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Melissa A. Burt, David A. Randall, and Mark D. Branson

Abstract

As the Arctic sea ice thins and ultimately disappears in a warming climate, its insulating power decreases. This causes the surface air temperature to approach the temperature of the relatively warm ocean water below the ice. The resulting increases in air temperature, water vapor, and cloudiness lead to an increase in the surface downwelling longwave radiation (DLR), which enables a further thinning of the ice. This positive ice–insulation feedback operates mainly in the autumn and winter. A climate change simulation with the Community Earth System Model shows that, averaged over the year, the increase in Arctic DLR is 3 times stronger than the increase in Arctic absorbed solar radiation at the surface. The warming of the surface air over the Arctic Ocean during fall and winter creates a strong thermal contrast with the colder surrounding continents. Sea level pressure falls over the Arctic Ocean, and the high-latitude circulation reorganizes into a shallow “winter monsoon.” The resulting increase in surface wind speed promotes stronger surface evaporation and higher humidity over portions of the Arctic Ocean, thus reinforcing the ice–insulation feedback.

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Mark C. Serreze, Martyn P. Clark, David L. McGinnis, and David A. Robinson

Abstract

Monthly data from 206 stations for the period 1947–93 are used to examine characteristics of snowfall over the eastern half of the United States and relationships with precipitation and the maximum temperature on precipitation days. Linkages between snowfall and modes of low-frequency circulation variability are diagnosed through composite analyses, based on results from a rotated Principal Component Analysis (PCA) of monthly 500-hPa geopotential height. Results are examined for the 2-month windows of November–December, January–February, and March–April. The three dominant PCAs for each window capture regional components of the Pacific–North American (PNA), Tropical-Northern Hemisphere (TNH), and east Pacific (EP) teleconnection patterns.

Two general snowfall regimes are identified: 1) the dry and cold upper midwest, Nebraska and Kansas, where snowfall is strongly a function of precipitation; and 2) the Midwest, southeast, and northeast, where snowfall is more closely tied to the mean maximum temperature on precipitation days. The PNA (the dominant circulation mode) and the EP pattern are both associated with strong snowfall signals, best expressed for November–December and January–February. Snowfall for the PNA over the southeast, midwest, and mid-Atlantic states increases (decreases) under positive (negative) extremes, when the eastern United States is dominated by a strong 500-hPa trough (zonal flow or weak ridge) with associated lower (higher) precipitation-day temperatures. Snowfall signals are more extensive under positive PNA extremes where the lower temperatures have a greater impact on precipitation phase. An opposing precipitation-controlled snowfall signal is found over the upper Midwest. The positive phase of the EP pattern, describing a western ridge–eastern trough, is associated with negative snowfall signals clustered over the midwest and upper midwest. Opposing signals are found under the midwestern trough–eastern ridge pattern of the negative mode. These signals are primarily precipitation controlled, which for the Midwest are counter to the climatological control by temperature. TNH snowfall signals are fairly weak except for March–April, when significant differences are found for the upper Midwest and from Missouri northeast into New England. No coherent trends are observed in snowfall or in the strength of the circulation patterns derived from the PCA.

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Charlotte A. DeMott, Cristiana Stan, David A. Randall, and Mark D. Branson

Abstract

The interaction of ocean coupling and model physics in the simulation of the intraseasonal oscillation (ISO) is explored with three general circulation models: the Community Atmospheric Model, versions 3 and 4 (CAM3 and CAM4), and the superparameterized CAM3 (SPCAM3). Each is integrated coupled to an ocean model, and as an atmosphere-only model using sea surface temperatures (SSTs) from the coupled SPCAM3, which simulates a realistic ISO. For each model, the ISO is best simulated with coupling. For each SST boundary condition, the ISO is best simulated in SPCAM3.

Near-surface vertical gradients of specific humidity, (temperature, ), explain ~20% (50%) of tropical Indian Ocean latent (sensible) heat flux variance, and somewhat less of west Pacific variance. In turn, local SST anomalies explain ~5% (25%) of variance in coupled simulations, and less in uncoupled simulations. Ergo, latent and sensible heat fluxes are strongly controlled by wind speed fluctuations, which are largest in the coupled simulations, and represent a remote response to coupling. The moisture budget reveals that wind variability in coupled simulations increases east-of-convection midtropospheric moistening via horizontal moisture advection, which influences the direction and duration of ISO propagation.

These results motivate a new conceptual model for the role of ocean feedbacks on the ISO. Indian Ocean surface fluxes help developing convection attain a magnitude capable of inducing the circulation anomalies necessary for downstream moistening and propagation. The “processing” of surface fluxes by model physics strongly influences the moistening details, leading to model-dependent responses to coupling.

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Anna Harper, Ian T. Baker, A. Scott Denning, David A. Randall, Donald Dazlich, and Mark Branson

Abstract

Moisture recycling can be an important source of rainfall over the Amazon forest, but this process relies heavily upon the ability of plants to access soil moisture. Evapotranspiration (ET) in the Amazon is often maintained or even enhanced during the dry season, when net radiation is high. However, ecosystem models often over predict the dry season water stress. The authors removed unrealistic water stress in an ecosystem model [the Simple Biosphere Model, version 3 (SiB3)] and examined the impacts of enhanced ET on the dry season climate when coupled to a GCM. The “stressed” model experiences dry season water stress and limitations on ET, while the “unstressed” model has enhanced root water access and exhibits strong drought tolerance.

During the dry season in the southeastern Amazon, SiB3 unstressed has significantly higher latent heat flux (LH) and lower sensible heat flux (SH) than SiB3 stressed. There are two competing impacts on the climate in SiB3 unstressed: cooling resulting from lower SH and moistening resulting from higher LH. During the average dry season, the cooling plays a larger role and the atmosphere is more statically stable, resulting in less precipitation than in SiB3 stressed. During dry season droughts, significantly higher LH in SiB3 unstressed is a necessary but not sufficient condition for stronger precipitation. The moistening effect of LH dominates when the Bowen ratio (BR = SH/LH) is >1.0 in SiB3 stressed and precipitation is up to 26% higher in SiB3 unstressed. An implication of this analysis is that forest conservation could enable the Amazon to cope with drying conditions in the future.

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David A. Robinson, Mark C. Serreze, Roger G. Barry, Greg Scharfen, and George Kukla

Abstract

Visible-band satellite imagery is used to manually map surface brightness changes over sea ice throughout the Arctic Basin from May to mid-August over a 10-yr period. These brightness changes are primarily due to snowmelt atop the ice cover. Using image processor techniques, parameterized albedos are estimated for each brightness class. Snowmelt begins in May in the marginal seas, progressing northward with time, finally commencing near the pole in late June. large year-to-year differences are found in the timing of melt, exceeding one month in some regions. Parameterized albedo for most regions of the pack ice exceed 0.70 during May, declines rapidly during June, and reaches a seasonal low of between 0.40 and 0.50 by late July. For August, regional albedos, which also include areas of open water beyond the southern pack ice limit, are up to 0.16 lower than the corresponding values for pack ice areas only.

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David Chapman, Mark A. Cane, Naomi Henderson, Dong Eun Lee, and Chen Chen

Abstract

The authors investigate a sea surface temperature anomaly (SSTA)-only vector autoregressive (VAR) model for prediction of El Niño–Southern Oscillation (ENSO). VAR generalizes the linear inverse method (LIM) framework to incorporate an extended state vector including many months of recent prior SSTA in addition to the present state. An SSTA-only VAR model implicitly captures subsurface forcing observable in the LIM residual as red noise. Optimal skill is achieved using a state vector of order 14–17 months in an exhaustive 120-yr cross-validated hindcast assessment. It is found that VAR outperforms LIM, increasing forecast skill by 3 months, in a 30-yr retrospective forecast experiment.

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John E. Janowiak, Philip A. Arkin, Pingping Xie, Mark L. Morrissey, and David R. Legates

Abstract

Very few (if any) in situ measurements of rainfall are available in the Pacific ITCZ east of the Line Islands (157°W). Hence, climatological datasets, which are assembled from various in situ sources, and satellite-derived analyses of precipitation are frequently relied upon to provide information on the distribution of rainfall in this important region. A substantial amount of disagreement exists among these information sources as demonstrated in this paper. In particular, the east–west gradient of estimated rainfall intensity in the eastern Pacific ITCZ is quite different during the Northern Hemisphere warm season among six different satellite algorithms (one infrared and five microwave) and two climatologies that are examined. Some of these data suggest that a local minimum in rainfall intensity is located near 140°W in the Pacific ITCZ during northern summer, with increasing intensity toward the east and west, while the others depict steadily decreasing rainfall intensity from west of the Americas to the date line. Conversely, all of the precipitation estimates that are examined depict a rainfall maximum in the Pacific ITCZ near 140°W during the Northern Hemisphere cool season, although the magnitudes vary substantially among them.

The authors examine estimates of seasonal mean rainfall over the eastern Pacific ITCZ (cast of the date line) from two rainfall climatologies and six satellite precipitation estimation techniques during July 1987 through June 1990. Inconsistencies among the precipitation analyses are investigated by examining several independent datasets that include atmospheric circulation data, sea surface temperature data, and ship reports of weather type.

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Nathan P. Arnold, Mark Branson, Zhiming Kuang, David A. Randall, and Eli Tziperman

Abstract

The Madden–Julian oscillation (MJO) is the dominant mode of tropical intraseasonal variability, characterized by an eastward-propagating envelope of convective anomalies with a 30–70-day time scale. Here, the authors report changes in MJO activity across coupled simulations with a superparameterized version of the NCAR Community Earth System Model. They find that intraseasonal OLR variance nearly doubles between a preindustrial control run and a run with 4×CO2. Intraseasonal precipitation increases at a rate of roughly 10% per 1 K of warming, and MJO events become 20%–30% more frequent. Moist static energy (MSE) budgets of composite MJO events are calculated for each scenario, and changes in budget terms are used to diagnose the physical processes responsible for changes in the MJO with warming. An increasingly positive contribution from vertical advection is identified as the most likely cause of the enhanced MJO activity. A decomposition links the changes in vertical advection to a steepening of the mean MSE profile, which is a robust thermodynamic consequence of warming. Surface latent heat flux anomalies are a significant sink of MJO MSE at 1×CO2, but this damping effect is reduced in the 4×CO2 case. This work has implications for organized tropical variability in past warm climates as well as future global warming scenarios.

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Ryan C. Scott, Timothy A. Myers, Joel R. Norris, Mark D. Zelinka, Stephen A. Klein, Moguo Sun, and David R. Doelling

Abstract

Understanding how marine low clouds and their radiative effects respond to changing meteorological conditions is crucial to constrain low-cloud feedbacks to greenhouse warming and internal climate variability. In this study, we use observations to quantify the low-cloud radiative response to meteorological perturbations over the global oceans to shed light on physical processes governing low-cloud and planetary radiation budget variability in different climate regimes. We assess the independent effect of perturbations in sea surface temperature, estimated inversion strength, horizontal surface temperature advection, 700-hPa relative humidity, 700-hPa vertical velocity, and near-surface wind speed. Stronger inversions and stronger cold advection greatly enhance low-level cloudiness and planetary albedo in eastern ocean stratocumulus and midlatitude regimes. Warming of the sea surface drives pronounced reductions of eastern ocean stratocumulus cloud amount and optical depth, and hence reflectivity, but has a weaker and more variable impact on low clouds in the tropics and middle latitudes. By reducing entrainment drying, higher free-tropospheric relative humidity enhances low-level cloudiness. At low latitudes, where cold advection destabilizes the boundary layer, stronger winds enhance low-level cloudiness; by contrast, wind speed variations have weak influence at midlatitudes where warm advection frequently stabilizes the marine boundary layer, thus inhibiting vertical mixing. These observational constraints provide a framework for understanding and evaluating marine low-cloud feedbacks and their simulation by models.

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Chen Chen, Mark A. Cane, Naomi Henderson, Dong Eun Lee, David Chapman, Dmitri Kondrashov, and Mickaël D. Chekroun

Abstract

A suite of empirical model experiments under the empirical model reduction framework are conducted to advance the understanding of ENSO diversity, nonlinearity, seasonality, and the memory effect in the simulation and prediction of tropical Pacific sea surface temperature (SST) anomalies. The model training and evaluation are carried out using 4000-yr preindustrial control simulation data from the coupled model GFDL CM2.1. The results show that multivariate models with tropical Pacific subsurface information and multilevel models with SST history information both improve the prediction skill dramatically. These two types of models represent the ENSO memory effect based on either the recharge oscillator or the time-delayed oscillator viewpoint. Multilevel SST models are a bit more efficient, requiring fewer model coefficients. Nonlinearity is found necessary to reproduce the ENSO diversity feature for extreme events. The nonlinear models reconstruct the skewed probability density function of SST anomalies and improve the prediction of the skewed amplitude, though the role of nonlinearity may be slightly overestimated given the strong nonlinear ENSO in GFDL CM2.1. The models with periodic terms reproduce the SST seasonal phase locking but do not improve the prediction appreciably. The models with multiple ingredients capture several ENSO characteristics simultaneously and exhibit overall better prediction skill for more diverse target patterns. In particular, they alleviate the spring/autumn prediction barrier and reduce the tendency for predicted values to lag the target month value.

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