The document discusses the NASA Soil Moisture Active Passive (SMAP) mission, which is scheduled for launch in 2014. SMAP will map global soil moisture and freeze/thaw state from space to further understanding of the water, energy, and carbon cycles. The mission involves an L-band radar and radiometer to provide soil moisture measurements. Algorithms are being developed and tested to generate products like soil moisture maps from the radar-radiometer data. Validation efforts and working groups are helping prepare for the mission.
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...debasishagri
Climate change is one of the most important global environmental challenges of this century. Green House Gases (GHGs) are the main culprit for this problem. Though much of research has already been done about the distribution and sources (and sinks) of GHGs , still much more uncertainties are present. Currently, there are only a few satellite instruments in orbit which are able to measure atmospheric GHGs. The High Resolution Infrared Radiation Sounder (HIRS), the Atmospheric InfraRed Sounder (AIRS), and the Infrared Atmospheric Sounding Interferometer (IASI) perform measurements in the thermal infrared (TIR) spectral region. But these are having low sensitivity to lower troposphere. In contrast to this, the sensitivity of instruments measuring reflected solar radiation in the near-infrared (NIR)/shortwave infrared (SWIR) spectral region is much more constant (with height) and shows maximum values near the surface. At present, SCIAMACHY aboard ENVISAT launched in 2002 and TANSO (Thermal And Near infrared Sensor for carbon Observation) aboard GOSAT (Greenhouse gases Observing SATellite) launched in 2009 are the only orbiting instruments measuring in NIR region. Among all the algorithms the WFM-DOAS algorithm (Weighting Function Modified Differential Optical Absorption Spectroscopy) developed at the University of Bremen for the retrieval of trace gases from SCIAMACHY (Buchwitz et al.2005) is mostly used. This is based on the principle of differential detection of radiance in gaseous absorption channels with respect to neighboring atmospheric transparent spectral channels (not influenced by gas) to detect the conc. of desired gas. But scattering at aerosol and/or cloud particles remains a major source of uncertainty for SCIAMACHY XCO2 retrievals(Houweling 2005, Schneising 2008).Of late with the use of new merged fit window approach scientists have come up with less than 0.5 ppm error in the estimation of CO2 in the presence of thin cirrus cloud(Reuter, Buchwitz et. al. 2010). Schneising et. al.,2007,retrieved d three year’s column-averaged CO2 dry air mole fraction from the SCIAMACHY instrument using the retrieval algorithm WFM-DOAS version 1.0, with precision of about 2 ppm. In India a study was undertaken to compare the atmospheric methane concentration pattern from SCIAMACHY with the vegetation dynamics from SPOT, showed fairly good correlation of methane emission with the rice cultivation(Goroshi et. al.).
Retrieval & monitoring of atmospheric green house gases (gh gs) through remot...debasishagri
Climate change is one of the most important global environmental challenges of this century. Green House Gases (GHGs) are the main culprit for this problem. Though much of research has already been done about the distribution and sources (and sinks) of GHGs , still much more uncertainties are present. Currently, there are only a few satellite instruments in orbit which are able to measure atmospheric GHGs. The High Resolution Infrared Radiation Sounder (HIRS), the Atmospheric InfraRed Sounder (AIRS), and the Infrared Atmospheric Sounding Interferometer (IASI) perform measurements in the thermal infrared (TIR) spectral region. But these are having low sensitivity to lower troposphere. In contrast to this, the sensitivity of instruments measuring reflected solar radiation in the near-infrared (NIR)/shortwave infrared (SWIR) spectral region is much more constant (with height) and shows maximum values near the surface. At present, SCIAMACHY aboard ENVISAT launched in 2002 and TANSO (Thermal And Near infrared Sensor for carbon Observation) aboard GOSAT (Greenhouse gases Observing SATellite) launched in 2009 are the only orbiting instruments measuring in NIR region. Among all the algorithms the WFM-DOAS algorithm (Weighting Function Modified Differential Optical Absorption Spectroscopy) developed at the University of Bremen for the retrieval of trace gases from SCIAMACHY (Buchwitz et al.2005) is mostly used. This is based on the principle of differential detection of radiance in gaseous absorption channels with respect to neighboring atmospheric transparent spectral channels (not influenced by gas) to detect the conc. of desired gas. But scattering at aerosol and/or cloud particles remains a major source of uncertainty for SCIAMACHY XCO2 retrievals(Houweling 2005, Schneising 2008).Of late with the use of new merged fit window approach scientists have come up with less than 0.5 ppm error in the estimation of CO2 in the presence of thin cirrus cloud(Reuter, Buchwitz et. al. 2010). Schneising et. al.,2007,retrieved d three year’s column-averaged CO2 dry air mole fraction from the SCIAMACHY instrument using the retrieval algorithm WFM-DOAS version 1.0, with precision of about 2 ppm. In India a study was undertaken to compare the atmospheric methane concentration pattern from SCIAMACHY with the vegetation dynamics from SPOT, showed fairly good correlation of methane emission with the rice cultivation(Goroshi et. al.).
Backscatter Working Group Software Inter-comparison Project Requesting and Co...Giuseppe Masetti
Backscatter mosaics of the seafloor are now routinely produced from multibeam sonar data, and used in a wide range of marine applications. However, significant differences (up to 5 dB) have been observed between the levels of mosaics produced by different software processing a same dataset. This is a major detriment to several possible uses of backscatter mosaics, including quantitative analysis, monitoring seafloor change over time, and combining mosaics. A recently concluded international Backscatter Working Group (BSWG) identified this issue and recommended that “to check the consistency of the processing results provided by various software suites, initiatives promoting comparative tests on common data sets should be encouraged […]”. However, backscatter data processing is a complex (and often proprietary) sequence of steps, so that simply comparing end-results between software does not provide much information as to the root cause of the differences between results.
In order to pinpoint the source(s) of inconsistency between software, it is necessary to understand at which stage(s) of the data processing chain do the differences become substantial. We have invited willing software developers to discuss this framework and collectively adopt a list of intermediate processing steps. We provided a small dataset consisting of various seafloor types surveyed with the same multibeam sonar system, using constant acquisition settings and sea conditions, and have the software developers generate these intermediate processing results, to be eventually compared. If the experiment proves fruitful, we may extend it to more datasets, software and intermediate results. Eventually, software developers may consider making the results from intermediate stages a standard output as well as adhering to a consistent terminology, as advocated by Schimel et al. (2018). To date, the developers of four software (Sonarscope, QPS FMGT, CARIS SIPS, MB Process) have expressed their interest in collaborating on this project.
Using Physical Modeling to Evaluate Re-entrainment of Stack EmissionsSergio A. Guerra
Fume re-entry is an important concern for many types of facilities such as hospitals and laboratories that emit pathogens and toxic chemicals that may impact public health by being re-entrained into the building though nearby air intakes. Numerical methods can be used to evaluate dispersion of pollutants from stacks at sensitive receptors. However, numerical methods have limitations and simplifications that can significantly affect its predictions. An alternate way of analyzing stack re-entrainment is with physical modeling in a wind tunnel. In such a study, a scale model that accounts for buildings, topography, and vegetation is used with planned and alternate stack designs to determine the toxic emission impacts on air intakes and other sensitive locations. In a wind tunnel study different stack designs and possible mitigation options can be evaluated. This method is superior to numerical methods (e.g., dispersion models) because it accounts for the immediate structures, topography, and vegetation that is often ignored or oversimplified in numerical methods.
This presentation will show a hypothetical case study evaluating a site with toxic air emissions using AERMOD and physical modeling.
Numerous studies have found an average increase in extreme precipitation for both the U.S. and Northern Hemisphere mid-latitude land areas, consistent with the expectations arising from the observed increase in greenhouse gas concentrations (now more than 40% above pre-industrial levels). However, there are important regional variations in these trends that are not fully explained. These trend studies are typically based on direct analyses of observational station data. Such analyses confront multiple challenges, such as incomplete data and uneven spatial coverage of stations. Central scientific questions related to this general finding are: Are there changes in weather system phenomenology that are contributing to this observed increase? What is the contribution of increases in atmospheric water vapor? There are also questions related to application of potential future changes in planning. Because of the rarity (by definition) of extreme events, trends are mostly found only when aggregating over space. When would we expect to see a signal at the local level? What are the uncertainties surrounding future changes and their potential incorporation into future design? Further development of statistical/mathematical methods, or innovative application of existing methods, is desirable to aid scientists in exploring these central scientific questions. This talk will describe characteristics of the observation record and the issues surrounding the above questions.
Presentation includes information related to gently sloping terrain, AERMINUTE, and EPA formula height.
Presented at the 27th Annual Conference on the Environment on November 13, 2012.
Master Thesis Final Presentation: Ionosphere monitoring in GBAS using Dual Fr...Joan Erencia
The motivation: Detection of different Ionosphere gradients, which cause different ionospheric delays in aviation applications (GBAS)
The objectives: First, estimate the airborne and ground ionospheric delays and second, monitor the ionospheric. Bias between both estimates and compare it to a threshold
The contribution: Present a GBAS Ionospheric monitor monitor that allows to estimate the ionospheric differential delay without moving to a whole Dual-Frequency GBAS concept.
Complying with EPA's Guidance for SO2 DesignationsSergio A. Guerra
EPA is under a Court order to complete the remaining SO2 designations for the rest of the country in three additional rounds. On March 20, 2015 the EPA released an updated guidance for 1-hr SO2 area designations. The two options included are compliance through dispersion modeling or ambient monitoring. Of these two options, dispersion modeling is the fastest and most cost effective one to characterize SO2 air quality. However, this compliance demonstration can be challenging given that AERMOD tends to produce overly conservative concentration estimates. Source characterization techniques and probabilistic techniques may be used to achieve compliance with the 1-hour NAAQS. Three advanced methods discussed: 1) Equivalent Building Dimensions (EBD); 2) Emission Variability Processor (EMVAP); 3) 50th Percentile Background Concentrations.
Backscatter Working Group Software Inter-comparison Project Requesting and Co...Giuseppe Masetti
Backscatter mosaics of the seafloor are now routinely produced from multibeam sonar data, and used in a wide range of marine applications. However, significant differences (up to 5 dB) have been observed between the levels of mosaics produced by different software processing a same dataset. This is a major detriment to several possible uses of backscatter mosaics, including quantitative analysis, monitoring seafloor change over time, and combining mosaics. A recently concluded international Backscatter Working Group (BSWG) identified this issue and recommended that “to check the consistency of the processing results provided by various software suites, initiatives promoting comparative tests on common data sets should be encouraged […]”. However, backscatter data processing is a complex (and often proprietary) sequence of steps, so that simply comparing end-results between software does not provide much information as to the root cause of the differences between results.
In order to pinpoint the source(s) of inconsistency between software, it is necessary to understand at which stage(s) of the data processing chain do the differences become substantial. We have invited willing software developers to discuss this framework and collectively adopt a list of intermediate processing steps. We provided a small dataset consisting of various seafloor types surveyed with the same multibeam sonar system, using constant acquisition settings and sea conditions, and have the software developers generate these intermediate processing results, to be eventually compared. If the experiment proves fruitful, we may extend it to more datasets, software and intermediate results. Eventually, software developers may consider making the results from intermediate stages a standard output as well as adhering to a consistent terminology, as advocated by Schimel et al. (2018). To date, the developers of four software (Sonarscope, QPS FMGT, CARIS SIPS, MB Process) have expressed their interest in collaborating on this project.
Using Physical Modeling to Evaluate Re-entrainment of Stack EmissionsSergio A. Guerra
Fume re-entry is an important concern for many types of facilities such as hospitals and laboratories that emit pathogens and toxic chemicals that may impact public health by being re-entrained into the building though nearby air intakes. Numerical methods can be used to evaluate dispersion of pollutants from stacks at sensitive receptors. However, numerical methods have limitations and simplifications that can significantly affect its predictions. An alternate way of analyzing stack re-entrainment is with physical modeling in a wind tunnel. In such a study, a scale model that accounts for buildings, topography, and vegetation is used with planned and alternate stack designs to determine the toxic emission impacts on air intakes and other sensitive locations. In a wind tunnel study different stack designs and possible mitigation options can be evaluated. This method is superior to numerical methods (e.g., dispersion models) because it accounts for the immediate structures, topography, and vegetation that is often ignored or oversimplified in numerical methods.
This presentation will show a hypothetical case study evaluating a site with toxic air emissions using AERMOD and physical modeling.
Numerous studies have found an average increase in extreme precipitation for both the U.S. and Northern Hemisphere mid-latitude land areas, consistent with the expectations arising from the observed increase in greenhouse gas concentrations (now more than 40% above pre-industrial levels). However, there are important regional variations in these trends that are not fully explained. These trend studies are typically based on direct analyses of observational station data. Such analyses confront multiple challenges, such as incomplete data and uneven spatial coverage of stations. Central scientific questions related to this general finding are: Are there changes in weather system phenomenology that are contributing to this observed increase? What is the contribution of increases in atmospheric water vapor? There are also questions related to application of potential future changes in planning. Because of the rarity (by definition) of extreme events, trends are mostly found only when aggregating over space. When would we expect to see a signal at the local level? What are the uncertainties surrounding future changes and their potential incorporation into future design? Further development of statistical/mathematical methods, or innovative application of existing methods, is desirable to aid scientists in exploring these central scientific questions. This talk will describe characteristics of the observation record and the issues surrounding the above questions.
Presentation includes information related to gently sloping terrain, AERMINUTE, and EPA formula height.
Presented at the 27th Annual Conference on the Environment on November 13, 2012.
Master Thesis Final Presentation: Ionosphere monitoring in GBAS using Dual Fr...Joan Erencia
The motivation: Detection of different Ionosphere gradients, which cause different ionospheric delays in aviation applications (GBAS)
The objectives: First, estimate the airborne and ground ionospheric delays and second, monitor the ionospheric. Bias between both estimates and compare it to a threshold
The contribution: Present a GBAS Ionospheric monitor monitor that allows to estimate the ionospheric differential delay without moving to a whole Dual-Frequency GBAS concept.
Complying with EPA's Guidance for SO2 DesignationsSergio A. Guerra
EPA is under a Court order to complete the remaining SO2 designations for the rest of the country in three additional rounds. On March 20, 2015 the EPA released an updated guidance for 1-hr SO2 area designations. The two options included are compliance through dispersion modeling or ambient monitoring. Of these two options, dispersion modeling is the fastest and most cost effective one to characterize SO2 air quality. However, this compliance demonstration can be challenging given that AERMOD tends to produce overly conservative concentration estimates. Source characterization techniques and probabilistic techniques may be used to achieve compliance with the 1-hour NAAQS. Three advanced methods discussed: 1) Equivalent Building Dimensions (EBD); 2) Emission Variability Processor (EMVAP); 3) 50th Percentile Background Concentrations.
Af sis midterm_review_consortium_presentation_v3Bob MacMillan
This presentation summarizes the activities and results for Objective 1 of the AfSIS project - This objective aims to create and maintain a global consortium that will produce grid maps of soil properties at a fine spatial resolution of 100 m for the entire world. The slidies in this presentation highlight accomplishments and contributions towards this objective in 2010.
Toward a Global Interactive Earth Observing CyberinfrastructureLarry Smarr
05.01.12
Invited Talk to the 21st International Conference on Interactive Information Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology Held at the 85th AMS Annual Meeting
Title: Toward a Global Interactive Earth Observing Cyberinfrastructure
San Diego, CA
Surface and soil moisture monitoring, estimations, variations, and retrievalsJenkins Macedo
This presentation explored five leading articles in the remotely sensed and in situ surface and soil moisture monitoring, estimations, variations, and retrievals for global environmental change. The presentation gives insight to the purpose of each study, subjects of investigations, methods used to collect and analyze data sets, results and implications, and conclusions. This project is in fulfillment of the course on remote sensing for global environmental change and precedes our preview on water resources monitoring. This project was conducted by Christina Geller, 5th year accelerated graduate student in Geographic Information Systems for Development, and Environment and Jenkins Macedo, 2nd year graduate students in Environmental Science and Policy at the Department of International Development, Community, and Environment (IDCE) at Clark University. All academic materials used in this study were appropriately referenced (see bibliography for details).
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Accelerate your Kubernetes clusters with Varnish Caching
3178_IGARSS11.ppt
1. NASA Soil Moisture Active Passive (SMAP) Mission Formulation Dara Entekhabi (MIT) Eni Njoku (JPL Caltech/NASA) Peggy O'Neill (GSFC/NASA) Kent Kellogg (JPL Caltech/NASA) Jared Entin (NASA HQ) IGARSS’11 Session WE1.T03.1 Paper #3178
2.
3.
4. May 10 Dry soil, clear, mild winds. (LE≈H) May 18 90 mm Rain May 20 Moist soil, clear, mild winds. (LE>H) Pathways of Soil Moisture Influence on Weather and Climate CASES’97 Field Experiment, BAMS , 81(4), 2000. Dry Soil Moist Soil 5°C Dry Surface Moist Surface Deep Mixing up to 1.5 km Altitude Shallow Mixing to 1.0 km
5. Source: Cahill et al., J. Appl. Met ., 38 Key Determinants of Land Evaporation Latent heat flux (evaporation) links the water , energy , and carbon cycles at the surface. Closure relationship, yet virtually unknown. Lack of knowledge of soil moisture control on surface fluxes causes uncertainty in weather and climate models.
6. NOAH CLM What Do We Do Today? Dirmeyer et al., J. Hydromet., 7, 1177-1198, 2006 Atmospheric model representations of this function are essentially “guesses”, given scarcity of soil moisture and evaporation data.
7. (*) % classification accuracy (binary Freeze/Thaw) (**) [cm 3 cm -3 ] volumetric water content, 1-sigma Science Requirements (1) North of 45N latitude Requirement Hydro-Meteorology Hydro-Climatology Carbon Cycle Baseline Mission Soil Moisture Freeze/Thaw Resolution 4–15 km 50–100 km 1–10 km 10 km 3 km Refresh Rate 2–3 days 3–4 days 2–3 days (1) 3 days 2 days (1) Accuracy 4–6% ** 4–6%** 80–70%* 4%** 80%* DS Objective Application Science Requirement Weather Forecast Initialization of Numerical Weather Prediction (NWP) Hydrometeorology Climate Prediction Boundary and Initial Conditions for Seasonal Climate Prediction Models Hydroclimatology Testing Land Surface Models in General Circulation Models Drought and Agriculture Monitoring Seasonal Precipitation Prediction Hydroclimatology Regional Drought Monitoring Crop Outlook Flood Forecast Improvements River Forecast Model Initialization Hydrometeorology Flash Flood Guidance (FFG) NWP Initialization for Precipitation Forecast Human Health Seasonal Heat Stress Outlook Hydroclimatology Near-Term Air Temperature and Heat Stress Forecast Hydrometeorology Disease Vector Seasonal Outlook Hydroclimatology Disease Vector Near-Term Forecast (NWP) Hydrometeorology Boreal Carbon Freeze/Thaw Date Freeze/Thaw State
8. Sources: Global Forecast/Analysis System Bulletins http://www.emc.ncep.noaa.gov/gmb/STATS/html/model_changes.html The ECMWF Forecasting System Since 1979 http://ecmwf.int/products/forecasts/guide/The_general_circulation_model.html Trends in Short-Term Weather (0-14 Days) NWP Resolution Hydrometeorology Applications: NWP SMAP
9. Operational Flood and Drought Applications Current : Empirical Soil Moisture Indices Based on Rainfall and Air Temperature ( By Counties >40 km and Climate Divisions >55 km ) Future : SMAP Soil Moisture Direct Observations of Soil Moisture at 10 km
10.
11. Data Products SMAP is Taking Aggressive Hardware & Softwate Measures to Detect & Partially Mitigate RFI Product Description Resolution Latency L1A_TB Radiometer Data in Time-Order - 12 hrs Instrument Data L1A_S0 Radar Data in Time-Order - 12 hrs L1B_TB Radiometer T B in Time-Order 36x47 km 12 hrs L1B_S0_LoRes Low Resolution Radar σ o in Time-Order 5x30 km 12 hrs L1C_S0_HiRes High Resolution Radar σ o in Half-Orbits 1-3 km 12 hrs L1C_TB Radiometer T B in Half-Orbits 36 km 12 hrs L2_SM_A Soil Moisture (Radar) 3 km 24 hrs Science Data (Half-Orbit) L2_SM_P Soil Moisture (Radiometer) 36 km 24 hrs L2_SM_A/P Soil Moisture (Radar+Radiometer) 9 km 24 hrs L3_F/T_A Freeze/Thaw State 3 km 50 hrs Science Data (Daily Composite) L3_SM_A Soil Moisture (Radar) 3 km 50 hrs L3_SM_P Soil Moisture (Radiometer) 36 km 50 hrs L3_SM_A/P Soil Moisture (Radar+Radiometer) 9 km 50 hrs L4_SM Soil Moisture (Surface and Root Zone ) 9 km 7 days Science Value-Added L4_C Carbon Net Ecosystem Exchange (NEE) 9 km 14 days
12.
13. L2_SM_AP Radar-Radiometer Algorithm Heterogeneity in Vegetation and Roughness Conditions Estimated by Sensitivities Γ in Radar HV Cross-Pol: T B ( M j ) is Used to Retrieve Soil Moisture at 9 km T B -Disaggregation Algorithm is: National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Temporal Changes in T B and σ pp are Related. Relationship Parameter β is Estimated at Radiometer-Scale Using Successive Overpasses. Based on PALS Observations From: SGP99, SMEX02, CLASIC and SMAPVEX08
14. SGP99, SMEX02, CLASIC and SMAPVEX08 WE2.T03.2 Paper #: 3398 Title: Evaluation of the SMAPCombined Radar-Radiometer Soil Moisture Algorithm Authors: N. Das, D. Entekhabi, S. Chan, S. Kim, E. Njoku, R. Dunbar, J.C. Shi Active-Passive Algorithm Performance Minimum Performance Algorithm RMSE: 0.055 [cm 3 cm -3 ] Active-Passive Algorithm RMSE: 0.033 [cm 3 cm -3 ]
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16. SMAP Algorithm Testbed TB (K) L2_SM_AP Combined Soil Moisture Product (9 km) L2_SM_P Radiometer Soil Moisture Product (36 km) L3_SM_A Radar Soil Moisture Product (3 km) L1C_TB Radiometer Brightness Temperature Product (36km) Simulated products generated with prototype algorithms on the SDS Testbed National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California WE2.T03.1 Paper #2069 Title: Utilization of ancillary data sets for SMAP Algorithm Development and Product Generation Authors: P. O'Neill, E. Podest, E. Njoku L1C_S0_Hi-Res Radar Backscatter Product (1-3 km)
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