Decline in Water Ice Abundance in the Martian Mesosphere during Aphelion

Clouds on Mars are primary elements for understanding the past and present climate of the planet. Cloud particles can affect the energy balance of the planet, and so the atmospheric dynamic, as well as influence the vertical distribution of dust particles through dust scavenging. The dust scavenging by clouds has critical consequences in the water cycle of the planet; e.g. regions in the atmosphere with insufficient quantity of dust particles (or condensation nuclei) can inhibit the formation of H2O clouds and thus lead to the presence of water vapor in excess of saturation. The study of these interactions requires observations whose analysis allows us to infer simultaneously the properties of both the clouds and dust. To address these observations, the Radiation and Dust Sensor (RDS) is part of the Mars Environmental Dynamics Analyzer (MEDA) payload onboard of the Mars 2020 rover Perseverance.In this work we analysed the RDS observations made during twilight in the period Ls 39◦-262◦ to characterize the clouds above ∼ 30 km over the Perseverance rover site. From the ratio between the irradiance measured at zenith at 450 nm and 750 nm, we inferred that from Ls= 39◦ to 150◦ (referred as the cloudy period), water ice is the main constituent of the detected high-altitude aerosol layers. For Ls 150◦-262◦ dust is the main aerosol present. A total of 161 twilights were analysed in the cloudy period with a radiative transfer code in spherical geometry. Among other results we found: i) signatures of clouds or hazes on the RDS signals in the 58 % of the twilights; ii) most of the clouds were at altitudes between 40 km and 50 km and with particle sizes between 0.6 μm and 2 μm (in effective radius); iii) the cloud activity at sunrise is slightly higher that at sunset (65 % against 52 %), likely due to the differences in temperature; iv) the cloudiest time in Perseverance site and with the greatest cloud opacities is in Ls 120◦-150◦; and v) a notable decrease in the cloud activity around the aphelion (Ls ∼ 70◦), along with lower cloud altitudes and opacities. The drop in cloud activity around Ls ∼ 70◦ indicates lower concentrations of water vapor or cloud nuclei (dust) around this period in the Martian mesosphere. In this presentation, we will discuss the implications of our results on the water cycle of the planet.

Understanding the complex relationship between aerosols and clouds is crucial for accurately estimating anthropogenic aerosol radiative forcing and its impact on weather and climate. However, quantifying the relationship between cloud droplet number concentration (CDNC) and cloud condensation nuclei (CCN) concentration remains challenging due to extensive heterogeneities in cloud properties, processes occurring during cloud lifecycle, and observational uncertainties. This study integrates satellite observations with a global climate model and employs advanced statistical techniques to improve estimates of cloud droplet susceptibility to aerosol perturbations, particularly focusing on the CCN‐CDNC slope. A key challenge in determining this relationship is that CDNC is influenced by factors beyond CCN alone, such as atmospheric dynamics and cloud microphysics. These additional factors introduce variability that complicates direct correlation between CCN and CDNC, making it difficult to ascertain their true relationship. In addition, traditional methods like Ordinary Least Squares regression can produce biased slope estimates due to uncertainties in both CCN and CDNC measurements. When applied to CCN‐CDNC data, advanced curve fitting methods, such as bivariate least squares, often yield slopes exceeding 1, deviating from expected physical behavior. Our machine learning analysis identifies updraft velocity, among other key predictors, as a major factor leading to this larger‐than‐one slope between CCN and CDNC. To address this, we utilized Elastic Net Regression to isolate the effect of changes in CCN concentration on CDNC. This method refines the slope estimates by accounting for factors affecting CDNC, resulting in a slope that better captures the susceptibility of CDNC to CCN changes.

Mars, with a rich CO2 atmosphere and Titan, with an abundance of hydrocarbons, have both been proposed as models for the atmosphere of early Earth. In the current atmospheres of Mars and Titan, CO2 and hydrocarbons, respectively, may condense to form clouds. In this paper, we explore cloud formation processes in these two very different planetary atmospheres. Under early Martian conditions, infrared scattering by CO2 clouds could have warmed the planet’s surface above freezing. However, the radiative effect of the clouds depends strongly on the nucleation and growth kinetics of the cloud particles. We experimentally examine the nucleation and growth of CO2 on water ice under Martian conditions. We find that a critical saturation of S=1.3 is required for nucleation, corresponding to a contact parameter of m=0.95. After nucleation, growth of CO2 proceeds rapidly without a surface kinetic barrier. Using a microphysical cloud model, our data suggest that CO2 clouds are best described as “snow,” having a small...

<p indent=0mm>As the planet warms, shifts in the thermodynamic and dynamic environments of the climate system exert substantial impacts on the energy budget and water cycle. Understanding the response of precipitation extremes to climate change is essential for mitigating weather-related hazards and facilitating adaptive water resources management. The moisture holding capacity of the atmosphere, governed by the Clausius-Clapeyron (C-C) relationship, increases with temperature at a rate of about 7%/°C. Thermodynamically, precipitation intensity is expected to increase exponentially and worsen flood conditions with atmospheric warming. However, both observational and satellite data have revealed a nonmonotonic (hook) scaling of precipitation and storm runoff, in which extremes strengthen with warming temperature up to a peak point (<italic>T</italic>_pp) and decline thereafter. Few studies have yet considered whether and why the hook structure might change in a future warming climate. Moreover, existing studies have largely failed to detect and attribute changes of extreme precipitation to atmospheric thermodynamics versus dynamics, limiting reliable projection of future hydrological hazards and climate simulations. Here, we build upon existing studies to understand how precipitation and storm runoff scaling might change over Chinese mainland. We use gridded observational data to examine the temperature scaling of precipitation and storm runoff extremes, extending the C-C relationship. Using the ERA5 reanalysis dataset, we diagnose the impacts of total column water vapor (TCWV), convective available potential energy (CAPE) and relative humidity on precipitation extremes. After partitioning the thermodynamic and dynamic contributions of precipitation extremes based on the energy budget and water vapor balance, we quantify the underlying physical mechanisms of hook structures. Future climate scenarios are projected by using a large ensemble from 21 global climate models (GCMs) within Coupled Model Inter-comparison Project Phase-6 (CMIP6). Future streamflow series of 151 basins are projected by forcing hydrological model with bias-corrected climate model outputs. We quantify changes in the hook structures and their <italic>T</italic>_pp, and investigate implications of these shifts for future storms and flooding. The results show that relative humidity usually decreases with warming near-surface temperatures over most areas of China, while the TCWV and CAPE exhibit positive scaling rates with temperatures. The ERA5 reanalysis data over China reveals that atmospheric dynamics are responsible for the intensification of precipitation extremes and even flooding under very warm temperatures. The daily bias correction method reduces the systematical biases of GCMs outputs adequately, and captures extreme precipitation and temperatures well. By using four different hydrological models, we find that the Xinanjiang model typically exhibits the best performance in simulating daily streamflow over Chinese mainland. Projections of future hydro-climatological scenarios indicate that the hook structures do not set a firm upper-bound constraint on the intensification of extremes; rather, both the hook structure and the <italic>T</italic>_pp shift toward warmer temperatures in a warming climate. Alongside the shifts in <italic>T</italic>_pp, future storm and flooding extremes are projected to intensify by 20%−30%. These findings highlight the urgency in enhancing societal resilience to climate change, and understanding how the intensification of weather-related hazards might affect existing infrastructure and ecosystems.

A new method is proposed to predict the optical thickness, effective radius, and concentration of cloud droplets in water layer clouds by using the spectrum of cloud condensation nuclei (CCN), ascent velocity at cloud base, and liquid water path (LWP). A retrieval method is also proposed to predict CCN number concentration by using independent observational data of ascent velocity at the cloud base, the optical thickness and LWP of clouds. For this purpose, a newly developed cloud microphysical model that relates cloud droplet size distributions to the updraft velocity, and to CCN constituents and size distribution is used. Cloud droplet growth is calculated, with special care being taken to avoid non-physical numerical diffusion of the droplet spectrum. Near the cloud base, CCN activation and subsequent cloud droplet growth are calculated in a Lagrangian framework to model the effect of CCN on growth by condensation more accurately. In the middle and upper parts of the cloud, an Eulerian framework is used to estimate growth by coalescence for cloud droplet size distributions. Simulated vertical profiles of droplet size distributions, and a solu-tion to the radiative transfer equation using the discrete ordinate method, with no parameterizations, yield the optical properties of the cloud for short-wavelength radiation. Using the approximation equation proposed in this study, the maximum value of supersaturation in a cloud (Smax) is predicted by observing cumulative activated CCN number concentration at 0.075% supersaturation Nc(075%)), and the ascent velocity at the cloud base. Using this Smax, we can estimate Nc(Smax), which is the cumulative number concentration of CCN, whose critical supersaturations are lower than Smax. Nc(Smax) is used to predict the concentration of cloud droplets at the middle altitude of layer cloud (Nd). Conventionally Nd is assumed to be Nc(Smax). However, our parameterization can show that Nd is smaller than Nc(Smax), when Nc(Smax) is large. For the fixed liquid water path, optical thickness and effective radius can be expressed as a function of Nd, unless drizzle is falling from the cloud. The parameterizations developed in this paper are based on the U.S. Standard Atmosphere 1976. If necessary, the parameterizations for the extremely different atmosphere from that used here can be developed in the same way.

Determining the susceptibilities of cloud properties to perturbations in aerosols has been a persisting challenge in climate research. For example, satellite-retrieved susceptibility of cloud droplet number concentration (CDNC) to changes in cloud condensation nuclei (CCN) varies regionally, also having opposite correlations over land and ocean. Over the oceans, the correlation between CCN and CDNC is positive and in many cases, with a proper regression method, the dlogCDNC/dlogCCN exceeds 1. On the other hand, over land, many studies have found a negative correlation. As our preliminary global climate model simulations give qualitatively similar results to satellite retrievals, we have used the model together with reanalysis data of aerosol, meteorological properties, and cloud properties to interpret how other parameters such as cloud activation updrafts and vertical mixing of aerosol affect the satellite derived CCN vs CDNC correlations. In this study, we focus on ocean regions determining how these different atmospheric properties affect the derived slope between CCN and CDNC. Our results indicate that as satellite derived CCN is a columnar value, does not properly represent the true variability of cloud base CCN. Thus, the mixing of aerosol as well as cloud activation updrafts cause biases in the satellite determined CCN vs CDNC correlations.

Ground‐based temperature and water vapor profiling of the atmosphere of Mars point to large annual variations in the water vapor saturation altitude, or hygropause, of the entire low‐to middle‐latitude atmosphere, as forced by the elliptical Mars orbit [Clancy et al., 1996]. We examine the effects of such an annual variation in the hygropause altitude (from &lt;10 km to &gt;30 km) on the photochemistry of the Mars atmosphere. The one‐dimensional, diffusive transport photochemical model of Nair et al. [1994] is run in a diurnally averaged mode for time‐dependent calculations of the annual behavior of Mars photochemistry at low to middle latitudes. The model incorporates a specified annual variation of the water vapor profile, based on the microwave observations of Mars water vapor and temperature profiles versus season (solar longitude, Ls). Due to their long photochemical lifetimes, Mars CO and O2 are expected and found to be in significant non‐equilibrium with the annually varying water vapor (and hence HOx) densities, and to present nearly constant abundances representative of the annual average water vapor profile. In contrast, Mars O3 has a photochemical lifetime of hours, and exhibits very large annual variations in response to the annual variation in the hygropause altitude. The global‐scale abundance of O3 at altitudes of 20–40 km is predicted to vary from &gt;109 cm−3 around Mars aphelion (northern spring/summer, Ls = 71°) to ∼108 cm−3 around Mars perihelion (southern spring/summer, Ls = 251°). These model ozone variations are discussed in the context of the disparate Mars 5 (1974 [Krasnopolsky and Parshev, 1979]) and Phobos (1989 [Blamont and Chassefière, 1993]) measurements of low‐latitude ozone densities at 35–50 km altitude, as well as Hubble space telescope observations of enhanced low‐latitude ozone during the 1995 aphelion of Mars [Clancy et al., this issue].

Low-level mixed-phase clouds (LLMPCs) containing both ice and supercooled liquid water are ubiquitous in the Arctic and play a crucial role for radiative fluxes. Mixed-phase clouds are inherently instable due to the competition over water between ice crystals and liquid droplets. The persistence of LLMPCs in the Arctic is challenging to reproduce in models, which affects predictions of the energy budget. These challenges stem from current uncertainties related to the complex web of interactions between aerosol particles, cloud microphysics, atmospheric (thermo-)dynamics and surface processes. These uncertainties can be partly attributed to the scarcity of detailed observations of aerosol characteristics and cloud microphysical properties as well as their interactions within clouds.LLMPCs highly depend on the presence of aerosol particles acting as cloud condensation nuclei (CCN) or ice nucleating particles (INPs). In the Arctic, where aerosol concentrations can be very low, small changes in aerosol properties (e.g., size, chemical composition, hygroscopicity) can significantly impact the radiative properties and lifetime of LLMPCs. Accurate knowledge of aerosol characteristics at cloud level and their influence on cloud properties is crucial for improving the representation of clouds and their radiative behavior.To address the need for more observations of aerosols and cloud properties at cloud level, a tethered-balloon equipped with the Modular Multiplatform Compatible Air Measurements System (MoMuCAMS) was deployed from the Swedish icebreaker Oden during the Atmospheric River and onset of sea ice melt (ARTofMELT) expedition. The expedition took place in the Fram Strait during the transition from spring to summer (May &amp;#8211; June) in 2023. In total, 23 flights up to 645 m above mean sea level were performed, collecting unique and detailed measurements of aerosol and cloud droplet size distributions from 8 nm to 50 &amp;#181;m, below, inside and above LLMPCs. A key aspect addressed with the measurements is how boundary layer and free tropospheric aerosols contribute to the formation of clouds.Results from of a case study examining the data collected from three consecutive flights through a single cloud layer located between roughly 150 and 350 meters above the surface will be presented. A combination of in situ vertical and surface-based measurements with remote sensing data and modeling studies is used to understand to what extent aerosols from below and above the cloud contribute to the formation of cloud droplets. Results indicate that the cloud is coupled to the surface and profiles of particle number size distributions show a homogenous distribution between the surface and the cloud. A comparison between estimated CCN concentrations below and above the cloud and observed cloud droplet number concentrations suggests however, that entrainment of aerosol from the free troposphere is needed to produce the amount of droplets observed.These observations suggest that also when clouds are coupled to the surface, a different and significant source of CCN and INPs can feed the cloud from above, which is then not observable from surface-based measurements. This can have important implications for the representation of cloud microphysical and radiative properties based solely on surface-based observations.

The production and subsequent emission of volatile compounds is one of the numerous ways by which microbial plankton participate in the cycling of elements and influence the Earth's climate. Dimethylsulfide (DMS), produced by enzymatic decomposition of the algal intracellular compound dimethylsulfoniopropionate (DMSP), is the more abundant organic volatile in the upper ocean. Its global emission amounts ca. 28 Tg S per year, and represents the main biogenic source of sulfur to the troposphere and about 30% of the total S emission (anthropogenic, biogenic and volcanic). Atmospheric oxidation of DMS contributes to atmospheric acidity, and is believed to promote the formation and growth of aerosols. Furthermore, DMSderived sulfate aerosols have been suggested to cool the climate by reducing the amount of shortwave solar radiation reaching the Earth's surface through two mechanisms: by scattering solar radiation and, more important, by acting as cloud condensation nuclei, thus making clouds brighter and longerlived. The `CLAW' hypothesis postulates that, if oceanic DMS emission was in turn stimulated by solar radiation, a regulatory feedback mechanism could operate between marine plankton and the radiative budget over the oceans. However, the relationship between DMS emission and solar radiation is not straightforward, since a number of biochemical and photochemical transformations come into action from the moment DMSP is synthesized by phytoplankton until DMS is emitted. These transformations are intimately linked to the physical environment, the ecological setting and the microbial interactions, rendering the picture of dimethylated sulfur cycling a lot more complicated. Surprisingly, though, the seasonal cycle of seawater DMS concentration seems to follow that of solar radiation in the majority of oceanic regions, regardless their productivity regimes. The premise of this thesis is that, to understand this emerging pattern, we need to understand what regulates the DMS production and consumption processes and their balance (that is, DMS budgets). To this end, we have studied the response of biotic and abiotic DMS cycling to solar radiation by means of incubation experiments. At another level, we have studied the response of ecosystem DMS budgets to different radiation climates. Since the depth of the upper mixed layer regulates the amount and spectral composition of the `light' seen by the cells and molecules, our studies have been backed by a careful characterization of underwater radiation fields and vertical mixing dynamics. Our results show that solar radiation has a stimulating effect on gross DMS production. Moreover, the stimulation is more effective at shorter and more energetic wavelengths in the ultraviolet (UV) region. Direct DMS production and/or increased DMSP release by UVstressed phytoplankton is the most plausible explanation for this observation, leaving a secondary role for DMS production mechanisms related to bacterial metabolism and microzooplankton grazing. At the ecosystem level, we have shown that vertical mixingmediated solar exposure regulates whether DMS is preferentially oxidized by bacteria or by photochemical reactions. The outcome of this competition between DMS sinks is that total DMS loss rate constants vary little across oceanic biomes. As a result, the seasonal and also the shortterm variability in DMS concentrations respond mainly to gross DMS production. The stress response occurs at different temporal scales: seasonally, through the succession of microbial communities towards stronger DMSP producers and higher DMS yields in summer stratified waters; and across daynight cycles, where shortterm radiative stress modulates DMSP to DMS conversion yields. By means of a literature metaanalysis, we have improved the current understanding of the different DMS(P) cycling regimes and their links with the ecological geography of the sea.

IntroductionIn Titan’s atmosphere and on its surface, methane plays a crucial role in the global climate. Since the methane cycle resembles Earth’s water cycle, and one important aspect of Earth’s water cycle is infiltration into the ground and storage in underground aquifers, it is reasonable to draw parallels. We know from the Cassini mission (2004 -2017) that methane precipitation occurs on Titan’s surface [1], and from the Huygens probe that the surface is moist [2]. It is therefore easy to imagine that, just like on Earth, methane infiltrates Titan’s soil, creating a subsurface cycle that alters the soil’s properties and its temperature. Certain aspects of the methane cycle are not well understood, and models struggle to reproduce some observations. The lack of data on many parameters of Titan’s soil and atmosphere makes accurate modeling challenging. Understanding the distribution of methane in the subsurface and its overall effect on surface temperature could improve the interpretation of observations of lakes and surface moisture, as well as predict regions of precipitation. Like the asymmetry of the seasons which creates an uneven distribution of methane across Titan’s surface and atmosphere. The Titan Planetary climate model of Titan, first developed at the Institut Pierre-Simon Laplace [3], is a useful tool for exploring the interaction between the surface and the atmosphere. Adding a subsurface model to this existing framework which already includes surface precipitation and evaporation would make it possible to visualize the distribution of methane within Titan’s soil and its interaction with atmospheric dynamics. The microphysical processes associated with the clouds of various species present in Titan PCM allow for a better representation of cloud formation through nucleation and condensation.2 Method and objectiveFor the inclusion of a liquid infiltration and diffusion model in Titan’s PCM, inspired by [4], the subsurface is given the ability to retain liquid methane within its layers. A liquid flux through a porous medium is added to the thermal transfer processes, based on mass conservation and Darcy’s law. The transfer of liquid mass within the subsurface impacts the soil’s energy balance. Transfers are calculated in three dimensions, with diffusion and gravity driving the movement of the liquid. Vertically, the gravitational potential dominates, but horizontally, the slope between a flat surface and that inferred from the topography is weaker. The subsurface reservoir creates methane storage zones that can become lakes, depending on the height of the saturated layer and Titan’s topography. A sufficiently detailed topography could reproduce methane basins where underground methane forms shorelines at the surface. This would affect the availability of surface methane. Many parameters, particularly the characteristics of the soil, remain unknown. By comparing model results to observations, refining the free parameters can provide estimates of Titan’s subsurface conditions such as soil porosity, tortuosity, and the degree of saturation with liquid methane. In this presentation we will present the result of simulations perfomed with the PCM that accounts for surface methane without and with interaction with the subsurface. We will focus on the difference in the cloud maps, precipitations and methane planetery flux in the atmoshere and in the subsurface. Several scenario will be considered and our model will be combared to available data.

Optical secondary eclipse measurements made by Kepler reveal a diverse set of geometric albedos for hot Jupiters with equilibrium temperatures between 1550 and 1700 K. The presence or absence of high-altitude condensates, such as Mg2SiO4, Fe, Al2O3, and TiO2, can significantly alter optical albedos, but these clouds are expected to be confined to localized regions in the atmospheres of these tidally locked planets. Here, we present 3D general circulation models and corresponding cloud and albedo maps for six hot Jupiters with measured optical albedos in this temperature range. We find that the observed optical albedos of K2-31b and K2-107b are best matched by either cloud-free models or models with relatively compact cloud layers, while Kepler-8b’s and Kepler-17b’s optical albedos can be matched by moderately extended (f sed = 0.1) parametric cloud models. HATS-11b has a high optical albedo, corresponding to models with bright Mg2SiO4 clouds extending to very low pressures (f sed = 0.03). We are unable to reproduce Kepler-7b’s high albedo, as our models predict that the dayside will be dominated by dark Al2O3 clouds at most longitudes. We compare our parametric cloud model with a microphysical cloud model. We find that even after accounting for the 3D thermal structure, no single cloud model can explain the full range of observed albedos within the sample. We conclude that a better knowledge of the vertical mixing profiles, cloud radiative feedback, cloud condensate properties, and atmospheric metallicities is needed in order to explain the unexpected diversity of albedos in this temperature range.

Destabilization of the water cycle threatens human lives and livelihoods. Meanwhile our understanding of whether and how changes in vegetation cover could trigger transitions in moisture availability remains incomplete. This challenge calls for better evidence as well as for the theoretical concepts to describe it. Here we briefly summarize the theoretical questions surrounding the role of vegetation cover in the dynamics of a moist atmosphere. We discuss the previously unrecognized sensitivity of local wind power to condensation rate as revealed by our analysis of the continuity equation for a gas mixture. Using the framework of condensation-induced atmospheric dynamics, we then show that with the temperature contrast between land and ocean increasing up to a critical threshold, ocean-to-land moisture transport reaches a tipping point where it can stop or even reverse. Land-ocean temperature contrasts are affected by both global and regional processes, in particular, by the surface fluxes of sensible and latent heat that are strongly influenced by vegetation. Our results clarify how a disturbance of natural vegetation cover, e.g., by deforestation, can disrupt large-scale atmospheric circulation and moisture transport: an increase of sensible heat flux upon deforestation raises land surface temperature and this can elevate the temperature difference between land and ocean beyond the threshold. In view of the increasing pressure on natural ecosystems, successful strategies of mitigating climate change require taking into account the impact of vegetation on moist atmospheric dynamics. Our analysis provides a theoretical framework to assess this impact. The available data for the Northern Hemisphere indicate that the observed climatological land-ocean temperature contrasts are close to the threshold. This can explain the increasing fluctuations in the continental water cycle including droughts and floods and signifies a yet greater potential importance for large-scale forest conservation.

Evapotranspiration (ET) is a critical term in the surface energy budget as well as the water cycle. There are few direct measurements of ET, and thus the magnitude and variability are poorly constrained at large spatial scales. Estimates of the annual cycle of ET over the Amazon are critical because they influence predictions of the seasonal cycle of carbon fluxes, as well as atmospheric dynamics and circulation. The authors estimate ET for the Amazon basin using a water budget approach by differencing rainfall, discharge, and time-varying storage from the Gravity Recovery and Climate Experiment. It is found that the climatological annual cycle of ET over the Amazon basin upstream of Óbidos shows suppression of ET during the wet season and higher ET during the dry season, consistent with flux-tower-based observations in seasonally dry forests. They also find a statistically significant decrease in ET over the time period 2002–15 of −1.46 mm yr−1. The direct estimate of the seasonal cycle of ET is largely consistent with previous indirect estimates, including energy-budget-based approaches, an upscaled station-based estimate, and land surface model estimates, but suggests that suppression of ET during the wet season is underestimated by existing products.

&amp;lt;p&amp;gt;Feedbacks between biosphere and other components of the Earth system are challenging to model accurately and therefore are often omitted or oversimplified in Earth system models (ESMs). However, their importance is increasingly recognized as rapid disturbances due to anthropogenic (e.g., deforestation) or natural (e.g. regional increase in fires) drivers are already observed.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here we couple the well established and comprehensively validated dynamic global vegetation model LPJmL5.1 (von Bloh et al., 2018) to an Earth System model CM2Mc (MOM5/AM2, Galbraith et al. 2011). We replace the simple static vegetation model LaD with LPJmL5.1 and couple the water- and energy cycle by using GFDL&amp;amp;#8217;s Flexible Modeling System (FMS). In order to stabilize the model performance, several adjustments to LPJmL5.1 had to be done, including the introduction of a subdaily cycle for the energy and water calculations, the implementation of a conductance of the soil evaporation and plant interception, the calculation of a canopy layer humidity, and the surface energy balance in order to calculate the surface and canopy layer temperature within LPJmL5.1.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The coupled system allows us to answer questions regarding ecosystem stability with a complete energy and water cycle. For example, changes in the vegetation have a large impact on atmosphere dynamics, which in turn affects precipitation and feeds back into vegetation growth and mortality. To examine this feedback a simple experiment is performed by deforesting the whole Amazon basin and replacing it with grassland. Our results show decreasing precipitation and increasing canopy temperature which becomes a stable climate state in this treeless scenario. Future applications of the coupled model may include the investigation of tipping points in the biosphere, the impact of different atmospheric CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; concentrations or climate change and land-use change scenarios.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;

Impacts of extreme weather events on highly eutrophic marine ecosystem (Rogoznica Lake, Adriatic coast)