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NASA NTRS2010

SERVIR: The Regional Visualization and Monitoring System

This slide presentation reviews the SERVIR program. SERVIR is a partnership between NASA and USAID and three international nodes: Central America, Africa, and the Himalaya region. SERVIR,using satellite observations and ground based observations, is used by decision makers to allow for improved monitoring of air quality, extreme weather, biodiversity, and changes in land cove and has also been used to respond to environmental threats, such as wildfires, floods, landslides, harmful algal blooms, and earthquakes.

Irwin, Daniel E.↗
NASA NTRS2011

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Brown, Molly E.↗
NASA NTRS2012

360 deg Camera Head for Unmanned Sea Surface Vehicles

The 360 camera head consists of a set of six color cameras arranged in a circular pattern such that their overlapping fields of view give a full 360 view of the immediate surroundings. The cameras are enclosed in a watertight container along with support electronics and a power distribution system. Each camera views the world through a watertight porthole. To prevent overheating or condensation in extreme weather conditions, the watertight container is also equipped with an electrical cooling unit and a pair of internal fans for circulation.

Townsend, Julie A.↗
NASA NTRS2012

Changes in the Intensity and Frequency of Atmospheric Blocking and Associated Heat Waves During Northern Summer Over Eurasia in the CMIP5 Model Simulations

The Russia heat wave and wild fires of the summer of 2010 was the most extreme weather event in the history of the country. Studies show that the root cause of the 2010 Russia heat wave/wild fires was an atmospheric blocking event which started to develop at the end of June and peaked around late July and early August. Atmospheric blocking in the summer of 2010 was anomalous in terms of the size, duration, and the location, which shifted to the east from the normal location. This and other similar continental scale severe summertime heat waves and blocking events in recent years have raised the question of whether such events are occurring more frequently and with higher intensity in a warmer climate induced by greenhouse gases. We studied the spatial and temporal distributions of the occurrence and intensity of atmospheric blocking and associated heat waves for northern summer over Eurasia based on CMIPS model simulations. To examine the global warming induced change of atmospheric blocking and heat waves, experiments for a high emissions scenario (RCP8.S) and a medium mitigation scenario (RCP4.S) are compared to the 20th century simulations (historical). Most models simulate the mean distributions of blockings reasonably well, including major blocking centers over Eurasia, northern Pacific, and northern Atlantic. However, the models tend to underestimate the number of blockings compared to MERRA and NCEPIDOE reanalysis, especially in western Siberia. Models also reproduced associated heat waves in terms of the shifting in the probability distribution function of near surface temperature. Seven out of eight models used in this study show that the frequency of atmospheric blocking over the Europe will likely decrease in a warmer climate, but slightly increase over the western Siberia. This spatial pattern resembles the blocking in the summer of 2010, indicating the possibility of more frequent occurrences of heat waves in western Siberia. In this talk, we will also discuss the potential effect of atmosphere-land feedback, particularly how the wetter spring affects the frequency and intensity of atmospheric blocking and heat wave during summer.

Kim, Kyu-Myong↗
NASA NTRS2012

GPM Avionics Module Heat Pipes Design and Performance Test Results

GPM is a satellite constellation to study precipitation formed from a partnership between NASA and the Japanese Aerospace Exploration Agency (JAXA). The GPM Core Observatory, being developed and tested at GSFC, serves as a reference standard to unify precipitation measurements from the GPM satellite constellation. The Core Observatory carries an advanced radar/radiometer system to measure precipitation from space. The scientific data gained from GPM will benefit both NASA and JAXA by advancing our understanding of Earth's water and energy cycle, improving forecasts of extreme weather events, and extending our current capabilities in using accurate and timely precipitation information to benefit society.

Ottenstein, Laura↗
NASA NTRS2012

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

USAID↗
NASA NTRS2014

Implications of Arctic Sea Ice Decline for the Earth System

Arctic sea ice decline has led to an amplification of surface warming and is projected to continue to decline from anthropogenic forcing, although the exact timing of ice-free summers is uncertain owing to large natural variability. Sea ice reductions affect surface heating patterns and the atmospheric pressure distribution, which may alter midlatitude extreme weather patterns. Increased light penetration and nutrient availability during spring from earlier ice breakup enhances primary production in the Arctic Ocean and its adjacent shelf seas. Ice-obligate marine mammals may be losers, whereas seasonally migrant species may be winners from rapid sea ice decline. Tundra greening is occurring across most of the Arctic, driven primarily by warming temperatures, and is displaying complex spatial patterns that are likely tied to other factors. Sea ice changes are affecting greenhouse gas exchanges as well as halogen chemistry in the Arctic. This review highlights the heterogeneous nature of Arctic change, which is vital for researchers to better understand.

Decline↗
NASA NTRS2013

A 6U CubeSat Constellation for Atmospheric Temperature and Humidity Sounding

We are currently developing a 118/183 GHz sensor that will enable observations of temperature and precipitation profiles over land and ocean. The 118/183 GHz system is well suited for a CubeSat deployment as ~10cm antenna aperture provides sufficiently small footprint sizes (is approx. 25km). This project will enable low cost, compact radiometer instrumentation at 118 and 183 GHz that would fit in a 6U CubeSat with the objective of mass-producing this design to enable a suite of small satellites to image the key geophysical parameters that are needed to improve prediction of extreme weather events. We will take advantage of past and current technology developments at JPL viz. HAMSR (High Altitude Microwave Scanning Radiometer), Advanced Component Technology (ACT'08) to enable low-mass and low-power high frequency airborne radiometers. The 35 nm InP enabling technology provides significant reduction in power consumption (Low Noise Amplifier + Mixer Block consumes 24 mW). In this paper, we will describe the design and implementation of the 118 GHz temperature sounder and 183 GHz humidity sounder instrument on the 6U CubeSat. In addition, a summary of radiometer calibration and retrieval techniques of the temperature and humidity will be discussed. The successful demonstration of this instrument on the 6U CubeSat would pave the way for the development of a constellation consisting of suite of these instruments. The proposed constellation of these 6U CubeSat radiometers would allow sampling of tropospheric temperature and humidity with fine temporal (on the order of minutes) and spatial resolution (is approx. 25 km).

radiometer↗
NASA NTRS2015

Preface

The potential effects of climate change on the food production system are raising concern both globally and regionally. The system is already challenged to deliver sufficient and healthy sustenance to all people, and is certain to be even further challenged as world population grows and price shocks loom. The prospect of climate change intensifies these challenges, raising the risk that more frequent and intense extreme weather events threaten the stability of agricultural production in regions around the globe. This two-part set is an important contribution to the ongoing Imperial College Press (ICP) Series on Climate Change Impacts, Adaptation, and Mitigation. This series aims to provide the know ledge base necessary for understanding and responding to climate change, in both its current form and future manifestations. In these volumes, ·leading agricultural researchers have come together to contribute their expertise on actual and potential climate change impacts, adaptation strategies, and mitigation efforts. This ongoing series is jointly published by The American Society of Agronomy (ASA), Crop Science Society of America (CSSA), and Soil Science Society of America (SSSA), together with ICP. We hope that this fruitful cooperation will continue for many years to come, as it spurs the global effort to define and meet the great food security and climate change challenges of our time.

farmlands↗
NASA NTRS2016

NASA's Earth Science Flight Program Meets the Challenges of Today and Tomorrow

NASA's Earth science flight program is a dynamic undertaking that consists of a large fleet of operating satellites, an array of satellite and instrument projects in various stages of development, a robust airborne science program, and a massive data archiving and distribution system. Each element of the flight program is complex and present unique challenges. NASA builds upon its successes and learns from its setbacks to manage this evolving portfolio to meet NASA's Earth science objectives. NASA fleet of 16 operating missions provide a wide range of scientific measurements made from dedicated Earth science satellites and from instruments mounted to the International Space Station. For operational missions, the program must address issues such as an aging satellites operating well beyond their prime mission, constellation flying, and collision avoidance with other spacecraft and orbital debris. Projects in development are divided into two broad categories: systematic missions and pathfinders. The Earth Systematic Missions (ESM) include a broad range of multi-disciplinary Earth-observing research satellite missions aimed at understanding the Earth system and its response to natural and human-induced forces and changes. Understanding these forces will help determine how to predict future changes, and how to mitigate or adapt to these changes. The Earth System Science Pathfinder (ESSP) program provides frequent, regular, competitively selected Earth science research opportunities that accommodate new and emerging scientific priorities and measurement capabilities. This results in a series of relatively low-cost, small-sized investigations and missions. Principal investigators whose scientific objectives support a variety of studies lead these missions, including studies of the atmosphere, oceans, land surface, polar ice regions, or solid Earth. This portfolio of missions and investigations provides opportunity for investment in innovative Earth science that enhances NASA's capability for better understanding the current state of the Earth system. ESM and ESSP projects often involve partnerships with other US agencies and/or international organizations. This adds to the complexity of mission development, but allows for a greater scientific return on NASA's investments. The Earth Science Airborne Science Program provides manned and unmanned aircraft systems that further science and advance the use of satellite data. NASA uses these assets worldwide in campaigns to investigate extreme weather events, observe Earth system processes, obtain data for Earth science modeling activities, and calibrate instruments flying aboard Earth science spacecraft. The Airborne Science Program has six dedicated aircraft and access to many other platforms. The Earth Science Multi-Mission Operations program acquires, preserves, and distributes observational data from operating spacecraft to support Earth Science research focus areas. The Earth Observing System Data and Information System (EOSDIS), which has been in operations since 1994, primarily accomplishes this. EOSDIS acquires, processes, archives, and distributes Earth Science data and information products. The archiving of NASA Earth Science information happens at eight Distributed Active Archive Centers (DAACs) and four disciplinary data centers located across the United States. The DAACs specialize by topic area, and make their data available to researchers around the world. The DAACs currently house over 9 petabytes of data, growing at a rate of 6.4 terabytes per day. NASA's current Earth Science portfolio is responsive to the National Research Council (NRC) 2007 Earth Science Decadal Survey and well as the 2010 NASA Response to President Obama's Climate Plan. As the program evolves into the future it will leverage the lessons learned from the current missions in operations and development, and plan for adjustments to future objectives in response to the anticipated 2017 NRC Decadal Survey.

Flight Program↗
NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗
NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗
NASA NTRS2016

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Agricultural↗
NASA NTRS2017

Hydrometeorological Hazards: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Responses

Hydrometeorological hazards are caused by extreme meteorological and climate events, such as floods, droughts, hurricanes,tornadoes, or landslides. They account for a dominant fraction of natural hazards and occur in all regions of the world, although the frequency and intensity of certain hazards and societies vulnerability to them differ between regions. Severe storms, strong winds, floods, and droughts develop at different spatial and temporal scales, but all can become disasters that cause significant infrastructure damage and claim hundreds of thousands of lives annually worldwide. Oftentimes, multiple hazards can occur simultaneously or trigger cascading impacts from one extreme weather event. For example, in addition to causing injuries, deaths, and material damage, a tropical storm can also result in flooding and mudslides, which can disrupt water purification and sewage disposal systems, cause overflow of toxic wastes, andincrease propagation of mosquito-borne diseases.

hydrometeorological↗
NASA NTRS2017

Online Visualization and Value Added Services of MERRA-2 Data at GES DISC

NASA climate reanalysis datasets from MERRA-2, distributed at the Goddard Earth Sciences Data and Information Services Center (GES DISC), have been used in broad research areas, such as climate variations, extreme weather, agriculture, renewable energy, and air quality, etc. The datasets contain numerous variables for atmosphere, land, and ocean, grouped into 95 products. The total archived volume is approximately 337 TB ( approximately 562K files) at the end of October 2017. Due to the large number of products and files, and large data volumes, it may be a challenge for a user to find and download the data of interest. The support team at GES DISC, working closely with the MERRA-2 science team, has created and is continuing to work on value added data services to best meet the needs of a broad user community. This presentation, using aerosol over Asia Monsoon as an example, provides an overview of the MERRA-2 data services at GES DISC, including: How to find the data? How many data access methods are provided? What are the best data access methods for me? How do download the subsetted (parameter, spatial, temporal) data and save in preferred spatial resolution and data format? How to visualize and explore the data online? In addition, we introduce a future online analytic tool designed for supporting application research, focusing on long-term hourly time-series data access and analysis.

Shen, Suhung↗
NASA NTRS2017

Investigating Access Performance of Long Time Series with Restructured Big Model Data

Data sets generated by models are substantially increasing in volume, due to increases in spatial and temporal resolution, and the number of output variables. Many users wish to download subsetted data in preferred data formats and structures, as it is getting increasingly difficult to handle the original full-size data files. For example, application research users such as those involved with wind or solar energy, or extreme weather events are likely only interested in daily or hourly model data at a single point (or for a small area) for a long time period, and prefer to have the data downloaded in a single file. With native model file structures, such as hourly data from NASA Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2), it may take over 10 hours for the extraction of parameters-of-interest at a single point for 30 years. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is exploring methods to address this particular user need. One approach is to create value-added data by reconstructing the data files. Taking MERRA-2 data as an example, we have tested converting hourly data from one-day-per-file into different data cubes, such as one-month, or one-year. Performance is compared for reading local data files and accessing data through interoperable services, such as OPeNDAP. Results show that, compared to the original file structure, the new data cubes offer much better performance for accessing long time series. We have noticed that performance is associated with the cube size and structure, the compression method, and how the data are accessed. An optimized data cube structure will not only improve data access, but also may enable better online analysis services

reanalysis↗
NASA NTRS2017

Climatic History of the Northeastern United States During the Past 3000 Years

Many ecosystem processes that influence Earth system feedbacks - vegetation growth, water and nutrient cycling, disturbance regimes - are strongly influenced by multidecadal- to millennial-scale climate variations that cannot be directly observed. Paleoclimate records provide information about these variations, forming the basis of our understanding and modeling of them. Fossil pollen records are abundant in the NE US, but cannot simultaneously provide information about paleoclimate and past vegetation in a modeling context because this leads to circular logic. If pollen data are used to constrain past vegetation changes, then the remaining paleoclimate archives in the northeastern US (NE US) are quite limited. Nonetheless, a growing number of diverse reconstructions have been developed but have not yet been examined together. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions (primarily summer) show a long-term cooling trend (1000BCE - 1700CE) consistent with hemispheric-scale reconstructions, while hydroclimate data show gradually wetter conditions through the present day. Multiple proxies suggest that a prolonged, widespread drought occurred between 550 and 750CE. Dry conditions are also evident during the Medieval Climate Anomaly, which was warmer and drier than the Little Ice Age and drier than today. There is some evidence for an acceleration of the longer-term wetting trend in the NE US during the past century; coupled with an abrupt shift from decreasing to increasing temperatures in the past century, these changes could have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US to make inter-proxy comparisons and to improve estimates of uncertainty in reconstructions.

Marlon, Jennifer R.↗
NASA NTRS2017

Workshop on Using NASA Data for Time-Sensitive Applications

Over the past decade, there has been an increase in the use of NASA's Earth Observing System (EOS) data and imagery for time-sensitive applications such as monitoring wildfires, floods, and extreme weather events. In September 2016, NASA sponsored a workshop for data users, producers, and scientists to discuss the needs of time-sensitive science applications.

Davies, Diane K.↗