Precipitation Evaporation Research Articles

Evaluating Performances of LSTM, SVM, GPR, and RF for Drought Prediction in Norway: A Wavelet Decomposition Approach on Regional Forecasting

A serious natural disaster that poses a threat to people and their living spaces is drought, which is difficult to notice at first and can quickly spread to wide areas through subtle progression. Numerous methods are being explored to identify, prevent, and mitigate drought, and distinct metrics have been developed. In order to contribute to the research on measures to be taken against drought, the Standard Precipitation Evaporation Index (SPEI), one of the drought indices that has been developed and accepted in recent years and includes a more comprehensive drought definition, was chosen in this study. Machine learning and deep learning algorithms, including support vector machine (SVM), random forest (RF), long short-term memory (LSTM), and Gaussian process regression (GPR), were used to model the droughts in six regions of Norway: Bodø, Karasjok, Oslo, Tromsø, Trondheim, and Vadsø. Four distinct model architectures were employed for this goal, and as a novel approach, the models’ output was enhanced by using discrete wavelet decomposition/transformation (WT). The model outputs were evaluated using the correlation coefficient (r), Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE) as performance evaluation criteria. When the findings were analyzed, the GPR model (W-GPR), which was acquired after WT, typically produced the best results. Furthermore, it was discovered that, out of all the recognized models, M04 had the most effective model structure. Consequently, the most successful outcomes were obtained with W-SVM-M04 for Bodø and W-GPR-M04 for Karasjok, Oslo, Tromsø, Trondheim, and Vadsø. Furthermore, W-GPR-M04 in the Oslo region had the best results across all regions (r: 0.9983, NSE: 0.9966 and RMSE:0.0539).

Analyzing the impact of climatic conditions on rainfed wheat yield in northwest Iran: a parametric and nonparametric approach

ABSTRACT It is essential to comprehend the relationship between agricultural yields and climatic conditions, especially concerning food security and the possible threats to crop output. Wheat is a crucial agricultural crop that covers a significant amount of rainfed production regions in Iran. This study utilized parametric and nonparametric approaches to assess rainfed wheat yield. The study centered on the Tabriz area in northwest Iran, examining precipitation patterns concerning rainfed wheat cultivation. The study focused on analyzing seasonal and distinct rainfall patterns during the cultivation period, utilizing widely recognized drought metrics such as the standardized precipitation index and the standardized precipitation–evaporation index. The study findings indicate a notable upward trend in rainfed wheat output over the analyzed period. The Mann–Kendall test resulted in a p-value of 0.031, indicating statistical significance for the observed rising trend. We conducted trend removal and normalized rainfed wheat yield figures based on seasonal precipitation to study the data more thoroughly. The second phase of the growing season was particularly notable, spanning from the completion of germination to the beginning of blooming. Instead of analyzing precipitation for the full growing season, concentrating on autumn precipitation or the time from germination to blooming might improve yield forecasts and determinations.

Updates to NOAA’s Unified Forecast System’s Cumulus Convection Parameterization Scheme between GFSv16 and GFSv17

Abstract This study outlines the updates made to cumulus convection parameterizations between Global Forecast System, version 16 (GFSv16), and the forthcoming GFSv17 which will be the first global forecast application to become operational under the Unified Forecast System infrastructure. The updates, addressing known systematic errors and biases, incorporate innovations such as stochasticity, three-dimensional subgrid organizational effects, and a prognostic closure evolution. The changes are shown to improve tropical temperature/humidity biases, convective available potential energy (CAPE) forecasts, CONUS precipitation, and tropical variability. By examining individual updates’ impact on temperature, humidity profiles, and precipitation power spectra, we find that the new prognostic closure and stricter precipitation evaporation criteria alleviate a dry and cold bias in the tropical boundary layer and enhance precipitation variability in the tropics. Stricter triggering criteria also allow for more CAPE buildup, particularly over the tropics. The cumulus convection updates have a modest impact on precipitation skill scores over CONUS, but overall, there is an improvement when comparing GFSv16 and the latest GFSv17 prototype configurations, in particularly for larger thresholds. The study also highlights the challenges in developing convection parameterizations suitable for both coupled and uncoupled model configurations. Evaluation of the MJO shows varying responses to cumulus convection changes depending on whether the model is coupled with a dynamic ocean model.

Drying trend in land and sea in East Asia during the warm season over the past four decades

Abstract The East Asian region is typically characterized by warm and humid conditions from late spring to summer. However, in recent decades, this region has experienced an increase in severe drying conditions, deviating from historical climatological patterns. This study investigated the precipitation − evaporation (P − E) trends across land and sea regions in East Asia (EA) during the extended summer season (April–September) from 1980 to 2022, and the key physical processes driving these trends through moisture budget decomposition and numerical experiments. The results reveal pronounced drying trends in southeastern China and the Yellow Sea and parts of the Korea Strait and Korean Peninsula over the past 43 years. The underlying physical processes driving these drying conditions differ between land and sea in EA. In southeastern China, the drying is driven by dynamic processes, particularly moisture divergence related to wind changes. This is linked to anomalous strengthening of descending motion due to the Indo-Pacific warm pool warming induced by both anthropogenic global warming and natural Pacific Decadal Oscillation-like sea surface temperature (SST) patterns. Conversely, drying in the Yellow Sea and adjacent areas is influenced by thermodynamic moisture advection. The altered humidity distribution due to global warming-induced SST patterns, which are higher over the Northwest Pacific marginal sea and lower in inland China, drives dry air transport from inland China to the Yellow Sea via background southwesterly wind. These findings enhance our understanding of the drying trend and their distinct processes in EA’s land and sea areas during the extended summer.

A Multiscalar Standardized Vapor Pressure Deficit Index for Drought Monitoring and Impacts

ABSTRACTVapour pressure deficit (VPD) is a critical measure of the atmospheric demand for water and can be used to assess short‐term and seasonal drought. To provide for probabilistic comparisons of VPD across space and time, we develop a Standardized Vapor Pressure Deficit Index (SVPDI). Similar to the way that other standardised drought indices are used, SVPDI allows for the analysis and comparison of changes in VPD across regions with different base level VPD values. It also should be useful for analysing impacts on vegetation that has varying levels of adaptation to high VPD. We use 1‐, 3‐, 6‐ and 12‐month timescales for the development of SVPDI and show that the gamma distribution is superior to other zero‐limited probability distributions for analysing VPD and, therefore, for calculating SVPDI. Then, focusing on the short‐term variations at the 1‐ and 3‐month timescales, we show how SVPDI has changed globally from 1958 to 2023 and how those changes differ from those of the commonly used Standardized Precipitation Evaporation Index (SPEI). We find that SVPDI shows more widespread drying conditions that also are larger in magnitude compared to those of SPEI. Although the two indices are moderately well correlated across the terrestrial surface, we discover that they are more decoupled in humid and arid regions compared to dry sub‐humid and semi‐arid regions. Using four locations that have recently experienced severe drought, we find that SVPDI generally showed longer drought duration and more severe drought events in the last decade when compared to SPEI.

Phasic and periodic change of drought under greenhouse effect

Purpose Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes. Design/methodology/approach The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns. Findings The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%. Research limitations/implications The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution. Practical implications Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland. Originality/value The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

Spatiotemporal variation of modern lake, stream, and soil water isotopes in Iceland

Abstract. As global warming progresses, changes in high-latitude precipitation are expected to impart long-lasting impacts on Earth systems, including glacier mass balance and ecosystem structures. Reconstructing past changes in high-latitude precipitation and hydroclimate from networks of continuous lake records offers one way to improve forecasts of precipitation and precipitation–evaporation balances, but these reconstructions are currently hindered by the incomplete understanding of controls on lake and soil water isotopes. Here, we study the distribution of modern water isotopes in Icelandic lakes, streams, and surface soils collected in 2002, 2003, 2004, 2014, 2019, and 2020 to understand the geographic, geomorphic, and environmental controls on their regional and interannual variability. We find that lake water isotopes in open-basin (through-flowing) lakes reflect local precipitation, with biases toward the cold season, particularly in lakes with sub-annual residence times. Closed-basin lakes have water isotope and deuterium excess values consistent with evaporative enrichment. Interannual and seasonal variabilities of lake water isotopes at repeatedly sampled sites are consistent with instrumental records of winter snowfall; summer relative humidity; and atmospheric circulation patterns, such as the North Atlantic Oscillation. Summer surface soil water isotopes span the entire range of seasonal precipitation values in Iceland and appear to be consistently overprinted by evaporative enrichment, which can occur throughout the year, although the sampling depths were shallower than rooting depths for many plant types. This dataset provides new insight into the functionality of water isotopes in Icelandic environments and offers renewed possibilities for optimized site selection and proxy interpretation in future paleohydrological studies on this North Atlantic outpost.

Refined simple model of stable water isotopic content in central Antarctic precipitation including Oxygen 17 fractionation

Modeling the isotopic composition of atmospheric precipitation is an important tool for climatic, paleoclimatic and hydrological studies. This paper presents an improved simple model of the isotopic composition of precipitation in Central Antarctica. It differs from the previous version published by Salamatin et al. (2004) by 1) the included geochemical cycle of oxygen 17 and 2) the possibility of solving the inverse problem (i.e., finding the trajectory parameters that could form the isotopic composition of the precipitation observed at the end of the trajectory). The paper examines in detail the main tuning parameters of the model, among which the most important are the temperature and humidity in the moisture source, the “circulation parameter”, which takes into account the advection of vapor into the moisture source, the condensation temperature and the degree of air supersaturation with moisture in ice clouds. Based on the analysis of data on the isotopic composition (including “excess of oxygen 17”, 17O-xs) of water vapor in the surface layer of the atmosphere over the ocean and surface snow sampled along meridional profiles in East Antarctica, the optimal tuning of the model for calculating the isotopic composition of atmospheric precipitation at the Antarctic Vostok station was performed. In particular, it is shown that the temperature and humidity of the air in the moisture source are +17.4°C and 72%, respectively, and the condensation temperature is –41.3°C. The possibilities of using the model to analyze the isotopic composition of liquid precipitation falling on other continents are discussed. The final part of the paper discusses the limitations of the model. In particular, it is noted that the model does not take into account such processes as the evaporation of precipitation when it falls in arid conditions, mixing of trajectories, the influence of local sources of moisture, as well as the features of isotope fractionation during the evaporation of moisture from the continents.

Analysis of large-scale high-quality graphene production and applications

Graphene, a single-atom-thick layer of carbon atoms arranged in a hexagonal lattice, is the thinnest and strongest material known to mankind. It has excellent electrical, thermal, and mechanical properties, making it a promising material for a wide range of applications in electronics, optoelectronics, energy storage, and more. With the increasing demand for graphene in various applications, large-scale and high-quality graphene production has become a significant challenge. While early methods of graphene production involved mechanical exfoliation, this method is limited in terms of scalability and yield. To meet the increasing demand for large-scale production of graphene, various methods have been developed in recent years, including chemical vapor precipitation, epitaxial crystal growth, graphene oxide reduction and solvent exfoliation and so on. This study aims to introduce several existing methods for the mass production of graphene with high quality and analyzes the advantages and disadvantage involve thereof. The findings in this paper may provide a valuable reference for the industrial-scale production of graphene.

The influence of multidecadal climate variability and abrupt landscape change on terrestrial ecosystem composition and fire regime in the upper Columbia River basin - A high-resolution Holocene perspective

High-resolution paleoclimatic and paleoecologic datasets from a small lake in eastern Washington (USA) help elucidate Holocene environmental dynamics in the interior Pacific Northwest. Round Lake lies near the ecotone between sagebrush steppe and dry pine forest, making it highly sensitive to changes in precipitation-evaporation (P-E) balance. We present isotopic, sedimentological, and paleoecological data from a single sedimentary sequence analyzed at sufficient resolution to detect sub-decadal climatic variability. During the early Holocene (11,000–8500 cal yr BP), when summer insolation was higher than present, Round Lake experienced persistent aridity that led to reduced forest cover and small, probably frequent surface fires. Sub-centennial hydroclimate fluctuations during this period were muted, as indicated by low multi-decadal variability in δ18Ocarbonate records from the region. Oxygen isotopes indicate increased cool-season moisture during the middle Holocene (8500-5300 BP), but stratigraphic evidence suggests intermediate and variable lake levels. The deposition of the Mazama tephra (ca. 7600 cal yr BP) immediately preceded to a protracted expansion of steppe at the expense of forest. Increased hydroclimate variability and fire activity following ash deposition likely restricted conifer taxa even when elevated cool-season moisture would have facilitated their growth. The late Holocene was marked by persistently high lake levels, as indicated by the lithostratigraphic and pollen records. Comparatively large multidecadal variations in precipitation, which peaked during the last millennium, were also prominent features of late-Holocene hydroclimate, and may have been related to the strengthening of the El Niño Southern Oscillation and Pacific Decadal Oscillation. Pinus and Pseudotsuga show a 60–100 year lag in their response to hydroclimatic variations inferred from the oxygen isotope records. These results highlight how millennial-to-decadal scale hydroclimate conditions, along with abrupt landscape change, influence ecology in a water-stressed region of western North America.

How Might the May 2015 Flood in the U.S. Southern Great Plains Induced by Clustered MCSs Unfold in the Future?

AbstractThe historic 22–26 May 2015 flood event in Texas and Oklahoma was caused by anomalous clustered mesoscale convective systems (MCSs) that produced record‐breaking rainfall and $3 billion of damage in the region. A month‐long regional convection‐permitting simulation is conducted to reconstruct multiple clustered MCSs that lead to this flood event. We further use the pseudo global warming approach to examine how a similar event may unfold in a warmer climate and the driving physical factors for the changes. Tracking of MCSs in observations and simulations shows that the historical simulation reproduces the salient characteristics of the observed MCSs. In a warmer climate under a high‐emission (SSP5‐8.5) scenario, the Southern Great Plains is projected to experience a near surface warming of 4–6 K, accompanied by enhanced moisture transport by the strengthened Great Plains low‐level jet. A warmer and moister lower troposphere leads to 36%–59% larger convective available potential energy, supporting wider and more intense convective updrafts and rainfall production. Consistently, MCSs have wider convective areas and stronger rainfall intensities, producing 50% larger rain volumes during the mature stage. Extreme (99.5%) MCS rainfall frequency and amount will increase by threefold. However, MCS stratiform rain area decreases as a result of elevated stratiform cloud bases that lead to stronger sublimation and evaporation of precipitation in response to warming, resulting in reduced weak‐to‐moderate surface precipitation. Results suggest that global warming greatly increases precipitation intensity of clustered MCS events under strong synoptic influence, with much higher potential to produce serious floods without additional climate adaptation.

Intensification of evaporative precipitation of lignin in a spinning disc evaporator

A continuous process for the evaporative precipitation of lignin derived from Organosolv black liquor was successfully developed and implemented in a spinning disc evaporator (SDE). A maximum of 95 % of the lignin was recovered at a disc speed of 1200 rpm, black liquor feed flow rate of 1 ml s−1 on a smooth disc surface heated to 100 ⁰C. These optimal flow rate and disc speed values corresponded to conditions which maximised residence time to <1 s in 4 disc passes without compromising on the rate of evaporative heat transfer. The lignin precipitate did not have any detectable impurities present after being washed and dried. The particle size for the lignin precipitate was in the region of 3 – 9 µm with minor agglomeration occurring, providing good filterability. A scaled up version of the process was modelled for benchmarking purposes and it was found that the SDE had a better theoretical performance than a falling film evaporator (FFE) system developed for the same process, with the energy consumption reduced by 23% and a higher lignin recovery rate per volume of black liquid processed once adjusted for processing time (38.1 g L−1 h−1 for the SDE vs. 3.23 g L−1 h−1 for the FFE).

Long‐term variability and trends of meteorological droughts in Ukraine

AbstractThe purpose of this research is to identify changes in the spatiotemporal distribution and severity of meteorological droughts in Ukraine between 1946 and 2020. In order to determine the role of precipitation and atmospheric evaporative demand on drought severity, two drought indices were applied for comparative analysis: the standardized precipitation index (SPI) and the standardized evaporation precipitation index (SPEI). Both indices were calculated on 3‐ and 12‐month timescales. The gridded dataset of monthly air temperature and atmospheric precipitation for Ukraine with high spatial resolution (0.1° × 0.1°), developed in the Ukrainian Hydrometeorological Institute, was used. Results of time series analysis of drought indices showed at least 20 episodes, in which more than 25% of the territory of Ukraine was affected by drought of varying intensity. Trends show an increase in drought severity determined mostly by a strong observed increase in the atmospheric evaporative demand. Tendencies towards an increase in the duration and intensity of droughts were observed mainly in the southwestern, central and northern regions of Ukraine. The main cause of the increase was droughts in spring and summer. The temporal analysis of the spatial distribution of areas affected by drought during the identified main drought episodes showed different patterns in drought propagation across the territory of Ukraine.

Synthesis and characterization of capsaicin nanoparticles: An attempt to enhance its bioavailability and pharmacological actions

Abstract Herein, capsaicin nanoparticles (NPs) were prepared by two different methods, namely, evaporative precipitation of nanosuspension (EPN) and anti-solvent precipitation with a syringe pump (APSP). The nanoparticles of the necessary sizes were obtained after optimizing experimental parameters such as the solvent-to-anti-solvent ratio and stirring speed. They had spherical shapes and an average diameter of 171.29 ± 1.94 and 78.91 ± 0.54 nm when prepared using the EPN and APSP methods, respectively. Differential scanning calorimetry and an X-ray diffractometer showed that the capsaicin crystallinity decreased. FTIR results showed that the NPs were produced with their original configuration and did not result in the synthesis of any additional structures. The NP formulation had a desirable drug content. They surpassed the unprocessed drug in solubility and displayed the desired stability. Capsaicin NP cream showed many folds of enhanced analgesic, anti-inflammatory, and antimicrobial effects compared to unprocessed capsaicin.

An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index

Coastal arid regions are similar to deserts, where it receives significantly less rainfall, less than 10 cm. Perhaps the world's worst natural disaster, coastal area droughts, can only be detected using reliable monitoring systems. Creating a reliable drought forecast model and figuring out how well various models can analyze drought factors in coastal arid regions are two of the biggest obstacles in this field. Different time-series methods and machine-learning models have traditionally been utilized in forecasting strategies. Deep learning is promising when describing the complex interplay between coastal drought and its contributing variables. Considering the possibility of enhancing our understanding of drought features, applying deep learning approaches has yet to be tried widely. The current investigation employs a deep learning strategy. Coastal Drought indices are commonly used to comprehend the situation better; hence the Standard Precipitation Evaporation Index (SPEI) was used since it incorporates temperatures and precipitation into its computation. An integrated coastal drought monitoring model was presented and validated using convolutional long short-term memory with self-attention (SA-CLSTM). The Climatic Research Unit (CRU) dataset, which spans 1901–2018, was mined for the drought index and predictor data. To learn how LSTM forecasting could enhance drought forecasting, we analyzed the findings regarding numerous drought parameters (drought severity, drought category, or geographic variation). The model's ability to predict drought intensity was assessed using the Coefficient of Determination (R2), the Root Mean Square Error (RMSE), and the Mean Absolute Error (MAE). Both the SPEI 1 and SPEI 3 examples had R2 values more than 0.99 for the model. The range of predicted outcomes for each drought group was analyzed using a multi-class Receiver Operating Characteristic based Area under Curves (ROC-AUC) method. The research showed that the AUC for SPEI 1 was 0.99 and for SPEI 3, 0.99. The study's results indicate progress over machine learning models for one month in advance, accounting for various drought conditions. This work's findings may be used to mitigate drought, and additional improvement can be achieved by testing other models.

Responses of radial growth to climate change for two dominant artificial coniferous trees

The adaptability of plantation ecosystems to climate change has become an important issue in many drylands worldwide. The plantation forests of the Loess Plateau, one of the driest areas in China, have greatly increased, and Picea crassifolia and Pinus tabuliformis are the dominant artificial coniferous species in this region. However, quantitative evaluations of the responses of radial growth to climate change for these two dominant artificial coniferous trees are rare. In this study, we collected tree-ring sample data from four sampling sites in Huajialing and Chankou in the arid Loess Plateau and analysed the radial growth of two artificial conifers and their climate response characteristics (precipitation, temperature, and standardised precipitation evaporation index (SPEI)) using Pearson correlation and the Climwin model. The results showed that (1) low precipitation during the growing season (April-August) and the resulting drought stress were major growth-limiting factors for plantation forests in the arid Loess Plateau, and this impact increased with the duration of drought stress. (2) P. tabuliformis was more susceptible to drought stress than P. crassifolia, and its soil water content at the 0–200 cm depth was already close to the wilting point. (3) The site conditions of planted areas, including initial planting density, elevation, and stand structure (canopy cover), significantly influenced the response of the same tree species to drought stress. (e.g., P. tabuliformis in high-density and low-elevation areas was more susceptible to drought stress than trees in low-density and high-elevation areas). We concluded that forest managers should select appropriate initial planting densities and altitudes and implement pruning and thinning measures at specific ages (15 years for P. crassifolia and 20 years for P. tabuliformis) based on basal area growth curves. Our results provide valuable information for the sustainable management of plantations against the background of climate warming.

Effects of Wind Shear and Aerosol Conditions on the Organization of Precipitating Marine Stratocumulus Clouds

AbstractThis study examines how wind shear affects precipitating marine stratocumulus clouds under different cloud droplet number concentrations (Nd). We performed a series of large eddy simulations (LES) of nocturnal marine stratocumulus clouds using Cloud Model 1 (CM1). The simulations show that Nd is the dominant factor for cloud cellular organization in this cloud regime rather than wind shear. Low Nd characterizes the open cellular structure with a high in‐cloud liquid water path (LWP). When wind shear is increased, the cloud fraction tends to decrease along with LWP, suggesting the cloud top region is significantly influenced by the entrainment and mixing of dry air from the free troposphere. We also examine cold pools in open and closed cellular clouds. Open‐cell clouds produce larger and deeper cold pools compared to closed‐cell clouds. Interestingly, cold pools can exist without surface precipitation and are produced by evaporation of light precipitation (drizzle) below the cloud base with weak downdrafts. The evaporation of raindrops and drizzle play an important role in initiating new convection, particularly where colliding outflows occur downstream of the cloud. This secondary convection contributes to the development and maintenance of the cloud cellular organization and formation.

Geological controls on lithium production from basinal brines across North America

With increasing lithium (Li) demands for electric car batteries and grid storage, additional Li beyond traditional continental brines and hard-rock sources might be necessary. Elevated Li concentrations have been reported in select oil field brines. Li could be extracted from the large volumes of saline fluids produced by oil and gas wells or from new wells dedicated to Li production. However, the spatial distribution of Li+ concentrations, the rates at which fluids can be produced in areas with elevated Li+ concentrations, and potential sources of Li enrichment are not well characterized. To help identify additional sources of Li, this study investigates the concentration, origin, and potential production rates of Li from sedimentary basin brines across North America. New Li data from brines in various stratigraphic units in the Paradox Basin are combined with existing datasets from the basin and others across North America. New Li analyses of organic-rich shales in the Paradox Basin are also examined to provide insights into the origins of Li. Results from this study show the median Li+ concentration in oil and gas produced waters across North America is ~5 mg/L; these generally low concentrations are unlikely to support Li production. However, higher Li+ concentrations (>65 mg/L) are found in select basins and strata containing deep saline fluids, associated with evaporation of paleo-seawater and precipitation of halite and potash salts, that have not been flushed by meteoric recharge. High Li content of organic-rich shales (range: 20–440 ppm; median: 60 ppm) interbedded with evaporites in the Paradox Basin suggest fluid-rock interactions with diagenetically-altered shales and organic matter are one potential source of Li-enrichment in basinal brines. Observed fluid production and injection rates indicate that Li production will likely be highest in sandstone and carbonate formations with relatively high permeability. Potential Li production rates can vary by orders of magnitude even within these strata due to heterogeneity in both Li concentrations and permeability, as well as recovery efficiencies between 40 and 70 % with current technology. Targeted Li production wells, rather than relying on existing oil and gas wells, would likely be necessary to produce brines at sufficient volumes to support Li production at these low concentrations. Co-recovery of other critical elements or combination with other subsurface developments, such as geothermal energy production, may make Li production from sedimentary basin fluids more viable.

Significant relationships between drought indicators and impacts for the 2018–2019 drought in Germany

Despite the scientific progress in drought detection and forecasting, it remains challenging to accurately predict the corresponding impact of a drought event. This is due to the complex relationships between (multiple) drought indicators and adverse impacts across different places/hydroclimatic conditions, sectors, and spatiotemporal scales. In this study, we explored these relationships by analyzing the impacts of the severe 2018–2019 central European drought event in Germany. We first computed the standardized precipitation index (SPI), the standardized precipitation evaporation index (SPEI), the standardized soil moisture index (SSMI) and the standardized streamflow index (SSFI) over various accumulation periods, and then related these indicators to sectorial losses from the European drought impact report inventory (EDII) and media sources. To cope with the uncertainty associated with both drought indicators and impact data, we developed a fuzzy method to categorize them. Lastly, we applied the method at the region level (EU NUTS1) by correlating monthly time series. Our findings revealed strong and significant relationships between drought indicators and impacts over different accumulation periods, albeit in some cases region-specific and time-variant. Furthermore, our analysis established the interconnectedness between various sectors, which displayed systematically co-occurring impacts. As such, our work provides a new framework to explore drought indicators-impacts dependencies across space, time, sectors, and scales. In addition, it emphasizes the need to leverage available impact data to better forecast drought impacts.

Global high-resolution drought indices for 1981–2022

Abstract. Droughts are among the most complex and devastating natural hazards globally. High-resolution datasets of drought metrics are essential for monitoring and quantifying the severity, duration, frequency, and spatial extent of droughts at regional and particularly local scales. However, current global drought indices are available only at a coarser spatial resolution (&gt;50 km). To fill this gap, we developed four high-resolution (5 km) gridded drought records based on the standardized precipitation evaporation index (SPEI) covering the period 1981–2022. These multi-scale (1–48 months) SPEI indices are computed based on monthly precipitation (P) from the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS, version 2) and Multi-Source Weighted-Ensemble Precipitation (MSWEP, version 2.8), and potential evapotranspiration (PET) from the Global Land Evaporation Amsterdam Model (GLEAM, version 3.7a) and hourly Potential Evapotranspiration (hPET). We generated four SPEI records based on all possible combinations of P and PET datasets: CHIRPS_GLEAM, CHIRPS_hPET, MSWEP_GLEAM, and MSWEP_hPET. These drought records were evaluated globally and exhibited excellent agreement with observation-based estimates of SPEI, root zone soil moisture, and vegetation health indices. The newly developed high-resolution datasets provide more detailed local information and can be used to assess drought severity for particular periods and regions and to determine global, regional, and local trends, thereby supporting the development of site-specific adaptation measures. These datasets are publicly available at the Centre for Environmental Data Analysis (CEDA; https://doi.org/10.5285/ac43da11867243a1bb414e1637802dec) (Gebrechorkos et al., 2023).