UFS S2S AT All-Hands Meetings - UFS R2O
The UFS S2S Application Team is joining efforts with the EMC Coupled Modeling Team in organizing monthly All-Hands meetings on UFS Coupled Global Model Evaluation on S2S Time Scales. Meetings will be organized around S2S science topics, including prediction skill of the UFS and other models on this timescale, and new diagnostics designed to advance the understanding of Earth system variability of the S2S timescale. Another goal of these meetings is to identify projects that can be spun up to fill the gap in the model evaluation, improving the forecast skill, and how to communicate and apply the S2S forecasts. The format of the meetings will alternate between informal presentations followed by short discussions and informal discussions around topics of interest identified by the UFS S2S community.
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Upcoming UFS S2S AT All-Hands Presentations
The next S2S AT All-Hands is planned for: Friday April 19th, 2024 at 2:00 - 3:00 PM ET
2024
- Title: The CESM2 Seasonal-to-Multiyear Large Ensemble (SMYLE) forecast system: Past Performance and Recent Applications
- Speaker: Steve Yeager, Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
- Abstract: The SMYLE prediction system is a roughly 8,500 simulation-year experiment consisting of 24-month hindcasts initialized 4 times per year (February, May, August, November) between 1970 and present, with each hindcast comprising a 20-member ensemble. The system uses the Community Earth System Model version 2 (CESM2) at nominal 1° horizontal resolution, and a full suite of output is available for exploring seasonal-to-interannual predictability
of all Earth system components represented in CESM2 (including ocean biogeochemistry). The extended forecast range permits investigation of Earth system predictability out through Year 2, including the dependence of skill on initialization season. The system exhibits competitive skill for seasonal forecasts of El Niño – Southern Oscillation (ENSO), and it outperforms the North American Multi-Model Ensemble (NMME) system for hindcasts initialized in February. The SMYLE prediction framework has facilitated a growing number of studies on seasonal predictability, prediction, and initialized attribution by the CESM community. - Presentation Slides
- Title: An NSST Alternative: SkinSST
- Speaker: Shan Sun & Rainer Bleck, NOAA Global Systems Laboratory
- Abstract: We analyzed the modeled sea surface temperature (SST) bias in multiple seasonal forecast experiments with NOAA's coupled Unified Forecast System (UFS) model. The UFS model consists of the FV3 atmospheric model with the Global Forecast System (GFS) physics package, as well as the MOM6 ocean model and CICE6 sea ice model. The baseline experiment utilized the UFS coupled model Prototype/HR3, with the NSST (near-surface SST) algorithm as the default setting. Notably, the modeled SST exhibited an overall positive bias.
To address this, we conducted a second experiment mirroring the control experiment in all aspects, except replacing the NSST algorithm, whose original purpose was to simulate the diurnal SST cycle in uncoupled applications, by a skin temperature scheme tailored to coupled ocean-atmosphere simulations. The outcome demonstrates a small reduction in error in SST, cloud cover and shortwave radiation, in comparison to the control experiments. This highlights the sensitivity of the coupled system to differences in ocean skin temperature parameterization. We also find that model biases in atmospheric physics are one of the main sources of model errors at the subseasonal time scale.
- Title: Process-oriented diagnostics of precipitation in the NOAA-MDTF
- Speaker: Fiaz Ahmed
- Abstract: Process-oriented diagnostics (PODs) target representations of physical processes in climate
models—in contrast to benchmark diagnostics such as TOA energy balance. The NOAA-funded Model Diagnostics Task Force (MDTF) aims to move PODs developed within smaller research teams, into the model development pipeline at GFDL and NCAR. In this talk, I will provide a short introduction to the MDTF and the software framework that maintains a collection of PODs. I will then highlight how process-level diagnostics can be deployed in the model development workflow, by using precipitation-related PODs as examples. In particular, these PODs aim to constrain aspects of the convective parameterization schemes in climate models, using a combination of theory and observational data. I will conclude with a look at some of the newer features available in the MDTF framework, with an emphasis on the capability to concurrently diagnose multiple model runs. Ideas to adapt the MDTF framework for use with forecast ensembles will be discussed. Thoughts and feedback on this aspect of the MDTF framework are welcome. - Presentation Slides
- Title: The origin and structure of the Monsoon Onset Vortex: Integrating Theory and predictability studies using the UFS
- Speaker: Shreyas Dhavale
- Abstract: In certain years, during the onset of the Indian Summer Monsoon, a synoptic scale vortex, known as the Monsoon onset vortex (MOV) forms in the Arabian Sea within the seasonal northward propagating region of precipitating convection. Many MOVs intensify into tropical cyclones and significantly impact the onset and advance of the Monsoon. This study focuses on the predictability of the MOV and the associated features of the Indian Summer Monsoon in the UFS S2S prototypes. Through some process-based diagnostics, we highlight the potential interactions between precipitation and monsoon dynamics, which still pose challenges for accurate sub-seasonal weather prediction in the monsoon regions.
- Presentation Slides
2023
- Title: The Spring Minimum in 2-meter Temperature Forecast Skill over North America
- Speaker: Melissa L. Breeden (a)(b), John R. Albers (b), Amy H. Butler (c), Matthew Newman (b)
- a. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
- b. NOAA/Physical Sciences Laboratory, Boulder, Colorado
- c. NOAA/Chemical Sciences Laboratory, Boulder, Colorado
- Abstract: This talk will explore the subseasonal prediction and predictability of 2-meter temperature (2mT) forecast skill over North America. In particular, a comparison of 2mT skill between spring and other seasons will be provided, revealing a clear skill minimum relative to winter and summer. Using a linear stochastic model – namely a linear inverse model (LIM) – it is found that while on average, subseasonal 2mT skill is low over many parts of North America, more skillful ‘forecasts of opportunity’ can be identified and are associated with optimal patterns that maximize 2mT growth over a period of 21 days. However, skill improvements during these forecasts of opportunity are minimal during spring compared to winter and summer, highlighting the lack of skill in spring. This skill minimum is consistent with theory and arises from a rapid decline in the predictable ‘signal’ from winter to spring, while unpredictable ‘noise’ declines to a lesser degree, driving down the signal-to-noise ratio and predictability. Finally, current applications of the LIM to subseasonal 2mT prediction will be provided.
- Presentation Slides
- Speaker: Melissa L. Breeden (a)(b), John R. Albers (b), Amy H. Butler (c), Matthew Newman (b)
- Title: Forecasts of T2m in the High-Resolution Coupled UFS Prototypes
- Speaker: Lydia Stefanova
- Abstract: This presentation will focus primarily on the CONUS T2m forecasts in the high-resolution prototypes of the coupled UFS (HR1 and HR2). Among the known shortcomings in the current operational GFSv16 are a wintertime cold bias and a summertime warm bias, particularly over the western CONUS. We will discuss the extent to which these characteristic biases are also present in HR1 and HR2, and some of the factors likely to ameliorate or exacerbate the problem.
- Presentation Slides
- Title: MJO Evaluation for UFS High Resolution Prototype
- Speaker: Wei Li SAIC/EMC/NCEP
- Abstract: In this presentation, the MJO, MJO components’ forecast skill, as well as the MJO intensity and phase biases in UFS high resolution prototype (HR1) is first reviewed. A case study is included to further explore the possible linkage between the Maritime Continent (MC) barrier and diabatic heating. The combined effect of the latent heat and radiative heat over the Indian Ocean and MC are considered to be associated with the circulation bias over the MC region.
- Presentation Slides
- Title: MJO-teleconnection in UFS prototype 5 and 6 in the troposphere: impact of vertical model levels
- Speaker: Cheng Zheng
- Abstract: This study evaluates the prediction of MJO teleconnections in two versions of the NOAA Unified Forecast System (UFS): prototype 5 (UFS5) and prototype 6 (UFS6). One of the differences between two prototypes with a potential impact on the prediction of MJO teleconnections is the number of vertical layers (127 in UFS6 vs. 64 in UFS5) along with the model top (80 km in UFS6 vs. 54 km in UFS5). With respect to ERA-Interim, the global teleconnections of the MJO to the Northern Hemisphere 500hPa geopotential height show similar biases over the North Atlantic and European sectors in both prototypes, whereas UFS6 has slightly smaller biases over the North Pacific region. Both prototypes capture the extratropical cyclone activity occurring in week 3-4 over the North Atlantic after the MJO phase 6-7 and over the North Pacific and North America after the MJO phase 4-5. Both prototypes forecast the sign, amplitude, and approximate locations of 2-meter temperature anomalies over the mid-to-high latitude continents occurring in weeks 3-4 after MJO phase 3 but fail to capture the sign reversal of anomalies over North America between weeks 3 and 4 after MJO phase 7. Overall, the two prototypes show similar performance in simulating the tropospheric basic state as well as prediction skill of the MJO and MJO teleconnections.
- Presentation Slides
Title: FV3 in a Nutshell
Speaker: Lucas Harris, GFDL
Abstract: In this presentation, I briefly describe the GFDL Finite-Volume Cubed-Sphere Dynamical Core. This dynamical core, called FV3, was designed specifically for frontier modeling challenges in weather prediction and climate science through a combination of accuracy, adaptability, robustness, and efficiency. My presentation will summarize the numerical algorithms in FV3 and how design choices were made to address these challenges, including the new frontiers of ultra-high resolution global modeling and global-nested modeling. Configurations most relevant to S2S prediction will be described. Successful applications from the worldwide FV3 community will be shown. I will close with some views regarding how to make the most of FV3's unique advantages and how to best foster a productive community.
Title: Towards More Accurate and Efficient Integration of the UFS
Speaker: Kevin Viner, NOAA/NWS/NCEP/EMC
Abstract: The current iteration of the UFS suffers from a handful of seemingly fixable deficiencies with respect to accuracy and efficiency. Firstly, all applications are running with an acoustic time step reduction of approximately 40% versus the analytic stability limit; this is largely to appease an unexpected restriction associated with the Lagrangian vertical coordinates. Secondly, the use of an a priori remapping time step (k_split) to maintain stability potentially adds unnecessary expense to the model; an adaptive method could reduce the cost of vertical remapping and tracer transport significantly. Lastly, introduction of a new physics-dynamics coupling could increase the accuracy of the model, especially for the large physics time steps used in global and S2S applications. Plans to remedy these issues will be discussed in detail.
Title: Modifying a Land Surface Model to Improve the Subseasonal Forecasting of Hydrological Variables
Randal Koster, GMAO, NASA/GSFC
Abstract: Past work has shown that a land surface model’s (LSM’s) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM’s mean hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and use them as targets for a specific LSM’s further development, focusing on improving the LSM’s performance in predicting hydrological variables (soil moisture and streamflow) at subseasonal leads. An offline hydrological forecast system is used as a testbed to evaluate potential LSM improvements. In essence, the LSM in this offline system is driven with bias-corrected meteorological forcings produced by a full subseasonal-to-seasonal (S2S) forecast system; soil moistures and streamflow estimates produced in the offline forecast simulations are then compared to in-situ observations. In our first experiments performed using this testbed, we find that moving the LSM’s implicit ET and runoff relationships toward the targeted relationships does indeed lead to improved hydrological predictions at the subseasonal lead, particularly (at this early point in our analysis) for soil moisture.
Title: UFS land capabilities and needs
Mike Barlage, NOAA/EMC
Title: Sea Ice: Model Development, Predictability, and Prediction
David Bailey, NCAR
Abstract: The NCAR Community Earth System Model (CESM) is in the process of developing version 3 for likely release in 2024. The sea ice component will be CICE6 (maintained and developed by the CICE Consortium) and the coupling infrastructure is based on ESMF/NUOPC. Note that we have been working with NOAA/EMC on unified caps for CICE6, MOM6, and WW3. I will discuss progress in CESM-CICE6 towards CESM3 including the new physics options we intend to include. I will also touch briefly on the efforts at NCAR in sea ice predictability and seasonal prediction.
Title: UFS sea ice information from a user's perspective
Robert Grumbine, NCEP/EMC, NOAA
Abstract: In this presentation, I'll turn around the usual consideration of a component in UFS. Rather than the viewpoint of a modeler, I'll take the viewpoint of a user of sea ice guidance on time scales from hours to a couple of years. Through the talk and discussion, we'll look to who the users are, what decisions they are making which rely on sea ice information, and what ice variables they need to know about to make those decisions. Conversely, what can we modelers do or provide to give users confidence about the guidance? Obviously that includes documenting that there are no absurd results (an issue with a different operational model), but also to document when, where, and why users can expect guidance to be better or worse than usual.
Title:Thompson Microphysics Updates in the Unified Forecast System
Ruiyu Sun1,2, Fanglin Yang2, Song-You Hong3.4, Jian-Wen Bao3, Jongil Han2, Eric Aligo5,2, Anning, Cheng1,2, Greg Thompson6, Jili Dong1,2 , Qingfu Liu2
1:Lynker/EMC/NCEP, 2: EMC/NCEP, 3: PSL/NOAA, 4: CIRES,5: SAIC, 6: JCSDA/UCAR
Abstract: The Thompson microphysics scheme was evaluated in the Unified Forecast System (UFS) for medium-range weather application in both atmosphere-only and fully coupled atmosphere-ocean-ice-wave system configurations. Initial tests based on the Global Forecast System (GFS) version 16 configuration showed that the Thompson microphysics scheme became unstable with a typical GFS time step. An inner-loop time-splitting approach and a new semi-Lagrangian sedimentation scheme for rain and graupel were implemented in the scheme to alleviate this numerical instability problem. To reduce biases of radiative fluxes at the surface and at the top of the atmosphere, the conversions from cloud ice to snow and from snow to graupel in the scheme were modified along with the ice falling velocity. A few other parameters related to the ice formation process were also adjusted to help improve radiative fluxes. Convective cloud condensate was included in the calculations of cloud cover and radiative transfer. Both coupled and uncoupled experiments were conducted to examine the impacts of these changes on global and regional forecast skills at different temporal and spatial scales.
Title: Improving Across-scale Predictive with Updated GFDL Microphysics
Linjiong Zhou and GFDL FV3 Team
Abstract: The GFDL microphysics has been widely adopted in weather, sub-seasonal-to-seasonal, and climate models for predictions from the regional convective scale to the global climate scale. Some significant upgrades have been made to enhance the physical consistency and capabilities of the GFDL microphysics in recent years. These upgrades include inlining the whole microphysics into the dynamical core, updating the thermodynamics equations to be consistent with the FV3 dynamics, introducing more realistic particle size distributions for the cloud water and cloud ice species, deriving the cloud droplet number concentration with aerosol data, and others. In this talk, I will present recent development activities of the GFDL microphysics and its prediction performance in the GFDL weather-to-seasonal prediction system, SHiELD. I will showcase how the GFDL microphysics has improved the prediction skill across a range of time and space scales, from regional convective events to global circulation.
Title: Subseasonal prediction skill from atmosphere, land, and ocean initial conditions
Anne (Sasha) Glanville
Abstract: Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is evidence that predictability on subseasonal timescales comes from a combination of atmosphere, land, and ocean initial conditions. Predictability from the land is often attributed to slowly varying changes in soil moisture and snow pack, while predictability from the ocean is attributed to sources such as the El Niño Southern Oscillation. Here we use a unique set of subseasonal reforecast experiments to quantify the respective roles of atmosphere, land, and ocean initial conditions on subseasonal prediction skill over land. The majority of prediction skill for global surface temperature in weeks 3-4 comes from the atmosphere, while ocean initial conditions become important after week 4. In this subseasonal prediction system, the land initial state does not contribute to surface temperature prediction skill in weeks 3-6. Indeed, climatological land conditions lead to higher skill, challenging our current understanding. However, land-atmosphere coupling is important in week 1. Results are similar over most land regions except South America, where ocean initialization is more important. Subseasonal precipitation prediction skill (weeks 3-6) comes primarily from the atmosphere initial condition, except for a few regions for which the ocean state becomes important.
Title: Global Data Assimilation Plans at NCEP - The Transition to JEDI and Coupled DA
Sergey Frovlov
Title: Representation of the stratosphere and stratosphere-troposphere coupling in subseasonal-to-seasonal forecasting systems
Zachary D. Lawrence (CIRES / NOAA PSL)
Abstract:
Title: Tropical Origins of UFS Weeks 2–4 Forecast Errors during the Northern Hemisphere Cool Season
Juliana Dias, Stefan Tulich, Maria Gehne and George Kiladis
Abstract: UFS remote impacts of tropical forecast errors are analyzed using a set of 30-day reforecast experiments, focused on the Northern Hemisphere (NH) cool season (November–March). The approach is to nudge the model toward reanalyses in the tropics and then measure the change in skill at higher latitudes as a function of lead time. In agreement with previous analogous studies, results show that midlatitude predictions tend to be improved in association with reducing tropical forecast errors during weeks 2–4, particularly over the North Pacific and western North America, where gains in subseasonal precipitation anomaly pattern correlations are substantial. To relate this result to predictable modes of variability in the tropics, we focus on a Madden–Julian oscillation (MJO) conditional skill analysis that indicates that improved MJO predictions at a given lead week could improve the subsequent week NH precipitation prediction.
Title: Diagnostics of Tropical Variability for Numerical Weather Forecasts
Maria Gehne, Brandon Wolding, Juliana Dias, and George Kiladis
Abstract: We introduce and apply diagnostics from a recently developed tropical variability diagnostics toolbox, where we focus on several versions of the subseasonal-seasonal (S2S) component of the UFS: coupled prototypes 5, 7 and 8. For comparison we also include forecasts from the ECMWF S2S database. The diagnostics include space-time coherence spectra to identify preferred scales of coupling between circulation and precipitation, pattern correlations of Hovmoeller diagrams to assess model skill in zonal propagation of precipitating features, CCEW skill assessment, plus a diagnostic aimed at evaluating moisture - convection coupling in the tropics. The comparison between the UFS prototypes highlights the utility of these physically based diagnostics in the pursuit of better understanding of NWP model performance in the tropics, and during model development.
2022
Title: The UFS coupled ensemble prototype experiments
Bing Fu, Yuejian Zhu, Philip Pegion, Hong Guan, Bo Yang, Eric Sinsky, Xianwu Xue, Jiayi Peng, Fanglin Yang and Avichal Mehra
NOAA / NWS / NCEP / EMC / CPC
Abstract: NOAA/NCEP is planning to implement a fully coupled UFS global forecast system (GFS) and global ensemble forecast system (GEFS) in 2024. In preparation for this implementation plan, a series of UFS coupled model prototypes have been developed during the past years, and the tests and evaluations of each UFS coupled model prototype have been carried out and presented in the UFS weekly meeting following the development of the prototypes 1-8. In alignment with the development of the UFS coupled model prototypes, three UFS coupled ensemble prototypes (EP1, EP2, EP3) have also been developed based on UFS coupled model prototypes 5, 7 and 8 (P5,P7,P8) respectively. These ensemble prototypes focus on quantifying forecast uncertainties through tuning and merging existing stochastic schemes (SKEB, SPPT) for atmosphere, and introducing initial ocean perturbations and ocean stochastic schemes. This presentation aims to evaluate and compare the results from these coupled ensemble prototypes experiments as well as the applications of stochastic physics schemes, configurations and tunings/adjustments in these coupled ensemble prototypes for weather and subseasonal forecast.
Title: MJO simulation and predictability studies with CFSv2: roles of convection parameterization and oceanic feedback
Jieshun Zhu, Wanqiu Wang and Arun Kumar
Climate Prediction Center, NOAA/NWS/NCE
Abstract: In this talk, we will present a series of experiments with NCEP CFSv2 about MJO simulations and predictability, with a particular interest on impacts of convection parameterization and oceanic feedback. On the simulation part, it is found that air-sea coupling establishes consistent ocean surface conditions in the eastern maritime continent (MC) seas, and is necessary for simulating MJO propagation across the MC. However, coupling alone is not sufficient to maintain a realistic MJO propagation across the MC, and favorable SST conditions must develop in the eastern MC seas and western Pacific, for which both zonal and meridional wind anomalies must be correctly simulated with proper convection parameterization to produce realistic surface latent heat flux anomalies. On the predictability part, experiments indicate that the convection scheme alone can have substantial influence on the estimate of MJO predictability with estimates differing by as much as 15 days. The shorter predictability with one convection scheme is found mainly caused by too weak an MJO signal. In terms of oceanic feedbacks, it is found that SST presents significant influences on MJO predictability (extends predictability by ~25 days), but the role of SSS seems marginal. The finding about the SSS role, however, might be related to barrier layer simulation biases in CFSv2.
Title:Impact of Aerosol-Cloud Interactions on Seasonal Prediction
Donifan Barahona, Zhao Li and Andrea Molod Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Abstract: Since version 2, the NASA Goddard Earth Observing System Subseasonal to Seasonal prediction system, GEOS-S2S, implements comprehensive representations of aerosol-radiation (ARI) and aerosol-cloud (ACI) interactions. These include aerosol effects on radiation, stratiform and convective cloud evolution, and ice cloud formation. In this talk we will show results from extended reforecasts where ACI and ARI are removed from GEOS-S2S as a mean to understand their effect on the forecast skill. The inclusion of aerosol effects in GEOS-S2S had significant effects on surface temperature, cloud fraction, precipitation and aerosol optical depth. Aerosol indirect effects act to reduce bias in temperature, but they may be too strong leading to biases in the opposite direction, particularly in the Northern Hemisphere. Preliminary analysis shows mostly positive impacts on the forecast skill, although degradation in some places. It is likely that aerosol concentrations are regulated by the feedback between aerosol scavenging and droplet activation. Hence ACI and ARI may be required for their correct representation in forecasting systems.
Title: UFS-Aerosol, the Unified Forecast System’s global aerosol component
Greg Frost (NOAA OAR CSL), on behalf of the UFS R2O Atmospheric Composition team
Abstract: This presentation will report on a successful collaborative effort by NOAA OAR, NWS, NESDIS, and their partners to improve the global representation of aerosols and their impacts on meteorology in the Unified Forecast System (UFS). UFS-Aerosol is the aerosol component of the UFS 6-way coupled system developed as a prototype for global subseasonal prediction in the Global Ensemble Forecast System version 13 (GEFSv13). UFS-Aerosol development, supported in part by the UFS Research-to-Operations (R2O) Project, builds on the expertise and approaches employed in NOAA’s currently operational GEFSv12-Aerosol. Advances in UFS-Aerosol include improved descriptions of aerosol processes, realistic aerosol spatial distributions and temporal variability in forecasts out to 4 weeks, and treatment of the impact of aerosols on radiation. Increased collaboration among UFS teams working on the global coupled system, such as those focusing on aerosols, physics and data assimilation, is key for progress to date and in future plans. The development of UFS-Aerosol, evaluations of its global aerosol predictions, initial assessments of the impacts of its aerosol-radiation interactions on meteorology, and plans for future work under the R2O Project will be discussed.
Title: Development and Evaluations of Coupled UFS Prototypes for Future Global, Ensemble and Seasonal Forecasts at NOAA/NCEP
Dr. Lydia Stefanova, NOAA/NWS/NCEP/EMC
Abstract: NOAA’s Unified Forecast System (UFS) is a community-based modeling system developed to provide a common framework for all NCEP Production Suite operational forecast models. One of the UFS targets is a coupled model for global predictions of weather to seasonal time scales. In its final configuration, the coupled UFS will consist of: (1) FV3 dynamical core and CCPP atmospheric physics package, (2) Noah MP land model, (3) MOM6 ocean model, (4) CICE6 sea ice model, (5) WAVEWATCH III wave model, and (6) GOCART aerosol model.
With this goal as a target, a sequence of eight prototypes (P1–P8) of the coupled UFS have been configured to date, each building upon the preceding one. Each prototype is evaluated in a common hindcasst framework, and the results are used to inform further developments and refinement of the system’s components and coupling, in addition to pre-planned upgrades.
The first five prototypes (P1–P5) focused primarily on system engineering. Major physics changes were introduced in recent prototypes (P6–P8). The latest prototype (P8) of the coupled UFS, which is still in testing, is fully coupled for the first five components listed above, and one-way coupled for the aerosol component; implementation of full coupling of the latter is expected in the future.
Title: Desired improvements for the UFS S2S
Dr. Wanqiu Wang, Climate Prediction Center, NOAA/NWS
Abstract:Operational subseasonal to seasonal (S2S) predictions at the National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) rely on forecasts from dynamical models and statistical methods. The current dynamical models used for CPC’s S2S predictions include the Climate Forecast System (CFS) and the Global Ensemble Forecast System version 12 (GEFSv12). In this presentation, we summarize the applications of the CFS and GEFS for CPC’s S2S forecast products. In particular, we highlight the representation of the processes in the CFS that affect the forecast of the Madden Julian Oscillation (MJO) and El Nino Southern Oscillation (ENSO). Improved representation of these processes in the Unified Forecast System for subseasonal to seasonal predictions (UFS S2S) is highly desired. We will also discuss deficiencies in the Climate Forecast System Reanalysis (CFSR) which is used to initialize the CFS. These deficiencies adversely affect the performance of its S2S forecasts and it is important they are minimized in the initialization for UFS S2S.