Abstract

This study used both observations and global climate model simulations to investigate the characteristics of winter extreme snowfall events along the coast (the Interstate 95 corridor) of the northeast United States where several mega-cities are located. Observational analyses indicate that, during 1980–2015, 110 events occurred when four coastal cities—Boston, New York City, Philadelphia, and Washington, D.C.—had either individually or collectively experienced daily snowfall exceeding the local 95th percentile thresholds. Boston had the most events, with a total of 69, followed by 40, 36, and 30 (moving southward) in the other three cities. The associated circulations at 200 and 850 hPa were categorized via K-means clustering. The resulting three composite circulations are characterized by the strength and location of the jet at 200 hPa and the coupled low pressure system at 850 hPa: a strong jet overlying the cities coupled with an inland trough, a weak and slightly southward shifted jet coupled with a cyclone at the coast, and a weak jet stream situated to the south of the cities coupled with a cyclone over the coastal oceans. Comparative analyses were also conducted using the GFDL High Resolution Atmospheric Model (HiRAM) simulation of the same period. Although the simulated extreme events do not provide one-to-one correspondence with observations, the characteristics nevertheless show consistency notably in total number of occurrences, intraseasonal and multiple-year variations, snow spatial coverage, and the associated circulation patterns. Possible future change in extreme snow events was also explored utilizing the HiRAM RCP8.5 (2075–2100) simulation. The analyses suggest that a warming global climate tends to decrease the extreme snowfall events but increase extreme rainfall events.

Abstract

This study uses the atmospheric general circulation model (AGCM) ECHAM5 coupled with the newly developed Snow–Ice–Thermocline model (ECHAM5-SIT) to examine the effects of orography and land–sea contrast on the Madden–Julian oscillation (MJO) in the Maritime Continent (MC) during boreal winter. The ECHAM5-SIT is one of the few AGCMs that realistically simulate the major characteristics of the MJO. Three experiments are conducted with realistic topography, without orography, and with oceans only in the MC region to evaluate the relative effects of orography and land–sea contrast. Orography and land–sea contrast have the following effects on the MJO in the MC: 1) a larger amplitude, 2) a smaller zonal scale, 3) more realistic periodicity and stronger eastward-propagating signals, 4) a stronger southward detour during the eastward propagation, 5) a distorted coupled Kelvin–Rossby wave structure, and 6) larger low-level moisture convergence. The existence of mountainous islands also enhances the mean westerly in the eastern Indian Ocean and the western MC, as well as the moisture content over the MC. This enhancement of mean states contributes to the stronger eastward-propagating MJO. The findings herein suggest that theoretical and empirical studies, which are largely derived from an aquaplanet framework, have likely provided an oversimplified view of the MJO. The effects of mountainous islands should be considered for better understanding and more accurate forecast of the MJO.

Abstract

Observations indicate that the East Asian summer monsoon (EASM) exhibits distinctive characteristics of large cloud amounts with associated heavy and persistent rainfall, although short breaks for clear sky usually occur. Consequently, the effects of cloud–radiation interactions can play an important role in the general circulation of the atmosphere and, thus, the evolution of the EASM. In this note, as a first step toward studying the topic, the 5-yr (January 1985–December 1989) Earth Radiation Budget Experiment (ERBE) dataset is used to show the spatial and temporal patterns of both shortwave (SW) and longwave (LW) cloud radiative forcing (CRF) at the top of the atmosphere over east China, and to compare the observed features with Atmospheric Model Intercomparison Project-II (AMIP-II) simulations with the University at Albany, State University of New York (SUNYA) Community Climate Model 3 (CCM3) and the ECHAM4 general circulation models.

The observations indicate that the net CRF provides a cooling effect to the atmosphere–surface climate system, dominated by the SW CRF cooling (albedo effect) with partial compensation from the LW CRF warming (greenhouse effect). The SW CRF shows a strong seasonal cycle, and its peak magnitude is particularly large, ∼110 W m⁻², for south China and the Yangtze–Huai River valley (YHRV) during May and June, while the LW CRF is about 50 W m⁻² for the same months with a weak dependence on the latitudes and seasons. These characteristics are in sharp contrast to the Northern Hemispheric zonal means of the same latitude bands and seasons, thus implying a unique role for cloud–radiation interaction in east China. Both model simulations show similar observed characteristics, although biases exist. For example, in May, the ECHAM4 underestimates the SW CRF while the SUNYA CCM3 simulates a significantly larger value, both attributed to the respective biases in the simulated total cloud cover. Model-to-observation comparisons of the association between total cloud cover and SW CRF, and between high cloud cover and LW CRF, are also presented and their differences are discussed. Finally, the SUNYA CCM3 biases in the CRF and its relevance to the model cloud biases are discussed in the context of model cold and dry biases in climate simulations.

Constellations of driftsonde systems— gondolas floating in the stratosphere and able to release dropsondes upon command— have so far been used in three major field experiments from 2006 through 2010. With them, high-quality, high-resolution, in situ atmospheric profiles were made over extended periods in regions that are otherwise very difficult to observe. The measurements have unique value for verifying and evaluating numerical weather prediction models and global data assimilation systems; they can be a valuable resource to validate data from remote sensing instruments, especially on satellites, but also airborne or ground-based remote sensors. These applications for models and remote sensors result in a powerful combination for improving data assimilation systems. Driftsondes also can support process studies in otherwise difficult locations—for example, to study factors that control the development or decay of a tropical disturbance, or to investigate the lower boundary layer over the interior Antarctic continent. The driftsonde system is now a mature and robust observing system that can be combined with flight-level data to conduct multidisciplinary research at heights well above that reached by current research aircraft. In this article we describe the development and capabilities of the driftsonde system, the exemplary science resulting from its use to date, and some future applications.