• Air temperature, airport elevation, and aircraft weight influence necessary takeoff speed • Takeoff speed determines necessary runway length • At high temperatures or elevations, aircraft may be weight restricted if runway length is not sufficient.

Резюме. Метеорологические условия в температурном диапазоне около нуля градусов Цельсия являются в высшей степени некомфортными и, в некоторых условиях, опасными. Для исследования их особенностей в комплексе, были использованы совместные функции распределения вероятности для двух метеорологических величин (в разных вариантах). Их анализ показал, что совокупность экстремумов скорости ветра в диапазоне температуры около нуля содержит смесь двух различных по генезису данных, причем каждое из подмножеств хорошо описывается распределением Вейбулла. Используя современную метафорическую терминологию, их можно отнести к черным лебедям и драконам. В то же время экстремумы осадков принадлежат только к одной совокупности. Данные модели земной системы INMCM4 содержат только экстремумы, относящиеся к черным лебедям. Важными показателями, характеризующими метеорологические условия около нуля градусов, являются даты устойчивого перехода через ноль. Такой переход происходит весной и осенью. Показано, что глобальное потепление проявляется в сдвиге этих дат. Вдоль трансекта поперек Кольского полуострова интервал между осенним и весенним переходами возрастет к концу 21 века на величину от 1 месяца на юге до 2.5 месяцев на севере. Ключевые слова. Изменения климата, Кольский полуостров, температурный диапазон «около 0oС», черные лебеди, драконы.

type="main" xml:id="rssb12058-abs-0001"> The paper focuses primarily on temperature extremes measured at 24 European stations with at least 90 years of data. Here, the term extremes refers to rare excesses of daily maxima and minima. As mean temperatures in this region have been warming over the last century, it is automatic that this positive shift can be detected also in extremes. After removing this warming trend, we focus on the question of determining whether other changes are still detectable in such extreme events. As we do not want to hypothesize any parametric form of such possible changes, we propose a new non-parametric estimator based on the Kullback–Leibler divergence tailored for extreme events. The properties of our estimator are studied theoretically and tested with a simulation study. Our approach is also applied to seasonal extremes of daily maxima and minima for our 24 selected stations.

[1] The prealpine Rietholzbach research catchment provides long-term continuous hydroclimatological measurements in northeastern Switzerland, including lysimeter evapotranspiration measurements since 1976, and soil moisture measurements since 1994. We analyze here the monthly data record over 32 years (1976–2007), with a focus on the extreme 2003 European drought. In particular, we assess whether the well-established hypothesis that the 2003 event was due to spring precipitation deficits is valid at the site. The Rietholzbach measurements are found to be internally consistent and representative for a larger region in Switzerland. Despite the scale discrepancy (3.14 m2 versus 3.31 km2), the lysimeter seepage and catchment-wide streamflow show similar monthly dynamics. High correlations are further found with other streamflow measurements within the Thur river basin (1750 km2) and—for interannual anomalies—also in most of northern Switzerland. Analyses for 2003 confirm the occurrence of extreme heat and drought conditions at Rietholzbach. However, unlike findings from regional-scale modeling studies, they reveal a late onset of the soil moisture deficit (from June onward), despite large precipitation deficits from mid-February to mid-April. These early spring deficits were mostly compensated for by decreased runoff during this period and excess precipitation in the preceding weeks to months (including in the 2002 fall). Our results show that evapotranspiration excess in June 2003 was the main driver initiating the 2003 summer drought conditions in Rietholzbach, contributing 60% of the June 2003 water storage deficit. Finally, long-lasting drought effects on the lysimeter water storage due to rewetting inhibition were recorded until spring 2004.

[1] The potential impact of climate change on the variability structure of climate has been investigated predominately through changes to extreme event frequency or the shape of the daily frequency distribution. Recent change to interannual climate variability has received less attention. Here we report that the interannual variability of temperature and precipitation has marginally decreased since 1970. However, within this marginal decrease the inter-decadal component of interannual variability has decreased for both temperature and precipitation. The temperature results are consistent across urban and rural stations indicating that they are not due to any urbanisation effect.

[1] Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000–2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both PT and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as PT. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change.

[1] Land subsidence in drained cultivated peatlands is responsible for a number of serious environmental concerns and economical problems at both the local and the global scale. In low-lying coastal areas it enhances the risk of flooding, the saltwater contamination of shallow aquifers, and the maintenance costs of the systems that help keep the farmland drained. Since the subsidence is a major consequence of the bio-oxidation of the soil organic fraction in the upper aerated zone, cropped peatlands in temperate and tropic regions are important sources of CO2 into the atmosphere. A 4-year long experimental study has been performed in a drained peatland located south of the Venice Lagoon, Italy, to help calibrate a land subsidence model developed to predict the expected behavior of the ground surface elevation. Continuous monitoring of the hydrological regime and land displacements shows that the vertical movement of the peat surface consists of the superimposition of daily/seasonal time-scale reversible deformations related to soil moisture, depth to the water table, and temperature fluctuations, and long term irreversible subsidence due to peat oxidation. A novel two-step modeling approach to separate the two contributions from the available observations is presented. First, the elastic component is computed by integrating the peat vertical deformations evaluated by a constitutive relationship describing the porosity variation with the moisture content and pore pressure changes implemented into a variably saturated flow equation-based numerical code. The observed trend is then filtered from the computed reversible displacement and is used to calibrate an empirical relationship relating land subsidence rate to drainage depth and soil temperature. The results show that in recent years the subsidence rate ranged from 3 to 15 mm a−1. The large variability is due to the different climate conditions underlying the monitoring period, in particular a wet 2002 and a very dry 2003. The model is then used to investigate the effect of human activities and climate change on the expected reduction of the peat thickness. The results suggest that the long term subsidence is mainly controlled by the manner in which the water table is managed in the peatland. For example, the subsidence rate is almost halved if the current 0.5 m mean water table depth is kept at 0.2 m. Conversely, even the extreme warning scenario provided by the IPCC in 2007 do not suggest significant changes on the expected subsidence trend, at least in low lying reclamation areas where the average temperature rise should not be accompanied by a significant reduction of water availability.

[1] In this study, we evaluate the accuracy of four regional climate models (NHRCM, NRAMS, TRAMS, and TWRF) and one bias correction-type statistical model (CDFDM) for daily precipitation indices under the present-day climate (1985–2004) over Japan on a 20 km grid interval. The evaluated indices are (1) mean precipitation, (2) number of days with precipitation ≥1 mm/d (corresponds to number of wet days), (3) mean amount per wet day, (4) 90th percentile of daily precipitation, and (5) number of days with precipitation ≥90th percentile of daily precipitation. The boundary conditions of the dynamical models and the predictors of the statistical model are given from the single reanalysis data, i.e., JRA25. Both types of models successfully improved the accuracy of the indices relative to the reanalysis data in terms of bias, seasonal cycle, geographical pattern, cumulative distribution function of wet-day amount, and interannual variation pattern. In most aspects, NHRCM is the best model of all indices. Through the intercomparison between the dynamical and statistical models, respective strengths and weaknesses emerged. Briefly, (1) many dynamical models simulate too many wet days with a small amount of precipitation in humid climate zones, such as summer in Japan, relative to the statistical model, unless the cumulus convection scheme improved for such a condition is incorporated; (2) a few dynamical models can derive a better high-order percentile of daily precipitation (e.g., 90th percentile) than the statistical model; (3) both the dynamical and statistical models are still insufficient in the representation of the interannual variation pattern of the number of days with precipitation ≥90th percentile of daily precipitation; (4) the statistical model is comparable to the dynamical models in the long-term mean geographical pattern of the indices even on a 20 km grid interval if a dense observation network is applicable; (5) the statistical model is less accurate than the dynamical models in the temporal variation pattern due to the strong dependence of the predictand on the relatively less accurate predictor (daily reanalysis precipitation); and (6) the simple statistical model is less plausible in the physical sense because of the oversimplification of underlying physical processes compared to the dynamical models and more sophisticated statistical models.

[1] In a future climate warmed by increased greenhouse gases, increases of precipitation intensity do not have a uniform spatial distribution. Here we analyze a multi-model AOGCM data set to examine processes that produce the geographic pattern of these precipitation intensity changes over land. In the tropics, general increases in water vapor associated with positive SST anomalies in the warmer climate produce increased precipitation intensity over most land areas. In the midlatitudes, the pattern of precipitation intensity increase is related in part to the increased water vapor being carried to areas of mean moisture convergence to produce greater precipitation, as well as to changes in atmospheric circulation. Advective effects, indicated by sea level pressure changes, contribute to greatest precipitation intensity increases (as well as mean precipitation increases) over northwestern and northeastern North America, northern Europe, northern Asia, the east coast of Asia, southeastern Australia, and south-central South America.

[1] In November 2004, a regional climate change workshop was held in Guatemala with the goal of analyzing how climate extremes had changed in the region. Scientists from Central America and northern South America brought long-term daily temperature and precipitation time series from meteorological stations in their countries to the workshop. After undergoing careful quality control procedures and a homogeneity assessment, the data were used to calculate a suite of climate change indices over the 1961–2003 period. Analysis of these indices reveals a general warming trend in the region. The occurrence of extreme warm maximum and minimum temperatures has increased while extremely cold temperature events have decreased. Precipitation indices, despite the large and expected spatial variability, indicate that although no significant increases in the total amount are found, rainfall events are intensifying and the contribution of wet and very wet days are enlarging. Temperature and precipitation indices were correlated with northern and equatorial Atlantic and Pacific Ocean sea surface temperatures. However, those indices having the largest significant trends (percentage of warm days, precipitation intensity, and contribution from very wet days) have low correlations to El Nino–Southern Oscillation. Additionally, precipitation indices show a higher correlation with tropical Atlantic sea surface temperatures.

[1] Gridded daily temperature from 1950 to 2011 and atmospheric CO2concentration data from high-latitude observing stations and the CarbonTracker assimilation system are used to examine recent spatiotemporal variability of the thermal growing season and its relationship with seasonal biospheric carbon uptake and release in the Northern Hemisphere. The thermal growing season has lengthened substantially since 1950 but most of the lengthening has occurred during the last three decades (2.9 days decade−1, p 0.05). Unlike most previous studies, which had more limited data coverage over the past decade, we find that strong autumn warming of about 1°C during the second half of the 2000s has led to a significant shift toward later termination of the thermal growing season, resulting in the longest potential growing seasons since 1950. On average, the thermal growing season has extended symmetrically by about a week during this period, starting some 4.0 days earlier and ending about 4.3 days later. The earlier start of the thermal growing season is associated with earlier onset of the biospheric carbon uptake period at high northern latitudes. In contrast, later termination of the growing season is associated with earlier termination of biospheric carbon uptake, but this relationship appears to have decoupled since the beginning of the period of strong autumn warming during the second half of the 2000s. Therefore, owing to these contrasting biospheric responses at the margins of the growing season, the current extension in the thermal growing season length has not led to a concomitant extension of the period of biospheric carbon uptake.

[1] Extreme value analysis of observed daily temperature anomalies from a new quasi-global data set indicates that extreme daily maximum and minimum temperatures (>98.5 or <1.5 percentile) have warmed for most regions since 1950. Changes in extreme anomalous daily temperatures are determined by fitting extreme value distributions with time-varying parameters. Changes in the distribution of anomaly exceedances above a high threshold are found to be statistically significant at the 10% level for most land areas when compared with a time-invariant distribution and with the unforced natural variability produced by a coupled climate model. The largest positive trends in the location parameter of the extreme distribution are found in Canada and Eurasia where daily maximum temperatures have typically warmed by 1 to 3°C since 1950. The total area exhibiting positive trends is significantly greater than can be attributed to unforced natural variability. For most regions, positive trend magnitudes are larger and cover a greater area for daily minimum temperatures than for maximum temperatures. The comparatively small areas of cooling are found to be consistent with unforced natural climate variability. The North Atlantic Oscillation (NAO) is found to have a significant influence on extreme winter daily temperatures for many areas, with a negative NAO of one standard deviation reducing expected extreme winter daily temperatures by ∼2°C over Eurasia but increasing temperatures over northeastern North America.

[1] Extreme precipitation is generally underestimated by current climate models relative to observations of present-day rainfall distributions. Possible causes of this systematic error include the convective parameterization in these models that have been designed to reproduce measurements of climatological mean precipitation. One possible approach to improve the interaction of subgrid-scale physical processes and large-scale climate is to replace the conventional convective parameterizations with a high-resolution cloud-system resolving model. A “super-parameterized” Community Atmosphere Model (SP-CAM) utilizing this approach is used in this study to investigate the distribution of extreme precipitation in the United States. Results show that SP-CAM better simulates the distributions of both light and intense precipitation compared to the standard version of CAM based upon conventional parameterizations. The improvements are mostly seen in regions dominated by convective precipitation, suggesting that super-parameterization provides a better representation of subgrid convective processes.

[1] Changes in indices of climate extremes are studied on the basis of daily series of temperature and precipitation observations from 116 meteorological stations in central and south Asia. Averaged over all stations, the indices of temperature extremes indicate warming of both the cold tail and the warm tail of the distributions of daily minimum and maximum temperature between 1961 and 2000. For precipitation, most regional indices of wet extremes show little change in this period as a result of low spatial trend coherence with mixed positive and negative station trends. Relative to the changes in the total amounts, there is a slight indication of disproportionate changes in the precipitation extremes. Stations with near-complete data for the longer period of 1901–2000 suggest that the recent trends in extremes of minimum temperature are consistent with long-term trends, whereas the recent trends in extremes of maximum temperature are part of multidecadal climate variability.

[1] Changes in indices of climate extremes are analyzed on the basis of daily maximum and minimum surface air temperature and precipitation at 71 meteorological stations with elevation above 2000 m above sea level in the eastern and central Tibetan Plateau (TP) during 1961–2005. Twelve indices of extreme temperature and nine indices of extreme precipitation are examined. Temperature extremes show patterns consistent with warming during the studied period, with a large proportion of stations showing statistically significant trends for all temperature indices. Stations in the northwestern, southwestern, and southeastern TP have larger trend magnitudes. The regional occurrence of extreme cold days and nights has decreased by −0.85 and −2.38 d/decade, respectively. Over the same period, the occurrence of extreme warm days and nights has increased by 1.26 and 2.54 d/decade, respectively. The number of frost days and ice days shows statistically significant decreasing at the rate of −4.32 and −2.46 d/decade, respectively. The length of growing season has statistically increased by 4.25 d/decade. The diurnal temperature range exhibits a statistically decreasing trend at a rate of −0.20°C per decade. The extreme temperature indices also show statistically significant increasing trends, with larger values for the index describing variations in the lowest minimum temperature. In general, warming trends in minimum temperature indices are of greater magnitude than those for maximum temperature. Most precipitation indices exhibit increasing trends in the southern and northern TP and show decreasing trends in the central TP. On average, regional annual total precipitation, heavy precipitation days, maximum 1-day precipitation, average wet days precipitation, and total precipitation on extreme wet days show nonsignificant increases. Decreasing trends are found for maximum 5-day precipitation, consecutive wet days, and consecutive dry days, but only the last is statistically significant.

[1] A new data set of 45 daily precipitation series, covering quite uniformly Italian territory for the period 1880–2002, was recovered. The series have been homogenized on daily basis, completed by means of statistical methods and grouped into five regions by a Principal Component Analysis. Seasonal and yearly total precipitation, number of wet days, and precipitation intensity were analyzed for each station record and averaged into five regional series for a synthetic description of the results. Proportion and frequency of daily rainfall amounts, belonging to six precipitation class-intervals, defined on the basis of some percentiles of the precipitation distribution, were also analyzed. The results show a negative significant trend in the number of wet days all over Italy, and a positive trend in precipitation intensity, which is significant only in the northern regions. The negative trend in wet days has persisted since the end of 19th century and is due to the marked decrease in the number of low intensity precipitation events. An increase in the number of events belonging to the highest intensity class interval was observed too, but only in northern regions.

[1] A January 2001 workshop held in Kingston, Jamaica, brought together scientists and data from around the Caribbean region and made analysis of indices of extremes derived from daily weather observation in the region possible. The results of the analyses indicate that the percent of days having very warm maximum or minimum temperatures increased strongly since the late 1950s while the percent of days with very cold temperatures decreased. One measure of extreme precipitation shows an increase over this time period while the one analyzed measure of dry conditions, the maximum number of consecutive dry days, is decreasing. These changes generally agree with what is observed in many other parts of the world.

[1] This study first homogenizes time series of daily maximum and minimum temperatures recorded at 825 stations in China over the period from 1951 to 2010, using both metadata and the penalized maximum t test with the first-order autocorrelation being accounted for to detect change points and using the quantile-matching algorithm to adjust the data time series to diminish discontinuities. Station relocation was found to be the main cause for discontinuities, followed by station automation. The effects of discontinuities on estimation of long-term trends in the annual mean and extreme indices of temperature are illustrated. The data homogenization is shown to have improved the spatial consistency of estimated trends. Using the homogenized daily minimum and daily maximum temperature data, this study also analyzes trends in extreme temperature indices. The results show that the vast majority (85%–90%) of the 825 sites have experienced significantly more warm nights and less cold nights since 1951. There have also been more warm days and less cold days since 1951, although these trends are less extensive. About 62% of the 825 sites were found to have experienced significantly more warm days and about 50% significantly less cold days. None of the 825 sites were found to have significantly more cold nights/days or less warm nights/days. These indicate that the warming is stronger in nighttime than in daytime and stronger in winter than in summer. Thus, the diurnal temperature range was found to have significantly decreased at 49% of the 825 sites, with significant increases being identified only at 3% of these sites.

[1] Outputs of five Earth System Models (ESMs) under historical and Representative Concentration Pathways (RCPs) scenarios from the Coupled Model Intercomparison Project phase 5 multimodel data set, as well as daily precipitation from 527 rain gauge stations in China for the period of 1960–2005 are used to investigate the spatiotemporal variations of precipitation extremes over China for 2071–2100. After the evaluation of the indices by the Mann-Whitney U test and the quantile-quantile plot, the weather generator model (WGEN) is used to downscale precipitation extremes. The average of precipitation extremes and values of the 5 and 20 year return periods under RCP26 and RCP85 scenarios are analyzed. Results showed the following: (1) WGEN works well in downscaling extreme heavy precipitation indices and consecutive dry days. (2) The risks of meteorological droughts and floods resulting from extreme long-duration precipitation would decrease in southwest China, but the risks of floods due to extreme heavy precipitation would increase. In north and southeast China, the risks of droughts would decrease, but floods might occur with higher frequencies; (3) The spatiotemporal variations of averages and values of 5 year return period extreme precipitation would be similar, but those of 20 year return period would be a little different: The 20 year consecutive dry days would decrease faster, and the 20 year values of other indices would increase relatively slower. (4) The spatial patterns of changes in precipitation extremes under RCP26 and RCP85 would be similar, but the changes in RCP85 would be intensifying.

[1] Daily and monthly maximum and minimum surface air temperatures at 66 weather stations over the eastern and central Tibetan Plateau with elevations above 2000 m were analyzed for temporal trends and spatial variation patterns during the period 1961 - 2003. Statistically significant warming trends were identified in various measures of the temperature regime, such as temperatures of extreme events and diurnal temperature range. The warming trends in winter nighttime temperatures were among the highest when compared with other regions. We also confirmed the asymmetric pattern of greater warming trends in minimum or nighttime temperatures as compared to the daytime temperatures. The warming in regional climate caused the number of frost days to decrease significantly and the number of warm days to increase. The length of the growing season increased by approximately 17 days during the 43-year study period. Most of the record-setting months for cold events were found in the earlier part of the study period, while that of the warm events occurred mostly in the later half, especially since the 1990s. The changes in the temperature regime in this region may have brought regional-specific impacts on the ecosystems. It was found that grain production in Qinghai Province, located in the area of prominent warming trends, exhibited strong correlations with the temperatures, although such relationships were obscured by the influence of precipitation in this arid/semiarid environment in juniper tree ring records. In western Sichuan Province under a more humid environment, the tree growth ( spruces) was more closely related to the changing temperatures.