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NASA NTRS2016

Caribbean Oceans: Utilizing NASA Earth Observations to Detect, Monitor, and Respond to Unprecedented Levels of Sargassum in the Caribbean Sea

In 2011 and 2015, the nations of the Caribbean Sea were overwhelmed by the unprecedented quantity of Sargassum that washed ashore. This issue prompted international discussion to better understand the origins, distribution, and movement of Sargassum, a free-floating brown macro alga with ecological, environmental, and commercial importance. In the open ocean, Sargassum mats serve a vital ecological function. However, when large quantities appear onshore without warning, Sargassum threatens local tourist industries and nearshore ecosystems within the Caribbean. As part of the international response, this project investigated the proliferation of this macro alga within the Caribbean Sea from 2003-2015, and used NASA Earth observations to detect and model Sargassum growth across the region. The Caribbean Oceans team calculated the Floating Algal Index (FAI) using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data, and compared the FAI to various oceanic variables to determine the ideal pelagic environment for Sargassum growth. The project also examined the annual spread of Sargassum throughout the region by using Earth Trends Modeler (ETM) in Clark Labs' TerrSet software. As part of the international effort to better understand the life cycle of Sargassum in the Caribbean, the results of this project will help local economies promote sustainable management practices in the region.

Ped, Jordan↗
NASA NTRS2015

IOCCG Report Number 16, 2015 Ocean Colour Remote Sensing in Polar Seas : The Polar Environment: Sun, Clouds, and Ice - Chapter 2

The polar regions are places of extremes. There are months when the regions are enveloped in unending darkness, and months when they are in continuous daylight. During the daylight months the sun is low on the horizon and often obscured by clouds. In the dark winter months temperatures are brutally cold, and high winds and blowing snow are common. Even in summer, temperatures seldom rise above 0degC. The cold winter temperatures cause the ocean to freeze, forming sea ice. This sea ice cover acts as a barrier limiting the transfer of heat, moisture, and momentum between the atmosphere and the ocean. It also greatly complicates the optical signature of the surface. Taken together, these factors make the polar regions a highly challenging environment for optical remote sensing of the ocean.

ocean colour↗
NASA NTRS2016

Radiative Effect of Springtime Biomass-Burning Aerosols over Northern Indochina During 7-SEAS Baseline 2013 Campaign

The direct aerosol radiative effects of biomass-burning (BB) aerosols over northern Indochina were estimated by using aerosol properties (physical, chemical, and optical) along with the vertical profile measurements from ground-based measurements with integration of an optical and a radiative transfer model during the Seven South East Asian Studies Biomass-Burning Aerosols Stratocumulus Environment: Lifecycles Interactions Experiment (7-SEASBASELInE) conducted in spring 2013. Cluster analysis of backward trajectories showed the air masses arriving at mountainous background site (Doi Ang Khang; 19.93degN, 99.05degE, 1536 m above mean sea level) in northern Indochina, mainly from near-source inland BB activities and being confined in the planetary boundary layer. The PM(sub10) and black carbon (BC)mass were 87 +/- 28 and 7 +/- 2 micrograms m(exp -3), respectively. The aerosol optical depth (AOD (sub 500) was found to be 0.26--1.13 (0.71 +/- 0.24). Finer (fine mode fraction is approximately or equal to 0.95, angstrom-exponent at 440-870 nm is approximately or equal to 1.77) and significantly absorbing aerosols(single scattering albedo is approximately or equal to 0.89, asymmetry-parameter is approximately or equal to 0.67, and absorption AOD 0.1 at 440 nm) dominated over this region. BB aerosols (water soluble and BC) were the main contributor to the aerosol radiative forcing (ARF), while others (water insoluble, sea salt and mineral dust) were negligible mainly due to their low extinction efficiency. BC contributed only 6 to the surface aerosol mass but its contribution to AOD was 12 (2 times higher). The overall mean ARF was 8.0 and -31.4 W m(exp -2) at top-of-atmosphere (TOA) and at the surface (SFC), respectively. Likely, ARF due to BC was +10.7 and -18.1 W m(exp -2) at TOA and SFC, respectively. BC imposed the heating rate of +1.4 K d(exp -1) within the atmosphere and highlighting its pivotal role in modifying the radiation budget. We propose that to upgrade our knowledge on BB aerosol radiative effects in BB source region, the long-term and extensive field measurements are needed.

aerosol optical properties↗
NASA NTRS2017

Improvements in Ice-Sheet Sea-Level Projections

Ice losses from Antarctica and Greenland are the largest uncertainty in sea-level projections. Nevertheless, improvements in ice-sheet models over recent decades have led to closer agreement with satellite observations, keeping track with their increasing contribution to global sea-level rise.

Shepherd, Andrew↗
NASA NTRS2018

Atmosphere-Ocean Coupled Data Assimilation Using NASA GEOS: Estimation of Air-Sea Interface State Variables

Air-sea interface variables, such as the skin Sea Surface Temperature (SST) are essential for atmosphere-ocean coupling. In the NASA GMAO Data Assimilation System (DAS), the skin SST and 3-D atmospheric state are jointly estimated [1]. This presentation is focused on the prior or background error covariance that is used in this analysis. The GEOS DAS uses an ensemble-variational assimilation strategy. In that, specification of a climatological background (CB) error covariance for SST relies on the NOAA's OI SST, with estimates of standard deviation and correlation length scales based on weekly analyses of the bulk SST at 1 degree resolution. However, present analysis system is striving to resolve SST diurnal variability with six hourly analyses and assimilates a vast number of in-situ and satellite observations. The first part of this presentation re-derives the CB error covariance using OSTIA SST analyses and illustrates the impact of this update on assimilating satellite observations. In a hybrid assimilation system the CB error covariances are appended with a flow-dependent background error covariance estimate implied by the underlying ensemble. The second part of this presentation refers to: a. treatment of the skin SST in the ensemble members, b. corresponding ensemble spread, and c. impact of these additions on the data assimilation system. [1] S. Akella, et al. (2017), doi:10.1002/qj.2988

Akella, Santha↗
NASA NTRS2018

The SUMup Dataset: Compiled Measurements of Surface Mass Balance Components over Ice Sheets and Sea Ice with Analysis over Greenland

Increasing atmospheric temperatures over ice cover affect surface processes, including melt, snowfall, and snow density. Here, we present the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset, a standardized dataset of Arctic and Antarctic observations of surface mass balance components. The July 2018 SUMup dataset consists of three subdatasets, snow/firn density (https://doi.org/10.18739/A2JH3D23R), at least near-annually resolved snow accumulation on land ice (https://doi.org/10.18739/A2DR2P790), and snow depth on sea ice (https://doi.org/10.18739/A2WS8HK6X), to monitor change and improve estimates of surface mass balance. The measurements in this dataset were compiled from field notes, papers, technical reports, and digital files. SUMup is a compiled, community-based dataset that can be and has been used to evaluate modeling efforts and remote sensing retrievals. Active submission of new or past measurements is encouraged. Analysis of the dataset shows that Greenland Ice Sheet density measurements in the top 1m do not show a strong relationship with annual temperature. At Summit Station, Greenland, accumulation and surface density measurements vary seasonally with lower values during summer months. The SUMup dataset is a dynamic, living dataset that will be updated and expanded for community use as new measurements are taken and new processes are discovered and quantified.

Montgomery, Lynn↗
NASA NTRS2018

Air-Sea Interactions in a High-Resolution Ocean-Atmosphere Simulation

During the past few years the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these "nature" simulations is the lack of interaction between the ocean and the atmosphere, which limits their usefulness for studying air-sea interactions and for designing observing missions to study these interactions. We present here results from a coupled GEOS-MIT "nature run" simulation, wherein we have coupled a cubed-sphere-720 (~ 1/8) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere simulation to equivalent atmosphere-only and ocean-only simulations. A particular focus of the comparisons is the coupled versus uncoupled differences in interactions between Sea Surface Temperature (SST) and ocean surface wind. We discuss, in particular, a several-day mode of temporal variability in the SST-wind cycle and how it is represented in the different model simulations and in observationally-based products. A mechanism for the cycle, which is driven by SST-wind feedback, is proposed.

Strobach, Ehud↗
NASA NTRS2019

An Ocean-Atmosphere Simulation for Studying Air-Sea Interactions

During the past few years the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these "nature" simulations is the lack of interaction between the ocean and the atmosphere, which limits their usefulness for studying air-sea interactions and for designing observing missions to study these interactions. To remove this limitation, we aim to perform a coupled simulation using the km-scale GEOS atmosphere and the km-scale MIT ocean models. The initial attempt at the km-scale coupled simulation resulted in computational issues which will be presented here. As a preliminary step towards the km-scale objective, we present results from a high resolution but not yet km-scale simulation, wherein we have coupled a cubed-sphere-720 (~ 1/8) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. A particular focus of the comparisons is the differences in interactions between Sea Surface Temperature (SST) and ocean surface wind for the coupled and uncoupled simulations. We discuss observed and modeled high temporal variability (~days) SST-wind cycle and how it is represented in the different systems. A mechanism for the cycle, which is driven by SST-wind feedback, is proposed.

Strobach, Ehud↗
NASA NTRS2018

Increased Snowfall over the Antarctic Ice Sheet Mitigated Twentieth-Century Sea-Level Rise

Changes in accumulated snowfall over the Antarctic Ice Sheet have an immediate and time-delayed impact on global mean sea level. The immediate impact is due to the instantaneous change in freshwater storage over the ice sheet, whereas the time-delayed impact acts in opposition through enhanced ice dynamic flux into the ocean. Here, we reconstruct 200 years of Antarctic-wide snow accumulation by synthesizing a newly compiled database of ice core records using reanalysis derived spatial coherence patterns. The results reveal that increased snow accumulation mitigated twentieth-century sea-level rise by approximately 10 millimeters since 1901, with rates increasing from 1.1 mm per decade between 1901 and 2000 to 2.5 mm per decade after 1979. Reconstructed accumulation trends are highly variable in both sign and magnitude at the regional scale, and linked to the trend towards a positive Southern Annular Mode since 1957. Because the observed Southern Annular Mode trend is accompanied by a decrease in Antarctic Ice Sheet accumulation, changes in the strength and location of the circumpolar westerlies cannot explain the reconstructed increase, which may instead be related to stratospheric ozone depletion. However, our results indicate that a warming atmosphere cannot be excluded as a dominant force in the underlying increase.

Antarctic↗
NASA NTRS2019

Retrieval of Snow Freeboard of Antarctic Sea Ice Using Waveform Fitting of CryoSat-2 Returns

In this paper we develop a CryoSat-2 algorithm to retrieve the surface elevation of the air–snow interface over Antarctic sea ice. This algorithm utilizes a two-layer physical model that accounts for scattering from a snow layer atop sea ice as well as scattering from below the snow surface. The model produces waveforms that are fit to CryoSat-2 level 1B data through a bounded trust region least-squares fitting process. These fit waveforms are then used to track the air–snow interface and retrieve the surface elevation at each point along the CryoSat-2 ground track, from which the snow freeboard is computed. To validate this algorithm, we compare retrieved surface elevation measurements and snow surface radar return power levels with those from Operation IceBridge, which flew along a contemporaneous CryoSat-2 orbit in October 2011 and November 2012. Average elevation differences (standard deviations) along the flight lines (IceBridge Airborne Topographic Mapper, ATM – CryoSat-2) are found to be 0.016 cm (29.24 cm) in 2011 and 2.58 cm (26.65 cm) in 2012. The spatial distribution of monthly average pan-Antarctic snow freeboard found using this method is similar to what was observed from NASA's Ice, Cloud, and land Elevation Satellite (ICESat), where the difference (standard deviation) between October 2011–2017 CryoSat-2 mean snow freeboard and spring 2003–2007 mean freeboard from ICESat is 1.92 cm (9.23 cm). While our results suggest that this physical model and waveform fitting method can be used to retrieve snow freeboard from CryoSat-2, allowing for the potential to join laser and radar altimetry data records in the Antarctic, larger (∼30 cm) regional differences from ICESat and along-track differences from ATM do exist, suggesting the need for future improvements to the method. Snow–ice interface elevation retrieval is also explored as a potential to obtain snow depth measurements. However, it is found that this retrieval method often tracks a strong scattering layer within the snow layer instead of the actual snow–ice interface, leading to an overestimation of ice freeboard and an underestimation of snow depth in much of the Southern Ocean but with promising results in areas such as the East Antarctic sector.

Fons, Steven W.↗
NASA NTRS2019

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite sea surface salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (North American Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF (Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive satellite) V4.1 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by satellite at approximately 1-centimeter depth) and in situ measurements (typically measured by Argo floats at 3-meters depth). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from GMAO S2S spring reanalyses that assimilate/withhold along-track (L2) SSS. In particular, we contrast forecasts of the big 2015 El Nino, the 2017 La Nina and the 2018 weak El Nino. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrade the mixed layer depth leading to more accurate coupled air/sea interaction. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of gridded satellite sea surface salinity observations on dynamical ENSO forecasts for the big 2015 El Nino.

Hackert, E.↗
NASA NTRS2019

Diurnal Cycle of ASCAT-Identified Cold Pools and Associated Convective Systems in the Maritime Continent and South China Sea

Mesoscale convective cold pools are known to alter the turbulent air-sea fluxes in the regions of active convection such as maritime tropics. Satellite-based Ocean Vector Wind instruments have proven to be useful in observing these mesoscale outflows corresponding to convective cold pools. A new storm-centric, tensor-based wind-gradient identification algorithm identifies gradients associated with convective cold pools and other boundaries such as land-sea breeze fronts. We term these as Gradient Features or GFs; analyzed over tropical oceans (2007-2018) using horizontal winds from Advanced Scatterometer (ASCAT-A).

Nesbitt, Stephen W.↗
NASA NTRS2019

The Southern Ocean Sea Surface Temperature Response to Ozone Depletion: A Multi-Model Comparison

The effect of the Antarctic ozone hole extends downwards from the stratosphere, with clear signatures in surface weather patterns including a positive trend in the Southern Annular Mode (SAM). Several recent studies have used coupled climate models to investigate the impact of these changes on Southern Ocean sea surface temperature (SST), notably motivated by the observed cooling from the late 1970s. Here we examine the robustness of these model results through comparison of both previously published and new simulations. We focus on the calculation of ‘climate response functions' (CRFs), transient responses to an instantaneous step-change in ozone concentrations. The CRF for most models consists of a rapid cooling of SST, followed by a slower warming trend. However, inter-model comparison reveals large uncertainties, such that even the sign of the impact of ozone depletion on historical SST, when reconstructed from the CRF, remains unconstrained. Comparison of these CRFs with SST responses to a hypothetical step-change in the SAM, inferred through lagged linear regression, shows broadly similar results. Causes of uncertainty are explored by examining relationships between model climatologies and their CRFs. The inter-model spread in CRFs can be reproduced by varying a single subgrid-scale mixing parameter within a single model. Antarctic sea-ice CRFs are also calculated: these do not generally exhibit the two-time-scale behavior of SST, suggesting a complex relationship between the two. Finally, by constraining model climatology-response relationships with observational values, we conclude that ozone depletion in unlikely to have been the primary driver of the observed SST cooling trend.

Climate response functions (CRF)↗
NASA NTRS2019

Improved Earth Oblateness Rate Reveals Increased Ice Sheet Losses and Mass-Driven Sea Level Rise

Satellite laser ranging (SLR) observations are routinely applied toward the estimation of dynamic oblateness, C(sub 20), which is the largest globally integrated component of Earth's time-variable gravity field. Since 2002, GRACE and GRACE Follow-On have revolutionized the recovery of higher spatial resolution features of global time-variable gravity, with SLR continuing to provide the most reliable estimates of C (sub 20).We quantify the effect of various SLR processing strategies on estimating C(sub 20) and demonstrate better signal recovery with the inclusion of GRACE-derived low-degree gravity information in the forward model. This improved SLR product modifies the Antarctic and Greenland Ice Sheet mass trends by -15.4 and -3.5 Gt/year, respectively, as compared to CSR TN11, and improves global mean sea level budget closure by modifying sea level rise by +0.08 mm/year. We recommend that this new C(sub 20) product be applied to RL06 GRACE data products for enhanced accuracy and scientific interpretation.

Loomis, B. D.↗
NASA NTRS2019

Decadal-Scale Vegetation Change Driven by Salinity at Leading Edge of Rising Sea Level

As sea levels rise, low-lying coastal forests increasingly are subject to stressors such as inundation and saltwater exposure. At long timescales (for example, centuries), the extent of inundation and saltwater exposure will increase; however, on a decadal timescale, the role of these drivers may differ in both magnitude and direction. To investigate the drivers of decadal-scale vegetation change, we measured the changes in five metrics of vegetation composition and structure between 2003/2004 and 2016/ 2017 at 98 plots distributed across a vegetation gradient from coastal forest to brackish marshes (< 0.5–18 ppt). We used elevation as a proxy of inundation vulnerability and soil sodium concentration as a proxy of saltwater exposure, and we investigated relationships between these two variables and the change in vegetation conditions between the two sampling periods. Soil sodium concentration was a significant predictor of vegetation change for all five vegetation metrics, whereas the effect of elevation was not significant for any of the metrics. The one site that was affected by wildfire twice during the duration of the study shifted almost completely from forest to marsh with limited regeneration ofwoody vegetation observed in 2016/ 2017. Our results show that salinization in our system is a more important driver of vegetation change than inundation potential. Furthermore, the effects of drought-induced salinization could be amplified by the elevated risk of wildfire during droughts. Forecasting the response of coastal wetlands to rising sea levels will require a better understanding of the individual and combined effects of salinity, droughts, and wildfires on vegetation.

Taillie, Paul J.↗
NASA NTRS2019

Impact of Aquarius and SMAP Satellite Sea Surface Salinity Observations on Coupled El Niño/Southern Oscillation Forecasts

This study demonstrates the positive impact of including gridded Aquarius and SMAP sea surface salinity (SSS) into initialization of coupled forecasts for the tropical Indo-Pacific. An experiment that assimilates conventional ocean observations serves as the control. In a separate experiment, Aquarius and SMAP satellite SSS are additionally assimilated into the control initialization. Analysis of the initialization differences with the control indicates that SSS assimilation causes a freshening and shallowing of the mixed layer depth (MLD) near the equator and enhanced Kelvin wave amplitude. For each month from September 2011 to September 2018, 12 month coupled ENSO forecasts are initialized from both the control and satellite SSS assimilation experiments. The experiment assimilating Aquarius and SMAP SSS significantly outperforms the control relative to observed NINO3.4 sea surface temperature anomalies. This work highlights the importance of inclusion of satellite SSS for improving the initialization ENSO coupled forecasts.

Hackert, Eric C.↗
NASA NTRS2019

Climatology of Transient Luminous Events and Lightning Observed Above Europe and the Mediterranean Sea

In 1999, the first sprites were observed above European thunderstorms using sensitive cameras. Since then, Eurosprite campaigns have been conducted to observe sprites and other transient luminous events (TLEs), expanding into a network covering large parts of Europe and coastal areas. In 2009 through 2013, the number of optical observations of TLEs reached a peak of 2000 per year. Because of this unprecedented number of European observations, it was possible to construct a climatology of 8394 TLEs observed above 1018 thunderstorm systems and study for the first time their distribution and seasonal cycle above Europe and parts of the Mediterranean Sea. The number of TLEs per thunderstorm was found to follow a power law, with less than 10 TLEs for 801 thunderstorms and up to 195 TLEs above the most prolific one. The majority of TLEs were classified as sprites, 641 elves, 280 halos, 70 upward lightning, 2 blue jets and 1 gigantic jet. The climatology shows intense TLE activity during summer over continental areas and in late autumn over coastal areas and sea. The two seasons peak, respectively, in August and November, separated by March and April with almost no TLEs, and a relative minimum around September. The observed TLE activity, i.e. mostly sprites, is shown to be largely consistent with lightning activity, with a 1/1000 of observed TLE-to-lightning ratio in regions with most observations. The overall behaviour is consistent among individual years, making the observed seasonal cycle a robust general feature of TLE activity above Europe.

Arnone, Enrico↗
NASA NTRS2019

Sea Surface Salinity Retrievals from Aquarius Using Neural Networks

Even though the Sea Surface Salinity (SSS) retrieved from Aquarius are generally very close to in-situ measurements, the level of similarity varies with the region and with the circumstances of the observations (wind speed, sea surface temperature, etc.). SSS is currently retrieved from the brightness temperatures measured by Aquarius and applying the current theoretical model for the propagation and emission of the natural thermal radiation. In this contribution we consider an alternative retrieval approach based on a Neural Network (NN) with the goal of improving the subsets of Aquarius SSS data that are in poorer agreement within-situ measurements. The subset considered here are the SSS retrieved at latitudes higher than 30 ̊. The output of the NN approach are compared against in-situ measurements using four statistical metrics (correlation coefficient, bias, RMSD and 5% trimmed range). The output of the NN and the nominal Aquarius SSS are compared against SSS values from in-situ measurements and from ocean models. From these comparisons it appears that the output of the NN matches the in-situ measurements better than the nominal Aquarius SSS.

Soldo, Yan↗