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Using a newly available 134-years long record of daily and 114-years hourly observations at Jakarta observatory, trends and variability in temperature, extreme precipitation, and changes in the diurnal cycle over Jakarta have been analysed. Although the number of days with rainfall has decreased over the 1866–2010 period, the fraction of events with rainfall exceeding 50 mm day−1 exhibits a positive trend over the 1866–2010 period with an even stronger trend over the period 1961–2010. The number of days with rainfall exceeding 50 and 100 mm day−1 has shown a statistically significant increase over the 1961–2010 period as well. Over the recent decades, the heaviest 1% of all precipitation events (q99%) also exhibits an increasing trend. These trends in extremes are strongest during the wet season. The rainfall intensity with 200 mm return level has a shorter return period in the most recent decade than earlier in the historic time series. Over the last century, the annual mean temperature in Jakarta has increased about 1.6 °C per century, which exceeds the rise of the global mean land temperature. The increase in the daily maximum temperature is stronger than the increase in mean and minimum temperature, although the trend in minimum temperature is stronger during the last 50 years. The mean diurnal cycles of Jakarta temperature and precipitation have changed markedly as well. This analysis was enabled by the availability of high quality hourly observations in the historic record. Comparing the 2001–2010 period to historic decades, a considerable increase in night-time temperature was found. During the wet season, the early morning rainfall has increased in intensity, while in other seasons a delay of the late afternoon rainfall peak was observed for the recent observation periods.

Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.

The temperature in De Bilt in the Netherlands has risen by 1 K over the 20th century. This rise parallels the rise in global temperature quite closely, albeit with a slightly higher amplitude. A linear relationship between the two, with a regression coefficient close to one, is an obvious first-order approximation. This is supported by the spatial homogeneity of global warming during the 20th century, the lack of seasonality in the temperature rise, and the residuals being almost white in time. The wind direction is used as a proxy for circulation type. Locally measured wind direction gives the same results as geostrophic wind direction from pressure stations, so that systematic errors are not likely to be large. The temperature in the Netherlands, on the edge of the continent, strongly depends on the wind direction. For most wind directions and seasons the average temperature per wind direction has increased. The exception is northeasterly winds in winter, in which the variability is too large to observe a trend. The increased temperature for each wind direction can explain the observed temperature rise in all seasons within the 95% error estimates. Changes in the distribution of wind directions explain most of the interannual variability of temperature. On longer time scales, these changes have led to cooler weather in the middle of the century, but no trend is discernible over the whole century. However, in late winter and spring there is clear evidence for a change in the frequency distribution of circulation patterns affecting the Netherlands over the second half of the 20th century. During the months of February to April, more days with southwesterly wind and fewer with northeasterlies have increased the temperature even more than the observed increase in temperature per wind direction. Copyright © 2003 Royal Meteorological Society

A strong lagged relationship between El Nino–Southern Oscillation (ENSO) and rainfall in the main rain season (October–January) on the leeward islands of Aruba, Curacao and Bonaire is found. It can easily be used for skilful seasonal predictions, with an anomaly correlation coefficient r ≈ 0.6 at lag 4 months on historical data. The other two seasons, February–May and June–September, also show correlations with ENSO that can be exploited for predictions, r = 0.4 to 0.5. In the February–May dry season there is also a lagged correlation with sea-surface temperature (SST) in the Pacific Ocean off the Central American coast that can be used to increase the forecast skill. A June–September small rains season correlation to equatorial Atlantic Ocean SST is absent in earlier data. Most of these results are also applicable to other stations in northern South America. Regressions with the circulation show that the main intermediate factors are upper-level divergence and vorticity, and at lower levels a veering of the trade winds. This modifies the descending limb of the sea–continent breeze circulation that is responsible for the dry zone off the coast. Copyright © 2002 Royal Meteorological Society.

In a statistical analysis of more than a century of data, a strong connection was found between strong warm El Nino winter events and high spring precipitation in a band from southern England eastwards into Asia. This relationship is an extension of the connection mentioned by Kiladis and Diaz (1989. ‘Global climatic anomalies associated with extremes in the Southern Oscillation’, J. Climate, 2, 1069–1090), and is much stronger than the winter season teleconnection that has been the subject of other studies. Correlation coefficients between December–January (DJF) NINO3 indices and March–May (MAM) precipitation are higher than r=0.3 for individual stations, and as high as r=0.49 for an index of precipitation anomalies around 50°N from 5°W to 35°E. The lagged correlation suggests that southeast Asian surface temperature anomalies may act as intermediate variables. Copyright © 2000 Royal Meteorological Society