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Chlorophyll is one of the most abundant pigments found in microalgae, which can affect the stability of its byproducts. The conventional bleaching procedure involves an adsorption approach, such as with clay and activated carbon, to remove chlorophyll from the oil, but this can cause disposal problems. Therefore, the present study proposed the novel pretreatment of biomass using sodium chlorite (NaClO2) to remove chlorophyll from the microalgae prior to lipid extraction. The chlorophyll reduction and lipid loss rates were evaluated. The findings revealed that approximately 70% of the chlorophyll in biomass was removed using NaClO2and chlorophyll extraction solvents. The oil yielded by chlorophyll-reduced biomass was orange-green color, and extracted oil was very fluidic. In the treated biomass, the proportion of the saturated fatty acids reduced, whereas the unsaturated fatty acids level increased. Different treated biomass demonstrated a varied lipid loss rate, with 13% being the lowest for DMSO-NaClO2. The biochemical composition including carbohydrate and proteins in treated biomass was not significantly different as compared to untreated biomass. In summary, the findings provide a useful pathway to remove chlorophyll that can serve as an alternative to the bleaching of microalgae oil in producing high-value lipid-based bioproducts.

To address the deficient activity of TrCel5A in naturally secreted cellulase preparation, this study used the GAP promoter to induce constitutive expression of Trichoderma reesei TrCel5A in Pichia pastoris. A recombinant TrCel5A was screened out after gene optimization, synthesis, and expression. The biochemical and enzymatic properties of the new recombinant were characterized. As a result, optimization of shake-flask fermentation of the recombinant was obtained at 28 °C, 2% inoculum volume, an initial pH of 6.0, as well as glycerol and Tween-80 additions of 30 g/L and 6 g/L, respectively. Under the above-optimized conditions, the recombinant produced 14.8 U/mL of the enzyme activity at 96 h of fermentation. To further enhance enzyme production, pilot-scale cultivation was evaluated using 5-L bioreactors. Using high-cell-density fermentation, the recombinant strain increased enzyme activity to 130.4 U/ml and protein content to 2.49 g/L. In addition, the kinetic factors, including Kmand Vmaxvalues for TrCel5A, were detected to be 5.1 mg/mL and 265.9 μmol/(min.mg), respectively. Thus, TrCel5A was effectively expressed in P.pastorisunder the GAP promoter, and it demonstrated its potential in commercially relevant enzyme hydrolysis of lignocellulosic biomass.

Vegetation responses to rising atmospheric CO2levels can significantly affect water availability (defined as precipitation minus evapotranspiration (ET)). While this effect has long been recognized and assessed for the mean state, its influence on interannual variability, which is more closely associated with extreme events, has yet to be comprehensively quantified. In this study, our primary focus is to evaluate the impacts of ETby plant physiology (denoted as ETPhy) on the mean and interannual variability of water availability under elevated CO2using multiple CO2sensitivity experiments from the coupled model intercomparison project phase 6. We show that the contribution of vegetation physiological effects to the mean water availability varies among regions, while it consistently contributes to variability by about 33%. Considering CO2physiological effects alone, ETPhyexerts a more significant influence on the mean state than on variability, particularly in humid regions. Consequently, ETPhycontributes less than 5% to the variability of water availability in humid regions under rising CO2, whereas it accounts for about 20% of the mean state. This distinction could be attributed to the different mechanisms governing the mean and variability of ETPhy. Specifically, evaporation from CO2physiological forcing is the most critical contributor to the variability of ETPhyin most regions while showing minimal impacts on the mean state. Our findings identify the divergent effects of ETPhyon the mean state and interannual variability of water availability under elevated CO2, as important in future climate projections. Rising atmospheric CO2concentrations impacts on vegetation physiological processes are expected to change the evapotranspiration (ET) by plant physiology (denoted as ETPhy), allowing for altering the mean and the interannual variability of water availability (defined as precipitation minus ET). Using an ensemble of Earth system model simulations, this study reveals that the impacts of CO2physiological effects on the mean of water availability are region‐specific, but with a nearly consistent contribution to its interannual variability. Combined with the impact of ETPhyon the mean and variability of water availability resulting from CO2physiological forcing, ETPhytypically contributes less than 5% to the variability of water availability in humid regions under rising CO2, whereas it accounts for about 20% of the mean state. This discrepancy could arise from the different mechanisms governing the mean and variability of ETPhy. These results underscore the importance of accounting for the effects of ETPhyin response to increasing CO2in altering the mean and the interannual variability of regional water resources. The effects of CO2vegetation responses contribute variably in space to mean annual water availability but uniformly to variabilityThe evapotranspiration (ET) from CO2physiological forcing (ETPhy) shows more impacts on the mean of water availability than its variabilityThe evaporation from CO2physiological forcing plays an important role in the variability of ETPhybut has weak effects on the mean The effects of CO2vegetation responses contribute variably in space to mean annual water availability but uniformly to variability The evapotranspiration (ET) from CO2physiological forcing (ETPhy) shows more impacts on the mean of water availability than its variability The evaporation from CO2physiological forcing plays an important role in the variability of ETPhybut has weak effects on the mean

Graphical abstract:

Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei (BTH) region of China were analyzed using the Palmer Drought Severity index (PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions (EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOFmodes were analyzed. According to the first leading EOFmode (48.5%), the temporal variability (Principal Components, PC1) was highly positively correlated with annual series of PDSI(r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale (r=0.71, p<0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming (P1: 1961–1989 and P2: 1990–2013), we find that temperature sensitivity in the P2 was three times more than that in the P1.

Comprehending the correlation between alterations in human‐flood distance and flood fatalities (as well as displacements) is pivotal for formulating effective human adaptive strategies in response to floods. However, this relationship remains inadequately explored in existing global analyses. To address this gap, we examine 910 flood events occurring from 2000 to 2018, resulting in significant numbers of fatalities and displacements. We find that in 53% of countries, humans tend to distance from floods, particularly in the Middle East. Such distancing greatly mitigates flood fatalities and displacements. Simultaneously, in areas with increased flood protection level (FPL), humans are less likely to move away from floods. Furthermore, FPL and human‐flood distance have decreased in regions affected by ice jam‐ and hurricane‐induced floods from 2000 to 2018. Notably, regions with human‐flood distance slightly below the average for a given flood type experience more severe flood fatalities. People have developed effective ways (i.e., distancing from flood and increasing flood protection level) to adapt and minimize the impact of catastrophic floods on exposed populations. However, the relationship between these behaviors and flood fatalities (as well as displacements) is not well understood on a global scale. To address this knowledge gap, we study 910 flood events that occurred between 2000 and 2018, leading to significant fatalities and displacements. We find that in 53% of countries, people tend to move away from flood‐affected areas, especially in the Middle East. This distancing behavior greatly reduces the number of fatalities and displaced individuals caused by floods. Additionally, in areas with higher flood protection level, people are less likely to relocate away from floods. Over the studied period, both flood protection levels and the distance between humans and flood‐prone areas have decreased in regions affected by ice jam‐ and hurricane‐induced floods. Importantly, regions where the distance between humans and floods is slightly below the average for a given flood type experience more severe flood fatalities. These findings could help improve the efficiency of flood control management and the adoption of adaptive policies. 53% of countries witnessed humans distancing themselves from floods between 2000 and 2018, especially those in the Middle EastHumans distancing from the floods leads to a substantial reduction in both flood fatalities and flood displaced populationHumans residing in regions with a high flood protection level tend not to move away from the flood 53% of countries witnessed humans distancing themselves from floods between 2000 and 2018, especially those in the Middle East Humans distancing from the floods leads to a substantial reduction in both flood fatalities and flood displaced population Humans residing in regions with a high flood protection level tend not to move away from the flood

Based on the large ensembles of the half a degree additional warming, prognosis, and projected impacts historical, +1.5 and +2 °C experiments, we quantify changes in the magnitude of water availability (i.e., precipitation minus actual evapotranspiration; a function of monthly precipitation flux, latent heat flux, and surface air temperature) below normal conditions (less than median, e.g., 20th percentile water availability). We found that, relative to the historical experiment, water availability below normal conditions of the +1.5 and +2 °C experiments would decrease in the midlatitudes and the tropics, indicating that hydrological drought is likely to increase in warmer worlds. These cause more (less) people in East Asia, Central Europe, South Asia, and Southeast Asia (West Africa and Alaska/Northwest Canada) to be exposed to water shortage. Stabilizing warming at 1.5 °C instead of 2 °C would limit population impact in most of the regions, less effective in Alaska/Northwest Canada, Southeast Asia, and Amazon. Globally, this reduced population impact is ~117 million people. This study emerges from the lack of scientific investigations to inform climate policy about differences between two global warming targets (i.e., 1.5 and 2 °C) for the “Intergovernmental Panel on Climate Change Special Report on Global Warming of 1.5°C.” We seek to understand the following: How would water availability below normal conditions (the drier end of hydrological extremes) change at these targets? How would they affect the water shortage of human society? Could we limit the impact by stabilizing the global warming at 1.5 °C instead of 2 °C? To address these questions, we employ the HAPPI (half a degree additional warming, prognosis, and projected impacts) experiments, explicitly designed to differentiate impacts between these targets. Relative to the historical period, future water availability below normal conditions (less than median, e.g., 20th percentile or lower) would decrease in the midlatitudes and the tropics; the globe and most of the regions would endure water shortages. Relative to the 2 °C warming target, stabilizing temperature increase at 1.5 °C would constrain adverse impact on people suffering water shortages in most of the regions (particularly Central Europe, East Africa, East Asia, South Asia, and West Africa) but ineffective in Alaska/Northwest Canada, Southeast Asia, and Amazon. A global sum of this reduced risk is ~117 million people. The first evaluation of global freshwater availability below normal conditions in +1.5 versus +2 °C worlds is conductedRelative to the historical period, future water availability below normal conditions would decrease in the midlatitudes and the tropicsRisk of freshwater shortages in a +1.5 °C world is less than a +2 °C world

Although gridded air temperature data sets share much of the same observations, different rates of warming can be detected due to different approaches employed for considering elevation signatures in the interpolation processes. Here we examine the influence of varying spatiotemporal distribution of sites on surface warming in the long‐term trend and over the recent warming hiatus period in China during 1951–2015. A suspicious cooling trend in raw interpolated air temperature time series is found in the 1950s, and 91% of which can be explained by the artificial elevation changes introduced by the interpolation process. We define the regression slope relating temperature difference and elevation difference as the bulk lapse rate of −5.6°C/km, which tends to be higher (−8.7°C/km) in dry regions but lower (−2.4°C/km) in wet regions. Compared to independent experimental observations, we find that the estimated monthly bulk lapse rates work well to capture the elevation bias. Significant improvement can be achieved in adjusting the interpolated original temperature time series using the bulk lapse rate. The results highlight that the developed bulk lapse rate is useful to account for the elevation signature in the interpolation of site‐based surface air temperature to gridded data sets and is necessary for avoiding elevation bias in climate change studies. We find elevation signature in surface temperature time series caused by varying spatiotemporal data coverageWe develop a simple and physically robust approach to make adjustments on original surface temperature time seriesThe artifact cooling trend in 1950s caused by elevation change signature has profound impact on the trend

Streamflow prediction in ungauged basins (PUB) is challenging, and Long Short‐Term Memory (LSTM) is widely used to for such predictions, owing to its excellent migration performance. Traditional LSTM forced by meteorological data and catchment attribute data barely highlight the optimum data integration strategy for LSTM and its migration from data‐rich basins to ungauged ones. In this study, we experimented with 1,897 global catchments and found that LSTM‐corrected Global Hydrological Models (GHMs) outperformed uncorrected GHMs, improving the median Nash‐Sutcliff efficiency (NSE) from 0.03 to 0.66. Notably, there was a large gap between traditional LSTM modeling in ungauged basins and autoregressive modeling in data‐rich basins, and GHM‐forced LSTM were an effective way to close this gap in ungauged basins. The spatial heterogeneity of the performance of GHM‐forced LSTM was mainly influenced by three metrics (dryness, the leaf area index and latitude), which described the hydrological similarity among catchments. Weaker hydrological similarity among continental catchments results in larger variability in GHM‐forced LSTM, with the best performance in Siberia (NSE, 0.54) and the worst in North America (NSE, 0.10). However, the migration performance of GHM‐forced LSTM was significantly improved (NSE, 0.63) in ungauged basins when hydrological similarity was considered. This study stressed the advantages of GHM‐forced LSTM and due significance should be attached to hydrological similarities among catchments to improve hydrological prediction in ungauged catchments. Compared to Global Hydrological Models, GHM‐forced LSTM improved the median Nash‐Sutcliff efficiency (NSE) from 0.03 to 0.66Three metrics (dryness, the leaf area index, and latitude) helped to quickly identify hydrological similarities between catchmentsGHM‐forced LSTM reached a high NSE value of 0.63 for prediction in ungauged basins when hydrological similarity is considered Compared to Global Hydrological Models, GHM‐forced LSTM improved the median Nash‐Sutcliff efficiency (NSE) from 0.03 to 0.66 Three metrics (dryness, the leaf area index, and latitude) helped to quickly identify hydrological similarities between catchments GHM‐forced LSTM reached a high NSE value of 0.63 for prediction in ungauged basins when hydrological similarity is considered

Although global variation in actual evapotranspiration has been widely investigated, it remains unclear how its two major components, transpiration and soil evaporation, are driven by climate drivers across global land surface. This paper uses a well‐validated, process‐based model that estimates transpiration and soil evaporation, and for the first time investigates and quantifies how the main global drivers, associated to vegetation process and the water and energy cycle, drive the spatiotemporal variation of the two components. The results show that transpiration and soil evaporation dominate the variance of actual evapotranspiration in wet and dry regions, respectively. Dry southern hemisphere from 13°S to 27°S is highlighted since it contributes to 21% global soil evaporation variance, with only 11% global land area. In wet regions, particularly in the humid tropics, there are strong correlations between transpiration, actual evapotranspiration, and potential evapotranspiration, with precipitation playing a relatively minor role, and available radiative energy is the major contributor to the interannual variability in transpiration and actual evapotranspiration in Amazonia. Conversely in dry regions, there are strong correlations between soil evaporation, actual evapotranspiration, and precipitation. Our findings highlight that ecohydrological links are highly related to climate regimes, and the small region such as Australia has important contribution to interannual variation in global soil evaporation and evapotranspiration, and anthropogenic activities strongly influence the variances in irrigation regions. This is the first study investigating how global drivers drive spatiotemporal variation of soil evaporation and transpirationTranspiration and soil evaporation dominate the variance of actual evapotranspiration in wet and dry regions, respectivelyEcohydrological links are highly related to climate regimes, and the small region such as Australia has important contribution

A binary deep eutectic solvent consisting of choline chloride and glycerol (ChCl/Gly) is proven to be ineffective in lignocellulosic pretreatment, and arbitrarily screening coordination agents makes it difficult to directionally construct a valid solvent. This study investigated the designable diversity of ternary ChCl/Gly coordinated with various metal-salts by elucidating solvent properties and reaction characteristics. Alkaline/acidic strengths and hydrogen-bonding forces were key factors for component fractionation. Pretreatment performance was typically poor for solvents with few acidic sites and active protons (i.e.,ChCl/Gly-KCl and MgCl2), as well as those with close proximity of H-bond donor and acceptor abilities (ChCl/Gly-ZnCl2). By contrast, strong alkaline ChCl/Gly-K2CO3could achieved 72 % of delignification with a remarkable holo-cellulose preservation (70.8–80.9 %). Delignification underwent an independent rate-control of solvent diffusion and surface reaction with an endothermic nature (17.1 kJ/mol of ΔHand 20.3 kJ/mol of apparent activation energy). High temperature was beneficial for mitigating diffusion constraint at the initial pretreatment stage, maximally increasing the reaction rate by 7.7-fold. Moreover, Lewis acidic ChCl/Gly-FeCl3(or AlCl3) removed 76–84.4 % of hemicellulose and 47.6–61.9 % of lignin while significantly deconstructing the aryl-ether bonds and β-O-4 linkages. But for acidic ChCl/Gly solvents, biomass dissolution was inconformity with the independent diffusion/reaction-controlling process, owing to the excessive hemicellulose degradation and hydrolytic by-product formation (maximally 91 g/kg xylose and 4 g/kg furans). Based on the lignin structural characterization, the potential reaction mechanism related to solvent properties was proposed to develop efficient ternary coordinated deep eutectic solvents.

Waste generation from food manufacturing facilities poses a serious hazard like environmental degradation, water pollution, and land pollution due to its high nutrient composition. Specifically, solid waste (powder) disposal requires additional energy sources in terms of scientific treatment, structured collection, and disposal packaging according to the safety regulation. Thus, this research discusses the viewpoint of integrating food processing waste as an organic carbon source with BG-11 medium for Chlorella vulgaris(FSP-E) growth. The food processing waste powders investigated in this study were obtained from milk, and biscuit manufacturing facilities. The culture medium was modified by combining both BG-11 and food processing waste powders to identify the optimal algal growth and biochemical content. Compared to the microalgae grown in BG-11 alone (IBG), the combination of biscuit waste and IBG produced higher biomass concentration (44%), with increased lipid (11%), protein (20%), and carbohydrate (57%) contents. Chlorella vulgariswas able to uptake nutrients from the culture medium with combination of food processing waste and IBG thus enhancing its growth. The results obtained also indicate that an integrated culture system using food processing waste and synthetic sources can generate energy out of waste by improving the bio-composition of the microalgae biomass.

Hydroclimatic process in the Yarlung Tsangpo River (YTR) basin, a sensitive area to climate change, is obviously changing during recent years, but there has limited understanding about it. In this study, we investigated the spatiotemporal variation of precipitation over last four decades in the basin and the impact thereon of the changing Indian summer monsoon at interannual and decadal time scales. All the precipitation series have similar scaling behavior, reflecting similar climatic regime throughout the basin. However, the effect of the Indian monsoon strengthens from the downstream to upstream, causing spatial variability in the seasonal distribution of precipitation, and on this basis, the YTR basin is roughly divided into three regions: east, middle, and west. Both the occurrence times and magnitude of precipitation extremes, ranging 25–50 mm/d, are exhibiting downward trends over the last four decades, which bodes well for water disaster controls in the basin. The Indian summer monsoon index, as an intensity indicator for the Indian summer monsoon, shows a positive relationship with the summer precipitation in the YTR basin. Periodic variability of the Indian monsoon determines the interannual nonstationary fluctuations of precipitation. Especially, the weakening effect of the Indian summer monsoon has caused an obvious decrease in precipitation over the rainy season after 1998. If the Indian summer monsoon keeps weakening, the precipitation would decrease and potentially water shortage would become more severe in the basin. Effective adaptation strategy should therefore be developed proactively to handle the unfavorable water situation, which is likely to occur in the future. The effect of the Indian summer monsoon strengthens from downstream to upstream in the YTR basinPeriodic variability of the Indian summer monsoon controls interannual nonstationary variation of precipitation in the YTR basinThe weakening Indian summer monsoon caused precipitation decrease in the YTR basin during the recent two decades

Here we assess estimates of atmospheric evaporative demand over China in 12 state‐of‐the‐art global climate models (GCMs) against observed D20 pan evaporation (Epan) over the period of 1961–2000. To do that, we use an energy‐relevant and physical‐based approach, namely, PenPan model, to comprehensively evaluate GCM performance with respect to their ability to simulate annual, seasonal, and monthly statistics of Epan(and its radiative and aerodynamic components, Ep,Rand Ep,A). The results indicated that most GCMs generally captured the spatial pattern and seasonal cycle of Epan, Ep,R, and Ep,A. However, regional means of annual and monthly Epan, Ep,R, and Ep,Awere underestimated by most GCMs mainly due to negatively biased surface air temperature (Ta) and vapor pressure deficit (vpd) outputted/simulated by the GCMs. Overall, the discrepancies among GCMs in estimating the regional statistics (regional means and seasonal cycles) of Ep,Awere relatively larger than that of Ep,R, which indicates considerable uncertainties in the calculation of the aerodynamic component of evaporation based on the GCM outputs. Moreover, a few GCMs captured negative trends of regional mean annual and seasonal Epan, Ep,R, and Ep,Awell over the period of 1961– 2000, but most showed positive trends. The underestimation of net radiation (Rn) and overestimation of wind speed at 2 m (u2) in most GCMs may, to some extent, accentuate/compensate the negative biases in GCM‐estimated annual and seasonal Epan, Ep,R, and Ep,A. The results demonstrate the importance of incorporating observation of pan evaporation and well‐validated PenPan model to evaluate GCM performance on atmospheric evaporative demand that is relevant to projections of future drought and regional water‐energy budgets. First comprehensive assessment of GCM‐estimated Epanover China using observed D20 pan evaporationMost GCMs used generally captured the spatial pattern and seasonal cycle of observed EpanNegatively biased Taand vpd from most GCMs contributed more to the underestimated Epan

The Palmer Drought Severity Index (PDSI) can lead to controversial results in assessing droughts responding to global warming. Here we assess recent changes in the droughts over China (1961–2013) using the PDSI with two different estimates, i.e., the Thornthwaite (PDSI_th) and Penman‐Monteith (PDSI_pm) approaches. We found that droughts have become more severe in the PDSI_thbut slightly lessened in the PDSI_pmestimate. To quantify and interpret the different responses in the PDSI_thand PDSI_pm, we designed numerical experiments and found that drying trend of the PDSI_thresponding to the warming alone is 3.4 times higher than that of the PDSI_pm, and the latter was further compensated by decreases in wind speed and solar radiation causing the slightly wetting in the PDSI_pm. Interestingly, we found that interbasin difference in the PDSI_thand PDSI_pmresponses to the warming alone tends to be larger in warmer basins, exponentially depending on mean temperature. Droughts have become more severe in the PDSI_thbut slightly lessened in the PDSI_pmestimateDrought responding to warming was compensated by decreases in wind speed and solar radiationPDSI_thresponds much more strongly to global warming than PDSI_pm

Higher temperatures are usually reported during meteorological drought and there are two prevailing interpretations for this observation. The first is that the increase in temperature (T) causes an increase in evaporation (E) that dries the environment. The second states that the decline in precipitation (P) during drought reduces the available water thereby decreasing E, and in turn the consequent reduction in evaporative cooling causes higher T. To test which of these interpretations is correct, we use climatic data (T, P) and a recently released database (CERES) that includes incoming and outgoing shortwave and longwave surface radiative fluxes to study meteorological drought at four sites (parts of Australia, US, and Brazil), using the Budyko approximation to calculate E. The results support the second interpretation at arid sites. The analysis also showed that increases in Tdue to drought have a different radiative signature from increases in Tdue to elevated CO2. Temperature increases during drought but the interpretation is disputedTemperature increase during drought is partly due to surface feedbacksRadiative signature of drought differs from a direct global warming signature

River flooding is among the costliest natural disasters with severe economic, societal, and environmental consequences. However, substantial uncertainties remain in global and regional projections of future flood conditions simulated by global climate models (GCMs) and/or global hydrological models (GHMs). Using physical models coupled with machine learning (ML), for the first time, we project changes in flood magnitudes of 2062 global river basins by constraining physical‐based streamflow simulations with observations under 1.5°C and 2°C warming scenarios identified for the Representative Concentration Pathway 8.5. We found that, during the validation period, the GHMs‐simulated flood magnitudes would improve with reduced uncertainty over the selected river basins after ML with a Long Short‐Term Memory network. Our estimation suggested that flood magnitudes would increase in many Northern Hemisphere mid‐ and high‐latitude rivers (e.g., Lena River, Amur River and Volga River) but decrease in some river basins in southern Finland and Eastern Europe in future periods (i.e., 1.5°C and 2°C warming levels). In 1.5°C and 2°C warmer worlds, the decreasing flood magnitudes in most South American rivers are associated with decreased soil moisture and increased evapotranspiration induced by warmer temperatures. Although the geographical pattern of changes in flood magnitudes for the +2°C experiment is close to that of the +1.5°C experiment, a 1.5°C warming target is more likely to reduce flood magnitudes of many river basins worldwide (e.g., in central and eastern Siberia, Alaska/Northwest Canada and South America). Changes in global flood magnitudes are projected through physical‐based modeling pipelines constrained by observationsUncertainty in flood magnitude simulations has been reduced through LSTM‐based machine learningFewer floods would occur in Siberia and low‐latitude Africa when keeping warming to 1.5°C instead of 2°C above pre‐industrial levels Changes in global flood magnitudes are projected through physical‐based modeling pipelines constrained by observations Uncertainty in flood magnitude simulations has been reduced through LSTM‐based machine learning Fewer floods would occur in Siberia and low‐latitude Africa when keeping warming to 1.5°C instead of 2°C above pre‐industrial levels

Nonrainy days have rather different hydrologic and radiative conditions than rainy days, but few investigations considered how these different conditions contribute to the observed global warming. Here, we show that global warming is considerably stronger on nonrainy days using observations from China. We find that trends in mean temperature on nonrainy days are about 0.1 ° C/10 yrhigher than on rainy days, and that about 80% of the total temperature increase is contributed by nonrainy days. The main reason is likely to be a stronger sensitivity of downwelling longwave radiation to greenhouse forcing on nonrainy days due to fewer clouds and water vapor compared with rainy days, which is not a hydrological effect but mainly a radiative effect. Our findings are consistent with the stronger mean temperature trends in drier regions and imply that the different temperature sensitivities on nonrainy and rainy days may have profound effects on natural and social systems. We find stronger temperature trends on nonrainy days compared to rainy days in observations from ChinaThe reason is likely to be the different sensitivity of downwelling longwave radiation to greenhouse gases on nonrainy and rainy daysOur findings are consistent with the stronger temperature trends in drier regions because of fewer rainy days

Snow has been widely recognized as a crucial component of water resources and is expected to be vulnerable to climate change in cold and mountainous regions. Here we projected climate change impacts on snow hydrology in the upper Yellow River (UYR) basin through a distributed biosphere hydrological model with improved snow physics, forced with Inter‐Sectoral Impact Model Intercomparison Project climate model outputs under two emission scenarios (representative concentration pathways, RCP4.5 and RCP8.5) during the period of 1996–2025. The results indicated that the climate in the UYR basin is turning warmer and wetter. In this context, more precipitation would occur as rain (snow‐to‐precipitation ratio would decrease accordingly). The total runoff generation would increase slightly with increased precipitation. The simulated snow depth and snow water equivalent would decrease by 33% and 19% per 1 °C warming under the RCP4.5. These declined rates would further enlarge under the RCP8.5. Accordingly, the multimodel ensemble mean snowmelt‐to‐runoff ratio decreases by 9% and 7% per 1 °C warming under the two emission scenarios. The projected responses of snow hydrology (e.g., snow depth, snow water equivalent, and snowmelt) to the changing climate in the UYR basin are consistent among different climate models and RCP scenarios, which would provide valuable insights for water resources management, environmental protection, and climate change adaption in high mountainous basins and their downstream regions. Snow hydrological responses to climate change were projected in the UYR basin through a climate‐land surface hydrologic modeling frameworkSnow depth and SWE in the UYR basin would decline with regional climate warming and wettingBiased ISI‐MIP‐GCMs‐outputted air temperature leads to impractical simulation of changes in snow seasonality