David B. Stephenson

Global observed changes in daily climate extremes of temperature and precipitation

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

Forecast verification : a practitioner's guide in atmospheric science

List of Contributors. Preface. 1. Introduction (I. Jolliffe & D. Stephenson). 2. Basic Concepts (J. Potts). 3. Binary Events (I. Mason). 4. Categorical Events (R. Livezey). 5. Continuous Variables (M. Deque). 6. Verification of Spatial Fields (W. Drosdowsky & H. Zhang). 7. Probability and Ensemble Forecasts (Z. Toth, et al.). 8. Economic Value and Skill (D. Richardson). 9. Forecast Verification: Past, Present and Future (D. Stephenson & I. Jolliffe). Glossary. References. Author Index. Subject Index.

Arctic oscillation or North Atlantic oscillation

The definition and interpretation of the Arctic oscillation (AO) are examined and compared with those of the North Atlantic oscillation (NAO). It is shown that the NAO reflects the correlations between the surface pressure variability at its centers of action, whereas this is not the case for the AO. The NAO pattern can be identified in a physically consistent way in principal component analysis applied to various fields in the Euro-Atlantic region. A similar identification is found in the Pacific region for the Pacific‐North American (PNA) pattern, but no such identification is found here for the AO. The AO does reflect the tendency for the zonal winds at 358 and 558N to anticorrelate in both the Atlantic and Pacific regions associated with the NAO and PNA. Because climatological features in the two ocean basins are at different latitudes, the zonally symmetric nature of the AO does not mean that it represents a simple modulation of the circumpolar flow. An increase in the AO or NAO implies strong, separated tropospheric jets in the Atlantic but a weakened Pacific jet. The PNA has strong related variability in the Pacific jet exit, but elsewhere the zonal wind is similar to that related to the NAO. The NAO-related zonal winds link strongly through to the stratosphere in the Atlantic sector. The PNA-related winds do so in the Pacific, but to a lesser extent. The results suggest that the NAO paradigm may be more physically relevant and robust for Northern Hemisphere variability than is the AO paradigm. However, this does not disqualify many of the physical mechanisms associated with annular modes for explaining the existence of the NAO.

NORTH ATLANTIC OSCILLATION - CONCEPTS AND STUDIES

This paper aims to provide a comprehensive review of previous studies and concepts concerning the North Atlantic Oscillation. The North Atlantic Oscillation (NAO) and its recent homologue, the Arctic Oscillation/Northern Hemisphere annular mode (AO/NAM), are the most prominent modes of variability in the Northern Hemisphere winter climate. The NAO teleconnection is characterised by a meridional displacement of atmospheric mass over the North Atlantic area. Its state is usually expressed by the standardised air pressure difference between the Azores High and the Iceland Low. ThisNAO index is a measure of the strength of the westerly flow (positive with strong westerlies, and vice versa). Together with the El Niño/Southern Oscillation (ENSO) phenomenon, the NAO is a major source of seasonal to interdecadal variability in the global atmosphere. On interannual and shorter time scales, the NAO dynamics can be explained as a purely internal mode of variability of the atmospheric circulation. Interdecadal variability maybe influenced, however, by ocean and sea-ice processes.

Evidence of trends in daily climate extremes over southern and west Africa

Received 31 May 2005; revised 10 January 2006; accepted 23 March 2006; published 21 July 2006. [1] There has been a paucity of information on trends in daily climate and climate extremes, especially from developing countries. We report the results of the analysis of daily temperature (maximum and minimum) and precipitation data from 14 south and west African countries over the period 1961–2000. Data were subject to quality control and processing into indices of climate extremes for release to the global community. Temperature extremes show patterns consistent with warming over most of the regions analyzed, with a large proportion of stations showing statistically significant trends for all temperature indices. Over 1961 to 2000, the regionally averaged occurrence of extreme cold (fifth percentile) days and nights has decreased by � 3.7 and � 6.0 days/decade, respectively. Over the same period, the occurrence of extreme hot (95th percentile) days and nights has increased by 8.2 and 8.6 days/decade, respectively. The average duration of warm (cold) has increased (decreased) by 2.4 (0.5) days/decade and warm spells. Overall, it appears that the hot tails of the distributions of daily maximum temperature have changed more than the cold tails; for minimum temperatures, hot tails show greater changes in the NW of the region, while cold tails have changed more in the SE and east. The diurnal temperature range (DTR) does not exhibit a consistent trend across the region, with many neighboring stations showing opposite trends. However, the DTR shows consistent increases in a zone across Namibia, Botswana, Zambia, and Mozambique, coinciding with more rapid increases in maximum temperature than minimum temperature extremes. Most precipitation indices do not exhibit consistent or statistically significant trends across the region. Regionally averaged total precipitation has decreased but is not statistically significant. At the same time, there has been a statistically significant increase in regionally averaged daily rainfall intensity and dry spell duration. While the majority of stations also show increasing trends for these two indices, only a few of these are statistically significant. There are increasing trends in regionally averaged rainfall on extreme precipitation days and in maximum annual 5-day and 1-day rainfall, but only trends for the latter are statistically significant.

Is the North Atlantic Oscillation a random walk

The North Atlantic Oscillation (NAO) is a major mode of large-scale climate variability which contains a broad spectrum of variations. There are substantial contributions from short-term 2–5 year variations, which have clearly marked teleconnections. Decadal trends are also apparent in the historical record of the NAO and may be due to either stochastic or deterministic processes. Evidence is presented that suggests the NAO exhibits ‘long-range’ dependence having winter values residually correlated over many years. Several simple stochastic models have been used to fit the NAO SLP (sea-level pressure) wintertime index over the period 1864–1998, and their performance at predicting the following year has been assessed. Long-range fractionally integrated noise provides a better fit than does either stationary red noise or a non-stationary random walk. Copyright

Use of the “Odds Ratio” for Diagnosing Forecast Skill

This study investigates ways of quantifying the skill in forecasts of dichotomous weather events. The odds ratio, widely used in medical studies, can provide a powerful way of testing the association between categorical forecasts and observations. A skill score can be constructed from the odds ratio that is less sensitive to hedging than previously used scores. Furthermore, significance tests can easily be performed on the logarithm of the odds ratio to test whether the skill is purely due to chance sampling. Functions of the odds ratio and the Peirce skill score define a general class of skill scores that are symmetric with respect to taking the complement of the event. The study illustrates the ideas using Finley’s classic set of tornado forecasts.

The “normality” of El Niño

The amplitude of the El Nino-Southern Oscillation (ENSO) would be normally distributed if the coupled Pacific ocean-atmosphere were a linear system forced by Gaussian weather noise. Moment estimates of skewness and kurtosis demonstrate that this is not the case for monthly mean anomalies in Pacific sea surface temperatures during 1950–97. The noted predominance of El Nino events compared to La Nina events is related to the high skewness in the eastern Pacific. Skewness and kurtosis both exhibit an intriguing geographical variation from positive in the eastern to negative in the western Pacific. We have also examined Nino-3 indices generated by three climate models having widely different complexity. These exhibit a wide range of skewness and kurtosis values rather different from those found for the observations. Skewness and kurtosis can be used to diagnose non-linear processes and provide powerful tools for validating models, and for testing observed sea-surface temperatures for the presence of possible climate change.

Observed trends and teleconnections of the Siberian high: A recently declining center of action

Abstract This study investigates variability in the intensity of the wintertime Siberian high (SH) by defining a robust SH index (SHI) and correlating it with selected meteorological fields and teleconnection indices. A dramatic trend of –2.5 hPa decade−1 has been found in the SHI between 1978 and 2001 with unprecedented (since 1871) low values of the SHI. The weakening of the SH has been confirmed by analyzing different historical gridded analyses and individual station observations of sea level pressure (SLP) and excluding possible effects from the conversion of surface pressure to SLP. SHI correlation maps with various meteorological fields show that SH impacts on circulation and temperature patterns extend far outside the SH source area extending from the Arctic to the tropical Pacific. Advection of warm air from eastern Europe has been identified as the main mechanism causing milder than normal conditions over the Kara and Laptev Seas in association with a strong SH. Despite the strong impacts of the...

A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.