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This paper quantifies the potential benefit of limiting the global warming to 1.5°C above the preindustrial level on the high‐latitude climate of the Southern Hemisphere compared to 2.0°C and above. A set of Coupled Model Intercomparison Project Phase 5 global climate model experiments is used in order to determine the mean projected changes in surface air temperature, sea level pressure, surface winds and sea ice distribution over and around Antarctica. Alongside, changes in selected variables related to extremes (such as the annual number of extremely cold mornings and extremely cold days) are also quantified as a function of the Representative Concentration Pathway (RCP) considered reaching the given warming threshold. Physical mechanisms for the projected variations in sea ice are proposed, including surface air temperature, changes in low‐level air temperature advection and meridional winds. Results show that there would be significant differences in the atmospheric and sea ice variable changes depending on the warming threshold and RCP considered, and that indeed keeping the global warming under 1.5°C could have a noticeable impact particularly on the distribution of sea ice over the Southern Ocean. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper studies how the anthropogenic-induced global warming affects the East Asian winter monsoon ( EAWM) by using 26 Coupled Model Intercomparison Project phase 5 ( CMIP5) models. The simulated present-day EAWM is evaluated and future projections under RCP4.5 and RCP8.5 scenarios are presented in terms of the climatology and interannual variability. All 26 models can well reproduce the spatial pattern of EAWM climatology and 16 out of the 26 models can reasonably capture major features of interannual variability. The projection made by 26-model ensemble mean indicate that winter surface air temperature averaged over 20°-60°N, 100°-140°E will increase by 3 °C in RCP4.5 and 5.5 °C in RCP8.5 towards the end of the 21st century. The corresponding regional mean precipitation will increase by 12.3% in RCP4.5 and 21.8% in RCP8.5. The strong warming over high-latitude North Pacific due to melting sea ice in the Bering Sea and Okhotsk Sea leads to significant intensification and a northward shift of the Aleutian Low, resulting in prominent increase in the low-level northerly along the coastal regions of northeastern Asia. At 500 hPa the characteristic East Asian Trough is projected to weaken slightly and tilt more eastward with latitude. The selected 16-model ensemble mean projects future enhanced interannual variability of surface air temperature and sea-level pressure over mid-latitude North Pacific and high-latitude East Asia ( EA) and reduced variability over eastern China, suggesting that the EAWM will be more variable in the high-latitude EA and mid-latitude North Pacific but less variable in East China. Accordingly, the year-to-year precipitation variability will be significantly enhanced over high-latitude EA. Majority of the 26 models project that the leading mode of EAWM interannual variation (the 'northern mode') will become more dominant in the warmer climate. [ABSTRACT FROM AUTHOR]

ABSTRACT The aim of this paper is to study the model's simulated frequency, track, intensity and location of cyclonic storms (CSs) and severe cyclonic storms (SCSs) in the Bay of Bengal (BoB), India. For the purpose, the PRECIS (Providing REgional Climates for Impacts Studies) a regional climate modelling system, of UK Met Office, is used. This model is integrated for the period 1961-1990 (baseline) and the future time period 2071-2100 (High emission scenario, A2). To run the model, the initial and lateral boundary conditions are supplied by UK Met Office. The analysis of frequency, track, intensity and location are carried out for May, June, September and October for the period 1961-1990 and 2071-2100. To evaluate the model's performance in simulating storms frequency during 1961-1990, chi square test is carried out with observed storms for the same period. The model's simulated frequency of storms is an overestimation of observations although the frequency of model's simulated storms during 2071-2100 is less than that of during 1961-1990. In general, model's simulated storms are found moving in the northwest direction from their initial location in all months during 1961-1990 and 2071-2100. In model's simulations, the drop in central pressure is relatively more in the months of May, June, September and October during 2071-2100 compared with that during 1961-1990. During 2071-2100, more intense storms may be possible in the months of May and June compared with that of September and October. It is observed that the model is able to simulate the initial locations of storms during 1961-1990 and 2071-2100 close to observations for the months of June and September, especially. [ABSTRACT FROM AUTHOR]

Global warming acts to prolong thermal summers and shorten winters. In this work, future changes in the lengths and timing of four thermal seasons in northern Europe, with threshold temperatures 0 and 10°C, are derived from bias‐adjusted output data from 23 CMIP5 global climate models. Three future periods and two Representative Concentration Pathway (RCP) scenarios are discussed. The focus is on the period 2040–2069 under RCP4.5, which approximately corresponds to a 2°C global warming relative to the preindustrial era. By the period 2040–2069, the average length of the thermal summer increases by nearly 30 days relative to 1971–2000, and the thermal winter shortens by 30–60 days. The timing of the thermal springs advances while autumns delay. Within the model ensemble, there is a high linear correlation between the modelled annual‐mean temperature increase and shifts in the thermal seasons. Thermal summers lengthen by about 10 days and winters shorten by 10–24 days per 1°C of local warming. In the mid‐21st century, about two‐thirds of all summers (winters) are projected to be very long (very short) according to the baseline‐period standards, with an anomaly greater than 20 days relative to the late‐20th century temporal mean. The proportion of years without a thermal winter increases remarkably in the Baltic countries and southern Scandinavian peninsula. Implications of the changing thermal seasons on nature and human society are discussed in a literature review. [ABSTRACT FROM AUTHOR]

The Red Sea trough (RST) is a low‐pressure trough extending from south towards the Levant. Unlike previous synoptic classifications covering all systems that affect the region, our algorithm focuses on the RST alone. It uses sea‐level pressure (SLP) and relative geostrophic vorticity for identifying the existence of an RST and classifying it to one of three types, according to the location of the trough axis with respect to 35°E longitude. The following conditions were imposed to assure the existence of an RST: (a) north to south SLP drop across the Levant, (b) average positive sea‐level relative vorticity over the region of interest, (c) existence of a distinct and continuous trough axis from the south towards the region of interest and (d) absence of any pronounced closed cyclone near the Levant. The algorithm was applied on the NCEP/NCAR reanalysis, 2.5° × 2.5° resolution and the ERA‐Interim, 2.5° × 2.5° and 0.75° × 0.75° resolutions. An evaluation of the algorithm against subjective identification, based on the NCEP reanalysis, showed an agreement of 93% for RST identification and 79% for correct classification. The use of fine resolution data may insert noise that reduce the identification rate of RSTs but improves the axis locating. The autumn is the main season of RST, with a maximum in November and a consistent decrease towards the July minimum. The annual frequency varies among the data sources between 17.6 and 24.6%. The trough axis is shown to have a diurnal oscillation; towards the eastern coast of the Mediterranean at nighttime and eastward, inland, at noontime. No consistent long‐term trend was found for the period 1979–2016, during which the global warming was persistent. This automated algorithm is flexible in the sense that it is not confined to any predetermined spatial resolution and is applicable to operational forecast model as well as to climate model outputs. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) plays an important role in modulating the location of tropical cyclone (TC) genesis over the western North Pacific (WNP). This study evaluated the simulation of the ENSO's impact on WNP TC genesis in 10 CMIP5 models based on a TC detection method, and projected its changes under global warming using the historical and the representative concentration pathway 8.5 (RCP8.5) simulations. The observed southeast–northwest shift role of ENSO in the WNP TC genesis location can be well reproduced in most of the models, although the strength of the ENSO's impact is underestimated as the underestimated climatological TC genesis frequency in these models. Moreover, we found the WNP TC during both El Niño and La Niña events shows an apparent eastwards shift under global warming. However, this eastwards shift of WNP TC genesis could be associated with the changes in climatological TC genesis but not the changes in the ENSO's impact. The projected changes in the ENSO's impact on WNP TC genesis is not as certain as we expected based on the previous conclusions of the robust changes in ENSO's impact on large‐scale environment. As a result, we suggest that both the TC genesis climatology and ENSO's impact on TC genesis simulated in the models need improvement in future to project the changes in ENSO's impact under global warming, and more models with 6‐hourly outputs used to detect TCs are needed to increase the confidence of multi‐model ensemble projections. [ABSTRACT FROM AUTHOR]

As the climate changes, increasing variations in environmental factors directly influence crop cultivation at different magnitudes over a broad range of local communities worldwide. As a result, there is an urgent need to develop local impact assessments and adaptation strategies for use at local, rather than national or global, levels. In this study, we predicted the future frost damage of kiwifruit in the Jeonnam province, Korea, as a case study for the local impact assessment of climate change. This study included a series of models that integrated both the biological responses of plants and the physical influences of climatic factors. First, potential changes in the suitable area for kiwifruit cultivation under a changing climate were simulated using downscaled high resolution (1 km) climate data. Through the development of a frost‐forecasting model and linking it to a kiwifruit phenology model, we also assessed the interaction of plant and climatic factors. Because of the warming climate, the last frost date in spring occurred 13.7 days earlier in average under climate change. Nevertheless, the potential risk of spring frost damage of kiwifruit continued to exist at a similar magnitude in the future. Additional study at the county level indicated that the date of bud burst is advancing even faster than the last frost date (approximately 1 day per every decade), resulting in the increasing risk of spring frost damage for kiwifruit through 2100. In this study, the local impacts of climate change on kiwifruit frost damage were assessed using the integrated modelling approach. As such, local policy makers and stakeholders will be able to prepare more realistic adaptation strategies to cope with upcoming threats in a changing climate. In this study, the local impacts of climate change on kiwifruit frost damage in the Jeonnam Province, Korea were assessed using an integrated modelling approach. First, optimal areas for kiwifruit cultivation under a changing climate were simulated, resulting in almost 98% of lands becoming "Highly suitable" in the 2080s. In addition, through the development of a frost‐forecasting model and linking it to a kiwifruit phenology model, we found that the potential risk of spring frost damage of kiwifruit continued to exist at a similar magnitude as shown in the figure below. [ABSTRACT FROM AUTHOR]

Inhomogeneities in climate data are the main source of uncertainty for secular warming estimates. To reduce the influence of inhomogeneities in station data statistical homogenization compares a candidate station to its neighbours to detect and correct artificial changes in the candidate. Many studies have quantified the performance of statistical break detection tests used in this comparison. Also, full homogenization methods have been studied numerically, but correction methods by themselves have not been studied much. We analyse the ANOVA (analysis of variance) joint correction method, which is expected to be the most accurate published method. We find that, if all breaks are known, this method produces unbiased trend estimates and that in this case the uncertainty in the trend estimates is not determined by the variance of the inhomogeneities, but by the variance of the weather and measurement noise. For low signal‐to‐noise ratios and high numbers of breaks, the correction may also worsen the data by increasing the original random unbiased trend error. Any uncertainty in the break dates leads to a systematic undercorrection of the trend errors and in this more realistic case the variance of the inhomogeneities is also important. Inhomogeneities in climate station data may produce spurious temperature trends. After the detection of the breaks the data have to be adjusted by a correction scheme. We analyse simulated data with known properties to assess their skill. The scatterplot compares the trend error before and after the adjustment. The original trend error is largely reduced, but not completely removed. [ABSTRACT FROM AUTHOR]

The "Warm‐Arctic/Cold‐continents" (WACC) winter weather pattern is investigated using the European Centre for Medium‐Range Weather Forecasts 20th Century reanalysis data (ERA20C) spanning 1901–2010. Both the 1920–1940 and 1990–2010 periods are characterized by Arctic amplification (AA) and mid‐latitude continental cooling, although the Arctic warming signal for 1990–2010 is twice as strong as that for 1920–1940. Significant weakening in the mid‐latitude polewards temperature gradient and zonal wind, wavier upper‐level flow character, and strong regional blocking frequency/intensity changes are also detected during both AA periods. These results based on statistical analyses highlight the possible role of AA in affecting mid‐latitude weather patterns, but further work is needed to quantify the influence of AA on particular mid‐latitude dynamical features. "Warm‐Arctic/Cold‐continents" (WACC) winter weather pattern is clearly shown in both 1920–1940 and 1990–2010 periods. Significant weakening in mid‐latitude polewards temperature gradient and zonal wind, wavier upper‐level flow character, and strong regional blocking frequency/intensity changes are detected during both periods. Noticeable regional differences of trends in these dynamical features between AA1 and AA2 period suggest the need for a more in‐depth dynamical meteorological investigation of regional mechanisms of AA and mid‐latitude weather linkages. [ABSTRACT FROM AUTHOR]

Extreme precipitation and associated flooding cause severe damage to society and the environment. Future climate projections suggest an intensification of precipitation extremes in many regions. However, there is an increasing need for climate change impact assessment at higher spatial resolution, particularly for regions with complex geography such as Southeast Asia (SEA). In this study, we analysed the NASA Earth Exchange 0.25° resolution daily precipitation projections from an ensemble of 20 climate models under two emission scenarios RCP4.5 and RCP8.5. The variability in future precipitation projections is analysed and quantified for six geographical subregions, two climatological regions (wet and dry), and the low‐elevation coastal zones in SEA. Various aspects of precipitation structure are studied using indices that characterize precipitation amount, number of heavy precipitation days, extreme precipitation amount, and maximum daily precipitation at annual and seasonal scales. The results show substantial increases in mean and extreme precipitation in many parts of SEA by the end of the 21st century under both emission scenarios, thus increasing the region's vulnerability to precipitation‐driven hazards. The projected centennial increase in total annual precipitation relative to the baseline period of 1970–1999 when averaged over all land grid cells is about 15% under RCP8.5 scenario, with larger values (∼20%) over mainland SEA and Philippines and smaller values (∼6%) in Java island. The projected changes in extreme precipitation are stronger compared to the total annual precipitation under both emission scenarios. The New Guinea and Java regions show the largest and smallest increases in annual maximum daily precipitation, with ensemble mean values of 30 and 17%, respectively, under RCP8.5 scenario. The results also reveal large inter‐model spread in projected changes, particularly during boreal winter and summer months. The study assessed changes in different precipitation characteristics such as the annual maximum daily rainfall (shown here) over nine regional masks in Southeast Asia for the time period 2070–2099 relative to the baseline period of 1970–1999. Results indicate substantial changes in total precipitation and extreme precipitation, particularly for the RCP8.5 scenario. The regional and seasonal variability in future changes and associated uncertainties are described in detail in this study. [ABSTRACT FROM AUTHOR]

Simulations and future projections of year‐to‐year variation in global monsoon precipitation (GMP), defined as the summer precipitation amount per unit area within the global monsoon domain, are investigated using the 33 models that participated in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). The inter‐annual standard deviation of GMP, which presents the amplitude of year‐to‐year variability in monsoon rainfall, is simulated well by the multi‐model ensemble (MME) mean of the 33 models and of the best five (B5) models. The B5 models show superior skills in reproducing the climatological monsoon precipitation and its inter‐annual variability. The inter‐annual standard deviations of 25‐year GMP in the present day (1979–2005) derived from the MME average of the 33 models and of the B5 models are 0.17 and 0.15 mm/day per unit area, respectively, both being close to the observation (0.16 mm/day per unit area). Consistent with the observed El Niño–Southern Oscillation (ENSO)–GMP relationship, the simulated variability of GMP is negatively correlated with the sea surface temperature in the Niño areas at the inter‐annual timescale. Projections by the 33 CMIP5 models under the RCP4.5 scenario indicate that wet and dry monsoon years would occur more intensively in a warmer climate. Around 61% (20 out of the 33) of the models show enhanced inter‐annual variability of GMP by the end of the 21st century (2072–2098) compared to the period 1979–2005. The MME of the B5 models suggests that the amplitude of projected GMP variability would increase by ~20% from present day to the late 21st century. However, the increasing rate of GMP variability detected by the 33 models' MME is relatively small (~6%), which is even smaller than the inter‐model standard deviation, suggesting the amplitude changes in GMP variability feature non‐negligible uncertainty among the 33 models. Under global warming, the inter‐annual variation of GMP would still be tightly connected with ENSO, although the projected amplitude changes in ENSO variability are noticeably diverse across the 33 CMIP5 models. The enhanced amplitude of inter‐annual GMP variability may be attributable to the increase in mean‐state moisture associated with global warming. The dynamic effect related to changes in the variability of monsoon circulation is small and less robust among the 33 CMIP5 models. Taking advantage of the large number of members in phase 5 of the Coupled Model Intercomparison Project (CMIP5), we identified robust changes in monsoon rainfall variability at the inter‐annual timescale under global warming. Around 61% (20 out of 33) of the models show enhanced inter‐annual variability of GMP by the end of the 21st century (2072–2098) compared to the period 1979–2005. ENSO is still the major driving force behind the inter‐annual variability of global monsoon precipitation under global warming, although the amplitude changes in ENSO variability are remarkably diverse in future projections. From the moisture budget perspective, the enhanced amplitude of inter‐annual GMP variability may be attributable to the increase in mean‐state moisture associated with global warming. Figure shows (a) differences in the inter‐annual variability (defined as the inter‐annual standard deviation) of GMP (red), NHMP (blue) and SHMP (green) between the historical run (1979–2005) and RCP4.5 (2072–2098) in the CMIP5 models. The rightmost bars are the results derived from the average of CMAP and GPCP precipitation (unit: mm/day per unit area). (b) TCCs between the GMP and 2‐m air temperature anomalies (shading), and between the GMP and 850‐hPa wind anomalies (vectors), during the period 2072–2098. White dots mark the regions with correlation coefficients at the 95% confidence level. (c) Relative contributions of mean‐state specific humidity and the variability of vertical motion to the enhanced variability of GMP under GW (unit: 10−5 kg m−1 s−3). [ABSTRACT FROM AUTHOR]

ABSTRACT: We use the Global Historical Climatology Network – daily database to calculate a nonparametric statistic that describes the rate at which all‐time daily high‐ and low‐temperature records have been set in nine geographic regions (continents or major portions of continents) during periods mostly from the mid‐20th century to the present. This statistic was defined in our earlier work on temperature records in the 48 contiguous United States. In contrast to this earlier work, we find that in every region except North America all‐time high records were set at a rate significantly (at least 3σ) higher than in the null hypothesis of a stationary climate. Except in Antarctica, all‐time low records were set at a rate significantly lower than in the null hypothesis. In Europe, North Africa and North Asia the rate of setting new all‐time highs increased suddenly in the 1990s, suggesting a change in regional climate regime; in most other regions there was a steadier increase. [ABSTRACT FROM AUTHOR]

ABSTRACT This study analysed the time series of tropical cyclone ( TC) frequency during October-December ( OND) for 32 years (1980-2011). There was a strong decreasing trend of TCs until recently, and the TC sharply decreased from 1996 after the statistical change-point analysis was applied to this time series. To investigate the cause of such recent decrease in TC genesis frequency, the differences ( TC activity and its relation to large-scale environments, and others) between the mean of the period from 1996 to 2011 and the mean of the period from 1980 to 1995 were analysed. TCs during the period 1996-2011 mainly occurred in the western region of tropical western North Pacific ( TWNP), whereas during the 1980-1995 period they mainly occurred in the eastern region of TWNP. In the analysis of differences periods in the 850 hPa and 500 hPa stream flows between the two periods, an anomalous huge anticyclone existed from the north Pacific to the TWNP, and an anomalous huge cyclone existed to the west of 125°E including the East Asian continent. In other words, this is a typical low-west-high-east pressure system that appears in East Asia during summer, and this anomalous pressure system pattern caused the low TC genesis frequency during the 1996-2011 period. The low-west-high-east anomalous pressure system pattern which has been strengthened recently in East Asia suggests that the East Asian winter monsoon ( EAWM) has weakened during the 1996-2011 period. As a result, the amount of snow depth decreased in many areas of the East Asian continent except for the North China and the ground heat net flux also increased in many areas. This weakening of the EAWM strengthened the anomalous huge anticyclone in the TWNP as well as in the central North Pacific, which caused the low TC genesis frequency during the OND in recent years. [ABSTRACT FROM AUTHOR]

ABSTRACT The village Haparanda in northern Sweden hosts one of the longest meteorological station records in Europe depicting climate conditions in the subarctic. Since the station was relocated several times, moving gradually from urbanized to more rural areas, the record is likely biased by anthropogenic influences. We here assess these influences and demonstrate that even in villages urban heat island biases might affect the temperature readings. We detail a method to quantify this bias and remove it from the long Haparanda station record running since 1859. The correction is based on parallel temperature measurements at previous station locations in Haparanda. These measurements revealed a distinct urban warming pattern, largest in minimum temperatures during summer, since urban geometry and its heat capacity amplify additional warming and night-time heat release, especially during a period of high insolation and calm conditions. Due to the station movement from the village centre to the outskirts, the net correction results in an additional warming trend over the past 155 years. The trend increase is most substantial for minimum temperatures (+0.03 °C 10 years−1). Maximum and mean temperatures are less affected (+0.01 °C 10 years−1). An increase in trend is even more severe if the 20th century is regarded exclusively, displaying a rise in annual mean temperature trend by +0.03 °C 10 years−1 and +0.07 °C 10 years−1 in annual minimum temperatures, respectively. Our approach of using actual temperature differences between historical station locations did not take into account other factors that might have influenced the data such as changes in instruments or observers. The presented adjustment for temperature residuals caused by a change in historical station locations might be considered as a minimum approach to improve long-term temperature readings. The adjustment of the Haparanda station record results in an increased warming trend, thereby adding critical information to the evaluation and explanation of 20th century anthropogenic warming. [ABSTRACT FROM AUTHOR]

The Chajnantor plateau is located in the Atacama Desert at over 4800m above sea level. The plateau features a large fraction of days during the year where dry and stable atmospheric conditions predominate. The suitability of the type of astronomy observations routinely made at sites across the Chajnantor region at different times of the year depends on the variability of atmospheric water vapour. In this work, we study seasonal and intraseasonal variability associated with periods of large and low precipitable water vapour (PWV) in the Chajnantor region over 32 years. We establish large-scale conditions favourable for above- and below-normal PWV for each of the four seasons. We also explore whether intraseasonal PWV variations are related to the Madden-Julian Oscillation (MJO). Below-normal PWV in winter, spring, and autumn seasons was found associated with mostly zonal 500-hPa winds, which advect drier than normal air from the anticyclone over the eastern portions of the southeast (SE) Pacific Ocean. In summer, periods with below-normal PWV were found to have anomalously south-westerly winds at mid-levels, also indicating transport of anomalously dry air from the stable SE Pacific. In winter, spring, and autumn seasons, above-normal PWV was generally associated with north-westerly mid-tropospheric wind anomalies, indicating advection of above-normal PWV from the subtropical and tropical regions of the SE Pacific Ocean. Above-normal PWV conditions in summer were associated with nearly calm winds at 500 hPa. Months and phases of the MJO for the most extreme anomalies of PWV for each season agreed well with the seasonal anomalies. Furthermore, three independent reanalysis data sets generally agreed on MJO phases associated with largest positive and negative PWV anomalies. This agreement provides evidence for the first time that the MJO modulates the PWV content over the Atacama Desert. [ABSTRACT FROM AUTHOR]

Simulations of the regional climate model REMO at 25 and 50 km (0.44° and 0.22°, respectively) grid spacing are evaluated over Central Africa for the period 1998-2010. The model's ability to simulate various aspects of the observed climate is assessed with a main focus on precipitation characteristics. The results show that the REMO model has a good skill to reproduce the main regional features of the mean climate fields as well as seasonal and annual cycles, although some biases still exist. The model captures the variability in precipitation anomalies between different events associated with El Niño/Southern Oscillation. Generally, the findings remain largely insensitive to the refinement of the horizontal resolution, especially when considering the regional scale. This points the fact that the model dynamical and physical setup may have to be adjusted when setting a focus on the Central African region, in order to better represent the climate mechanisms. It is further found that REMO is capable of capturing the basic features of climatic extremes and accurately represents the shape of the frequency distribution of daily precipitation data. Daily characteristics of precipitation are simulated much better by REMO at 25 km. [ABSTRACT FROM AUTHOR]

This study investigates the El Niño-Southern Oscillation (ENSO)-related seasonal variations in precipitation extremes based on the observed daily precipitation dataset of 23 meteorological stations in Malaysia, spanning a period of 46 years from 1966 to 2011. The extreme indices were a subset of the Expert Team for Climate Change Detection and Indices (ETCCDI) that covers the duration, frequency and intensity aspects of precipitation extremes. Seasonal composites of 'El Niño minus neutral' and 'La Niña minus neutral' years of these indices were computed based on El Niño and La Niña occurrences during the period. The results showed that the ENSO-related variations in precipitation extremes were generally coherent with the variations in total precipitation. Generally, dry (wet) precipitation extremes tended to enhance during El Niño (La Niña); however, this was dependent on season and location. The El Niño and La Niña influences on precipitation extremes were not entirely linear. While the impacts of El Niño and La Niña were generally opposite for most locations and seasons, there were cases where both exerted in-phase influences. The impacts were also dependent on the intensity of the event itself. While the El Niño impacts were generally coherent across different intensities, La Niña can have entirely different impacts among different categories. During December–January–February (DJF), strong (moderate) La Niña caused a significant decrease (increase) in wet precipitation extremes over the Peninsular Malaysia. This was related to the broadening (narrowing and westward displacement) of the anomalous cyclonic circulation over the western north Pacific during strong (moderate) La Niña. Hence, the likelihood for widespread flooding over the east coast of the Peninsular Malaysia during DJF increases during moderate but not during strong La Niña events. [ABSTRACT FROM AUTHOR]

The purpose of this study is to assess the ability of Coupled Model Intercomparison Project 5 (CMIP5) models in reproducing the variability and change of the austral summer precipitation observed in Southeastern South America (SESA) along the 20th century and beginning of the 21st. Models show a reduction in mean precipitation biases and inter-model dispersion, and a significant improvement in the representation of the leading pattern of precipitation interannual variability (EOF1), in comparison with Coupled Model Intercomparison Project 3 (CMIP3) models. Changes of the EOF1 activity in the present climate, as represented by both, climate model simulations and rainfall gridded datasets, evidence an increase of the frequency of EOF1 positive events (associated with positive precipitation anomalies in SESA and negative ones in the South Atlantic Convergence Zone) and a decrease of the frequency of EOF1 negative events. Nevertheless there are still large uncertainties due to model differences and the internal variability of the climate system. In order to reduce the impact of model uncertainties, an ensemble of the climate simulations that represent better the features associated with EOF1 activity was built, regardless to which model they correspond. The results obtained with this ensemble confirm that largest precipitation trends in SESA are those represented by climate simulations associated with an increase (decrease) of EOF1 positives (negative) events. It was also found that positive precipitation trends in SESA resulted from climate simulations forced by anthropogenic sources are the largest and significantly different from those from simulations forced by natural sources only, which are not significantly different from zero. [ABSTRACT FROM AUTHOR]

ABSTRACT This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program ( GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value ( GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio ( AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions. [ABSTRACT FROM AUTHOR]

ABSTRACT The science that humans are the cause of global warming, and that the associated climate change would lead to serious changes in climate extreme events, food production, freshwater resources, biodiversity, human mortality, etc. is unequivocal. After several political negotiations, a 2 °C warming has been considered to be the benchmark for such damaging changes. However, an increasing amount of scientific research indicates that higher levels of warming are increasingly likely. What would the world be like if such higher levels of warming occurred? This study aims to provide information for better politically driven mitigation through an investigation of the changes in temperature- and precipitation-based extreme indices using CMIP5 (coupled model intercomparison project phase 5) simulations of a warming of 1, 2, and 3 °C in China. Warming simulations show more dramatic effects in China compared with the global average. In general, the results show relatively small change signals in climate extreme events in China at 1 °C, larger anomalies at 2 °C, and stronger and more extended anomalies at 3 °C. Changes in the studied temperature indices indicate that warm events would be more frequent and stronger in the future, and that cold events would be reduced and weakened. For changes in the precipitation indices, extreme precipitation generally increases faster than total wet-day precipitation, and China will experience more intensified extreme precipitation events. Furthermore, the risk of flooding is projected to increase, and the dry conditions over northern China are projected to be mitigated. In certain regions, particularly Southwest China, the risks of both drought and flood events would likely increase despite the decreased total precipitation in the future. Uncertainties mainly derived from inter-model and scenario variabilities are attached to these projections, but a high model agreement can be generally observed in the likelihood of these extreme changes. [ABSTRACT FROM AUTHOR]

ABSTRACT The purpose of this article is to describe the effect of cloudiness on long-term changes in air temperature. The article attempts to assess the role of clouds in contemporary climate change. The article is based on archived air temperature and cloudiness data obtained from the Jagiellonian University in Krakow. The analyses include mean daily air temperature and cloud cover data for years 1863-2010 and noontime cloud genus observations for years 1906-2010. It was concluded that the increase in air temperature in Krakow is more strongly associated with changes in the structure of cloudiness than changes in the amount of cloudiness. The relationship between these two types of changes is more apparent during the second half of the 20th century, in an era of accelerating climate warming. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT The Chinese Himalayas ( CH) is highly sensitive to global climate change. The analyses of monthly mean air temperature and monthly precipitation data during the 1971-2007 from 24 meteorological stations show a significant increase of 0.31 °C per decade or about 1.15 °C for annual mean air temperature over the entire region. The temperature rise occurs primarily during the period of 1991-2007, up to 0.73 °C per decade. Climate warming is characterized by all-year temperature increase in particular during winters with the maximum value of 0.38 °C per decade during the 1971-2007, up to 1.24 °C per decade during 1991-2007. Distributions of annual temperature trends show significant south-to-north, low-to-high and east-to-west warming trends to increase with the latitude and elevation while to decrease with the longitude in the CH, respectively. Annual precipitation increases, but not significantly during the 1971-2007. Seasonal precipitation has no significant trend during the same period, either. Spatial discrepancy of the variations in precipitation is particularly great. It is evident that the climate was significantly warming and drying in the western CH over the past 37 years. [ABSTRACT FROM AUTHOR]

ABSTRACT We intercompare three gridded observed daily rainfall datasets over Africa (FEWS (Famine Early Warning System), GPCP (Global Precipitation Climatology Project) and TRMM (Tropical Rainfall Measuring Mission)) in order to assess uncertainties in observation products towards the evaluation of the performance of a Regional Climate Model (RegCM3) in simulating daily precipitation characteristics over a domain encompassing the whole African continent. We find that different observation products exhibit substantial systematic differences in mean rainfall, but especially in higher order daily precipitation statistics, such as frequency of wet days, precipitation intensity and extremes as well as maximum length of wet and dry spells. For example, FEWS shows mostly higher frequency and lower intensity events than TRMM and GPCP. Thus, the different datasets provide quite different representations of daily precipitation behavior. As a result, although RegCM3 captures pretty well the monsoon rainband evolution and exhibits a representation of daily precipitation statistics within the range of the observations, it performs differently with respect to the various products. For instance, it simulates more intense but less frequent events over East and Southern Africa than in FEWS and vice versa compared to TRMM. We thus highlight the uncertainty in observations as a key factor preventing a rigorous and unambiguous evaluation of climate models over Africa. Improving the quality and consistency of observation products is thus paramount for a better understanding of the response of African climate to global warming. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article offers information on the impacts of persistent atmospheric circulation for the occurrence and severity of temperature extremes in Europe. Using the Hess-Brezowsky catalogue of circulation type and temperature data, the connection between atmospheric circulation and surface air temperature anomalies is studied. The experiment shows that the persistence of circulation patterns is related to surface air temperature anomalies. The severity of temperature extremes and occurrence became more evident under the condition of more persistent circulation. It is inferred that the worsening and frequency of heat waves in Europe is related to enhanced atmospheric circulation. The abnormalities in atmosphere is associated on the worsening climate change.