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NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗
NASA NTRSDate not supplied

Climate Information and Lessons Learned from the NASA Earth eXchange (NEX), Short-term Prediction Research and Transition Center (NASA SPoRT), and the NASA Regional Climate Model Evaluation System (RCMES)

Climate resilience can emerge from a combination of (1) climate projections that enable future-oriented planning and (2) contemporary observations that can be used for adaptation in the face of realized climate. NASA is uniquely positioned to provide global climate projections and satellite-based observations to users who must take a global perspective on climate risk (e.g., supply chain managers). Here, we will share the capabilities and experiences of three NASA projects. The first project, the NASA Earth eXchange (NEX) provides two downscaled climate projections, NEX-GDDP-CMIP6, a global 25 km resolution product, and NEX-DCP30-CMIP6, an 800 m resolution product covering the coterminous U.S. specifically designed for U.S. National Climate Assessment (NCA). NEX also offers land surface products that mirror the twice-daily products provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) but are derived from operational geostationary weather satellite data collected at 5-10 minutes intervals. The second project, the Short-term Prediction Research and Transition Center (SPoRT), was established in 2002 to transition unique NASA satellite products and capabilities to stakeholders to improve decision-making that benefits society. SPoRT provides products and capabilities derived from NASA observations and models to end users in government, academia, and the private sector. SPoRT translates NASA Earth science into actionable solutions reaching over 400 stakeholders across 80 organizations. Finally, the Regional Climate Model Evaluation System (RCMES) is designed to facilitate regional-scale evaluations of climate models by providing standardized access to a vast and comprehensive set of observations, such as satellite, in-situ, and reanalyses, and modeling resources such as CMIP & CORDEX. These three projects form part of the core capabilities at the NASA Centers deliver climate information under the new NASA Earth Science to Action (ES2A) strategy.

NEX↗
DOE OSTI2020

A Baseline for Global Weather and Climate Simulations at 1 km Resolution

In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four-month simulation (November 2018 to February 2019) with ECMWF's hydrostatic Integrated Forecasting System (IFS) at an average grid spacing of 1.4 km. The impact of explicitly simulating deep convection on the atmospheric circulation and its variability is assessed by comparing the 1.4 km simulation to the equivalent well-tested and calibrated global simulations at 9 km grid spacing with and without parametrized deep convection. The explicit simulation of deep convection at 1.4 km results in a realistic large-scale circulation, better representation of convective storm activity, and stronger convective gravity wave activity when compared to the 9 km simulation with parametrized deep convection. Comparison of the 1.4 km simulation to the 9 km simulation without parametrized deep convection shows that switching off deep convection parametrization at a too coarse resolution (i.e., 9 km) generates too strong convective gravity waves. Based on the limited statistics available, improvements to the Madden-Julian Oscillation or tropical precipitation are not observed at 1.4 km, suggesting that other Earth system model components and/or their interaction are important for an accurate representation of these processes and may well need adjusting at deep convection resolving resolutions. Overall, the good agreement of the 1.4 km simulation with the 9 km simulation with parametrized deep convection is remarkable, despite one of the most fundamental parametrizations being turned off at 1.4 km resolution and despite no adjustments being made to the remaining parametrizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

PCMDI Metrics Package

The Program for Climate Model Diagnosis & Intercomparison (PCMDI) Metrics Package (PMP) is used to provide "quick-look" objective comparisons of Earth System Models (ESMs) with one another and available observations. The PMP provides a diverse suite of analysis utilities each of which produce summary statistics that gauge the consistency between climate model simulations and available observations. The primary application of the PMP is to evaluate simulations from the Coupled Model Intercomparison Project (CMIP). It can also be used to provide objective performance summaries during the model development process as well as selected research purposes.

Ullrich, PaulA [Lawrence Livermore National Labora↗
DOE OSTI2023

Assessing Tropical Pacific-induced Predictability of Southern California Precipitation Using a Novel Multi-input Multi-output Autoencoder

We construct a novel Multi-Input Multi-Output Autoencoder-decoder (MIMO-AE) to capture the non-linear relationship of Southern California precipitation and tropical Pacific Ocean sea surface temperature. The MIMO-AE is trained on both monthly TP-SST and SC-PRECIP anomalies simultaneously. The co-variability of the two fields in the MIMO-AE shared nonlinear latent space can be condensed into an index, termed the MIMO-AE index. We use a transfer learning approach to train a MIMO-AE on the combined dataset of 100 years of output from a historical simulation with the Energy Exascale Earth Systems Model version 1 and a segment of observational data. We further use Long Short-Term Memory networks to assess sub-seasonal predictability of SC-PRECIP using the MIMO-AE index. We find that the MIMO-AE index provides enhanced predictability of SC-PRECIP for a lead-time of up-to four months as compared to Niño 3.4 index and the El Niño Southern Oscillation Longitudinal Index.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessment of Precipitating Marine Stratocumulus Clouds in the E3SMv1 Atmosphere Model: A Case Study from the ARM MAGIC Field Campaign

This paper presents a process-oriented evaluation of precipitating stratocumulus and its transition to cumulus in version 1 of the Energy Exascale Earth System Model (E3SMv1) using comprehensive case-study observations from a field campaign of the Atmospheric Radiation Measurement program (ARM). The E3SMv1 single-column model (SCM) of the marine boundary layer and its low clouds and precipitation are compared to observations including subcloud drizzle retrievals from a combination of Doppler radar and lidar backscatter measurements. Additionally, the SCM is also compared to a large-eddy simulation (LES) of the same case. The combination of advanced remote sensing observations and LES is a powerful framework to evaluate the physical parameterizations of large-scale models. Given the observed large-scale environment, the E3SMv1 SCM realistically represents the evolution of clouds and boundary layer structure during the stratocumulus-to-cumulus transition. The model well simulates the liquid water path and its diurnal cycle in the stratocumulus period as well as the two-layer vertical thermodynamic structure and lower cloud fraction in the transition period. E3SMv1’s success in simulating the cloud in the stratocumulus period permitted examination of its precipitation processes. Here problems were identified with E3SMv1 producing an unrealistically small subcloud precipitation fraction, an unrealistic double peak in the vertical profiles of precipitation mass, and drizzle that evaporates too close to the surface. Further model diagnostics determined that these unrealistic characteristics resulted from an overly long microphysics time step and an unrealistic parameterization of the precipitation fraction. These results imply that careful consideration of these issues is needed in order to better simulate precipitation processes in marine stratocumulus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coastal-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) Science Plan

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations regarding the impacts of climate change and associated mitigation and adaptation measures. Earth system (climate and weather) models have not yet been adapted to provide accurate predictions of climate and weather variability within cities, nor do they provide well-tested representations of the impacts of urban systems on the atmospheric environment. These limitations are largely due to limited field data available for testing and development of these models. We will deploy the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first Mobile Facility (AMF1) to the mid-Atlantic region surrounding the city of Baltimore for the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE). This deployment will create a four-node regional atmospheric observatory network including Baltimore and its three primary surrounding environments – rural, urban, and bay. CoURAGE investigators will study the interactions among the Earth’s surface, the atmospheric boundary layer, aerosols and atmospheric composition, clouds, radiation, and precipitation at each site, and examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. This study will determine the degree to which Baltimore’s atmospheric environment depends on interactive feedbacks in the atmospheric system and the degree to which conditions in Baltimore depend on the surrounding environment. Some topics of interest include how urban land management exacerbates heat waves, the impact of regional mesoscale winds (nocturnal jet, bay breeze) on urban air pollution and cloud cover, and the impact of the urban heat island and aerosol production on heavy precipitation events. Understanding this integrated coast-urban-rural system quantitatively and with good accuracy and precision is critical to informing climate adaptation and mitigation efforts in the city of Baltimore. The understanding gained should be applicable to many similar coastal, mid-latitude urban centers. Another important objective of CoURAGE is to improve the representation of the climate of coastal cities in Earth systems models (ESMs). CoURAGE investigators will use the observations to test current ESMs, identify weaknesses and work towards improved simulations of this complex environment. The ARM core facility will be deployed in the city of Baltimore, complementing the Baltimore Social-Environmental Collaborative (BSEC), a DOE urban integrated field laboratory (UIFL). Ancillary sites will be deployed to rural Maryland northwest of Baltimore, and to the southern end of Kent Island within Chesapeake Bay. The fourth node will be a long-term atmospheric observatory operated in Beltsville, Maryland by Howard University and the Maryland Department of the Environment. Measurements will be conducted for one year, starting in December of 2024. There will be two intensive operational periods (IOPs), one in summer and one in winter, when the ancillary sites will be enhanced with additional balloon launches, tethered balloon system (TBS) operation, and added atmospheric composition measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SCILLA Scanning Electrical Mobility Spectrometer (SEMS) airborne data

The Scanning Electrical Mobility Spectrometer (SEMS) provides measurements of bulk aerosol size distributions, which are crucial for studying aerosol-cloud interactions. The instrument sampled through two different inlets: an isokinetic inlet and a counter-flow virtual impactor (CVI) inlet. Data were collected to help improve climate and earth systems models, characterize atmospheric conditions, and validate satellite observations and climate simulations.

Scanning Electrical Mobility Spectrometer↗
NASA NTRS1990

HgZnTe-based detectors for LWIR NASA applications

The initial goal was to grow and characterize HgZnTe and determine if it indeed had the advantageous properties that were predicted. Researchers grew both bulk and liquid phase epitaxial HgZnTe. It was determined that HgZnTe had the following properties: (1) microhardness at least 50 percent greater than HgCdTe of equivalent bandgap; (2) Hg annealing rates of at least 2 to 4 times longer than HgCdTe; and (3) higher Hg vacancy formation energies. This early work did not focus on one specific composition (x-value) of HgZnTe since NASA was interested in HgZnTe's potential for a variety of applications. Since the beginning of 1989, researchers have been concentrating, however, on the liquid phase growth of very long wavelength infrared (VLWIR) HgZnTe (cutoff approx. equals 17 microns at 65K) to address the requirements of the Earth Observing System (EOS). Since there are no device models to predict the advantages in reliability one can gain with increased microhardness, surface stability, etc., one must fabricate HgZnTe detectors and assess their relative bake stability (accelerated life test behavior) compared with HgCdTe devices fabricated in the same manner. Researchers chose to fabricate HIT detectors as a development vehicle for this program because high performance in the VLWIR has been demonstrated with HgCdTe HIT detectors and the HgCdTe HIT process should be applicable to HgZnTe. HIT detectors have a significant advantage for satellite applications since these devices dissipate much less power than conventional photoconductors to achieve the same responsivity.

Patten, Elizabeth A.↗
NASA NTRS2011

Methane Sensitivity to Perturbations in Tropospheric Oxidizing Capacity

Methane is an important greenhouse gas and has a 25 times greater global warming potential than CO2 on a century timescale. Yet there are considerable uncertainties in the magnitude and variability of its sources and sinks. The response of the coupled non-linear methane-carbon monoxide-hydroxyl radical (OH) system is important in determining the tropospheric oxidizing capacity. Using the NASA Goddard Earth Observing System, Version 5 (GEOS-5) chemistry climate model, we study the response of methane to perturbations of OH and wetland emissions. We use a computationally-efficient option of the GEOS-5 CCM that includes an OH parameterization that accurately represents OH predicted by a full chemical mechanism. The OH parameterization allows for studying non-linear CH4-CO-OH feedbacks in computationally fast sensitivity experiments. We compare our results with surface observations (GMD) and discuss the range of uncertainty in OH and wetland emissions required to bring modeling results in better agreement with surface observations. Our results can be used to improve projections of methane emissions and methane growth.

Yegorova, Elena↗
NASA NTRS2012

The Response of Tropospheric Ozone to ENSO in Observations and a Chemistry-Climate Simulation

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent results have revealed an ENSO induced wave-l anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this result using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show targeted comparisons with observations from NASA's Aura satellite Microwave Limb Sounder (MLS), and the Tropospheric Emissions Spectrometer (TES) to provide insight into the vertical structure of ozone changes. The tropospheric ozone response to ENSO could be a useful chemistry-climate model evaluation tool and should be considered in future modeling assessments.

Oman, L. D.↗
NASA NTRS2012

The Response of Lower Atmospheric Ozone to ENSO in Aura Measurements and a Chemistry-Climate Simulation

The El Nino-Southern Oscillation (ENSO) is the dominant mode of tropical variability on interannual time scales. ENSO appears to extend its influence into the chemical composition of the tropical troposphere. Recent work has revealed an ENSO-induced wave-1 anomaly in observed tropical tropospheric column ozone. This results in a dipole over the western and eastern tropical Pacific, whereby differencing the two regions produces an ozone anomaly with an extremely high correlation to the Nino 3.4 Index. We have successfully reproduced this feature using the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 25 years. An examination of the modeled ozone field reveals the vertical contributions of tropospheric ozone to the column over the western and eastern Pacific region. We will show composition sensitivity in observations from NASA s Aura satellite Microwave Limb Sounder (MLS) and the Tropospheric Emissions Spectrometer (TES) and a simulation to provide insight into the vertical structure of these ENSO-induced ozone changes. The ozone changes due to the Quasi-Biennial Oscillation (QBO) in the extra-polar upper troposphere and lower stratosphere in MLS measurements will also be discussed.

Oman, L. D.↗
NASA NTRS2013

Impacts of Atmosphere-Ocean Coupling on Southern Hemisphere Climate Change

Climate in the Southern Hemisphere (SH) has undergone significant changes in recent decades. These changes are closely linked to the shift of the Southern Annular Mode (SAM) towards its positive polarity, which is driven primarily by Antarctic ozone depletion. There is growing evidence that Antarctic ozone depletion has significant impacts on Southern Ocean circulation change. However, it is poorly understood whether and how ocean feedback might impact the SAM and climate change in the SH atmosphere. This outstanding science question is investigated using the Goddard Earth Observing System Coupled Atmosphere-Ocean-Chemistry Climate Model(GEOS-AOCCM).We perform ensemble simulations of the recent past (1960-2010) with and without the interactive ocean. For simulations without the interactive ocean, we use sea surface temperatures and sea ice concentrations produced by the interactive ocean simulations. The differences between these two ensemble simulations quantify the effects of atmosphere-ocean coupling. We will investigate the impacts of atmosphere-ocean coupling on stratospheric processes such as Antarctic ozone depletion and Antarctic polar vortex breakup. We will address whether ocean feedback affects Rossby wave generation in the troposphere and wave propagation into the stratosphere. Another focuson this study is to assess how ocean feedback might affect the tropospheric SAM response to Antarctic ozone depletion

Chemistry-Climate Modeling↗
NASA NTRS2014

SERVIR Presentation for the Hyperwall at the ESRI International Users Conference

From space, we can view our planet in new ways. As a joint initiative of NASA and USAID working in partnership with leading regional organizations, SERVIR connects space to village by helping people in developing countries use that view to gain knowledge and insights about their environments. We teach regional decision-makers to use Earth observation satellite data, Geographic Information Systems, and predictive models for addressing issues such as water and land use, natural disasters, agricultural problems, biodiversity conservation, and more to improve the lives, livelihoods, safety, and future of the people in their countries.

Irwin, Dan↗
NASA NTRS2016

The NASA Applied Sciences Program: Volcanic Ash Observations and Applications

Since 2000, the NASA Applied Sciences Program has been actively transitioning observations and research to operations. Particular success has been achieved in developing applications for NASA Earth Observing Satellite (EOS) sensors, integrated observing systems, and operational models for volcanic ash detection, characterization, and transport. These include imager applications for sensors such as the MODerate resolution Imaging SpectroRadiometer (MODIS) on NASA Terra and Aqua satellites, and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NASA/NOAA Suomi NPP satellite; sounder applications for sensors such as the Atmospheric Infrared Sounder (AIRS) on Aqua, and the Cross-track Infrared Sounder (CrIS) on Suomi NPP; UV applications for the Ozone Mapping Instrument (OMI) on the NASA Aura Satellite and the Ozone Mapping Profiler Suite (OMPS) on Suomi NPP including Direct readout capabilities from OMI and OMPS in Alaska (GINA) and Finland (FMI):; and lidar applications from the Caliop instrument coupled with the imaging IR sensor on the NASA/CNES CALIPSO satellite. Many of these applications are in the process of being transferred to the Washington and Alaska Volcanic Ash Advisory Centers (VAAC) where they support operational monitoring and advisory services. Some have also been accepted, transitioned and adapted for direct, onboard, automated product production in future U.S. operational satellite systems including GOES-R, and in automated volcanic cloud detection, characterization and alerting tools at the VAACs. While other observations and applications remain to be developed for the current constellation of NASA EOS sensors and integrated with observing and forecast systems, future requirements and capabilities for volcanic ash observations and applications are also being developed. Many of these are based on technologies currently being tested on NASA aircraft, Unmanned Aerial Systems (UAS) and balloons. All of these efforts and the potential advances that will be realized by integrating them are shared in this presentation.

Murray, John J.↗
NASA NTRS2017

GEOS-5 Seasonal Forecast System

Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9 month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

GEOS-5↗
NASA NTRS2018

Simulation and Prediction of Warm Season Drought in North America

This presentation presents our recent work on model simulation and prediction of warm season drought in North America. The emphasis will be on the contribution from the leading modes of subseasonal atmospheric circulation variability, which are often present in the form of stationary Rossby waves. Here we take advantage of the results from observations, reanalyses, and simulations and reforecasts performed using the NASA Goddard Earth Observing System (GEOS-5) atmospheric and coupled General Circulation Model (GCM). Our results show that stationary Rossby waves play a key role in Northern Hemisphere (NH) atmospheric circulation and surface meteorology variability on subseasonal timescales. In particular, such waves have been crucial to the development of recent short-term warm season heat waves and droughts over North America (e.g. the 1988, 1998, and 2012 summer droughts) and northern Eurasia (e.g., the 2003 summer heat wave over Europe and the 2010 summer drought and heat wave over Russia). Through an investigation of the physical processes by which these waves lead to the development of warm season drought in North America, it is further found that these waves can serve as a potential source of drought predictability. In order to properly represent their effect and exploit this source of predictability, a model needs to correctly simulate the Northern Hemisphere (NH) mean jet streams and be able to predict the sources of these waves. Given the NASA GEOS-5 AGCM deficiency in simulating the NH jet streams and tropical convection during boreal summer, an approach has been developed to artificially remove much of model mean biases, which leads to considerable improvement in model simulation and prediction of stationary Rossby waves and drought development in North America. Our study points to the need to identify key model biases that limit model simulation and prediction of regional climate extremes, and diagnose the origin of these biases so as to inform modeling group for model improvement.

Rossby Waves↗
NASA NTRS2018

GEOS S2S-2_1 File Specification: GMAO Seasonal and Sub-Seasonal Forecast Output

The NASA GMAO seasonal (9 months) and subseasonal (45 days) forecasts are produced with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model and Data Assimilation System Version S2S-2_1. The new system replaces version S2S-1.0 described in Borovikov et al (2017), and includes upgrades to many components of the system. The atmospheric model includes an upgrade from a pre-MERRA-2 version running on a latitude-longitude grid at approx. 1 degree resolution to a current version running on a cubed sphere grid at approximately 1/2 degree resolution. The important developments are related to the dynamical core (Putman et al., 2011), the moist physics (''two-moment microphysics'' of Barahona et al., 2014) and the cryosphere (Cullather et al., 2014). As in the previous GMAO S2S system, the land model is that of Koster et al (2000). GMAO S2S-2_1 now includes the Goddard Chemistry Aerosol Radiation and Transport (GOCART, Colarco et al., 2010) single moment interactive aerosol model that includes predictive aerosols including dust, sea salt and several species of carbon and sulfate. The previous version of GMAO S2S specified aerosol amounts from climatology, which were used to inform the atmospheric radiation only. The ocean model includes an upgrade from MOM4 to MOM5 (Griffies 2012), and continues to be run on the tripolar grid at approximately 1/2 degree resolution in the tropics with 40 vertical levels. As in S2S-1.0, the sea ice model is from the Los Alamos Sea Ice model (CICE4, Hunke and Lipscomb 2010). The Ocean Data Assimilation System (ODAS) has been upgraded from the one described in Borovikov et al., 2017 to one that uses a modified version of the Penny, 2014 Local Ensemble Transform Kalman Filter (LETKF), and now assimilates along-track altimetry. The ODAS also does a nudging to MERRA-2 SST and sea ice boundary conditions. The atmospheric data assimilation fields used to constrain the atmosphere in the ODAS have been upgraded from MERRA to a MERRA-2 like system. The system is initialized using a MERRA-2-like atmospheric reanalysis (Gelaro et al. 2017) and the GMAO S2S-2_1 ocean analysis. Additional ensemble members for forecasts are produced with initial states at 5-day intervals, with additional members based on perturbations of the atmospheric and ocean states. Both subseasonal and seasonal forecasts are submitted to the National MultiModel Ensemble (NMME) project, and are part of the US/Canada multimodel seasonal forecasts (http://www.cpc.ncep.noaa.gov/products/NMME/). A large suite of retrospective forecasts (''hindcasts'') have been completed, and contribute to the calculation of the model's baseline climatology and drift, anomalies from which are the basis of the seasonal forecasts.

Seasonal Forecast↗