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NASA NTRS2007

MODIS Aerosol Observations used to Constrain Dust Distributions and Lifecycle in the NASA GEOS-5 Model

Approximately 240 Tg of mineral dust aerosol are transported annually from Saharan Africa to the Atlantic Ocean. Dust affects the Earth radiation budget, and plays direct (through scattering and absorption of radiation) and indirect (through modification of cloud properties and environment) roles in climate. Deposition of dust to the surface provides an important nutrient source to terrestrial and oceanic ecosystems. Dust is additionally a contributor to adverse air quality. Among the tools toward understanding the lifecycle and impacts of mineral dust aerosols are numerical models. Important constraints on these models come from quantitative satellite observations, like those from the space-based Moderate Resolution Imaging Spectroradiometer (MODIS). In particular, Kauhan et al. [2005] used MODIS aerosol observations to infer transport and deposition fluxes of Saharan dust over the Atlantic, Caribbean, and Amazonian basins. Those observations are used here to constrain the transport of dust and its interannual variability simulated in the NASA GEOS-5 general circulation model and data assimilation system. Significant uncertainty exists in the MODIS-derived fluxes, however, due to uncertainty in the wind fields provided by meteorological analyses in this region. That same uncertainty in the wind fields is manifest in our GEOS-5 simulations of dust distributions. Here we use MODIS observations to investigate the seasonality and location of the Saharan dust plume and explore through sensitivity analysis of our model the meteorological controls on the dust distribution, including dust direct radiative effects and sub-gridscale source and sink processes.

Colarco, P.↗

NASA NTRS2022

Future Climate Change Under SSP Emission Scenarios with GISS-E2.1

This paper presents the response to anthropogenic forcing in the GISS-E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non-interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One-Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1-G) and HYCOM (E2.1-H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1-2.6, SSP2-4.5, SSP4-6.0, and SSP5-8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high-mitigation scenarios SSP1-1.9 and SSP1-2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1-H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5-8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1-G (−1.21 × 106 km2/°C) and E2.1-H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5-8.5 in the E2.1-G model, comparable to the reduction in the corresponding CMIP5 GISS-E2 RCP8.5 simulation. Both low-end scenarios SSP1-1.9 and SSP1-2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).

climate models↗

NASA NTRS2001

Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

Kakar, Ramesh↗

NASA NTRS2009

Developing a Model-based Capability to Analyze Requirements for the Climate Observing System

Models are foundational for estimating states of the earth's climate system, both as tools to extrapolate information in time and space, and as observation 'operators' used to relate what is analyzed and predicted to what is observed. Expanding the simulation approach further, observing system simulation experiments (OSSEs) are designed to mimic the complete process of analyzing the climate state by replacing real observations with entirely simulated ones determined from a model-based depiction of nature. OSSEs provide a framework to 'fly' simulated satellite instruments through a synthetic atmosphere and investigate the trade-spaces of measurements for various satellite configurations and sampling strategies, and assess their measurement impact on modeling and forecasting capabilities. Such a tool is a crucial but as yet unfulfilled need for future mission selection and design. The components of a state-of-the-art OSSE system are being assembled at the Global Modeling and Assimilation Office (GMAO, Code 610.1) at NASA/GSFC, leveraging on the GMAO's existing modeling and data assimilation infrastructure for numerical weather prediction (NWP). The OSSE framework is based on the GMAO's Goddard Earth Observing System atmospheric general circulation model, version 5 (GEOS-5) and the Gridpoint Statistical Interpolation (GSI) observational analysis scheme, combined with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model developed by the Atmospheric Chemistry and Dynamics Branch (Code 613.3). This system is an evolving, key component of Goddard's planned development of an Integrated Earth System Analysis (IESA) capability, which will bring together into a single, fully interactive system Goddard's modeling and assimilation efforts in atmosphere, ocean and chemistry and aerosols to provide a comprehensive analysis and prediction system for weather and climate In addition to providing a state-of-the-art capability for assimilating current observation types, GEOS-5, and the future IESA, provide the capability to identify the need for, and assess the potential impact of, future observing systems under consideration for improving weather and climate prediction.

Gelaro, Ronald↗

NASA NTRS2021

Performance of JAXA’s SGLI standard ocean color products for oceanic to coastal waters: chlorophyll a concentration and light absorption coefficients of colored dissolved organic matter

We present the performance of JAXA’s SGLI standard algorithms for estimating chlorophyll a (chl a) concentration and the light absorption coefcients of colored dissolved organic matter (CDOM) using recently compiled high-quality data obtained from oceanic to coastal waters. Prior to the evaluation of the algorithms, we frst compare two forward models (Gordon et al. in J Geophys Res 93(D9):10909-10924, 1988: G88 and Park and Ruddick in Appl Opt 44(7):1236–1249, 2005: PR05) using a wide range of inherent optical properties (IOPs) to (1) examine if the water refectance is appropriately reproduced and (2) correct measured refectance in terms of its bidirectionality. Based on a good reproducibility of water refectance using the PR05, the optimized IOPs are further used for explaining errors in estimates of chl a concentration and CDOM absorption when using the SGLI, the GSM (Maritorena et al. in Appl Opt 41:2705–2714, 2002), and the QAA (Lee et al. in Appl Opt 41:5755, 2002) inversion algorithms. Results show that the mean error for estimating chl a concentration using the SGLI algorithm is 110% for our dataset. Although this error is lower than that of the GSM and the QAA algorithms, a signifcant underestimate at chl a higher than 2.0 mg m−3 is observed, which is further shown by independent match-up analyses. Another SGLI CDOM product includes the mean error of 50% and shows deviation at high CDOM range (>1.0 per m). A similar trend is observed for the GSM but not for the QAA when a global relationship of CDOM to colored detrital matter is applied. The sources of errors are discussed for potentially improving the retrievals

Second-generation GLobal Imager (SGLI)↗

DOE OSTI2025

ISMIP6-based Antarctic projections to 2100: simulations with the BISICLES ice sheet model

The contribution of the Antarctic Ice Sheet is one of the most uncertain components of sea level rise to 2100. Ice sheet models are the primary tool for projecting future sea level contribution from continental ice sheets. The Ice Sheet Model Intercomparison for the Coupled Model Intercomparison Phase 6 (ISMIP6) provided projections of the ice sheet contribution to sea level over the 21st century, quantifying uncertainty due to ice sheet model, climate model, emission scenario, and uncertain parameters. We present simulations following the ISMIP6 framework with the BISICLES ice sheet model and new experiments extending the ISMIP6 protocol to more comprehensively sample uncertainties in future climate, ice shelf sensitivity to ocean melting, and their interactions. These results contributed to the land ice projections of Edwards et al. (2021), which formed the basis of sea level projections for the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (AR6). Our experiments show the important interplay between surface mass balance processes and ocean-driven melt in determining Antarctic sea level contribution. Under higher-warming scenarios, high accumulation offsets more ocean-driven mass loss when sensitivity to ocean-driven melt is low. Conversely, we show that when sensitivity to ocean warming is high, ocean melting drives increased mass loss despite high accumulation. Overall, we simulate a sea level contribution range across our experiments from 2 to 178 mm. Finally, we show that collapse of ice shelves due to surface warming increases sea level contribution by 25 mm relative to the no-collapse experiments, for both moderate and high sensitivity of ice shelf melting to ocean forcing.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Southern Ocean Response to NADW Changes

The possibility of North Atlantic Deep Water (NADW) changes in both past and future climates has raised the issue of how the Southern Ocean would respond. Recent experiments with the GISS coupled atmosphere-ocean model have shown that a "bipolar see-saw" between NADW production and Antarctic Bottom Water (AABW) production in the Weddell Sea can occur in conjunction with freshening of the North Atlantic. However, this effect operates not through a slow ocean response but via a rapid atmospheric mechanism. As NADW reduces, colder temperatures in the North Atlantic, and Northern Hemisphere in general, are associated with higher surface pressure (increased atmospheric mass). Reduced mass in the Southern Hemisphere occurs in response, with lower pressure over the South Pole (an EOF #1 effect, the "high phase" of the Antarctic Oscillation).The lower pressure is associated with stronger west winds that generate an intensified Antarctic Circumpolar Current (ACC), which leads to longitudinal heat divergence in the South Atlantic (and heat convergence in the Southern Indian Ocean). Colder temperatures in the Weddell Sea region lead to sea ice growth, increased salinity and surface water density, and greater Weddell Sea Bottom Water production. Increased poleward transport of heat occurs in the South Atlantic in conjunction with increased bottom water production, but its convergence at high latitudes is not sufficient to offset the longitudinal heat divergence due to the intensified ACC. The colder temperatures at high latitudes in the South Atlantic increase the latitudinal temperature gradient, baroclinic instability, eddy energy and eddy poleward transport of momentum, helping to maintain the lower pressure over the pole in an interactive manner. The heat flux convergence in the Indian Ocean provides a warming tendency in that region, and overall global production of AABW remains unchanged. These results have implications for the interpretation of the ice core records of the last deglaciation, but may also be relevant for changes during the Holocene and perhaps even in response to increased CO2 forcing,

Rind, David↗

NASA NTRS2006

Terrestrial Water Mass Load Changes from Gravity Recovery and Climate Experiment (GRACE)

Recent studies show that data from the Gravity Recovery and Climate Experiment (GRACE) is promising for basin- to global-scale water cycle research. This study provides varied assessments of errors associated with GRACE water storage estimates. Thirteen monthly GRACE gravity solutions from August 2002 to December 2004 are examined, along with synthesized GRACE gravity fields for the same period that incorporate simulated errors. The synthetic GRACE fields are calculated using numerical climate models and GRACE internal error estimates. We consider the influence of measurement noise, spatial leakage error, and atmospheric and ocean dealiasing (AOD) model error as the major contributors to the error budget. Leakage error arises from the limited range of GRACE spherical harmonics not corrupted by noise. AOD model error is due to imperfect correction for atmosphere and ocean mass redistribution applied during GRACE processing. Four methods of forming water storage estimates from GRACE spherical harmonics (four different basin filters) are applied to both GRACE and synthetic data. Two basin filters use Gaussian smoothing, and the other two are dynamic basin filters which use knowledge of geographical locations where water storage variations are expected. Global maps of measurement noise, leakage error, and AOD model errors are estimated for each basin filter. Dynamic basin filters yield the smallest errors and highest signal-to-noise ratio. Within 12 selected basins, GRACE and synthetic data show similar amplitudes of water storage change. Using 53 river basins, covering most of Earth's land surface excluding Antarctica and Greenland, we document how error changes with basin size, latitude, and shape. Leakage error is most affected by basin size and latitude, and AOD model error is most dependent on basin latitude.

Seo, K.-W.↗

NASA NTRS2011

Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition

Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.

Lau, William K. M.↗

NASA NTRS2014

Far-Reaching Impacts of African Dust- A Calipso Perspective

African dust can transport across the tropical Atlantic and reach the Amazon basin, exerting far-reaching impacts on climate in downwind regions. The transported dust influences the surface-atmosphere interactions and cloud and precipitation processes through perturbing the surface radiative budget and atmospheric radiative heating and acting as cloud condensation nuclei and ice nuclei. Dust also influences biogeochemical cycle and climate through providing nutrients vital to the productivity of ocean biomass and Amazon forests. Assessing these climate impacts relies on an accurate quantification of dust transport and deposition. Currently model simulations show extremely large diversity, which calls for a need of observational constraints. Kaufman et al. (2005) estimated from MODIS aerosol measurements that about 144 Tg of dust is deposited into the tropical Atlantic and 50 Tg of dust into the Amazon in 2001. This estimated dust import to Amazon is a factor of 3-4 higher than other observations and models. However, several studies have argued that the oversimplified characterization of dust vertical profile in the study would have introduced large uncertainty and very likely a high bias. In this study we quantify the trans-Atlantic dust transport and deposition by using 7 years (2007-2013) observations from CALIPSO lidar. CALIPSO acquires high-resolution aerosol extinction and depolarization profiles in both cloud-free and above-cloud conditions. The unique CALIPSO capability of profiling aerosols above clouds offers an unprecedented opportunity of examining uncertainties associated with the use of MODIS clear-sky data. Dust is separated from other types of aerosols using the depolarization measurements. We estimated that on the basis of 7-year average, 118142 Tg of dust is deposited into the tropical Atlantic and 3860 Tg of dust into the Amazon basin. Substantial interannual variations are observed during the period, with the maximum to minimum ratio of about 1.6 and 2.5 for the deposition to the tropical Atlantic and Amazon, respectively. The MODIS-based estimates appear to fall within the range of CALIPSO-based estimates; and the difference between MODIS and CALIPSO estimates can be largely attributed to the interannual variability, which is corroborated by long-term surface dust concentration observations in the tropical Atlantic. Considering that CALIPSO generally tends to underestimate the aerosol loading, our estimate is likely to represent a low bound for the dust transport and deposition estimate. The finding suggests that models have substantial biases and considerable effort is needed to improve model simulations of dust cycle.

dust↗

NASA NTRS2021

Quantifying the role of ocean coupling in Arctic amplification and sea-ice loss over the 21st century

The enhanced warming of the Arctic, relative to other parts of the Earth, a phenomenon known as Arctic amplification, is one of the most striking features of climate change, and has important climatic impacts for the entire Northern Hemisphere. Several mechanisms are believed to be responsible for Arctic amplification; however, a quantitative understanding of their relative importance is still missing. Here, using ensembles of model integrations, we quantify the contribution of ocean coupling, both its thermodynamic and dynamic components, to Arctic amplification over the 20th and 21st centuries. We show that ocean coupling accounts for ~80% of the amplification by 2100. In particular, we show that thermodynamic coupling is responsible for future amplification and sea-ice loss as it overcomes the effect of dynamic coupling which reduces the amplification and sea-ice loss by ~35%. Our results demonstrate the utility of targeted numerical experiments to quantify the role of specific mechanisms in Arctic amplification, for better constraining climate projections.

Ocean heat transport↗

NASA NTRS2023

PACE Technical Report Series, Volume 11: The PACE Postlaunch Airborne eXperiment (PACE-PAX)

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; https://pace.gsfc.nasa.gov) mission is NASA's latest and greatest effort to study the ocean-atmosphere system and build upon the legacy of previous satellite missions that have revolutionized our understanding of our home planet. By using advanced radiometric and polarimetric instruments to measure ocean color and key atmospheric variables, PACE aims to provide new insights into the complex interactions between the ocean, atmosphere, and biosphere. This information will be critical for improving our ability to model and predict changes in the Earth's climate, as well as to manage and conserve our planet's valuable natural resources. Performance assessments and science data product validation is a critical process for any Earth Science space-borne mission, as it involves assessing and verifying the quality of the data products generated by the mission while it is in orbit, as well as assigning uncertainties to these retrievals. More specifically, validation efforts are essential for assessing the accuracy of instrument data and the derived science products across varied spatial and temporal scales and ensuring their reliability and consistency with the mission's scientific goals and objectives. The overall plan for validation of PACE data is described in “PACE Science Data Product Validation Plan” (see, e.g., https://pace.gsfc.nasa.gov), and among range of post-launch activities, it describes the need and requirements for a post-launch airborne field campaign in support of PACE validation. This volume outlines the plans and requirements of the PACE Postlaunch Airborne eXperiment (PACE-PAX). The main goal of PACE-PAX is to gather validation and assessment data for the PACE mission, using a variety of airborne and ground-based assets. These assets will be coordinated to obtain complementary measurements of key ocean and atmospheric variables, such as ocean color, aerosols, and clouds. By collecting data from multiple sources, PACE-PAX will help to validate and refine the data products generated by the PACE mission, as well as to identify any potential errors or biases in the measurements. This will be essential for ensuring the accuracy and reliability of the PACE data products, and for maximizing the scientific value of the mission.

Kirk D Knobelspiesse↗

NASA NTRS2016

North American Megadroughts in the Common Era: Reconstructions and Simulations

During the Medieval Climate Anomaly (MCA), Western North America experienced episodes of intense aridity that persisted for multiple decades or longer. These megadroughts are well documented in many proxy records, but the causal mechanisms are poorly understood. General circulation models (GCMs) simulate megadroughts, but do not reproduce the temporal clustering of events during the MCA, suggesting they are not caused by the time history of volcanic or solar forcing. Instead, GCMs generate megadroughts through (1) internal atmospheric variability, (2) sea-surface temperatures, and (3) land surface and dust aerosol feedbacks. While no hypothesis has been definitively rejected, and no GCM has accurately reproduced all features (e.g., timing, duration, and extent) of any specific megadrought, their persistence suggests a role for processes that impart memory to the climate system (land surface and ocean dynamics). Over the 21st century, GCMs project an increase in the risk of megadrought occurrence through greenhouse gas forced reductions in precipitation and increases in evaporative demand. This drying is robust across models and multiple drought indicators, but major uncertainties still need to be resolved. These include the potential moderation of vegetation evaporative losses at higher atmospheric [CO2], variations in land surface model complexity, and decadal to multidecadal modes of natural climate variability that could delay or advance onset of aridification over the the next several decades. Because future droughts will arise from both natural variability and greenhouse gas forced trends in hydroclimate, improving our understanding of the natural drivers of persistent multidecadal megadroughts should be a major research priority.

atmospheric temperature↗

NASA NTRS2001

Importance of the Annual Cycles of SST and Solar Irradiance for Circulation and Rainfall: A Climate Model Simulation Study

Annual cycle of climate and precipitation is related to annual cycle of sunshine and sea-surface temperatures. Understanding its behavior is important for the welfare of humans worldwide. For example, failure of Asian monsoons can cause widespread famine and grave economic disaster in the subtropical regions. For centuries meteorologists have struggled to understand the importance of the summer sunshine and associated heating and the annual cycle of sea-surface temperatures (SSTs) on rainfall in the subtropics. Because the solar income is pretty steady from year to year, while SSTs depict large interannual variability as consequence of the variability of ocean dynamics, the influence of SSTs on the monsoons are better understood through observational and modeling studies whereas the relationship of annual rainfall to sunshine remains elusive. However, using NASA's state of the art climate model(s) that can generate realistic climate in a computer simulation, one can answer such questions. We asked the question: if there was no annual cycle of the sunshine (and its associated land-heating) or the SST and its associated influence on global circulation, what will happen to the annual cycle of monsoon rains? By comparing the simulation of a 4-year integration of a baseline Control case with two parallel anomaly experiments: 1) with annual mean solar and 2) with annual mean sea-surface temperatures, we were able to draw the following conclusions: (1) Tropical convergence zone and rainfall which moves with the Sun into the northern and southern hemispheres, specifically over the Indian, African, South American and Australian regions, is strongly modulated by the annual cycles of SSTs as well as solar forcings. The influence of the annual cycle of solar heating over land, however, is much stronger than the corresponding SST influence for almost all regions, particularly the subtropics; (2) The seasonal circulation patterns over the vast land-masses of the Northern Hemisphere at mid and high latitudes also get strongly influenced by the annual cycles of solar heating. The SST influence is largely limited to the oceanic regions of these latitudes; (3) The annual mode of precipitation over Amazonia has an equatorial regime revealing a maxima in the month of March associated with SST, and another maxima in the month of January associated with the solar annual cycles, respectively. The baseline simulation, which has both annual cycles, depicts both annual modes and its rainfall is virtually equal to the sum of those two modes; (4) Rainfall over Sahelian-Africa is significantly reduced (increased) in simulations lacking (invoking) solar irradiation with (without) the annual cycle. In fact, the dominant influence of solar irradiation emerges in almost all monsoonal-land regions: India, Southeast Asia, as well as Australia. The only exception is the Continental United States, where solar annual cycle shows only a relatively minor influence on the annual mode of rainfall.

Sud, Yogesh C.↗

DOE OSTI2024

The Nonlinear and Distinct Responses of Ocean Heat Content and Anthropogenic Carbon to Ice Sheet Freshwater Discharge in a Warming Climate

Anthropogenic climate change will drive extensive mass loss across both the Antarctic (AIS) and Greenland Ice Sheets (GrIS), with the potential for global climate system feedbacks, especially in polar regions. Historically, the high-latitude North Atlantic and Southern Ocean have been critical regions for anthropogenic heat and carbon uptake, but our understanding of how this uptake will be altered by future freshwater discharge is incomplete. We assess each ice sheet's impact on global ocean anthropogenic heat and carbon storage for a high-emission scenario over the 21 st -century using a coupled Earth system model. We explore the impact of contemporaneous mass loss from both ice sheets on anthropogenic heat and carbon storage and quantify their linear and nonlinear contributions. Notably, added freshwater reduces ocean heat and carbon storage by 2,100, and the sum of individual freshwater effects differ from those induced by simultaneous freshwater discharge from both ice sheets. Combined AIS and GrIS freshwater engenders distinct anthropogenic storage anomalies—particularly in the high-latitude Southern Ocean and North Atlantic. From 2080 to 2100, GrIS freshwater exerts primary control on the temporal evolution of global ocean heat storage, while global ocean carbon storage is modulated by the linear AIS and GrIS freshwater impacts. Nonlinear impacts of simultaneous ice sheet discharge have a non-negligible contribution to the evolution of global ocean heat storage. Further, anthropogenic heat changes are realized more quickly in response to ice sheet discharge than anthropogenic carbon. Our results highlight the need to incorporate both ice sheets actively in climate models to accurately project future global climate.

Gorte, Tessa↗

NASA NTRS2000

Atlas of Seasonal Means Simulated by the NSIPP 1 Atmospheric GCM

This atlas documents the climate characteristics of version 1 of the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Atmospheric General Circulation Model (AGCM). The AGCM includes an interactive land model (the Mosaic scheme), and is part of the NSIPP coupled atmosphere-land-ocean model. The results presented here are based on a 20-year (December 1979-November 1999) "ANIIP-style" integration of the AGCM in which the monthly-mean sea-surface temperature and sea ice are specified from observations. The climate characteristics of the AGCM are compared with the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasting (ECMWF) reanalyses. Other verification data include Special Sensor Microwave/Imager (SSNM) total precipitable water, the Xie-Arkin estimates of precipitation, and Earth Radiation Budget Experiment (ERBE) measurements of short and long wave radiation. The atlas is organized by season. The basic quantities include seasonal mean global maps and zonal and vertical averages of circulation, variance/covariance statistics, and selected physics quantities.

Suarez, Max J.↗

NASA NTRS2013

Interannual Variation in Phytoplankton Primary Production at a Global Scale

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on group-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Coccolithophores↗

NASA NTRS2022

Ambiguous Stability of Glaciers at Bed Peaks

Increasing ice flux from glaciers retreating over deepening (retrograde) bed topography has been implicated in the recent acceleration of mass loss from the Greenland and Antarctic ice sheets. We show in observations that some glaciers have remained at peaks in bed topography without retreating despite enduring significant changes in climate. Observations also indicate that some glaciers which persist at bed peaks undergo sudden retreat years or decades after the onset of local ocean or atmospheric warming. Using model simulations, we show that persistence of a glacier at a bed peak is caused by ice slowing as it flows up a reverse-sloping bed to the peak. Persistence at bed peaks may lead to two very different future behaviors for a glacier: one where it persists at a bed peak indefinitely, and another where it retreats from the bed peak after potentially long delays following climate forcing. However, it is nearly impossible to distinguish which of these two future behaviors will occur from current observations. We conclude that inferring glacier stability from observations of persistence obscures our true commitment to future sea-level rise under climate change. We recommend that further research is needed on seemingly stable glaciers to determine their likely future.

ice dynamics↗