Physical processes driving intensification of future precipitation in the mid- to high latitudes

Precipitation is changing as the climate warms, and downpours can become more intense due to the increased water holding capacity of the atmosphere. However, the exact nature of the precipitation response and its characteristics is still not well understood due to the complex nature of the physical processes underlying the formation of clouds and precipitation. In this study, present and future Norwegian climate is simulated at convection-permitting scales with a regional climate model. The future climate is a high emission scenario at the middle of the century. Hourly precipitation is separated into three categories (convective, stratiform, and orographically enhanced stratiform) using a physically-based algorithm. We investigate changes in the frequency, intensity and duration of precipitation events for each category, delivering a more nuanced insight into the precipitation response to a changing climate. Results show very strong seasonality, with significant intensification of autumn precipitation. An increase in convective precipitation frequency and intensity dominates the climate change signal regardless of season. While changes in winter and summer are well explained by thermodynamical theory, the precipitation response in autumn and spring deviates from the idealised thermodynamic response, partly owing to changes in cloud microphysics. These results show that changes in the precipitation distribution are affected in complex ways by the local climatology, terrain, seasonality and cloud processes. They illustrate the need for further and more detailed investigations about physical processes underlying projected precipitation changes and their seasonal and regional dependence.publishedVersio

Reconciling conflicting evidence for the cause of the observed early 21st century Eurasian cooling

It is now well established that the Arctic is warming at a faster rate than the global average. This warming, which has been accompanied by a dramatic decline in sea ice, has been linked to cooling over the Eurasian subcontinent over recent decades, most dramatically during the period 1998–2012. This is a counter-intuitive impact under global warming given that land regions should warm more than ocean (and the global average). Some studies have proposed a causal teleconnection from Arctic sea-ice retreat to Eurasian wintertime cooling; other studies argue that Eurasian cooling is mainly driven by internal variability. Overall, there is an impression of strong disagreement between those holding the “ice-driven” versus “internal variability” viewpoints. Here, we offer an alternative framing showing that the sea ice and internal variability views can be compatible. Key to this is viewing Eurasian cooling through the lens of dynamics (linked primarily to internal variability with some potential contribution from sea ice; cools Eurasia) and thermodynamics (linked to sea-ice retreat; warms Eurasia). This approach, combined with recognition that there is uncertainty in the hypothesized mechanisms themselves, allows both viewpoints (and others) to co-exist and contribute to our understanding of Eurasian cooling. A simple autoregressive model shows that Eurasian cooling of this magnitude is consistent with internal variability, with some periods exhibiting stronger cooling than others, either by chance or by forced changes. Rather than posit a “yes-or-no” causal relationship between sea ice and Eurasian cooling, a more constructive way forward is to consider whether the cooling trend was more likely given the observed sea-ice loss, as well as other sources of low-frequency variability. Taken in this way both sea ice and internal variability are factors that affect the likelihood of strong regional cooling in the presence of ongoing global warming.publishedVersio

Behaviourally modern humans in coastal southern Africa experienced an increasingly continental climate during the transition from Marine Isotope Stage 5 to 4

Unravelling evolution-by-environment interactions on the gut microbiome is particularly relevant considering the unprecedented level of human-driven disruption of the ecological and evolutionary trajectories of species. Here, we aimed to evaluate whether an evolutionary response to size-selective mortality influences the gut microbiome of medaka (Oryzias latipes), how environmental conditions interact with the genetic background of medaka on their microbiota, and the association between microbiome diversity and medaka growth-related traits. To do so, we studied two lineages of medaka with known divergence in foraging efficiency and life history raised under antagonistic size-selective regimes for 10 generations (i.e. the largest or the smallest breeders were removed to mimic fishing-like or natural mortality). In pond mesocosms, the two lineages were subjected to contrasting population density and light intensity (used as proxies of resource availability). We observed significant differences in the gut microbiome composition and richness between the two lines, and this effect was mediated by light intensity. The bacterial richness of fishing-like medaka (small-breeder line) was reduced by 34% under low-light conditions compared to high-light conditions, while it remained unchanged in natural mortality-selected medaka (large-breeder line). However, the observed changes in bacterial richness did not correlate with changes in adult growth-related traits. Given the growing evidence about the gut microbiomes importance to host health, more in-depth studies are required to fully understand the role of the microbiome in size-selected organisms and the possible ecosystem-level consequences.publishedVersio

Regional water cycle sensitivity to afforestation: synthetic numerical experiments for tropical Africa

Afforestation as a climate change mitigation option has been the subject of intense debate and study over the last few decades, particularly in the tropics where agricultural activity is expanding. However, the impact of such landcover changes on the surface energy budget, temperature, and precipitation remains unclear as feedbacks between various components are difficult to resolve and interpret. Contributing to this scientific debate, regional climate models of varying complexity can be used to test how regional climate reacts to afforestation. In this study, the focus is on the gauged Nzoia basin (12,700 km2) located in a heavily farmed region of tropical Africa. A reanalysis product is dynamically downscaled with a coupled atmospheric-hydrological model (WRF-Hydro) to finely resolve the land-atmosphere system in the Nzoia region. To overcome the problem of Nzoia river flooding over its banks we enhance WRF-Hydro with an overbank flow routing option, which improves the representation of daily discharge based on the Nash-Sutcliffe efficiency and Kling-Gupta efficiency (from −2.69 to 0.30, and −0.36 to 0.63, respectively). Changing grassland and cropland areas to savannas, woody savannas, and evergreen broadleaf forest in three synthetic numerical experiments allows the assessment of potential regional climate impacts of three afforestation strategies. In all three cases, the afforestation-induced decrease in soil evaporation is larger than the afforestation-induced increase in plant transpiration, thus increasing sensible heat flux and triggering a localized negative feedback process leading to more precipitation and more runoff. This effect is more pronounced with the woody savannas experiment, with 7% less evapotranspiration, but 13% more precipitation, 8% more surface runoff, and 12% more underground runoff predicted in the Nzoia basin. This study demonstrates a potentially large impact of afforestation on regional water resources, which should be investigated in more detail for policy making purposes.publishedVersio

Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble

In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990?2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell?Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max ?2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40?60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (?2.8 °C); this location suggests that land?atmosphere rather than cloud?radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain?Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15?30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.The contribution from Universidad de Cantabria was funded by the Spanish R&D programme through projects CORWES (CGL2010-22158-C02-01) and WRF4G (CGL2011-28864), co-funded by the European Regional Development Fund. M. García-Díez acknowledges financial support from the EXTREMBLES (CGL2010-21869) project

Extreme wind projections over Europe from the Euro-CORDEX regional climate models

Extreme weather events represent one of the most visible and immediate hazards to society. Many of these types of phenomena are projected to increase in intensity, duration or frequency as the climate warms. Of these extreme winds are among the most damaging historically over Europe yet assessments of their future changes remain fraught with uncertainty. This uncertainty arises due to both the rare nature of extreme wind events and the fact that most model are unable to faithfully represent them. Here we take advantage of a 15 member ensemble of high resolution Euro-CORDEX simulations (12 km) and investigate projected changes in extreme winds using a peaks-over-threshold approach. Additionally we show that – despite lingering model deficiencies and inadequate observational coverage – there is clear added value of the higher resolution simulations over coarser resolution counterparts. Further, the spatial heterogeneity and highly localised nature is well captured. Effects such as orographic interactions, drag due to urban areas, and even individual storm tracks over the oceans are clearly visible. As such future changes also exhibit strong spatial heterogeneity. These results emphasise the need for careful case-by-case treatment of extreme wind analysis, especially when done in a climate adaptation or decision making context. However, for more general assessments the picture is more clear with increases in the return period (i.e. more frequent) extreme episodes projected for Northern, Central and Southern Europe throughout the 21st century. While models continue to improve in their representation of extreme winds, improved observational coverage is desperately needed to obtain more robust assessments of extreme winds over Europe and elsewhere.publishedVersio

Resampling of ENSO teleconnections: accounting for cold-season evolution reduces uncertainty in the North Atlantic

We re-examine the uncertainty of the El Niño–Southern Oscillation (ENSO) teleconnection to the North Atlantic following the investigation of Deser et al. (2017) (DES2017). Our analyses are performed on the November–December (ND) and January–February (JF) means separately and for a geographical area that covers a larger extent in the midlatitude North Atlantic than DES2017. The motivation for splitting the cold season in this way arises from the fact that the teleconnection patterns and underlying physical mechanisms are different in late fall compared to midwinter. As in DES2017, our main technique in quantifying the uncertainty is bootstrap resampling. Amplitudes and spatial correlations of the bootstrap samples are presented together effectively using Taylor diagrams. In addition to the confidence intervals calculated from Student's t tests and the percentiles of anomalous sea level pressure (SLP) values in the bootstrap samples, we also investigate additional confidence intervals using techniques that are not widely used in climate research but have different advantages. In contrast to the interpretation by DES2017, our results indicate that we can have confidence (at the 5 % significance level) in the patterns of the teleconnected SLP anomalies. The uncertainties in the amplitudes remain large, with the upper-percentile anomalies at up to 2 times those of the lower percentiles in the North Pacific and 2.8 times in the North Atlantic

Resampling of ENSO teleconnections: accounting for cold-season evolution reduces uncertainty in the North Atlantic

We re-examine the uncertainty of the El Niño–Southern Oscillation (ENSO) teleconnection to the North Atlantic following the investigation of Deser et al. (2017) (DES2017). Our analyses are performed on the November–December (ND) and January–February (JF) means separately and for a geographical area that covers a larger extent in the midlatitude North Atlantic than DES2017. The motivation for splitting the cold season in this way arises from the fact that the teleconnection patterns and underlying physical mechanisms are different in late fall compared to midwinter. As in DES2017, our main technique in quantifying the uncertainty is bootstrap resampling. Amplitudes and spatial correlations of the bootstrap samples are presented together effectively using Taylor diagrams. In addition to the confidence intervals calculated from Student's t tests and the percentiles of anomalous sea level pressure (SLP) values in the bootstrap samples, we also investigate additional confidence intervals using techniques that are not widely used in climate research but have different advantages. In contrast to the interpretation by DES2017, our results indicate that we can have confidence (at the 5 % significance level) in the patterns of the teleconnected SLP anomalies. The uncertainties in the amplitudes remain large, with the upper-percentile anomalies at up to 2 times those of the lower percentiles in the North Pacific and 2.8 times in the North Atlantic.publishedVersio

Precipitation over southern Africa: is there consensus among global climate models (GCMs), regional climate models (RCMs) and observational data?

The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modeling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behavior of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (October–March), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensembles exhibited improved performance compared to their forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher-resolution regional climate simulations. The CMIP6 ensemble displayed a similar behavior to CMIP5, but reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angola Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic processes that take place. Improvements in observational networks (both in situ and satellite) as well as continued advancements in high-resolution modeling will be critical, in order to develop a robust assessment of climate change for southern Africa.publishedVersio

Resampling of ENSO teleconnections: accounting for cold-season evolution reduces uncertainty in the North Atlantic

We re-examine the uncertainty of the El Niño–Southern Oscillation (ENSO) teleconnection to the North Atlantic following the investigation of Deser et al. (2017) (DES2017). Our analyses are performed on the November–December (ND) and January–February (JF) means separately and for a geographical area that covers a larger extent in the midlatitude North Atlantic than DES2017. The motivation for splitting the cold season in this way arises from the fact that the teleconnection patterns and underlying physical mechanisms are different in late fall compared to midwinter. As in DES2017, our main technique in quantifying the uncertainty is bootstrap resampling. Amplitudes and spatial correlations of the bootstrap samples are presented together effectively using Taylor diagrams. In addition to the confidence intervals calculated from Student's t tests and the percentiles of anomalous sea level pressure (SLP) values in the bootstrap samples, we also investigate additional confidence intervals using techniques that are not widely used in climate research but have different advantages. In contrast to the interpretation by DES2017, our results indicate that we can have confidence (at the 5 % significance level) in the patterns of the teleconnected SLP anomalies. The uncertainties in the amplitudes remain large, with the upper-percentile anomalies at up to 2 times those of the lower percentiles in the North Pacific and 2.8 times in the North Atlantic