Sensible heat has significantly affected the global hydrological cycle over the historical period

Imprint of urbanization on snow precipitation over the continental USA

Urbanization can alter the local climate through modifications in land-atmosphere feedback. However, a continental scale evaluation of its influence on precipitation phase remains unknown. Here, we assess the difference in the likelihood of snow dominated events (SDEs) over 7,415 urban and surrounding non-urban (buffer) regions across the continental United States. Among 4,856 urban-buffer pairs that received at least five SDEs per year, 81% of urban regions are characterized by a smaller snow probability, 99% by a lower frequency of SDEs, and 57% by faster declining trends in SDEs compared to their buffer counterparts. Notably, urban (buffer) regions with lower snow probability are often characterized by higher net incoming and sensible energy fluxes as compared to buffer (urban) regions, thus highlighting the influence of land-energy feedback on precipitation phase. Results highlight a clear imprint of urbanization on precipitation phase and underscore the need to consider these influences while projecting hydro-meteorological risks.

Automatic extraction of surface water based on lightweight convolutional neural network

Automatic extraction of surface water is of great significance to the study of the global water cycle and the dynamic management of water resources. At present, the water extraction accuracy of high-resolution multi-spectral remote sensing images has been greatly improved. But it is still affected by the shadow of the mountains and the shadow of the tall buildings inside the city. The spectral information of shadow is basically consistent with the spectral information of water, so the accuracy of any traditional index extraction of water will be questioned by users. Or the user must adjust threshold parameters many times to obtain good extraction results, which is contradictory to fast and large-area remote sensing monitoring. To solve the above problems, this paper firstly introduces the thermal infrared band at the data end for pre-treatment. Then, a lightweight neural network (EDCM) combining the most advanced lightweight image classification model and semantic segmentation model is proposed, which is specially used for fast, large area and automatic water extraction. Multi-scale training of samples using lightweight convolutional networks aims to extract multi-scale context information. The newly constructed model was tested in three highly heterogeneous scenarios, and the results showed that the trained EDCM model achieved the highest accuracy in all selected test areas, reaching more than 95.28%. The EDCM model can be used for the high-precision extraction of surface water in complex areas.

River ecosystem metabolism and carbon biogeochemistry in a changing world

River networks represent the largest biogeochemical nexus between the continents, ocean and atmosphere. Our current understanding of the role of rivers in the global carbon cycle remains limited, which makes it difficult to predict how global change may alter the timing and spatial distribution of riverine carbon sequestration and greenhouse gas emissions. Here we review the state of river ecosystem metabolism research and synthesize the current best available estimates of river ecosystem metabolism. We quantify the organic and inorganic carbon flux from land to global rivers and show that their net ecosystem production and carbon dioxide emissions shift the organic to inorganic carbon balance en route from land to the coastal ocean. Furthermore, we discuss how global change may affect river ecosystem metabolism and related carbon fluxes and identify research directions that can help to develop better predictions of the effects of global change on riverine ecosystem processes. We argue that a global river observing system will play a key role in understanding river networks and their future evolution in the context of the global carbon budget.

Response of distribution patterns of two closely related species in Taxus genus to climate change since last inter-glacial

Climate change affects the species spatio-temporal distribution deeply. However, how climate affects the spatio-temporal distribution pattern of related species on the large scale remains largely unclear. Here, we selected two closely related species in Taxus genus Taxus chinensis and Taxus mairei to explore their distribution pattern. Four environmental variables were employed to simulate the distribution patterns using the optimized Maxent model. The results showed that the highly suitable area of T. chinensis and T. mairei in current period was 1.616 × 105 km2 and 3.093 × 105 km2, respectively. The distribution area of T. chinensis was smaller than that of T. mairei in different periods. Comparison of different periods shown that the distribution area of the two species was almost in stasis from LIG to the future periods. Temperature and precipitation were the main climate factors that determined the potential distribution of the two species. The centroids of T. chinensis and T. mairei were in Sichuan and Hunan provinces in current period, respectively. In the future, the centroid migration direction of the two species would shift towards northeast. Our results revealed that the average elevation distribution of T. chinensis was higher than that of T. mairei. This study sheds new insights into the habitat preference and limiting environment factors of the two related species and provides a valuable reference for the conservation of these two threatened species.

Scientific data from precipitation driver response model intercomparison project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

The Effects of Plant and Soil Characteristics on Partitioning Different Rainfalls to Soil in a Subtropical Chinese Fir Forest Ecosystem

The climate-induced changes in soil water patterns pose a serious threat to subtropical plantations. Mixed species stands have been advocated as an efficient way to enhance ecosystem stability. However, little is known about their possible impact on the soil water-holding capacity in the subtropics. In this study, we employed a stable hydrogen isotope to assess the contribution of rainfall to soil water (CRSW) in a pure Chinese fir (Cunninghamia lanceolata) plantation and in two mixtures of Chinese fir with Cinnamomum camphora or with Alnus cremastogyne after three different magnitudes of rainfall events in subtropical China. Furthermore, we used structure equation modeling (SEM) to quantify the relative importance of vegetation and soil properties on the CRSW. The results indicated that the CRSW did not differ among these three Chinese fir plantations after light rainfall, whereas the CRSW of moderate and heavy rainfall to soil water were 15.95% and 26.06% higher in Chinese fir plantation with Cinnamomum camphora, and 22.67% and 22.93% higher in Chinese fir plantation with Alnus cremastogyne than that in the pure Chinese fir plantation, respectively. SEM analysis showed that the vegetation biomass and soil properties significantly affected the CRSW following light rainfall, but the soil properties were the most important factors influencing the CRSW under moderate and heavy rainfall. Our findings demonstrate that the mixed conifer–broad-leaved plantation is a more effective strategy for improving the soil water-holding capacity than the pure conifer plantation in subtropical regions, which is conducive to coping with the frequent seasonal droughts and extreme precipitation events.

Simulation of Earth’s Outward Radiative Flux and Its Radiance in Moon-Based View

To study the Earth’s energy balance and to extend exoplanet research, the Earth’s outward radiative flux and its radiance in the Moon-based view were simulated according to the Earth–Sun–Moon geometry model, with the help of ERA5. A framework was developed to identify the angular distribution model (ADM) of Earth’s surface and its scene types, according to the surface and atmospheric data from ERA5. Our simulation shows that the specific viewing geometry controls the periodical variations in the Moon-based view radiative flux and its radiance, which reflect the orbital period of the Moon. The seasonal variations in shortwave and longwave radiative flux follow the energy balance in general, which is probably influenced by the Earth albedo. The derived global ADM would help to identify the anisotropic factor of observations at DSCOVR. Our simulations prove that Moon-based observation is a valuable source for Earth observation and that the orbital information of exoplanets could be derived from the radiance observation.

Ocean surface energy balance allows a constraint on the sensitivity of precipitation to global warming

Climate models generally predict higher precipitation in a future warmer climate. Whether the precipitation intensification occurred in response to historical warming continues to be a subject of debate. Here, using observations of the ocean surface energy balance as a hydrological constraint, we find that historical warming intensified precipitation at a rate of 0.68 ± 0.51% K⁻¹, which is slightly higher than the multi-model mean calculation for the historical climate (0.38 ± 1.18% K⁻¹). The reduction in ocean surface albedo associated with melting of sea ice is a positive contributor to the precipitation temperature sensitivity. On the other hand, the observed increase in ocean heat storage weakens the historical precipitation. In this surface energy balance framework, the incident shortwave radiation at the ocean surface and the ocean heat storage exert a dominant control on the precipitation temperature sensitivity, explaining 91% of the inter-model spread and the spread across climate scenarios in the Intergovernmental Panel on Climate Change Fifth Assessment Report.

There is some disagreement between climate models about how much precipitation changes under global warming. Here, the authors use the ocean surface energy balance to constrain the sensitivity of precipitation to historical warming and find that it is increasing by 0.68 ± 0.51% per degree warming.

Spatio-Temporal Trends of Surface Energy Budget in Tibet from Satellite Remote Sensing Observations and Reanalysis Data

Being the highest and largest land mass of the earth, the Tibetan Plateau has a strong impact on the Asian climate especially on the Asian monsoon. With high downward solar radiation, the Tibetan Plateau is a climate sensitive region and the main water source for many rivers in South and East Asia. Although many studies have analyzed energy fluxes in the Tibetan Plateau, a long-term detailed spatio-temporal variability of all energy budget parameters is not clear for understanding the dynamics of the regional climate change. In this paper, satellite remote sensing and reanalysis data are used to quantify spatio-temporal trends of energy budget parameters, net radiation, latent heat flux, and sensible heat flux over the Tibetan Plateau from 2001 to 2019. The validity of both data sources is analyzed from in situ ground measurements of the FluxNet micrometeorological tower network, which verifies that both datasets are valid and reliable. It is found that the trend of net radiation shows a slight increase. The latent heat flux increases continuously, while the sensible heat flux decreases continuously throughout the study period over the Tibetan Plateau. Varying energy fluxes in the Tibetan plateau will affect the regional hydrological cycle. Satellite LE product observation is limited to certain land covers. Thus, for larger spatial areas, reanalysis data is a more appropriate choice. Normalized difference vegetation index proves a useful indicator to explain the latent heat flux trend. Despite the reduction of sensible heat, the atmospheric temperature increases continuously resulting in the warming of the Tibetan Plateau. The opposite trend of sensible heat flux and air temperature is an interesting and explainable phenomenon. It is also concluded that the surface evaporative cooling is not the indicator of atmospheric cooling/warming. In the future, more work shall be done to explain the mechanism which involves the complete heat cycle in the Tibetan Plateau.

The Role of Samalas Mega Volcanic Eruption in European Summer Hydroclimate Change

In this study, the role of AD 1258 Samalas mega volcanic eruption in the summer hydroclimate change over Europe and the corresponding mechanisms are investigated through multi-member ensemble climate simulation experiments based on the Community Earth System Model (CESM). The results show that the CESM simulations are consistent with the reconstructed Palmer Drought Severity Index (PDSI) and the historical records of European climate. Europe experiences significant summer cooling in the first three years after the Samalas mega volcanic eruption, peaking at −3.61 °C, −4.02 °C, and −3.21 °C in year 1 over the whole Europe, Southern Europe, and Northern Europe, respectively. The summer surface air temperature (SAT, °C) changes over the European continent are mainly due to the direct weakening of shortwave solar radiation induced by volcanic aerosol. The summer precipitation over the European continent shows an obvious dipole distribution characteristic of north-south reverse phase. The precipitation increases up to 0.42 mm/d in year 1 over Southern Europe, while it decreases by −0.28 mm/d in year 1 over Northern Europe, respectively. Both simulations and reconstructions show that the centers with the strongest increase in precipitation have always been located in the Balkans and Apennine peninsulas along the Mediterranean coast over Southern Europe, and the centers with the strongest precipitation reduction are mainly located in the British Isles and Scandinavia over northwestern Europe. The negative response of North Atlantic Oscillation (NAO) with significant positive sea level pressure (SLP) anomaly in the north and negative SLP anomaly in the south is excited in summer. The low tropospheric wind anomaly caused by the negative phase of NAO in summer affects the water vapor transport to Europe, resulting in the distribution pattern of summer precipitation in Europe, which is drying in the north and wetting in the south. The knowledge gained from this study is crucial to better understand and predict the potential impacts of single mega volcanic eruption on the future summer hydroclimate change in Europe.

Advances in understanding large-scale responses of the water cycle to climate change

Globally, thermodynamics explains an increase in atmospheric water vapor with warming of around 7%/°C near to the surface. In contrast, global precipitation and evaporation are constrained by the Earth's energy balance to increase at ∼2-3%/°C. However, this rate of increase is suppressed by rapid atmospheric adjustments in response to greenhouse gases and absorbing aerosols that directly alter the atmospheric energy budget. Rapid adjustments to forcings, cooling effects from scattering aerosol, and observational uncertainty can explain why observed global precipitation responses are currently difficult to detect but are expected to emerge and accelerate as warming increases and aerosol forcing diminishes. Precipitation increases with warming are expected to be smaller over land than ocean due to limitations on moisture convergence, exacerbated by feedbacks and affected by rapid adjustments. Thermodynamic increases in atmospheric moisture fluxes amplify wet and dry events, driving an intensification of precipitation extremes. The rate of intensification can deviate from a simple thermodynamic response due to in-storm and larger-scale feedback processes, while changes in large-scale dynamics and catchment characteristics further modulate the frequency of flooding in response to precipitation increases. Changes in atmospheric circulation in response to radiative forcing and evolving surface temperature patterns are capable of dominating water cycle changes in some regions. Moreover, the direct impact of human activities on the water cycle through water abstraction, irrigation, and land use change is already a significant component of regional water cycle change and is expected to further increase in importance as water demand grows with global population.

Black carbon over an urban atmosphere in northern peninsular Southeast Asia: Characteristics, source apportionment, and associated health risks

Black carbon (BC) has been demonstrated to pose significant negative impacts on climate and human health. Equivalent BC (EBC) measurements were conducted using a 7-wavelength aethalometer, from March to May 2016, over an urban atmosphere, viz., Chiang Mai (98.957°E, 18.795°N, 373 m above sea level), Thailand in northern peninsular Southeast Asia. Daily variations in aerosol light absorption were mainly governed by open fire activities in the region. The mean mass-specific absorption cross-section (MAC) value of EBC at 880 nm was estimated to be 9.3 m² g^-1. The median EBC mass concentration was the highest in March (3.3 μg m^-3) due to biomass-burning (comprised of forest fire and agricultural burning) emissions accompanied by urban air pollution within the planetary boundary layer under favorable meteorological conditions. Daily mean absorption Ångström exponent (AAE_470/950) varied between 1.3 and 1.7 and could be due to variations in EBC emission sources and atmospheric mixing processes. EBC source apportionment results revealed that biomass-burning contributed significantly more to total EBC concentrations (34-92%) as compared to fossil-fuel (traffic emissions). Health risk estimates of EBC in relation to different health outcomes were assessed in terms of passive cigarette equivalence, highlighting the considerable health effects associated with exposure to EBC levels. As a necessary action, the reduction of EBC emissions would promote considerable climate and health co-benefits.

Quantifying the Importance of Rapid Adjustments for Global Precipitation Changes

Different climate drivers influence precipitation in different ways. Here we use radiative kernels to understand the influence of rapid adjustment processes on precipitation in climate models. Rapid adjustments are generally triggered by the initial heating or cooling of the atmosphere from an external climate driver. For precipitation changes, rapid adjustments due to changes in temperature, water vapor, and clouds are most important. In this study we have investigated five climate drivers (CO2, CH4, solar irradiance, black carbon, and sulfate aerosols). The fast precipitation responses to a doubling of CO2 and a 10-fold increase in black carbon are found to be similar, despite very different instantaneous changes in the radiative cooling, individual rapid adjustments, and sensible heating. The model diversity in rapid adjustments is smaller for the experiment involving an increase in the solar irradiance compared to the other climate driver perturbations, and this is also seen in the precipitation changes.

Large increase in global storm runoff extremes driven by climate and anthropogenic changes

Weather extremes have widespread harmful impacts on ecosystems and human communities with more deaths and economic losses from flash floods than any other severe weather-related hazards. Flash floods attributed to storm runoff extremes are projected to become more frequent and damaging globally due to a warming climate and anthropogenic changes, but previous studies have not examined the response of these storm runoff extremes to naturally and anthropogenically driven changes in surface temperature and atmospheric moisture content. Here we show that storm runoff extremes increase in most regions at rates higher than suggested by Clausius-Clapeyron scaling, which are systematically close to or exceed those of precipitation extremes over most regions of the globe, accompanied by large spatial and decadal variability. These results suggest that current projected response of storm runoff extremes to climate and anthropogenic changes may be underestimated, posing large threats for ecosystem and community resilience under future warming conditions.

Storm runoff extremes dominate flash flood formation and generation, posing a grand threat to ecosystems and communities across the world. Here the authors show that current projected response of these storm runoff extremes to climate and anthropogenic changes are underestimated.