Unsupervised classification is becoming an increasingly common method to objectively identify coherent structures within both observed and modelled climate data. However, in most applications using this method, the user must choose the number of classes into which the data are to be sorted in advance. Typically, a combination of statistical methods and expertise is used to choose the appropriate number of classes for a given study; however, it may not be possible to identify a single “optimal” number of classes. In this work, we present a heuristic method, the ensemble difference criterion, for unambiguously determining the maximum number of classes supported by model data ensembles. This method requires robustness in the class definition between simulated ensembles of the system of interest. For demonstration, we apply this to the clustering of Southern Ocean potential temperatures in a CMIP6 climate model, and show that the data supports between four and seven classes of a Gaussian mixture model.

The East Asian winter monsoon (EAWM) is one of the most dynamic components of the global climate system. Although poorly understood, knowledge of long-term spatial differences in EAWM variability during the glacial–interglacial cycles is important for understanding the dynamic processes of the EAWM. We reconstructed the spatiotemporal characteristics of the EAWM since the last glacial maximum (LGM) using a comparison of proxy records and long-term transient simulations. A loess grain-size record from northern China (a sensitive EAWM proxy) and the sea surface temperature gradient of an EAWM index in sediments of the southern South China Sea were compared. The data–model comparison indicates pronounced spatial differences in EAWM evolution, with a weakened EAWM since the LGM in northern China but a strengthened EAWM from the LGM to the early Holocene, followed by a weakening trend, in southern China. The model results suggest that variations in the EAWM in northern China were driven mainly by changes in atmospheric carbon dioxide (CO2) concentration and Northern Hemisphere ice sheets, whereas orbital insolation and ice sheets were important drivers in southern China. We propose that the relative importance of insolation, ice sheets, and atmospheric CO2 for EAWM evolution varied spatially within East Asia.

We used the process-oriented niche model CLIMEX to estimate the potential global distribution of serrated tussock under projected future climates. Serrated tussock is a drought-tolerant, wind- and human-dispersed grass of South American origin that has invaded pastures in Australia, Europe, New Zealand, and South Africa. The likely effect of climate change on its potential global distribution was assessed by applying six climate-change scenarios to a previously developed model. The projections of climatic suitability under the current climate revealed considerable scope for spread, with the most suitable areas occurring adjacent to existing naturalized populations in Australia, New Zealand, and Western Europe. Under future climates, projected to the 2080s, the land area suitable for serrated tussock contracts globally between 20 and 27%. Changes in projected potential area under the six scenarios were very similar in all geographical regions apart from North America and New Zealand, where the projections range from little change or contraction under the National Center for Atmospheric Research (NCAR) and Centre for Climate Research (MIROC) global climate models (GCMs) to expansion under the Commonwealth Scientific and Industrial Research Organisation (CSIRO) GCM. Elsewhere, contractions occur in Australia, Asia, South America, and Africa under all six future climate scenarios. By contrast, for Europe, the area climatically suitable for serrated tussock increases under all six scenarios (average increase 47%) through expansions into eastern European countries that are currently unsuitable and through increases in the suitable area in England, Ireland, and Denmark. Since pastoralism is a dominant land use in these regions of Europe, a prudent biosecurity strategy would be to contain the nascent foci of serrated tussock in southern France, along the west coast of Italy, and in the United Kingdom. This strategy could consist of a set of policies to limit human-assisted dispersal of the species' seeds and to reduce wind-borne spread through cultural control of the plant.

Japanese knotweed (JK) is one of the most aggressive invasive plants known in the U.K., where its biology has been well-studied. It was introduced into Canada around 1900, but only recently has it become a serious concern in the province of British Columbia (BC). Climatic conditions, including annual degree days and mean-annual minimum temperatures at knotweed sites in British Columbia were modeled in BioSIM, using weather normals and long-term daily weather data, and compared to published thresholds (degree day = 2,505 DD, minimum temperature = −30.2 C, base temperature 0 C). The degree-day threshold was more limiting to JK in British Columbia than mean-minimum temperature (12.3% of province habitat was suitable for JK based on degree days compared with 26% for mean-minimum temperature). A new annual-precipitation threshold of 735 mm/year based on 95% of known knotweed sites in BC was identified. The best-fit logistic regression model included degree days and annual precipitation and predicted knotweed presence/absence with over 97% efficiency. Existing knotweed sites occupy just over half of the suitable habitat in BC, indicating there are still significant areas to be invaded. The limiting threshold for knotweed was reversed in Southern Ontario with between 35 to 53% of the habitat suitable based on minimum temperatures, whereas degree-day accumulations and annual precipitation were not limiting. Warmer temperatures from 2000 to 2008 resulted in an increase to 53% of the habitat in Southern Ontario being suitable for knotweed, compared to 35% when 1971 to 2000 weather normals were used. Different climatic thresholds among provinces might result in selection for different invasive knotweed genotypes. This could influence the success of biological control agents because of differential host suitability of knotweed genotypes. Habitat suitability maps generated will enable better targeting of knotweed surveys based on the risk of knotweed establishment.