Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China.

Different scenarios of precipitation, that lead to such phenomena as droughts and floods are influenced by concurrent multiple teleconnection factors. However, the multivariate relationship between precipitation indices and teleconnection factors, including large-scale atmospheric circulations and sea surface temperature signals in China, is rarely explored. Understanding this relationship is crucial for drought early warning systems and effective response strategies.

Meteorological drought migration characteristics based on an improved spatiotemporal structure approach in the Loess Plateau of China.

The development of drought has spatial and temporal synchronization. Previous studies usually explore the spatial and temporal evolution of drought separately. Moreover, existing approaches are based on a fixed overlapping area and do not consider the variable drought cluster area during development.

The negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics.

There are complex bidirectional feedback relationships among different types of droughts (e.g., meteorological and agricultural droughts).

Precipitation and vegetation transpiration variations dominate the dynamics of agricultural drought characteristics in China.

Agricultural drought posing a significant threat to agricultural production is subject to the complex influence of ocean, terrestrial and meteorological multi-factors. Nevertheless, which factor dominating the dynamics of agricultural drought characteristics and their dynamic impact remain equivocal. To address this knowledge gap, we used ERA5 soil moisture to calculate the standardized soil moisture index (SSI) to characterize agricultural drought.

Synergistic effect of drought and rainfall events of different patterns on watershed systems.

The increase in extreme climate events such as flooding and droughts predicted by the general circulation models (GCMs) is expected to significantly affect hydrological processes, erosive dynamics, and their associated nonpoint source (NPS) pollution, resulting in a major challenge to water availability for human life and ecosystems. Using the Hydrological Simulation Program-Fortran model, we evaluated the synergistic effects of droughts and rainfall events on hydrology and water quality in an upstream catchment of the Miyun Reservoir based on the outputs of five GCMs. It showed substantial increases in air temperature, precipitation intensity, frequency of heavy rains and rainstorms, and drought duration, as well as sediment and nutrient loads in the RCP 8.

Varying response of vegetation to sea ice dynamics over the Arctic.

Recent reduction of sea ice may have contributed to vegetation growth over the Arctic through albedo feedback effects to atmospheric warming. Understanding the varying response of vegetation to sea ice dynamics is critical for predicting future climate change over the Arctic and middle-high latitudes. Instead of looking at the direct response characteristics, we perform a systematic analysis of the time-lag and time-cumulation responses of vegetation to sea ice dynamics, using a long-term Arctic Normalized Difference Vegetation Index (NDVI) dataset and three sea ice indices (sea ice concentration (SIC), sea ice area (SIA) and sea ice extent (SIE)) from 1982 to 2015.

Where is the Planetary Boundary for freshwater being exceeded because of livestock farming?

Livestock production has significant impacts on the environment, including due to the use of water. In this study, we provide a spatially explicit estimation of livestock blue water use, by analyzing feed crop water use and livestock drinking water. For the past four decades, livestock water use has increased from 145 km/year in 1971 to 270 km/year in 2012 with an increasing trend of 1.

Time-scale dependent mechanism of atmospheric CO concentration drivers of watershed water-energy balance.

The elevated atmospheric carbon dioxide concentration (CO), as a key variable linking human activities and climate change, seriously affects the watershed hydrological processes. However, whether and how atmospheric CO influences the watershed water-energy balance dynamics at multiple time scales have not been revealed. Based on long-term hydrometeorological data, the variation of non-stationary parameter n series in the Choudhury's equation in the mainstream of the Wei River Basin (WRB), the Jing River Basin (JRB) and Beiluo River Basin (BLRB), three typical Loess Plateau regions in China, was examined.

Predicting spatial and temporal variability in crop yields: an inter-comparison of machine learning, regression and process-based models.

Pervious assessments of crop yield response to climate change are mainly aided with either process-based models or statistical models, with a focus on predicting the changes in average yields, whilst there is growing interest in yield variability and extremes. In this study, we simulate US maize yield using process-based models, traditional regression model and a machine-learning algorithm, and importantly, identify the weakness and strength of each method in simulating the average, variability and extremes of maize yield across the country. We show that both regression and machine learning models can well reproduce the observed pattern of yield averages, while large bias is found for process-based crop models even fed with harmonized parameters.

Watershed water-energy balance dynamics and their association with diverse influencing factors at multiple time scales.

The Budyko parameter, which controls the shape of Budyko curve, represents the superimposed impact of various periodic factors (including climatic factors, catchment characteristics, large-scale climate patterns, solar activity and anthropogenic activity) on the watershed water-energy balance dynamics. However, this superimposition is not conducive to identifying the drivers of Budyko parameter dynamics at different time scales, and thus affects parameter estimation. Here we obtain the Budyko parameter ω in the Fu's equation (one form of the Budyko framework) for the Wei River Basin (WRB), and then adopt the Empirical Mode Decomposition method to reveal the relationships between factors and ω series at multiple time scales by considering the interplay among different influencing factors.

Propagation thresholds of meteorological drought for triggering hydrological drought at various levels.

What the extent of meteorological drought could trigger the corresponding hydrological drought with different levels? This question is an important topic in the field of drought propagation, which however has not been resolved. Therefore, a novel model based on a Bayesian network was proposed to address this issue in this study. In this model, the drought pooling and excluding methods were applied to eliminate minor drought events.

Long-term spatiotemporal variation of drought patterns over the Greater Horn of Africa.

Understanding historical patterns of changes in drought is essential for drought adaptation and mitigation. While the negative impacts of drought in the Greater Horn of Africa (GHA) have attracted increasing attention, a comprehensive and long-term spatiotemporal assessment of drought is still lacking. Here, we provided a comprehensive spatiotemporal drought pattern analysis during the period of 1964-2015 over the GHA.

Can We Use Satellite-Based FAPAR to Detect Drought?

Drought in Australia has widespread impacts on agriculture and ecosystems. Satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has great potential to monitor and assess drought impacts on vegetation greenness and health. Various FAPAR products based on satellite observations have been generated and made available to the public.

Assessing the non-stationarity of low flows and their scale-dependent relationships with climate and human forcing.

It is necessary to assess the non-stationarity of a hydrological series under changing environments. This study aimed to determine the validity of the stationarity of low flow series in terms of trends and possible change points, as well as the time-scale that is responsible for the production of trends and change points in low flow series. Further, we investigated how climatic variables affect low flow variations by studying their scale-dependent relationships.

Recent changes in county-level maize production in the United States: Spatial-temporal patterns, climatic drivers and the implications for crop modelling.

Despite the fact that it is the total crop production that shapes future food supply rather than one of its single component, previous studies have mainly focused on the changes in crop yield. It is possible that recent gains in crop production are mainly due to improvement of yield rather than growth of harvest area. However, it remains unclear about the geographical patterns of their relative contributions at fine scales and the possible mechanisms.

Comparison of urbanization and climate change impacts on urban flood volumes: Importance of urban planning and drainage adaptation.

Understanding the drivers behind urban floods is critical for reducing its devastating impacts to human and society. This study investigates the impacts of recent urban development on hydrological runoff and urban flood volumes in a major city located in northern China, and compares the urbanization impacts with the effects induced by climate change under two representative concentration pathways (RCPs 2.6 and 8.

Crop yield sensitivity of global major agricultural countries to droughts and the projected changes in the future.

Understanding the potential drought impacts on agricultural production is critical for ensuring global food security. Instead of providing a deterministic estimate, this study investigates the likelihood of yield loss of wheat, maize, rice and soybeans in response to droughts of various intensities in the 10 largest producing countries. We use crop-country specific standardized precipitation index (SPI) and census yield data for 1961-2016 to build a probabilistic modeling framework for estimating yield loss risk under a moderate (-1.

Keeping global warming within 1.5 °C reduces future risk of yield loss in the United States: A probabilistic modeling approach.

This study assess the possible outcomes of yield changes in the United States which is responsible for 40% of global maize supply under 1.5 °C and 2 °C global warming scenarios. Instead of providing deterministic estimates, this study introduces a probability-based approach that allow for examination of the associated probability of each outcome, which has great implications for decision-makings.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences.

Recent changes in county-level corn yield variability in the United States from observations and crop models.

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors.

Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability.

Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950-1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage.

Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980-2010.

Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors.

Airborne observations reveal elevational gradient in tropical forest isoprene emissions.

Isoprene dominates global non-methane volatile organic compound emissions, and impacts tropospheric chemistry by influencing oxidants and aerosols. Isoprene emission rates vary over several orders of magnitude for different plants, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft eddy covariance measurements over the Amazonian forest.

Crop yield response to climate change varies with crop spatial distribution pattern.

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States.