ORCID Profile
0000-0001-9365-5759
Current Organisation
Royal Netherlands Meteorological Institute
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Publisher: Springer Science and Business Media LLC
Date: 18-08-2020
Publisher: Springer Science and Business Media LLC
Date: 28-05-2015
Publisher: Copernicus GmbH
Date: 06-01-2021
Abstract: Abstract. In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit.
Publisher: Copernicus GmbH
Date: 24-05-2019
Publisher: Wiley
Date: 15-12-2015
DOI: 10.1002/QJ.2692
Publisher: Wiley
Date: 17-02-2015
DOI: 10.1002/QJ.2508
Publisher: Copernicus GmbH
Date: 24-05-2019
DOI: 10.5194/ESD-2019-20
Abstract: Abstract. In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe, however, the link between droughts and climate change is not sufficiently understood. In the current study we focus on agricultural drought and the influence of high temperatures and precipitation deficits on this. Using a combination of models and observational datasets, we studied trends in six regions in eastern Africa in four drought-related annually averaged variables – soil moisture, precipitation, temperature and, as a measure of evaporative demand, potential evapotranspiration (PET). In standardized soil moisture data, we find no discernible trends. Precipitation was found to have a stronger influence on soil moisture variability than temperature or PET, especially in the drier, or water-limited, study regions. The error margins on precipitation-trend estimates are however large and no clear trend is evident. We find significant positive trends in local temperatures. However, the influence of these on soil moisture annual trends appears limited as evaporation is water limited. The trends in PET are predominantly positive, but we do not find strong relations between PET and soil moisture trends. Nevertheless, the PET-trend results can still be of interest for irrigation purposes as it is PET that determines the maximum evaporation rate. We conclude that, until now, the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and recommend that any soil moisture analysis be supplemented by analysis of precipitation deficit.
Publisher: Springer Science and Business Media LLC
Date: 05-2021
DOI: 10.1007/S10584-021-03071-7
Abstract: The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-7120
Abstract: & & The frequency and severity of droughts and heatwaves are projected to increase under global warming. However, their impacts on the terrestrial biosphere and the anthropogenic CO& sub& & /sub& & sink remain poorly understood. Here we analyse the effects of six hypothetical climate scenarios with stationary climate but differing drought-heat signatures on vegetation distribution and land carbon dynamics, as modelled by seven state-of-the-art dynamic global vegetation models. The six forcing scenarios are s led from a long climate model simulation and consist of a control& em& & /em& scenario representing a natural climate, a scenario with no hot and dry extremes, one with no compound hot and dry extremes but univariate extremes are possible, one with only hot extremes, one with only dry extremes, and one with both hot and dry extremes. Models show substantial differences in their vegetation coverage response to the different scenarios. While in some models, climate with no droughts and heatwaves favours tree growth, this is not the case for other models, where grasses benefit. Similarly, climates with frequent droughts promote grasses in some models and reduce forest growth in others. Models tend to agree that a climate with frequent concurrent droughts and heatwaves leads to reduced tree cover and increased grass cover. The changes in coverage are mirrored by changes in gross and net carbon fluxes. The stark differences among model responses illustrate the different modelling processes dealing with heat and drought stress and how they are differently affected by the extremes. Overall, this comparison helps quantify model uncertainties and process differences that are important for how vegetation behaves under extreme climate events.& & & & Our study illustrates how factorial model experiments can be employed to disentangle the impacts from single and compound extremes. The findings from this model comparison may also help to identify sources of uncertainty in carbon cycle projections.& &
Publisher: American Geophysical Union (AGU)
Date: 11-2021
DOI: 10.1029/2021EF002340
Abstract: Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for ex le, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (a) preconditioned , (b) multivariate , (c) temporally compounding , and (d) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (a) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (b) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non‐stationary multivariate process. For instance, future mean sea‐level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (c) In Portugal, deep‐landslides are often caused by temporal clusters of moderate precipitation events. Finally, (d) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Karin van der Wiel.