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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:

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:

Improving subseasonal to seasonal forecast skill of North American precipitation and surface air temperature using multi-model strategy

View abstract
"This proposal responds to the 2016 solicitation for CPO’s Modeling, Analysis, Prediction and Projection (MAPP) program Competition 2: “Research to Advance Prediction of Subseasonal to Seasonal Phenomena.” The proposed project focuses on some of MAPP’s primary objectives, namely, “improving methodologies for global to regional-scale analysis, predictions, and projections” and “developing integrated assessment and prediction capabilities relevant to decision makers based on climate analyses, predictions, and projections.”

A large number of forecasts from a suite of models are routinely provided by the Subseasonal to Seasonal (S2S) Prediction Project and the North American Multi-Model Ensemble (NMME) Project. To develop a reliable and timely climate product from these datasets, we propose a new methodology to assess an individual model’s forecast skill, generate statistical weights based on the skill of member model forecasts of slowly-varying surface states, and use aforementioned weights to produce an optimized single forecast. We will compare this methodology to traditional multi-model combination techniques. The new methodology has unique advantages: a) It provides an ideal framework for regional analyses and prediction; b) It allows the combined atmospheric forecast to rely more on models with superior forecast skill of surface anomalies, which are the main drivers of the S2S forecast skill; c) Calculations of forecast skill and weights for each model are highly flexible, and the methodology has many potential applications. The weight of each model member can be calculated from the latest evaluation of the model’s forecast performance and may evolve over time.

Preliminary results show that the new methodology outperforms individual models and can increase the one-month lead forecast skill of surface air temperature by 50% over the simple multi-model average across much of the area of focus. Even though the forecast skill improvement of precipitation (P) and surface air temperature (T2m) over North America is our primary target, the effects are expected to reach all forecast variables over the globe. We propose to identify regions where there is significant forecast skill of North American P and T2m and diagnose the dominant factors influencing such skill. We seek to understand how these factors contribute to the forecast skill of P and T2m, especially the role of land surface processes in achieving S2S forecast skill, through crafted numerical experiments with the Climate Forecast System (CFS). The project will also explore the potential to improve S2S forecast skill by improving the quality of land surface initial states in CFS and examine impacts of land initialization on S2S forecast skill. The overall goal of the proposal is to enhance the Nation’s capability to predict variability on S2S time scales. By performing our analysis with the NMME and S2S forecast datasets and adapting it to operational settings, this proposal directly contributes to the NOAA Next-Generation Strategic Plan objectives of “an improved scientific understanding of the changing climate system and its impacts” and “mitigation and adaptation choices supported by sustained, reliable, and timely climate services.”"

Principal Investigator (s): Zhichang Guo (GMU/COLA)

Co-PI (s): Paul Dirmeyer (GMU/COLA)
Year Initially Funded: 2011
Task Force:
CMIP5 Task Force
Final Report:

Nonlinearity of the Tropical Convection and the Asymmetry of the El Niño Southern Oscillation

View abstract

The asymmetry of ENSO is a measure of its nonlinearity, and may be a key ingredient in climate variability on the decadal and longer time-scales, particularly for the Pacific sector. Understanding its causes and ensuring accurate simulation of it by climate models is a key issue facing climate modelers who strive to make reliable forecast/projections of climate changes over the coming decades.

The proposed research attempts to address this issue by analyzing existing model runs as well as through conducting specially designed experiments. Our working hypothesis— is that the nonlinearity in deep convection is an important cause of the asymmetry in ENSO. Specifically, an increase of the nonlinearity of tropical convection will lead to an increase in the asymmetry of zonal wind stress and therefore an increase in the asymmetry of subsurface signal, favoring an increase of ENSO asymmetry.

We plan to analyze the coupled runs as well as the corresponding AMIP runs from the latest NCAR and GFDL models, including the diagnosis of the NCAR model runs with different convection schemes and with different model resolutions and the GFDL model runs with different convection schemes. We not only examine ENSO asymmetry in the surface fields such as SST, surface heat flux, and precipitation but also its subsurface manifestation. To understand how the changed wind stress associated with changed convection scheme will affect the subsurface asymmetry and thereby the SST asymmetry, we will perform forced experiments with the NCAR Pacific basin model, the POP global ocean models (the ocean component of CCSM4/CESM1) and the MOM4 (the ocean component of the GFDL coupled model) using the winds from the AMIP runs of NCAR and GFDL models. We will compare the results from the forced runs driven by observed winds. In addition, the forced runs will be perturbed by warm anomaly, cold anomaly, and the residual of wind stress from observations and model simulations. Experiments especially designed to understand the relative importance of the nonlinearity from the atmosphere and the nonlinearity from the ocean dynamics will also be conducted.

To further validate the effect of changes in convection schemes and model resolutions on the simulation of ENSO asymmetry we will find from NCAR and GFDL models, we also plan to examine the coupled runs as well as the corresponding AMIP runs from the ongoing IPCC AR5 data sets.

The purpose of proposed research is to provide a better understanding of how the simulation of ENSO—the asymmetry between its two phases in particular—in global climate models is affected by increases in model resolution and changes in convection scheme, in support of the development of next-generation climate models involving both higher resolution and improved physical representations.

Principal Investigator (s): Zhang, Tao (NOAA/ESRL)

Co-PI (s): Sun, De-Zheng (NOAA/ESRL)
Year Initially Funded: 2011
Task Force:
Final Report:

Evaluate Recently Developed Reanalysis Projects

View abstract

This proposal is submitted to NOAA Climate Project Office Modeling, Analysis, Prediction and Projection (MAPP) Program in Response to Funding Opportunity for FY2011. In this project, we will make efforts to contribute to the MAPP FY2011 theme of Evaluate Recently Developed Reanalysis Projects. The overall goal of this proposed project is to provide quantitative information that may guide us to properly use diabatic heating profiles from the recent reanalysis products: MERRA, CFS-R, and ERA-Interim. We propose to (i) quantify similarities and differences between Q1 (total diabatic heating estimated as a residual of heat budget) and QT (direct output of total diabatic heating) from the reanalyses, (ii) compare Q1 (and QT if they are equivalent) from the reanalyses to Q1 estimated using sounding data from selected field campaign, and (iii) define our current knowledge of diabatic heating profiles and its uncertainties by quantifying the agreement and discrepancies between diabatic heating profiles from the reanalyses. The research will be conducted at CIMAS/RSMAS, University of Miami, addressing CIMAS Theme 1: Climate Variability (Task 3).


Principal Investigator (s): Zhang, Chidong (RSMAS/University of Miami)

Co-PI (s):
Year Initially Funded: 2011
Task Force:
Drought Task Force
Final Report:

Dual assimilation of microwave and thermal-infrared satellite observations of soil moisture into NLDAS for improved drought monitoring

View abstract

We propose to produce an operational data assimilation (DA) system for optimal integration of thermal infrared (TIR) and microwave (MV) soil moisture (SM) information and near real-time green vegetation fraction (GVF) into the Noah land-surface model component of the National Land Data Assimilation System (NLDAS). NLDAS produces hydrologic products (e.g. soil moisture, evapotranspiration, and runoff) used by NCEP for operational drought monitoring, but these products are sensitive to model input errors in soil texture (affecting infiltration rates) and prescribed precipitation rates. These types of model errors can be compensated for by periodically updating SM state variables in LSMs through assimilation of remotely sensed SM information. The work proposed here will build on a project currently funded under the Climate Test Bed Program entitled “A GOES Thermal-Based Drought Early Warning Index for NIDIS”, which is developing an operational TIR SM index (Evaporative Stress Index; ESI) based on maps of the ratio of actual-to-potential ET (fPET) generated with the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm.

The assembled research team has demonstrated that diagnostic information about SM and evapotranspiration (ET) from MW and TIR remote sensing can significantly reduce SM drifts in LSMs such as Noah. The two retrievals have been shown to be quite complementary: TIR provides relatively high spatial resolution (down to 100 m) and low temporal resolution (due to cloud cover) retrievals over a wide range of GVF, while MW provides relatively low spatial (25 to 60 km) and high temporal resolution (can retrieve through cloud cover), but only over areas with low GVF. Furthermore, MW retrievals are sensitive to SM only in the first few centimeters of the soil profile, while in vegetated areas TIR provides information about SM conditions integrated over the full rootzone, reflected in the observed canopy temperature. The added value of TIR over MW alone is most significant in areas of moderate to dense vegetation cover where MW retrievals have very little sensitivity to SM at any depth.

Building on this work, the proposed study will develop an optimal strategy for assimilating TIR and MW SM signals into the Noah model over the NLDAS domain using the Land Information System (LIS) developed by NASA. Additionally, near real-time green vegetation fraction (GVF) data products generated in NESDIS will be ingested, replacing climatological fields currently used in NLDAS, which are not always representative of actual conditions on the ground, especially in areas suffering from drought. We propose to use relative TIR / MW skill maps developed by Co-I Hain to spatiotemporally modify error characteristics needed by the EnKF as a function of GVF.

Assimilation results will be validated in comparison with in-situ SM observations and using a data denial validation methodology. Outputs from the operational DA system will include near real-time (updated each night) maps of surface and root-zone SM, ET and runoff. Anomalies computed from these improved hydrologic products will be compared to ALEXI ESI and standard drought metrics, including the operational NLDAS output. Output will be distributed in real-time to NCEP-CPC for use in the North America Drought Briefing and to the National Drought Mitigation Center in support of the U.S. Drought Monitor.

Principal Investigator (s): Zhan, Xiwu (NOAA/NESDIS)

Co-PI (s): Anderson, Martha (USDA-ARS); Hain, Chris (NESDIS); Ek, Michael (NOAA/EMC); Svoboda, Mark (NDMC)
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: 2013
Task Force:
Climate Reanalysis Task Force
Final Report:

Evaluating CFSR Air-Sea Heat, Freshwater, and Momentum Fluxes in the context of the Global Energy and Freshwater Budgets

View abstract
This proposed research aims at providing a comprehensive assessment of the partially coupled Climate Forecast System Reanalysis (CFSR) by NOAA NCEP in representing air-sea heat, freshwater, and momentum fluxes in the context of the global energy and water budgets. The proposed research addresses the MAPP call on improving our ability to “better quantify uncertainties in reanalysis data including the impacts of data and model error”, and addresses the climate objectives of NOAA’s Next Generation Strategic Plan (NGSP) with particular focus on providing quantitative assessments of current state of the climate system.

The CFSR is the first and only reanalysis that incorporates a coupled atmosphere-oceanland climate system with an interactive sea-ice component, and the one that has the finest spatial resolution (~0.5°) ever produced by any reanalysis. Evidence has clearly pointed to the advantages and strengths of the finer-resolution coupled CFSR reanalysis in characterizing airsea fluxes at regional and global scales, but biases/errors in the CFSR flux components at various temporal scales have also been reported. The biases/errors appear to have significant impact on the estimates of the energy and water budgets over the global oceans. Currently, the CFSR produces a global energy imbalance of 15 Wm-2, which is about 10 Wm-2 higher than the estimates from the earlier NCEP reanalyses. We recognize that balancing the global energy/water budgets has long been a challenging issue, with global energy budgets differing considerably, from 2 to 30 Wm-2, when computed using reanalyzed, ship-, and satellite-based flux products. However, the global energy/water budgets are central to the understanding of climate variability and climate changes produced by the reanalyses. A good knowledge of the impact of biases/errors in surface flux components on the global budget estimates will be highly beneficial to not only the users of CFSR products but also the developers for the next-generation Earth System reanalysis. Therefore, this proposed assessment study will analyze the biases/errors in the CFSR surface fluxes in the context of the global energy/water budget and will also compare the CFSR with the earlier and the latest reanalyses as value-added evaluation.

The proposed approaches include: (i) in situ validation, in which a database consisting of more than 130 flux buoys is used as ground truth for identifying and quantifying biases/errors in flux products; (ii) spectral analysis, in which ship- and satellite-based global flux analyses are used as reference to evaluate and characterize the regional and global spectral structures of flux products, and (iii) dynamical diagnosis, in which dynamic constraints (such as energy and freshwater budgets in an enclosed volume) are used to test the physical consistency of flux products with ocean state variables (temperature and salinity).

The primary objectives of the proposed research are to (i) identify the strength and weakness of the CFSR surface flux components by comparison with in situ flux measurement, satellite-based analyses and other reanalyses products and understand the sources of biases, (ii) examine the effect of spatial resolution in improving the accuracy and spatial structure of CFSR fluxes on regional and global scales, (iii) investigate the use of physical constraints together with ocean state variables to diagnose and understand the uncertainties in CFSR air-sea fluxes.

The significance of the proposed research is in the potential to (i) establish a baseline that can be used to help determine the scope and extent of the CFSR surface fluxes to be applied; (ii) improve our understanding of the state-of-estimation of air-sea fluxes in latest reanalyses; (iii) obtain new insights on the cause of the discrepancies in global energy/freshwater budget estimates based on air-sea fluxes; and (iv) obtain practical recommendations for future improvement of air-sea flux estimation in reanalyses.

Principal Investigator (s): Yu, Lisan (Woods Hole Oceanographic Institution)

Co-PI (s): Yan Xue (NOAA/NCEP/CPC)
Year Initially Funded: 2011
Task Force:
CMIP5 Task Force
Final Report:

Understanding the Emerging Central-Pacific ENSO and Its Impacts on North American Climate

View abstract

It is being increasingly recognized that there are two distinct types of El Niño-Southern Oscillation (ENSO): an Eastern-Pacific (EP) type that has its sea surface temperature (SST) anomalies centered near the South America coast and a Central-Pacific (CP) type that has its SST anomalies centered near the international dateline. IPCC AR4 simulations project that the CP type may become the prevailing type of ENSO in a future warmer world, which is consistent with the fact that CP ENSO events have occurred more frequently in the past three decades than in earlier decades. There is a need to better prepare for the emergence of this mode of tropical climate variability, and to revise existing modeling and prediction strategies developed primarily with the conventional EP type of ENSO in mind. One source of uncertainty in the prediction and projection of North American climate may have to do with whether or not modern climate models can produce both types of ENSO, simulate the alternation between them, and capture their different impacts. This project proposes data analyses and model experiments to better understand the evolution of the CP ENSO and its regional impacts on the Pacific-North America sector and to identify the key atmospheric and oceanic processes for differing the impacts of the CP and EP ENSO’s on North American climate.

Specifically, this project will make use of the existing Coupled Model Intercomparison Project Phase 3 (CMIP3) simulations and the upcoming CMIP5 simulations to understand the relative importance of the extratropical forcing and tropical coupling in controlling the evolution of the CP ENSO and to identify the concurrent and extended impacts of CP and EP ENSOs on North American Climate. The different impacts produced by the EP and CP ENSOs will be translated into uncertainties in the prediction and projection of the North American climate variability and will be assessed. Partial-coupling and forced experiments will then be conducted to further understand how the ocean and atmosphere in the Pacific-North American sector respond to CP and EP ENSO forcing, how the responses are projected onto the Pacific-North American (PNA) and North Pacific Oscillation (NPO) modes of variability, and how they are manifested as variations in the Aleutian Low, Subtropical High, and tropospheric jestreams. Special attention will be given to understanding the ENSO-induced SST anomalies in the North Pacific, which are hypothesized to extend ENSO’s influence on North America after the demise of the ENSO events. The possibility of using statistical models, such as the Markov model, to perform CP ENSO predictions using both extratropical and tropical information will also be explored.

This project is expected to quantify the sensitivity of North American climate to the alternation of the ENSO type and to make suggestions on how it can be better captured in modern climate models by laying out the specific atmospheric, oceanic, and coupled processes that establish the sensitivity. New metrics that gauge not only tropical but also extratropical atmospheric and ocean fields will also be developed to help further improve model simulations of the two types of ENSO. These efforts are relevant to (a) “support the development of next-generation global climate models” and (b) “evaluate uncertainties in regional-scale climate predictions and projections”, both of which are priority areas specified by the FY2011 MAPP program for the research theme of Advance in Regional-Scale Climate Predictions and Projections.

Principal Investigator (s): Yu, Jin-Yi (UC Irvine)

Co-PI (s):
Year Initially Funded: 2015
Task Force:
Model Diagnostics Task Force
Final Report:

Evaluation and Diagnosis of the Atlantic Meridional Overturning Circulation 3D Structure in Climate Models

View abstract
"The Atlantic Meridional Overturning Circulation (AMOC), with its large heat and freshwater transports and interaction with the atmosphere and sea-ice, plays a fundamental role in establishing the mean state and the temporal variability of the Earth’s climate system. Existing studies have shown a wide spread of AMOC state in the current state-of-art climate models, CIMIP5, and hence a better understanding of the driving mechanisms is urgently needed. The current analysis, however, typically quantifies the AMOC as one maximum volume transport stream function at certain latitudes. This overly simplified AMOC index, while important, is insufficient for formulating a comprehensive picture of the AMOC structure across the entire Atlantic and characterizing its fundamental role in the climate system, such as transport of heat/freshwater and water mass transformation.

Recognizing this problem, here we propose a collaborative effort to conduct more comprehensive analyses on the structure of the AMOC in climate models. The analyze are built on observational results and high-resolution ocean simulations, and include a) AMOC transport on temperature-salinity plane and density spaces across trans-Atlantic sections at different latitudes, b) water mass transportation due to surface buoyancy forcing as well as diapycnal/isoptcnal mixing in the ocean interior, and c) diapycnal velocity. The overall goals are 1) to derive a better and more comprehensive diagnosis for evaluating the AMOC representation, including time mean structure and temporal variability, in current climate models, and 2) to identify and understand the key physical process or mechanisms that lead to the wide spread of the AMOC state among the CMIP5 models as well as the AMOC variability in individual models.

This project is a direct contribution to the “Process-oriented evaluation of climate and earth system models and derived projections” in the area A: metric for climate and earth model development. The proposed analysis will help a) evaluate the AMOC structure in current earth system models, compared to observations and high-resolution models; and b) isolate the model biases on AMOC structure due to contributions from air-sea interaction and/or oceanic advection and mixing process. Botha re critical for the ongoing efforts to improve our scientific understanding of the changing climate system and its impact, and to enhance our capability to predict climate variability and changes in climate and earth system models."

Principal Investigator (s): Xu, Xiaobiao (Florida State University)

Co-PI (s): Eric Chassignet (FSU), Molly Baringer (NOAA/AOML), Shenfu Dong (NOAA/AOML)
Year Initially Funded: 2014
Task Force:
Final Report:

Bridging the gap in NOAA's extended and long range prediction systems through the development of new forecast products for weeks 3 and 4

View abstract
We propose to develop new operational temperature and precipitation forecast products over North America for lead times of 3 and 4 weeks that would bridge the gap between NCEP/CPC’s 8-14 day and monthly outlooks and complete a seamless prediction system that links NOAA’s intraseasonal and seasonal forecast products. At the foundation of this proposal, recent work by the PIs demonstrates the feasibility of a simple statistical forecast model that combines information from the Madden-Julian Oscillation (MJO), El Niño-Southern Oscillation (ENSO), and linear temperature trend to generate skillful North American wintertime temperature forecasts in weeks 3 and 4. To build upon this effort, the purpose of this project is (1) to transition this statistical model into an operational week 3 and week 4 temperature and precipitation outlook for all seasons; (2) to determine the feasibility of providing information on extremes at these lead times; (3) to calibrate CFSv2 forecasts with the use of archived reforecasts to evaluate the performance of products for weeks 3 and 4 based on the CFSv2; and (4) to explore extending the model calibration approach to the US National Multi-Model Ensemble (NMME).

Principal Investigator (s): Xie, Shang-Ping (University of California, San Diego)

Co-PI (s): Nat Johnson (University of Hawaii), Steven Feldstein (Penn State University), Michelle L'Heureux (NOAA/CPC), Stephen Baxter (NOAA/CPC)
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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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