Bivariate colour maps for visualizing climate data

The increasing availability of gridded, high-resolution, multivariate climatological data sets calls for innovative approaches to visualize inter-variable relations. In this study, we present a methodology, based on properties of common colour schemes, to plot two variables in a single colour map by using a two-dimensional colour legend for both sequential and diverging data. This is especially suited for climate data as the spatial distribution of the relation between different variables is often as important as the distribution of variables individually. Two example applications are given to illustrate the use of the method: one that shows the global distribution of climate based on observed temperature and relative humidity, and the other showing the distribution of recent changes in observed temperature and precipitation over Europe. A flexible and easy-to-implement method is provided to construct different colour legends for sequential and diverging data

Parameter Sensitivity in LSMs: An Analysis Using Stochastic Soil Moisture Models and ELDAS Soil Parameters

Integration of simulated and observed states through data assimilation as well as model evaluation requires a realistic representation of soil moisture in land surface models (LSMs). However, soil moisture in LSMs is sensitive to a range of uncertain input parameters, and intermodel differences in parameter values are often large. Here, the effect of soil parameters on soil moisture and evapotranspiration are investigated by using parameters from three different LSMs participating in the European Land Data Assimilation System (ELDAS) project. To prevent compensating effects from other than soil parameters, the effects are evaluated within a common framework of parsimonious stochastic soil moisture models. First, soil parameters are shown to affect soil moisture more strongly than the average evapotranspiration. In arid climates, the effect of soil parameters is on the variance rather than the mean, and the intermodel flux differences are smallest. Soil parameters from the ELDAS LSMs differ strongly, most notably in the available moisture content between the wilting point and the critical moisture content, which differ by a factor of 3. The ELDAS parameters can lead to differences in mean volumetric soil moisture as high as 0.10 and an average evapotranspiration of 10%–20% for the investigated parameter range. The parsimonious framework presented here can be used to investigate first-order parameter sensitivities under a range of climate conditions without using full LSM simulations. The results are consistent with many other studies using different LSMs under a more limited range of possible forcing condition

Regional scaling of annual mean precipitation and water availability with global temperature change

Changes in regional water availability belong to the most crucial potential impacts of anthropogenic climate change, but are highly uncertain. It is thus of key importance for stakeholders to assess the possible implications of different global temperature thresholds on these quantities. Using a subset of climate model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), we derive here the sensitivity of regional changes in precipitation and in precipitation minus evapotranspiration to global temperature changes. The simulations span the full range of available emission scenarios, and the sensitivities are derived using a modified pattern scaling approach. The applied approach assumes linear relationships on global temperature changes while thoroughly addressing associated uncertainties via resampling methods. This allows us to assess the full distribution of the simulations in a probabilistic sense. Northern high-latitude regions display robust responses towards wetting, while subtropical regions display a tendency towards drying but with a large range of responses. Even though both internal variability and the scenario choice play an important role in the overall spread of the simulations, the uncertainty stemming from the climate model choice usually accounts for about half of the total uncertainty in most regions. We additionally assess the implications of limiting global mean temperature warming to values below (i) 2 K or (ii) 1.5 K (as stated within the 2015 Paris Agreement). We show that opting for the 1.5 K target might just slightly influence the mean response, but could substantially reduce the risk of experiencing extreme changes in regional water availability

Today's virtual water consumption and trade under future water scarcity

The populations of most nations consume products of both domestic and foreign origin, importing together with the products the water which is expended abroad for their production (termed 'virtual water'). Therefore, any investigation of the sustainability of present-day water consumption under future climate change needs to consider the effects of potentially reduced water availability both on domestic water resources and on the trades of virtual water. Here we use combinations of Global Climate and Global Impact Models from the ISI–MIP ensemble to derive patterns of future water availability under the RCP2.6 and RCP8.5 greenhouse gas (GHG) concentrations scenarios. We assess the effects of reduced water availability in these scenarios on national water consumptions and virtual water trades through a simple accounting scheme based on the water footprint concept. We thereby identify countries where the water footprint within the country area is reduced due to a reduced within-area water availability, most prominently in the Mediterranean and some African countries. National water consumption in countries such as Russia, which are non-water scarce by themselves, can be affected through reduced imports from water scarce countries. We find overall stronger effects of the higher GHG concentrations scenario, although the model range of climate projections for single GHG concentrations scenarios is in itself larger than the differences induced by the GHG concentrations scenarios. Our results highlight that, for both investigated GHG concentration scenarios, the current water consumption and virtual water trades cannot be sustained into the future due to the projected patterns of reduced water availability

Observed trends in global indicators of mean and extreme streamflow

Published online 23 JAN 2019This study investigates global changes in indicators of mean and extreme streamflow. The assessment is based on the Global Streamflow Indices and Metadata archive and focuses on time series of the annual minimum, the 10th, 50th, and 90th percentiles, the annual mean, and the annual maximum of daily streamflow. Trends are estimated using the Sen‐Theil slope, and the significance of mean regional trends is established through bootstrapping. Changes in the indices are often regionally consistent, showing that the entire flow distribution is moving either upward or downward. In addition, the analysis confirms the complex nature of hydrological change where drying in some regions (e.g., in the Mediterranean) is contrasted by wetting in other regions (e.g., North Asia). Observed changes are discussed in the context of previous results and with respect to model estimates of the impacts of anthropogenic climate change and human water management.L. Gudmundsson, M. Leonard, H. X. Do, S. Westra, and S. I. Seneviratn

Reconciling spatial and temporal soi moisture effects on aftrnoon rainfall

Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks

Climate damage projections beyond annual temperature

Estimates of global economic damage from climate change assess the effect of annual temperature changes. However, the roles of precipitation, temperature variability and extreme events are not yet known. Here, by combining projections of climate models with empirical dose–response functions translating shifts in temperature means and variability, rainfall patterns and extreme precipitation into economic damage, we show that at +3 °C global average losses reach 10% of gross domestic product, with worst effects (up to 17%) in poorer, low-latitude countries. Relative to annual temperature damage, the additional impacts of projecting variability and extremes are smaller and dominated by interannual variability, especially at lower latitudes. However, accounting for variability and extremes when estimating the temperature dose–response function raises global economic losses by nearly two percentage points and exacerbates economic tail risks. These results call for region-specific risk assessments and the integration of other climate variables for a better understanding of climate change impacts

Local ecosystem feedbacks and critical transitions in the climate

Global and regional climate models, such as those used in IPCC assessments, are the best tools available for climate predictions. Such models typically account for large-scale land-atmosphere feedbacks. However, these models omit local vegetationenvironment 5 feedbacks that are crucial for critical transitions in ecosystems. Here, we reveal the hypothesis that, if the balance of feedbacks is positive at all scales, local vegetation-environment feedbacks may trigger a cascade of amplifying effects, propagating from local to large scale, possibly leading to critical transitions in the largescale climate. We call for linking local ecosystem feedbacks with large-scale land10 atmosphere feedbacks in global and regional climate models in order to yield climate predictions that we are more confident about

HESS opinions: a perspective on isotope versus non-isotope approaches to determine the contribution of transpiration to total evaporation

Current techniques to disentangle the evaporative fluxes from the continental surface into a contribution evaporated from soils and canopy, or transpired by plants, are under debate. Many isotope-based studies show that transpiration contributes generally more than 70% to the total evaporation, while other isotope-independent techniques lead to considerably smaller transpiration fractions. This paper provides a perspective on isotope-based versus non-isotope-based partitioning studies. Some partitioning results from isotope-based methods, hydrometric measurements, and modeling are presented for comparison. Moreover, the methodological aspects of the partitioning analysis are considered, including their limitations, and explanations of possible discrepancies between the methods are discussed. We suggest sources of systematic error that may lead to biases in the results, e.g., instruments inaccuracy, assumptions used in analyses, and calibration parameters. A number of comparison studies using isotope-based methods and hydrometric measurements in the same plants and climatic conditions are consistent within the errors; however, models tend to produce lower transpiration fractions. The relatively low transpiration fraction in current state-of-the-art land-surface models calls for a reassessment of the skill of the underlying model parameterizations. The scarcity of global evaporation data makes calibration and validation of global isotope-independent and isotope-based results difficult. However, isotope-enabled land-surface and global climate modeling studies allow for the evaluation of the parameterization of land-surface models by comparing the computed water isotopologue signals in the atmosphere with the available remote sensing and flux-based data sets. Future studies that allow for this evaluation could provide a better understanding of the hydrological cycle in vegetated regions

Flood risk and climate change: global and regional perspectives

A holistic perspective on changing rainfall-driven flood risk is provided for the late 20th and early 21st centuries. Economic losses from floods have greatly increased, principally driven by the expanding exposure of assets at risk. It has not been possible to attribute rain-generated peak streamflow trends to anthropogenic climate change over the past several decades. Projected increases in the frequency and intensity of heavy rainfall, based on climate models, should contribute to increases in precipitation-generated local flooding (e.g. flash flooding and urban flooding). This article assesses the literature included in the IPCC SREX report and new literature published since, and includes an assessment of changes in flood risk in seven of the regions considered in the recent IPCC SREX report-Africa, Asia, Central and South America, Europe, North America, Oceania and Polar regions. Also considering newer publications, this article is consistent with the recent IPCC SREX assessment finding that the impacts of climate change on flood characteristics are highly sensitive to the detailed nature of those changes and that presently we have only low confidence1 in numerical projections of changes in flood magnitude or frequency resulting from climate change