Funded Projects

Enter Search Value:
- without any prefix or suffix to find all records where a column contains the value you enter, e.g. Net
- with | prefix to find all records where a column starts with the value you enter, e.g. |Network
- with | suffix to find all records where a column ends with the value you enter, e.g. Network|
- with | prefix and suffix to find all records containing the value you enter exactly, e.g. |Network|

Sort by: Title | Principal Investigator | Program | Year Initially Funded

The impact of meridional variations in cloud albedo on tropical climatology, and biases, in Earth system models

Principal Investigator (s) Alexey Fedorov, Yale University

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: NA14OAR4310277 | View Publications on Google Scholar

Abstract: A salient feature of the tropical Pacific is the pronounced east-west gradient in sea surface temperature along the equator. This temperature gradient is coupled to the atmospheric zonal circulation and oceanic thermocline tilt. Together they define the Warm pool, Cold tongue, Walker circulation Complex (WCWC). Asymmetry in the SST and precipitation fields about the equator sets the position of the Intertropical Convergence Zone (ITCZ). This is a proposal to study the effect of meridional variation in cloud albedo across the entire Pacific basin on this tropical climatological state in Earth system models.

Coupled model simulations of the tropical Pacific, while improved over the past decades, still show significant biases. A cold bias within the cold tongue region, a cold tongue that extends far west into the warm pool, and the double-ITCZ problem remain persistent issues in climate models. The mean east-west temperature gradient along the equator in the CMIP5 models varies between 3 and 8 degrees C, compared to nearly 6 degrees C in the observations. Developing a comprehensive understanding of what determines this temperature gradient and related characteristics of the fully coupled ocean-atmosphere system is critical for understanding tropical climatology and potential biases in climate models. Often, this question is treated as a local problem in the equatorial band – improvements are sought by tuning local parameters affecting the properties of deep convection in the warm pool or the amount of shortwave radiation reaching the eastern Pacific. However, the strength of the cold tongue is ultimately controlled by the temperature of waters subducted in the extra-tropics and transported to the equator by the ocean subtropical cells (STC). Consequently to understand tropical biases one needs to treat this coupled problem in a broader geographical context and consider latitudinal variations in the main dynamical factors.

Our preliminary analysis indicates that the meridional gradient in cloud albedo is one of these key factors. A close relationship exists across the pre-industrial CMIP5 simulations and our preliminary numerical experiments that connects the mean east-west gradient in upper-ocean temperatures and the contrast in cloud albedo between the extra-tropical and tropical Pacific. For example, when extra-tropical cloud albedo is higher than observed, or tropical cloud albedo is too low, the east-west temperature gradient is stronger than observed. Thus, we propose that in coupled climate models the zonal SST gradient and the related characteristics of the tropical ocean-atmosphere system (e.g. zonal winds and the thermocline tilt) are largely controlled by the meridional gradient in cloud albedo between the equator and the extra-tropics. Further, we propose that it is the inter-hemispheric albedo contrast that controls the position of the ITCZ. To investigate these problems we will conduct (i) sensitivity experiments with CESM, in which we systematically modify cloud properties affecting cloud albedo, (ii) a theoretical analysis of the coupled system with cloud feedbacks included, and (iii) an analysis of CMIP5 models focused on the effects of latitudinal variations in cloud albedo on the tropical climate.

Relevance to long-term NOAA goals and current solicitation: The overarching goal of this study is to understand the fundamental physical mechanisms that control tropical climatology and model biases. This objective is directly relevant to the current solicitation and longer-term NOAA goals, since simulating tropical climate correctly is critical for climate prediction on a variety of timescales from seasonal to interannual, to decadal and longer. Funding from this grant will support cross-disciplinary training of a postdoctoral associate at Yale, Dr. Natalie Burls.

A Global View of Tropical Pacific Biases and Their Effect on Connections Between the Southern Hemisphere and the Equatorial Pacific Climate

Principal Investigator (s) Amy Clement, University of Miami, RSMAS

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: NA14OAR4310275 | View Publications on Google Scholar

Abstract: Previous studies have shown that extra-tropical influences from the North Pacific can impact the tropical Pacific climate, offering some additional degree of predictability of El Nino/Southern Oscillation (ENSO). More recent work has also shown that similar physical mechanisms operate in the Southern hemisphere, and further suggest that the connection between the southern extra-tropics and the equatorial climate is even more direct than the north. The reason is that southeasterly trade winds cross the equator and allow signals to propagate from the south deep into the tropics, while in the northern hemisphere signals are essentially ‘blocked’ by the convergence of winds in the northern ITCZ. Simulating this connection from the southern hemisphere is problematic in coupled GCMS in which an erroneous southern ITCZ can potentially block extra-tropical signals originating in the south. Thus, in this project we will test the hypothesis:

That Pacific ITCZ biases in climate models weaken the southern hemisphere influence on the equator and diminish a potential source of ENSO predictability.

We will test this hypothesis using a collection of climate model simulations that offer multiple realizations of the mean state biases in the Pacific ITCZ. We will perform diagnostic studies using CMIP5 model simulations to test the model-dependence of the mean state and its influence on variability propagating from the southern hemisphere to the equator. We will perform a large number of experiments with climate models in which the ITCZ position is altered in two ways: First by externally imposed perturbations to the energy budget of the model, and second by altering the strength of regional radiative feedbacks using a novel approach that we have developed in prior work (funded by NOAA). This dual method approach of altering ITCZ builds upon recent work that suggests that in addition to local processes in the Pacific that can lead to biases in the ITCZ, the mean ITCZ position is also influenced by processes outside the tropics that alter the radiative balance of the planet. This experimental approach has the advantage of being able to (1) test which regions of the globe are key for the simulation of the Pacific ITCZ, and (2) examine mean state interactions with variability in a consistent framework. Further we will use a hierarchy of models including aqua planet models, AGCM-slab ocean mixed layer models, and fully coupled models, which will allow us to identify the fundamental mechanisms which control the position of the ITCZ and impact Pacific climate variability. The ultimate goal of this work is to design an experimental framework in which we can test how potential sources of predictability, particularly from the southern hemisphere, are affected by Pacific ITCZ biases.

This work will contribute to the goals of the ‘ESS - Climate Variability and Predictability (CVP): Improving Understanding of Tropical Pacific’ by identifying processes and regions outside the tropical Pacific that exert a remote influence on the mean climate. This will help to provide a more complete and global context for understanding tropical Pacific biases, and suggest novel ways in which models can be developed to reducing this external influence on these biases. A unique aspect of this work is that we are focused on additional (an perhaps unexploited) sources of predictability in the Pacific climate system, namely signals or precursors from the southern hemisphere. By testing the central hypothesis or this project, our work will enhance NOAA’s core capabilities in both ‘Modeling and understanding’ and in ‘Predictions’ of the Pacific climate system.

Understanding Tropical Pacific Biases in Climate Simulations and Initialized Predictions

Principal Investigator (s) Andrew Wittenberg, NOAA/GFDL; Gabriel Vecchi, NOAA/GFDL; Tom Delworth, NOAA/GFDL; Yan Xue, NCEP/CPC; Arun Kumar, NCEP/CPC;

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: GC14-250a | View Publications on Google Scholar

Abstract: We propose a collaborative study between GFDL and NCEP, to advance understanding, simulation, and forecasting of tropical Pacific climate and its variability. Motivated by the central role that the tropical Pacific plays in climate variability worldwide -- in particular via the El Niño / Southern Oscillation (ENSO) -- there is an urgent need to advance mechanistic understanding of the tropical Pacific climatology and its impacts on climate variability, and to improve the coupled general circulation models (CGCMs) upon which society relies for seasonal-to-interannual (SI) forecasts and decadal-to-centennial predictions and projections. A unique strength of this proposal is close coordination between two of NOAA’s premier institutions for simulation, assimilation, and prediction of tropical Pacific climate and ENSO. In particular, a critical aspect of the proposed work is the development of common metrics, and a coordinated design and analysis of focused simulation and forecast experiments leveraging next generation models. This coordination will facilitate assessment of the robustness of the model results and underlying mechanisms, to accelerate improvements in NOAA’s SI simulation and prediction capabilities. Our goals are to (1) diagnose the spatiotemporal structure of tropical Pacific climatological biases in GFDL’s and NCEP’s coupled simulations, reanalysis systems, and forecasts; (2) identify similarities and differences among GFDL’s and NCEP’s model biases, and understand how differences can be linked to model parameterizations, assimilation methods, and observational inputs; (3) understand the processes which seed and amplify tropical Pacific biases; (4) assess how these biases affect the simulation and prediction of climate fluctuations; and (5) develop methods to mitigate these biases and their impacts on forecast skill. We will use our findings to evaluate existing hypotheses for the emergence of tropical Pacific biases, and to assess the applicability of our results to the broader set of community models and forecasts, including those available from the CMIP5 and NMME projects.

Relevance: The proposed work is highly relevant to the NOAA CPO. We seek to improve scientific understanding and prediction of the climate system, by evaluating and advancing methodologies used for simulations and forecasts. We directly address several objectives of NOAA’s Next Generation Strategic Plan (NGSP), including (1) Improved scientific understanding of the changing climate system and its impacts, by elucidating the causes and effects of simulation biases, and advancing climate modeling, predictions, and projections; (2) An integrated environmental modeling system, by advancing fundamental climate research and transitioning it toward NOAA’s production of seasonal forecasts, by coordinating within NOAA to enhance the accuracy of global models and predictions, and by evaluating and optimizing NOAA’s investments in observation and monitoring through the use of models; and (4) A climate-literate public that understands its vulnerabilities to climate, by elucidating the strengths and limitations of climate information affected by simulation biases. Relevance to the Competition: This proposal directly addresses the ESS CVP solicitation. The analysis and multimodel experimentation will focus on understanding tropical Pacific biases in two of NOAA’s leading coupled GCMs, which are widely used for climate simulation, reanalysis, and predictions. The work will leverage nearly all of the methods suggested in the proposal call, including advanced physical metrics, reduced-model experiments, and short-term forecasts, to diagnose the sources and amplifiers of model biases.

A Nudging and Ensemble Forecasting Approach to Identify and Correct Tropical Pacific Bias-Producing Processes in CESM

Principal Investigator (s) Aneesh Subramanian, Regents of the University of California; Art Miller, Regents of the University of California

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: NA14OAR4310276 | View Publications on Google Scholar

Abstract: Current short-term tropical climate forecasts (e.g, of the Madden Julian Oscillation (MJO) and of El Niño/Southern Oscillation (ENSO) events) experience both a systematic error (climate drift) that results in sustained biases of the model tropical climatology and an error in representing the space-time scales of the transients (e.g., phase speed errors, etc.) We propose to identify the physical mechanisms that lead to the seasonal biases in the tropical Pacific by isolating the parameters and parameterizations that influence the development of biases in short-term climate forecasts. Our overarching scientific objective is to identify, explain, and correct the climate biases in the Pacific ocean that occur in the Community Earth System Model (CESM). We are currently using the Community Atmospheric Model (CAM3) in MJO forecast experiments and tests of convective parameterization improvements. We propose to extend these MJO forecast studies to include (a) the fully coupled CESM system, and (b) ENSO timescale forecasts.

We plan to study the spatiotemporal structures of bias development in CESM forecasts, launched from numerous initial states and during which random ENSO and MJO events occur, to determine the relative importance of poor mean-state representation versus the integrated impacts of the transient flows. This bias development will be studied as a function of season to account for significant changes in the background state of the coupled oceanatmosphere system in the tropical Pacific. We will also seek to ascribe these effects to wellknown physical processes for the specific climate modes of variability. We will test the sensitivity of the bias development to changes in coupled model resolution and model parameter selection. We will also implement nudging experiments (towards observations) to pinpoint where the worst parts of the biases develop apart from the nudged variables.

We expect this research to result in identification of the physical processes that lead to the mean biases in the model system and an improvement in parameterizations used in CESM and CAM for forecasts of the climate-scale processes in the tropical Pacific.

This proposal contributes to the CVP component of the NOAA ESS Program by attempting to improve our understanding of the processes contributing to tropical Pacific biases in global climate models (CESM, in this case). Specifically, our work involves (i) short-term forecast experiments, from weeks to a year, to isolate the time scales of bias development and the responsible processes, (ii) development of metrics for coupled GCMs that help to elucidate the main processes contributing to biases, (iii) atmosphere-only and ocean-only models to isolate the sources and amplifiers of biases, and (iv) intercomparison of model parameterizations within CESM. Our overall research will thereby contribute significantly to NOAA’s Next Generation Strategic Plan by improving our scientific understanding of the climate system that will result in better identifying potential climate impacts.

Collaborative Research: Regional and Global views of CGCM biases

Principal Investigator (s) Roberto Mechoso, Regents of the University of California, Los Angeles; Benjamin Kirtman, University of Miami - RSMAS; Paquita Zuidema, University of Miami - RSMAS; Paquita Zuidema, University of Miami - RSMAS;

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: NA14OAR4310278 OR NA14OAR4310279 | View Publications on Google Scholar

Abstract: Scientists at the University of California Los Angeles (UCLA) and Rosenstiel School of Marine & Atmospheric Science, University of Miami (RSMAS) propose to perform collaborative research in support of the NOAA’s Earth System Science (ESS) Program. The work proposed aims to improve the understanding of tropical Pacific processes, climatology, and model biases. Therefore, it is relevant to the Climate Variability and Predictability (CVP) competition.

The present proposal focuses on the tropical Pacific and the fundamental subject of error generation and evolution in the simulation of the regional climate by coupled atmosphere-ocean general circulation models (CGCMs). The overall hypothesis is that addressing the problem of CGCM biases in the simulation of the tropical Pacific climate requires both regional and global approaches. The working hypotheses are (1) Evaluating fast error growth before longer-time scale feedbacks develop will contribute significantly to identify parameterization deficiencies, (2) A better understanding of the local processes that determine the sea surface temperature (SST) in the region will be a major step towards the solution of tropical errors, and (3) Investigating the links between different biases, particularly those that are affected by remote and local processes, will lead to important insight into parameterization deficiencies. In view of these hypotheses we have designed a three-pronged research strategy based on the analysis of (1) the four-dimensional (space-time) structure of the error fields, (2) the asymptotic (climate) limit of the error fields, and (3) the contribution to the errors from locations that may be far away from the tropics. It will be argued that parameterizations have to be improved, but they may not be just those that refer to key processes in a particular region.

Specifically, it is proposed to examine the initial error growth in initialized seasonal climate forecasts from the US National Multi-Model Ensemble (NMME) phase II data set. An novel set of flux override experiments will explore the contribution of net surface shortwave radiation and wind stress errors to the fast SST error growth by first imposing observed fluxes and then allowing the atmosphere and ocean to recouple and redevelop their SST bias. Further experimentation will contrast flux override results from low- and high-resolution NCAR CESM runs to assess the contribution of their differing thermocline representations. To examine the processes that determine the SST under the stratus clouds in the SEP (and SEA) we will use a very high-resolution regional model (ROMS6) in upwelling regions running both uncoupled and embedded in a full CGCM. To examine the links between CGCM errors far away from the tropics and those in the tropics we will investigate why not all CGCMs that have severe warm SST biases in the tropical Pacific experience the double ITCZ problem.

BROADER IMPACTS: The CGCM biases in the tropical Pacific greatly compromise the models ability to predict climate variability and change. We expect this project to contribute significantly to eliminate these errors by providing new insights on parameterization shortcomings and thus suggesting future research on model improvements. In shorter time scales, decreasing the biases will improve the simulation and prediction of climate variability including El Niño.

Tropical Pacific moist dynamical processes, sensitivity and biases

Principal Investigator (s) David Neelin, Regents of the University of California, Los Angeles

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: NA14OAR4310274 | View Publications on Google Scholar

Abstract: Moist dynamical processes, originating in the atmosphere but involving ocean-atmosphere feedbacks, are among the leading effects requiring better constraints to address tropical Pacific biases and many applications to Pacific variability. We propose to bring together two themes developed under prior work: fast-process diagnostics from observations and parameter perturbation runs aimed at assessing sensitivity of moist processes to parameterized physics. Specifically, we will have available from prior work a set of runs with the Community Earth System Model (CESM1; atmospheric component Community Atmosphere Model 5) that perturb the convective physics in both uncoupled and coupled modes. These include nonstandard, high time-resolution output to aid assessment of fast-process diagnostics and sufficient length to establish statistical significance in quantities that might elude short-term forecast experiments. Data from a related set of perturbed physics runs from the NOAA Geophysical Fluid Dynamics Laboratory High Resolution Atmospheric Model (HIRAM) model will also be available via existing collaborations. In both models, initial results suggest high parameter sensitivity in the tropical Pacific, for instance, precipitation differences exceeding ± 3 mm/day across large parts of the basin for convection-related parameters varied across their feasible range. The proposed work addresses some of the challenges in making use of such information: (i) Sensitivity does not necessarily equate to improvement. We will quantify contributions to this across multiple variables and parameters, including assessing trade-offs where some metrics improve while others degrade for a given parameter change. (ii) The impacts on the climatology involve large-scale dynamical ocean-atmosphere feedbacks even in experiments where the parameterization change is known. We will aim to disentangle such effects using hypothesis-driven investigation informed by simpler models. Examples of this include assessment of convective instability as a function of parameter and model state using a column version of the CAM, and convective margins diagnostics. (iii) Reduction of biases should not simply be a tuning exercise based on improvement in the climatology. Rather, we will seek cases where current fast-process diagnostics can provide independent constraints on the parameter range or parameterization form. For example, diagnostics for convective onset as a function of temperature and water vapor will be used to constrain the entrainment range. Processes exhibiting high sensitivity in the Pacific will be used to target the development of further diagnostics, and parallels with common error modes in the Coupled Model Intercomparison Project phase 5 will be examined.

The proposed work, for the competition Improved Understanding of Tropical Pacific Processes, Biases, and Climatology (Earth System Science Competition 3, Climate Variability and Predictability), addresses the following aspects of the competition goals: intercomparison of model parameterizations, including convection and clouds, and reduced and conceptual modeling coordinated with analysis of full coupled model experiments and development of metrics for atmospheric relationships that constrain moist dynamical processes key to understanding and reducing biases. It addresses elements of the NOAA long-term climate goal as described in NOAA’s Next-Generation Strategic Plan in the core capability of “Understanding and modeling”, supporting the “ Predictions and projections” capability. Furthermore, the information from the observational analysis will help to design and refine the diagnostics that can be obtained from observing systems. The proposed work is relevant to societal challenges identified in the NGSP of climate impacts in water resources, changes in extremes of weather and climate, and provides current climate baselines for model projections for mitigating climate change impacts.

Excessive Cold-tongue and Weak ENSO Asymmetry: Are These Two Tropical Biases Linked?

Principal Investigator (s) De-Zheng Sun, ESRL-PSD; Richard Neale ,(unfunded) NCAR

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: GC14-244 | View Publications on Google Scholar

Abstract: Among the biases in the tropical Pacific that are common in the climate models, two stand out. One is the excessive cold-tongue in the mean state---the pool of the cold water that is normally in the eastern tropical Pacific extends too far to the west. The other is the underestimate of the asymmetry of El Nino-Southern Oscillation—the fact that El Nino and La Nina are more or less a mirror image of each other in the models while they are not so in the observations. The importance of the tropical Pacific sea surface temperature in affecting climate variability on a range of time-scales over the continental U.S and the world at large demands our attention to the causes and removal of these two common biases in climate models.

The proposal attempts to delineate the relationship between these two common biases in the stateof- the-art climate models and isolate the root causes of them. Toward this objective, we will conduct focused data analysis as well as numerical experiments with climate models of varying complexity. The hypothesis the proposed project sets out to test is that these two tropical biases are linked. More specifically, we suspect that an excessive cold-tongue in the mean climatological state renders the two phases of ENSO more symmetric, possibly through its impact on the stability of the ENSO system, while a more symmetric ENSO results in less nonlinear heating to the cold-tongue which in turn contributes to the development of an excessive coldtongue. Moreover, we suspect that these two biases may be the symptoms of a single structural inadequacy in the models: a weak dynamical coupling between the atmosphere and ocean.

To test our hypothesis and pin down the physical processes responsible for the aforementioned biases, we will

(1) Capitalize on the greater range of variability among the CMIP5 models than CMIP3 models in their simulations of the tropical Pacific climate to examine the relationship between the zonal extent of the cold-tongue and ENSO asymmetry in the models.

(2) Conduct coupled experiments with two models of intermediate complexity to delineate the mechanisms by which an excessive cold-tongue affect the asymmetry of ENSO.

(3) Conduct forced ocean GCM experiments with surface forcing from models with different level of biases as well as from observations to quantify the feedback from ENSO events.

(4) Evaluate the precipitation-wind-SST relationship in the corresponding AMIP runs in conjunction with the coupled runs to fully evaluate the coupling strength as well as to diagnose causes for the initial error

(5) Conduct experiments with a fully coupled GCM (the NCAR Community Climate System Model-version 4) as well as experiments with its atmospheric and oceanic components.

The proposed project utilizes data analysis and models of varying complexity to achieve a deeper understanding of the causes of two prominent biases in the tropical Pacific and thereby helps to improve the simulations and predictions of the tropical Pacific climate—a key source for climate variability and predictability in the earth’s climate system-- by our state-of-the-art climate models. Thus, the proposed project is highly relevant to the objectives and priorities of the Earth System Science Program of NOAA.

Process Level Investigation of the Role of Convection and Cloud Parameterization in Tropical Pacific Bias in GFDL Next Generation Global Climate Models

Principal Investigator (s) Ming Zhao, NOAA/GFDL; Chris Golaz, NOAA/GFDL

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: GC14-252 | View Publications on Google Scholar

Abstract: Despite their climatic importance, simulations of tropical Pacific mean climate and variability in state-of-the-art global coupled ocean-atmosphere climate models remains unsatisfactory. During the past few decades, tremendous community efforts have been devoted to understand common problems, especially those associated with models analyzed by the IPCC assessment reports. New theories, hypotheses, and analysis approaches have been proposed. We are at a point when some major progress could happen. At GFDL, recent model development efforts have led to a range of prototype configurations for the next generation GFDL climate model AM4/CM4. These configurations exhibit large differences in tropical Pacific biases, such as the equatorial Pacific cold/dry bias, the double ITCZ, the overly strong trades, and the biases related to MJO. The models include configurations based on previous generation AM3 and HIRAM models, as well as configurations using a new double-plume convection (DPC) scheme under development. Preliminary coupled simulations suggest that DPC produces significant improvements in the tropical Pacific mean climate, ENSO, and MJO in coupled simulations. However, we do not understand at this time the mechanisms by which changes in the convection scheme lead to the improvements, since these improvements result from complex interactions and feedback among convection, clouds, radiation, atmospheric circulation, boundary layer processes, and the underlying ocean processes. Without an in-depth understanding of the mechanisms, new improvement cannot be generalized and transferred to other models.

Given the abundance of theories on tropical Pacific biases in the literature and given that we have various prototype configurations of AM4/CM4, we propose a research project to bring these together in order to strengthen our understanding of the mechanisms by which parameterization details lead to model improvements. We believe that the next generation GFDL climate models could significantly benefit from an integration of the existing theories, hypothesis, analysis approach, as well as new observational data in the area of convection-cloudair- sea interactions into the model development routine. Experiments and analyses will be designed and conducted to connect our model results to theories and conceptual models. Results will be compared with previous analyses to assess their generality for the broader GCM modeling community.

Toward Improving ENSO Modeling

Principal Investigator (s) Tao Zhang, ESRL/PSD; Martin Hoerling,ESRL/PSD; Judith Perlwitz, ESRL/PSD;

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: GC14-251 | View Publications on Google Scholar

Abstract: A fundamental attribute of tropical Pacific variability is the asymmetry in equatorial SST anomalies between the extreme phases of ENSO. Such ENSO asymmetry has implications for U.S. seasonal forecasting for which ENSO is the primary skill source. Also, given ENSO’s global impacts, ensuring accurate simulation of ENSO asymmetry in climate models is important for increasing reliability in projections of regional climate change.

The proposed research attempts to understand ENSO in climate models by focusing on ENSO asymmetry and seeking causes for the inability of most state-of-the–art coupled models to simulate ENSO asymmetry. We hypothesize that ENSO asymmetry is fundamentally linked to the climatological tropical winds, and that model biases in the former might be linked to biases in the latter through wind impacts on mean SST states.

We propose to conduct model data analysis and perform reduced model experiments (atmosphere-only, and ocean-only, regional, NCAR Pacific basin model) to address the following questions related to our hypothesis:

(1) What is the relative role of the biases in mean winds and biases in their interannual variability in simulating ENSO asymmetry?

(2) In which regions (equatorial, Pacific basin, etc.) would an improvement in mean winds and their interannual variability be most effective in simulating ENSO asymmetry?

We will utilize the latest version of NCAR’s CESM1 and the atmospheric component CAM5 for which long coupled runs and AMIP runs are available. We will also analyze CCSM4 and the corresponding CAM4 model experiments to understand the origin of changes in ENSO asymmetry between CCSM4 and CESM1.

Answers to these questions will guide the development of a new metric for the representation of ENSO asymmetry in coupled models that can better elucidate the main processes contributing to biases in ENSO features. This proposal will thus directly relate to the 2014 goal of ESS/CVP to conduct reduced-model experiments that can better isolate the sources and amplifiers of biases in climate models, and thus improve predictions and projections. It is also relevant to NOAA’s long-term climate goal—an improved scientific understanding of the changing climate system and its impact, which requires to support understanding and modeling core capabilities.

Towards Understanding Pacific ITCZ Biases in Global Atmosphere Models

Principal Investigator (s) Stefan Tulich, ESRL/PSD & CIRES; Christopher Fairall, ESRL/PSD & CIRES; Andrey Grachev, ESRL/PSD & CIRES; Juliana Dias, ESRL/PSD & CIRES

Year Initially Funded: 2014

Program (s): Climate Variability and Predictability

Competition: Improved Understanding of Tropical Pacific Processes, Biases, and Climatology
Award Number: GC14-246 | View Publications on Google Scholar

Abstract: Tropical biases remain a significant problem in global atmosphere models, even at horizontal grid spacings of 5-­‐10 km. A well-­‐known example is the “double-­‐ITCZ” bias in the Pacific, which has been plaguing both coupled and uncoupled models for more than several decades now. Because this bias has been found even in global models that can be considered near “cloud-­‐resolving”, it would seem that other deficiencies than those involving convection schemes are also an important part of the problem. This idea is supported by our own current idealized simulations of the ITCZ, which are showing surprisingly strong sensitivity to the treatment of surface fluxes under light-­‐ wind conditions. In particular, schemes that predict weaker surface latent heat fluxes (LH) at low wind speeds tend to favor a double-­‐ITCZ pattern in rainfall, while a much more realistic pattern is favored using schemes that predict the opposite. Similarly, in real-­‐world reforecast simulations of the MJO, we are finding that model performance is substantially degraded as the amplitude of the “gustiness” effect on LH is made smaller. Here, we propose to extend these findings to a set of more focused reforecast simulations of the Pacific ITCZ using two different global models: 1) the NCEP Global Forecast System (GFS) and 2) the global Weather Research and Forecast model with a “super-­‐parameterization” for convection (SP-­‐WRF). The goal will be to characterize the lead-­‐time dependence of each model’s climatological ITCZ bias to changes in various aspects of the PBL/surface-­‐layer scheme, including the treatment of gustiness. Our hypothesis is that the amplitude of the double-­‐ITCZ bias will become smaller as the amplitude of the “gustiness” effect on LH is made larger, owing to enhanced availability of moisture on the equatorward flank of the ITCZ, where wind speeds are typically weaker. To allow direct statistical comparisons of the model output against NOAA R/V observations of LH, reforecasts will be generated for each of the past major field campaigns: EPIC, DYNAMO, TOGA-­‐COARE, KWAJEX, JASMINE, and Nauru99. Also, as a further test of our hypothesis, we will explore the statistical relationship between LH and wind speed in the set of global models that have contributed data to the CMIP5 archive. On the observational side of the problem, we will revisit the limited set of NOAA LH observations collected under weak wind speeds, to understand why direct (covariance) estimates are systematically smaller than indirect (inertial-­‐dissipation) estimates. Ultimately, the goal will be to develop an improved physically based treatment of gustiness effects in global models.

Page  3 of 11                   First     1  2  [3]  4  5  6  7  8  9  10       Last  


Americans’ health, security and economic wellbeing are tied to climate and weather. Every day, we see communities grappling with environmental challenges due to unusual or extreme events related to climate and weather. 


1315 East-West Highway Suite 100
Silver Spring, MD 20910