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NASA NTRS2014

NMME Monthly / Seasonal Forecasts for NASA SERVIR Applications Science

This work details use of the North American Multi-Model Ensemble (NMME) experimental forecasts as drivers for Decision Support Systems (DSSs) in the NASA / USAID initiative, SERVIR (a Spanish acronym meaning "to serve"). SERVIR integrates satellite observations, ground-based data and forecast models to monitor and forecast environmental changes and to improve response to natural disasters. Through the use of DSSs whose "front ends" are physically based models, the SERVIR activity provides a natural testbed to determine the extent to which NMME monthly to seasonal projections enable scientists, educators, project managers and policy implementers in developing countries to better use probabilistic outlooks of seasonal hydrologic anomalies in assessing agricultural / food security impacts, water availability, and risk to societal infrastructure. The multi-model NMME framework provides a "best practices" approach to probabilistic forecasting. The NMME forecasts are generated at resolution more coarse than that required to support DSS models; downscaling in both space and time is necessary. The methodology adopted here applied model output statistics where we use NMME ensemble monthly projections of sea-surface temperature (SST) and precipitation from 30 years of hindcasts with observations of precipitation and temperature for target regions. Since raw model forecasts are well-known to have structural biases, a cross-validated multivariate regression methodology (CCA) is used to link the model projected states as predictors to the predictands of the target region. The target regions include a number of basins in East and South Africa as well as the Ganges / Baramaputra / Meghna basin complex. The MOS approach used address spatial downscaling. Temporal disaggregation of monthly seasonal forecasts is achieved through use of a tercile bootstrapping approach. We interpret the results of these studies, the levels of skill by several metrics, and key uncertainties.

Robertson, Franklin R.↗

NASA NTRSDate not supplied

Water and Disasters Tools and Development Across the SERVIR Program and Lessons-Learned Within the Hindukush Himalayan Region

The NASA-USAID SERVIR program works in partnership with leading regional organizations around the globe to help developing countries use information provided by earth observing satellites and geospatial technologies. The SERVIR Applied Sciences Team (AST) is assembled on a 3-year rotating cycle to partner with these regional organizations on the joint development and implementation of tools and techniques that can be used operationally in each region. The Portfolio of AST projects address regional priorities in four thematic service areas: Land Cover, Land Use Change & Ecosystems; Water and water-related Disasters; Weather & Climate and Food Security & Agriculture. An important goal of AST is knowledge sharing across the different regional entities to share tools and technologies for the improvement of all. This talk will focus on the Water and Disasters service area and review how tools developed in the Hindu Kush Himalayan region in partnership with the International Centre for Integrated Mountain Development (ICIMOD) have evolved over the AST cycles. We will provide examples of stakeholder engagement both at ICIMOD and across the regional partners they support. We will also share recent examples and lessons learned with users from other SERVIR regions.

Lori A Schultz↗

NASA NTRS2017

Experiences in Applying Earth Observing Satellite Technology in SERVIR Regions with an Emphasis on Disasters: Successes, Lessons and Paths Forward

Earth observing satellites offer a unique perspective of our environment from the vantage point of space. Repeated measurements of the Earths subsystems such as the biosphere, atmosphere, lithosphere, hydrosphere, and of humans interactions with their environments, allow for a better understanding of Earth system processes, and they can provide input for decision making in areas of environmental management and disaster risk reduction. SERVIR is a joint initiative of the US National Aeronautics and Space Administration (NASA) and the US Agency for International Development (USAID) that began in 2005 and has been active in applying Earth observations for sustainable development in many regions around the world, recently the Lower Mekong and West Africa regions. This talk will highlight some successes achieved and lessons learned through SERVIR in Central America, Eastern Southern Africa, and the Hindu Kush-Himalaya region, focusing on disasters. We will also present opportunities for enhanced decision making with Earth observations and geospatial technologies in the Lower Mekong region.

SERVIR↗

NASA NTRS2010

SERVIR-Africa: Developing an Integrated Platform for Floods Disaster Management in Africa

SERVIR-Africa is an ambitious regional visualization and monitoring system that integrates remotely sensed data with predictive models and field-based data to monitor ecological processes and respond to natural disasters. It aims addressing societal benefits including floods and turning data into actionable information for decision-makers. Floods are exogenous disasters that affect many parts of Africa, probably second only to drought in terms of social-economic losses. This paper looks at SERVIR-Africa's approach to floods disaster management through establishment of an integrated platform, floods prediction models, post-event flood mapping and monitoring as well as flood maps dissemination in support of flood disaster management.

Macharia, Daniel↗

NASA NTRS2013

Evaluating NMME Seasonal Forecast Skill for use in NASA SERVIR Hub Regions

The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The coupled forecasts have numerous potential applications, both national and international in scope. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in driving applications models in hub regions including East Africa, the Hindu Kush- Himalayan (HKH) region and Mesoamerica. A prerequisite for seasonal forecast use in application modeling (e.g. hydrology, agriculture) is bias correction and skill assessment. Efforts to address systematic biases and multi-model combination in support of NASA SERVIR impact modeling requirements will be highlighted. Specifically, quantilequantile mapping for bias correction has been implemented for all archived NMME hindcasts. Both deterministic and probabilistic skill estimates for raw, bias-corrected, and multi-model ensemble forecasts as a function of forecast lead will be presented for temperature and precipitation. Complementing this statistical assessment will be case studies of significant events, for example, the ability of the NMME forecasts suite to anticipate the 2010/2011 drought in the Horn of Africa and its relationship to evolving SST patterns.

Roberts, J. Brent↗

NASA NTRS2006

NASA'S SERVIR Gulf of Mexico Project: The Gulf of Mexico Regional Collaborative (GoMRC)

The Gulf of Mexico Regional Collaborative (GoMRC) is a NASA-funded project that has as its goal to develop an integrated, working, prototype IT infrastructure for Earth science data, knowledge and models for the five Gulf U.S. states and Mexico, and to demonstrate its ability to help decision-makers better understand critical Gulf-scale issues. Within this preview, the mission of this project is to provide cross cutting solution network and rapid prototyping capability for the Gulf of Mexico region, in order to demonstrate substantial, collaborative, multi-agency research and transitional capabilities using unique NASA data sets and models to address regional problems. SERVIR Mesoamerica is seen as an excellent existing framework that can be used to integrate observational and GIs data bases, provide a sensor web interface, visualization and interactive analysis tools, archival functions, data dissemination and product generation within a Rapid Prototyping concept to assist decision-makers in better understanding Gulf-scale environmental issues.

Quattrochi, Dale A.↗

NASA NTRS2011

ISERV Pathfinder. The ISS SERVIR Environmental Research and Visualization System

SERVIR integrates Earth observations (e.g., space imagery), predictive models, and in situ data to provide timely information products to support environmental decision makers. ISERV propoesed development -- ISERV-W: Internal Visible/Near-Infrared (VNIR), attached to ISS via Window Observational Research Facility (WORF), ISERV-E: External Visible/Broad-Infrared (V/IR) and ISERV-PM: External Passive Microwave.

Howell, Burgess↗

NASA NTRS2012

SERVIR: From Space to Village

SERVIR is a NASA/USAID partnership to improve environmental management and resilience to climate change by strengthening the capacity of governments and other key stakeholders to integrate earth observation information and geospatial technologies into development decision-making

Irwin, Dan↗

NASA NTRS2012

SERVIR and Public Health

Servir is a NASA-USAID partnership to improve environmental management and resilience to climate change by strengthening the capacity of governments and other key stakeholders to integrate Earth observations into development decision-making

Moreno-Madrinan, Max J.↗

NASA NTRS2014

SERVIR Presentation for the Hyperwall at the ESRI International Users Conference

From space, we can view our planet in new ways. As a joint initiative of NASA and USAID working in partnership with leading regional organizations, SERVIR connects space to village by helping people in developing countries use that view to gain knowledge and insights about their environments. We teach regional decision-makers to use Earth observation satellite data, Geographic Information Systems, and predictive models for addressing issues such as water and land use, natural disasters, agricultural problems, biodiversity conservation, and more to improve the lives, livelihoods, safety, and future of the people in their countries.

Irwin, Dan↗

NASA NTRS2014

SERVIR Support to NSDI Efforts in Mesoamerica, Africa and the Himalayas

SERVIR is a joint effort between NASA, USAID to build or improve capacities in developing regions to help adaptation to climate change by taking advantage of Earth Observation data for decision making. The project began in 2004, in Mesoamerica, partnering with the Central American Commission for Environment and Development(CCAD), the World Bank and CATHALAC. CATHALAC, located in Panama, serves as the regional hub for Mesoamerica since 2005. Two additional regional hubs have been established (in Easters & Western Africa - at RCMRD, Kenya, and The Himalayas- at ICIMOD, Nepal), and two more regional hubs are soon to be launched.

Delgado, Francisco↗

NASA NTRS2018

SERVIR: Connecting Space to Village

From space, we can view our planet in new ways. SERVIR empowers people in developing countries to use that view for gaining knowledge and insights about their environments and adaptation to a changing climate. We work with regional decision-makers to foster use of Earth observation satellite data, GIS, and predictive models for addressing water and land use, natural disasters, agricultural problems, biodiversity, and more. These tools can improve the lives, livelihoods, safety, and future of people in communities around the world.

Limaye, Ashutosh S.↗

NASA NTRS2018

SERVIR Connecting Space to Village

Puzzi Nicolau, Andrea↗

NASA NTRS2019

Providing Data Access and Analysis Capabilities to SERVIR’s Data-Sparse Regions

In developing regions of the world, the communications infrastructure pose enormous challenges for using Earth observation data. Limited internet bandwidth along with the high costs make it almost impossible to process and extract zonal statistics over large periods of time for even small geographic areas. In such cases, downloading daily rainfall data or dekadal series of NDVI data would take days and consume all the bandwidth allocated to an organization (for reference, internet connections in Niger would cost thousands of dollars per month at a maximum - and unreliable - bandwidth of just 10 Mbps). Running crop models or hydrological models typically require several years of historic data over the area of interest (AOI). In some cases, these AOIs are relatively small compared to the footprint of individual earth observation granules. Hence, systems that let the stakeholders subset the data to download to a user specified area, or even submit processing requests that let them download small result files for the AOI become critical. The SERVIR program has developed a tool to provide this type of access to help decision makers in developing regions use long time series of adjusted rainfall data (CHIRPS), NDVI values, seasonal weather forecasts, evaporative stress indices and others in a very efficient manner. This system, named ClimateSERV (https://climateserv.servirglobal.net) ingests the datasets in an automated fashion and allows interactive access (through a web application), or automated access through a simple API that developers can quickly incorporate in independent applications. This way, the extraction of daily averages of rainfall over a 50 square Km area through 30 years of archived data takes only a few seconds to process, and the results can be presented on an online chart or downloaded in a comma separated file that's only a few Kb.

Ashmall, William↗

NASA NTRS2014