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NASA NTRS2012

Application of Satellite Gravimetry for Water Resource Vulnerability Assessment

The force of Earth's gravity field varies in proportion to the amount of mass near the surface. Spatial and temporal variations in the gravity field can be measured via their effects on the orbits of satellites. The Gravity Recovery and Climate Experiment (GRACE) is the first satellite mission dedicated to monitoring temporal variations in the gravity field. The monthly gravity anomaly maps that have been delivered by GRACE since 2002 are being used to infer changes in terrestrial water storage (the sum of groundwater, soil moisture, surface waters, and snow and ice), which are the primary source of gravity variability on monthly to decadal timescales after atmospheric and oceanic circulation effects have been removed. Other remote sensing techniques are unable to detect water below the first few centimeters of the land surface. Conventional ground based techniques can be used to monitor terrestrial water storage, but groundwater, soil moisture, and snow observation networks are sparse in most of the world, and the countries that do collect such data rarely are willing to share them. Thus GRACE is unique in its ability to provide global data on variations in the availability of fresh water, which is both vital to life on land and vulnerable to climate variability and mismanagement. This chapter describes the unique and challenging aspects of GRACE terrestrial water storage data, examples of how the data have been used for research and applications related to fresh water vulnerability and change, and prospects for continued contributions of satellite gravimetry to water resources science and policy.

Rodell, Matthew↗
NASA NTRS2012

Radiative Transfer Through Clouds and Its Applications in Support of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) Mission

The Greenland and Antarctic ice sheets, which contain enough ice to raise sea level by about 7 and 60 m, respectively, are losing mass at an increasing rate. To acquire continuous information of the cryosphere, after the Ice, Cloud, and land Elevation Satellite (ICESat) (2003-2010), NASA is actively planning for the ICESat-2 mission. Both ICESat and ICESat-2 are space-borne lidar altimetry systems. The systems measure the time of flight of the arriving photons that are reflected by the surface to deduce the elevation of the underlying terrain. As one of NASA's top priority missions, ICESat-2 is scheduled to launch in 2016. One of the major science goals of ICESat-2 is to quantify the ice sheet mass balance to determine its contributions to the sea level change and its impacts on ocean circulation (Abdalati et al. 2010). Compared to ICESat, which operates at 40 Hz and records the reflected laser energy as a waveform, the significantly improved ICESat-2 lidar employs a 532 nm micro-pulse photon counting system that operates at a high frequency of 10kHz with single photon detectability (Yang et al. 2012). To achieve its science goals, ICESat-2 requires the ability of detecting the elevation change with an accuracy of 0.2 cm/year over the entire ice sheet. Since every photon emitted by the lidar system will travel through the atmosphere, clouds can certainly affect the flight time of the arriving photons. Forward scattering by cloud particles increases the photon path length, thus resulting in biases in ice sheet elevation measurements known as atmospheric path delay (Duta et al. 2001, Yang et al. 2010, 2011). To ensure the accuracy of ICESat-2 surface elevation measurements, it is critical to understand how clouds would affect the travel time of arriving photons. In this talk, we will first present a framework that simulates the behavior of a space-borne 532 mn micro-pulse photon counting lidar in cloudy and clear atmospheres. To investigate the process of laser propagation through clouds, a 3-D Monte Carlo radiative transfer model is used to simulate the photon path distribution and the Poisson distribution is adopted for the number of photon returns. Since the photon counting system only registers the time of the first arriving photon within the detector "dead time", the retrieved average surface elevation tends to bias towards higher values. This is known as the first photon bias. With the scenarios simulated here, the first photon bias for clear sky is about 6.5 cm. Clouds affect surface altimetry in two ways: (1) cloud attenuation lowers the average number of arriving photons and hence reduces the first photon bias; (2) cloud forward scattering increases the photon path length and makes the surface appear further away from the satellite. Compared to clear sky, the average surface elevation detected by the photon counting system for cloudy sky with optical depth 1.0 is 4.0 to 6.0 cm lower for the simulations conducted. The effect of surface roughness on the accuracy of elevation retrievals will also discussed.

Yang, Yuekui↗
NASA NTRS2012

Cosmic Complexity

What explains the extraordinary complexity of the observed universe, on all scales from quarks to the accelerating universe? My favorite explanation (which I certainty did not invent) ls that the fundamental laws of physics produce natural instability, energy flows, and chaos. Some call the result the Life Force, some note that the Earth is a living system itself (Gaia, a "tough bitch" according to Margulis), and some conclude that the observed complexity requires a supernatural explanation (of which we have many). But my dad was a statistician (of dairy cows) and he told me about cells and genes and evolution and chance when I was very small. So a scientist must look for me explanation of how nature's laws and statistics brought us into conscious existence. And how is that seemll"!gly Improbable events are actually happening a!1 the time? Well, the physicists have countless examples of natural instability, in which energy is released to power change from simplicity to complexity. One of the most common to see is that cooling water vapor below the freezing point produces snowflakes, no two alike, and all complex and beautiful. We see it often so we are not amazed. But physlc!sts have observed so many kinds of these changes from one structure to another (we call them phase transitions) that the Nobel Prize in 1992 could be awarded for understanding the mathematics of their common features. Now for a few examples of how the laws of nature produce the instabilities that lead to our own existence. First, the Big Bang (what an insufficient name!) apparently came from an instability, in which the "false vacuum" eventually decayed into the ordinary vacuum we have today, plus the most fundamental particles we know, the quarks and leptons. So the universe as a whole started with an instability. Then, a great expansion and cooling happened, and the loose quarks, finding themselves unstable too, bound themselves together into today's less elementary particles like protons and neutrons, liberating a little energy and creating complexity. Then, the expanding universe cooled some more, and neutrons and protons, no longer kept apart by immense temperatures, found themselves unstable and formed helium nuclei. Then, a little more cooling, and atomic nuclei and electrons were no longer kept apart, and the universe became transparent. Then a little more cooling, and the next instability began: gravitation pulled matter together across cosmic distances to form stars and galaxies. This instability is described as a "negative heat capadty" in which extracting energy from a gravitating system makes it hotter -- clearly the 2nd law of thermodynamics does not apply here! (This is the physicist's part of the answer to e e cummings' question: what is the wonder that's keeping the stars apart?) Then, the next instability is that hydrogen and helium nuclei can fuse together to release energy and make stars burn for billions of years. And then at the end of the fuel source, stars become unstable and explode and liberate the chemical elements back into space. And because of that, on planets like Earth, sustained energy flows support the development of additional instabilities and all kinds of complex patterns. Gravitational instability pulls the densest materials into the core of the Earth, leaving a thin skin of water and air, and makes the interior churn incessantly as heat flows outwards. And the heat from the sun, received mostly near the equator and flowing towards the poles, supports the complex atmospheric and oceanic circulations. And because or that, the physical Earth is full of natural chemical laboratories, concentrating elements here, mixing them there, raising and lowering temperatures, ceaselessly experimenting with uncountable events where new instabilities can arise. At least one of them was the new experiment called life. Now that we know that there are at least as many planets as there are stars, it is hard to imagine that nature's ceasess experimentation would not be able to produce life elsewhere -- but we don't know for sure. And life went on to cause new Instabilities, constantly evolving, with living things in an extraordinary range of environments, changing the global environment, with boom-and-bust cycles. with predators for every kInd of prey, with criminals for every possible crime, with governments to prevent them, and instabilities of the governments themselves. One of the instabilities Is that humans demand new weapons and new products of all sort, leading to serious investments in science and technology. So the natural/human world of competition and combat is structured to lead to advanced weaponry and cell phones. So here we are In 2012, with people writing essays and wondering whether their descendents will be artificial life forms travelling back into space. And, pondering what are the origins of those forces of nature that give rise to everything. Verllnde has argued that gravitation, the one force that has so far resisted our efforts at a Quantum description, is not even a fundamental force, but is itself it a statistical force, like osmosis. What an amazing turn of events! But after all I've just said, I should not be surprised a bit.

Mather, John C.↗
NASA NTRS2015

New Insights into Amino Acid Preservation in the Early Oceans Using Modern Analytical Techniques

Protein- and non-protein-amino acids likely occupied the oceans at the time of the origin and evolution of life. Primordial soup-, hydrothermal vent-, and meteoritic-processes likely contributed to this early chemical inventory. Prebiotic synthesis and carbonaceous meteorite studies suggest that non-protein amino acids were likely more abundant than their protein-counterparts. Amino acid preservation before abiotic and biotic destruction is key to biomarker availability in paleoenvironments and remains an important uncertainty. To constrain primitive amino acid lifetimes, a 1992 archived seawater/beach sand mixture was spiked with D,L-alanine, D,L-valine (Val), alpha-aminoisobutyric acid (alpha-AIB), D,L-isovaline (Iva), and glycine (Gly). Analysis by high performance liquid chromatography with fluorescence detection (HPLC-FD) showed that only D-Val and non-protein amino acids were abundant after 2250 days. The mixture was re-analyzed in 2012 using HPLC-FD and a triple quadrupole mass spectrometer (QqQ-MS). The analytical results 20 years after the inception of the experiment were strikingly similar to those after 2250 days. To confirm that viable microorganisms were still present, the mixture was re-spiked with Gly in 2012. Aliquots were collected immediately after spiking, and at 5- and 9-month intervals thereafter. Final HPLC-FD/QqQ-MS analyses were performed in 2014. The 2014 analyses revealed that only alpha-AIB, D,L-Iva, and D-Val remained abundant. The disappearance of Gly indicated that microorganisms still lived in the mixture and were capable of consuming protein amino acids. These findings demonstrate that non-protein amino acids are minimally impacted by biological degradation and thus have very long lifetimes under these conditions. Primitive non-protein amino acids from terrestrial synthesis, or meteorite in-fall, likely experienced great-er preservation than protein amino acids in paleo-oceanic environments. Such robust molecules may have reached a steady state concentration dependent on ocean circulation through hydrothermal systems and synthetic input processes. We are presently trying to estimate this concentration.

Parker, Eric T.↗
NASA NTRS2015

Testing the Deployment Repeatability of a Precision Deployable Boom Prototype for the Proposed SWOT Karin Instrument

NASA's proposed Surface Water Ocean Topography (SWOT) mission, scheduled to launch in 2020, would provide critical information about Earth's oceans, ocean circulation, fresh water storage, and river discharge. The mission concept calls for a dual-antenna Ka-band radar interferometer instrument, known as KaRIn, that would map the height of water globally along two 50 km wide swaths. The KaRIn antennas, which would be separated by 10 meters on either side of the spacecraft, would need to be precisely deployable in order to meet demanding pointing requirements. Consequently, an effort was undertaken to design build and prototype a precision deployable Mast for the KaRIn instrument. Each mast was 4.5-m long with a required dilitation stability of 2.5 microns over 3 minutes. It required a minimum first mode of 7 Hz. Deployment repeatability was less than +/- 7 arcsec in all three rotation directions. Overall mass could not exceed 41.5 Kg including any actuators and thermal blanketing. This set of requirements meant the boom had to be three times lighter and two orders of magnitude more precise than the existing state of the art for deployable booms.

boom↗
NASA NTRS2017

Estimating the Distribution of Colored Dissolved Organic Matter During the Southern Ocean Gas Exchange Experiment Using Four-Dimensional Variational Data Assimilation

We diagnosed the effect of various physical processes on the distribution of mixed-layer colored dissolved organic matter (CDOM) and a sulfur hexauoride (SF6) tracer during the Southern Ocean Gas Exchange Experiment (SO GasEx). The biochemical upper ocean state estimate uses in situ and satellite biochemical and physical data in the study region, including CDOM (absorption coefcient and spectral slope), SF6, hydrography, and sea level anomaly. Modules for photobleaching of CDOM and surface transport of SF6 were coupled with an ocean circulation model for this purpose. The observed spatial and temporal variations in CDOM were captured by the state estimate without including any new biological source term for CDOM, assuming it to be negligible over the 26 days of the state estimate. Thermocline entrainment and photobleaching acted to diminish the mixed-layer CDOM with time scales of 18 and 16 days, respectively. Lateral advection of CDOM played a dominant role and increased the mixed-layer CDOM with a time scale of 12 days, whereas lateral diffusion of CDOM was negligible. A Lagrangian view on the CDOM variability was demonstrated by using the SF6 as a weighting function to integrate the CDOM elds. This and similar data assimilation methods can be used to provide reasonable estimates of optical properties, and other physical parameters over the short-term duration of a research cruise, and help in the tracking of tracer releases in large-scale oceanographic experiments, and in oceanographic process studies.

Del Castillo, C. E.↗
NASA NTRS2010

Orbital Gravity Gradiometry Beyond GOCE: Mission Concepts

Significant advances in the technologies needed for space-based cryogenic instruments have been made in the last decade, including cryocoolers, spacecraft architectures and cryogenic amplifiers. These enable considerably more complex instruments to be put into orbit for long-duration missions. One such instrument is the Superconducting Gravity Gradiometer (SGG) developed by Paik, et al. A magnetically levitated version is under consideration for a follow-on mission to GRACE (Gravity Recovery and Climate Experiment) and GOCE (Gravity field and steady-state Ocean Circulation Explorer). With its inherently greater rejection of common mode accelerations and ability to cancel the coupling of angular accelerations into the gradient signal, the SGG can achieve [an accuracy of] 0.01 milli-Eotvos (gravitational gradient of the Earth) divided by the square root of frequency in hertz, with requirements for attitude control that can be met with existing spacecraft. In addition, the use of a cryocooler for cooling the instrument will alleviate the previously severe constraint on mission lifetime imposed by the use of superfluid helium,. enabling mission durations in the 5-10 year range. Studies are underway to determine requirements for orbit (polar versus sun-synchronous), altitude (which affects spacecraft drag), instrument temperature and stability, cryocooler vibration control, and control and readout electronics. These will be used to determine the SGG's sensitivity and ultimate resolution for gravity recovery. This paper will discuss preliminary instrument and spacecraft design, and toplevel mission requirements.

Shirron, Peter J.↗
NASA NTRS2017

Chapter 12: Sea Level Rise

Global mean sea level (GMSL) has risen by about 7-8 inches (about 16-21 cm) since 1900, with about 3 of those inches (about 7 cm) occurring since 1993. Human-caused climate change has made a substantial contribution to GMSL rise since 1900, contributing to a rate of rise that is greater than during any preceding century in at least 2,800 years. Relative to the year 2000, GMSL is very likely to rise by 0.3-0.6 feet (9-18 cm) by 2030, 0.5-1.2 feet (15-38 cm) by 2050, and 1.0-4.3 feet (30-130 cm) by 2100. Future pathways have little effect on projected GMSL rise in the first half of the century, but significantly affect projections for the second half of the century. Emerging science regarding Antarctic ice sheet stability suggests that, for high emission scenarios, a GMSL rise exceeding 8 feet (2.4 m) by 2100 is physically possible, although the probability of such an extreme outcome cannot currently be assessed. Regardless of pathway, it is extremely likely that GMSL rise will continue beyond 2100. Relative sea level (RSL) rise in this century will vary along U.S. coastlines due, in part, to changes in Earth's gravitational field and rotation from melting of land ice, changes in ocean circulation, and vertical land motion (very high confidence). For almost all future GMSL rise scenarios, RSL rise is likely to be greater than the global average in the U.S. Northeast and the western Gulf of Mexico. In intermediate and low GMSL rise scenarios, RSL rise is likely to be less than the global average in much of the Pacific Northwest and Alaska. For high GMSL rise scenarios, RSL rise is likely to be higher than the global average along all U.S. coastlines outside Alaska. Almost all U.S. coastlines experience more than global mean sea level rise in response to Antarctic ice loss, and thus would be particularly affected under extreme GMSL rise scenarios involving substantial Antarctic mass loss. As sea levels have risen, the number of tidal floods each year that cause minor impacts (also called "nuisance floods") have increased 5- to 10-fold since the 1960s in several U.S. coastal cities. Rates of increase are accelerating in over 25 Atlantic and Gulf Coast cities. Tidal flooding will continue increasing in depth, frequency, and extent this century. Assuming storm characteristics do not change, sea level rise will increase the frequency and extent of extreme flooding associated with coastal storms, such as hurricanes and nor'easters. A projected increase in the intensity of hurricanes in the North Atlantic could increase the probability of extreme flooding along most of the U.S. Atlantic and Gulf Coast states beyond what would be projected based solely on RSL rise. However, there is low confidence in the projected increase in frequency of intense Atlantic hurricanes, and the associated flood risk amplification and flood effects could be offset or amplified by such factors as changes in overall storm frequency or tracks.

Sweet, W. V.↗
NASA NTRS2021

The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations

The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

Last Glacial Maximum↗
NASA NTRS2021

Earth system modeling: can we stay ahead of what's actually happening?

Over the last forty years, Earth System Models have become more and more comprehensive and detailed. They have assimilated previously independent modeling efforts in ocean circulation, atmospheric composition, the stratosphere, land surface, and the cryosphere, and are today demonstrably more skillful than earlier efforts. Yet the structural uncertainty in the latest model projections is actually increasing. Meanwhile, impacts of climate change on, for instance, wildfires, tropical cyclones and sea level, appear to be increasing faster than we have been able to predict. I will address some of the current issues at the bleeding edges of model development and the continuing importance of model evaluation.

Gavin A Schmidt↗
NASA NTRS1993

Modeling Non-Gravitational Forces Acting on Topex/Poseidon: The Early Days

Topex/Poseidon is a satellite mission that will use altimetry to make precise measurements of sea-level with unprecedented acuracy such that small-amplitude, basin wide sea-level with unprecedented accuracy such that small-amplitude, basin wide sea-level changes caused by large-scale ocean circulation can be detected.

Topex/Poseidon↗
NASA NTRS1995

An Analysis of the TOPEX/Poseidon Operational Orbit: Observed Variations and Why

Launched in August 1992, TOPEX/Poseidon began and continues a very successful global study of the earth's ocean circulation using a combination of dual-frequency radar altimetry and precision orbit determination (POD). POD results are utilized here to reconstruct the operational orbit history in terms of precise classical mean elements. Elaborations of various facets related to mean elements is discussed.

TOPEX↗
NASA NTRS1996

NASA Scatterometer Experiment

Satellite scatterometers are microwave radars capable of measuring near-surface vector winds (both speed and direction) over the oceans under all weather conditions. The data generated from these instruments are used in scientific studies of upper ocean circulation, tropospheric dynamics, air -sea interaction, and climate change.

satellite↗
NASA NTRS2021

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences

The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×10^6 sq.km, compared to 6.46×10^6 sq.km for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×10^6 sq.km for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 %/yr) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Arctic sea ice↗
NASA NTRS2023

Global Radiative Flux Profile Dataset: Revised and Extended

The third generation of the radiative flux profile data product, called ISCCP-FH, is described. The revisions over the previous generation (called ISCCP-FD) include improvements in the radiative model representation of gaseous and aerosol effects, as well as a refined statistical model of cloud vertical layer variations with cloud types, and increased spatial resolution. The new product benefits from the changes in the new H-version of the ISCCP cloud products (called ISCCP-H): higher spatial resolution, revised radiance calibration and treatment of ice clouds, treatment of aerosol effects, and revision of all the ancillary atmosphere and surface property products. The ISCCP-FH product is evaluated against more direct measurements from the Clouds and the Earth’s Radiant Energy System and the Baseline Surface Radiation Network products, showing some small, overall reductions in average flux uncertainties; but the main results are similar to ISCCP-FD: the ISCCP-FH uncertainties remain ≲10 Wm −2 at the top-of-atmosphere (TOA) and ≲15 Wm −2 at surface for monthly, regional averages. The long-term variations of TOA, surface and in-atmosphere net fluxes are documented and the possible transient cloud feedback implications of a long-term change of clouds are investigated. The cloud and flux variations from 1998 to 2012 suggest a positive cloud-radiative feedback on the oceanic circulation and a negative feedback on the atmospheric circulation. This example demonstrates that the ISCCP-FH product can provide useful diagnostic information about weather-to-interannual scale variations of radiation induced by changes in cloudiness as well as atmospheric and surface properties.

ISCCP-FH↗
NASA NTRSDate not supplied

Inferred Sea Level Prediction in the NASA GMAO Seasonal Forecasting System

Reliable predictions of sea level anomalies on seasonal timescales with lead times of 1 to 9 months may have relevance to stakeholders – for example, in the advance deployment of resources for coastal flood mitigation. Routine prediction and analysis may also highlight physical processes associated with sea level change and modeling capabilities on seasonal and other timescales. These forecasts may represent interannual changes in the seasonal slope of the ocean surface, teleconnection effects such as the El Niño/Southern Oscillation phenomenon, and variations in seasonal hydrology including precipitation and coastal runoff. Coupled atmosphere/ocean models are routinely used in the seasonal prediction of temperature anomalies, precipitation anomalies, sea ice cover, and climate indices such as the Niño3.4 predictions under the North American Multi-Model Ensemble (NMME) protocol. Within the limits of their configuration, these complex Earth-system models have a potential for depicting regional changes in oceanic column properties, including the sea surface height. Seasonal prediction models generally have no representation of long-term mass contributions from melting land ice, or changes in vertical land motion; their output may be more specifically characterized as predictions of the ocean dynamic sea level. In practice however, the sea surface height prognostic variable is substantially compromised by the forecast model response to initial conditions. Imbalances between the initial, observed hydrologic cycle and the forecast model state produce abrupt adjustments in the model sea surface height. As a result, most seasonal prediction systems employ a constraint on the globally-averaged sea surface height that is applied at each time step. This essentially renders the prognostic sea surface height variable as unserviceable. Several approaches have previously been used to retrieve sea level information from seasonal forecasts beyond the use of the sea surface height variable. Here, we extend a method of relating other prognostic values, including ocean circulation and climate indices, to observed sea level variations. We use the merged altimetry record of the NASA MEaSUREs Gridded Sea Surface Height Anomalies data set and monthly revised local reference gauge observations from the National Oceanography Centre Permanent Service for Mean Sea Level (PSMSL) to evaluate derived prognostic variables from the NASA Global Modeling and Assimilation Office subseasonal-to-seasonal system version 2.1 (GMAO S2S v2.1). We focus on results for the midlatitudes with particular emphasis on US gauge locations. As shown in previous studies, prognostic ENSO-related indices in boreal winter are well correlated with gauge observations for the US west coast, but also for other locations in the southeastern US. Other forecast climate indices such as the North Atlantic Oscillation have relations to sea level that are limited both seasonally and spatially. As expected, surface atmospheric pressure (e.g., inverse barometer effect) is found to be particularly well correlated with observed sea level. We provide a characterization of forecast skill for seasonal sea level with this method.

Richard I Cullather↗
NASA NTRSDate not supplied

Visualizing Geospatial Data through ESRI Story Maps for Earth Science Education: Lessons Learned from My NASA Data

For 20 years My NASA Data (MND) has curated NASA Earth science data and provided the data to educators in engaging learner-centered resources. MND has recently featured story maps as an innovative way to engage students in NASA Earth data. A story map is a cloud-based lesson that engages the learner in interactive geospatial maps using NASA data, and other multimedia content, text, and tasks that can be seamlessly incorporated in classroom instruction. This immersive technology eliminates the need for the user to move among tricky interfaces to access and visualize Earth science data, and no special software is required to be downloaded. Each story map integrates data from different NASA satellite missions, retrieved from Distributed Active Archive Centers (DAACs). Story maps also employ data analysis tools, such as time series options and swipe tools that allow learners to view and analyze relationships between scientific variables. MND has produced 25 story map lesson plans on the topics of air quality, the urban heat island effect, Earth’s energy budget, phytoplankton distribution, hurricane formation, solar eclipses, ocean circulation patterns, sea ice extent, and volcanic eruptions. Nine of them are extended story maps and written in the 5E format, which is internationally recognized as best practice based on how children learn science. Each story map resource is developed by the MND team featuring a GIS programming specialist, a lead scientist, and educational specialist/s to ensure the context, content, and methods are scientifically and educationally sound. The MND story maps are written for middle and high school science teachers and students as they connect with the Earth Systems Science phenomena featured in the Next Generation Science Standards. Each story map includes supporting resources for smooth integration in the classroom. During Fiscal Year 2023, The My NASA Data website received over 100,000 story map engagements during. These metrics highlight the interest in story maps as an Earth Science educational resource.

Desiray Wilson↗