GFDL Past Events & Seminars - 2011

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An Exascale Computing Initiative

GFDL's CM2.5 high resolution global coupled model - formulation, simulation characteristics, and response to doubled CO2

In this talk I will describe the study of the mechanisms of Atlantic multidecadal SST variability (AMV) impact on the atmospheric circulation using SST forced GCMs and compare that with evidence from the IPCC AR4 models. I will then talk about diagnosing the ingredients of the variability in the GFDL CM2.1 model, with particular focus on the interaction between the the Atmosphere and the North Atlantic Ocean.

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Snow-covered surfaces are the most reflective on Earth, and therefore play an integral role in the planetary energy budget. Mid- and high-latitude insolation becomes intense during boreal spring, while a large portion of the hemisphere remains snow covered. Consequently, processes which alter the timing of snow melt can drive significant climate change through albedo feedback. Here, I discuss the influence of deposited atmospheric particles on snow reflectance and climate. Part-per-billion concentrations of black carbon significantly reduce snow reflectance because of unique radiative processes in snowpack, and subsequent solar heating can accelerate snow aging, further darkening snow in the near-infrared spectrum. Because of such feedbacks, aerosol-induced snow darkening likely drives greater change in global mean temperature per unit power of radiative forcing than any other anthropogenic forcing mechanism.

There is considerable certainty that we should expect a significant amount of global climate change as a result of human activities. Unfortunately, as scientists we have let climate change deniers get away with creating a perception that it is all based on complicated and speculative models. Multiple independent lines of evidence show that the observed increase of CO2 is fully due to human society, and similarly for other greenhouse gases. The resulting direct radiative forcing is well understood and quantified, and climate change is being observed. On the other hand, prognoses of future climate change span a wide range. The uncertainties start with the projected emissions themselves. Many of the IPCC CO2 emissions scenarios are likely much too high because they assume continuing exponential growth. Our economic system is on a collision course with a finite Earth, and we will be forced to adapt.

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Observations reveal marked trends in the extratropical circulation of both hemispheres over the past few decades. Numerical experiments suggest stratospheric ozone depletion has contributed to the observed trends in the Southern Hemisphere, and that increases in carbon dioxide will drive similar trends in both hemispheres in the future. But the physical mechanisms that drive the observed and simulated trends remain unclear. In this talk, I will survey the evidence for past and predictions for future trends in the extratropical circulation; I will examine the mechanisms thought to underlie the trends; and I will describe recent efforts to identify the key mechanisms using simple atmospheric models.

Detecting Saturation in the Ocean Carbon Sink

In response to the global warming problem, there has been a recent renewed interest in geoengineering "solutions" involving "solar radiation management" by injecting particles into the stratosphere, brightening clouds, or blocking sunlight with satellites between the Sun and Earth. While volcanic eruptions have been suggested as innocuous examples of stratospheric aerosols cooling the planet, the volcano analog actually argues against geoengineering because of ozone depletion and regional hydrologic responses. In this talk, I describe different proposed geoengineering designs, and then show climate model calculations that evaluate both their efficacy and their possible adverse consequences. No such systems to conduct geoengineering now exist, but a comparison of different proposed stratospheric injection schemes, using airplanes, balloons, and artillery, shows that using airplanes to put sulfur gases into the stratosphere would not be expensive. Nevertheless, it would be very difficult to create stratospheric sulfate particles with a desirable size distribution. We have just started a GeoMIP project to conduct standard stratospheric aerosol injection scenarios in the context of CMIP5, so as to examine the robustness of the few experiments conducted so far. 13 climate modeling groups are now participating, and I will urge GFDL to join us. If there were a way to continuously inject SO2 into the lower stratosphere, it would produce global cooling, stopping melting of the ice caps, and increasing the uptake of CO2 by plants. But there are 25 reasons why geoengineering may be a bad idea. These include disruption of the Asian and African summer monsoons, reducing precipitation to the food supply for billions of people; ozone depletion; no more blue skies; reduction of solar power; and rapid global warming if it stops. Furthermore, the prospect of geoengineering working may reduce the current drive toward reducing greenhouse gas emissions, there are concerns about commercial or military control, and it may seriously degrade terrestrial astronomy and satellite remote sensing. Global efforts to reduce anthropogenic emissions and to adapt to climate change are a much better way to channel our resources to address anthropogenic global warming.

Rethinking the global fisheries crisis: comparing stock status and management approaches across ecosystems

Climate feedback processes determine both the magnitude and the structure of global warming. Global climate models produce a consistently positive longwave cloud feedback. This is shown to be related to the strong coupling between clear-sky radiative cooling and cloud heating in the Tropics, sometimes called the fixed anvil temperature hypothesis. Cloud-resolving models, data and AR4 global climate simulations all support this general hypothesis, but indicate a host of remaing questions. Feedback analysis of AR4 simulations show some very consistent features, including strong clear-sky greenhouse feedback and longwave cloud feedback near the equator and strong negative cloud feedback and oceanic heat uptake in high latitudes that together imply a requirement for enhanced poleward transport associated with transient warming during this century.

Global cloud-resolving simulations with GEOS-5 and advances with the cubed-sphere dynamical core and GPUs

In prior work, we documented the existence of longer-than-Gaussian tails in the probability distribution functions (pdfs) of column-integrated anomalies for a wide range of tropospheric trace species, including water vapor, CO2, and CO, in satellite observations, meteorological reanalyses, and global chemical transport model (CTM) simulations. The occurrence of longer-than-Gaussian tails has implications for issues such as inverse modeling of pollutant and greenhouse gas source emissions and assessment of changes in extreme events under climate change. Here, we explore the morphology and genesis of long-tailed tracer anomaly pdfs for tropospheric constituents such as water vapor, CO2, CO, NOx, CH2O, and O3. In particular, we document the role of tropospheric transport acting across maintained three-dimensional (3D) gradients in producing ubiquitous long-tailed behavior in these constituents, although non-transport related processes acting on particular constituents (e.g., rainout of water vapor) are likely to influence the structural details of the pdfs, such as the point at which the tail separates from the pdf Gaussian core, the tail slope, and asymmetries between the positive and negative tails. Case studies focusing on synoptic-timescale tracer anomalies in the tails of the pdfs as simulated by the GEOS-Chem global CTM are used to illustrate meteorological conditions under which models can produce non-Gaussian excursions. Further by comparing observed pdfs and those simulated by GEOS-Chem, we demonstrate how the pdfs are potentially useful tools for diagnosing model strengths and weaknesses on both global and regional scales.

The impacts of anthropogenic induced climate change on ecosystems and biodiversity is one of the key topics for the upcoming fifth assessment report from the Intergovernmental Panel on Climate Change (IPCC). Critically endangered leatherback turtles in the eastern Pacific Ocean are excellent candidates for this assessment because they have been extensively studied in terms of their sensitivity to present-day climate variability at both their terrestrial and oceanic environment. If incidental fisheries mortality of leatherback turtles is reduced or eliminated, the population still faces the challenge of recovery in a rapidly changing climate. However, the synergistic impacts of climate change at their terrestrial and oceanic habitats have yet to be reconciled. Here I combine IPCC climate model projections and a leatherback population dynamics model to estimate a 7% per decade decline in the population over the next century. Whereas changes in ocean conditions had no effect on the population, the warming and drying of the nesting beach was the primary driver of the decline via decreased neonate recruitment. Therefore, even with the elimination of incidental fisheries mortality, the population may still become extirpated. This study highlights the potential for human intervention at nesting beaches to prevent the population collapse; climate mitigation of leatherback nests may be able to negate the precipitous population decline.

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24, 2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

In this talk I investigate the role of the harmonics of radiation on the coupled land-atmosphere system. I will first focus on the land-surface heat fluxes and demonstrate some new fundamental understanding of the energy partitioning at the land surface. In particular, I will show how the time scale of the radiation forcing is crucial to comprehend the response of the coupled system. A counter-intuitive finding is that soil heat flux acts as a high-pass filter of radiation, whereas sensible and latent (evapotranspiration) concentrate the lower daily frequencies. I will highlight several important consequences of these results for land-surface modeling and remote sensing of brightness temperature. I will then show how the high-frequency soil heat flux spectrum leads to systematic errors in the closure of the surface energy budget both in models and field measurements and propose a correction method to achieve better closure. Finally, I will discuss how inaccuracies in the surface energy balance on the soil and lower atmosphere (~10m) may impact data assimilation of remote sensing or meteorological variables. I suggest how the results of my work may inform the design of new remote sensing platforms and improve data assimilation strategies of land-surface variables such as soil moisture and heat fluxes.

The Arctic troposphere is heavily polluted in Winter and Spring as a result of long-range transport from northern mid-latitude continents and the lack of photochemical activity needed to cleanse the atmosphere. This talk will integrate fine resolution aircraft campaign measurements with global-scale satellite observations and global chemistry model simulations to examine the sources and impacts of pollution in the Arctic. Aircraft measurements from the NASA ARCTAS, NOAA ARCPAC, European POLARCAT and NSF/NCAR START-O8 campaigns in Spring and Summer 2008, along with the NSF TOPSE campaign in Spring 2000, have been analyzed in conjunction with satellite observations and model results. Global observations of carbon monoxide (CO) from the 10-year record of the Terra/MOPITT instrument provide a large-scale and multi-year context for the Arctic aircraft measurements, particularly highlighting the importance of Siberian fire activity during 2008. The global chemistry model simulations have been performed for these periods with MOZART-4 and CAM-chem (CESM1) with the MOZART-4 chemical scheme and specified dynamics (GEOS5). Evaluation of the model results with the aircraft and satellite observations has identified likely errors in the emission inventories and fire emission factors. The contributions of anthropogenic and fire emissions from different regions to the distributions of CO, ozone and black carbon in the Arctic troposphere have been quantified through "tagging" procedures in MOZART-4. The relative importance of different sources varies greatly depending on location, altitude and season.

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To date, human history has been marked by extraordinary material success, a flowering of science and technology, and an emerging policy framework to foster both. Despite this progress, economic development looks suspect, the environment and ecosystem services are deteriorating, and disaster losses are rising. Closer to home, NOAA seeks to be relevant in a problematic future world. This talk provides opportunity for to consider and discuss these timely issues.

The unexpected and widespread acceleration of outlet glaciers in Greenland over the last decade has contributed to a doubling of the ice sheets contribution to sea level rise. The mechanisms behind the acceleration are unclear but there is increasing evidence that warming of ocean waters coming in contact with the glaciers may have played a role. This, in turn, would imply that the ocean can impact the variability of the Greenland Ice Sheet on decadal timescales. Regardless of the oceans role in triggering the recent glaciers acceleration - ocean-driven melting at the ice sheets margins has recently emerged as a significant term in the ice sheets mass balance. Yet our understanding of the oceanic, atmospheric and glaciological processes controlling the properties of the waters reaching the glaciers and their variability is limited and this physics is either absent or crudely represented in ice sheet, glacier and climate models. Here, I will present recent observations from several major glacial fjords systems in East Greenland (some which have recently accelerated and some which have not) and discuss the first order dynamics that have emerged from these surveys. Amongst the relevant processes - I will argue that outlet glaciers are sensitive to the variability of both Arctic and Atlantic waters circulating around Greenland as well as synoptic weather systems which modulate the fjord/shelf exchange. Finally, I will argue that the shape of terminus, and hence the stability, of Greenlands glaciers is strongly controlled by large scale ocean circulation.

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The Madden-Julian Oscillation is a dominant mode of tropical variability. It holds a unique place in the environmental forecasting problem by having a time scale that lies between the more traditional predictions associated with weather and climate. In this regard, it represents an important bridge in considerations of developing seamless predictions and for its unique applications to decision support. Considerable progress has been made in the last decade in the development of forecasting capabilities and in understanding the links between the MJO and its impacts and interactions with weather, climate and applications. This presentation will provide some updates in the areas of science, forecasting and impact studies associated with the MJO, with particular emphasis on activities associated with the WCRP-WWRP/THORPEX MJO Task Force and its predecessor, the US CLIVAR Working Group, and on studies that utilize satellite resources to advance MJO science and applications.

In this talk, I will discuss physical mechanisms responsible for the amplitude asymmetry of the Indian Ocean dipole (IOD) and ENSO, based on the diagnosis of the oceanic mixed layer heat budget using the ocean assimilation datasets and NCAR/NCEP reanalysis data. It is found that two air-sea feedback processes are responsible for the negative skewness of SST anomaly (SSTA) in the IOD eastern pole (IODE). The first is the asymmetry of the wind stress-ocean advection-SST feedback. During the IOD developing stage (JJAS), the nonlinear advection tends to cool the ocean in both the positive and negative events, thus contributing to the negative skewness in IODE. The second process is attributed to the asymmetry of the SST-cloud-radiation feedback. The nonlinear zonal and meridional ocean temperature advections are essential to cause the El Nino and La Nina asymmetry in the far eastern equatorial Pacific. Whereas the zonal current anomaly is dominated by the geostrophic current in association with the thermocline depth variation, the meridional current anomaly is primarily attributed to the Ekman-induced wind stress forcing. The so-induced anomalous horizontal currents lead to warm nonlinear advection during both El Nino and La Nina episodes, and thus strengthen (weaken) the El Nino (La Nina) amplitude. Finally I will talk about the upscale feedback of high-frequency wind variability to the low-frequency wind stress and SST anomalies associated with ENSO, based on both observational analyses and ocean GCM simulations.

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While the IPCC regards detection of global climate change and attribution to human influence (in part) as positively solved problems, it regards the next frontiers of detection and attribution at regional scale and inter-decadal climate prediction as unsolved. Bayesian methods can be used to address both of these problems. Optimal detection using an ensemble of models is best posed in a Bayesian context, and when done, it reveals optimal fingerprinting as a way to infer climate change in any variable at any scale given arbitrary data. The resulting inference accounts for both internal variability of the climate and uncertain physics in climate models. The method is the foundation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO), a climate monitoring satellite constellation, which can be used to infer climate sensitivity using global, accurate data. The talk will encompass optimal fingerprinting and CLARREO.

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I will review recent work aimed at establishing the nature of, and factors underlying, patterns of large-scale climate variability in past centuries. Evidence is compared from (1) recent proxy-based reconstructions of spatial patterns of past surface temperature variability, (2) ensemble experiments in which proxy evidence is assimilated into coupled ocean atmosphere model simulations to constrain the observed realization of internal variability, and (3) coupled model simulations of the response to changes in natural external radiative forcing.

NOAA Brown Bag Seminar to be viewed in the Smag Room

As knowledge regarding the complex components of marine biogeochemical systems continues to grow, the models being developed to examine these systems are becoming correspondingly more complex and more diverse. It is becoming increasingly critical to compare these distinct modeling approaches, yet this is not a straightforward task. This typically involves the cooperation of large teams of investigators as well as the use of objective data assimilation methodologies and/or identical physical frameworks. Although such intercomparisons are difficult undertakings, they can help us gain a significantly better understanding of some of the advantages and limitations of different model structures and levels of model complexity. We have conducted two such model intercomparison exercises. First, the NSF-funded Regional Ecosystem Modeling Testbed Project involved an intercomparison of twelve 1-D biogeochemical models, each of which were tested in two distinct open-ocean regions. Each model was run within an identical physical framework together with a consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity. More recently, funding provided by the NOAA Integrated Ocean Observing System supported a second model intercomparison exercise. In this case the skill of six 3-D coupled biological-physical models were compared to each other and to EPA monitoring data in order to asses their skill in estimating the extent of hypoxia within Chesapeake Bay. These two exercises were conducted in very different environments (coastal vs. open ocean), and were motivated by different goals (global carbon cycling vs. operational modeling); however, many of the tools developed for model comparison, and the lessons learned in both instances were similar, and should be useful for other future model comparison exercises as well.

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The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to document how increased ocean model resolution impacts the simulation of large-scale climate variability. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5) - the forerunner to CCSM4. Two experiments are reported here. The first experiment (i.e., control) is a 155-year present-day climate simulation using a 0.5º atmosphere component (zonal resolution 0.625º meridional resolution 0.5º) coupled to ocean and sea-ice components with zonal resolution of 1.2º and meridional resolution varying from 0.27º at the equator to 0.54º in the mid-latitudes. The second simulation uses the same atmospheric model coupled to 0.1º ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming of about 0.2^o C. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The SST gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the interannual sea surface temperature anomaly (SSTA) variability is increased with the resolved eddies, but decreases in the deep tropics (i.e., the variance of El Niño and the Southern Oscillation is reduced). Changes in global SSTA teleconnections and local air-sea feedback are also documented and show large changes in ocean-atmosphere coupling.

Mountain snowpack responds to temperature variability with varying degree over the snow season. Using monthly and daily snow water equivalent station observations and gridded temperature data, I have identified the mechanisms by which warming affects the temporal and geographical structure of changes in western North American mountain snowpack since 1950. The mechanisms whereby temperature affects snowpack emerge in the mid to late portion of the snow season, but are nearly absent during the earliest phase, when temperatures are generally well below freezing. The mid to late snow season is precisely when significant loss of snowpack is seen at nearly all locations over the past few decades, both through decreases in snow accumulation and increases in snowmelt. In the earliest phase however, reduced temperature sensitivity has led to increased snowpack accumulation due to an increase in precipitation. The findings from this observational work have guided a present-climate study of California snowpack using the Weather Research and Forecasting model (a regional climate model) to better understand snowpack accumulation and melt. The model was run at 27, 9, and 3km resolution and compared with daily station observations to explore resolution-related errors. A framework is developed for calculating non-resolution dependent biases in the snowpack simulation and assessing the model's ability to reproduce observed intraseasonal sensitivities to temperature. Issues are identified and solutions are explored. This research is a necessary step towards both: (1) building a model for understanding the mechanisms controlling snowpack variability and (2) producing accurate high resolution snowpack projections in a warming world.

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High-resolution climate simulations present unique visualization and analysis challenges: the computational grids, consisting of billions of computation cells, are often semi-structured requiring complex manipulation for visualization and analysis purposes; the density of the data far exceeds our ability to represent an entire global snapshot in media such as image plots or display screens; individual data snapshots are in the order of 100s of gigabytes thus requiring efficient parallel visualization and analysis capabilities. We provide an overview of the landscape for analysis and visualization of such data sets and present our recent work in developing capabilities for the Global Cloud Resolving Model (GCRM). We have developed capabilities within the VisIt software to import geodesic grids and variables types. We will also present our work on command line tools for parallel data manipulation and analysis.

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An original high resolution dust sources inventory is derived from MODIS Deep Blue Level 2 data. The natural or anthropogenic origin of theses sources is attributed from vegetation, hydrological and land use datasets. These sources are then used to simulate dust distribution with the GFDL AM3 model. The differences in dust distribution and optical properties with the standard AM3 results are discussed by comparing with observations. Finally, the importance of anthropogenic dust at the continental and global scale is presented.

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A Significant Component of Unforced Multidecadal Variability

Study of the recent period of rapid climate change in Middle East and North Africa

Observational studies have shown strong correlation between surface temperature and ozone (O3) concentrations. It is widely anticipated that a warming climate will exacerbate O3 pollution in densely populated regions of the US, such as over the Northeast where climate models consistently show annual temperature increases of at least 2 K over the 21st century. We describe a mechanistic approach to model evaluation that seeks to characterize pollutant sensitivity to year-to-year fluctuations in weather, motivated by the hypothesis that our approach offers a good observational basis for assessing model skill at projecting air quality response to changes in climate. We first produce a monthly climatology of the surface O3-temperature relationship (d[O3]/dT) using monthly averages of daily maximum surface temperature (Tmax) and of maximum daily 8-hour average (MDA8) O3 from the US Environmental Protection Agency Clean Air Status and Trends Network (CASTNet) over the eastern US fr om 1988 through 2009. The CASTNet is designed to characterize conditions that are representative of the regional scale. Applying two distinct statistical approaches to aggregate local measurements to the regional scale, we find that summertime O3 sensitivity to temperature is 3–6 ppb K-1 (r = 0.5–0.8) over the Northeast, 3–4 ppb K-1 (r = 0.5–0.9) over the Great Lakes, and 3–6 ppb K-1 (r = 0.2–0.8) over the Mid-Atlantic. By separating our analysis into two periods, 1988–1999 and 2000–2009, we confirm the previously noted decrease in O3 sensitivity of roughly 1 ppb K-1 driven by NOx emission reductions from eastern US power plants in the late 1990s and early 2000s (Bloomer et al., 2009). We then evaluate the ability of the Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model version 3 (AM3), a global chemistry-climate model, to resolve the observation-derived O3-temperature relationship. The model captures the general features of the seasonal variations in the relatio nships despite biases in both monthly mean summertime MDA8 O3 (up to +10 to +30 ppb) and daily Tmax (up to +5 K) over the eastern US. We show that the model reproduces O3 sensitivities to temperature for the Northeast, although it severely underestimates them in some summer months over the Mid-Atlantic, in part due to excessively warm temperatures above which O3 production saturates in the model. Combining modeled daily Tmax biases with a conservative observation-based O3 sensitivity estimate we find that modeled temperature biases may explain as much as 5–15 ppb of the MDA8 O3 bias in August and September, though cannot account for the majority of the bias.

We conduct an integrated analysis of observational records from satellite, ozonesonde and ground-based networks with the GFDL AM3 global chemistry-climate model to examine the role of stratosphere-to-troposphere transport and Asian emissions in controlling near surface ozone over western North America in the past 30 years (1980-2010), including extreme episodes, interannual variability, and long-term changes. AM3 is nudged to reanalysis winds to allow for exact space-time comparisons with the observational datasets. For the 2010 NOAA CalNex field campaign, the AM3 simulations were employed at both C48 (~200 km) and C180 (~50 km) horizontal resolution. We will discuss the key synoptic to meso-scale processes governing the transport of stratospheric and Asian ozone into western U.S. surface air and the ability of AM3 to reproduce these processes. We further explore the role of El Nino-Southern Oscillation (ENSO) on modulating the interannual variability of tropospheric ozone. We expect that our analysis should provide insights regarding potential responses of ground-level ozone to climate shifts as well as inform air quality planning and control strategies to attain the national standard.

Identifying Robust Cloud Feedbacks in Observations and Models

Climate risks and development: the challenge of carbon offsets, climate adaptation and food security

The role of the winds in past climate change and CO2

State climate offices (SCOs) provide extensive climate services to meet the local needs of citizens and decision makers. As a multi-tiered, integrative national climate services program continues to evolve, SCOs remain well positioned to both benefit from and contribute to the increasing importance associated with such critical stakeholder needs that often extend down to county and municipal levels. Activities of the Office of the New Jersey State Climatologist (ONJSC) are used to demonstrate how these needs are being met as we fulfill our mission of: 1) gathering, archiving and disseminating NJ weather and climate observations, 2) conducting and fostering research associated with NJ’s weather and climate, and 3) providing critical climate outreach to those seeking assistance. The ONJSC attempts to meet the needs of organizations and individuals throughout the state who seek weather and climate data, assessments of weather and climate impacts, and a better understanding of climate variability and change. The stakeholder-driven ONJSC program embodies and visibly demonstrates the mission and spirit of our state university. It is these sorts of local climate services provided by SCOs that make for a rich, rewarding and ever expanding role of these offices in ensuring the health, safety and prosperity of all sectors of our populations.

The Recurrent Ice Ages: Tests for Climate Models

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Sea Ice in NCEP

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Using underwater gliders to observe the ocean: What have we learned so far?

The rapid warming of the North Atlantic in the mid 1990s: mechanisms and prediction

Climate uncertainty: moving from 'what' to 'when'

Strong winds associated to Tropical Cyclones (TCs) trigger intense mixing in the upper ocean. While the resulting surface cooling feeds back negatively on TCs intensity, the associated sub-surface warming has been suggested to substantially modify the ocean heat transport. A ½° global ocean model experiment that realistically samples the ocean response to more than 3,000 TCs over the last 30 years is used to first investigate the processes controlling the TC-induced surface cooling at the local scale and then to assess the impact of TCs at the global scale. Vertical mixing is the dominant process of the cooling occurring locally close to the TC track. I will show that the cooling magnitude can be described by combining an index measuring the storm’s power and an index measuring the resistance to surface cooling by upper-ocean stratification. The cooling is very sensitive to the pre-storm upper-ocean stratification, which can modulate its amplitude by up to an order of magnitude for a given storm’s power. The processes explaining the surface cooling under TCs also participates to modify the mean ocean heat budget. Previous studies have focused on the climatic importance of TC-induced mixing, but cooling is increasingly due to surface heat fluxes as we consider larger space scales. Both heat fluxes and vertical advection associated to TCs are shown to also influence the ocean mean state. Vertical mixing does induce an enhanced ocean heat uptake consistent with previous estimates. However, most of the heat injected into the ocean during TC seasons is re-entrained by the winter mixed layer deepening. As a consequence, we find that the main TCs’ climatological impact is to reduce the amplitude of surface temperature seasonal cycle more than to modify the ocean heat transport.

Quantifying uncertainty in predictions of 21st century warming

Climate change commitment and reversibility

Diagnosing and reducing spurious numerical mixing in OGCMs

Yoshimitsu Chikamoto (AORI, Univ of Tokyo) title: Overview of decadal climate prediction using a coupled climate model MIROC

Using two fully coupled ocean-atmosphere models (GFDL-CM2.1: our IPCC-AR4 model and basis of GFDL's experimental seasonal to decadal forecast system, and CM2.5: a new high-resolution global climate model based on CM2.1), the tropical Atlantic biases in the mean state, the seasonal cycle, and the interannual variations were investigated. Many aspects of the simulation are significantly improved in CM2.5 relative to CM2.1-yet others persist. CM2.5 successfully reproduces the annual mean and the seasonal cycle of the rainfall over the Sahel and the northern South America, a subsurface doming of the thermocline in the northeastern tropical Atlantic (known as the Guinea Dome), and the seasonal phase-locking of the interannual variations of the northern tropical Atlantic. This marked improvement is mainly due to a significant reduction of some biases in the seasonal meridional migration of the Intertropical Convergence Zone (ITCZ). Also, the idealized climate change response of the northern tropical Atlantic has been explored, using outputs from present-day Control and carbon dioxide doubling (2 times CO2) experiments with GFDL-CM2.5. We find that the interannual variations show a significant response to CO2 doubling: the seasonal peak of the interannual variations of the SST over the northern tropical Atlantic moves from boreal spring to early boreal summer, at which time it is about 25% stronger than in the Control run. This change in the character of interannual variability could be a factor in understanding the year-to-year risk of serious damages associated with the Atlantic hurricane in a future climate.

The leading, interdecadal eigenmode of the AMOC in a hierarchy of ocean and climate models

The Madden-Julian oscillation (MJO) is arguably the most important mode of natural variability in the climate system with time scales between days and decades whose underlying mechanisms remain almost completely obscure. Some of us have come to the view, based on multiple lines of evidence, that the MJO is a "moisture mode". This means that its growth and propagation are controlled by the factors that control large-scale anomalies in the moisture field. Some aspects of this idea can be illustrated by simulations with appropriately tuned climate models. We are still struggling with the construction of an idealized mathematical model (a "theory") which can show more explicitly how the mode works and why the properties of the observed MJO emerge.