This paper presents microphysical inference retrievals obtained from spectral polarimetry during the Relampago (Remote sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations) campaign. Spectral processing has been an essential part of weather radar moments estimation for a long period of time. Various processing can be performed in the spectral domain including precipitation detection in presence of strong clutter and noise, clutter & interference mitigation by algorithms such as GMAP, object-oriented filters and many more. However spectral applications to polarimetry have been rare. The C band CSU-CHIVO radar that was deployed in Cordoba region in Argentina between June 2018 and April 2019 during the Relampago campaign, recorded some of the tallest storms in the world characterized by strong wind shear, updrifts, turbulence and occurrence of severe hail and rain. The polarimetric spectrum in precipitation with rain and hail mixtures were characterized. This Spectral polarimetry revealed different spectral characteristics including multi-modal spectrum, spectral broadening, slopes in spectral differential reflectivity and lowering of coherency spectrum. These results characterized occurrence of mixed hydrometeor types in a radar resolution volume such as presence of rain and hail mixture, large drops formation and size sorting. Spectral displays are inherently noisy, and the paper also presented methodology to obtain clean quality spectrum implementing spectral quality index, that is used to process the observations and the results are presented.

Learning progressions provide a sequence, or progression, of concepts from naive to sophisticated. Astrobiology educators and scientists have identified the need to develop learning progressions for core, interdisciplinary concepts in astrobiology to support both educators of K-12 students to bring astrobiology concepts into their classrooms, and scientists to communicate with a range of audiences. The Astrobiology Learning Progressions resource organizes core concepts around the essential questions of astrobiology, and includes connections to the Next Generation Science Standards, progressed storylines, and concept boundaries for four levels: primary or adult naïve learners, elementary or emerging adult learners, middle school or building learner, and high school or sophisticated learner. The resource also links lesson plans and other learning materials to each core concept.

Eddies have two distinct properties known as eddy advection (K_GM ) and eddy diffusion (K_iso). These are parameterized by Gent-McWilliams [1990] (K_GM ) and Redi [1982] (K_iso), respectively, in low to moderate resolution global ocean models. Both processes play an active part in the uptake of tracers such as CO_2 and CFCs. The advective role of eddies is associated with slumping of isopycnals, whereas the diffusive role is associated with the down-gradient diffusion [Lee et al., 2007]. In this work we investigate, for the first-time, which eddy process plays a dominant role in controlling tracer distribution in models. The model (pyOM2) used in this work is a coarse-resolution (2°x 2°) global ocean model [Eden et al., 2014]. We use a suite of nine different experiments, each with different K_GM and K_iso values. An idealised passive tracer is introduced at the surface of the ocean after the model is well equilibrated and it evolves for 100 years. We found on decadal time scales eddy diffusion and eddy advection both play equally important roles in controlling tracer distribution. However, on the time scale of hundred years or more eddy advection dominates over eddy diffusion. Small K_GM values set the isopycnal slopes to be steep, which allows the tracer to easily penetrate the deep ocean along isopycnals. On the contrary, large K_GM values flatten the isopycnals and therefore tracer only weakly penetrates the deep ocean. Near Antarctica, large values of K_iso exert strong control over the tracer distribution and brings tracer rich water to depth.

The Hudson Bay Lowlands (HBL) is a vast continuous peatland in Northern Canada. The landscape is a mosaic of mostly bogs and fens, with more limited swamp, marsh, forest and open water. Owing to rapid rates of isostatic uplift, younger peats are found closer to the coasts of Hudson and James Bays, with fen-type peatlands somewhat more prevalent on these younger surfaces. More than 30 Pg of carbon have accumulated in the HBL over the Holocene. The rates of Holocene carbon accumulation vary considerably both spatially and temporally, with some sites showing more rapid rates of carbon accumulation in the first 2-3 millennia following peatland initiation. We evaluate here the hypothesis that vegetation changes over the course of the Holocene, including fen-to-bog transitions, partially explain the variability in carbon accumulation. We find that in some cases, more rapid rates of C accumulation in the middle Holocene (5000-8000 yrs before present) are associated with early successional minerotrophic fens with higher carbon densities. Fen-to-bog transitions are recorded in many peat cores collected from present day bogs; however, these transitions are time transgressive, and can depend on the time since initiation, suggesting that climate changes may play a secondary role, relative to hydrological changes and local ecological processes. Fens are highly prevalent in the HBL landscape (covering about 38% of land cover). Cores taken from present day fens and analyzed for carbon accumulation and vegetation change indicate that many fen sites have remained fens since peat initiation. Variability in rates of Holocene carbon accumulation within fen records which have not been subject to any major vegetation change may more closely reflect climate drivers.

Validation of cloud hydrometeors simulation from the global models is important issue as it pertains to the accuracy of climate predictions. In this study, the cloud hydrometeor data from Korean Integrated Model (KIM) is validated using different Reanalysis (ERAI, ERA5, and MERRA) and Satellite Observations (Cloudsat). In ERA5 products, cloud snow water and rain water are also available. Satellite observations are gridded to compare with model simulations. Cloud liquid water (Qc), Cloud snow water (Qs), Cloud ice water (Qi), Cloud rain water (Qr), Vapour mixing ratio (Qv) for January (dry) and July (wet seasons) of 2017 are considered for validation. BIAS and RMSE are calculated for comparison. To understand the vertical distribution of hydrometeors, contour frequency altitude diagrams (CFADs) are plotted. Early validation of KIM hydrometeors shows the reasonable estimate of different hydrometeors with KIM model showing more Qc at surface, more Qv at upper levels. The vertical structure of Qi has showed significant bias at upper levels with model showing large ice values at higher levels. ERAI and ERA5 products has showed distinct pattern of Qi due to different configurations. More Qs at upper levels is also evident in model simulations. Combined distribution (Qc+Qi) of KIM at lower (upper) levels is more comparable with ERA5 (MERRA) products. Further, Qr distribution shows underestimation at the equator and over estimation at the latitude belts. To examine the contribution of different physics modules related to the bias, the hydrometeors from cumulus, microphysics and shallow convection are also analyzed separately. Accuracy of KIM simulated cloud hydrometeors against different products and possible causes for biases will be discussed in the conference.

Western U.S. conifer forests harbor diverse ecological strategies that enable species to persist across a wide range of hydroclimate conditions, along with wildfire and eruptive insect outbreaks. Assessing climate influences on future forest composition and carbon sequestration requires vegetation process models that have sufficient ecological resolution to simulate this range of ecological variability. Here we present progress towards incorporating multiple shade and drought tolerance strategies in a vegetation demographic model parameterized for Western U.S. forests. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) to simulate a mixed conifer forest dominated by ponderosa pine and incense cedar in the Sierra Nevada Mountains of California. FATES resolves plant growth and respiration at the level of cohorts, defined by size and plant functional type. Incense cedar is shade and drought tolerant, while ponderosa pine is shade intolerant and the canopy dominant. We synthesized literature values of plant traits that correspond to important physiological and allometric parameters in FATES and conducted a sensitivity analysis within the observed parameter ranges with respect to carbon and water fluxes. Model output was benchmarked against carbon flux, water flux, and leaf area index measurements from the Critical Zone Observatory/AmeriFlux CZ2 site during 2010-2012. Specific leaf area, Vcmax, rooting distribution, and allometric equations had the most influence on simulated carbon and water fluxes. Final simulated average annual gross primary production (GPP) over 2010-2012 (1156 +- 79.2 gC/m2/yr) was 3.8% lower than observed GPP (1202 +-138.2 gC/m2/yr). Simulated evapotranspiration (ET, 373 +- 25 mm/yr) was 62% lower than measured ET (993 +-158 mm/yr). Simulated leaf area index (LAI, 1.2) was within the range of measured LAI (0.5-1.5). Preliminary analysis indicates underestimation of ET is likely due to an overestimation of soil water drainage. Our final parameter set allows pine and cedar coexistence to emerge from a bare ground initialization, and additional sensitivity testing of parameters important for coexistence are in progress. Clearly, observationally constrained parameters are critical for simulating ecosystem dynamics in Western U.S. forests.

Building design codes recommend using nonlinear dynamic analysis for an appropriate assessment of the seismic response of several types of structures. To perform nonlinear dynamic analysis, the recorded ground motion time histories of past events with a certain seismic intensity level compatible with the regional seismological characteristic are usually scarce. Therefore, alternative selection and scaling methods on the previously recorded ground motion data set are commonly employed to overcome this issue. However, the type of method and also the random characteristics of earthquake ground motion data induce variability in the estimation of structural response. In this paper, the effect of code-based ground motion selection approaches is investigated in predicting the seismic demand of masonry structures. The dynamic behavior of the masonry prototype is simulated through a 3D numerical model. The material non-linearities are taken into account by adopting a proper constitute law. The data set of PEER is used as the pool for selection and scaling based on alternative codes, including American standard and Eurocode. Results showed that alternative code-based selection approaches reach various seismic demand levels. Keywords: Ground motion records, PEER data set, Scaling, Code-based selection, Masonry structures, Incremental dynamic analysis

The Basque-Cantabrian basin is located in northern Spain in the westernmost part of the Pyrenees. It is a Mesozoic rift, inverted during the Tertiary. In this basin, a subsiding deep-water depocenter, called the Basque Trough formed during the Early Cretaceous, in response to the opening of the Bay of Biscay. In the Basque-Cantabrian basin, the Triassic salt-bearing red clays are exposed in several diapirs that display discordant contacts with the Mesozoic and the Tertiary successions, suggesting a long-lasting halokinetic growth at regional scale. The synthesis of previously published works, together with the analysis of the geological maps from the Spanish geological survey (IGME) as well as the building of new structural cross-sections, allows reviewing the history of halokinesis in the basin. At least four distinct areas may be defined according to the paleogeographical locations of the diapirs: the northern and southern margins of the Basque Trough, and the southern and eastern areas of the Basque-Cantabrian basin. In the northern margin of the Basque Trough, the Bakio and Gernika diapirs mainly recorded an Aptian-Albian growth history, although older and younger growth cannot be ruled out. These diapirs were growing in relatively deep-water environments and created some paleo-highs where isolated carbonate platforms developped. In the southern margin of the Basque Trough, the Villasana de Mena, Orduña, Murguía diapirs recorded an Early Cretaceous to Late Turonian growth evolution. These diapirs were growing in relatively shallow-water environments at the shelf of the southern margin. In the southern area of the Basque-Cantabrian basin, the Salinas de Rosío and Salinas de Añana diapirs recorded a Cretaceous salt growth in a shallow-marine to continental environment and the Tertiary reactivation during the inversion of the basin. The Salinas de Rosío diapir shows a salt glacier overlying the adjacent Tertiary Villarcayo Syncline that displays a mini-basin shape with a strong thinning of the Tertiary succession toward its margins. In the eastern area of the Basque-Cantabrian basin, five diapirs (Estella, Alloz, Salinas de Oro, Ollo and Anoz) are aligned along the Pamplona fault, that represent a Cretaceous transverse fault bounding the Basque Trough to the east. The Tertiary succession covers the older units masking the possible Cretaceous salt growth evolution. However, strong thinning of the Tertiary succession toward these diapirs together with the lateral facies changes highlights the Tertiary reactivation of these structures during the basin inversion. The compilation of all these data allows creating a geological chart that depicts the evolution of the salt structures through time and in the different areas of the Basque-Cantabrian basin.

Atmospheric ice-nucleating particles (INPs) from mineral dust and non-proteinaceous biological sources can influence cloud formation, precipitation, and Earth’s radiation budget due to their efficient freezing abilities. The ambient aerosol particles from these sources are abundant with ambient concentrations exceeding a few µg m^-3 for each type. Thus, the characterization of INPs and aerosol particles from these sources is important. We typically characterize their specific surface area (SSA), which is the primary variable to estimate their ice-nucleation active surface site density, using a sorbate gas, such as nitrogen. However, it is still uncertain how these particles interact with water vapor under subzero temperatures. To fill this gap, we used the 3Flex instrument (Micromeritics Instrument Corp.) with multiple sorbates to comprehensively characterize the nanoscale surface structure, pore size distribution, and accessibility to water molecules of a commercially available model proxy of mineral dust (illite NX) and cellulose materials. To date, we have completed more than 60 physisorption 3Flex experiments with various sorbates, such as CO2, H2O, Kr, and N2, for each sorbent. In particular, we examined SSA by water vapor sorption at temperatures relevant to atmospheric heterogeneous freezing (~ 0 to -20 °C). We will present our results as physisorption isotherms. In addition, our preliminary results of temperature-dependent SSA observed for micro- and nano-crystalline cellulose materials as well as illite NX will be discussed. Our preliminary result suggests that the SSA of illite NX is less temperature-dependent compared to the cellulose materials, which may be potentially swelling while interacting with water. Therefore, illite NX may be suitable for an INP test proxy.

The system of trade wind cumulus clouds observed during the RICO field project was simulated by an LES model over a 50x50 km2 domain size. Parameters of latent heat release were analyzed with the goal of parameterizing their effects on grids typical for NWP and large-scale models. Over 2000 clouds were examined focusing on relationship between parameters of latent heat release (phase transition rates) and dynamical/microphysical cloud characteristics. The phase transition rates (Tr), which in warm tropical clouds are represented by processes of condensation/evaporation, were analyzed by stratifying the clouds by their size/stage of maturity. The analyzed parameters included, among others, integral mass and buoyancy fluxes, cloud and rain water parameters. In our previous investigation we found that a remarkably strong correlation exists between Tr and upward mass flux (ℳ). The strong dependence of phase transition rates on ℳ, as well as linear relationship between Tr and ℳ, was explained by applying the condensation theory and the concept of “quasi-steady” supersaturation. The LES derived slope of the linear fit agreed with its theoretically predicted value with an error less than 5%. This result implies that supersaturation in clouds, on average, varies within a few percentage points of its quasi-steady value. The theory, as well as LES data, show that the Tr - ℳ linear fit is valid for local variables, and, therefore, may be integrated to obtain horizontal mean parameters. Expanding the Tr - ℳ relationship for vertically dependent horizontal mean variables, may provide the framework for development of sub-grid scale (SGS) latent heat release parameterization. It was also suggested that calculating the slope of the linear fit from concurrent measurements of temperature and vertical velocity, and comparing it with the theoretical slope based on the quasi-steady supersaturation assumption, may offer a method for estimating the supersaturation in clouds.

Researchers and end users using climate data face a challenge when they analyze the data they need. Data volumes are increasing very rapidly, and the ability to download all needed data is often no longer possible. Most of the climate analysis tools for research and application needs must use very large datasets, often distributed among several data centres and into a large quantity of files. This is especially true when they are stored in a federated architecture like the ESGF. One of these tools is icclim (https://github.com/cerfacs-globc/icclim ), a flexible python software package to calculate climate indices and indicators. This tool adhere as much as possible to metadata conventions such as CF, implementing also provenance information. It also aims at providing increasing support for all FAIR aspects. It is designed with performance and optimisation in mind, because the goal is to provide on-demand calculations for users. It provides the implementation of most of the international standard climate indices such as ECAD, ETCCDI, ET-SCI, including the correct methodology for calculating percentile indices using the bootstrapping method. It has been validated against R.Climdex as well (https://cran.r-project.org/web/packages/climdex.pcic/index.html ). The new 5.x version of icclim is now based on functions from the xclim python library, which was inspired by earlier versions of icclim, but using xarray and dask for data access and processing. icclim is also a candidate as the software to calculate climate indices for the C3S toolbox (https://cds.climate.copernicus.eu/cdsapp#!/toolbox ). icclim is integrated in the IS-ENES C4I 2.0 platform (https://climate4impact.eu/ ), using a Jupyter notebook collection in a SWIRRL environment (Software for Interactive Reproducible Research Labs https://gitlab.com/KNMI-OSS/swirrl ). Having access to this type of analysis tool is very useful, and seamless integration with front-ends like C4I enable the use of those tools by a larger number of researchers and end users. This project (IS-ENES3) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°824084.

The PRISM Data Library (DL) is designed to optimize the display, analysis, and retrieval of multiple domains datasets. Originally created for climate data, we aggregated data from agriculture and hydrology domains, as well as non-traditional domains for the DL such as ecology, finance, power outage and space weather data. These datasets range from simple geospatial point observations, to spatially gridded data products, to high-resolution satellite measurements, to GIS representation of administrative or domain-specific geographic entities. These datasets are represented in a consistent multi-dimensional (most often spatial and temporal) framework. As a result, dimension-wise comparisons are easily enabled through selection or transformation. Gridded data can be averaged over discrete geometrical entities (e.g. Counties, Bird Conservation Regions). The DL can be used in a browser, by connecting to servers at San Diego Supercomputing Center (SDSC) over the internet. Data selection, processing, and analysis are performed by the SDSC DL servers, and the resulting images or data files are sent back to the client’s desktop. This model optimizes the use of internet bandwidth.

We perform 3D simulations of seismic wavefields to clarify effects of strong reductions of shallow velocities on long-period seismic waves. The simulations use a reference community velocity model of Southern California and a modified version with strong velocity reductions in the top 500 m of the Los Angeles basin. Differences between wavefields generated by ten earthquakes in the reference and perturbed models are analyzed. Velocity changes are estimated by measuring relative time shifts between reference and perturbed seismograms using wavelet cross-correlation spectra. The results indicate that strong localized temporal velocity drops near the surface, such as those observed during strong ground motions, may generate regional perturbations of wavefields at periods up to 20 s. These perturbations may be misinterpreted as generated by temporal changes at seismogenic depths. The results also have important implications for waveform tomography studies.

Processes and timescales of magmas: U-series, 40Ar/39Ar chronology, and ternary feldspars, for the Quaternary Suswa volcano, Central Kenya Peralkaline Province, East African Rift Vanessa V. Espejel-García a, Elizabeth Y. Anthony b, Peter A. Omenda c, Alan L. Deino d, John C. White e a Facultad de Ingeniería, Universidad Autónoma de Chihuahua, Circuito No. 1, Campus Universitario 2, C.P. 31125, Chihuahua, Chih., México. b University of Texas at El Paso, El Paso, TX 79968, USA c Scientific and Engineering Power Consultants, P.0. Box 38991, Nairobi, Kenya d Berkeley Geochronology Center, Ridge Road, Berkeley, CA, 94709, USA. e Eastern Kentucky University, Richmond, KY 40475, USA Corresponding author. Vanessa V. Espejel-García, [email protected], Tel. (52) 614 221 7549. ORCID a 0000-0002-0486-8726 b 0000-0001-7951-1724 c —- d 0000-0002-0099-9382 e 0000-0001-5107-6847 Suswa is a Late Pleistocene to recent volcano in the axis of the East African Rift. Early activity saw construction of a trachytic shield volcano, followed by mafic-felsic magma mixing, explosive volcanism, and caldera collapse. Recent activity includes drawn down of the magma chamber to create a second, inner caldera, a resurgent dome, and eruption of phonolites (White et al., 2012, Lithos, 152, 88-104). 40Ar/39Ar ages for the initial shield volcano are ca. 110 ka. Formation of the outer caldera occurred at ca. 46 ka, and initial post-caldera eruptions followed soon thereafter at 32.5 ka. Final eruptions are ca. 11 ka to “zero age”. 230Th/232Th confirms simultaneity of mafic eruptions in the peripheral fields and the youthfulness of the final events. The 203Th/232Th data also demonstrate that depth for initial magma generation lies below the spinel peridotite field within garnet peridotite. Ground deformation includes deflation of 4.6 cm from 1997 to 2000 (Biggs et al., 2009) and subsequent inflation of 4.3 +/- 0.8 cm/yr from 2015 to 2020 (Albino and Biggs, 2021, G3). Alkali feldspar from pre- and most syn-caldera has a limited compositional range. Feldspars in mingled lavas include bimodal distribution of these alkali feldspar and plagioclase identical in composition to similar-age cinder cones and fissure flows adjacent to the volcano. Alkali feldspar shifts to greater An content in the post-caldera phonolite. Oscillatory and tabular textures record rapid crystal growth and turbulence in the phonolite magma chamber. However, neither the textures nor the composition range necessitate renewed addition of mafic material.

Deep-sea δ18O records show a pronounced difference in Milankovitch periodicity between the Early and Late Pleistocene. δ18O is interpreted as a proxy for ice sheet volume and temperature, which led to the conclusion that glacial-interglacial cycles considerably changed their rhythm during the mid-Pleistocene. This transition is referred to as the mid-Pleistocene Transition (MPT). Specifically, the precessional component of the Milankovitch cycles is absent in Early Pleistocene δ18O records, despite its continuous presence in solar insolation forcing to the ice sheets. Climate feedbacks involving (sea) ice, geological processes and carbon and nutrient cycling have been proposed as causes of this marked change. We however show that the absence of an Early Pleistocene precession signal in deep-sea δ18O records could be the result of destructive interference of the precessional cycle in the interior ocean. Such cancellation is caused by the anti-phasing of the precessional cycle between the North Atlantic and Southern Ocean deep-water sources (see Figure). We explore the potential for cancellation in the transient setup of the Total Matrix Intercomparison model for a wide range of source signal strengths. Our results show that cancellation can cause the absence of the precessional signal due to cancellation in the interior South-Atlantic, Indian and Pacific basins. Cancellation is especially widespread for a relative end-member contribution typical for the Early Pleistocene. We therefore conclude that the precessional component is likely incompletely archived in Early Pleistocene δ18O records, and appears as an actual change in Milankovitch periodicity across the MPT. Proxies not susceptible to cancellation of precession (such as those currently retrieved across the MPT from Antarctica) would be able to verify to what extent deep-sea δ18O correctly represents Pleistocene climate.

The watershed determined by Aburrá Valley system, located in northwestern Colombia, has significant urban development and steep hills. These features, together with the typical intense storms of the region, make the watershed prone to the occurrence of flash floods during the rainy seasons, affecting vulnerable communities. We propose a hybrid observational-modeling strategy to generate 30-minute discharge forecasts in different locations of the watershed, using an operational distributed hydrological model, information from stream gauges, and weather radar-derived precipitation using a quantitative precipitation estimation (QPE) technique. The forecast methodology is triggered when any stream gauge of interest reports levels over a predefined threshold. As a first step, the model uses different rainfall scenarios for the following 30 minutes. Every 5 minutes, the model forecast is executed after updating the observed rainfall and the rainfall scenarios. The scenarios correspond to (i) a lagrangian extrapolation of the precipitation fields, (ii) to a cellular automata-based extrapolation and to (iii) the last observed rain field multiplied by a time-varying ad-hoc factor based on historical event analysis. To parametrize the hydrological model and to validate the prediction methodology, we use 173 storm events from 2013 to 2018. The methodology is evaluated using the Nash coefficient, the Klin-Gupta index, differences in time-to-peak discharge, peak-discharge differences, and total storm-event volume differences. Operationally, the forecasted streamflow corresponds to the scenario with the best historical performance, given the total amount of observed rainfall. The overall results suggest that the described approach is promising. However, there are still some cases in which the method leads to discharge underestimation. Considering the forecast uncertainty, the results show that it is possible to design flash floods alerts using this simple but robust methodology.

The frequency of major flooding events continues to increase, fueling the already growing concern in numerous fields about quantifying the inequitable distribution of flood hazards. Our previous work of overlaying high resolution flood exposure data with social vulnerability information has already begun to highlight how different communities experience varying levels of risk. However, this fails to capture the complex nature by which flooding affects interconnected infrastructure and service networks which further have an impact on an individual and community’s risk. Our goal is to quantitatively define an individual’s vulnerability to flooding, encompassing how both pluvial and fluvial inundation impacts an individual’s place of residence and disrupts their access to critical resources, including flood, gas, healthcare, and emergency services, while still considering an individual’s socioeconomic standing. With the goal of estimating household level disruption of access to critical resources in near real time, our approach relies on a multilayer network of social vulnerability, transportation infrastructure, essential resources, and emergency services. To estimate inundation in near real time, we utilize the Heigh Above Nearest Drainage (HAND) method and a topographic depression hierarchy algorithm to estimate fluvial and pluvial flooding. Using a minimum cost flow algorithm, we determine an individual’s relative cost to access resources before, during, and after a major flooding event. Combining technical and social information leads to the identification of communities that are more vulnerable to the physical, economical, and social components of floods. This model will be useful in future descriptive and prescriptive analytical frameworks by identifying critical nodes across networks and providing actionable knowledge on at risk communities. Our model will inform agencies involved in flood management, urban planning, and emergency response on where they can best apply resources to increase the resiliency of communities and the infrastructure they rely on.

There are records of past Earth climates that were ice-free all the way to the poles (Barron 1983), which can be described as “hothouse” climates. These hothouse climates can be contrasted with an “all-tropics” planet, where the tropics are defined by the atmospheric dynamics, i.e. the Hadley Cell extent (Faulk et al. 2017). This classification is thus primarily dependent on a planet’s rotation, rather than its ice-free extent or surface temperatures. We investigate the parameter space between Earth and an all-tropics world using the open-source GCM Isca, developed by Vallis et al (2018). We take an Earth analog and perform a parameter sweep in two dimensions: global reservoir depth (10m, 1m, 1cm) and rotation period (8 days, 4 days, 1 day). The sweep will allow us to explore the effects of surface liquid coverage and large-scale atmospheric circulation on an Earth-like climate. To better represent the distribution of surface water, we utilize the surface hydrology scheme developed by Faulk et al. (2020) for the Titan Atmosphere Model. In this presentation we provide a status report and analysis of initial findings.