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Sort by: Title Principal Investigator (s) Task Force Year Initially Funded
Year Initially Funded: 2012
Task Force:
Climate Prediction Task Force
Final Report:

Variability and Predictability of the Atlantic Warm Pool and Its Impacts on Extreme Events in North America

View abstract

Our current/previous NOAA/CPO-funded research has pointed out the importance of the Atlantic Warm Pool (AWP) for summer climate and extreme events in the Western Hemisphere. AWP variability occurs on seasonal, interannual, multidecadal, and secular (global warming) timescales, with large AWPs being almost three times larger than small ones. The effect of the AWP is to weaken the North Atlantic subtropical high (NASH) and strengthen the summer continental low over the North American monsoon region. A large AWP also weakens the southerly Great Plains low-level jet, which results in reduced northward moisture transport from the AWP to the central U. S. and thus decreases the summer rainfall over the central United States. A large AWP increases the number of Atlantic hurricanes by reducing vertical wind shear and increasing the moist static instability of the troposphere, and influences the hurricane steering flow changes that become unfavorable for hurricanes to make landfall in the United States. Our research also suggests that the AWP serves as a link between the Atlantic Multidecadal Oscillation (AMO) and climate and hurricane activity. Despite its importance, almost of all stateof-the-art coupled models exhibit serious biases in the AWP region, which limit the seasonal prediction of AWP-related climate and extreme events.

We propose to continue our investigation of the AWP using fully coupled climate models. Two specific areas of proposed work are (1) diagnosing the CMIP5 outputs to assess model biases near the AWP region and to understand their skill in simulating the mechanisms and climate impacts of AWP variability, and (2) performing coupled model experiments using CESM1 (also called CCSM4) and analyzing the Climate Forecast System version 2 (CFSv2) reforecasts to assess and improve predictability of the AWP and its impacts on climate and extreme events such as hurricanes, flood and drought in North America. The diagnostic analyses will mainly focus on variability of the AWP, and its impacts on the NASH, the Caribbean low level jet and its moisture transport, and the Great Plains low-level jet and its moisture transport. Other areas of the focus in the diagnostic analyses include the relationships of rainfall in the U.S. with the AWP, the external influences (such as ENSO, the AMO, and the NAO) versus local ocean-atmosphere processes on AWP variability, and the relationships among environmental factors contributing to hurricane activity. We will perform CESM1 model simulations with and without realistic initialization of the AWP to explore the impact of AWP initialization on seasonal forecasts. We will also examine the influences of model resolution and deep convective parameterizations in CESM1 on AWP SST and rainfall biases. One of the tasks is to analyze the CFSv2 reforecasts to explore its skill for seasonal predication of the AWP and AWP-related climate and extreme events. The CESM1 experiments and the analysis of CFSv2 reforecasts are designed to identify the sources that contribute to the model biases, thus provide a basis for improving model simulations and predictions. In collaboration with scientists at NOAA/CPC, we will attempt to transition research results to operations at NOAA/CPC. The proposed work directly contributes to all of four topics listed in the NOAA/CPO MAPP FY12 Priority Area 3 of "modeling of IAS climate processes associated with extremes over North America". It is hoped that over a longer time frame, this work will result in the regional implementation of data- and model-based outlooks for flood/drought in the United States, hurricanes and climate variability, when successfully combined with land-based models.


Principal Investigator (s): Wang, Chunzai (NOAA/AMOL)

Co-PI (s): Lee, S.-K. (NOAA/AMOL); Enfield, D. (NOAA/AMOL)
Year Initially Funded: 2012
Task Force:
Climate Prediction Task Force
Final Report:

Predictability of Atlantic Hurricane Activity by the NMME Coupled Models

View abstract

We propose to investigate, and then implement into a real-time forecast system, the response of the CFS CGCM to the Madden-Julian Oscillation (MJO) in north Atlantic hurricane activity. The very high resolution (T382) version of CFS will be used, as it has already been found to reproduce the interannual variations of hurricane activity level and individual hurricane tracks quite effectively over a multidecadal hindcast period.

Seasonal Atlantic hurricane activity level is known to vary in response to environmental variables such as the ENSO state, the sea surface temperature (SST) in the Main Development Region (MDR), and the state of the north Atlantic multidecadal oscillation. Relatively recently, dynamical tools have been used to predict hurricane activity with some success, defining individual cyclones and quantifying their seasonal total energy. The MJO phase and strength is also definable, and some statistical and dynamical predictability for the MJO is discernible out to the first 2-3 weeks. The MJO is also found capable of affecting the genesis and strength of tropical cyclones in both the Pacific and Atlantic oceans, and this MJO-cyclone relationship is reproducible in some dynamical models. We plan to capture these relationships in a real-time hurricane prediction system that can distinguish preferred timings and locations of hurricane activity up to 2-3 weeks.

Four main tasks of the project will be to (1) assess the extent and quality of MJO representation in the T382 CFS model; (2) examine the relationship between the model's MJO and its hurricane activity compared with that found in observations, and statistically correct systematic errors; (3) repeat steps (I) and (2) for the standard (T 126) CFS version 2 model and for the other models in the NMME experiment, and test multimodel ensemble prediction; and (4) assuming favorable results from (l), (2) and/or (3), implement a real-time hurricane forecast system using the T382 CFS and/or other models in the NMME.

Better prediction of the seasonal Atlantic hurricane activity level, and of preferred subregions for hurricane activity in the medium-range timescale (first few weeks) due to the MJO, is relevant to U.S. economic, safety and national security issues--disaster management, water management, health, and protection of life and property. An example of the level of hurricane forecast detail potentially resulting from the proposed work would be: "During week 1, hurricanes are more likely to emerge in the Gulf of Mexico or in the vicinity of Cuba than near or north of the Leeward Islands, while during week 2 they are most likely in the subregion south of Haiti, the Dominican Republic, Puerto Rico and Virgin Islands, and relatively unlikely in the western Gulf of Mexico. " Such intraseasonal specificity, still not targeting individual hurricanes, would complement the overall seasonal prediction of hurricane activity to render the suite of time scales more seamless. This work is also more generally relevant to the Next Generation Strategic Plan, as better Atlantic hurricane predictions lead to more valued, relied-upon climate services for the benefit of hurricane-sensitive human activities (e.g., coastal sustainability). The combination of the effects of climate change and the year-to-year variations in hurricane activity has potential for the hazard of record-breaking extremes in coastal region inundation and storm surge.


Principal Investigator (s): Barnston, Anthony (IRI/Columbia University)

Co-PI (s): Tippett, Michael (IRI/Columbia University); Schemm, Jae-Kyung (NOAA/CPC)
Year Initially Funded: 2012
Task Force:
Climate Prediction Task Force
Final Report:

Mesoscale variability in the Gulf of Mexico and its importance in climate extremes over North America

View abstract

The motivation for this study is in the need to improve understanding and modeling capabilities of regional air-sea interaction processes within the Intra-Americas Sea (IAS) region and their relationship with climate extremes. Oceanic circulation, which is characterized by strong mesoscale (order of 10-100km) variability, strongly affects airsea interactions in the region and distribution of heat anomalies, which has important implications for U.S. climate. In particular, distribution of surface temperature anomalies associated with the Atlantic Warm Pool (AWP) influence the rainfall over North America, thus playing a key role in frequency and severity of draughts and rain events. In addition, heat anomalies play the role of a heat reservoir for hurricanes in the IAS, particularly in the Gulf of Mexico (GoM) region, controlling conditions favoring their formation and intensification. In this regard, the mesoscale variability in the GoM – a key region linking the IAS and continental U.S. – is particularly important. The GoM circulation is complex and highly variable, and its rich dynamics, as well as its connection to the North American climate, continue to be poorly understood. Furthermore, key mesoscale processes involved in the dynamics are not captured by the current generation of CMIP5-class climate models, which lack resolution in their ocean component.

The goal of this study is to improve understanding and modeling capabilities of the circulation within the IAS and its mesoscale variability with implications for U.S. climate and extreme events. Our particular focus is on the major conduit of oceanic heat transport in IAS – the Caribbean Current (CC) / Loop Current (LC) system and associated eddies through Yucatan and into the GoM. Specific objectives are to analyze: (i) the dynamics of mesoscale variability in GoM; (ii) the importance of this variability for the heat distribution; (iii) role of these processes and their adequate resolution for climate studies. To achieve these objectives, we propose a comprehensive approach, which will utilize a hierarchy of numerical simulations, both coupled atmosphere-ocean and ocean-only, including the analysis of CMIP5-class climate model existing simulations. Key novel elements of the proposed research include examination of mesoscale dynamics in ocean-only models at very high resolutions not previously available, as well as a comparative analysis of coupled CMIP5-class simulations with low and high resolution in the oceanic component.

This proposal addresses MAPP Priority Area 3: “Modeling of Intra-Americas Sea climate processes associated with extremes over North America”. The proposed work is relevant to NOAA’s long-term goal to "Understand Climate Variability and Change to Enhance Society's Ability to Plan and Respond", by offering a comprehensive, novel study of the oceanic mesoscale processes in the IAS (focusing on the GoM domain) which are relevant for hurricanes and rain/draught events over North America. Adequate spatial resolution of oceanic mesoscale circulation is essential for accurate representation of oceanic processes in climate simulations. Comprehensive studies of mesoscale processes and their relevance to climate variability are urgently needed. The proposed study will make progress in this direction, by focusing on the poorly known mesoscale variability in a dynamically active region of the IAS. In particular, expected outcomes of this study include investigation of the importance of increased resolution in the ocean in climate model ability to capture essential processes in the region and to improve prediction of extremes. This study will be conducted through CIMAS Themes, "Climate Research and Impacts" and "Ocean Modeling".


Principal Investigator (s): Kamenkovich, Igor (University of Miami/RSMAS)

Co-PI (s): Halliwell, George (NOAA/AMOL); Kourafalou, Villy H. (University of Miami/RSMAS); Kirtman, Benjamin (University of Miami/RSMAS)
Year Initially Funded: 2012
Task Force:
Climate Prediction Task Force
Final Report:

Modulation of Tropical Cyclone (TC) Activity over the Intra-Americas Sea by Intraseasonal Variability: Implications for Dynamical TC Prediction on Intraseasonal Time Scales

View abstract

Tropical intraseasonal variability (ISV, e.g. Madden-Julian Oscillation) exerts significant influences on global climate and weather systems including tropical cyclones (TCs). This serves as a critical basis of the "Seamless Prediction" concept by bridging the forecasting gap between medium to long-range weather forecast and short-term climate prediction. For extended range forecasts of TC activity on an intraseasonal time scale (10~60 days), most of current approaches are based on statistical models or downscaling techniques. Recently, with the development of high-resolution general circulation models (GCMs) with improved model physics, it has become possible for these GCMs to represent both ISV and hurricanes, leading to a new avenue for intraseasonal TC prediction by using dynamical models.

Our recent analyses (Jiang et al. 2011b; Jiang et al. 2011a) of ISV and TC activity over the eastern North Pacific (ENP) based on simulations by the high resolution NOAA/GFDL HiRAM AGCM illustrate that the observed dominant ISV modes over the ENP are captured well in HiRAM; meanwhile, the observed relationship between ISV and TC activity over the ENP can also be faithfully represented in this model. Motivated by these encouraging results, we propose to use HiRAM, a leading edge model in terms its ISV-TC fidelity, to qualify the predictive skill and estimate the predictability for TCs across the Intra-Americas Sea (IAS) on intraseasonal time scales. The objectives of this proposed study are as follows:

1. Conducting hindcast experiments to fully evaluate the prediction skill of ISV over the IAS by the NOAA/GFDL HiRAM;

2. Analyze the HiRAM hindcast ensembles to estimate the intrinsic predictability of TC activity over the IAS;

3. Evaluate the role of ISV in characterizing the prediction skill of TCs over the IAS on intraseasonal time scales;

4. Explore the physical mechanisms associated with ISV modulation of TC formation over the IAS;

5. Using both HiRAM climate simulations and hindcasts, evaluate how model horizontal resolution and different physical parameterization specifications influence model skill in simulating / predicting ISV and TC activity.

With a focus on the close linkage between TCs, one of the most disastrous extreme events, and ISV, a prominent climate mode with broad impacts over the IAS, this proposal directly addresses MAPP program's FY2012 goals of "modeling of Intra- Americas Sea climate processes associated with extremes over North America". Moreover, this proposed study is in great agreement with recommendations by the National Academy of Science’s 2010 report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability" that "Many sources of predictability remain to be fully exploited by intraseasonal to interannual (ISI) forecast systems. To better understand key processes that are likely to contribute to improved ISI predictions, …, MJO influences on other important components of the climate system, such as tropical cyclone genesis should continue to be explored and exploited for additional predictability."


Principal Investigator (s): Jiang, Xianan (UCLA)

Co-PI (s): Waliser, Duane (UCLA); Zhao, Ming (NOAA/GFDL); Lin, Shian-Jiann (NOAA/GFDL)
Year Initially Funded: 2012
Task Force:
CMIP5 Task Force
Final Report:

Intraseasonal to Interannual Variability in the Intra-Americas Sea in Climate Models

View abstract

This study assesses the ability of CMIP models to produce realistic intraseasonal to interannual variability (IAV to ISV) in the Atlantic warm pool (AWP) region and the implications for hurricanes, the ability of parameterization modifications in the GFDL AM3 to improve the simulation of AWP ISV, and how mean state biases in CMIP models develop and the implications for forecast biases in ISV and IAV. The following questions will be answered:

1. Can IAS-region intraseasonal variability in the GFDL AM3/CM3 be improved through modifications to the treatment of deep convection?

The sensitivity of IAS mean state and ISV to modifications in the Donner convection scheme in GFDL AM3/CM3 will be assessed, including different treatments of triggering, rain evaporation, and entrainment. The degree to which IASregion ISV is coherent with that in the Eastern Hemisphere will be assessed, which has consequences for prediction. Variables that impact hurricane genesis potential will be a focus.

2. How do model errors develop over the Atlantic warm pool?

In the AWP, the ensemble mean of CMIP3 models features SST errors of 2oC or larger in the annual mean, with considerable variability in rainfall errors among different atmosphere models forced by observed SSTs. A systematic investigation into errors of SST, rainfall, sea level pressure and wind in the AWP based on the CMIP3/5 database will be conducted, including the similarities and differences among models. Initial emphasis will be GFDL models, especially initialized seasonal forecasts, followed by a diagnosis in the broader suite of CMIP5 models.

3. How well can CMIP5 models simulate the ENSO-Atlantic hurricane teleconnection?

Substantial biases in the ENSO-Atlantic hurricane teleconnection occur in all CMIP3 models (Shaman and Maloney 2011). We will assess the ability of CMIP5 models to capture the ENSO teleconnection to the Atlantic and its manifestation in large-scale variables that affect tropical cyclone (TC) genesis, with specific focus on the GFDL CM3. We will also intercompare CMIP5 model ability to capture other modes of Atlantic IAV including the Atlantic meridional mode and Atlantic Multidecadal Oscillation, and the variables relevant for TCs.

4. How do IAS-region mean state biases affect forecasts of ISV and IAV and extreme events?

The climatology of a coupled prediction model drifts quickly, and the model errors approach the equilibrium in a matter of months. Biases in the mean state, such as those in SST, precipitation, and winds can have profound implications for Atlantic climate variability and how remote forcing from climate variability in other basins is manifest in the Atlantic. The effect of the climate drift on forecast results within the IAS will be assessed. The regional climate model from U. Hawaii will be used to examine how mean state biases affect biases in ISV and IAV and extreme events over the IAS region. ISV to IAV in boundary conditions will be retained while biasing the mean state to that of the GFDL CM and other CMIP models to determine how changes in the climate state and its statistics affect the simulation of extreme events like TCs.

This proposal directly addresses MAPP Priority Area Three. We intend a comprehensive study to document the ability of CMIP5 climate models including GFDL CM/AM to accurately simulate the ISV to IAV of the IAS region and associated TC activity. Parameterization modifications to the GFDL AM3 and their ability to improve ISV in the IAS region will be assessed. A close look into model biases in the IAS to identify their sources is an important step toward improving seasonal forecasts of extremes over the Americas. This proposal also supports NOAA's NGSP by improving understanding of model biases that will allow more accurate predictions of future climate, allowing society to better anticipate and respond to the challenges of climate change. This proposal entails research that advances the nation’s core capabilities in understanding and modeling the climate system, which is a primary goal of the CPO.


Principal Investigator (s): Maloney, Eric (Colorado State University)

Co-PI (s): Xie, Shang-Ping (University of Hawaii); Leavell, Doug (Colorado State University)
Year Initially Funded: 2011
Task Force:
CMIP5 Task Force
Final Report:

Tropical Cyclone tracks in present and future climates

View abstract

Due to the large social and economic impacts of tropical cyclones, it is fundamental to understand possible changes in tropical cyclone activity due to climate change. In this project we will focus on how tropical cyclone tracks could be influenced by climate change, especially due to the most robust projected changes in the tropical circulation. Tropical cyclone tracks strongly influence many tropical cyclone properties - including intensity and landfall frequency and location - which are of great importance to local populations. We will study changes in tropical cyclone tracks due to both natural variability and anthropogenically forced trends. As part of our analysis we will apply a cluster technique that we have previously applied to observed tropical cyclone tracks in different regions of the world, and that has given important insights on the different properties of tracks in different cluster types: e.g. seasonality, genesis location, intensity, landfalling rates and locations.

Our first approach will be to examine tracks of tropical cyclones in global and regional climate models under present and future climate scenarios. We will apply the same cluster technique to identify tropical cyclone track changes in future climate scenarios and the large-scale circulation associated with those changes. The analysis will be performed using output from many models, to assess the robustness of these track changes as well as the relevant dynamics.

The second approach is to examine synthetic tropical cyclone tracks generated by a statistical dynamical as well as a purely statistical approach. These tracks will be associated with current and future climate scenarios. We will then compare the cluster analysis of synthetic tracks to that of the dynamical models’ tracks. By using two distinct approaches, we will be able to make a detailed assessment of the robustness of the possible track changes in future climate. The long term objective of this project is to build a scientific foundation for future projections of tropical cyclone landfall change associated with climate change.

Principal Investigator (s): Camargo, Suzana (LDEO/Columbia University)

Co-PI (s): Hall, Timothy (NASA Goddard and Columbia University); Adam, Sobel (Columbia University)
Year Initially Funded: 2011
Task Force:
CMIP5 Task Force
Final Report:

Central U.S. abnormality in climate change and its response to global warming

View abstract

The climate system is complex and involves many intertwined, interactive processes. Consequently, the direction and magnitude of climate change is a result of the various positive and negative feedbacks. On a regional scale, local climate change also reflects remote forcing and teleconnection patterns. Diagnosing individual climate change feedbacks will improve the understanding of climate dynamics and shed light on separating climate change into natural and anthropogenic components. This project proposes feedback processes and examines their contribution to abnormal climate change in the central and eastern U.S., which experienced a cooling trend is past decades.

The first process to be examined is baroclinicity, where the horizontal gradient in surface warming increases thermal wind and baroclinic instability, which then further interacts with climate change. The second process is soil moisture feedback. Climate change causes soil moisture to change, which alters the soil heat capacity and thus causes a feedback on nearsurface temperature changes. The last process is the planetary boundary-layer (PBL) depth/lowlevel jet (LLJ) feedbacks. A stronger surface warming and thus a higher PBL height upstream produce a stronger nocturnal LLJ and moisture transport downstream, generating an increase in cloudiness leading to a subsequent cooling.

Given the processes outlined above, the objectives of our proposal are: 1) to determine to what extent the above regional feedbacks contribute to the unusual summer cooling in the central and eastern U.S.; 2) to assess if these feedbacks can help explain why most IPCC AR4 GCMs were unable to reproduce the cooling trends in their 20th century historic simulations; 3) to project if this cooling trend will continue in coming decades; and 4) examine if these feedback processes also contribute to similar local cooling documented over other continents. Address these issues will help determine whether the abnormal central and eastern U.S. climate change is a regional response to (i.e., a result of) global warming, suggesting that the cooling trend would continue in lock-step with global warming, or it is related to some other transient processes, meaning that the central and eastern U.S. would be much warmer if these processes disappear in the future.

To achieve our objectives, a series of numerical experiments will be carried out using the global NCAR Weather Research and Forecast (WRF) model and Climate WRF (CWRF) with enhanced land surface and boundary layer schemes. Statistical tools including canonical correlation analysis (CCA), principle component analysis (PCA), and factor separation will also be used to diagnose the associations between these feedbacks and anomalous mid-continent cooling.


Principal Investigator (s): Pan, Zaitao (Saint Louis University)

Co-PI (s): Eicher, Timothy (Saint Louis University)
Year Initially Funded: 2011
Task Force:
Drought Task Force
Final Report:

Quantification and reduction of uncertainties in projections of climate impacts on drought and agriculture for North America

View abstract

Introduction to the Problem: Agricultural productivity is highly dependent on climate variability and is thus susceptible to future changes including temperature extremes and drought. The latter is expected to increase in frequency regionally over this century. However, the uncertainty in projections of drought and its impacts on agriculture is high due to emission scenarios, climate model differences, uncertainty in initial/boundary conditions, and translation to regional scales. 

Climate models are unanimous in projecting future warming but differ in the magnitude and even sign of regional precipitation changes. They also differ in terms of extremes of temperature, precipitation and other meteorology. When projecting future impacts on crop productivity, these uncertainties are compounded because current crop models often use simplified treatments of climate response and do not include comprehensive treatments of water availability. Therefore, projections of regional climate change, variability and its impacts on water availability and agriculture are highly uncertain and reduction of uncertainties requires attention to all levels in the climate-water-agriculture continuum.

Rationale: Given the uncertainties in future agricultural production and the complex relationships between climate, hydrology and crop development, there is pressing need to make improved estimates of future changes in climate change and crop yields. We propose to evaluate the uncertainties in estimates of future changes in climate, water availability and agricultural production, and make improved estimates by incorporating state of the art knowledge of the relationships between climate, hydrology and agriculture into modeling and downscaling.

This has ramifications for disaster preparedness and mitigation, policy making and the political response to climate change, and intersects with fundamental science questions about climate change, extremes and hydrologic cycle intensification. It is central to the mission of the Climate Program Office’s MAPP program to “enhance the Nation’s capability to predict variability and changes of the Earth’s System” and directly addresses its priorities to evaluate and reduce uncertainties in climate projections. This work will leverage from the PIs’ experience and ongoing activities in large-scale climate analysis and hydrologic modeling, particularly in changes in drought historically and under future climates, and agricultural modeling and relationships between climate and crop productivity.

Summary of work to be completed: 1. Quantify the relationships between hydroclimate variables and the implications for water, drought and agriculture based on observational data. 2. Evaluate sensitivities of hydrologic and crop models to changes in climate and drought. Differences in climate variability, land-atmosphere coupling and hydrologic persistence will lead to differences in key metrics of water and agriculture which will form the basis for evaluation of the uncertainties in future projections. 3. Evaluate current climate models in how they replicate these observed relationships using the CMIP5 long-term and decadal predictions. 4. Estimate uncertainties in future projections of climate, drought and agriculture using a cascade of climate, downscaling, hydrologic and crop models with strategic sampling to decompose sources of uncertainty. 5. Implement a set of methods to reduce uncertainties in future projections based on observational constraints including merging of climate model predictions, bias correction and scaling of climate model output, and improvements to impact models.

 


Principal Investigator (s): Sheffield, Justin (Princeton University)

Co-PI (s): Lobell, David (Stanford University)
Year Initially Funded: 2011
Task Force:
CMIP5 Task Force
Final Report:

Observational constraints, diagnosis and physical pathways for precipitation and extreme event processes in next-generation global climate models

View abstract

As climate models move to finer resolution, they can be evaluated against observations using new metrics. We propose to use and extend a set of measures developed from observations, on the scales that high-resolution global climate models are now reaching, to evaluate a targeted set of processes in current climate models. These will be evaluated for a set of models across a range of resolutions, including the higher resolutionmodels fromthe CoupledModel Intercomparison Project 5 (CMIP 5), and various higher-resolution models from specific modeling groups. An example of a moderately high resolution model (Community Atmosphere Model at 0.5 degree resolution) is used to show that a model with parameterized convection can qualitatively capture several aspects of the categories below, but there is considerable sensitivity to ill-constrained factors such as entrainment.

The analysis will provide assessment of model suitability for evaluation of changes in these statistics under climate change and provide feedback for model development, drawing on tools developed under previous NOAA funding. Specifically, we focus on four categories of related features of precipitation, water vapor and temperature characteristics, on a set of statistics to quantify these, and on the underlying mechanisms producing these features.

1. Onset of deep convection, its water vapor-temperature dependence, and relation to entrainment assumptions. A set of convective onset statistics from remote sensing and in situ data provide a quantification of recent developments on the dependence of convection on water vapor in the lower free troposphere. There are several indications from other groups and from NOAA-supported prior work, of a strong sensitivity of climate models to errors in this process.

2. Excursions to high water vapor and strong precipitation regime. Prior work has provided evidence of long tails in the probability distribution (PDF) of water vapor, with a Gaussian core surrounded by approximately exponential tails, characteristic of an advection interacting with a forcing that maintains a gradient. Such tails imply much more frequent excursions into the high-water vapor regime associated with intense precipitation than would occur with Gaussian statistics.

3. Quantification of similar long-tail behavior for surface temperature PDFs, seen in preliminary work in many locations. The presence of such tails implies a rate of increase of extreme events under a shift of the distribution under global warming very different from that of a Gaussian.

4. Interactions at the margins of convective zones: the inflow air mass transported into a convective region is modified along its trajectory until conditions for convective onset are reached. If the onset condition evaluated in 1 is incorrect, the margins of the convection zones can have errors of hundreds of kilometers, creating large errors at the regional scale. Under global change, differences among model representations of this condition can yield large differences in the predicted regional change.

Coordinated with a proposal from Rutgers University, diagnostics from internal variability will help constrain models in this category, and the role of these mechanisms will be evaluated for regional climate change in the models.


Principal Investigator (s): Neelin, J. David (UCLA)

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

Towards improving convection parameterization and the MJO in next-generation climate models

View abstract

Tropical biases remain a significant problem in global atmosphere models, even at horizontal resolutions of 20-50 km. In addition to mean state errors, another glaring deficiency is the general absence of the 30-60-day Madden-Julian oscillation (MJO), which modulates the frequency of tropical cyclone genesis over several basins and interacts with the lower-frequency El-Nino Southern-Oscillation. It is thought that such errors stem mainly from deficiencies in convection parameterization, but the precise nature of these deficiencies remains unclear. In order to address such tropical problems, we propose to run and analyze a suite of short-term [O(10-day)], high-resolution weather hindcasts, focusing on a 40-day period of enhanced MJO activity during the Year of Tropical Convection (YoTC) when special observational and assimilated datasets are available. The hindcasts will be performed using 4 different high-resolution atmospheric models (GEOS-5, CAM5, HiRAM, and WRF) as part of a multi-institutional collaborative research effort. The goal is to see how simulations of the MJO and other high-impact weather phenomena, as well as the mean state, are affected by either i) increases in model resolution (going from 50- down to 5-km horizontal grid spacing) or ii) the use of a “superparameterization” of convection at 50-km horizontal grid spacing. Hindcasts will also be generated with each of the models’ convection schemes turned off, to see how the various schemes tend to improve (or degrade) their respective model’s performance at high resolution. We hypothesize that models with more realistic convective processes will do better at simulating the MJO, so our diagnosis of model output will include both process-level and global-scale aspects, and will compare these in order to test this hypothesis. Improved understanding of this convective process-global performance relationship will serve the overall goal of improved ability to simulate convection variability and the MJO in models used to predict changes in regional-scale climate and high-impact weather for the decades to come.


Principal Investigator (s): Tulich, Stefan (CIRES/University of Colorado and NOAA/ESRL)

Co-PI (s): Bacmeister, Julio (NCAR); Putman, William (NASA Goddard); Suarez, Max (NASA Goddard); Zhao, Ming (NOAA/GFDL)
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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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Download our program brochure (pdf).