Variability and trends of sub-continental scale surface climate in the twentieth century. Part II: AOGCM simulations

This work presents an analysis of simulated temperature and precipitation variability and trends throughout the twentieth century over 22 land regions of sub-continental scale in the HADCM3 and HADCM2 (two realizations) coupled models. Regional temperature biases in the HADCM3 and HADCM2 are mostly in the range of -5 K to +3 K for the seasonal averages and -3 K to +2 K for the annual average. Seasonal precipitation biases are mostly in the range of -50% to 75% of present day precipitation, with a tendency in both models to overpredict cold season precipitation. Except for cold season temperature in mid- and high-latitude Northern Hemisphere regions, the average climatology of the HADCM2 and HADCM3 is of comparable quality despite the lack of an ocean flux adjustment in the HADCM3. Both models show warming trends of magnitude in line with observations, although the observed inter-regional patterns of warming trend are not well reproduced. Measures of temperature and precipitation interannual to interdecadal variability in the models are in general agreement with observations except for Northern Hemisphere summer temperature variability, which is overestimated. The models somewhat underestimate the inter-decadal variations in interannual variability measures observed during the century and overestimate the range of anomalies. Both models tend to overpredict the occurrences of short persistences (1-3 years) and underpredict the occurrence and maximum length of long persistences (greater than three years), which is an indication of a deficiency in the simulation of long-lived anomaly regimes. Compared to observations, the models produce a higher magnitude of temporal anomaly correlation across regions and correlation between temperature and precipitation anomalies for a given region. This suggests that local processes that may be effective in decoupling the observed regional anomalies are not captured well. Overall, the variability measures in the HADCM2 and HADCM3 are of similar quality, indicating that the use of a flux correction in the HADCM2 does not strongly affect the regional variability characteristics of the model.     

Mid-twenty-first century climate change in the Central United States. Part II: Climate change processes

Ensemble regional model simulations over the central US with 30-km resolution are analyzed to investigate the physical processes of projected precipitation changes in the mid-twenty-first century under greenhouse gas forcing. An atmospheric moisture balance is constructed, and changes in the diurnal cycle are evaluated. Wetter conditions over the central US in April and May occur most strongly in the afternoon and evening, supported primarily by moisture convergence by transient eddy activity, indicating enhanced daytime convection. In June, increased rainfall over the northern Great Plains is strongest from 0000 to 0600 LT. It is supported by positive changes in stationary meridional moisture convergence related to a strengthening of the GPLLJ accompanied by an intensification of the western extension of the North Atlantic subtropical high. In the Midwest, decreased rainfall is strongest at 1500 LT and 0000 LT. Both a suppression of daytime convection as well as changes in the zonal flow in the GPLLJ exit region are important. Future drying over the northern Great Plains in summer is triggered by weakened daytime convection, and persists throughout August and September when a deficit in soil moisture develops and land–atmosphere feedbacks become increasingly important.     

Communicating global climate change using simple indices: an update

Previous studies have shown that there are several indices of global-scale temperature variations, in addition to global-mean surface air temperature, that are useful for distinguishing natural internal climate variations from anthropogenic climate change. Appropriately defined, such indices have the ability to capture spatio-temporal information in a similar manner to optimal fingerprints of climate change. These indices include the contrast between the average temperatures over land and over oceans, the Northern Hemisphere meridional temperature gradient, the temperature contrast between the Northern and Southern Hemisphere and the magnitude of the annual cycle of average temperatures over land. They contain information independent of the global-mean temperature for internal climate variations at decadal time scales and represent different aspects of the climate system, yet they show common responses to anthropogenic climate change. In addition, the ratio of average temperature changes over land to those over the oceans should be nearly constant for transient climate change. Hence, supplementing analysis of global-mean surface temperature with analyses of these indices can strengthen results of attribution studies of causes of observed climate variations. In this study, we extend the previous work by including the last 10 years of observational data and the CMIP3 climate model simulations analysed for the IPCC AR4. We show that observed changes in these indices over the last 10 years provide increased evidence of an anthropogenic influence on climate. We also show the usefulness of these indices for evaluating the performance of climate models in simulating large-scale variability of surface temperature.     

Atlantic tropical cyclones in the twentieth century: natural variability and secular change in cyclone count

The twentieth century record of the annual count of Atlantic tropical cyclones (TCs) is analyzed to develop consistent estimates of its natural variability and secular change components. The analysis scheme permits development of multidecadal trends from natural variability alone, reducing aliasing of the variability and change components. The scheme is rooted in recurrent variability modes of the influential SST field and cognizant of Pacific-Atlantic links. The origin of increased cyclone counts in the early 1930s, suppressed counts in 1950?C1960s, and the recent increase (since 1990s) is investigated using the count data set developed by Landsea et al. (J Clim 23: 2508?C2519, 2010). We show that annual TC counts can be more closely reconstructed from Pacific and Atlantic SSTs than SST of the main development region (MDR) of Atlantic TCs; the former accounting for ~60% of the decadal count variance as opposed to ~30% for MDR SST. Atlantic Multidecadal Oscillation (AMO) dominates the reconstruction, accounting for ~55% of the natural decadal count variance, followed by the ENSO Non-Canonical and Pan-Pacific decadal variability contributions. We argue for an expansive view of the domain of influential SSTs??extending much beyond the MDR. The additional accounting of count variance by SSTs outside the MDR suggests a role for remotely-forced influences over the tropical Atlantic: the Pan-Pacific decadal mode is linked with decreased westerly wind shear (200?C850?hPa) in its warm phase, much as the AMO impact itself. Non-canonical ENSO variability, in contrast, exerts little influence on decadal timescales. Interestingly, the secular but non-uniform warming of the oceans is linked with increased westerly shear, leading to off-setting dynamical and thermodynamical impacts on TC activity! The early-1930s increase in smoothed counts can be partially (~50%) reconstructed from SST natural variability. The 1950?C1960s decrease, in contrast, could not be reconstructed at all, leading, deductively, to the hypothesis that it results from increased aerosols in this period. The early-1990s increase is shown to arise both from the abatement of count suppression maintained by SST natural variability and the increasing SST secular trend contribution; the abatement is related to the AMO phase-change in early-1990s. Were it not for this suppression, TC counts would have risen since the early 1970s itself, tracking the secular change contribution. The analysis suggests that when SST natural variability begins to significantly augment counts in the post-1990 period??some evidence for which is present in the preceding decade??Atlantic TC counts could increase rapidly on decadal timescales unless offset by SST-unrelated effects which apparently account for a non-trivial amount (~40%) of the decadal count variance.     

Variability and trends of sub-continental scale surface climate in the twentieth century. Part I: observations

An analysis is presented of observed temperature and precipitation variability and trends throughout the twentieth century over 22 land regions of sub-continental scale. Summer, winter and annual data are examined using a range of variability measures. Statistically significant warming trends are found over the majority of regions. The trends have a magnitude of up to 2 K per century and are maximum over cold climate regions. Only a few precipitation trends are statistically significant. Regional temperature and precipitation show pronounced variability at scales from interannual to multidecadal, with maximum over cold climate regions. The interannual variability shows significant variations and trends throughout the century, the latter being mostly negative for precipitation and both positive and negative for temperature. Temperature and precipitation anomalies show a chaotic-type behavior in which the regional conditions oscillate around the long term mean trend and occasionally fall into long-lasting (up to 10 years or more) anomaly regimes. A generally modest temporal correlation is found between anomalies of different regions and between temperature and precipitation anomalies for the same region. This correlation is mostly positive for temperature in cases of adjacent regions or regions in the same latitude belts. Several cases of negative inter-regional precipitation anomaly correlation are found. The ENSO significantly affects the anomaly variability patterns over a number of regions, primarily in tropical areas, while the NAO significantly affects the variability over northern mid- and high-latitude regions of Europe and Asia.     

Climate change in Hungary during the twentieth century according to Feddema

Theoretical and Applied Climatology - Climate change in Hungary during the twentieth century is analyzed using Feddema’s original scheme suitable for global scale applications (F-GS) and...     

Twentieth century North Atlantic climate change. Part II: Understanding the effect of Indian Ocean warming

Ensembles of atmospheric general circulation model (AGCM) experiments are used in an effort to understand the boreal winter Northern Hemisphere (NH) extratropical climate response to the observed warming of tropical sea surface temperatures (SSTs) over the last half of the twentieth Century. Specifically, we inquire about the origins of unusual, if not unprecedented, changes in the wintertime North Atlantic and European climate that are well described by a linear trend in most indices of the North Atlantic Oscillation (NAO). The simulated NH atmospheric response to the linear trend component of tropic-wide SST change since 1950 projects strongly onto the positive polarity of the NAO and is a hemispheric pattern distinguished by decreased (increased) Arctic (middle latitude) sea level pressure. Progressive warming of the Indian Ocean is the principal contributor to this wintertime extratropical response, as shown through additional AGCM ensembles forced with only the SST trend in that sector. The Indian Ocean influence is further established through the reproducibility of results across three different models forced with identical, idealized patterns of the observed warming. Examination of the transient atmospheric adjustment to a sudden “switch-on” of an Indian Ocean SST anomaly reveals that the North Atlantic response is not consistent with linear theory and most likely involves synoptic eddy feedbacks associated with changes in the North Atlantic storm track. The tropical SST control exerted over twentieth century regional climate underlies the importance of determining the future course of tropical SST for regional climate change and its uncertainty. Better understanding of the extratropical responses to different, plausible trajectories of the tropical oceans is key to such efforts.     

Mid-twenty-first century warm season climate change in the Central United States. Part I: regional and global model predictions

A regional climate model (RCM) constrained by future anomalies averaged from atmosphere–ocean general circulation model (AOGCM) simulations is used to generate mid-twenty-first century climate change predictions at 30-km resolution over the central U.S. The predictions are compared with those from 15 AOGCM and 7 RCM dynamic downscaling simulations to identify common climate change signals. There is strong agreement among the multi-model ensemble in predicting wetter conditions in April and May over the northern Great Plains and drier conditions over the southern Great Plains in June through August for the mid-twenty-first century. Projected changes in extreme daily precipitation are statistically significant over only a limited portion of the central U.S. in the RCM constrained with future anomalies. Projected changes in monthly mean 2-m air temperature are generally consistent across the AOGCM ensemble average, North American Regional Climate Change Assessment Program RCM ensemble average, and RCM constrained with future anomalies, which produce a maximum increase in August of 2.4–2.9 K over the northern and southern Great Plains and Midwest. Changes in extremes in daily 2-m air temperature from the RCM downscaled with anomalies are statistically significant over nearly the entire Great Plains and Midwest and indicate a positive shift in the warm tail of the daily 2-m temperature distribution that is larger than the positive shift in the cold tail.     

Twentieth century simulation of the southern hemisphere climate in coupled models. Part II: sea ice conditions and variability

We examine the representation of the mean state and interannual variability of Antarctic sea ice in six simulations of the twentieth century from coupled models participating in the Intergovernmental Panel on Climate Change fourth assessment report. The simulations exhibit a largely seasonal southern hemisphere ice cover, as observed. There is a considerable scatter in the monthly simulated climatological ice extent among different models, but no consistent bias when compared to observations. The scatter in maximum winter ice extent among different models is correlated to the strength of the climatological zonal winds suggesting that wind forced ice transport is responsible for much of this scatter. Observations show that the leading mode of southern hemisphere ice variability exhibits a dipole structure with anomalies of one sign in the Atlantic sector associated with anomalies of the opposite sign in the Pacific sector. The observed ice anomalies also exhibit eastward propagation with the Antarctic circumpolar current, as part of the documented Antarctic circumpolar wave phenomenon. Many of the models do simulate dipole-like behavior in sea ice anomalies as the leading mode of ice variability, but there is a large discrepancy in the eastward propagation of these anomalies among the different models. Consistent with observations, the simulated Antarctic dipole-like variations in the ice cover are led by sea-level pressure anomalies in the Amundsen/ Bellingshausen Sea. These are associated, to different degrees in different models, with both the southern annular mode and the El Nino-Southern Oscillation (ENSO). There are indications that the magnitude of the influence of ENSO on the southern hemisphere ice cover is related to the strength of ENSO events simulated by the different models.     

Dissecting indices of aridity for assessing the impacts of global climate change

There is great interest in understanding how climate change will impact aridity through the interaction of precipitation changes with rising temperatures. The Aridity Index (AI), Climatic Moisture Deficit (CMD), and Climatic Moisture Surplus (CMS) are metrics commonly used to quantify and map patterns in aridity and water cycling. Here we show that these metrics have different patterns of change under future climate—based on an ensemble of nine general circulation climate models—and the different metrics are appropriate for different purposes. Based on these differences between the metrics, we propose that aridity can be dissected into three different types—hydrological (CMS), agricultural (CMD), and meteorological. In doing this, we propose a novel modified version of the Aridity Index, called AI+, that can be useful for assessing changes in meteorological aridity. The AI?+?is based on the same ratio between precipitation and evapotranspiration as the traditional AI, but unlike the traditional AI, the AI?+?only accounts for changes to precipitation during months when precipitation is less than reference/potential evapotranspiration (i.e. there is a deficit). Moreover, we show that the traditional AI provides a better estimate of change in moisture surplus driven by changes to precipitation during the wet season, rather than changes in deficit that occur during the drier seasons. These results show that it is important to select the most appropriate metric for assessing climate driven changes in aridity.     

Twentieth century north atlantic climate change. Part I: assessing determinism

Boreal winter North Atlantic climate change since 1950 is well described by a trend in the leading spatial structure of variability, known as the North Atlantic Oscillation (NAO). Through diagnoses of ensembles of atmospheric general circulation model (AGCM) experiments, we demonstrate that this climate change is a response to the temporal history of sea surface temperatures (SSTs). Specifically, 58 of 67 multi-model ensemble members (87%), forced with observed global SSTs since 1950, simulate a positive trend in a winter index of the NAO, and the spatial pattern of the multi-model ensemble mean trend agrees with that observed. An ensemble of AGCM simulations with only tropical SST forcing further suggests that variations in these SSTs are of primary importance. The probability distribution function (PDF) of 50-year NAO index trends from the forced simulations are, moreover, appreciably different from the PDF of a control simulation with no interannual SST variability, although chaotic atmospheric variations are shown to yield substantial 50-year trends. Our results thus advance the view that the observed linear trend in the winter NAO index is a combination of a strong tropically forced signal and an appreciable noise component of the same phase. The changes in tropical rainfall of greatest relevance include increased rainfall over the equatorial Indian Ocean, a change that has likely occurred in nature and is physically consistent with the observed, significant warming trend of the underlying sea surface.     

An intercomparison of model-simulated in extreme rainfall and temperature events during the last half of the twentieth century. Part 1: mean values and variability

In this study we examine the performance of eight of the IPCC AR4 global coupled climate models used in the WCRP CMIP3 Multimodel Dataset, as well as their ensemble mean, in simulating annual indices of extreme temperature and precipitation climate events in South America. In this first part we focus on comparing observed and modeled mean values and interannual variability. Two extreme temperature indices based on minimum temperature (warm nights and frost days) and three indices of extreme precipitation (R95t, R10 and consecutive dry days), obtained both from meteorological stations during 1961–2000 and model outputs, were compared. The number of warm nights are better represented by models than the FD. The interannual variability pattern is also in good agreement with the observed values. For precipitation, the index that is best represented by the models is the R95t, which relates the extreme precipitation to local climate. The maximum of dryness observed over the central Argentinian Andes or the extensive dry season of the Amazon region could not be represented by any model.     

Temporal rainfall variability in the Lake Victoria Basin in East Africa during the twentieth century

Water resources systems are designed and operated on assumption of stationary hydrology. Existence of trends and other changes in the data invalidates this assumption, and detection of the changes in hydrological time series should help us revise the approaches used in assessing, designing and operating our systems. In addition, trend and step change studies help us understand the impact of man’s activities (e.g. urbanisation, deforestation, dam construction, agricultural activities, etc.) on the hydrological cycle. Trends and step changes in the seasonal and annual total rainfall for 20 stations in the Lake Victoria basin were analysed. The seasonal rainfall for any station in a given year was defined in two ways: (1) fixed time period where the rainy seasons were taken as occurring from March–May (long rains) and from October–December (short rains); and (2) variable periods where the rainy seasons were taken as the three consecutive months with maximum total rainfall covering the period of January–June (long rains) and July–December (short rains), to take into account the fact that the onset of rainy seasons within the basin varies from year to year and from one station to the next. For each station, sub datasets were derived covering different periods (all available data at the station, 1941–1980, 1961–1990, 1971–end of each station’s time series). The trends were analysed using the Mann-Kendall method, while the step changes were analysed using the Worsley Likelihood method. The results show that positive trends predominate, with most stations showing trend being located in the northern part of the basin, though this pattern is not conclusive. In all, 17% of the cases have trends, of which 67% are positive. The 1960s represent a significant upward jump in the basin rainfall. Seasonal rainfall analysis shows that the short rains tend to have more trends than the long rains. The impact of the varying month of onset of the rainy season is that the results from analyzing the fixed-period and variable-period time series are rarely the same, meaning the two series have different characteristics. It may be argued that the variable-period time series are more reliable as a basis for analysing trends and step changes, since these time series reflect more closely the actual variability in rainy seasons from one year to the next. The fixed-period analysis would, on the other hand, find more practical use in planning.     

Climate variability and change in Bulgaria during the 20th century

Summary Climate data used for climate variability and change analyses, must be homogeneous, to be accurate. The data currently used in the Météo-France homogenization procedure, which does not require computation of regional reference series, was applied to precipitation and average air temperature series in Bulgaria. The Caussinus-Mestre method, with a double-step procedure, was used to detect multiple breaks and outliers in the long-term series of precipitation and average air temperature. A two factor linear model was applied for break correction. The homogenization procedure was run till all or most break risk was gone. Analysis of climate variability and change in Bulgaria during the 20^th century was done on already homogenized precipitation and average air temperature series. The statistical significance of the trends obtained was evaluated by the coefficient of Spearman rank correlation. The variations of annual precipitation in Bulgaria showed an overall decrease. The country has experienced several drought episodes during the 20^th century, most notably in the 1940s and 1980s. Seasonal precipitation in spring shows a positive trend at most weather stations across the country. The trend for summer and autumn precipitation is negative. A statistically significant increasing trend of winter precipitation in north Bulgaria was detected. No significant warming trend in the country was found during the last century inspite of the warming observed during the last two decades. Summer in Bulgaria tends to be warmer from the beginning of the 1980s. There is a statistically significant increasing trend of average air temperature during the winter season at the weather stations near the Danube river (north Bulgaria) during the periods 1901–2000 and 1931–2000.     

A scenario of European climate change for the late twenty-first century: seasonal means and interannual variability

A scenario of European climate change for the late twenty-first century is described, using a high-resolution state-of-the-art model. A time-slice approach is used, whereby the atmospheric general circulation model, HadAM3P, was integrated for two periods, 1960–1990 and 2070–2100, using the SRES A2 scenario. For the first time an ensemble of such experiments was produced, along with appropriate statistical tests for assessing significance. The focus is on changes to the statistics of seasonal means, and includes analysis of both multi-year means and interannual variance. All four seasons are assessed, and anomalies are mapped for surface air temperature, precipitation and snow mass. Mechanisms are proposed where these are dominated by straightforward local processes. In winter, the largest warming occurs over eastern Europe, up to 7°C, mean snow mass is reduced by at least 80% except over Scandinavia, and precipitation increases over all but the southernmost parts of Europe. In summer, temperatures rise by 6–9°C south of about 50°N, and mean rainfall is substantially reduced over the same area. In spring and autumn, anomalies tend to be weaker, but often display patterns similar to the preceding season, reflecting the inertia of the land surface component of the climate system. Changes in interannual variance are substantial in the solsticial seasons for many regions (note that for precipitation, variance estimates are scaled by the square of the mean). In winter, interannual variability of near-surface air temperature is considerably reduced over much of Europe, and the relative variability of precipitation is reduced north of about 50°N. In summer, the (relative) interannual variance of both variables increases over much of the continent.     

Scientific uncertainty and climate change: Part II. Uncertainty and mitigation

In public debate surrounding climate change, scientific uncertainty is often cited in connection with arguments against mitigative action. This article examines the role of uncertainty about future climate change in determining the likely success or failure of mitigative action. We show by Monte Carlo simulation that greater uncertainty translates into a greater likelihood that mitigation efforts will fail to limit global warming to a target (e.g., 2 °C). The effect of uncertainty can be reduced by limiting greenhouse gas emissions. Taken together with the fact that greater uncertainty also increases the potential damages arising from unabated emissions (Lewandowsky et al. 2014), any appeal to uncertainty implies a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.     

Variability and trends of local/regional scale surface climate in northern Africa during the twentieth century

Four regions are detected in northern Africa (20° W–40° E, 0–30° N) by applying the cluster analysis method on the annual rainfall anomalies of the period 1901–2000. The first region (R1), an arid land, covers essentially the north of 17.75° N from west to east of the study zone. The second region (R2), a semiarid land with a Sahelian climate, less warm than the dry climate of R1, is centred on Chad, with almost regular extension to the west towards Mauritania, and to the east, including the north of the Central African Republic and the Sudan. The region 3 (R3), a wet land, is centred on the Ivory Coast and covers totally Liberia, the south part of Ghana, Togo, Benin and the southwest of Nigeria. The fourth region (R4), corresponding to the wet equatorial forest, covers a part of Senegal, the Central Africa, the south of Sudan and a part of Ethiopia. An analysis of observed temperature and precipitation variability and trends throughout the twentieth century over these regions is presented. Summer, winter and annual data are examined using a range of variability measures. Statistically, significant warming trends are found over the majority of regions. The trends have a magnitude of up to 1.5 K per century. Only a few precipitation trends are statistically significant. Regional temperature and precipitation show pronounced variability at scales from interannual to multi-decadal. The interannual variability shows significant variations and trends throughout the century, the latter being mostly negative for precipitation and both positive and negative for temperature. Temperature and precipitation anomalies show a chaotic-type behaviour in which the regional conditions oscillate around the long-term mean trend and occasionally fall into long-lasting (up to 10 years or more) anomaly regimes. A generally modest temporal correlation is found between anomalies of different regions and between temperature and precipitation anomalies for the same region. This correlation is mostly positive for temperature in cases of adjacent regions. Several cases of negative interregional precipitation anomaly correlation are found. The El Niño Southern Oscillation significantly affects the anomaly variability patterns over a number of regions, mainly regions 3 (R3) and 4 (R4), while the North Atlantic Oscillation significantly affects the variability over arid and semiarid regions, R1 and R2.     

Changes in daily and nightly day-to-day temperature variability during the twentieth century for two stations in Switzerland

Summary  An analysis of day-to-day variability was performed on two century-long daily minimum and maximum temperature series from Switzerland. Warmer temperatures during the 20^th century have been accompanied by a reduction in day-to-day variability, particularly for minimum temperatures and for winter. There is a significant negative correlation between day-to-day variability and the skewness of the temperature distribution, particularly in winter and for minimum temperatures. Lower variability is linked to a reduced number of cold days and nights. Higher NAO index values tend to be associated not only with warmer temperatures but also with lower day-to-day variability. This paper confirms that the temperature warming during the 20^th century has happened mainly through the loss of the coldest part of the series, not only in the 24-hour or yearly cycle, but also through the loss of the coldest episodes in each month. Received September 20, 2000 Revised January 8, 2001