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Summer precipitation anomalies over eastern China are characterized spatially by meridionally banded structures fluctuating on interannual and interdecadal timescales, leading to regional droughts and floods. In addition to long-term trends, how these patterns may change under global warming has important implications for agricultural planning and water resources over this densely populated area. Using the latest Hadley Centre climate model, HadGEM3-GC2, this paper investigates the potential response of summer precipitation patterns over this region, by comparing the leading modes between a 4×CO2 simulation and the model’s pre-industrial control simulation. Empirical Orthogonal Function (EOF) analyses show that the first two leading modes account for about 20% of summer rainfall variability. EOF1 is a monopole mode associated with the developing phase of ENSO events and EOF2 is a dipole mode associated with the decaying phase of ENSO. Under 4×CO2 forcing, the dipole mode with a south-north orientation becomes dominant because of a strengthened influence from excessive warming of the Indian Ocean. On interdecadal time scales, the first EOF looks very different from the control simulation, showing a dipole mode of east-west contrast with enhanced influence from high latitudes. [ABSTRACT FROM AUTHOR]

In mountain regions, important differences in the time trends of climate series can be detected even within relatively small areas, leading to uncertainty when assessing climate change. The paper deals with a structured algorithm for high-resolution downscaling of climate characterisation in a region (precipitation and temperature), leading to a twofold application: increasing spatial resolution of past climate definition for the area and attaining high-resolution downscaling for climate projections. In the first stage, multi-variate analysis ('partial least squares' regression) was applied to a number of time series (10) in order to obtain climate averages for a larger number of sites. Predictions made with single-site values (such as seasonal means) can in some cases be improved by applying 'random perturbation' of the value and averaging single predictions in the ensemble. This analysis laid the foundation for implementing the same technique to the output of statistical downscaling of multi-model climate projections. Climate shift in the study area (Trentino), located in the north-eastern Italian Alps, was simulated for two 30-year time windows: 2021-2050 and 2071-2099. Progressive warming is predicted, being stronger in the summer, along with a mixed, seasonally differentiated trend for precipitation. [ABSTRACT FROM AUTHOR]

The hydrological cycle is expected to intensify with global warming, which likely increases the intensity of extreme precipitation events and the risk of flooding. The changes, however, often differ from the theorized expectation of increases in water‐holding capacity of the atmosphere in the warmer conditions, especially when water availability is limited. Here, the relationships of changes in extreme precipitation and flood intensities for the end of the twenty-first century with spatial and seasonal water availability are quantified. Results show an intensification of extreme precipitation and flood events over all climate regions which increases as water availability increases from wet to dry regions. Similarly, there is an increase in the intensification of extreme precipitation and flood with the seasonal cycle of water availability. The connection between extreme precipitation and flood intensity changes and spatial and seasonal water availability becomes stronger as events become less extreme. [ABSTRACT FROM AUTHOR]

Global warming has substantial impacts on the hydrologic cycle and precipitation characteristics. This study aimed to explore variability in the form of precipitation by analysis of trends in the snowfall-day (SD)/total precipitation-day (PD) ratio across Iran. To this end, the PD and SD records were acquired from 33 synoptic stations during 1965–2014. The Mann-Kendall (MK) test was the main method used for trend detection. Analyzing data exposed that the annual SD/PD ratio was less than 25% in a plethora of the stations. The MK test findings indicated downward tendencies in the SD/PD ratio over most regions of the country; although in many cases, the observed trends were not statistically significant. The changes in the annual SD/PD ratio were estimated down to − 2% per decade over ~ 70% of Iran's total area. Further studies are required to ascertain the linkages between the large-scale climate oscillations and the form of precipitation across this region. Also, using remotely sensed data (e.g., obtained from the MODIS) and fine-resolution gridded data (e.g., global and regional reanalysis data) in future research could improve the findings of such studies and dwindle the uncertainties caused by the scanty site-based observations. [ABSTRACT FROM AUTHOR]

As the recent global warming hiatus and the warming on high elevations are attracting worldwide attention, this study examined the robustness of the warming slowdown over the Tibetan plateau (TP) and its related driving forces. By integrating multiple-source data from 1982 to 2015 and using trend analysis, we found that the mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) showed a slowdown of the warming trend around 1998, during the period of the global warming hiatus. This was found over both the growing season (GS) and non-growing season (NGS) and suggested a robust warming hiatus over the TP. Due to the differences in trends of Tmax and Tmin, the trend of diurnal temperature range (DTR) also shifted after 1998, especially during the GS temperature. The warming rate was spatially heterogeneous. The northern TP (NTP) experienced more warming than the southern TP (STP) in all seasons from 1982 to 1998, while the pattern was reversed in the period from 1998 to 2015. Water vapour was found to be the main driving force for the trend in Tmean and Tmin by influencing downward long wave radiation. Sunshine duration was the main driving force behind the trend in Tmax and DTR through a change in downward shortwave radiation that altered the energy source of daytime temperature. Water vapour was the major driving force for temperature change over the NTP, while over the STP, sunshine duration dominated the temperature trend. [ABSTRACT FROM AUTHOR]

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4◦C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4◦C global warming will occur is 2084. Based on the median results of models that project a 4◦C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5◦C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation. [ABSTRACT FROM AUTHOR]

A two-step statistical downscaling method has been reviewed and adapted to simulate twenty-first-century climate projections for the Gulf of Fonseca (Central America, Pacific Coast) using Coupled Model Intercomparison Project (CMIP5) climate models. The downscaling methodology is adjusted after looking for good predictor fields for this area (where the geostrophic approximation fails and the real wind fields are the most applicable). The method’s performance for daily precipitation and maximum and minimum temperature is analysed and revealed suitable results for all variables. For instance, the method is able to simulate the characteristic cycle of the wet season for this area, which includes a mid-summer drought between two peaks. Future projections show a gradual temperature increase throughout the twenty-first century and a change in the features of the wet season (the first peak and mid-summer rainfall being reduced relative to the second peak, earlier onset of the wet season and a broader second peak). [ABSTRACT FROM AUTHOR]

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960-2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960- 1986 and 1987-2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4- year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices.Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970-1980 and after 1992. [ABSTRACT FROM AUTHOR]

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Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (R) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing R in spring (May-June) and autumn (September) and decreasing R in summer (July-August). Growing season R for alpine steppe increased slightly, mainly due to increasing R in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (R) for alpine meadow increased slightly, mainly in spring and summer, and R for alpine steppe increased, mainly in spring. Moreover, R for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. R for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity of Tibetan Plateau grassland. [ABSTRACT FROM AUTHOR]

The assessment of climate change impacts requires updated estimates of the tendencies in temperature extremes. With the objective of studying recent variations in frequency and intensity of temperature extremes over Italy, a collection of daily minimum and maximum temperature time series was selected for the calculation of a set of indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The trend of each index was investigated through a non-parametric statistical analysis over the last half-century (1961-2011), and its spatial variability was illustrated through trend maps. Mean national-scale trends were also assessed at annual and seasonal level. The results show that mean annual series exhibit a general warming tendency from 1961 to 2011, with significant trends for summer days, tropical nights, heat waves, and percentile-based indices at most stations, with warming trends more pronounced in summer and spring and weaker in winter and autumn. As a changepoint was identified in 1977 for the minimum ( T) and maximum temperature ( T) Italian annual series, the trend analysis was also performed for the two sub-periods 1961-1977 and 1978-2011. Non-significant 'cooling' trends characterize the sub-period 1961-1977, while significant 'warming' trends were identified over the period 1978-2011. This study updates previous research in the extent of time series, in the number of indices and in the approach followed for their analysis, providing useful information for evaluating the impacts of temperature extremes in the context of a changing climate in Italy. [ABSTRACT FROM AUTHOR]

In this work, we analyze climate variability and glacier evolution for a study area in the Northwestern Italian Alps from the Little Ice Age (LIA) to the 2010s. In this area, glacier retreat has been almost continuous since the end of the LIA, and many glaciers are now extinct. We compared glaciological and climatic data in order to evaluate the sensitivity of glaciers to temperature and precipitation trends. We found that temperatures show significant warming trends, while precipitation shows no clear signal. After the 1980s, the total number of positive trends in temperature increased, particularly minimum temperature. The latter does not seem to be the only cause of glacier shrinkage but rather on acceleration of an ongoing trend documented since the end of the LIA. In some rare cases, the effects of warming trends on glacier dynamics have been accentuated by a concomitant decrease in precipitation. We hope that this study will contribute to increase the knowledge of the relationships between climate variation and glacier evolution in the Greater Alpine Region. [ABSTRACT FROM AUTHOR]

According to the Intergovernmental Panel on Climate Change report released in September 2014, unprecedented changes in temperature and precipitation patterns have been recorded globally in recent decades and further change is predicted to occur in the near future, mainly as the result of human activity. In particular, projections show that the Mediterranean climate zone will be markedly affected with significant implications for lake water levels and salinity. This may be exacerbated by increased demands for irrigation water. Based on long-term data from seven lakes and reservoirs covering a geographical gradient of 52° of latitudes and a literature review, we discuss how changes in water level and salinity related to climate change and water abstraction affect the ecosystem structure, function, biodiversity and ecological state of lakes and reservoirs. We discuss mitigation measures to counteract the negative effects on ecological status that are likely to result from changes in climate and water abstraction practices. Finally, we highlight research required to improve knowledge of the impacts of anthropogenically induced changes on lake water level and consequent changes in salinity. [ABSTRACT FROM AUTHOR]

The intensity of the heaviest extreme precipitation events is known to increase with global warming. How often such events occur in a warmer world is however less well established, and the combined effect of changes in frequency and intensity on the total amount of rain falling as extreme precipitation is much less explored, in spite of potentially large societal impacts. Here, we employ observations and climate model simulations to document strong increases in the frequencies of extreme precipitation events occurring on decadal timescales. Based on observations we find that the total precipitation from these intense events almost doubles per degree of warming, mainly due to changes in frequency, while the intensity changes are relatively weak, in accordance to previous studies. This shift towards stronger total precipitation from extreme events is seen in observations and climate models, and increases with the strength – and hence the rareness – of the event. Based on these results, we project that if historical trends continue, the most intense precipitation events observed today are likely to almost double in occurrence for each degree of further global warming. Changes to extreme precipitation of this magnitude are dramatically stronger than the more widely communicated changes to global mean precipitation. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the statistical properties of precipitation. There are two related but consequentially distinct theories for changes to precipitation that have received some consensus: (1) the time-and-space integrated global total precipitation should increase with longwave cooling as the surface warms, (2) the most intense precipitation rates should increase at a faster rate related to the increase in vapor saturation. Herein, these two expectations are combined with an analytic integration of three conceptually independent properties of the tropical hydrological cycle, the intensity, probability, and frequency of precipitation. The total precipitation in both a cloud-resolving model and tropical Global Precipitation Measurement mission data is decomposed and reconstructed with the analytic integral. By applying (1) and (2) to the precipitation characteristics from the model and observations to form a warming proxy model, it is suggested that a wide range of future distributions of precipitation intensity, probability, and frequency are possible. Climate change: A simpler model for predicting precipitation change Models predict climate change will alter precipitation patterns across Earth, but the full range of possible changes is unknown. Matthew Igel and Joseph Biello at the University of California Davis created a new simple method that incorporated intensity, probability, and frequency to determine all potential responses of precipitation to climate change. Assuming a global warming of 2 °C and a tropical climate, the authors found that many future deviations in precipitation patterns are possible, even including little change to precipitation probability. The intensity of weak rates of rain could increase significantly with climate warming. Incorporating climates from other regions, such as ocean basins, could lead to larger scale application of this model. Future studies can use this method to determine which physical mechanisms need further study, increasing the accuracy of future precipitation simulations. [ABSTRACT FROM AUTHOR]

Based on temperature data from 79 meteorological stations, we estimate the warming rate by season on the Tibetan Plateau (TP) during 1984-2013. The warming rate was spatially heterogeneous across seasons over the past 30 years. The northern TP (NTP) experienced more warming than the southern TP (STP) (divided near 33°N) in all seasons. The greatest north-south difference in warming was 0.70 ± 0.11 °C for summer (June-August), while the smallest difference was 0.27 ± 0.14 °C for the cold season (November-April). Such seasonal and spatial heterogeneity in the warming rate is consistent with the seasonal precipitation patterns of the NTP and the STP. One possible cause for this phenomenon is that more precipitation occurs in the STP than in the NTP (especially for summer), accompanied by more low cloud cover, which may have slowed the warming rate. Our results imply that dry regions on the TP will possibly experience greater temperature increase than wet regions under future global warming, and this will be more prominent in summer. [ABSTRACT FROM AUTHOR]