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

Abstract

Hourly/daily wind gust simulation models and regression-based downscaling methods were developed to assess possible impacts of climate change on future hourly/daily wind gust events over the province of Ontario, Canada. Since the climate/weather validation process is critical, a formal model result verification process has been built into the analysis to ascertain whether the methods are suitable for future projections. The percentage of excellent and good simulations among all studied seven wind gust categories ranges from 94% to 100% and from 69% to 95%, respectively, for hourly and daily wind gusts, for both model development and validation.

The modeled results indicate that frequencies of future hourly/daily wind gust events are projected to increase late this century over the study area under a changing climate. For example, across the study area, the annual mean frequency of future hourly wind gust events ≥28, ≥40, and ≥70 km h−1 for the period 2081–2100 derived from the ensemble of downscaled eight-GCM A2 simulations is projected to be about 10%–15%, 10%–20%, and 20%–40% greater than the observed average during the period 1994–2007, respectively. The corresponding percentage increase for future daily wind gust events is projected to be <10%, ~10%, and 15%–25%. Inter-GCM-model and interscenario uncertainties of future wind gust projections were quantitatively assessed. On average, projected percentage increases in frequencies of future hourly/daily wind gust events ≥28 and ≥40 km h−1 are about 90%–100% and 60%–80% greater than inter-GCM-model–interscenario uncertainties, respectively. For wind gust events ≥70 km h−1, the corresponding projected percentage increases are about 25%–35% greater than the interscenario uncertainties and are generally similar to inter-GCM-model uncertainties.

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

Abstract

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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Richard C. Cornes
,
Philip D. Jones
, and
Cheng Qian

Abstract

The annual cycle of surface air temperature is examined across Northern Hemisphere land areas (north of 25°N) by comparing the results from the Climatic Research Unit Time Series (CRU TS) dataset against four reanalysis datasets: two versions of the NOAA Twentieth Century Reanalysis (20CR and 20CRC) and two versions of the ECMWF Twentieth Century Reanalysis, version 2 (ERA-20C) and version 2c (ERA-20CM). The modulated annual cycle is adaptively derived from an ensemble empirical mode decomposition (EEMD) filter, and is used to define the phase and amplitude of the annual cycle. The EEMD method does not impose a simple sinusoidal shape of the annual cycle. None of the reanalysis simulations assimilates surface temperature or land-use data. However, they differ in the parameters that are included: both ERA-20C and 20CR assimilate surface pressure data; ERA-20C also includes surface wind data over the oceans; and ERA-20CM does not assimilate any of these synoptic data. It is demonstrated that synoptic variability is critical for explaining the trends and variability of the annual cycle of surface temperature across the Northern Hemisphere. The CMIP5 forcings alone are insufficient to explain the observed trends and decadal-scale variability, particularly with respect to the decline in the amplitude of the annual cycle throughout the twentieth century. The variability in the annual cycle during the latter half of the twentieth century was unusual in the context of the twentieth century, and was most likely related to large-scale atmospheric variability, although uncertainty in the results is greatest before about 1930.

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

Abstract

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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William J. Randel
,
Anne K. Smith
,
Fei Wu
,
Cheng-Zhi Zou
, and
Haifeng Qian

Abstract

Temperature trends in the middle and upper stratosphere are evaluated using measurements from the Stratospheric Sounding Unit (SSU), combined with data from the Aura Microwave Limb Sounder (MLS) and Sounding of the Atmosphere Using Broadband Emission Radiometry (SABER) instruments. Data from MLS and SABER are vertically integrated to approximate the SSU weighting functions and combined with SSU to provide a data record spanning 1979–2015. Vertical integrals are calculated using empirically derived Gaussian weighting functions, which provide improved agreement with high-latitude SSU measurements compared to previously derived weighting functions. These merged SSU data are used to evaluate decadal-scale trends, solar cycle variations, and volcanic effects from the lower to the upper stratosphere. Episodic warming is observed following the volcanic eruptions of El Chichón (1982) and Mt. Pinatubo (1991), focused in the tropics in the lower stratosphere and in high latitudes in the middle and upper stratosphere. Solar cycle variations are centered in the tropics, increasing in amplitude from the lower to the upper stratosphere. Linear trends over 1979–2015 show that cooling increases with altitude from the lower stratosphere (from ~−0.1 to −0.2 K decade−1) to the middle and upper stratosphere (from ~−0.5 to −0.6 K decade−1). Cooling in the middle and upper stratosphere is relatively uniform in latitudes north of about 30°S, but trends decrease to near zero over the Antarctic. Mid- and upper-stratospheric temperatures show larger cooling over the first half of the data record (1979–97) compared to the second half (1998–2015), reflecting differences in upper-stratospheric ozone trends between these periods.

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Qian-Jin Zhou
,
Lei Li
,
Pak-Wai Chan
,
Xue-Ling Cheng
,
Chang-Xing Lan
,
Jia-Chen Su
,
Yu-Qing He
, and
Hong-Long Yang

Abstract

Supertyphoons (STs) and strong convection gales (SCGs) are extremely hazardous weather events over land. Knowledge of their processes is crucial for various applications, such as intensity forecasts of gales and the design of high-rise construction and infrastructure. Here, an observational analysis of two strong SCGs and two STs is presented based on data from the Shenzhen meteorological gradient tower, the tallest in Asia. Differences in the intrinsic physical characteristics measured at each event can be associated with different disaster-causing mechanisms. Wind speeds during STs are comparatively much larger but feature slower variations, while those of SCGs are more abrupt. Unlike that observed during STs, the vertical distribution of wind speeds during SCGs obeys a power law or exponential distribution only within 1-h maximum wind speed windows. In comparison with a Gaussian distribution, a generalized extreme value distribution can better characterize the statistical characteristics of the gusts of both STs and SCGs events. Deviations from Kolmogorov’s −5/3 power law were observed in the energy spectra of both phenomena at upper levels, albeit with differences. Different from what is seen in the ST energy spectrum distribution, a clear process of energy increase and decrease could be seen in SCGs during gale evolution. Nonetheless, both SCGs and STs exhibited a high downward transfer of turbulent momentum flux at a 320 m height, which could be attributed to the pulsation of the gusts rather than to the large-scale base flow.

Significance Statement

Strong gales induced by typhoons and severe convection have potential serious impacts on human society. The current study compares and analyzes the characteristics of the gales induced by the two different weather systems using the data observed by a 356-m-tall tower in South China. This paper also shows the relationship between gusts of the near-surface wind and the turbulent momentum fluxes, thus suggesting a possible mechanism leading to destructive forces in surface winds. In terms of social value, this study would contribute to increase the awareness of gales (the instantaneous wind speed over 17 m s−1) and improve the prediction and prevention of different types of gales, as well as the wind-resistant design of high-rise buildings.

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Cheng Qian
,
Jun Wang
,
Siyan Dong
,
Hong Yin
,
Claire Burke
,
Andrew Ciavarella
,
Buwen Dong
,
Nicolas Freychet
,
Fraser C. Lott
, and
Simon F. B. Tett
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