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NASA NTRS2012

Polarimetric Retrievals of Surface and Cirrus Clouds Properties in the Region Affected by the Deepwater Horizon Oil Spill

In 2010, the Goddard Institute for Space Studies (GISS) Research Scanning Polarimeter (RSP) performed several aerial surveys over the region affected by the oil spill caused by the explosion of the Deepwater Horizon offshore platform. The instrument was deployed on the NASA Langley B200 aircraft together with the High Spectral Resolution Lidar (HSRL), which provides information on the distribution of the aerosol layers beneath the aircraft, including an accurate estimate of aerosol optical depth. This work illustrates the merits of polarization measurements in detecting variations of ocean surface properties linked to the presence of an oil slick. In particular, we make use of the degree of linear polarization in the glint region, which is severely affected by variations in the refractive index but insensitive to the waviness of the water surface. Alterations in the surface optical properties are therefore expected to directly affect the polarization response of the RSP channel at 2264 nm, where both molecular and aerosol scattering are negligible and virtually all of the observed signal is generated via Fresnel reflection at the surface. The glint profile at this wavelength is fitted with a model which can optimally estimate refractive index, wind speed and direction, together with aircraft attitude variations affecting the viewing geometry. The retrieved refractive index markedly increases over oil-contaminated waters, while the apparent wind speed is significantly lower than in adjacent uncontaminated areas, suggesting that the slick dampens high-frequency components of the ocean wave spectrum. The constraint on surface reflectance provided by the short-wave infrared channels is a cornerstone of established procedures to retrieve atmospheric aerosol microphysical parameters based on the inversion of the RSP multispectral measurements. This retrieval, which benefits from the ancillary information provided by the HSRL, was in this specific case hampered by prohibitive variability in atmospheric conditions (very inhomogeneous aerosol distribution and cloud cover). Although the results presented for the surface are essentially unaffected, we discuss the results obtained by typing algorithms in sorting the complex mix of aerosol types, and show evidence of oriented ice in cirrus clouds present in the area. In this context, polarization measurements at 1880 nm were used to infer ice habit and cirrus optical depth, which was found in the subvisual/threshold-visible regime, confirming the utility of the aforementioned RSP channel for the remote sensing of even thin cold clouds.

Polarization↗
NASA NTRS2018

Satellite Sensor Requirements for Monitoring Essential Biodiversity Variables of Coastal Ecosystems

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration less than 2%, relative calibration of 0.2%, polarization sensitivity less than 1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

aquatic↗
NASA NTRSDate not supplied

Generating Essential Climate Variables from Multiple Satellite Hyperspectral Remote Sensors

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. There are two shortcomings of this approach. First, it is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Secondly, differences in level-2 retrieval algorithms can lead to errors in the fused multi-satellite data. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to data collected from Atmospheric Infrared Sounder (AIRS) on Aqua satellite and Cross-track Infrared Sounder (CrIS) on SNPP and NOAA20 and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Atmosphere Observing System (AOS).

Xu Liu↗
NASA NTRS2003

Fresh Water Content Variability in the Arctic Ocean

Arctic Ocean model simulations have revealed that the Arctic Ocean has a basin wide oscillation with cyclonic and anticyclonic circulation anomalies (Arctic Ocean Oscillation; AOO) which has a prominent decadal variability. This study explores how the simulated AOO affects the Arctic Ocean stratification and its relationship to the sea ice cover variations. The simulation uses the Princeton Ocean Model coupled to sea ice. The surface forcing is based on NCEP-NCAR Reanalysis and its climatology, of which the latter is used to force the model spin-up phase. Our focus is to investigate the competition between ocean dynamics and ice formation/melt on the Arctic basin-wide fresh water balance. We find that changes in the Atlantic water inflow can explain almost all of the simulated fresh water anomalies in the main Arctic basin. The Atlantic water inflow anomalies are an essential part of AOO, which is the wind driven barotropic response to the Arctic Oscillation (AO). The baroclinic response to AO, such as Ekman pumping in the Beaufort Gyre, and ice meldfreeze anomalies in response to AO are less significant considering the whole Arctic fresh water balance.

Hakkinen, Sirpa↗
NASA NTRS2010

Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

Land surface (or "skin") temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. Here we assimilate LST retrievals from the International Satellite Cloud Climatology Project (ISCCP) into the Noah and Catchment (CLSM) land surface models using an ensemble-based, off-line land data assimilation system. LST is described very differently in the two models. A priori scaling and dynamic bias estimation approaches are applied because satellite and model LST typically exhibit different mean values and variability. Performance is measured against 27 months of in situ measurements from the Coordinated Energy and Water Cycle Observations Project at 48 stations. LST estimates from Noah and CLSM without data assimilation ("open loop") are comparable to each other and superior to that of ISCCP retrievals. For LST, RMSE values are 4.9 K (CLSM), 5.6 K (Noah), and 7.6 K (ISCCP), and anomaly correlation coefficients (R) are 0.62 (CLSM), 0.61 (Noah), and 0.52 (ISCCP). Assimilation of ISCCP retrievals provides modest yet statistically significant improvements (over open loop) of up to 0.7 K in RMSE and 0.05 in anomaly R. The skill of surface turbulent flux estimates from the assimilation integrations is essentially identical to the corresponding open loop skill. Noah assimilation estimates of ground heat flux, however, can be significantly worse than open loop estimates. Provided the assimilation system is properly adapted to each land model, the benefits from the assimilation of LST retrievals are comparable for both models.

Reichle, Rolf H.↗
NASA NTRS2001

Microbial contamination of spacecraft

Spacecraft and space habitats supporting human exploration contain a diverse population of microorganisms. Microorganisms may threaten human habitation in many ways that directly or indirectly impact the health, safety, or performance of astronauts. The ability to produce and maintain spacecraft and space stations with environments suitable for human habitation has been established over 40 years of human space flight. An extensive database of environmental microbiological parameters has been provided for short-term (< 20 days) space flight by more than 100 missions aboard the Space Shuttle. The NASA Mir Program provided similar data for long-duration missions. Interestingly, the major bacterial and fungal species found in the Space Shuttle are similar to those encountered in the nearly 15-year-old Mir. Lessons learned from both the US and Russian space programs have been incorporated into the habitability plan for the International Space Station. The focus is on preventive measures developed for spacecraft, cargo, and crews. On-orbit regular housekeeping practices complete with visual inspections are essential, along with microbiological monitoring. Risks associated with extended stays on the Moon or a Mars exploration mission will be much greater than previous experiences because of additional unknown variables. The current knowledge base is insufficient for exploration missions, and research is essential to understand the effects of space flight on biological functions and population dynamics of microorganisms in spacecraft. Equally important is a better understanding of the immune response and of human-microorganism-environment interactions during long-term space habitation.

Mir Project↗
NASA NTRS2023

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗
NASA NTRS2004

Airborne In Situ and Ground-based Polarimetric Radar Measurements of Tropical Convection in Support of CRYSTAL-FACE

This report describes the work performed by the University of North Dakota (UND) under NASA Grant NAG5-11509, titled Airborne In Situ and Ground-based Polarimetric Radar Measurements of Tropical Convection in Support of CRYSTAL-FACE. This work focused on the collection of data by two key platforms: the UND Citation II research aircraft and the NASA NPOL radar system. The CRYSTAL-FACE (C-F) mission addresses several key issues from the NASA Earth System Enterprise, including the variability of water in the atmosphere, the forcing provided by tropical cirrus and the response of the Earth system to this forcing. In situ measurements and radar observations of tropical convection, cirrus clouds and their environment are core elements of C-F. One of the primary issues that C-F is addressing is the relationship of tropical cirrus anvils to precipitating deep convection. The in situ measurements from C-F are being used to validate remote sensing of Earth-Atmosphere properties, increase our knowledge of upper tropospheric water vapor and its distribution, and increase our knowledge of tropical cirrus cloud morphology and composition. Radar measurements, especially polarimetric diversity observations available fiom the NASA NPOL radar, are providing essential information about the initiation, modulation, and dissipation of convective cores and the generation of associated anvils in tropical convection. Specifically, NPOL radar measurements contain information about convective intensity and its vertical structure for comparison with thermodynamic and kinematic environmental measurements observed from soundings. Because of the polarimetric diversity of MOL, statistics on bulk microphysical properties can be retrieved and compared to the other characteristics of convection and associated cirrus anvils. In summary, the central objectives of this proposal were to deploy the UND Citation research aircraft as an in situ sensing platform for this mission and to provide collaborative analyses of the recorded data and to deploy the NPOL radar to observe the characteristics of cirrus and parent convection.

Poellot, Michael R.↗
NASA NTRS1999

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

Koster, Randal D.↗
NASA NTRS1991

Ocean transport and variability studies of the South Pacific, Southern, and Indian Oceans

The objectives of this study are to analyze ocean dynamics in the western South Pacific and the adjacent Southern Ocean and the eastern Indian Ocean. Specifically, our objectives for these three regions are, for the South Pacific Ocean: (1) To estimate the volume transport of the east Australian Current (EAC) along the Australian coast and in the Tasman Front, and to estimate the time variability (on seasonal and interannual time scales) of this transport. (2) To contribute to estimating the meridional heat and freshwater fluxes (and their variability) at about 30 deg S. Good estimates of the transport in the western boundary current are essential for accurate estimates of these fluxes. (3) To determine how the EAC transport (and its extension, the Tasman Front and the East Auckland Current) closes the subtropical gyre of the South Pacific and to better determine the structure at the confluence of this current and the Antarctic Circumpolar Current. (4) To examine the structure and time variability of the circulation in the western South Pacific and the adjacent Southern Ocean, particularly at the Tasman Front. For the Indian Ocean: (5) To study the seasonal interannual variations in the strength of the Leeuwin Current. (6) To monitor the Pacific-Indian Ocean throughflow and the South Equatorial and the South Java Currents between northwest Australia and Indonesia. (7) To study the processes that form the water of the permanent oceanic thermocline and, in particular, the way in which new thermocline water enters the permanent thermocline in late winter and early spring as the mixed layer restratifies. For the Southern Ocean: (8) To study the mesoscale and meridional structure of the Southern Ocean between 150 deg E and 170 deg E; in particular, to describe the Antarctic frontal system south of Tasmania and determine its interannual variability; to estimate the exchanges of heat, salt, and other properties between the Indian and Pacific Oceans; and to investigate the annual ventilation of the Antarctic Intermediate Water and Subantarctic Mode Water Masses.

Church, John A.↗
NASA NTRS2006

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

Kim, E. J.↗
NASA NTRS1994

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating surface temperature from passive microwave data (in conjunction with AVHRR clear sky samples) through the use of 'effective emissivities' and physical relationships between skin temperature and subsurface temperature. Use the general method outlined in MK93 to calculate a 12-year record of clear sky equivalent surface temperatures, or possibly all-sky snow-ice interface physical temperatures, from SMMR and SSM/I, compare these temperatures to climatologies, ECMWF modeled surface temperatures, and surface temperatures predicted by a 2-D ice model. And intercompare several ice surface retrieval methods and validate them against ground measurements from the Swiss Camp on the Greenland ice sheet. Additionally, we intend to develop a surface temperature product based on AVHRR data and possibly blended with drifting buoy and meteorological station temperatures.

Key, Jeff↗
NASA NTRS2016

Spatial and Temporal Trends in Precambrian Nitrogen Cycling: A Mesoproterozoic Offshore Nitrate Minimum

Fixed nitrogen is an essential nutrient for eukaryotes. As N2 fixation and assimilation of nitrate are catalyzed by metalloenzymes, it has been hypothesized that in Mesoproterozoic oceans nitrate was limited in offshore environments by low trace metal concentrations and high rates of denitrification in anoxic and episodically euxinic deep water masses, restricting eukaryotes to near-shore environments and limiting their evolutionary innovation. To date this hypothesis has only been tested in the Belt Supergroup (∼1.4 Ga), with results that support an onshore-offshore nitrate gradient as a potential control on eukaryote ecology. Here we present bulk nitrogen and organic carbon isotopic data from non-isochronous cross-basinal facies across the Bangemall (∼1.5 Ga) and the Roper (∼1.4–1.5 Ga) basins to better understand the extent and variability of onshore-offshore nitrogen isotope gradients in the Mesoproterozoic. Both basins show an average ∼1-2‰ enrichment in δ-15N(sub bulk) from deep to shallow facies, with a maximum range from ~1‰ offshore to +7.5‰ onshore. Unlike the Belt basin, the Bangemall and Roper basins show some offshore δ-15N(sub bulk) values that are enriched beyond the isotopic range associated with biological N2 fixation alone. This suggests a mixture of aerobic and anaerobic metabolisms offshore. In shallow waters, where δ-15N(sub bulk) enrichment peaks, an aerobic nitrogen cycle was evidently operating. Even though isotopic signatures of aerobic nitrogen cycling are seen in all parts of the Bangemall and Roper basins, our data are consistent with a lateral gradient in nitrate availability within the photic zone, with higher concentrations in near-shore environments than offshore. The variability in δ-15N(sub bulk) values in each depositional environment and the consistently low δ-15N(sub bulk) values from Mesoproterozoic units compared to the Paleoproterozoic and Neoproterozoic suggest that nitrate concentrations in the global ocean were likely low. This trend is now seen in all three Mesoproterozoic basins so far examined, and contrasts with the Paleoproterozoic and Neoproterozoic where nearly all δ-15N(sub bulk) data plot above the N2 fixation window. Thus, we propose that the Mesoproterozoic ocean was characterized by a nitrate minimum, with the lowest concentrations in offshore environments. This inference is consistent with a Mesoproterozoic O2 decline following a temporary Paleoproterozoic O2 peak, and it further supports the idea that nitrate limitation offshore may have contributed to the restriction of photosynthetic eukaryotes to near-shore environments, delaying their rise to ecological dominance until the Neoproterozoic Era.

Mesoproterozoic↗
NASA NTRS2016

Global Linkages Originating from Decadal Oceanic Variability in the Subpolar North Atlantic

The anomalous decadal warming of the subpolar North Atlantic Ocean (SPNA), and the northward spreading of this warm water, has been linked to rapid Arctic sea ice loss and more frequent cold European winters. Recently, variations in this heat transport have also been reported to covary with global warming slowdown/acceleration periods via a Pacific climate response. We here examine the role of SPNA temperature variability in this Atlantic-Pacific climate connectivity. We find that the evolution of ocean heat content anomalies from the subtropics to the subpolar region, likely due to ocean circulation changes, coincides with a basin-wide Atlantic warming/cooling. This induces an Atlantic-Pacific sea surface temperature seesaw, which in turn, strengthens/weakens the Walker circulation and amplifies the Pacific decadal variability that triggers pronounced global-scale atmospheric circulation anomalies. We conclude that the decadal oceanic variability in the SPNA is an essential component of the tropical interactions between the Atlantic and Pacific Oceans.

Atlantic variability↗
NASA NTRS1979

On surface drift currents in the ocean

It is pointed out that the motion of the surface water over the world's oceans is a critical factor in controlling the large-scale transport processes of mass, momentum, and energy. It is also the key to solving the global air-sea interaction problem. The formulation used in the reported analysis is based on that of Leibovich (1977) with the essential modification of adding the Coriolis term so that the Ekman drift can be included. This modification does not invalidate the results of Craik and Leibovich (1976) and Leibovich (1977), which are primarily for the small-scale motions, but rather extends their work to cover large-scale mean motion. The results of the model indicate that the sea state could have strong influence on surface drift currents in the ocean. A classification scheme is proposed to explain the highly variable conditions of the surface drift currents.

Huang, N. E.↗
NASA NTRS2003

Depth and Distribution of CO2 Snow on Mars

The dynamic role of volatiles on the surface of Mars has been a subject of longstanding interest. In the pre-Viking era, much of the debate was necessarily addressed by theoretical considerations. A particularly influential treatment by Leighton and Murray put forth a simple model relying on solar energy balance, and led to the conclusion that the most prominent volatile exchanging with the atmosphere over seasonal cycles is carbon dioxide. Their model suggested that due to this exchange, atmospheric CO2 partial pressure is regulated by polar ice. While current thinking attributes a larger role to H2O ice than did the occasional thin polar coating this model predicted, the CO2 cycle appears to be essentially correct. There are a number of observational constraints on the seasonal exchange of surface volatiles with the atmosphere. The growth and retreat of polar CO2 frost is visible from Earth-based telescopes and from spacecraft in Mars orbit, both at visible wavelengths and in thermal IR properties of the surface. Recently, variations in Gamma ray and neutron fluxes have also been used to infer integrated changes in CO2 mass on the surface. Measurements made by Viking's Mars Atmospheric Water Detector experiment were sensitive to atmospheric H2O vapor abundance. Surface condensates and their transient nature were detected by the Viking landers. The study here is motivated by recent data collected by the Mars Global Surveyor, affording the opportunity to not only detect the lateral distribution of volatiles, but also to constrain the variable volumes of the reservoirs. We elaborate on a technique first employed by Smith et al. By examining averages of a large number of topographic measurements collected by the Mars Orbiter Laser Altimeter (MOLA), that study showed that the zonal pattern of deposition and sublimation of CO2 can be determined. In their first approach, reference surfaces were fit to all measurements in narrow latitude annuli, and the time dependent variations about those mean surfaces were examined. In their second approach, height measurements from pairs of tracks that cross on the surface were interpolated and differenced, forming a set of crossover residuals. These residuals were then examined as a function of time and latitude. The initial studies averaged over longitude to maximize signal and minimize noise in order to isolate the expected small signal. In this follow-up study we now attempt to extract the elevation change pattern also as a function of longitude, and we focus on the crossover approach.

Aharonson, Oded↗
NASA NTRS2011

Projected Regime Shift in Arctic Cloud and Water Vapor Feedbacks

The Arctic climate is changing faster than any other large-scale region on Earth. A variety of positive feedback mechanisms are responsible for the amplification, most of which are linked with changes in snow and ice cover, surface temperature (T(sub s)), atmospheric water vapor (WV), and cloud properties. As greenhouse gases continue to accumulate in the atmosphere, air temperature and water vapor content also increase, leading to a warmer surface and ice loss, which further enhance evaporation and WV. Many details of these interrelated feedbacks are poorly understood, yet are essential for understanding the pace and regional variations in future Arctic change. We use a global climate model (Goddard Institute for Space Studies, Atmosphere-Ocean Model) to examine several components of these feedbacks, how they vary by season, and how they are projected to change through the 21st century. One positive feedback begins with an increase in T(sub s) that produces an increase in WV, which in turn increases the downward longwave flux (DLF) and T(sub s), leading to further evaporation. Another associates the expected increases in cloud cover and optical thickness with increasing DLF and T(sub s). We examine the sensitivities between DLF and other climate variables in these feedbacks and find that they are strongest in the non-summer seasons, leading to the largest amplification in Ts during these months. Later in the 21st century, however, DLF becomes less sensitive to changes in WV and cloud optical thickness, as they cause the atmosphere to emit longwave radiation more nearly as a black body. This regime shift in sensitivity implies that the amplified pace of Arctic change relative to the northern hemisphere could relax in the future.

Chen, Yonghua↗
NASA NTRS2022

Satellite-derived cyanobacteria frequency and magnitude in headwaters & near-dam reservoir surface waters of the Southern U.S.

Reservoirs are dominant features of the modern hydrologic landscape and provide vital services. However, the unique morphology of reservoirs can create suitable conditions for excessive algae growth and associated cyanobacteria blooms in shallow in-flow reservoir locations by providing warm water environments with relatively high nutrient inputs, deposition, and nutrient storage. Cyanobacteria harmful algal blooms (cyanoHAB) are costly water management issues and bloom recurrence is associated with economic costs and negative impacts to human, animal, and environmental health. As cyanoHAB occurrence varies substantially within different regions of a water body, understanding in-lake cyanoHAB spatial dynamics is essential to guide reservoir monitoring and mitigate potential public exposure to cyanotoxins. Cloud-based computational processing power and high temporal frequency of satellites enables advanced pixel-based spatial analysis of cyanoHAB frequency and quantitative assessment of reservoir headwater in-flows compared to near-dam surface waters of individual reservoirs. Additionally, extensive spatial coverage of satellite imagery allows for evaluation of spatial trends across many dozens of reservoir sites. Surface water cyanobacteria concentrations for sixty reservoirs in the southern U.S. were estimated using 300m resolution European Space Agency (ESA) Ocean and Land Colour Instrument (OLCI) satellite sensor for a five year period (May 2016–April 2021). Of the reservoirs studied, spatial analysis of OLCI data revealed 98% had more frequent cyanoHAB occurrence above the concentration of >100,000 cells/mL in headwaters compared to near-dam surface waters (P < 0.001). Headwaters exhibited greater seasonal variability with more frequent and higher magnitude cyanoHABs occurring mid-summer to fall. Examination of reservoirs identified extremely high concentration cyanobacteria events (>1,000,000 cells/mL) occurring in 70% of headwater locations while only 30% of near-dam locations exceeded this threshold. Wilcoxon signed-rank tests of cyanoHAB magnitudes using paired-observations (dates with observations in both a reservoir's headwater and near-dam locations) confirmed significantly higher concentrations in headwater versus near-dam locations (p < 0.001).

cyanobacteria↗