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Cheng Sun and Jianping Li

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In this paper the authors use the NCEP–Department of Energy (DOE) Reanalysis 2 (NCEP2) data from 1979 to 2004 to expand the daily 500-hPa geopotential height in the Southern Hemisphere (SH, 90°–20°S) into a double Fourier series, and analyze the temporal frequency characteristics of the expansion coefficients over various spatial scales. For the daily series over the whole year, the coefficient series of the extratropical-mean height is characterized by a significant low-frequency (10–30 day) variation. For zonal waves with (k, l) = (1–5, 1), where k and l are the zonal and meridional wavenumbers, respectively, the low-frequency variability is most pronounced for zonal wavenumbers 3 and 4; while the short wave with zonal wavenumber 5 has significant high-frequency (4–8 day) variability. For meridional waves with (k, l) = (0, 2–6), the meridional dipole (l = 2) makes a major contribution to the low-frequency variability, consistent with the intraseasonal space–time features of the southern annular mode (SAM). The meridional tripole (l = 3) also exhibits low-frequency variability. For two-dimensional waves (k, l) = (1–5, 2–6), the dipole is a preferred meridional structure for intraseasonal modes with large zonal scales, indicating an out-of-phase relationship between low-frequency planetary-scale waves at mid- and high latitudes. The diagnostic results outlined above can be explained, to a certain extent, by the dispersion relation for Rossby waves. Theoretical analysis indicates that zonal wavenumber 3, zonally symmetric flow such as SAM, and planetary-scale waves with meridional dipole structures may be interpreted as low-frequency eigenmodes of the atmosphere.

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Cheng Li, Andrew P. Ingersoll, and Fabiano Oyafuso

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A new formula is derived for calculating the moist adiabatic temperature profile of an atmosphere consisting of ideal gases with multiple condensing species. This expression unifies various formulas published in the literature and can be generalized to account for chemical reactions. Unlike previous methods, it converges to machine precision independent of mesh size. It accounts for any ratio of condensable vapors to dry gas, from zero to infinity, and for variable heat capacities as a function of temperature. Because the derivation is generic, the new formula is not only applicable to planetary atmospheres in the solar system but also to hot Jupiters and brown dwarfs in which a variety of alkali metals, silicates, and exotic materials condense. It is demonstrated that even though the vapors are ideal gases, they interact in their effects on the moist adiabatic lapse rate. Finally, the authors apply the new thermodynamic model to study the effects of downdrafts on the distribution of minor constituents and the thermal profile in the Galileo probe hot spot. The authors find that the Galileo probe measurements can be interpreted as a strong downdraft that displaces an air parcel from the 1-bar to the 4-bar level (1 bar = 100 000 Pa).

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Yifeng Cheng, Lu Wang, and Tim Li

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The southern China (SC) summer rainfall exhibits prominent intraseasonal variability, which exhibits a significant increase in the early 1990s with the turning point at 1993. The SC intraseasonal rainfall events could be divided into three categories according to different propagations, including the southward-propagating (SP) events, the northwestward-propagating (NWP) events, and the northward-propagating (NP) events. This study explores the causes of the observed interdecadal increase in the intraseasonal rainfall variability over SC by comparing the SC intraseasonal rainfall events of each category between the former decadal period (P1) and the later decadal period (P2). The result indicates that such interdecadal change is due to the more frequent NP events coming from the South China Sea (SCS). Based on the moisture and vorticity budget analysis, it is revealed that the summer mean southerly wind in the middle to lower troposphere is the dominant factor of the northward propagation over the SCS, as it could induce positive meridional moisture and vorticity advection anomalies ahead of the convection. A marked interdecadal enhancement of the summer mean southerly wind over the SCS is the cause of more frequent occurrence of NP events over SC, as it provides more favorable conditions for the northward propagation. The change of the atmospheric instability over the SCS where the NP convection perturbation originates was also investigated, but no significant change was found.

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Chad Shouquan Cheng, Guilong Li, Qian Li, and Heather Auld

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An automated synoptic weather typing and stepwise cumulative logit/nonlinear regression analyses were employed to simulate the occurrence and quantity of daily rainfall events. The synoptic weather typing was developed using principal component analysis, an average linkage clustering procedure, and discriminant function analysis to identify the weather types most likely to be associated with daily rainfall events for the four selected river basins in Ontario. Within-weather-type daily rainfall simulation models comprise a two-step process: (i) cumulative logit regression to predict the occurrence of daily rainfall events, and (ii) using probability of the logit regression, a nonlinear regression procedure to simulate daily rainfall quantities. The rainfall simulation models were validated using an independent dataset, and the results showed that the models were successful at replicating the occurrence and quantity of daily rainfall events. For example, the relative operating characteristics score is greater than 0.97 for rainfall events with daily rainfall ≥10 or ≥25 mm, for both model development and validation. For evaluation of daily rainfall quantity simulation models, four correctness classifications of excellent, good, fair, and poor were defined, based on the difference between daily rainfall observations and model simulations. Across four selected river basins, the percentage of excellent and good simulations for model development ranged from 62% to 84% (of 20 individuals, 16 cases ≥ 70%, 7 cases ≥ 80%); the corresponding percentage for model validation ranged from 50% to 76% (of 20 individuals, 15 cases ≥ 60%, 6 cases ≥ 70%).

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Chad Shouquan Cheng, Guilong Li, Qian Li, and Heather Auld

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This paper attempts to project possible changes in the frequency of daily rainfall events late in this century for four selected river basins (i.e., Grand, Humber, Rideau, and Upper Thames) in Ontario, Canada. To achieve this goal, automated synoptic weather typing as well as cumulative logit and nonlinear regression methods was employed to develop within-weather-type daily rainfall simulation models. In addition, regression-based downscaling was applied to downscale four general circulation model (GCM) simulations to three meteorological stations (i.e., London, Ottawa, and Toronto) within the river basins for all meteorological variables (except rainfall) used in the study. Using downscaled GCM hourly climate data, discriminant function analysis was employed to allocate each future day for two windows of time (2046–65, 2081–2100) into one of the weather types. Future daily rainfall and its extremes were projected by applying within-weather-type rainfall simulation models together with downscaled future GCM climate data. A verification process of model results has been built into the whole exercise (i.e., statistical downscaling, synoptic weather typing, and daily rainfall simulation modeling) to ascertain whether the methods are stable for projection of changes in frequency of future daily rainfall events.

Two independent approaches were used to project changes in frequency of daily rainfall events: method I—comparing future and historical frequencies of rainfall-related weather types, and method II—applying daily rainfall simulation models with downscaled future climate information. The increases of future daily rainfall event frequencies and seasonal rainfall totals (April–November) projected by method II are usually greater than those derived by method I. The increase in frequency of future daily heavy rainfall events greater than or equal to 25 mm, derived from both methods, is likely to be greater than that of future daily rainfall events greater than or equal to 0.2 mm: 35%–50% versus 10%–25% over the period 2081–2100 derived from method II. In addition, the return values of annual maximum 3-day accumulated rainfall totals are projected to increase by 20%–50%, 30%–55%, and 25%–60% for the periods 2001–50, 2026–75, and 2051–2100, respectively. Inter-GCM and interscenario uncertainties of future rainfall projections were quantitatively assessed. The intermodel uncertainties are similar to the interscenario uncertainties, for both method I and method II. However, the uncertainties are generally much smaller than the projection of percentage increases in the frequency of future seasonal rain days and future seasonal rainfall totals. The overall mean projected percentage increases are about 2.6 times greater than overall mean intermodel and interscenario uncertainties from method I; the corresponding projected increases from method II are 2.2–3.7 times greater than overall mean uncertainties.

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Ruibo Lei, Zhijun Li, Yanfeng Cheng, Xin Wang, and Yao Chen

Abstract

High-precision ice thickness observations are required to gain a better understanding of ocean–ice–atmosphere interactions and to validate numerical sea ice models. A new apparatus for monitoring sea ice and snow thickness has been developed, based on the magnetostrictive-delay-line (MDL) principle for positioning sensors. This system is suited for monitoring fixed measurement sites on undeformed ice. The apparatus presented herein has been tested on landfast ice near Zhongshan Station, East Antarctica, for about 6 months during the austral autumn and winter of 2006; valid data records from the deployment are available for more than 90% of the deployment’s duration. The apparatus’s precision has been estimated to be ±0.002 m for the deployment. Therefore, it is possible that this apparatus may become a standard for sea ice/snow thickness monitoring.

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Cheng Sun, Jianping Li, Juan Feng, and Fei Xie

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The time series of twentieth-century subtropical eastern Australian rainfall (SEAR) shows evident fluctuations over decadal to multidecadal time scales. Using observations from the period 1900–2013, it was found that SEAR is connected to the North Atlantic Oscillation (NAO) over decadal time scales, with the NAO leading by around 15 yr. The physical mechanism underlying this relationship was investigated. The NAO can have a delayed impact on sea surface temperature (SST) fluctuations in the subpolar Southern Ocean (SO), and these SST changes could in turn contribute to the decadal variability in SEAR through their impacts on the Southern Hemisphere atmospheric circulation. This observed lead of the NAO relative to SO SST and the interhemispheric SST seesaw mechanism are reasonably reproduced in a long-term control simulation of an ocean–atmosphere coupled model. The NAO exerts a delayed effect on the variation of Atlantic meridional overturning circulation that further induces seesaw SST anomalies in the subpolar North Atlantic and SO. With evidence that the NAO precedes SEAR decadal variability via a delayed SO bridge, a linear model for SEAR decadal variability was developed by combination of the NAO and Pacific decadal oscillation (PDO). The observed SEAR decadal variability is considerably well simulated by the linear model, and the relationship between the simulation and observation is stable. SEAR over the coming decade may increase slightly, because of the recent NAO weakening and the return of negative PDO phase.

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Nianliang Cheng, Yunting Li, Dawei Zhang, and Fan Meng
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Shaojun Zheng, Ming Feng, Yan Du, Xuhua Cheng, and Jiaxun Li

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This study documents the spatial distributions and temporal variations of anticyclonic eddies with identified radii ≥100 km in the equatorial eastern tropical Pacific Ocean [viz., tropical instability vortices (TIVs)] using Lagrangian surface drifters. The TIVs identified from Lagrangian surface drifters are distributed in a band along 5°N and are closely associated with latitudinal barotropically unstable shear between the westward South Equatorial Current (SEC) and the eastward North Equatorial Countercurrent (NECC). Fewer TIVs are identified from February to June when the shear between the SEC and NECC is weak, whereas more TIVs are found from July to January when the shear is enhanced. The number of identified TIVs also exhibits substantial interannual variability, with fewer TIVs identified during El Niño events and more TIVs found during La Niña events. This relationship is likely associated with the interannual variations of the zonal circulation in the equatorial Pacific modulated by El Niño–Southern Oscillation (ENSO).

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Chad Shouquan Cheng, Heather Auld, Guilong Li, Joan Klaassen, Bryan Tugwood, and Qian Li

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Freezing rain is a major weather hazard that can compromise human safety, significantly disrupt transportation, and damage and disrupt built infrastructure such as telecommunication towers and electrical transmission and distribution lines. In this study, an automated synoptic typing and logistic regression analysis were applied together to predict freezing rain events. The synoptic typing was developed using principal components analysis, an average linkage clustering procedure, and discriminant function analysis to classify the weather types most likely to be associated with freezing rain events for the city of Ottawa, Ontario, Canada. Meteorological data used in the analysis included hourly surface observations from the Ottawa International Airport and six atmospheric levels of 6-hourly NCEP–NCAR upper-air reanalysis weather variables for the winter months (Nov– Apr) of 1958/59–2000/01. The data were divided into two parts: a developmental dataset (1958/59–1990/91) for construction (development) of the model and an independent or validation dataset (1991/90–2000/01) for validation of the model. The procedure was able to successfully identify weather types that were most highly correlated with freezing rain events at Ottawa.

Stepwise logistic regression was performed on all days within the freezing rain–related weather types to analytically determine the meteorological variables that can be used as forecast predictors for the likelihood of freezing rain occurrence at Ottawa. The results show that the model is best able to identify freezing rain events lasting several hours during a day. For example, in the validation dataset, for likelihood values ≥0.6, the procedure was able to identify 74% of all freezing rain events lasting at least 6 h during a day. Similarly, the procedure was able to identify 91% of all freezing rain events occurring at least 8 h during a day. This study has further potential to be adapted to an operational forecast mode to assist in the prediction of major ice storms.

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