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  1. Abstract

    Past studies based on univariate scaling analyses at the weather time scale documented a negative scaling of extreme precipitation intensity (EPI), which prevents EPI extrapolation from past climate. Here we present a bivariate scaling analysis and show that, contrary to the univariate scaling results, EPI monotonically increases with temperature and shows no negative scaling when controlled for saturation deficit. The observed EPI‐temperature relationship in saturated atmosphere is surprisingly similar among different regions and closely follows the Clausius‐Clapeyron scaling; climate models produce greater regional dependence of the scaling relationship with a wide range of scaling rate. For extratropical regions, the model‐simulated EPI‐temperature relationship under saturation shows a past‐to‐future continuity, which could potentially support extrapolation to a warmer climate. The scaling at saturation bridges the EPI‐temperature relationship between weather and climate time scales and may enable potential prediction of future precipitation extremes via extrapolation from past observations.

     
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  2. Flash drought often leads to devastating effects in multiple sectors and presents a unique challenge for drought early warning due to its sudden onset and rapid intensification. Existing drought monitoring and early warning systems are based on various hydrometeorological variables reaching thresholds of unusually low water content. Here, we propose a flash drought early warning approach based on spaceborne measurements of solar-induced chlorophyll fluorescence (SIF), a proxy of photosynthesis that captures plant response to multiple environmental stressors. Instead of negative SIF anomalies, we focus on the subseasonal trajectory of SIF and consider slower-than-usual increase or faster-than-usual decrease of SIF as an early warning for flash drought onset. To quantify the deviation of SIF trajectory from the climatological norm, we adopt existing formulas for a rapid change index (RCI) and apply the RCI analysis to spatially downscaled 8-d SIF data from GOME-2 during 2007–2018. Using two well-known flash drought events identified by the operational US Drought Monitor (in 2012 and 2017), we show that SIF RCI can produce strong predictive signals of flash drought onset with a lead time of 2 wk to 2 mo and can also predict drought recovery with several weeks of lead time. While SIF RCI shows great early warning potential, its magnitude diminishes after drought onset and therefore cannot reflect the current drought intensity. With its long lead time and direct relevance for agriculture, SIF RCI can support a global early warning system for flash drought and is especially useful over regions with sparse hydrometeorological data. 
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  3. Abstract Although the intensity of extreme precipitation is predicted to increase with climate warming, at the weather scale precipitation extremes over most of the globe decrease when temperature exceeds a certain threshold, and the spatial extent of this negative scaling is projected to increase as the climate warms. The nature and cause of the negative scaling at high temperature and its implications remain poorly understood. Based on sub-daily data from observations, reanalysis data, and output from a coarse-resolution (∼200 km) global model and a fine-resolution (4 km) convection-permitting regional model, we show that the negative scaling is primarily a reflection of high temperature suppressing precipitation over land and storm-induced temperature variation over the ocean. We further identify the high temperature-induced increase of saturation deficit as a critical condition for the negative scaling of extreme precipitation over land. Large saturation deficit reduces precipitation intensity by slowing down the convective updraft condensation rate and accelerating condensate evaporation. The heat-induced suppression of precipitation, both for its mean and extremes, provides one mechanism for the co-occurrence of drought and heatwaves. As the saturation deficit over land is expected to increase in a warmer climate, our results imply a growing prevalence of negative scaling, potentially increasing the frequency of compound drought and heat events. Understanding the physical mechanisms underlying the negative scaling of precipitation at high temperature is, therefore, essential for assessing future risks of extreme events, including not only flood due to extreme precipitation but also drought and heatwaves. 
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  4. Abstract This study assesses the ecohydrological effects of recent meteorological droughts in tropical South America based on multiple sources of data, and investigates the possible mechanisms underlying the drought response and recovery of different ecohydrological systems. Soil drought response and recovery lag behind the meteorological drought, with delays longer in the dry region (Nordeste) than in the wet region (Amazonia), and longer in deep soil than in shallow soil. Evapotranspiration (ET) and vegetation in Nordeste are limited by water under normal conditions and decrease promptly in response to the onset of shallow soil drought. In most of the Amazon where water is normally abundant, ET and vegetation indices follow an increase-then-decrease pattern, increase at the drought onset due to increased sunshine and decrease when the drought is severe enough to cause a shift from an energy-limited regime to a water-limited regime. After the demise of meteorological droughts, ET and vegetation rapidly recover in Nordeste with the replenishment of shallow soil moisture (SM), but take longer to recover in southern Amazon due to their dependence on deep SM storage. Following severe droughts, the negative anomalies of ET and vegetation indices in southern Amazon tend to persist well beyond the end of soil drought, indicating drought-induced forest mortality that is slow to recover from. Findings from this study may have implications on the possibility of a future forest dieback as drought is projected to become more frequent and more severe in a warmer climate. 
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  5. Abstract The relationship between extreme precipitation intensity and temperature has been comprehensively studied over different regions worldwide. However, the effect of temperature on the spatiotemporal organization of precipitation, which can have a significant impact on precipitation intensity, has not been adequately studied or understood. In this study, we propose a novel approach to quantifying the spatial and temporal concentration of precipitation at the event level and study how the concentration varies with temperature. The results based on rain gauge data from 843 stations in the Ganzhou county, a humid region in south China, show that rain events tend to be more concentrated both temporally and spatially at higher temperature, and this increase in concentration qualitatively holds for events of different precipitation amounts and durations. The effects of temperature on precipitation organization in space and in time differ at high temperatures. The temporal concentration increases with temperature up to a threshold (approximately 24°C) beyond which it plateaus, whereas the spatial concentration keeps rising with temperature. More concentrated precipitation, in addition to a projected increase of extreme precipitation, would intensify flooding in a warming world, causing more detrimental effects. 
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  6. null (Ed.)
    Abstract This study investigates the potential effects of historical deforestation in South America using a regional climate model driven with reanalysis data. Two different sources of data were used to quantify deforestation during the 1980s to 2010s, leading to two scenarios of forest loss: smaller but spatially continuous in scenario 1 and larger but spatially scattered in scenario 2. The model simulates a generally warmer and drier local climate following deforestation. Vegetation canopy becomes warmer due to reduced canopy evapotranspiration, and ground becomes warmer due to more radiation reaching the ground. The warming signal for surface air is weaker than for ground and vegetation, likely due to reduced surface roughness suppressing the sensible heat flux. For surface air over deforested areas, the warming signal is stronger for the nighttime minimum temperature and weaker or even becomes a cooling signal for the daytime maximum temperature, due to the strong radiative effects of albedo at midday, which reduces the diurnal amplitude of temperature. The drying signals over deforested areas include lower atmospheric humidity, less precipitation, and drier soil. The model identifies the La Plata basin as a region remotely influenced by deforestation, where a simulated increase of precipitation leads to wetter soil, higher ET, and a strong surface cooling. Over both deforested and remote areas, the deforestation-induced surface climate changes are much stronger in scenario 2 than scenario 1; coarse-resolution data and models (such as in scenario 1) cannot represent the detailed spatial structure of deforestation and underestimate its impact on local and regional climates. 
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