosphere between the first and second halves of July 2018.
Evaluation of Novel NASA MODIS and VIIRS Aerosol Products and Assessment of Smoke Height Boundary Layer Ratio During Extreme Smoke Events in the Western U.S.
We analyze new aerosol products from NASA satellite retrievals over the western U.S. during August 2013, with special attention to locally generated wildfire smoke and downwind plume structures. Aerosol optical depth (AOD) at 550 nm from MODIS (Terra and Aqua Collections 6 and 6.1) and VIIRS Deep Blue (DB) and MODIS (Terra and Aqua) Multi‐Angle Implementation of Atmospheric Correction (MAIAC) retrievals are evaluated against ground‐based AErosol RObotic NETwork (AERONET) observations. We find a significant improvement in correlation with AERONET and other metrics in the latest DB AOD (MODIS C6.1 r^2=0.75, VIIRS r^2=0.79) compared to MODIS C6 (r2=0.62). In general, MAIAC (r^2=0.84) and DB (MODIS C6.1 and VIIRS) present similar statistical evaluation metrics for the western U.S. and are useful tools to characterize aerosol loading associated with wildfire smoke. We also evaluate three novel NASA MODIS plume injection height (PIH) products, one from MAIAC and two from the Aerosol Single scattering albedo and layer Height Estimation (ASHE) (MODIS and VIIRS) algorithm. Both Terra and Aqua MAIAC PIHs statistically agree with ground‐based and satellite lidar observations near the fire source, as do ASHE, although the latter is sensitive to assumptions about aerosol absorption properties. We introduce a first‐order approximation Smoke Height Boundary Layer Ratio (SHBLR) to qualitatively distinguish between aerosol pollution within the planetary boundary layer and the free troposphere. We summarize the scope, limitations, and suggestions for scientific applications of surface level aerosol concentrations specific to wildfire emissions and smoke plumes using these novel NASA MODIS and VIIRS aerosol products.
Rainfall Field Reconstruction by Opportunistic Use of the Rain- Induced Attenuation on Microwave Satellite Signals: The July 2021 Extreme Rain Event in Germany as a Case Study
This paper presents a practical application of an opportunistic technique for the estimation of rainfall intensity and accumulated precipitation. The proposed technique is based upon signal strength measurements made by commercial-grade interactive satellite terminals. By applying some processing, the rain-induced attenuation on the microwave downlink from the satellite is first evaluated; then the rain attenuation is eventually mapped into a rainfall rate estimate via a tropospheric model. This methodology has been applied to a test area of 30 × 30 km 2 around the city of Dortmund (North Rhine-Westphalia, upper basin of Ermscher river), for the heavy rain event that devastated western Germany in July, 2021. A rainfall map on this area is obtained from the measurements collected by a set of satellite terminals deployed in the region, and successfully compared with a map obtained with a conventional weather radar.
Extreme Aerosol Events Over Eastern North America: 1. Characterizing and Simulating Historical Events
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A Multiparameter Degeneracy in Microlensing Events with Extreme Finite Source Effects
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