Earth system models (ESMs) are a common tool for estimating local and global greenhouse gas emissions under current and projected future conditions. Efforts are underway to expand the representation of wetlands in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) by resolving the simultaneous contributions to greenhouse gas fluxes from multiple, different, sub-grid-scale patch-types, representing different eco-hydrological patches within a wetland. However, for this effort to be effective, it should be coupled with the detection and mapping of within-wetland eco-hydrological patches in real-world wetlands, providing models with corresponding information about vegetation cover. In this short communication, we describe the application of a recently developed NDVI-based method for within-wetland vegetation classification on a coastal wetland in Louisiana and the use of the resulting yearly vegetation cover as input for ELM simulations. Processed Harmonized Landsat and Sentinel-2 (HLS) datasets were used to drive the sub-grid composition of simulated wetland vegetation each year, thus tracking the spatial heterogeneity of wetlands at sufficient spatial and temporal resolutions and providing necessary input for improving the estimation of methane emissions from wetlands. Our results show that including NDVI-based classification in an ELM reduced the uncertainty in predicted methane flux by decreasing the model’s RMSE when compared to Eddy Covariance measurements, while a minimal bias was introduced due to the resampling technique involved in processing HLS data. Our study shows promising results in integrating the remote sensing-based classification of within-wetland vegetation cover into earth system models, while improving their performances toward more accurate predictions of important greenhouse gas emissions.

Wetlands are the largest emitters of biogenic methane (CH₄) and represent the highest source of uncertainty in global CH₄ budgets. Here, we aim to improve the realism of wetland representation in the U.S. Department of Energy's Exascale Earth System Model land surface model, ELM, thereby reducing uncertainty of CH₄ flux predictions. We develop an updated version, ELM‐Wet, where we activate a separate landunit for wetlands that handles multiple wetland‐specific eco‐hydrological patch functional types. We introduce more realistic hydrological forcing through prescribing site‐level constraints on surface water elevation, which allows resolving different sustained inundation depth for different patches, and if data exists, prescribing inundation depth. We modified the calculation of aerenchyma transport diffusivity based on observed conductance per leaf area for different vegetation types. We use Bayesian Optimization to parameterize CO₂ and CH₄ fluxes in the developed wet‐landunit. Site‐level simulations of a coastal non‐tidal freshwater wetland in Louisiana were performed with the updated model. Eddy covariance observations of CO₂ and CH₄ fluxes from 2012 to 2013 were used to train the model and data from 2021 were used for validation. Patch‐specific chamber flux observations and observations of CH₄ concentration profiles in the soil porewater from 2021 were used for evaluation of the model performance. Our results show that ELM‐Wet reduces the model's CH₄ emission root mean squared error by up to 33% and is able to represent inter‐daily CO₂ and CH₄ flux variability across the wetland's eco‐hydrological patches, including during periods of extreme dry or wet conditions.

The proposed article is devoted to the study and analysis of changes in the field of average monthly air temperature on the territory of Ukraine over the past fifteen years (2006-2020) of the period 1991-2020 to determine the trends that have emerged as a result of changes in global circulation over the Atlantic-European sector of the Northern Hemisphere and the possible occurrence of frequent drought events on the territory of Ukraine. Тaking into account the drastic climate changes that have occurred during the last decades, there is a problem in adapting a number of branches of the production complex to such changes in order to prevent economic losses and develop a new strategy in this direction. Connection with research tasks. The presented study is related to the implementation of a number of state-ordered research works dedicated to the study of the peculiarities of modern climate changes in Ukraine and the identification of climate-vulnerable areas on its territory. Problems to be solved in the article. Taking into account the accumulated material regarding the features of the distribution of the air temperature field in Ukraine and the probabilistic scenarios for its change under the influence of general warming in the Northern Hemisphere, for the territory of Ukraine it is necessary to find out the mechanism of its current changes and determine their direction on a temporal and territorial scale. The main purpose of the presented article was to investigate and establish the main trends in the current field of average monthly air temperature in Ukraine over the past 15 years (2006-2020) and show the nature of the spatial and temporal distribution of these changes. Materials and methods. The data of the average monthly air temperature at 55 stations of Ukraine during all months of the year for the fifteen-year periods 1991-2005 and 2006-2020 served as the research materials. The main research methods were physical and statistical to determine the deviations of two 15-year periods and cartographic to determine spatio-temporal differentiation of detected cells. Main results. It was established that on the territory of Ukraine in January 2006-2020 there was a certain decrease in the average monthly air temperature due to lower temperatures. In the rest of the winter months, its growth is observed, especially in the territory of the northwestern, northern, and northeastern regions and in some central and southern regions.. In the spring, the increase in the average monthly air temperature in 2006-2020 occurred more intensively in the northern regions and in a number of regions of the western region (Peredkarpattia). In the summer, the increase in air temperature was observed throughout the territory of Ukraine, but most intensively in July. Territorially, the greatest increase in the average monthly air temperature was expressed in the north, northeast and south. In autumn, the increase in the average monthly air temperature was most intense in November 2006-2020 in the regions of the northern and central regions, as well as in the Carpathian region. In the last 15 years, the average monthly air temperature in Ukraine has increased, but in January it decreased in the north, northeast, in some places in the center and south. This trend is new for today's climate. The results of the study for the territory of Ukraine are presented for the first time and can be used for planning agricultural works.

Formulation of the problem. In recent years, interest in the atmospheric river (AR) phenomenon is growing, as more and more researchers associate it with extreme precipitation. Relatively few works are devoted to the assessment of the influence of atmospheric rivers on precipitation in Eastern Europe. The purpose of the article is to assess the occurrence of atmospheric river events during extreme precipitation in the western regions of Ukraine (Lviv and Volyn regions) and to analyze the geographical features of the spatial distribution of atmospheric river bends during extreme precipitation. Methods. We used the catalog of atmospheric rivers identified according to the methodology of D. Walliser and B. Guan to analyze the occurrence of atmospheric river events on the territory of the western part of Ukraine. Also, we used the sample of days with extreme precipitation (greater than 95th percentile for each meteorological station and each month) in the Lviv and Volyn oblasts of Ukraine to match it with AR episodes. It is shown that in most cases extreme precipitation events were accompanied by the atmospheric river phenomenon detected on the territory of Ukraine or the bordering territories. Results. The typical shape of atmospheric river bends during extreme precipitation most often is arc-shaped while the typical spatial coverage stretched from North Africa through the Mediterranean Sea and Turkey to the territory of Ukraine. Less often, the form of detected AR area had the form of a meridional bend extending from the eastern part of the Mediterranean Sea towards Ukraine. However, the analysis showed that the presence of atmospheric river phenomenon is not the exceptional reason for extreme precipitation. Part of the extreme precipitation events is associated with specific synoptic situations (precipitation caused by cold fronts or occluded fronts) whereas conditions for atmospheric river detection are not fulfilled (bend size, meridional flow component, flow intensity). Atmospheric river episodes were not observed at most of the days of general sample (on average 72.36%) within the study area based on the period of 1991-2020. At the same time, precipitation events in the absence of AR were recorded on average in 32.2% of days (relative to the total number of days). In the presence of AR, precipitation was not recorded in about a third of cases. In the sample of days in the absence of AR and in the presence of AR, the proportion of precipitation of different gradations is as follows: for 10-20 mm is 2.73% and 2.64% respectively; for 20-50 mm is 1.37% and 1.63%; more than 50 mm is 0 .19% against 0.16%. In the spring, there is a certain consistency with the negative daily value of the NAO index and the AR axis orientation from the southwest to the territory of Ukraine. Thus, within 5 days before the localization of AR on the territory of Ukraine, values of the NAO index <-0.5 are noted, but the index changes in the process of the pressure field change. Based on a limited sample of extreme precipitation (94 cases), we assessed the correspondence of the precipitation rate to the area of atmospheric rivers and their features of the spatial orientation. ARs extending from the southwest (north of Africa) and the south (western part of the Mediterranean Sea) are characterized by the greatest recurrence. No regularities were found either concerning the dependence of the precipitation rate on the orientation of the AR, or concerning the dependence of the number of stations with extreme precipitation on the orientation of the AR. No linear dependence was found for the area of atmospheric rivers within both the study region and the territory of Eastern and Southeastern Europe with daily precipitation in the western regions of Ukraine.

It is obvious that hydrogeological drought is caused by meteorological drought and is caused by a decrease in groundwater recharge and an increase in its flow. However, it remains unclear which factor is more influential: rising air temperatures, decreased precipitation, declining river stages, or other related variables. The article highlights a method for identifying hydrogeological drought based on the analysis of SGI indices and confirmation of meteorological drought. Based on retrospective data, the duration of meteorological droughts was assessed to determine whether it was sufficient to trigger significant and prolonged recession in groundwater levels. Groundwater level depths affected by meteorological drought were also analyzed. Spatial and temporal patterns of drought manifestation were identified, along with the degree of inertia in groundwater level response to climatic changes and meteorological phenomena. The analysis was conducted using data from hydrogeological monitoring wells in the Southern Bug River Basin, by calculating and comparing the Standardized Precipitation Index (SPI) and the Standardized Groundwater Index (SGI). A series of SPI and SGI maps for the year 2016 was developed using the spline interpolation method in the ArcMap environment. Additionally, the long-term dynamics of SGI over the 1980–2020 period were analyzed using data from nine monitoring wells. The results showed spatial correlation between the indices, but with a temporal lag: the most intense meteorological drought was recorded in July–September, while the greatest groundwater level decline was observed in August–October. The analysis allowed the identification of the most drought-prone regions in the central part of the basin and substantiated the feasibility of combining SPI and SGI indices for comprehensive water resource monitoring. The proposed approach can serve as a foundation for the development of a regional early warning system for groundwater droughts and adaptive groundwater management under climate change conditions.

We intoduce the development of a new wetland-focused version of the Energy’s Exascale Earth System Model (E3SM) Land-surface Model (ELM). The updated version, ELM-Wet, activates a separate wet-landunit for simulation of wetlands. This Wet-landunit handles multiple eco-hydrological functional type patches. We introduced wetland-specific hydrology through prescribing site-level (whole wetland) constraints on surface water elevation and including a patch-level characteristic maximal inundation depth that enables resolving different sustained inundation depth for different patches, and if data exists, prescribing inundation depth at the site and patch levels. We modified the calculation of methane transport through palnt aerenchyma based on observed conductance for different vegetation types. We use BOA, a new Bayesian Optimization toolpack, to parameterize the processes controlling CO2 and CH4 fluxes in the wetland landunit. Site-level simulations of a coastal freshwater wetland in Louisiana (US-LA2) were performed with the updated model. Eddy covariance observations of CO2 and CH4 fluxes from 2012-2013 were used to train the model. Flux data from 2021 were used for validation. Patch-specific chamber flux observations and observations of CH4 concentration profiles in the soil porewater from 2021 were used for evaluation of the model performance in terms of soil concentration profiles at the patch level. Our results show that ELM-Wet with BOA optimization was able torepresent inter-daily and seasonal CO2 and CH4 fluxes and concentration dynamics across the wetland’s eco-hydrological patches.