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Xiaolan L. Wang
,
Hanfeng Chen
,
Yuehua Wu
,
Yang Feng
, and
Qiang Pu

Abstract

This study integrates a Box–Cox power transformation procedure into a common trend two-phase regression-model-based test (the extended version of the penalized maximal F test, or “PMFred,” algorithm) for detecting changepoints to make the test applicable to non-Gaussian data series, such as nonzero daily precipitation amounts or wind speeds. The detection-power aspects of the transformed method (transPMFred) are assessed by a simulation study that shows that this new algorithm is much better than the corresponding untransformed method for non-Gaussian data; the transformation procedure can increase the hit rate by up to ∼70%. Examples of application of this new transPMFred algorithm to detect shifts in real daily precipitation series are provided using nonzero daily precipitation series recorded at a few stations across Canada that represent very different precipitation regimes. The detected changepoints are in good agreement with documented times of changes for all of the example series. This study clarifies that it is essential for homogenization of daily precipitation data series to test the nonzero precipitation amount series and the frequency series of precipitation occurrence (or nonoccurrence), separately. The new transPMFred can be used to test the series of nonzero daily precipitation (which are non Gaussian and positive), and the existing PMFred algorithm can be used to test the frequency series. A software package for using the transPMFred algorithm to detect shifts in nonzero daily precipitation amounts has been developed and made freely available online, along with a quantile-matching (QM) algorithm for adjusting shifts in nonzero daily precipitation series, which is applicable to all positive data. In addition, a similar QM algorithm has also been developed for adjusting Gaussian data such as temperatures. It is noticed that frequency discontinuities are often inevitable because of changes in the measuring precision of precipitation, and that they could complicate the detection of shifts in nonzero daily precipitation data series and void any attempt to homogenize the series. In this case, one must account for all frequency discontinuities before attempting to adjust the measured amounts. This study also proposes approaches to account for detected frequency discontinuities, for example, to fill in the missed measurements of small precipitation or the missed reports of trace precipitation. It stresses the importance of testing the homogeneity of the frequency series of reported zero precipitation and of various small precipitation events, along with testing the series of daily precipitation amounts that are larger than a small threshold value, varying the threshold over a set of small values that reflect changes in measuring precision over time.

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Hui Wan
,
Xiaolan L. Wang
, and
Val R. Swail

Abstract

In this study a comprehensive quality assurance (QA) system, which includes the hydrostatic check combined with a statistical homogeneity test, is designed and applied to hourly pressure records (for 1953–2002) from 761 Canadian stations, to produce a high-quality database of hourly station and sea level pressures for various climate studies. The main principles of the QA system are described in detail, followed by a brief emphasis on the error correction algorithms. The general performance of the QA system and the main problems in the Canadian historical hourly pressure database are discussed and illustrated through various examples. The results show that there are serious systematic errors (i.e., sudden changes in the mean, or mean shifts) in the Canadian hourly pressure database, which are caused either by the use of incorrect station elevation values in the reduction of barometer readings to station or sea level pressure values (e.g., the “50-ft rule” or station relocation without updates to the station elevation), by transposing/swapping station and sea level pressure values, or by mistakes made in the archive data ingestion or data recording/digitization processes (e.g., use of a wrong base number). Random errors also exist and are mainly due to the transposition of two digits or miscoding of one or two digits. These errors must be corrected before the data are used in various climate studies, especially climate change–related studies.

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Xiaolan L. Wang
,
Qiuzi H. Wen
, and
Yuehua Wu

Abstract

In this paper, a penalized maximal t test (PMT) is proposed for detecting undocumented mean shifts in climate data series. PMT takes the relative position of each candidate changepoint into account, to diminish the effect of unequal sample sizes on the power of detection. Monte Carlo simulation studies are conducted to evaluate the performance of PMT, in comparison with the most popularly used method, the standard normal homogeneity test (SNHT). An application of the two methods to atmospheric pressure series recorded at a Canadian site is also presented. It is shown that the false-alarm rate of PMT is very close to the specified level of significance and is evenly distributed across all candidate changepoints, whereas that of SNHT can be up to 10 times the specified level for points near the ends of series and much lower for the middle points. In comparison with SNHT, therefore, PMT has higher power for detecting all changepoints that are not too close to the ends of series and lower power for detecting changepoints that are near the ends of series. On average, however, PMT has significantly higher power of detection. The smaller the shift magnitude Δ is relative to the noise standard deviation σ, the greater is the improvement of PMT over SNHT. The improvement in hit rate can be as much as 14%–25% for detecting small shifts (Δ < σ) regardless of time series length and up to 5% for detecting medium shifts (Δ = σ–1.5σ) in time series of length N < 100. For all detectable shift sizes, the largest improvement is always obtained when N < 100, which is of great practical importance, because most annual climate data series are of length N < 100.

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Sofia Caires
,
Val R. Swail
, and
Xiaolan L. Wang

Abstract

The nonhomogeneous Poisson process is used to model extreme values of the 40-yr ECMWF Re-Analysis (ERA-40) significant wave height. The parameters of the model are expressed as functions of the seasonal mean sea level pressure anomaly and seasonal squared sea level pressure gradient index. Using projections of the sea level pressure under three different forcing scenarios by the Canadian coupled climate model, projections of the parameters of the nonhomogeneous Poisson process are made, trends in these projections are determined, return-value estimates of significant wave height up to the end of the twenty-first century are projected, and their uncertainties are assessed. The uncertainty of estimates associated with the nonhomogeneous Poisson process estimates is studied and compared with the homologous estimates obtained using a nonstationary generalized extreme value model.

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Xiaolan L. Wang
,
H. Wan
, and
Val R. Swail

Abstract

This study assessed the climate and trend of cyclone activity in Canada using mainly the occurrence frequency of cyclone deepening events and deepening rates, which were derived from hourly mean sea level pressure data observed at 83 Canadian stations for up to 50 years (1953–2002). Trends in the frequency of cyclone activity were estimated by logistic regression analysis, and trends of seasonal extreme cyclone intensity, by linear regression analysis.

The results of trend analysis show that, among the four seasons, winter cyclone activity has shown the most significant trends. It has become significantly more frequent, more durable, and stronger in the lower Canadian Arctic, but less frequent and weaker in the south, especially along the southeast and southwest coasts. Winter cyclone deepening rates have increased in the zone around 60°N but decreased in the Great Lakes area and southern Prairies–British Columbia. However, extreme winter cyclone activity seems to have experienced a weaker increase in northwest-central Canada but a stronger decline in the Great Lakes area and in southern Prairies. The results also show more frequent summer cyclone activity with slower deepening rates on the east coast, as well as less frequent cyclone activity with faster deepening rates in the Great Lakes area in autumn.

Cyclone activity in Canada was found to be closely related to the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), and El Niño–Southern Oscillation (ENSO). Overall, cyclone activity in Canada is most closely related to the NAO. The simultaneous NAO index explains about 44% (41%) of the winter (autumn) cyclone activity variance in the east coast, 31% of winter cyclone activity variance in the 60°–70°N zone, and 17% of autumn cyclone activity variance in the Great Lakes area. Also, in several regions (e.g., the east coast, the southwest, and the 60°–70°N zone) up to 15% of the seasonal cyclone activity variance can be explained by the NAO/PDO/ENSO index one–three seasons earlier, which is useful for seasonal forecasting.

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Xiaolan L. Wang
,
Francis W. Zwiers
, and
Val R. Swail

Abstract

Using the observed relationships between sea level pressure (SLP) and significant wave height (SWH) as represented by regression models, climate change scenarios of SWH in the North Atlantic were constructed by means of redundancy analysis (for seasonal means and 90th percentiles of SWH) and nonstationary generalized extreme value analysis (for seasonal extreme SWH). SWH scenarios are constructed using output from a coupled climate model under three different forcing scenarios. Scenarios of future anomaly seasonal statistics of SWH are constructed using climate model projections of anomaly seasonal mean SLP while projections of seasonal extreme SWH are made using projections of seasonal mean SLP and seasonal SLP gradient index. The projected changes in SWH are assessed by means of a trend analysis.

The northeast Atlantic is projected to have increases in both winter and fall seasonal means and extremes of SWH in the twenty-first century under all three forcing scenarios. These changes are generally accompanied by decreases in the midlatitudes of the North Atlantic and increases in the southwest North Atlantic. The rate and sign of the projected SWH change is not constant throughout the twenty-first century. In the Norwegian and North Seas, the projected SWH changes are characterized either by faster increases in the late decades than in the early decades, or by decreases in the early decades followed by increases, depending on the forcing scenario and the specific location. Using lower or higher rates of increase in greenhouse gases forcing generally leads to reduced or increased rates of change, respectively, in ocean wave heights. The sign and rate of future wave height changes in the North Sea in particular appear to be quite dependent on the forcing conditions. In general, global warming is associated with more frequent occurrence of the positive phase of the North Atlantic Oscillation (NAO) and strong cyclones, which leads to increases of wave heights in the northeast Atlantic.

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Lucie A. Vincent
,
Xuebin Zhang
, and
Xiaolan L. Wang
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Xiaolan L. Wang
,
Yang Feng
,
Val R. Swail
, and
Andrew Cox

Abstract

This study characterizes historical changes in surface wind speed and ocean surface waves in the Beaufort–Chukchi–Bering Seas using Environment Canada’s Beaufort Wind and Wave Reanalysis for the period 1970–2013. The results show that both the significant wave height ( ) and mean wave period ( ) have increased significantly over the Bering Sea in July and August and over the Canadian Beaufort Sea westward to the northern Bering Sea in September, and that the 1992–2013 trends in September mean agree well with satellite-based trend estimates for 1993–2010. Most outstandingly, the regional mean has increased at a rate of 3%–4% yr−1 of the corresponding 1970–99 climatology; it has more than tripled since 1970. Also, the regional mean has increased at a rate of 0.3% to 0.8% yr−1. The trends of lengthening wave period and increasing wave height imply a trend of increasing wave energy flux, providing a mechanism to break up sea ice and accelerate ice retreat. The results also show that changes in the local wind speeds alone cannot explain the significant changes in waves. The wind speeds show significant increases over the Bering Sea to the north of Alaska in July and over the central part of the domain in August and September, with decreases in the region off the Canadian coasts in August. In the region west of the Canadian coast, the climatological mean wind direction has rotated clockwise in July and August, with the climatological anticyclonic center being displaced northeastward in August.

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Hui Wan
,
Xiaolan L. Wang
, and
Val R. Swail

Abstract

Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends.

This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.

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Xiaolan L. Wang
,
Val R. Swail
, and
Francis W. Zwiers

Abstract

In this study, a cyclone detection/tracking algorithm was used to identify cyclones from two gridded 6-hourly mean sea level pressure datasets: the 40-yr ECMWF Re-Analysis (ERA-40) and the NCEP–NCAR reanalysis (NNR) for 1958–2001. The cyclone activity climatology and changes inferred from the two reanalyses are intercompared. The cyclone climatologies and trends are found to be in reasonably good agreement with each other over northern Europe and eastern North America, while ERA-40 shows systematically stronger cyclone activity over the boreal extratropical oceans than does NNR. However, significant differences between ERA-40 and NNR are seen over the austral extratropics. In particular, ERA-40 shows significantly greater strong-cyclone activity and less weak-cyclone activity over all oceanic areas south of 40°S in all seasons, while it shows significantly stronger cyclone activity over most areas of the austral subtropics in the warm seasons.

The most notable historical trends in cyclone activity are found to be associated with strong-cyclone activity. Over the boreal extratropics, both ERA-40 and NNR show a significant increasing trend in January–March (JFM) strong-cyclone activity over the high-latitude North Atlantic and over the midlatitude North Pacific, with a significant decreasing trend over the midlatitude North Atlantic and a small increasing trend over northern Europe. The JFM changes over the North Atlantic are associated with the mean position of the storm track shifting about 181 km northward. Importantly, there is no evidence of abrupt changes identified for the boreal extratropics, although previous studies have suggested that the upward trend found in the NNR data could be biased high. However, there exist a few abrupt changes over the austral extratropics, which appear to be attributable to the increasing availability of observations assimilated in the reanalyses. After diminishing the effects of these abrupt changes, strong-cyclone activity over the austral circumpolar oceanic region is identified to have an increasing trend in October–December (OND) and July–September (JAS), with a decreasing trend over the 40°–60°S zone in JAS.

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