Changing Seasonal Rainfall Distribution With Climate Directs Contrasting Impacts at Evapotranspiration and Water Yield in the Western Mediterranean Region

Over the past century, climate change has been reflected in altered precipitation regimes worldwide. Because evapotranspiration is sensitive to both water availability and atmospheric demand for water vapor, it is essential to assess the likely consequences of future changes of these climate variables to evapotranspiration and, thus, runoff. We propose a simplified approach for annual evapotranspiration predictions, based on seasonal evapotranspiration estimates, accounting for the strong seasonality of meteorological conditions typical of Mediterranean climate, still holding the steady state assumption of basin water balance at mean annual scale. Sardinian runoff decreased over the 1975-2010 period by more than 40% compared to the preceding 1922-1974 period. Most of annual runoff in Sardinian basins is produced by winter precipitation, a wet season with relatively high evaporation rates. We derived linear seasonal evapotranspiration responses to seasonal precipitation, and, in turn, a relationship between the parameters of the linear functions and the seasonal vapor pressure deficit (D), accounting for residuals with basin properties. We then used these relationships to predict evapotranspiration and runoff using future Intergovernmental Panel on Climate Change climate scenarios, considering changing precipitation and D seasonality. We show that evapotranspiration is insensitive to D scenario changes. Although both evapotranspiration and runoff are sensitive to precipitation seasonality, future changes in runoff are related only to changes of winter precipitation, while evapotranspiration changes are related to those of spring and summer precipitation. Future scenario predicting further runoff decline is particularly alarming for the Sardinian water resources system, requiring new strategies and designs in water resources planning and management.Peer reviewe

A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia

This article provides high-resolution information on the projected changes in annual extreme rainfall and high and low streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971&ndash;2050. Eleven rainfall indices were calculated along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981&ndash;2010 and the near-future period 2021&ndash;2050 were considered for this analysis. Results indicate that over Indochina, Myanmar faces more challenges in the near future. The east coast of Myanmar will experience more extreme high rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from the increase in dry spell length of up to 40 %, while the increase of extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low flow event than in a high flow event. The majority of rivers in the central Mekong catchment, Sumatra, the Malaysian peninsula, Borneo, and Java will experience more extreme low flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low flow occurrences, which reaches 101 % and 122 % on average over Sumatra and Java, respectively. Finally, the changes in extreme high and low streamflow events are more pronounced in rivers with steep hydrographs, while rivers with shallow hydrographs have a higher risk in the probability of low flow change. Our study highlights the importance of catchment properties in aggregating and/or buffering the impact of extreme climate change.</p

Building long homogeneous temperature series across Europe: a new approach for the blending of neighboring series

Long and homogeneous series are a necessary requirement for reliable climate analysis. Relocation of measuring equipment from one station to another, such as from the city center to a rural area or a nearby airport, is one of the causes of discontinuities in these long series which may affect trend estimates. In this paper an updated procedure for the composition of long series, by combining data from nearby stations, is introduced. It couples an evolution of the blending procedure already implemented within the European Climate Assessment and Dataset (which combines data from stations no more than 12.5 km apart from each other) with a duplicate removal, alongside the quantile matching homogenization procedure. The ECA&D contains approximately 3000 homogenized series for each temperature variable prior to the blending procedure, around 820 of these are longer than 60 years; the process of blending increases the number of long series to more than 900. Three case studies illustrate the effects of the homogenization on single blended series, showing the effectiveness of separate adjustments on extreme and mean values (Geneva), on cases where blending is complex (Rheinstetten) and on series which are completed by adding relevant portions of GTS synoptic data (Siauliai). Finally, a trend assessment on the whole European continent reveals the removal of negative and very large trends, demonstrating a stronger spatial consistency. The new blended and homogenized data-set will allow a more reliable use of temperature series for indices calculation and for the calculation of gridded data-sets, and will be available for users on www.ecad.eu

On tail trend detection: modeling relative risk

The climate change dispute is about changes over time of environmental characteristics (such as rainfall). Some people say that a possible change is not so much in the mean but rather in the extreme phenomena (that is, the average rainfall may not change much but heavy storms may become more or less frequent). The paper studies changes over time in the probability that some high threshold is exceeded. The model is such that the threshold does not need to be specified, the results hold for any high threshold. For simplicity a certain linear trend is studied depending on one real parameter. Estimation and testing procedures (is there a trend?) are developed. Simulation results are presented. The method is applied to trends in heavy rainfall at 18 gauging stations across Germany and The Netherlands. A tentative conclusion is that the trend seems to depend on whether or not a station is close to the sea.Comment: 38 page

Geomagnetic activity and polar surface air temperature variability

Here we use the ERA-40 and ECMWF operational surface level air temperature data sets from 1957 to 2006 to examine polar temperature variations during years with different levels of geomagnetic activity, as defined by the A(p) index. Previous modeling work has suggested that NOx produced at high latitudes by energetic particle precipitation can eventually lead to detectable changes in surface air temperatures (SATs). We find that during winter months, polar SATs in years with high A(p) index are different than in years with low A(p) index; the differences are statistically significant at the 2-sigma level and range up to about +/- 4.5 K, depending on location. The temperature differences are larger when years with wintertime Sudden Stratospheric Warmings (SSWs) are excluded. We take into account solar irradiance variations, unlike previous analyses of geomagnetic effects in ERA-40 and operational data. Although we cannot conclusively show that the polar SAT patterns are physically linked by geomagnetic activity, we conclude that geomagnetic activity likely plays a role in modulating wintertime surface air temperatures. We tested our SAT results against variation in the Quasi Biennial Oscillation, the El Nino Southern Oscillation and the Southern Annular Mode. The results suggested that these were not driving the observed polar SAT variability. However, significant uncertainty is introduced by the Northern Annular Mode, and we cannot robustly exclude a chance linkage between sea surface temperature variability and geomagnetic activity

UK community Earth system modelling for CMIP6

We describe the approach taken to develop the UK’s first community Earth System model, UKESM1. This is a joint effort involving the Met Office and the Natural Environment Research Council (NERC), representing the UK academic community. We document our model development procedure and the subsequent UK submission to CMIP6, based on a traceable hierarchy of coupled physical and Earth system models. UKESM1 builds on the well‐established, world‐leading HadGEM models of the physical climate system and incorporates cutting‐edge new representations of aerosols, atmospheric chemistry, terrestrial carbon and nitrogen cycles, and an advanced model of ocean biogeochemistry. A high‐level metric of overall performance shows that both the physical model, HadGEM3‐GC3.1 and UKESM1 perform better than most other CMIP6 models so far submitted for a broad range of variables. We point to much more extensive evaluation performed in other papers in this special issue. The merits of not using any forced climate change simulations within our model development process are discussed. First results from HadGEM3‐GC3.1 and UKESM1 include the emergent climate sensitivity (5.5K and 5.4K respectively) which is high relative to the current range of CMIP5 models. The role of cloud microphysics and cloud‐aerosol interactions in driving the climate sensitivity, and the systematic approach taken to understand this role is highlighted in other papers in this special issue. We place our findings within the broader modelling landscape indicating how our understanding of key processes driving higher sensitivity in the two UK models seems to align with results from a number of other CMIP6 models

Effects of Temperature–Climate Patterns on the Production of Some Competitive Species on Grounds of Modelling

Climate change has serious effects on the setting up and the operation of natural ecosystems. Small increase in temperature could cause rise in the amount of some species or potential disappearance of others. During our researches, the dispersion of the species and biomass production of a theoretical ecosystem were examined on the effect of the temperature–climate change. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during modelling a theoretical ecosystem, and several important theoretical questions could be answered

An ecological time-series study of heat-related mortality in three European cities

BACKGROUND: Europe has experienced warmer summers in the past two decades and there is a need to describe the determinants of heat-related mortality to better inform public health activities during hot weather. We investigated the effect of high temperatures on daily mortality in three cities in Europe (Budapest, London, and Milan), using a standard approach. METHODS: An ecological time-series study of daily mortality was conducted in three cities using Poisson generalized linear models allowing for over-dispersion. Secular trends in mortality and seasonal confounding factors were controlled for using cubic smoothing splines of time. Heat exposure was modelled using average values of the temperature measure on the same day as death (lag 0) and the day before (lag 1). The heat effect was quantified assuming a linear increase in risk above a cut-point for each city. Socio-economic status indicators and census data were linked with mortality data for stratified analyses. RESULTS: The risk of heat-related death increased with age, and females had a greater risk than males in age groups > or =65 years in London and Milan. The relative risks of mortality (per degrees C) above the heat cut-point by gender and age were: (i) Male 1.10 (95%CI: 1.07-1.12) and Female 1.07 (1.05-1.10) for 75-84 years, (ii) M 1.10 (1.06-1.14) and F 1.08 (1.06-1.11) for > or = or =85 years in Budapest (> or =24 degrees C); (i) M 1.03 (1.01-1.04) and F 1.07 (1.05-1.09), (ii) M 1.05 (1.03-1.07) and F 1.08 (1.07-1.10) in London (> or =20 degrees C); and (i) M 1.08 (1.03-1.14) and F 1.20 (1.15-1.26), (ii) M 1.18 (1.11-1.26) and F 1.19 (1.15-1.24) in Milan (> or =26 degrees C). Mortality from external causes increases at higher temperatures as well as that from respiratory and cardiovascular disease. There was no clear evidence of effect modification by socio-economic status in either Budapest or London, but there was a seemingly higher risk for affluent non-elderly adults in Milan. CONCLUSION: We found broadly consistent determinants (age, gender, and cause of death) of heat related mortality in three European cities using a standard approach. Our results are consistent with previous evidence for individual determinants, and also confirm the lack of a strong socio-economic gradient in heat health effects currently in Europe

A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia

This article provides high-resolution information on the projected changes in annual extreme rainfall and high- and low-streamflow events over Southeast Asia under extreme climate change. The analysis was performed using the bias-corrected result of the High-Resolution Model Intercomparison Project (HighResMIP) multi-model experiment for the period 1971–2050. Eleven rainfall indices were calculated, along with streamflow simulation using the PCR-GLOBWB hydrological model. The historical period 1981–2010 and the near-future period 2021–2050 were considered for this analysis. Results indicate that, over former mainland Southeast Asia, Myanmar will face more challenges in the near future. The east coast of Myanmar will experience more extreme high-rainfall conditions, while northern Myanmar will have longer dry spells. Over the Indonesian maritime continent, Sumatra and Java will suffer from an increase in dry-spell length of up to 40 %, while the increase in extreme high rainfall will occur over Borneo and mountainous areas in Papua. Based on the streamflow analysis, the impact of climate change is more prominent in a low-flow event than in a high-flow event. The majority of rivers in the central Mekong catchment, Sumatra, Peninsular Malaysia, Borneo, and Java will experience more extreme low-flow events. More extreme dry conditions in the near future are also seen from the increasing probability of future low-flow occurrences, which reaches 101 % and 90 %, on average, over Sumatra and Java, respectively. In addition, based on our results over Java and Sumatra, we found that the changes in extreme high- and low-streamflow events are more pronounced in rivers with steep hydrographs (rivers where flash floods are easily triggered), while rivers with flat hydrographs have a higher risk in terms of the probability of low-flow change.</p

Reassessing changes in diurnal temperature range: Intercomparison and evaluation of existing global data set estimates

Changes in diurnal temperature range (DTR) over global land areas are compared from a broad range of independent data sets. All data sets agree that global-mean DTR has decreased significantly since 1950, with most of that decrease occurring over 1960–1980. The since-1979 trends are not significant, with inter-data set disagreement even over the sign of global changes. Inter-data set spread becomes greater regionally and in particular at the grid box level. Despite this, there is general agreement that DTR decreased in North America, Europe, and Australia since 1951, with this decrease being partially reversed over Australia and Europe since the early 1980s. There is substantive disagreement between data sets prior to the middle of the twentieth century, particularly over Europe, which precludes making any meaningful conclusions about DTR changes prior to 1950, either globally or regionally. Several variants that undertake a broad range of approaches to postprocessing steps of gridding and interpolation were analyzed for two of the data sets. These choices have a substantial influence in data sparse regions or periods. The potential of further insights is therefore inextricably linked with the efficacy of data rescue and digitization for maximum and minimum temperature series prior to 1950 everywhere and in data sparse regions throughout the period of record. Over North America, station selection and homogeneity assessment is the primary determinant. Over Europe, where the basic station data are similar, the postprocessing choices are dominant. We assess that globally averaged DTR has decreased since the middle twentieth century but that this decrease has not been linear