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NASA NTRS1989

A study on cloud-radiation interaction

Most empirical studies estimating the climate sensitivity due to cloud amount are based on calculating a cloud sensitivity parameter by means of satellite measurements. A different way to estimate the interaction between clouds and radiation is to determine the effect of radiative heating and cooling by clouds on the generation of available potential energy (GAPE). This provides a measure of the influence of clouds on the general circulation. The radiative contribution of clouds to the GAPE is given by the net cloud generated radiative heating (CGRH) and an efficiency factor. The CGRH, parameterized in terms of cloud type, height, and optical depth, can be estimated from satellite measurements. The efficiency factor is only a function of the temperature distribution of the atmosphere. Thus, taking satellite measurements as for instance those of the ISCCP, the radiative impact of clouds on the general circulation can be inferred.

Stuhlmann, R.↗
DOE OSTI2021

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗
NASA NTRS2021

Improving the Representation of Subtropical Boundary Layer Clouds in the NASA GEOS Model with the Eddy-Diffusivity/Mass-Flux Parameterization

A systematic underestimation of subtropical planetary boundary layer (PBL) stratocu-mulus clouds by the GEOS model has been significantly improved by a new Eddy-Diffusivity/Mass-Flux (EDMF) parameterization. The EDMF parameterization representsthe subgrid-scale transport in the dry and moist parts of the PBL in a unified mannerand it combines an adjusted eddy-diffusivity PBL scheme from GEOS with a stochasticmulti-plume mass-flux model. The new EDMF version of the GEOS model is first com-pared against the CONTROL version in a single-column model (SCM) framework for twobenchmark cases representing subtropical stratocumulus and shallow cumulus clouds, andvalidated against large eddy simulations. Global simulations are performed and comparedagainst observations and reanalysis data. The results show that the EDMF version of theGEOS model produces more realistic subtropical PBL clouds. Noteworthy, the EDMF im-provements first detected in the SCM framework translate into similar improvements of theglobal GEOS model.

Kay Suselj↗
DOE OSTI2023

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Subseasonal Tropical Convection Characteristics in the Energy Exascale Earth System Model Version 2

Accurate simulation of subseasonal tropical moist convection remains a key challenge for Earth system models. The difficulties stem from the reliance of cumulus cloud processes on model parameterizations and the need to represent the multiscale nature of interactions among clouds, radiation, moisture, circulation, and surface energy fluxes. Equatorial convection drives circulation anomalies that can affect weather patterns and extremes globally, motivating efforts to better understand and simulate these tropical disturbances. Here, a detailed review of subseasonal tropical convective behavior as simulated in the Energy Exascale Earth System Model version 2 (E3SMv2) is presented, with comparison to its predecessor version 1 (E3SMv1) and reference data sets. Model structural changes to the deep convective trigger function and surface fluxes, along with parametric tuning of the cloud and microphysics schemes, together result in an improved depiction of organized tropical convection across scales. In particular, E3SMv2 exhibits a more realistic Madden‐Julian oscillation (MJO) and low‐frequency Kelvin waves—owing to a sharper time mean equatorial meridional moisture gradient and improved convection‐circulation coupling —as well as a better depiction of MJO Northern Hemisphere teleconnections. Despite these improvements, subseasonal precipitation variance continues to be strongly underestimated in E3SMv2. Use of a cloud plume model also reveals that the coupling between daily averaged tropical precipitation and lower tropospheric instability in E3SM is inconsistent with observations, a bias that could potentially impact the simulation of intraseasonal disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Project Title: Adaptive Vertical Grid Enhancement for E3SM (Final Technical Report)

During the first phase of the project (2018/05-2021/05), we proved the hypothesis that, without tuning, high vertical resolution improves the representation of unresolved, parameterized low altitude clouds such as stratocumulus clouds in global climate models. We evaluated the effectiveness of the newly developed computational framework, Framework for Improvement by Vertical Enhancement (FIVE) by implementing it into E3SM. FIVE aims to improve representation of the target cloud, low level cloud for this project, with use of a locally high vertical resolution for computation of selected processes. FIVE was assessed via direct comparison among E3SM, E3SM-FIVE, and satellite data as well as a newly developed ensemble artificial neural network methodology. We demonstrated that E3SM-FIVE remarkably improves marine stratocumulus representation. To advance the FIVE methodology, we took a first step toward the adaptive vertical grid in the FIVE method by modifying the E3SM single column model. For future application of FIVE to the global storm resolving model with a few km horizontal grid resolution, we developed the vertical-meridional two-dimensional (2D) Hadley circulation model, which allows one to run simulations with much higher vertical resolution and significantly longer duration than current three-dimensional global storm resolving model. During the second phase of the project (2021/05-2023/11; period for this technical report), we sought a way to appropriately transform FIVE to a regionalized version of FIVE, which allows one to select locations with/without FIVE. In parallel, we demonstrated that E3SM-FIVE with a 25-km mesh significantly reduced the bias associated with coastal stratocumulus. Furthermore, we showed that the same improvement was able to be obtained with the use of both the Regional Refined Model (RRM) targeted to one of the stratocumulus regions with 25-km resolution and FIVE. We explored a new implementation strategy of FIVE with our 2D Hadley circulation model. In parallel we applied the 2D Hadley circulation model to study the double intertropical convergence zone bias with storm resolving model resolution and aerosol-cloud interactions within the Hadley circulation with near large eddy simulation resolution. Last, we have been investigating Arctic mixed-phase stratocumulus clouds with large eddy simulations in order to improve their representation in global models. During the course of the entire project, 6 journal articles were published, and 3 manuscripts are currently in preparation. We gave a total of 30 presentations at various domestic and international conferences. In addition we gave 6 seminar talks at universities and a national laboratory. E3SM- FIVE is available as a branch of E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA

Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.

Liang, Jiakun [University of Hawai'i at Manoa] (OR↗
NASA NTRS1982

Cloud/climate sensitivity experiments

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Roads, J. O.↗
NASA NTRS1987

Closure assumptions in the cumulus parameterization problem

While concentrating on the thermodynamical aspects of parameterizing deep cumulus clouds, some of the existing schemes are reviewed with an emphasis on their closure assumptions. It is shown that the closure assumptions in these schemes are some combination of four types. It is emphasized that observations should be used more extensively than in the past to directly verify and improve closure assumptions and to assess the limit of parameterizability. As an example, results from an analysis of the macroscopic behavior of moist convection are presented. The results suggest that cumulus clouds are basically parameterizable, in spite of the existence of mesoscale organization.

Arakawa, Akio↗
NASA NTRS2003

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) observations and it is based on models that simulate high-resolution brightness temperatures as functions of observed reflectivity profiles and a parameter related to the rain drop-size-distribution. The modeled high-resolution brightness temperatures are used to determine normalized brightness temperature polarizations at the microwave radiometer resolution. An optimal estimation procedure is employed to minimize the differences between the simulated and observed normalized polarizations by adjusting the drop-size-distribution parameter. The impact of other unknowns that are not independent variables in the optimal estimation but affect the retrievals is minimized through statistical parameterizations derived from cloud model simulations. The retrieval technique is investigated using TRMM observations collected during the Kwajalein Experiment (KWAJEX). These observations cover an area extending from 5 deg to deg N latitude and 166 deg to 172 deg E longitude from July to September 1999, and are coincident with various ground-based observations, facilitating a detailed analysis of the retrieved precipitation. Using the method developed in this study, precipitation estimates consistent with both the passive and active TRMM observations are obtained. Various parameters characterizing these estimates, i.e. the rain rate, the precipitation water content, the drop-size-distribution intercept, and the mass weighted mean drop diameter, are in good qualitative agreement with independent experimental and theoretical estimates. Combined rain estimates are in general higher than the official TRMM Precipitation Radar (PR) only estimates for the area and the period considered in the study. Ground-based precipitation estimates, derived from an analysis of rain gauge and ground radar data, are in better agreement with the combined estimates than with the TRMM PR-only estimates, which suggests that information useful for improving the radar-only estimates is contained in the brightness temperature data.

Grecu, Mircea↗
NASA NTRS2016

A42F-03: Small-Scale Variability in Tropical Tropopause Layer Humidity

Recent advances in statistical parameterizations of cirrus cloud processes for use in global models are highlighting the need for information about small-scale fluctuations in upper tropospheric humidity and the physical processes that control the humidity variability. To address these issues, we have analyzed high-resolution airborne water vapor measurements obtained in the Airborne Tropical TRopopause EXperiment (ATTREX) over the tropical Pacific between 14 and 20 km. Using accurate and precise 1-Hz water vapor measurements along approximately-level aircraft flight legs, we calculate structure functions spanning horizontal scales ranging from about 0.2 to 50 km, and we compare the water vapor variability in the lower (about 14 km) and upper (16-19 km) Tropical Tropopause Layer (TTL). We also compare the magnitudes and scales of variability inside TTL cirrus versus in clear-sky regions. The measurements show that in the upper TTL, water vapor concentration variance is stronger inside cirrus than in clear-sky regions. Using simulations of TTL cirrus formation, we show that small variability in clear-sky humidity is amplified by the strong sensitivity of ice nucleation rate to supersaturation, which results in highly-structured clouds that subsequently drive variability in the water vapor field. In the lower TTL, humidity variability is correlated with recent detrainment from deep convection. The structure functions indicate approximately power-law scaling with spectral slopes ranging from about minus 5 divided by 3, to minus 2.

water vapor↗
NASA NTRS2002

A New Statistically based Autoconversion rate Parameterization for use in Large-Scale Models

The autoconversion rate is a key process for the formation of precipitation in warm clouds. In climate models, physical processes such as autoconversion rate, which are calculated from grid mean values, are biased, because they do not take subgrid variability into account. Recently, statistical cloud schemes have been introduced in large-scale models to account for partially cloud-covered grid boxes. However, these schemes do not include the in-cloud variability in their parameterizations. In this paper, a new statistically based autoconversion rate considering the in-cloud variability is introduced and tested in three cases using the Canadian Single Column Model (SCM) of the global climate model. The results show that the new autoconversion rate improves the model simulation, especially in terms of liquid water path in all three case studies.

Lin, Bing↗
NASA NTRS2002

Coordinated Parameterization Development and Large-Eddy Simulation for Marine and Arctic Cloud-Topped Boundary Layers

The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.

Bretherton, Christopher S.↗
NASA NTRS1985

Preliminary GCM Results with a New Radiation Parameterization

A new parameterization of solar and terrestrial radiation was developed and tested. The solar radiation parameterization is based on that of Lacis and Hansen (1974), but with zenith-angle-dependent surface albedoes, and revised treatments of cloudiness. The terrestrial radiation parameterization is based on the work of Chou (1984) for water vapor, Chou and Peng (1983) for carbon dioxide, and Rogers (1968) for ozone, with a new parameterization of the effects of clouds. Results obtained were compared with the new parameterizations to those obtained with the earlier parameterization described by Schlessinger (1976). Several dramatic improvements came to light. For the most part these are related to the fact that the new terrestrial radiation paramerization includes the effects of the water vapor continuum, while the earlier parameterization does not. In the moist tropical planetary boundary layer (PBL) continuum emission leads to much stronger cooling of the PBL over the oceans. Over land, however, the cooling of the PBL is significantly reduced. The latter, somewhat paradoxical result is due to the strong diurnal cycle of the continental PBL. At night the shallow continental PBL is overlain by a moist layer created by mixing during the previous afternoon. The moist upper layer acts as a radiative blanket, reducing the time-averaged radiative cooling of the continental PBL.

Randall, D.↗
NASA NTRS2000

The Influence of Soil Moisture, Coastline Curvature, and Land-Breeze Circulations on Sea-Breeze Initiated Precipitation

Idealized numerical simulations are performed with a coupled atmosphere/land-surface model to identify the roles of initial soil moisture, coastline curvature, and land breeze circulations on sea breeze initiated precipitation. Data collected on 27 July 1991 during the Convection and Precipitation Electrification Experiment (CAPE) in central Florida are used. The 3D Goddard Cumulus Ensemble (GCE) cloud resolving model is coupled with the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, thus providing a tool to simulate more realistically land-surface/atmosphere interaction and convective initiation. Eight simulations are conducted with either straight or curved coast-lines, initially homogeneous soil moisture or initially variable soil moisture, and initially homogeneous horizontal winds or initially variable horizontal winds (land breezes). All model simulations capture the diurnal evolution and general distribution of sea-breeze initiated precipitation over central Florida. The distribution of initial soil moisture influences the timing, intensity and location of subsequent precipitation. Soil moisture acts as a moisture source for the atmosphere, increases the connectively available potential energy, and thus preferentially focuses heavy precipitation over existing wet soil. Strong soil moisture-induced mesoscale circulations are not evident in these simulations. Coastline curvature has a major impact on the timing and location of precipitation. Earlier low-level convergence occurs inland of convex coastlines, and subsequent precipitation occurs earlier in simulations with curved coastlines. The presence of initial land breezes alone has little impact on subsequent precipitation. however, simulations with both coastline curvature and initial land breezes produce significantly larger peak rain rates due to nonlinear interactions.

Baker, David R.↗
NASA NTRSDate not supplied

Impacts of aerosol size-dependent below-cloud scavenging on tropospheric aerosol in the NASA GEOS model

Wet deposition is the major sink for a suite of tropospheric aerosols, and thus largely affects the global distribution and lifetime of aerosols as well as the formation of clouds in the atmosphere. In this study, we implement the aerosol size-dependent below-cloud scavenging (BCS; washout) parameterization of Croft et al. (Atmos. Chem. Phys., 2009; hereafter referred to as C09) in the GOCART bulk aerosol scheme coupled with the NASA Goddard Earth Observing System (GEOS) model, and evaluate the simulated tropospheric aerosols against surface, airborne, and satellite observations. The current below-cloud scavenging in GOCART employs a first-order removal function with a constant scavenging coefficient that is independent of aerosol sizes and precipitation fluxes. The C09 BCS parameterization instead calculates aerosol below-cloud scavenging coefficients based on a size-dependent collision efficiency between aerosol particles and raindrops (or snow crystals). A look-up table of compiled collision efficiencies provides scavenging coefficients for sixty aerosol sizes and nine rain flux rates. We determine instantaneous coefficients according to the C09 BCS look-up table, precipitation fluxes, and a log-normal size distribution of aerosols. The implemented BCS parameterization tends to result in a large diversity of scavenging coefficient values with higher magnitudes, leading to more efficient scavenging. The model-simulated global mean tropospheric Pb-210 aerosol lifetime decreases from 7.4 days to 5.8 days. The separate consideration of rain and snow conditions in the scavenging coefficient lookup table leads to a bi-mode distribution of scavenging coefficients. These changes also cause increased mass fractions of smaller aerosols compared to the current simulation. We examine the impacts of the C09 BCS parameterization on the simulated aerosol vertical profiles, tropospheric lifetimes, and deposition fluxes through comparisons with NASA aircraft measurements (ATom), surface observations of aerosol concentrations (IMPROVE) and wet deposition fluxes (NADP and APQMP), and MODIS aerosol optical depth (AOD) retrievals.

Aerosols↗
NASA NTRS1993

Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. I - Parameterization of radiance fields

The impact of using phase functions for spherical droplets and hexagonal ice crystals to analyze radiances from cirrus is examined. Adding-doubling radiative transfer calculations are employed to compute radiances for different cloud thicknesses and heights over various backgrounds. These radiances are used to develop parameterizations of top-of-the-atmosphere visible reflectance and IR emittance using tables of reflectances as a function of cloud optical depth, viewing and illumination angles, and microphysics. This parameterization, which includes Rayleigh scattering, ozone absorption, variable cloud height, and an anisotropic surface reflectance, reproduces the computed top-of-the-atmosphere reflectances with an accruacy of +/- 6 percent for four microphysical models: 10-micron water droplet, small symmetric crystal, cirrostratus, and cirrus uncinus. The accuracy is twice that of previous models.

Minnis, Patrick↗
NASA NTRS2001

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

Evans, K. Franklin↗