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Xiaolan L. Wang

Abstract

This study proposes an empirical approach to account for lag-1 autocorrelation in detecting mean shifts in time series of white or red (first-order autoregressive) Gaussian noise using the penalized maximal t test or the penalized maximal F test. This empirical approach is embedded in a stepwise testing algorithm, so that the new algorithms can be used to detect single or multiple changepoints in a time series. The detection power of the new algorithms is analyzed through Monte Carlo simulations. It has been shown that the new algorithms work very well and fast in detecting single or multiple changepoints. Examples of their application to real climate data series (surface pressure and wind speed) are presented. An open-source software package (in R and FORTRAN) for implementing the algorithms, along with a user manual, has been developed and made available online free of charge.

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Xiaolan L. Wang

Abstract

In this study, a penalized maximal F test (PMFT) is proposed for detecting undocumented mean shifts that are not accompanied by any sudden change in the linear trend of time series. PMFT aims to even out the uneven distribution of false alarm rate and detection power of the corresponding unpenalized maximal F test that is based on a common-trend two-phase regression model (TPR3). The performance of PMFT is compared with that of TPR3 using Monte Carlo simulations and real climate data series.

It is shown that, due to the effect of unequal sample sizes, the false alarm rate of TPR3 has a W-shaped distribution, with much higher than specified values for points near the ends of the series and lower values for points between either of the ends and the middle of the series. Consequently, for a mean shift of certain magnitude, TPR3 would detect it with a lower-than-specified level of confidence and hence more easily when it occurs near the ends of the series than somewhere between either of the ends and the middle of the series; it would mistakenly declare many more changepoints near the ends of a homogeneous series. These undesirable features of TPR3 are diminished in PMFT by using an empirical penalty function to take into account the relative position of each point being tested. As a result, PMFT has a notably higher power of detection; its false alarm rate and effective level of confidence are very close to the nominal level, basically evenly distributed across all possible candidate changepoints. The improvement in hit rate can be more than 10% for detecting small shifts (Δ ≤ σ, where σ is the noise standard deviation).

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Xiaolan L. Wang and Val R. Swail

Abstract

In this study, seasonal extremes of wave height in the North Atlantic are analyzed. The analysis is based on a 40-yr (1958–97) numerical wave hindcast using an intensive kinematic reanalysis of wind fields. Changes in the ocean wave extremes are identified by performing the Mann–Kendall test, and are further related to changes in the atmospheric circulation (sea level pressure) by means of redundancy analysis. The relationship between sea level pressure and ocean wave extremes is also used to reconstruct the seasonal wave statistics for the last century (back to 1899).

Consistent with previous studies, this high-resolution Atlantic wave hindcast also shows that the northeast North Atlantic Ocean has experienced significant multidecadal variations in the last century, and it has indeed roughened in winters of the last four decades. The winter wave height increases are closely related to changes in the North Atlantic oscillation during the last four decades.

While showing trend patterns similar to the ones identified from a previous global wave hindcast using the NCEP reanalysis wind fields, this detailed Atlantic hindcast shows more significant increases in the region off the Canadian coast in summer and fall; and in winter it shows higher rates of increases in the region northwest of Ireland but less significant changes in the North Sea and in the region off the Scandinavian coast.

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John M. Hanesiak and Xiaolan L. Wang

Abstract

This study provides an assessment of changes in the occurrence frequency of four types of adverse-weather (freezing precipitation, blowing snow, fog, and low ceilings) and no-weather (i.e., no precipitation or visibility obscuration) events as observed at 15 Canadian Arctic stations of good hourly weather observations for 1953–2004. The frequency time series were subjected to a homogenization procedure prior to a logistic regression–based trend analysis.

The results show that the frequency of freezing precipitation has increased almost everywhere across the Canadian Arctic since 1953. Rising air temperature in the region has probably resulted in more times that the temperature is suitable for freezing precipitation. On the contrary, the frequency of blowing snow occurrence has decreased significantly in the Canadian Arctic. The decline is most significant in spring. Changes in fog and low ceiling (LC) occurrences have similar patterns and are most (least) significant in summer (autumn). Decreases were identified for both types of events in the eastern region in all seasons. In the southwest, however, the fog frequency has increased significantly in all seasons, while the LC frequency has decreased significantly in spring and summer. The regional mean rate of change in the frequency of the four types of adverse weather was estimated to be 7%–13% per decade.

The frequency of no-weather events has also decreased significantly at most of the 15 sites. The decrease is most significant and extensive in autumn. Comparison with the adverse-weather trends above indicates that the decline in no-weather occurrence (i.e., increase in weather occurrence) is not the result of an increase in blowing snow or fog occurrence; it is largely the result of the increasing frequency of freezing precipitation and, most likely, other types of precipitation as well. This is consistent with the reported increases in precipitation amount and more frequent cyclone activity in the lower Canadian Arctic.

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Su Yang, Xiaolan L. Wang, and Martin Wild

Abstract

This paper presents a study on long-term surface solar radiation (SSR) changes over China under clear- and all-sky conditions and analyzes the causes of the “dimming” and “brightening.” To eliminate the nonclimatic signals in the historical records, the daily SSR dataset was first homogenized using quantile-matching (QM) adjustment. The results reveal rapid dimming before 2000 not only under all-sky conditions, but also under clear-sky conditions, at a decline rate of −9.7 ± 0.4 W m−2 decade−1 (1958–99). This is slightly stronger than that under all-sky conditions at −7.4 ± 0.4 W m−2 decade−1, since the clear-sky dimming stopped 15 years later. A rapid “wettening” of about 40-Pa surface water vapor pressure (SWVP) from 1985 to 2000 was found over China. It contributed 2.2% to the SSR decline under clear-sky conditions during the whole dimming period (1958–99). Therefore, water vapor cannot be the main cause of the long-term dimming in China. After a stable decade (1999–2008), an intensive brightening appeared under the clear-sky conditions at a rate of 10.6 ± 2.0 W m−2 decade−1, whereas a much weaker brightening (−0.8 ± 3.1 W m−2 decade−1) has been observed under all-sky conditions between 2008 and 2016. The remarkable divergence between clear- and all-sky trends in recent decades indicates that the clouds played two opposite roles in the SSR changes during the past 30 years, by compensating for the declining SSR under the cloud-free conditions in 1985–99 and by counteracting the increasing SSR under cloud-free conditions in 2008–16. Aerosols remain as the main cause of dimming and brightening over China in the last 60 years, although the clouds counteract the effects of aerosols after 2000.

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Xiaolan L. Wang and Francis W. Zwiers

Abstract

In this paper log–linear analysis and analysis of variance methods were used to analyze the interannual variability and potential predictability of precipitation as simulated in an ensemble of six 10-yr Atmospheric Model Intercomparison Project climate simulations conducted with CCC GCM2, the second-generation general circulation model of the Canadian Centre for Climate Modelling and Analysis. Since observed 1979–88 sea surface temperatures (SSTs) and sea ice extent were prescribed as lower boundary conditions in all six simulations, it is possible to diagnose the extent to which the variability of the seasonal frequency, seasonal mean intensity, and seasonal total of precipitation is affected by the prescribed boundary conditions. The specified SST–sea ice forcing was found to significantly affect both the frequency and intensity of precipitation, particularly in the Tropics, but also in the temperate latitudes. Precipitation frequency appears to be more sensitive to the external forcing than precipitation intensity, especially over land areas. Potential predictability from internal sources such as land surface variations is generally small.

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Xiaolan L. Wang and Han-Ru Cho

Abstract

Combinations of statistical analyses including principal component analysis, and uni- and multivariate singular spectrum analyses, were carried out to characterize the spatial–temporal structures of trend and interannual oscillatory variabilities of precipitation over the major north-flowing river basins in the former Soviet Union.

The series of monthly precipitation were corrected for the biases of precipitation measurement due to the gauge-type change and changes in observing procedures. An upward trend was found in the monthly precipitation series for the last half century. This upward trend was stronger in the North Dvina and Pechora River basins, and in the Ob-Irtysh River basins, but much weaker (still upward, though) in the Yenisey–Lena River basins. The notable increases of precipitation over the southwestern part—the Volga and Ural River basins—were found to be due at least in part to the upward phase of some quasi-century periodicity. Generally speaking, the precipitation increases appeared to be more apparent during the cold seasons in the western half of the sector, while in the eastern part, it appeared to be equally or more notable during summer.

On the interannual timescales, signals of 4–5-yr and quasi-biennial oscillations were found in the space–time-dependent precipitation series. The 4–5-yr oscillation was quite apparent over the entire Northern Eurasian sector, being stronger over the southeastern and western parts. This oscillation appeared to propagate eastward. The quasi-biennial oscillation was generally weaker; it was very weak during the 1955–65 period. This oscillation was relatively stronger in the western half of the sector and weaker over the eastern half.

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Xiaolan L. Wang and Val R. Swail

Abstract

This study assesses trends in seasonal extremes (90- and 99-percentiles) of Significant Wave Height (SWH) in the North Atlantic and the North Pacific, as simulated in a 40-yr global wave hindcast using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis wind fields. For the last four decades, statistically significant changes in the seasonal extremes of SWH in the North Atlantic (NA) are detected only for the winter (January–March) season. These changes are found to be intimately connected with the North Atlantic oscillation (NAO). To be specific, significant increases of SWH in the northeast NA, matched by significant decreases in the subtropical NA, are found to be associated with an intensified Azores high and a deepened Icelandic low. This is consistent with the findings of previous studies based on different datasets. Changes in seasonal extremes of SWH in the North Pacific (NP) are found to be statistically significant for the winter and spring (April–June) seasons. Significant increases in the extremes of SWH in the central NP are found to be connected with a deeper and eastward extended Aleutian low. For both oceans, no significant trends of SWH are detected for the last century, though significant changes are found in the last four decades. However, multidecadal fluctuations are very noticeable, especially in the North Pacific.

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Su Yang, Xiaolan L. Wang, and Martin Wild

Abstract

This paper presents a method to homogenize China’s surface solar radiation (SSR) data and uses the resulting homogenized SSR data to assess the SSR trend over the period 1958–2016. Neighboring surface sunshine duration (SSD) data are used as reference data to assess the SSR data homogeneity. A principal component analysis is applied to build a reference series, which is proven to be less sensitive to occasional data issues than using the arithmetic mean of data from adjacent stations. A relative or absolute test is applied to detect changepoints, depending on whether or not a suitable reference series is available. A quantile-matching method is used to adjust the data to diminish the inhomogeneities. As a result, 60 out of the 119 SSR stations were found to have inhomogeneity issues. These were mainly caused by changes in instrument and observation schedule. The nonclimatic changes exaggerated the SSR change rates in 1991–93 and resulted in a sudden rise in the national average SSR series, causing an unrealistically drastic trend reversal in the 1990s. This was diminished by the data homogenization. The homogenized data show that the national average SSR has been declining significantly over the period 1958–90; this dimming trend mostly diminished over the period 1991–2005 and was replaced by a brightening trend in the recent decade. From the homogenized SSR data, the 1958–90 and 1958–2005 dimming rate is estimated to be −6.13 ± 0.47 and −5.08 ± 0.27 W m−2 decade−1, respectively, and the 2005–16 brightening rate is 6.13 ± 1.77 W m−2 decade−1.

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