Land-atmosphere feedbacks contribute to crop failure in global rainfed breadbaskets

Global crop yields are highly dependent on climate variability, with the largest agricultural failures frequently occurring during extremely dry and hot years. Land-atmosphere feedbacks are thought to play a crucial role in agricultural productivity during such events: precipitation deficits cause soil desiccation, which reduces evaporation and enhances sensible heating from the land surface; the amplified local temperatures and moisture deficits can be detrimental to crop yield. While this impact of local land-atmosphere feedbacks on agricultural productivity has recently been reported, the dependency of crop yields on upwind regions remains understudied. Here, we determine the spatio-temporal origins of moisture and heat over the world's largest 75 rainfed breadbaskets, and illustrate the crop yield dependency on upwind regions. Further, we disentangle the role of local and upwind land-atmosphere interactions on anomalous moisture and heat transport during low-yield years. Our results indicate that crop failure increases on average by around 40% when both upwind and local land-atmosphere feedbacks cause anomalously low moisture and high heat transport into the breadbaskets. The impact of upwind land-atmosphere feedbacks on productivity deficits is the largest in water-limited regions, which show an increased dependency on moisture supply from upwind land areas. Better understanding these upwind-downwind dependencies in agricultural regions can help develop adaptation strategies to prevent food shortage in a changing climate.

Are Global Drylands Self-Expanding? [DOI: 10.5194/egusphere-egu23-2320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Aridification threatens not only water availability but also adversely affects ecosystem health, and energy security. Using the (atmospheric) aridity index (AI) – defined as precipitation, (P) over potential evaporation (Ep) – several studies have shown that global drylands are either expanding or will expand in the future. Expansion is defined as the reduction of AI below 0.65, i.e., a change from a humid to a dry region may be owed to deficits in P and/or increases in Ep. However, the actual mechanisms and processes driving dryland expansion remain less explored. Here, we use an observationally-constrained Lagrangian transport model to test if expansion of drylands is self-fuelled: can reductions in moisture transport from existing drylands result in aridification of existing humid regions and thus lead to dryland expansion?To estimate the spatial extent of drylands, we calculate AI using P from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) (Beck et al 2019) and Ep from the hPET dataset (Singer et al. 2021). To quantify the changes in moisture and heat transport into newly expanded drylands, we use global simulations of the FLEXPART version 10.4, forced with the ERA-Interim reanalysis for a period of 38 years (1981–2018). The FLEXPART outputs include the properties of the air parcels at 3-hourly time steps, which are then post-processed using the Heat and Moisture Tracking Framework (HAMSTER v1.2.0) described by Keune et al. (2022) and bias-corrected using evaporation from the GLEAM-Hybrid dataset (Koppa et al. 2022).Preliminary results show that between 1981 and 2018, ~5.5 million km2 of the terrestrial land surface underwent aridification (humid to dryland transition). Further, our results indicate that, on an average, ~45% of the reduction in AI can be attributed to reduction in P, out of which ~32% can be traced to reduction in moisture transport from existing drylands. Preliminary findings support our hypothesis that drylands are indeed self-expanding. References:Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., van Dijk, A. I. J. M., McVicar, T. R., & Adler, R. F. (2019). MSWEP V2 Global 3-Hourly 0.1° Precipitation: Methodology and Quantitative Assessment, Bulletin of the American Meteorological Society, 100(3), 473-500.Keune, J., Schumacher, D. L., & Miralles, D. G. (2022). A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models. Geoscientific Model Development, 15(5), 1875–1898. doi:10.5194/gmd-15-1875-2022.Koppa, A., Rains, D., Hulsman, P., Poyatos, R., & Miralles, D. G. (2022). A deep learning-based hybrid model of global terrestrial evaporation. Nature Communications, 13(1), 1912. doi:10.1038/s41467-022-29543-7.Singer, M. B., Asfaw, D. T., Rosolem, R., Cuthbert, M. O., Miralles, D. G., MacLeod, D., … Michaelides, K. (2021). Hourly potential evapotranspiration at 0.1° resolution for the global land surface from 1981-present. Scientific Data, 8(1), 224. doi:10.1038/s41597-021-01003-9

The Contribution of Transpiration to Precipitation Over African Watersheds

The redistribution of biological (transpiration) and non-biological (interception loss, soil evaporation) fluxes of terrestrial evaporation via atmospheric circulation and precipitation is an important Earth system process. In vegetated ecosystems, transpiration dominates terrestrial evaporation and is thought to be crucial for regional moisture recycling and ecosystem functioning. However, the spatial and temporal variability in the dependency of precipitation on transpiration remains understudied, particularly in sparsely sampled regions like Africa. Here, we investigate how biological and non-biological sources of evaporation in Africa contribute to rainfall over the major watersheds in the continent. Our study is based on simulated atmospheric moisture trajectories derived from the Lagrangian model FLEXPART, driven by 1° resolution reanalysis data over 1981-2016. Using daily satellite-based fractions of transpiration over terrestrial evaporation, we isolate the contribution of vegetation to monthly rainfall. Furthermore, we highlight two watersheds (Congo and Senegal) for which we explore intra- and interannual variability of different precipitation sources, and where we find contrasting patterns of vegetation-sourced precipitation within and between years. Overall, our results show that almost 50% of the annual rainfall in Africa originates from transpiration, although the variability between watersheds is large (5%-68%). We conclude that, considering the current and projected patterns of land use change in Africa, a better understanding of the implications for continental-scale water availability is needed.

Drought self-propagation in drylands due to land-atmosphere feedbacks

Reduced evaporation due to dry soils can affect the land surface energy balance, with implications for local and downwind precipitation. When evaporation is constrained by soil moisture, the atmospheric supply of water is depleted, and this deficit may propagate in time and space. This mechanism could theoretically result in the self-propagation of droughts, but the extent to which this process occurs is unknown. Here we isolate the influence of soil moisture drought on downwind precipitation using Lagrangian moisture tracking constrained by observations from the 40 largest recent droughts worldwide. We show that dryland droughts are particularly prone to self-propagating, because evaporation tends to respond strongly to enhanced soil water stress. In drylands precipitation can decline by more than 15% due to upwind drought in during a single event, and up to 30% during individual months. In light of projected widespread reductions in water availability, this feedback may further exacerbate future droughts.

Soil drought can mitigate deadly heat stress thanks to a reduction of air humidity

Global warming increases the number and severity of deadly heatwaves. Recent heatwaves often coincided with soil droughts that intensify air temperature but lower air humidity. Since lowering air humidity may reduce human heat stress, the net impact of soil desiccation on the morbidity and mortality of heatwaves remains unclear. Combining weather balloon and satellite observations, atmospheric modelling, and meta-analyses of heatwave mortality, we find that soil droughts—despite their warming effect—lead to a mild reduction in heatwave lethality. More specifically, morning dry soils attenuate afternoon heat stress anomaly by ~5%. This occurs because of reduced surface evaporation and increased entrainment of dry air aloft. The benefit appears more pronounced during specific events, such as the Chicago 1995 and Northern U.S. 2006 and 2012 heatwaves. Our findings suggest that irrigated agriculture may intensify lethal heat stress, and question recently proposed heatwave mitigation measures involving surface moistening to increase evaporative cooling.

Atmospheric heat and moisture transport to energy- and water-limited ecosystems

The land biosphere is a crucial component of the Earth system that interacts with the atmosphere in a complex manner through manifold feedback processes. These relationships are bidirectional, as climate affects our terrestrial ecosystems, which, in turn, influence climate. Great progress has been made in understanding the local interactions between the terrestrial biosphere and climate, but influences from remote regions through energy and water influxes to downwind ecosystems remain less explored. Using a Lagrangian trajectory model driven by atmospheric reanalysis data, we show how heat and moisture advection affect gross carbon production at interannual scales and in different ecoregions across the globe. For water‐limited regions, results show a detrimental effect on ecosystem productivity during periods of enhanced heat and reduced moisture advection. These periods are typically associated with winds that disproportionately come from continental source regions, as well as positive sensible heat flux and negative latent heat flux anomalies in those upwind locations. Our results underline the vulnerability of ecosystems to the occurrence of upwind climatic extremes and highlight the importance of the latter for the spatiotemporal propagation of ecosystem disturbances.

A Precipitation Recycling Network to Assess Freshwater Vulnerability: Challenging the Watershed Convention

Water resources and water scarcity are usually regarded as local aspects for which a watershed-based management appears adequate. However, precipitation, as a main source of freshwater, may depend on moisture supplied through land evaporation from outside the watershed. This notion of evaporation as a local "green water" supply to precipitation is typically not considered in hydrological water assessments. Here we propose the concept of a watershed precipitation recycling network, which establishes atmospheric pathways and links land surface evaporation as a moisture supply to precipitation, hence contributing to local but also remote freshwater resources. Our results show that up to 74% of summer precipitation over European watersheds depends on moisture supplied from other watersheds, which contradicts the conventional consideration of autarkic watersheds. The proposed network approach illustrates atmospheric pathways and enables the objective assessment of freshwater vulnerability and water scarcity risks under global change. The illustrated watershed interdependence emphasizes the need for global water governance to secure freshwater availability.

Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter

Objectives

Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer's disease (AD) and dementia portrayal on Twitter to demonstrate its use. The approach improves feasibility of examining large publicly available datasets.

Method

Machine learning techniques modeled stigmatization expressed in 31,150 AD-related tweets collected via Twitter's search API based on 9 AD-related keywords. Two researchers manually coded 311 random tweets on 6 dimensions. This input from 1% of the dataset was used to train a classifier against the tweet text and code the remaining 99% of the dataset.

Results

Our automated process identified that 21.13% of the AD-related tweets used AD-related keywords to perpetuate public stigma, which could impact stereotypes and negative expectations for individuals with the disease and increase "excess disability".

Discussion

This technique could be applied to questions in social gerontology related to how social media outlets reflect and shape attitudes bearing on other developmental outcomes. Recommendations for the collection and analysis of large Twitter datasets are discussed.