bluuebunny/crossref_metadata_2025_split huggingface dataset:
Submonthly Polar Vortex Variability and Stratosphere–Troposphere Coupling in the Arctic
Authors: Black Robert X. , McDaniel Brent A. 
Published: June 2009

Abstract
A principal component analysis is performed to characterize intraseasonal variability in the boreal stratospheric polar vortex. In contrast to previous studies, the current analysis examines daily zonal-mean variability within a limited spatial domain encompassing the stratospheric polar vortex. The leading EOFs are vertically coherent north–south dipoles in the zonal-mean zonal wind extending through the lower stratosphere. The first mode represents variability in polar vortex strength and is highly correlated with the stratospheric northern annular mode (SNAM). The second mode, the polar annular mode (PAM), represents variability in the latitudinal position of the polar vortex and possesses a poleward-retracted dipole anomaly structure. Composite analyses indicate that large-amplitude PAM events are relatively short lived (1–2 weeks) compared to SNAM events (1 month or longer). Trend analyses further reveal that recent decadal trends in the boreal polar vortex project more strongly onto PAM than SNAM.
Composite analyses illustrate that the time evolution of sudden stratospheric warming events is dominated by SNAM, whereas SNAM and PAM play approximately equal roles in final warming events. Linear regression analyses reveal that SNAM and PAM result in circumpolar circulation and temperature anomalies of similar magnitudes within the high-latitude troposphere. It is concluded that PAM represents a previously unrecognized annular mode that strongly couples the stratosphere and troposphere on submonthly time scales at mid- to high latitudes. It is further suggested that the SNAM/PAM framework provides a means for isolating the proximate tropospheric response to respective variations in the strength and position of the stratospheric polar vortex.
Amazon Deforestation and Climate Change in a Coupled Model Simulation
Authors: Nobre Paulo , Malagutti Marta , Urbano Domingos F. , de Almeida Roberto A. F. , Giarolla Emanuel 
Published: June 2009

Abstract
The effects of Amazon deforestation on climate change are investigated using twin numerical experiments of an atmospheric general circulation model (AGCM) with prescribed global sea surface temperature and the same AGCM coupled to an ocean GCM (CGCM) over the global tropics. An ensemble approach is adopted, with 10-member ensemble averages of a control simulation compared with perturbed simulations for three scenarios of Amazon deforestation. The latest 20 yr of simulation from each experiment are analyzed. Local surface warming and rainfall reduction are simulated by both models over the Amazon basin. The coupled model presented a rainfall reduction that is nearly 60% larger compared to its control run than those obtained by the AGCM. The results also indicated that both the fraction of the deforested area and the spatial continuity of the vegetated area might be important for modulating global climate variability and change. Additionally, significant remote atmospheric responses to Amazon deforestation scenarios are detected for the coupled simulations, which revealed global ocean and atmosphere circulation changes conducive to enhanced ocean–atmosphere variability over the Pacific Ocean. This, in turn, is interpreted as a manifestation of enhanced El Niño–Southern Oscillation (ENSO) activity over the Pacific and a positive feedback contributing to the extra rainfall reduction over the Amazon on the coupled simulations.
Historical SAM Variability. Part I: Century-Length Seasonal Reconstructions*
Authors: Jones Julie M. , Fogt Ryan L. , Widmann Martin , Marshall Gareth J. , Jones Phil D. , Visbeck Martin 
Published: June 2009

Abstract
Seasonal reconstructions of the Southern Hemisphere annular mode (SAM) index are derived to extend the record before the reanalysis period, using station sea level pressure (SLP) data as predictors. Two reconstructions using different predictands are obtained: one [Jones and Widmann (JW)] based on the first principal component (PC) of extratropical SLP and the other (Fogt) on the index of Marshall. A regional-based SAM index (Visbeck) is also considered.
These predictands agree well post-1979; correlations decline in all seasons except austral summer for the full series starting in 1958. Predictand agreement is strongest in spring and summer; hence agreement between the reconstructions is highest in these seasons. The less zonally symmetric SAM structure in winter and spring influences the strength of the SAM signal over land areas, hence the number of stations included in the reconstructions. Reconstructions from 1865 were, therefore, derived in summer and autumn and from 1905 in winter and spring.
This paper examines the skill of each reconstruction by comparison with observations and reanalysis data. Some of the individual peaks in the reconstructions, such as the most recent in austral summer, represent a full hemispheric SAM pattern, while others are caused by regional SLP anomalies over the locations of the predictors. The JW and Fogt reconstructions are of similar quality in summer and autumn, while in winter and spring the Marshall index is better reconstructed by Fogt than the PC index is by JW. In spring and autumn the SAM shows considerable variability prior to recent decades.
Seasonal Variations of Yellow Sea Fog: Observations and Mechanisms*
Authors: Zhang Su-Ping , Xie Shang-Ping , Liu Qin-Yu , Yang Yu-Qiang , Wang Xin-Gong , Ren Zhao-Peng 
Published: June 2009

Abstract
Sea fog is frequently observed over the Yellow Sea, with an average of 50 fog days on the Chinese coast during April–July. The Yellow Sea fog season is characterized by an abrupt onset in April in the southern coast of Shandong Peninsula and an abrupt, basin-wide termination in August. This study investigates the mechanisms for such steplike evolution that is inexplicable from the gradual change in solar radiation. From March to April over the northwestern Yellow Sea, a temperature inversion forms in a layer 100–350 m above the sea surface, and the prevailing surface winds switch from northwesterly to southerly, both changes that are favorable for advection fog. The land–sea contrast is the key to these changes. In April, the land warms up much faster than the ocean. The prevailing west-southwesterlies at 925 hPa advect warm continental air to form an inversion over the western Yellow Sea. The land–sea differential warming also leads to the formation of a shallow anticyclone over the cool Yellow and northern East China Seas in April. The southerlies on the west flank of this anticyclone advect warm and humid air from the south, causing the abrupt fog onset on the Chinese coast. The lack of such warm/moist advection on the east flank of the anticyclone leads to a gradual increase in fog occurrence on the Korean coast. The retreat of Yellow Sea fog is associated with a shift in the prevailing winds from southerly to easterly from July to August. The August wind shift over the Yellow Sea is part of a large-scale change in the East Asian–western Pacific monsoons, characterized by enhanced convection over the subtropical northwest Pacific and the resultant teleconnection into the midlatitudes, the latter known as the western Pacific–Japan pattern. Back trajectories for foggy and fog-free air masses support the results from the climatological analysis.
Physical Mechanisms Linking the Winter Pacific–North American Teleconnection Pattern to Spring North American Snow Depth
Authors: Ge Yan , Gong Gavin , Frei Allan 
Published: June 2009

Abstract
The wintertime Pacific–North American (PNA) teleconnection pattern has previously been shown to influence springtime snow conditions over portions of North America. This paper develops a more complete physical understanding of this linkage across the continent, using a recently released long-term, continental-scale gridded North American snow depth dataset and the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis data. An empirical orthogonal function–based filtering process is used to identify and isolate the interannual snow depth variations associated with PNA. Then linear and partial correlations are employed to investigate the physical mechanisms that link winter PNA with spring snow depth. In the positive phase of PNA, the enhanced PNA pressure centers lead to warmer temperatures over northwestern North America and less precipitation at midlatitudes. The temperature and precipitation pathways act independently and in distinct geographical regions, and together they serve to reduce winter snow depth across much of North America. Winter anomalies in the snow depth field then tend to persist into spring. Dynamic mechanisms responsible for the PNA-influenced North American precipitation and temperature anomalies, involving moisture transport and cold air intrusions, are confirmed in this study and also extended to continental snow depth anomalies.
Maintenance of Lower Tropospheric Temperature Inversion in the Saharan Air Layer by Dust and Dry Anomaly
Authors: Wong Sun , Dessler Andrew E. , Mahowald Natalie M. , Yang Ping , Feng Qian 
Published: June 2009

Abstract
The role of Saharan dust and dry anomaly in maintaining the temperature inversion in the Saharan air layer (SAL) is investigated. The dust aerosol optical thickness (AOT) in the SAL is inferred from the measurements taken by Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and the corresponding temperature and specific humidity anomalies are identified using the National Centers for Environmental Prediction (NCEP) data in August–September over the North Atlantic tropical cyclone (TC) main development region (MDR; 10°–20°N, 40°–60°W). The authors also study the SAL simulated in the National Center of Atmospheric Research (NCAR) Community Atmosphere Model, version 3 (CAM3), coupled with dust radiative effect. It is found that higher AOT is associated with warmer and dryer anomalies below 700 hPa, which increases the atmospheric stability. The calculated instantaneous radiative heating anomalies from a radiative transfer model indicate that both the dust and low humidity are essential to maintaining the temperature structure in the SAL against thermal relaxation. At 850 hPa, heating anomalies caused by both the dust and dry anomalies (for AOT &gt; 0.8) are 0.2–0.4 K day−1. The dust heats the atmosphere below 600 hPa, while the dry anomaly cools the atmosphere below 925 hPa, resulting in a peak of heating rate anomaly located at 700–850 hPa. In the eastern Atlantic, dust contributes about 50% of the heating rate anomaly. Westward of 40°W, when the dust content becomes small (AOT &lt; 0.6), the heating rates are more sensitive to the water vapor profile used in the radiative transfer calculation. Retrieving or simulating correct water vapor profiles is essential to the assessment of the SAL heating budgets in regions where the dust content in the SAL is small.
Warm Season Variations in the Low-Level Circulation and Precipitation over the Central United States in Observations, AMIP Simulations, and Idealized SST Experiments
Authors: Weaver Scott J. , Schubert Siegfried , Wang Hailan 
Published: June 2009

Abstract
Sea surface temperature (SST) linkages to central U.S. low-level circulation and precipitation variability are investigated from the perspective of the Great Plains low-level jet (GPLLJ) and recurring modes of SST variability. The observed and simulated links are first examined via GPLLJ index regressions to precipitation, SST, and large-scale circulation fields in the NCEP–NCAR and North American Regional Reanalysis (NARR) reanalyses, and NASA’s Seasonal-to-Interannual Prediction Project (NSIPP1) and Community Climate Model, version 3 (CCM3) ensemble mean Atmospheric Model Intercomparison Project (AMIP) simulations for the 1949–2002 (1979–2002 for NARR) period. Characteristics of the low-level circulation and its related precipitation are further examined in the U.S. Climate Variability and Predictability (CLIVAR) Drought Working Group idealized climate model simulations (NSIPP1 and CCM3) forced with varying polarities of recurring modes of SST variability.
It is found that the observed and simulated correlations of the GPLLJ index to Atlantic and Pacific SST, large-scale atmospheric circulation, and Great Plains precipitation variability for 1949–2002 are robust during the July–September (JAS) season and show connections to a distinct global-scale SST variability pattern, one similar to that used in forcing the NSIPP1 and CCM3 idealized simulations, and a subtropical Atlantic-based sea level pressure (SLP) anomaly with a maximum over the Gulf of Mexico. The idealized simulations demonstrate that a warm Pacific and/or a cold Atlantic are influential over regional hydroclimate features including the monthly preference for maximum GPLLJ and precipitation in the seasonal cycle. Furthermore, it appears that the regional expression of globally derived SST variability is important for generating an anomalous atmospheric low-level response of consequence to the GPLLJ, especially when the SST anomaly is positioned over a regional maximum in climatological SST, and in this case the Western Hemisphere warm pool.
Impact of Climate Change on Stratospheric Sudden Warmings as Simulated by the Canadian Middle Atmosphere Model
Authors: McLandress Charles , Shepherd Theodore G. 
Published: June 2009

Abstract
The dynamics of Northern Hemisphere major midwinter stratospheric sudden warmings (SSWs) are examined using transient climate change simulations from the Canadian Middle Atmosphere Model (CMAM). The simulated SSWs show good overall agreement with reanalysis data in terms of composite structure, statistics, and frequency. Using observed or model sea surface temperatures (SSTs) is found to make no significant difference to the SSWs, indicating that the use of model SSTs in the simulations extending into the future is not an issue. When SSWs are defined by the standard (wind based) definition, an absolute criterion, their frequency is found to increase by ∼60% by the end of this century, in conjunction with a ∼25% decrease in their temperature amplitude. However, when a relative criterion based on the northern annular mode index is used to define the SSWs, no future increase in frequency is found. The latter is consistent with the fact that the variance of 100-hPa daily heat flux anomalies is unaffected by climate change. The future increase in frequency of SSWs using the standard method is a result of the weakened climatological mean winds resulting from climate change, which make it easier for the SSW criterion to be met. A comparison of winters with and without SSWs reveals that the weakening of the climatological westerlies is not a result of SSWs. The Brewer–Dobson circulation is found to be stronger by ∼10% during winters with SSWs, which is a value that does not change significantly in the future.
Relationship between Winter/Spring Snowfall and Summer Precipitation in the Northern Great Plains of North America
Authors: Quiring Steven M. , Kluver Daria B. 
Published: June 2009

Abstract
On the basis of snowfall observations from 1929 to 1999, positive (negative) snowfall anomalies are associated with wetter (drier) than normal conditions during the summer [July–August (JJA)] in the northern Great Plains. The five driest summers are associated with negative snowfall anomalies during the preceding winter (−66.7 mm) and spring (−62.4 mm) that cover most of the study region (∼85%). Snowfall anomalies during the late spring (April–May) are more important for determining summer moisture conditions than snowfall anomalies in fall [September–November (SON)] or winter [December–February (DJF)]. The link between snowfall anomalies and summer moisture conditions appears to be, at least partly, through soil moisture since positive (negative) snowfall anomalies are associated with wetter (drier) soils, a later (earlier) date of snowmelt, cooler (warmer) air temperatures, and more (less) evaporation during spring and summer. However, the relationship between spring snowfall and summer moisture conditions is only statistically significant when the moisture anomaly index (Z), which accounts for both temperature and precipitation, is used to characterize summer moisture conditions and the signal is weak when just considering precipitation (e.g., standardized precipitation index). Results also indicate that the strength of the relationship between winter/spring snowfall and summer moisture varies significantly over space and time, which limits its utility for seasonal forecasting.
LMODEL: A Satellite Precipitation Methodology Using Cloud Development Modeling. Part I: Algorithm Construction and Calibration
Authors: Bellerby Tim , Hsu Kuo-lin , Sorooshian Soroosh 
Published: June 2009

Abstract
The Lagrangian Model (LMODEL) is a new multisensor satellite rainfall monitoring methodology based on the use of a conceptual cloud-development model that is driven by geostationary satellite imagery and is locally updated using microwave-based rainfall measurements from low earth-orbiting platforms. This paper describes the cloud development model and updating procedures; the companion paper presents model validation results. The model uses single-band thermal infrared geostationary satellite imagery to characterize cloud motion, growth, and dispersal at high spatial resolution (∼4 km). These inputs drive a simple, linear, semi-Lagrangian, conceptual cloud mass balance model, incorporating separate representations of convective and stratiform processes. The model is locally updated against microwave satellite data using a two-stage process that scales precipitable water fluxes into the model and then updates model states using a Kalman filter. Model calibration and updating employ an empirical rainfall collocation methodology designed to compensate for the effects of measurement time difference, geolocation error, cloud parallax, and rainfall shear.
Wave Modeling—Missing the Peaks
Authors: Cavaleri Luigi 
Published: June 2009

Abstract
The paper analyzes the capability of the present wave models of properly reproducing the conditions during and at the peak of severe and extreme storms. After providing evidence that this is often not the case, the reasons for it are explored. First, the physics of waves considered in wave models is analyzed. Although much improved with respect to the past, the wind accuracy is still a relevant factor at the peak of the storms. Other factors such as wind variability and air density are considered. The classical theory of wave generation by J. W. Miles’s mechanism, with subsequent modifications, is deemed not sufficiently representative of extreme conditions. The presently used formulations for nonlinear energy transfer are found to lead to too wide distributions in frequency and direction, hence reducing the input by wind. Notwithstanding some recent improvements, the white-capping formulation still depends on parameters fitted to the bulk of the data. Hence, it is not obvious how they will perform in extreme conditions when the physics is likely to be different.
Albeit at different levels in different models, the advection still implies the spreading of energy, hence a spatial smoothing of the peaks. The lack of proper knowledge of the ocean currents is found to substantially affect the identification of how much energy can—in some cases—be concentrated at a given time and location. The implementation of the available theories and know-how in the present wave models are often found inconsistent from model to model. It follows that in this case, it is not possible to exchange corresponding pieces of software between two models without substantially affecting the quality of the results.
After analyzing various aspects of a wave model, the paper makes some general considerations. Because wave growth is the difference between processes (input and output) involving large amounts of energy, it is very sensitive to small modifications of one or more processes. Together with the strong, but effective, tuning present in a wave model, this makes the introduction of new physics more complicated. It is suggested that for long-term improvements, operational and experimental applications need to proceed along parallel routes, with the latter looking more to the physics without the necessity of an immediately improved overall performance.
In view of the forthcoming increase of computer power, a sensitivity study is suggested to identify the most critical areas in a wave model to determine where to invest for further improvements.
The limits on the description of the physics of the processes when using the spectral approach, particularly in extreme conditions, are considered. For further insights and as a way to validate the present theories in these conditions, the use is suggested of numerical experiments simulating in great detail the physical interaction between the lower atmosphere and the single waves.
High-Spectral- and High-Temporal-Resolution Infrared Measurements from Geostationary Orbit
Authors: Schmit Timothy J. , Li Jun , Ackerman Steven A. , Gurka James J. 
Published: June 2009

Abstract
The first of the next-generation series of the Geostationary Operational Environmental Satellite (GOES-R) is scheduled for launch in 2015. The new series of GOES will not have an infrared (IR) sounder dedicated to acquiring high-vertical-resolution atmospheric temperature and humidity profiles. High-spectral-resolution sensors have a much greater vertical-resolving power of temperature, moisture, and trace gases than low-spectral-resolution sensors. Because of coarse vertical resolution and limited accuracy in the legacy sounding products from the current GOES sounders, placing a high-spectral-resolution IR sounder with high temporal resolution in the geostationary orbit can provide nearly time-continuous three-dimensional moisture and wind profiles. This would allow substantial improvements in monitoring the mesoscale environment for severe weather forecasting and other applications. Application areas include nowcasting (and short-term forecasts) and numerical weather prediction, which require products such as atmospheric moisture and temperature profiles as well as derived parameters, clear-sky radiances, vertical profiles of atmospheric motion vectors, sea surface temperature, cloud-top properties, and surface properties. Other application areas include trace gases/air quality, dust detection and characterization, climate, and calibration. This paper provides new analysis that further documents the available information regarding the anticipated improvements and their benefits.