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Lessons Learned from Autonomous Sciencecraft Experiment

An Autonomous Science Agent has been flying onboard the Earth Observing One Spacecraft since 2003. This software enables the spacecraft to autonomously detect and responds to science events occurring on the Earth such as volcanoes, flooding, and snow melt. The package includes AI-based software systems that perform science data analysis, deliberative planning, and run-time robust execution. This software is in routine use to fly the EO-l mission. In this paper we briefly review the agent architecture and discuss lessons learned from this multi-year flight effort pertinent to deployment of software agents to critical applications.

Autonomous Sciencecraft Experiment (ASE)↗

Warm Season Subseasonal Variability and Climate Extremes in the Northern Hemisphere: The Role of Stationary Rossby Waves

This study examines the nature of boreal summer subseasonal atmospheric variability based on the new NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) for the period 1979-2010. An analysis of the June, July and August subseasonal 250hPa v-wind anomalies shows distinct Rossby wave-like structures that appear to be guided by the mean jets. On monthly subseasonal time scales, the leading waves (the first 10 rotated empirical orthogonal functions or REOFs of the 250hPa v-wind) explain about 50% of the Northern Hemisphere vwind variability, and account for more than 30% (60%) of the precipitation (surface temperature) variability over a number of regions of the northern middle and high latitudes, including the U.S. northern Great Plains, parts of Canada, Europe, and Russia. The first REOF in particular, consists of a Rossby wave that extends across northern Eurasia where it is a dominant contributor to monthly surface temperature and precipitation variability, and played an important role in the 2003 European and 2010 Russian heat waves. While primarily subseasonal in nature, the Rossby waves can at times have a substantial seasonal mean component. This is exemplified by REOF 4 which played a major role in the development of the most intense anomalies of the U.S. 1988 drought (during June) and the 1993 flooding (during July), though differed in the latter event by also making an important contribution to the seasonal mean anomalies. A stationary wave model (SWM) is used to reproduce some of the basic features of the observed waves and provide insight into the nature of the forcing. In particular, the responses to a set of idealized forcing functions are used to map the optimal forcing patterns of the leading waves. Also, experiments to reproduce the observed waves with the SWM using MERRA-based estimates of the forcing indicate that the wave forcing is dominated by sub-monthly vorticity transients.

Schubert, Siegfried↗

The 28 November 2020 Landslide, Tsunami, and Outburst Flood – A Hazard Cascade Associated With Rapid Deglaciation at Elliot Creek, British Columbia, Canada

We describe and model the evolution of a recent landslide, tsunami, outburst flood, and sediment plume in the southern Coast Mountains, British Columbia, Canada. On November 28, 2020, about 18 million m3 of rock descended 1,000 m from a steep valley wall and traveled across the toe of a glacier before entering a 0.6 km2 glacier lake and producing >100-m high run-up. Water overtopped the lake outlet and scoured a 10-km long channel before depositing debris on a 2-km2 fan below the lake outlet. Floodwater, organic debris, and fine sediment entered a fjord where it produced a 60+km long sediment plume and altered turbidity, water temperature, and water chemistry for weeks. The outburst flood destroyed forest and salmon spawning habitat. Physically based models of the landslide, tsunami, and flood provide real-time simulations of the event and can improve understanding of similar hazard cascades and the risk they pose. Plain Language Summary Glacier retreat exposes unstable slopes that can suddenly fail. We describe and model one such event with far-reaching consequences. The landslide mass (50 million tonnes, equivalent to the combined mass of all Canadian automobiles) entered and suddenly drained a 0.6-km2 alpine lake in the southern Coast Mountains of British Columbia. Displaced water destroyed salmon-spawning habitat over a distance of 8.5 km and created a plume of sediment and organic matter more than 60 km from the head of the fjord into which the floodwaters discharged. Physically based models are able to simulate the hazard cascade, and such models could be used to improve hazard and risk assessments of these events under future climate change.

M. Geertsema↗

Toa Baja Disasters: Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Mitigation Efforts and Educate the Public

Toa Baja, located just west of San Juan in Puerto Rico, is known as “the underwater city” due to its propensity to flood. The city contains the mouth of the island’s longest river, Río de la Plata, which drains into the Atlantic Ocean on the northern edge of the municipality. Proximity to these major water features and the flat, low terrain contribute to the flood-prone nature of the area. During tropical storm events, such as Hurricane Maria in 2017, Toa Baja experienced inundation of up to 20 feet. Changes in the global climate system are causing more intense and frequent tropical storms, making places like Toa Baja subject to irreparable damage. This NASA DEVELOP project collaborated with the Municipio Autónomo de Toa Baja, ResilientSEE, and the Massachusetts Institute of Technology Urban Risk Lab to supplement recent 2018 Federal Emergency Management Agency Hydraulic Engineering Centers-River Analysis System flood maps, which designated 63% of the area as a flood plain. The analysis provides a high-resolution interpretation of flood susceptibility using a variety of factors that collectively influence the likelihood of flooding. Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) data processed with Google Earth Engine scripting identified historical inundation and was used for validation purposes. Socioeconomic factors were combined with the inundation layer producing a final risk output. These outputs will improve public understanding of exposure to flood risk in Toa Baja and provide scientific evidence for flood mitigation advocacy.

Disasters↗

Toa Baja Disasters: Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Mitigation Efforts and Educate the Public

Toa Baja, located just west of San Juan in Puerto Rico, is known as “the underwater city” due to its propensity to flood. The city contains the mouth of the island’s longest river, Río de la Plata, which drains into the Atlantic Ocean on the northern edge of the municipality. Proximity to these major water features and the flat, low terrain contribute to the flood-prone nature of the area. During tropical storm events, such as Hurricane Maria in 2017, Toa Baja experienced inundation of up to 20 feet. Changes in the global climate system are causing more intense and frequent tropical storms, making places like Toa Baja subject to irreparable damage. This NASA DEVELOP project collaborated with the Municipio Autonómo de Toa Baja, ResilientSEE, and the Massachusetts Institute of Technology Urban Risk Lab to supplement recent 2018 Federal Emergency Management Agency Hydraulic Engineering Centers-River Analysis System flood maps, which designated 63% of the area as a flood plain. The analysis provides a high-resolution interpretation of flood susceptibility using a variety of factors that collectively influence the likelihood of flooding. Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR) data processed with Google Earth Engine scripting identified historical inundation and was used for validation purposes. Socioeconomic factors were combined with the inundation layer producing a final risk output. These outputs will improve public understanding of exposure to flood risk in Toa Baja and provide scientific evidence for flood mitigation advocacy.

Disasters↗

Interconnected Hydrologic Extreme Drivers and Impacts Depicted By Remote Sensing Data Assimilation

In a changing climate, the likelihood of hydrologic extremes has been increasing as climate change can impact both means and extremes4 of hydrologic cycle processes, potentially resulting in an increased frequency of floods in some regions and decreases in others. In a warming world, the physical processes that affect hydrologic response, such as rain-on snow runoff events, are also changing, such that the seasonality of streamflow has been shifting. The geography of rain-on-snow runoff events is predicted to move from low to high elevations. In addition to floods, there is also potential for an increase in dry extremes in a warming world with increased drought frequency and occurrences in many parts of the world. The increased frequency of drought and heatwave events is expected to have consequences such as escalating crop failures in future projection scenarios1. Thus, the consensus of literature shows that climate change is increasing the magnitude and frequency of extreme hydrologic events, and the human influence in many of these events is substantial.

Timothy M. Lahmers↗

Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: the Case of Rio deJaneiro, Brazil

Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001-2019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4mm/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12-35%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.

IMERG↗

Large-Scale Influences on Atmospheric River–Induced Extreme Precipitation Events Along the Coast of Washington State

Transient, narrow plumes of strong water vapor transport, referred to as Atmospheric Rivers (ARs) are responsible for much of the precipitation along the west coast of the United States. Along the coast of Oregon and Washington, the most intense cool season precipitation events are almost always induced by an AR and can result in detrimental impacts on society due to mudslides and flooding. It is therefore important to understand the large scale influence on extreme AR events so that they can be accurately predicted on timescales ranging from numerical weather prediction to seasonal forecasts. Here, characteristics of ARs that result in observed extreme precipitation events are compared to typical ARs on the coast of Washington State using data from the Modern Era Retrospective analysis for Research and Applications, Version 2. In addition to more intense water vapor transport, notable differences in the synoptic scale forcing are present during extreme precipitation events that are not present during typical AR events. In particular, an anomalously deep low pressure system is stationed to the west in the Gulf of Alaska, alongside a jet streak overhead. Attention will also be given to subseasonal and seasonal teleconnection patterns that are known to influence the weather in the Pacific Northwest of the United States. While little influence can be seen from the phase of the El Nino Southern Oscillation, Pacific Decadal Oscillation, and Pacific North American Pattern, the Madden Julian Oscillation (MJO) can play a role in determining the strength of precipitation associated with in AR on the Washington Coast. Lastly, interactions between the MJO and other teleconnection patterns will be explored to determine key features that should be investigated when making subseasonal predictions for AR activity and the associated precipitation in the Pacific Northwest.

Collow, Allison↗

Mars geologic mapping program: Review and highlights

The Mars Geologic Mapping (MGM) Program was introduced by NASA in 1987 as a new initiative in the Planetary Geology and Geophysics (PGG) Program. The overall purpose of the program is to support research on topical science problems that address specific questions. Among the objectives of the project are: (1) to produce highly detailed geologic maps that will greatly increase the knowledge of the materials and processes that have contributed to the evolutionary history of Mars; (2) to define areas of special interest for possible future investigation by planned missions (Mars Observer, Mars Sample Return); and (3) to maintain the interest of the planetary community in the development of new concepts and the re-evaluation of Martian geology as new data in usable form become available. Some interesting highlights of the geologic mapping indicate that multiple flood episodes occurred at different times during the Hesperian Period in both Kasei and Maja Valles. Studies of small channels in the Memnonia, Mangala, and Tharsis regions show that fluvial events appear to have occurred during the Amazonian Period at equatorial latitudes. Flood waters occurred during the Amazonian Period at equatorial latitudes. Flood waters from Mangala Valles may have seeped into surficial materials with the subsequent development of numerous sapping channels and debris flows; this suggests that the ancient highland terrain consists of relatively unconsolidated materials. Multiple layers were observed for the first time in the ridged plains lava flows covering large areas of Lunae Planum; some wrinkle ridges in this area are associated with grabens and collapse volcanic units at Hadriaca and Tyrrhena Paterae indicates that the units may have been emplaced by gravity-driven pyroclastic flows. Unlike the north polar layered deposits, those in the south polar region show no angular unconformities or evidence of faulting and folding. Water ice in the south polar layered deposits may be protected from solar heating and sublimation by a weathering rind or lag deposit on the surface.

Scott, David H.↗

A Dusty Atmospheric River Brings Floods to the Middle East

Torrential rainfall and rapid snowmelt in April 2017 caused deadly floods in northwestern Iran. An atmospheric river (AR), propagating across the Middle East and North Africa, was found responsible for this extreme event. The snowmelt was triggered by precipitation and warm advection associated with the AR. Total satellite-based rainfall for April 2017 was moderately below normal, suggesting that a heavy flood can happen during dry years. The AR was fed by moisture from the Mediterranean and Red Seas. Despite its adverse societal consequences, this event was beneficial to the recovery of the desiccating Lake Urmia. The impacts of this AR were not limited to flooding; it also facilitated dust transport to the region. This distinct characteristic of the ARs in the Middle East is attributed to major mineral dust sources located along their pathways. This event was reasonably predicted at 7-day lead time, crucially important for successful early warning systems.

Atmospheric river↗

Volcanic features of far side Crater Aitken

Volcanic features of the far side Aitken Crater including post-impact volcanism and volcanic events extending beyond the period of mare type crater flooding are discussed. The features attributed to extrusions of viscous lava are also discussed.

Bryan, W. B.↗

GPM Mission Overview and U.S. Science Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products [1-2]. Water is fundamental to life on Earth. Knowing where and how much rain and snow falls globally is vital to understanding how weather and climate impact both our environment and Earth's water and energy cycles, including effects on agriculture, fresh water availability, and responses to natural disasters. Since rainfall and snowfall vary greatly from place to place and over time, satellites can provide more uniform observations of rain and snow around the globe than ground instruments, especially in areas where surface measurements are difficult. Relative to current global rainfall products, GPM data products will be characterized by: (l) more accurate instantaneous precipitation measurements (especially for light rain and cold-season solid precipitation), (2) more frequent sampling by an expanded constellation of domestic and international microwave radiometers including operational humidity sounders, (3) intercalibrated microwave brightness temperatures from constellation radiometers within a unified framework, and (4) physical-based precipitation retrievals from constellation radiometers using a common a priori cloud/hydrometeor database derived from GPM Core sensor measurements. The cornerstone of the GPM mission is the deployment of a Core Observatory in a unique 65 non-Sun-synchronous orbit to serve as a physics observatory and a reference standard to unify precipitation measurements by a constellation of dedicated and operational passive microwave sensors. The design of the GPM Core Observatory is an advancement of the Tropical Rainfall Measuring Mission (TRMM)'s highly successful rain-sensing package. The Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a multichannel (l0-183 GHz) GPM Microwave Radiometer (GMI). Since light rain and falling snow account for a significant fraction of precipitation occurrence in middle and high latitudes, the GPM instruments extend the capabilities of the TRMM sensors to detect falling snow, measure light rain, and provide, for the first time, quantitative estimates of microphysical properties of precipitation particles. The combined use of DPR and GMI measurements will place greater constraints on possible solutions to radiometer retrievals to improve the accuracy and consistency of precipitation retrievals from all constellation radiometers. The GMI uses 13 different microwave channels to observe energy from the different types of precipitation through clouds for estimating everything from heavy to light rain and for detecting falling snow. As the satellite passes over Earth, the GMI constantly scans a region 885 kilometers across. The Ball Aerospace and Technology Corporation built the GMI under contract with NASA Goddard Space Flight Center. The DPR provides three-dimensional information about precipitation particles derived from reflected energy by these particles at different heights within the cloud system. The two frequencies of the DPR also allow the radar to infer the sizes of precipitation particles and offer insights into a storm's physical characteristics. The Ka-band frequen~y scans across a region of 125 kilometers and is nested within the wider scan of the Ku-band frequency of 245 kilometers. The Japan Aerospace and Exploration Agency (JAXA) and Japan's National Institute of Information and Communications Technology (NICT) built the DPR. The Core Observatory satellite will fly at an altitude of 253 miles (407 kilometers) in a non-Sun-synchronous orbit that covers the Earth from 65 S to 65 N - from about the Antarctic Circle to the Arctic Circle. The GPM Core Observatory is being developed and tested at NASA Goddard Space Flight Center. Once complete, a Japanese H-lIA rocket will carry thPM Core Observatory into orbit from Tanegashima Island, Japan in 2014. The GPM constellation is envisioned to comprise 8 or more microwave sensors provided by partners, including both conical imagers and cross-track sounders. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Additional partnerships are under development to include microwave radiometers on the French-Indian Megha-Tropiques satellite and U.S. Defense Meteorological Satellite Program (DMSP) satellites, as well as humidity sounders or precipitation sensors on operational satellites such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), NOAA-NASA Joint Polar Satellite System (JPSS) satellites, European MetOp satellites, and DMSP follow-on sensors. In addition, data from Chinese and Russian microwave radiometers may be available through international cooperation under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). GPM's next-generation global precipitation data will lead to scientific advances and societal benefits in the following areas: (1) Improved knowledge of the Earth's water cycle and its link to climate change (2) New insights into precipitation microphysics, storm structures and large-scale atmospheric processes (3) Better understanding of climate sensitivity and feedback processes (4) Extended capabilities in monitoring and predicting hurricanes and other extreme weather events (5) Improved forecasting capabilities for natural hazards, including floods, droughts and landslides. (6) Enhanced numerical prediction skills for weather and climate (7) Better agricultural crop forecasting and monitoring of freshwater resources. An overview of the GPM mission concept and science activities in the United States, together with an update on international collaborations in radiometer intercalibration and ground validation, will be presented.

Hou, Arthur Y.↗

Climate Change Adaptation Science Activities at NASA Johnson Space Center

The Johnson Space Center (JSC), located in the southeast metropolitan region of Houston, TX is the prime NASA center for human spaceflight operations and astronaut training, but it also houses the unique collection of returned extraterrestrial samples, including lunar samples from the Apollo missions. The Center's location adjacent to Clear Lake and the Clear Creek watershed, an estuary of Galveston Bay, puts it at direct annual risk from hurricanes, but also from a number of other climate-related hazards including drought, floods, sea level rise, heat waves, and high wind events all assigned Threat Levels of 2 or 3 in the most recent NASA Center Disaster/Risk Matrix produced by the Climate Adaptation Science Investigator Working Group. Based on prior CASI workshops at other NASA centers, it is recognized that JSC is highly vulnerable to climate-change related hazards and has a need for adaptation strategies. We will present an overview of prior CASI-related work at JSC, including publication of a climate change and adaptation informational data brochure, and a Resilience and Adaptation to Climate Risks Workshop that was held at JSC in early March 2012. Major outcomes of that workshop that form a basis for work going forward are 1) a realization that JSC is embedded in a regional environmental and social context, and that potential climate change effects and adaptation strategies will not, and should not, be constrained by the Center fence line; 2) a desire to coordinate data collection and adaptation planning activities with interested stakeholders to form a regional climate change adaptation center that could facilitate interaction with CASI; 3) recognition that there is a wide array of basic data (remotely sensed, in situ, GIS/mapping, and historical) available through JSC and other stakeholders, but this data is not yet centrally accessible for planning purposes.

Stefanov, William L.↗

Surface Freshwater Storage and Variability in the Amazon Basin from Multi-Satellite Observations, 1993-2007

The amount of water stored and moving through the surface water bodies of large river basins (river, floodplains, wetlands) plays a major role in the global water and biochemical cycles and is a critical parameter for water resources management. However, the spatio-temporal variations of these freshwater reservoirs are still widely unknown at the global scale. Here, we propose a hypsographic curve approach to estimate surface freshwater storage variations over the Amazon basin combining surface water extent from a multi-satellite-technique with topographic data from the Global Digital Elevation Model (GDEM) from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Monthly surface water storage variations for 1993-2007 are presented, showing a strong seasonal and interannual variability, and are evaluated against in situ river discharge and precipitation. The basin-scale mean annual amplitude of approx. 1200 cu km is in the range of previous estimates and contributes to about half of the Gravity Recovery And Climate Experiment (GRACE) total water storage variations. For the first time, we map the surface water volume anomaly during the extreme droughts of 1997 (October-November) and 2005 (September-October) and found that during these dry events the water stored in the river and flood-plains of the Amazon basin was, respectively, approx. 230 (approx. 40%) and 210 (approx. 50%) cu km below the 1993-2007 average. This new 15year data set of surface water volume represents an unprecedented source of information for future hydrological or climate modeling of the Amazon. It is also a first step toward the development of such database at the global scale.

Storage↗

Dynamical Mechanisms Underlying the 2022/23 California Flooding: Analysis With A Stationary Wave Model

In late December 2022 and the first half of January 2023, much of California experienced an unprecedented series of atmospheric rivers that produced heavy rains and near-record flooding. Previous work shows that a chain of dynamical events contributed to the extreme precipitation, including the development of a Rossby wave (as a result of forcing linked to the MJO) that emerged from the Indian Ocean in mid-December, and the subsequent development of a persistent positive Pacific North American (PNA) pattern that ultimately directed moisture onto the US West Coast starting in late December. Here, we use a stationary wave model (SWM) to further elucidate the dynamical and thermodynamical processes that drove the aforementioned chain of events. The results reveal the following: 1) The mid-December Rossby wave was likely induced by vorticity stretching and advection in the middle East linked indirectly to the MJO, 2) The initial development of the PNA in late December was triggered by transient and stretching sources of vorticity in the Pacific that were themselves induced by the aforementioned Rossby wave, and 3) The PNA was maintained through mid-January in part by diabatic heating west of Hawaii that was associated with anomalous precipitation influenced by the PNA circulation anomalies, thus representing a feedback on the PNA. One key finding from the SWM analysis is the limited direct role of tropical heating for inducing any of the dynamical mechanisms related to the California extreme event.

Anthony M. DeAngelis↗

Dynamical Mechanisms Underlying the 2022/23 California Flooding: Analysis With A Stationary Wave Model

In late December 2022 and the first half of January 2023, much of California experienced an unprecedented series of atmospheric rivers that produced heavy rains and near-record flooding. Previous work shows that a chain of dynamical events contributed to the extreme precipitation, including the development of a Rossby wave (as a result of forcing linked to the MJO) that emerged from the Indian Ocean in mid-December, and the subsequent development of a persistent positive Pacific North American (PNA) pattern that ultimately directed moisture onto the US West Coast starting in late December. Here, we use a stationary wave model (SWM) to further elucidate the dynamical and thermodynamical processes that drove the aforementioned chain of events. The results reveal the following: 1) The mid-December Rossby wave was likely induced by vorticity stretching and advection in the middle East linked indirectly to the MJO, 2) The initial development of the PNA in late December was triggered by transient and stretching sources of vorticity in the Pacific that were themselves induced by the aforementioned Rossby wave, and 3) The PNA was maintained through mid-January in part by diabatic heating west of Hawaii that was associated with anomalous precipitation influenced by the PNA circulation anomalies, thus representing a feedback on the PNA. One key finding from the SWM analysis is the limited direct role of tropical heating for inducing any of the dynamical mechanisms related to the California extreme event.

Anthony M. DeAngelis↗

The NASA Disasters Response Coordination System’s (DRCS) Response to the 2024 Hurricane Season

The National Aeronautics and Space Administration (NASA) Disasters Response Coordination System (DRCS) leverages the best available science and expertise to aid federal, state, local, and non-governmental organization (NGO) partners in addressing identified needs during a disaster response. During the 2024 hurricane season, the DRCS activated for seven hurricanes/tropical storms, providing openly available geospatial data through NASA’s Disasters Mapping Portal. Hurricanes Helene and Milton were major hurricanes that impacted the southeastern United States within weeks of one another. Impacts from Helene and Milton to the region included inland flooding, record coastal storm surge, over a thousand landslides, and regional power and telecommunications outages. In response to Helene and Milton, DRCS provided actionable information and products to stakeholders, including Synthetic Aperture Radar (SAR) analysis for landslide and flood detection, Black Marble nighttime lights products for assessing power outages, and Normalized Difference Vegetation Index (NDVI) analysis for post-event vegetation change detection. NASA deployed an Uninhibited Aerial Vehicle SAR (UAVSAR) instrument to collect data on flood extent, providing crucial information on affected communities. Additionally, astronauts aboard the International Space Station (ISS) collected hand-held photography along the paths of Hurricane Helene and Milton to aid in response efforts. Here, we summarize the DRCS responses to Helene and Milton, in particular highlighting the information and products that were provided by the DRCS and how they were utilized by partners to address immediate response needs.

Earth observations↗

Evaluating Flood Forecasting System Performance in Cambodia

Every year, Cambodia experiences flooding as a result of monsoon rains and typhoons. Flood forecasting systems are designed to enable people to mitigate economic and social impacts from these events. However, in order for forecasts to be used effectively, an assessment of their accuracy is needed. This study demonstrates the performance of regional and global flood forecasting systems over the 2019 flood season. To do this, we assess the flood forecast accuracy at different forecast lead times and gauge locations in Cambodia. We then compare the flood forecast performance to satellite-based flood maps produced by the Hydrological Remote Sensing Analysis of Floods (HYDRAFloods) tool currently being co-developed by SERVIR-Mekong in collaboration with the Myanmar Department of Disaster Management. This assessment of the flood forecasting systems’ performance and comparison to flood extents helps (1) provide valuable information to forecasters and disaster managers as they make improvements to their models, and (2) provides support to forecast users as they evaluate the strengths and weaknesses of different systems for taking action.

Nauman, Claire↗