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Sort by: Title Principal Investigator (s) Task Force Year Initially Funded
Year Initially Funded: 2016
Task Force:
S2S Prediction Task Force
Final Report:

A categorical assessment of forecast skill, uncertainty and biases in extended-range ensemble forecast of stratospheric regime changes

View abstract
"Relevance to NOAA’s MAPP competition and long-term climate goal: The proposed work is highly relevant to the MAPP completion: Research to Advance Prediction of Subseaonal to Seasonal Phenomena (ID: 2542967) as it examines the ability of operational NWP systems to represent underlying predictability sources, both physical and dynamical, that influence the subseasonal phenomena of stratospheric regime changes. During the winter season troposphere-stratosphere coupling provides a dynamic mechanism for the stratosphere to influence the troposphere on subseasonal timescales. Stratosphere-troposphere coupling can manifest itself as a stratospheric regime change or, in extreme cases, a sudden stratospheric warming (SSW). On subseasonal timescales, SSWs have been linked to extreme weather and climate, such as cold air outbreaks and negative Arctic Oscillation (AO), which can impact the U.S., Europe and Asia.

When troposphere-stratosphere coupling is skillfully resolved in a forecast, it can provide valuable information to public and private sector forecasters and end users in industry. However, there is a gap in our understanding of the skill, uncertainty and biases in forecasts of stratospheric regime changes that is currently a source of confusion for decision makers. In addressing NOAA’s long term climate goal (e.g., NGSP section I.A.i), this research aims to close the gap in our understanding such that end-users of subseasonal forecast data will be better informed and have higher confidence in planning and decision-making.

The increase in our understanding of the two-way coupling between the troposphere and stratosphere has led many operational centers to raise the top of their NWP models to more fully resolve the stratosphere. Raising the top in a model was the first step in the goal to improve forecast skill beyond the medium range. The next steps in reaching this goal are to understand when stratospheric forecasts of wave coupling events are skillful and to increase our understanding of the sources of uncertainty in the forecast of troposphere-stratosphere wave coupling events. This research addresses these next steps by conducting research to assess stratospheric forecast skill and assess sources of uncertainty in operational NWP models during wave coupling events that produce a stratospheric regime change.

The proposed work explicitly examines how model physics, model horizontal resolution, model vertical resolution, and model top level impact the forecast skill and uncertainty of the physical (i.e., diabatic processes) and dynamical (i.e., wave activity) forcing for stratospheric regime changes at several forecast lead times. For the analysis, the physical forcing is represented by metrics that quantify the diabatic processes in the mid- and upper troposphere and the dynamical forcing is represented by metrics that quantify the troposphere-stratosphere wave coupling. Composite forecasts from the ensemble members that produce the top and bottom quartile of metrics in a forecast will serve as a means to investigate forecast biases. The model biases associated with the physical and dynamical metrics will be quantified in terms of their manifestations in important flow features in the troposphere and stratosphere. Biases in the location and amplitude of the tropospheric precursor blocking as well as biases in the location, shape and strength of the stratospheric vortex best-fit ellipse will be calculated for each composite group. The main scientific objective of this work is to evaluate whether a categorical assessment of errors and uncertainty associated with physical forcing mechanisms lead to an improved understanding of sources of biases in the stratospheric forecasts initialized prior to a stratospheric regime changes. The results of the proposed work will be available online for immediate use by the forecasting community as they become available."

Principal Investigator (s): Andrea Lang (University at Albany, SUNY)

Co-PI (s):
Year Initially Funded: 2016
Task Force:
S2S Prediction Task Force
Final Report:

Variability of Rossby Wave Breaking and its Impacts on the Large-scale Circulation and Extreme Weathers: Implications for S2S Prediction and Predictability

View abstract
"Rossby wave breaking (RWB) is characterized by large-scale, irreversible overturning of potential vorticity (PV) on isentropic surfaces. The eddy-mean interaction involved in RWB is an important process for the maintenance and variability of the midlatitude jet, and mixing associated with RWB plays an important role in moisture and momentum transport between the tropics and extratropics. In particular, extratropical PV intrusion modulates the moisture distribution in the subtropical dry zone, which affects the infrared energy loss and is an important factor in the global energy budget.

RWB is also closely related to extreme weathers, such as blocking and atmospheric rivers. Our recent study revealed a strong relationship between RWB and Atlantic tropical cyclones (TC). Anomalously frequent RWB enhances the equatorward intrusion of cold, dry extratropical air and leads to a significant reduction in precipitable water over the tropical/subtropical Atlantic and an increase in vertical wind shear, both hindering TC formation and intensification. The correlation of Atlantic hurricane counts with a basinwide RWB frequency index is comparable to the correlation with the Atlantic Main Development Region SST, and stronger than the correlation with the ENSO.

In this project, we propose to i) examine the variability and impacts of RWB on the subseasonal to seasonal (S2S) time scales using reanalysis and observational data; ii) assess the representation of RWB in global prediction systems and investigate model deficiencies using the WWRP/THORPEX/WCRP S2S prediction project database; and iii) investigate the implications of the findings for the S2S prediction and predictability, especially for the prediction and predictability of Atlantic tropical cyclones.

Studies on S2S prediction have primarily focused on tropical forcing and processes (such as the MJO and tropical SST) in the past. This project complements those efforts through its unique perspective in emphasizing the extratropical impacts on tropical circulation and extreme weathers and stressing the link between midlatitude transient eddies and the S2S prediction and predictability. The ultimate goal of the project is to improve the prediction skill of global models on the S2S time scales, and it is well aligned with the focus of the NOAA MAPP Competition 2 to “improve the understanding of predictability” and “advance the prediction of phenomena occurring on S2S time scales”. It is also highly relevant to the NOAA’s long-term climate goal to improve the scientific understanding of the changing climate system and its impacts. This project team consists of scientists from research institutes and operational centers. Their combined expertise in atmospheric dynamics, global modeling, and operational forecasting together forms the particular strength of this project, and will also facilitate transition from research to operations and help to bridge the gap between numerical weather forecasting and short-term climate prediction."

Principal Investigator (s): Zhuo Wang (University of Illinois at Urbana-Champaign)

Co-PI (s): Melinda Peng (NRL), Stan Benjamin (NOAA/ESRL)
Year Initially Funded: 2016
Task Force:
S2S Prediction Task Force
Final Report:

Role of stratospheric processes in predicting ENSO-NAO connections on subseasonal time scale

View abstract
"There is increasing evidence that stratospheric processes and stratospheric-tropospheric coupling contribute to an enhanced predictive skill of tropospheric phenomena, including El Niño/Southern Oscillation-North Atlantic Oscillation (ENSO-NAO) connections on seasonal time scale. The role of the stratosphere on the predictive skill on the subseasonal time scale has not been systematically explored, and the available data and model studies are not conducive to understanding the responsible processes. This joint proposal between CIRES-University of Colorado/NOAA-ESRL-Physical Sciences Division and CGD-NCAR aims to improve our understanding of the role of the stratosphere on the predictability of the NAO and related extremes and to quantify to what extend NAO predictability can be improved by including a well-resolved stratosphere in a subseasonal modeling framework.

This proposed project has three main objectives:
1. To improve our understanding of the role of the stratosphere on the predictability of the NAO and related extremes on subseasonal time scale in the context of ENSO-NAO connections,
2. To quantify changes in predictive skill of a model with and without a well-resolved
stratosphere,
3. To provide the scientific community with a thoroughly tested and evaluated stratospheric
resolving subseasonal to seasonal (S2S) forecast system and dataset based on the Community Earth System Model (CESM).

We hypothesize that the skill of predicting the NAO phase and related climate extremes on a subseasonal time scale can be advanced during periods of extreme stratospheric vortex events, and the knowledge of the phase of the tropical stratospheric Quasi-biennial Oscillation (QBO) specifically when also taking into account the phase of ENSO. This project will utilize the default 30-level, as well as the newly developed 46-level version of CESM in subseasonal forecasting and reforecasting mode. The detailed comparison of reforecasts performed with two models with the same tropospheric physics and model resolution but a poorly and well-resolved stratosphere, will allow for the examination of the processes responsible for potentially enhanced predictive skill. Predictive skill of the 46-level CESM subseasonal to seasonal forecasting system (46LCESM-S2S) will be compared to the predictive skill of other S2S systems from the international modeling community participating in the Subseasonal to Seasonal Prediction Project, a joint research program between the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP). All datasets generated as part of this project will follow the S2S protocol and will be provided for public use. The proposed project directly addresses MAPP competition 2 on research to advance prediction of phenomena on S2S time scale in the context of troposphere-stratosphere coupling and NAO predictability. This project addresses NOAA’s long-term goal: “Weather-Ready Nation Society is prepared for and responds to weather-related events” by carrying out research on and providing tools for the prediction of extreme events on the subseasonal time scale."

Principal Investigator (s): Judith Perlwitz (CIRES/University of Colorado and NOAA/ESRL/PSD)

Co-PI (s): Jadwiga Richter (NCAR), Lantao Sun (CU/CIRES and NOAA/ESRL/PSD), Julio Bacmeister (NCAR), Joe Tribbia (NCAR)
Year Initially Funded: 2016
Task Force:
S2S Prediction Task Force
Final Report:

Investigation of the Causes for Systematic Breakdown of Numerical Subseasonal Forecasts

View abstract
"A recent analysis of the THORPEX Interactive Grand Ensemble (TIGGE) showed that while the operational global ensemble forecast systems of the world’s leading numerical weather prediction centers were efficient, in general, in capturing the uncertainty dynamics associated with the high-frequency (synoptic scale) transients, they all predicted the slowly varying large-scale component of the flow with a systematic error whose magnitude increased with the forecast time. Such a systematic error poses a major obstacle to extending skillful forecasting into the subseasonal to seasonal (S2S) forecast range. The fact that the different ensemble forecast systems, which use different models and are also generated differently, all fail in the same general fashion, suggests that there may be one or more important dynamical processes that are not accounted for in the current forecast models. Our goal is to investigate the possibility that ocean mesoscale eddy-atmosphere (OME-A) feedback from the ocean to the atmosphere is such a process. This goal is driven by the hypothesis that oceanic mesoscale eddies, which can persist for months in the western boundary current regimes, may play an important role in S2S predictability through modulating the midlatitude storm tracks by inducing mesoscale SST variability.

We will carry out both deterministic and ensemble forecast experiments with a global atmospheric model (the NCAR CAM model at 1/4° resolution) coupled to a simple thermodynamic ocean model. The focus will be on representing the OME-A feedback (and the uncertainty in the OME-A feedback) from oceanic fronts and eddies in the mid-latitude storm track regions. The effect of the parameterization of the OME-A feedback on the synoptic scale waves in the global model simulations will be validated against the results of previous high (9 km atmospheric and 3 km oceanic) resolution process studies with a regional coupled model. We will analyze the results of the forecast experiments by both detailed computations of the energy conversion processes and ensemble-based diagnostics.

The results of the proposed research project are likely to improve the understanding of predictability of phenomena occurring at the S2S time scales. The advances made are expected to lead to improved prediction and better understanding of such S2S process as the transitions between the two phases of NAO and a blocked flow regime."

Principal Investigator (s): Istvan Szunyogh (Texas A&M University)

Co-PI (s):
Year Initially Funded: 2016
Task Force:
Final Report:

Operational Transition of Soil Moisture and Snow Data Assimilation in the North American Land Data Assimilation System (NLDAS)

View abstract

Principal Investigator (s): Christa Peters-Lidard (NASA Goddard)

Co-PI (s): Michael Ek (NOAA/EMC), David Mocko (NASA/Goddard), Sujay Kumar (NASA/Goddard), Youlong Xia (NOAA/EMC), Jiarui Dong (NOAA/EMC)
Year Initially Funded: 2016
Task Force:
Final Report:

An NCEP Global Ensemble Forecast System for Monthly Forecasts

View abstract

Principal Investigator (s): Yuejian Zhu (NOAA/EMC)

Co-PI (s): Malaquías Peña (NOAA/EMC), Wei Li (NOAA/EMC), Xiaqiong Zhou (NOAA/EMC), Hong Guan (NOAA/EMC), Dingchen Hou (NOAA/EMC), Richard Wobus (NOAA/EMC), Xu Li (NOAA/EMC), Qin Zhang (NOAA/CPC), Dan Collins (NOAA/CPC), Jon Gottschalck (NOAA/CPC)
Year Initially Funded: 2016
Task Force:
Final Report:

Development of a Monitoring and Prediction System for Flash Droughts over the United States

View abstract

Principal Investigator (s): Dennis Lettenmaier (University of California, Los Angeles)

Co-PI (s): Kingtse Mo (NOAA/CPC)
Year Initially Funded: 2016
Task Force:
Final Report:

Estimating the Subseasonal Forecast Skill in the NASA GEOS-5 System with a Focus on the Madden Julian Oscillation and the Land Surface Memory Feedback Processes

View abstract

Principal Investigator (s): Deepthi Achuthavarier (NASA Goddard)

Co-PI (s): Randal Koster (NASA Goddard), Jelena Marshak (NASA Goddard), Dan Collins (NOAA/CPC), Jon Gottschalck (NOAA/CPC)
Year Initially Funded: 2016
Task Force:
Final Report:

Sub-Seasonal Prediction with CCSM4

View abstract

Principal Investigator (s): Ben Kirtman (University of Miami)

Co-PI (s): Kathy Pegion (GMU/COLA), Rong Fu (University of Texas at Austin), Jon Gottschalk (NOAA/CPC), Dan Collins (NOAA/CPC)
Year Initially Funded: 2016
Task Force:
Final Report:

NMME sub-seasonal to seasonal climate products for hydrology and water management

View abstract

Principal Investigator (s): Andy Wood (NCAR)

Co-PI (s): Rajagopalan Balaji (University of Colorado Boulder), Peitao Peng (NOAA/CPC), Yu Zhang (NOAA/NWC), Kevin Werner (NOAA/RCS), Subhrendu Gangopadhyay (Bureau of Reclamation), Jeffery Arnold (US Army Corps)
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The Modeling, Analysis, Predictions, and Projections (MAPP) Program's mission is to enhance the Nation's capability to understand and predict natural variability and changes in Earth's climate system. The MAPP Program supports development of advanced climate modeling technologies to improve simulation of climate variability, prediction of future climate variations from weeks to decades, and projection of long-term future climate conditions. To achieve its mission, the MAPP Program supports research focused on the coupling, integration, and application of Earth system models and analyses across NOAA, among partner agencies, and with the external research community.

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