Brigitte Mueller

Recent decline in the global land evapotranspiration trend due to limited moisture supply

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land—a key diagnostic criterion of the effects of climate change and variability—remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

Hot days induced by precipitation deficits at the global scale

Global warming increases the occurrence probability of hot extremes, and improving the predictability of such events is thus becoming of critical importance. Hot extremes have been shown to be induced by surface moisture deficits in some regions. In this study, we assess whether such a relationship holds at the global scale. We find that wide areas of the world display a strong relationship between the number of hot days in the regions’ hottest month and preceding precipitation deficits. The occurrence probability of an above-average number of hot days is over 70% after precipitation deficits in most parts of South America as well as the Iberian Peninsula and Eastern Australia, and over 60% in most of North America and Eastern Europe, while it is below 30–40% after wet conditions in these regions. Using quantile regression analyses, we show that the impact of precipitation deficits on the number of hot days is asymmetric, i.e. extreme high numbers of hot days are most strongly influenced. This relationship also applies to the 2011 extreme event in Texas. These findings suggest that effects of soil moisture-temperature coupling are geographically more widespread than commonly assumed.

Systematic land climate and evapotranspiration biases in CMIP5 simulations

[1] Land climate is important for human population since it affects inhabited areas. Here we evaluate the realism of simulated evapotranspiration (ET), precipitation, and temperature in the CMIP5 multimodel ensemble on continental areas. For ET, a newly compiled synthesis data set prepared within the Global Energy and Water Cycle Experiment-sponsored LandFlux-EVAL project is used. The results reveal systematic ET biases in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, with an overestimation in most regions, especially in Europe, Africa, China, Australia, Western North America, and part of the Amazon region. The global average overestimation amounts to 0.17 mm/d. This bias is more pronounced than in the previous CMIP3 ensemble (overestimation of 0.09 mm/d). Consistent with the ET overestimation, precipitation is also overestimated relative to existing reference data sets. We suggest that the identified biases in ET can explain respective systematic biases in temperature in many of the considered regions. The biases additionally display a seasonal dependence and are generally of opposite sign (ET underestimation and temperature overestimation) in boreal summer (June–August).

Sensitivity of inferred climate model skill to evaluation decisions: a case study using CMIP5 evapotranspiration

Confrontation of climate models with observationally-based reference datasets is widespread and integral to model development. These comparisons yield skill metrics quantifying the mismatch between simulated and reference values and also involve analyst choices, or meta-parameters, in structuring the analysis. Here, we systematically vary five such meta-parameters (reference dataset, spatial resolution, regridding approach, land mask, and time period) in evaluating evapotranspiration (ET) from eight CMIP5 models in a factorial design that yields 68 700 intercomparisons. The results show that while model–data comparisons can provide some feedback on overall model performance, model ranks are ambiguous and inferred model skill and rank are highly sensitive to the choice of meta-parameters for all models. This suggests that model skill and rank are best represented probabilistically rather than as scalar values. For this case study, the choice of reference dataset is found to have a dominant influence on inferred model skill, even larger than the choice of model itself. This is primarily due to large differences between reference datasets, indicating that further work in developing a community-accepted standard ET reference dataset is crucial in order to decrease ambiguity in model skill.

The dry season intensity as a key driver of NPP trends

We analyze the impacts of changing dry season length and intensity on vegetation productivity and biomass. Our results show a wetness asymmetry in dry ecosystems, with dry seasons becoming drier and wet seasons becoming wetter, likely caused by climate change. The increasingly intense dry seasons were consistently correlated with a decreasing trend in net primary productivity (NPP) and biomass from different products and could potentially mean a reduction of 10–13% in NPP by 2100. We found that annual NPP in dry ecosystems is particularly sensitive to the intensity of the dry season, whereas an increase in precipitation during the wet season has a smaller effect. We conclude that changes in water availability over the dry season affect vegetation throughout the whole year, driving changes in regional NPP. Moreover, these results suggest that usage of seasonal water fluxes is necessary to improve our understanding of the link between water availability and the land carbon cycle.

Historically hottest summers projected to be the norm for more than half of the world’s population within 20 years

We project that within the next two decades, half of the worlds population will regularly (every second summer on average) experience regional summer mean temperatures that exceed those of the historically hottest summer, even under the moderate RCP4.5 emissions pathway. This frequency threshold for hot temperatures over land, which have adverse effects on human health, society and economy, might be broached in little more than a decade under the RCP8.5 emissions pathway. These hot summer frequency projections are based on adjusted RCP4.5 and 8.5 temperature projections, where the adjustments are performed with scaling factors determined by regularized optimal fingerprinting analyzes that compare historical model simulations with observations over the period 1950–2012. A temperature reconstruction technique is then used to simulate a multitude of possible past and future temperature evolutions, from which the probability of a hot summer is determined for each region, with a hot summer being defined as the historically warmest summer on record in that region. Probabilities with and without external forcing show that hot summers are now about ten times more likely (fraction of attributable risk 0.9) in many regions of the world than they would have been in the absence of past greenhouse gas increases. The adjusted future projections suggest that the Mediterranean, Sahara, large parts of Asia and the Western US and Canada will be among the first regions for which hot summers will become the norm (i.e. occur on average every other year), and that this will occur within the next 1–2 decades.

Wavelet correlations to reveal multiscale coupling in geophysical systems

The interactions between climate and the environment are highly complex. Due to this complexity, process-based models are often preferred to estimate the net magnitude and directionality of interactions in the Earth system. However, these models are based on simplifications of our understanding of nature and thus are unavoidably imperfect. Conversely, observation-based data of climatic and environmental variables are becoming increasingly accessible over global scales due to the progress of spaceborne sensing technologies and data-assimilation techniques. Albeit uncertain, these data enable the possibility to start unraveling complex multivariable, multiscale relationships if the appropriate statistical methods are applied. Here we investigate the potential of the wavelet cross-correlation method as a tool for identifying time/frequency-dependent interactions, feedback, and regime shifts in geophysical systems. The ability of wavelet cross-correlation to resolve the fast and slow components of coupled systems is tested on synthetic data of known directionality and then applied to observations to study one of the most critical interactions between land and atmosphere: the coupling between soil moisture and near-ground air temperature. Results show that our method is able to capture the dynamics of the soil moisture-temperature coupling over a wide range of temporal scales (from days to several months) and climatic regimes (from wet to dry) and consistently identify the magnitude and directionality of the coupling. Consequently, wavelet cross-correlations are presented as a promising tool for the study of multiscale interactions, with the potential of being extended to the analysis of causal relationships in the Earth system.

Variability of Soil Moisture Proxies and Hot Days Across the Climate Regimes of Australia

The frequency of extreme events such as heatwaves are expected to increase due to the effect of climate change, particularly in semi-arid regions areas of Australia. Recent studies have indicated a link between soil moisture deficits and heat extreme, focusing on the coupling between the two. This study investigates the relationship between the number of hot-days (Tx90) and four soil moisture proxies (SPI, API, MSDI and KBDI), and how the strength of this relationship changes across various climate regimes within Australia. A strong anti-correlation between Tx90 and each moisture index is found, particularly for tropical savannas and temperate regions. However, the magnitude of the increase in Tx90 with decreasing moisture is strongest in semi-arid and arid regions. It is also shown that the Tx90-soil moisture relationship strengthens during the El Nino phases of ENSO in regions which are more sensitive to changes in soil moisture.