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Terrence R. Nathan and Long Li

Abstract

A simple β-plane model that couples radiative transfer, ozone advection, and ozone photochemistry with the quasi-geostrophic dynamical circulation is used to study the diabatic effects of Newtonian cooling and ozone–dynamics interaction on the linear stability of free planetary waves in the atmosphere. Under the assumption that the diabatic processes are sufficiently weak, an analytical expression is derived for the eigenfrequencies of these waves valid for arbitrary vertical distributions of background wind and ozone volume mixing ratio (&gamma¯). This expression shows the following: 1) the influence of meridional ozone advection on wave growth or decay depends on the wave and basic state vertical structures; 2) vertical ozone advection is locally (de)stabilizing when d&gamma¯/dz (>0) < 0, irrespective of the wave or basic state vertical structures; 3) photochemically accelerated cooling, which predominates in the upper stratosphere, augments the Newtonian cooling rate and is stabilizing.

The one-dimensional linear stability problem also is solved numerically for a Charney basic state (constant vertical shear and constant stratification) and for zonal mean basic states constructed from observational data characteristic of each season. It is shown that ozone heating generated by ozone–dynamics interaction in the stratosphere can reduce (enhance) the damping rates due to Newtonian cooling by as much as 50% for planetary waves of large vertical scale and maximum amplitude in the lower (upper) stratosphere. For waves with relatively large density-weighted amplitude in the lower to midstratosphere and small Doppler-shifted frequency, ozone-dynamics interaction in the stratosphere can significantly influence the zonally rectified wave fluxes in the troposphere.

For the summer basic state, adiabatic eastward- and westward-propagating neutral modes having the same zonal scale emerge; both are confined to the lower stratosphere and troposphere. For these modes ozone heating dominates over Newtonian cooling, and the modes amplify with growth rates comparable to those of baroclinically unstable waves of similar spatial scale.

The effects of radiative–photochemical feedbacks on the transient time scales of observed waves in the atmosphere also are discussed.

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Long Li and Terrence R. Nathan

Abstract

The extratropical response to localized, low-frequency tropical forcing is examined using a linearized, non-divergent barotropic model on a sphere. Zonal-mean basic states characterized by solid-body rotation or critical latitudes are considered. An analytical analysis based on WKB and ray tracing methods shows that, in contrast to stationary Rossby waves, westward moving, low-frequency Rossby waves can propagate through the tropical easterlies into the extratropics. It is shown analytically that the difference between the stationary and low-frequency ray paths is proportional to the forcing frequency and inversely proportional to the zonal wavenumber cubed. An expression for the disturbance amplitude is derived that shows the ability of the forced waves to maintain their strength well into middle latitudes depends on their meridional wave scale and northward group velocity, both of which are functions of the slowly varying background flow.

A local energetics analysis shows that the combination of energy dispersion from the forcing region and energy extraction from the equatorward flank of the midlatitude jet produces disturbances that have the greatest impact on the extratropical circulation. Under the assumption that the forcing amplitude is independent of frequency, this impact is largest when the tropical forcing period is in the range 10–20 days.

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Long Li and Terrence R. Nathan

Abstract

A spherical nondivergent barotropic model, linearized about a 300-mb climatological January flow, is used to examine the extratropical response to low-frequency tropical forcing. A two-dimensional WKB analysis shows that the energy propagation depends on the sum of three vectors: the basic state wind vector, a vector that is parallel to the absolute vorticity contours, and the local wave vector. The latter two vectors are functions of the slowly varying background flow and forcing frequency ω. As ω decreases, the ray paths approach that of the local wave vector, so that the energy propagates in a direction perpendicular to the wave fronts. The extratropical jet streams have a stronger influence on the long period (>30 day) ray paths than on those of intermediate period (∼10–30 day).

Global and local energetics calculations show that the energy conversion from the zonally varying basic flow increases as ω decreases. The local energetics show that for the long period disturbances, both the energy conversion and energy redistribution due to advection and pressure work are significant along the North African–Asian jet stream. The long period disturbances are less sensitive to the location of the tropical forcing than those of intermediate period. This provides a plausible explanation for the observations showing that the long period oscillations tend to be geographically fixed at the exits of the extratropical jet streams, whereas those of intermediate period are zonally mobile wave trains. The long (intermediate) timescale disturbances dominate in the Northern (Southern) Hemisphere, where the zonal variations in the basic flow are more (less) pronounced.

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Long Li and John W. Pomeroy

Abstract

The threshold wind speed for snow transport is related to properties of the surface snowpack: snow particle bonding, cohesion, and kinetic friction. These properties are controlled by meteorological factors. A method is proposed that relates the threshold wind speed for the initiation of snow transport to standard surface meteorological observations. A complete dataset on the hourly threshold condition for snow transport as determined from visual observation was developed for 16 stations on the prairies of western Canada over six winters. The threshold wind speeds for wet snow transport are significantly different from those for dry snow transport. The majority of recorded threshold 10-m wind speeds ranged from 7 to 14 m s−1 with an average of 9.9 m s−1 for wet snow transport, and from 4 to 11 m s−1 with an average of 7.7 m s−1 for dry snow transport. The observations display a nonlinear but generally positive correlation between threshold wind speed and air temperature. An empirical model between threshold wind speed and air temperature was developed for dry snow conditions. The model, on average, provides a good estimate of the threshold wind speed.

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Nick Rutter, Don Cline, and Long Li

Abstract

The National Operational Hydrologic Remote Sensing Center (NOHRSC) Snow Model (NSM) is an energy- and mass-balance model used by the National Oceanic and Atmospheric Administration’s National Weather Service for moderate-resolution spatially distributed snow analysis and data assimilation over the United States. The NSM was evaluated in a one-dimensional mode using meteorological and snowpit observations from five sites in Colorado collected during 2002–03. Four parameters estimated by the NSM [snow water equivalent (SWE), snow depth, average snowpack temperature, and snow surface temperature] were compared with snowpit observations and with estimates from another snow energy and mass-balance model, SNTHERM. Root-mean-squared differences (RMSDs) between snowpit SWE observations (January–June) at all sites and estimates from the NSM were about 11% (RMSD = 0.073 m) of the average maximum observed SWE from all sites of 0.694 m. SNTHERM exhibited only a slightly better agreement (RMSD = 0.066 m). During the winter and early spring period before snowpacks became isothermal at 273.15 K, both NSM and SNTHERM simulated significantly cooler average snowpack temperatures than observed (RMSD = 3 and 2 K, respectively). During this snow accumulation period estimates of SWE by both models were very similar. Differences in modeled SWE were traced to short periods (5–21 days) during isothermal conditions in early spring when the two models diverged. These events caused SWE differences that persisted throughout the ablation period and resulted in a range in melt-out times of 0.2–7.2 days between depth observations and modeled estimates. The divergence in SWE resulted from differences in snowmelt fluxes estimated by the two models, which are suggested to result from 1) liquid water fractions within a snowpack being estimated by the NSM using an internal energy method and by SNTHERM using a semiempirical temperature-based approach, and 2) SNTHERM, but not the NSM, accounting for the small liquid water fraction that coexists in equilibrium with snow when the snowpack surface is dry (<273.15 K).

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Shang-Min Long, Gen Li, Kaiming Hu, and Jun Ying

Abstract

Previous studies reveal that the last generation of coupled general circulation models (CGCMs) commonly suffer from the so-called Indian Ocean dipole (IOD)-like biases, lowering the models’ ability in climate prediction and projection. The present study shows that such IOD-like biases are reduced insignificantly or even worsen in CGCMs from phase 5 to phase 6 of the Coupled Model Intercomparison Project (CMIP). The origins of the IOD-like biases in CGCMs are further investigated by comparing model outputs from CMIP and the Atmospheric Model Intercomparison Project (AMIP). The CGCMs’ errors are divided into the biases from the AMIP simulation (AMIP biases) and ocean–atmosphere coupling (coupling biases). For the multimodel ensemble mean, the AMIP (coupling) biases account for about two-thirds (one-third) of the IOD-like CMIP biases. In AMIP simulations, the South Asian summer monsoon (SASM) is overly strong; therefore, it could advect overly large easterly momentum from the south Indian Ocean (IO) to the equator. The resultant equatorial easterly wind bias would initiate the convection–circulation feedback and develop large IOD-like AMIP biases. In contrast, the coupling biases weaken the SASM and hence generate warm SST error over the western IO during boreal summer. Such SST error persists to boreal autumn and triggers the Bjerknes feedback, developing the IOD-like coupling biases. Furthermore, the intermodel spread in the IOD-like CMIP biases is largely explained by the intermodel differences in the coupling biases rather than the AMIP biases. The results imply that substantial efforts should be respectively made on reducing the atmospheric models’ intrinsic monsoon biases as well as advancing the simulations of ocean–atmosphere coupling processes.

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Werner Bauer, Pranav Chandramouli, Bertrand Chapron, Long Li, and Etienne Mémin

Abstract

An important open question in fluid dynamics concerns the effect of small scales in structuring a fluid flow. In oceanic or atmospheric flows, this is aptly captured in wave–current interactions through the study of the well-known Langmuir secondary circulation. Such wave–current interactions are described by the Craik–Leibovich system, in which the action of a wave-induced velocity, the Stokes drift, produces a so-called “vortex force” that causes streaking in the flow. In this work, we show that these results can be generalized as a generic effect of the spatial inhomogeneity of the statistical properties of the small-scale flow components. As demonstrated, this is well captured through a stochastic representation of the flow.

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Xiaofeng Li, Jun A. Zhang, Xiaofeng Yang, William G. Pichel, Mark DeMaria, David Long, and Ziwei Li

In 2008, the Canadian Space Agency sponsored the Radarsat Hurricane Applications Project (RHAP), for researching new developments in the application of Radarsat-1 synthetic aperture radar (SAR) data and innovative mapping approaches to better understand the dynamics of tropical cyclone genesis, morphology, and movement. Although tropical cyclones can be detected by many remote sensors, SAR can yield high-resolution (subkilometer) and low-level storm information that cannot be seen below the clouds by other sensors. In addition to the wind field and tropical cyclone eye information, structures associated with atmospheric processes can also be detected by SAR. We have acquired 161 Radarsat-1 SAR images through RHAP between 2001 and 2007. Among these, 73 images show clear tropical cyclone eye structure. In addition, we also acquired 10 images from the European Space Agency's Envisat SAR between 2004 and 2010. Both Atlantic hurricanes and Pacific typhoons are included.

In this study, we analyze these 83 (73 Radarsat-1 and 10 Envisat) images with tropical cyclone eye information along with ancillary tropical cyclone intensity information from the archive to generate tropical cyclone morphology statistics. Histograms of wave-number asymmetry and intensity are presented. The statistics show that when the storm has higher intensity, the tropical cyclone eye tends to become more symmetric, and the area of the tropical cyclone eye, defined by the minimum wind area, tends to be smaller. Examples of finescale structures within the tropical cyclone (i.e., eye/eyewall mesovortices, arc clouds, double eyewalls, and abnormally high wind or rain within eyes) are presented and discussed.

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Yu-Long Xie, Philip K. Hopke, Pentti Paatero, Leonard A. Barrie, and Shao-Meng Li

Abstract

Week-long samples of airborne particulate matter were obtained at Alert, Northwest Territories, Canada, between 1980 and 1991. The concentrations of 24 particulate constituents have some strong, persistent seasonal variations that depend on the transport from their sources. In order to explore the nature of the cyclical variation of the different processes that give rise to the measured concentrations, the observations were arranged into both a two-way matrix and a three-way data array. For the latter, the three modes consist of chemical constituents, weeks within a year, and years. The two-way bilinear model and a three-way trilinear model were used to fit the data and a new data analysis technique, positive matrix factorization (PMF), has been used to obtain the solutions. PMF utilizes the error estimates of the observations to provide an optimal pointwise scaling data array for weighting, which enables it to handle missing data, a common occurrence in environmental measurements. It can also apply nonnegative constraints to the factors. Five factors have been obtained that reproduce the data quite well for both two-way and three-way analyses. Each factor represents a probable source with a compositional profile and distinctive seasonal variations. Specifically, there are (i) an acid photochemical factor typified by Br, H+, and SO2−4 and characterized by a concentration maximum around April, or shortly after polar sunrise;(ii) a soil factor representing by Si, Al, and Ca and having its main seasonal maximum in September and October;(iii) an anthropogenic factor dominated by SO2−4 together with metallic species like Pb, Zn, V, As, Sb, Se, In, etc., peaking from December to April; (iv) a sea salt factor consisting mainly of Cl, Na, and K with maximum concentrations during the period from October to April; and (v) a biogenic factor characterized by methanesulfonate and having a primary maximum at May and a secondary maximum in August. The results obtained by both two-way and three-way PMF analyses are generally consistent with one another. However, there are differences because of additional constraints on the solution imposed by the three-way analysis. The results also help to confirm the hypotheses regarding the origins of the Arctic aerosol.

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Zhongkun Hong, Zhongying Han, Xueying Li, Di Long, Guoqiang Tang, and Jianhua Wang

Abstract

Precipitation over the Tibetan Plateau (TP), known as Asia’s water tower, plays a critical role in regional water and energy cycles, largely affecting water availability for downstream countries. Rain gauges are indispensable in precipitation measurement, but are quite limited in the TP, which features complex terrain and a harsh environment. Satellite and reanalysis precipitation products can provide complementary information for ground-based measurements, particularly over large, poorly gauged areas. Here we optimally merged gauge, satellite, and reanalysis data by determining weights of various data sources using artificial neural networks (ANNs) and environmental variables including elevation, surface pressure, and wind speed. A Multi-Source Precipitation (MSP) dataset was generated at a daily time scale and a spatial resolution of 0.1° across the TP for the 1998–2017 period. The correlation coefficient (CC) of daily precipitation between the MSP and gauge observations was highest (0.74) and the root-mean-square error was the second lowest compared with four other satellite products, indicating the quality of the MSP and the effectiveness of the data merging approach. We further evaluated the hydrological utility of different precipitation products using a distributed hydrological model for the poorly gauged headwaters of the Yangtze and Yellow Rivers in the TP. The MSP achieved the best Nash–Sutcliffe efficiency coefficient (over 0.8) and CC (over 0.9) for daily streamflow simulations during 2004–14. In addition, the MSP performed best over the ungauged western TP based on multiple collocation evaluation. The merging method could be applicable to other data-scarce regions globally to provide high-quality precipitation data for hydrological research.

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