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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

High-Resolution Modeling of the Dust and Water Cycles with the NASA Ames Mars Global Climate Model

NASA’s Mars Climate Modeling Center at Ames Research Center is currently undergoing an exciting period of growth in personnel, modeling capabilities, and science productivity. We are transitioning from our legacy Arakawa C-grid finite-difference dynamical core to the NOAA/GFDL cubed-sphere finite-volume dynamical core for simulating the climate of Mars in a global framework. This highly parallelized core is scalable and flexible, which allows for significant improvements in the horizontal and vertical resolutions of our simulations. We have implemented the Ames water ice cloud microphysics package described in Haberle et al. (2018) into this new dynamical core. We will present high-resolution simulations of the dust and water cycles that show that sub-degree horizontal resolution improves the agreement between the vertical distribution of dust and water ice and observations. In particular, both water ice clouds and dust are transported to higher altitudes due to stronger topographic circulations at high resolution. Preliminary results suggest that high-resolution global modeling is needed to properly capture critical features of the dust and water cycles, and thus the current Mars climate.

Kahre, Melinda A.↗
DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗
NASA NTRS2022

Novel Parameterization of Ice Cloud Effective Diameter from Collocated CALIOP-IIR and CloudSat Retrievals

Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter D(e), that can be implemented for two separate applications: in numerical weather prediction models and lidar-based cloud radiative forcing studies. Ice cloud optical properties (i.e., spectral scattering and absorption) are estimated based on the effective size and habit mixture of the cloud particles. Historically, the ice cloud D(e) has been parameterized from aircraft in situ measurements. However, aircraft-based parameterizations are opportunistic in that they only represent specific types of clouds (e.g., convective anvil, tropopause-topped cirrus) in the regions in which they were sampled and, in some cases, are limited in fully resolving the entire vertical cloud layer. Breaking away from the aircraft-based parameterization paradigm, this study is the first of its kind to attempt a parameterization of D(e) as a function of temperature, ice water content (IWC), and lidar-derived extinction from satellite-based global oceanic measurements of ice clouds. Data from both active and passive remote sensing sensors from two of NASA’s A-Train satellites, CloudSat and CALIPSO, are collected to guide development of globally robust parameterizations of all ice cloud types and one exclusively for cirrus clouds.

Ice Cloud↗
NASA NTRS2011

Observational Evidence of Aerosol Enhancement of Lightning Activity and Convective Invigoration

Lightning activity over the West Pacific Ocean east of the Philippines is usually much less frequent than over the nearby maritime continents. However, in 2005 the Lightning Imaging Sensor (LIS) aboard the TRMM satellite observed anomalously high lightning activity in that area. In the same year the Moderate resolution Imaging Spectroradiometer (MODIS) measured anomalously high aerosol loading. The high aerosol loading was traced to volcanic activity, and not to any factor linked to meteorology, disentangling the usual convolution between aerosols and meteorology. We show that in general lightning activity is tightly correlated with aerosol loadings at both inter-annual and biweekly time scales. We estimate that a approximately 60% increase in aerosol loading leads to more than 150% increase in lightning flashes. Aerosols increase lightning activity through modification of cloud microphysics. Cloud ice particle sizes are reduced and cloud glaciation is delayed to colder temperature when aerosol loading is increased. TRMM precipitation radar measurements indicate that anomalously high aerosol loading is associated with enhanced cloud mixed phase activity and invigorated convection over the maritime ocean. These observed associations between aerosols, cloud microphysics, morphology and lightning activity are not related to meteorological variables or ENSO events. The results have important implications for understanding the variability of lightning and resulting aerosol-chemistry interactions.

Yuan, Tianle↗
NASA NTRS1999

Parameterizations of Depositional Growth of Cloud Ice in a Bulk Microphysical Scheme

Two aspects of the cloud ice parameterization in the Goddard Cumulus Ensemble Model cloud physics parameterization are examined: the conversion of cloud ice to snow by depositional growth, designated PSFI, and the saturation adjustment scheme. The original formulation of PSFI is shown to produce excessive conversion of cloud ice to snow because of an implicit assumption that the relative humidity is 100% with respect to water even though the air may actually be quite less humid. Two possible corrections to this problem are proposed, the first involving application of a relative humidity dependent correction factor to the original formulation of PSFI, and the second involving a new formulation of PSFI based on the equation for depositional growth of cloud ice. The sensitivity of these formulations of PSFI to the assumed masses of the ice particles is examined. Possible problems associated with using a saturation adjustment scheme for cloud ice are discussed and simulations of a squall line with and without application of the adjustment scheme for ice are compared.

Braun, Scott A.↗
NASA NTRS2007

Evaluation of a Cloud Resolving Model Using TRMM Observations for Multiscale Modeling Applications

The climate change simulation community is moving toward use of global cloud resolving models (CRMs), however, current computational resources are not sufficient to run global CRMs over the hundreds of years necessary to produce climate change estimates. As an intermediate step between conventional general circulation models (GCMs) and global CRMs, many climate analysis centers are embedding a CRM in each grid cell of a conventional GCM. These Multiscale Modeling Frameworks (MMFs) represent a theoretical advance over the use of conventional GCM cloud and convection parameterizations, but have been shown to exhibit an overproduction of precipitation in the tropics during the northern hemisphere summer. In this study, simulations of clouds, precipitation, and radiation over the South China Sea using the CRM component of the NASA Goddard MMF are evaluated using retrievals derived from the instruments aboard the Tropical Rainfall Measuring Mission (TRMM) satellite platform for a 46-day time period that spans 5 May - 20 June 1998. The NASA Goddard Cumulus Ensemble (GCE) model is forced with observed largescale forcing derived from soundings taken during the intensive observing period of the South China Sea Monsoon Experiment. It is found that the GCE configuration used in the NASA Goddard MMF responds too vigorously to the imposed large-scale forcing, accumulating too much moisture and producing too much cloud cover during convective phases, and overdrying the atmosphere and suppressing clouds during monsoon break periods. Sensitivity experiments reveal that changes to ice cloud microphysical parameters have a relatively large effect on simulated clouds, precipitation, and radiation, while changes to grid spacing and domain length have little effect on simulation results. The results motivate a more detailed and quantitative exploration of the sources and magnitude of the uncertainty associated with specified cloud microphysical parameters in the CRM components of MMFs.

Posselt, Derek J.↗
NASA NTRS2004

Comparison of Satellite and Aircraft Measurements of Cloud Microphysical Properties in Icing Conditions During ATREC/AIRS-II

Satellites are ideal for continuous monitoring of aircraft icing conditions in many situations over extensive areas. The satellite imager data are used to diagnose a number of cloud properties that can be used to develop icing intensity indices. Developing and validating these indices requires comparison with objective "cloud truth" data in addition to conventional pilot reports (PIREPS) of icing conditions. Minnis et al. examined the relationships between PIREPS icing and satellite-derived cloud properties. The Atlantic-THORPEX Regional Campaign (ATReC) and the second Alliance Icing Research Study (AIRS-II) field programs were conducted over the northeastern USA and southeastern Canada during late 2003 and early 2004. The aircraft and surface measurements are concerned primarily with the icing characteristics of clouds and, thus, are ideal for providing some validation information for the satellite remote sensing product. This paper starts the process of comparing cloud properties and icing indices derived from the Geostationary Operational Environmental Satellite (GOES) with the aircraft in situ measurements of several cloud properties during campaigns and some of the The comparisons include cloud phase, particle size, icing intensity, base and top altitudes, temperatures, and liquid water path. The results of this study are crucial for developing a more reliable and objective icing product from satellite data. This icing product, currently being derived from GOES data over the USA, is an important complement to more conventional products based on forecasts, and PIREPS.

Nguyen, Louis↗
NASA NTRS1999

The Dependence on Grid Resolution of Numerically Simulated Convective Cloud Systems Using Ice Microphysics

Mesoscale research and forecast models are increasingly being used at horizontal resolutions of 1-8 km to simulate a variety of precipitating systems. When the model is used to simulate convective systems, it is uncertain to what extent the dynamics and microphysics of convective updrafts can be resolved with grids larger than 1 km. In this study, two- and three-dimensional versions of the Goddard Cumulus Ensemble model are used to determine the impact of horizontal grid resolution on the behavior of the simulated storms and on the characteristics of the cloud microphysical fields. It will be shown that as resolution decreases from about 1 km to greater than 3 km, there is a fairly rapid degradation of the storm structure in the form of reduced convective mass fluxes, updraft tilts, and cloud microphysics. A high-resolution simulation of hurricane outer rainbands using the MM5 mesoscale model shows also that there can be a substantial modification of the key microphysical processes that contribute to rainfall as a result of reducing the horizontal resolution.

Braun, Scott A.↗
DOE OSTI2024

Partition between supercooled liquid droplets and ice crystals in mixed-phase clouds based on airborne in situ observations

Abstract. The onset of ice nucleation in mixed-phase clouds determines the lifetime and microphysical properties of ice clouds. In this work, we develop a novel method that differentiates between various phases of mixed-phase clouds, such as clouds dominated by pure liquid or pure ice segments, compared with those having ice crystals surrounded by supercooled liquid water droplets or vice versa. Using this method, we examine the relationship between the macrophysical and microphysical properties of Southern Ocean mixed-phase clouds at −40 to 0 °C (e.g. stratiform and cumuliform clouds) based on the in situ aircraft-based observations during the US National Science Foundation Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) flight campaign. The results show that the exchange between supercooled liquid water and ice crystals from a macrophysical perspective, represented by the increasing spatial ratio of regions containing ice crystals relative to the total in-cloud region (defined as ice spatial ratio), is positively correlated with the phase exchange from a microphysical perspective, represented by the increasing ice water content (IWC), decreasing liquid water content (LWC), increasing ice mass fraction, and increasing ice particle number fraction (IPNF). The mass exchange between liquid and ice becomes more significant during phase 3 when pure ice cloud regions (ICRs) start to appear. Occurrence frequencies of cloud thermodynamic phases show a significant phase change from liquid to ice at a similar temperature (i.e. −17.5 °C) among three types of definitions of mixed-phase clouds based on ice spatial ratio, ice mass fraction, or IPNF. Aerosol indirect effects are quantified for different phases using number concentrations of aerosols greater than 100 or 500 nm (N>100 and N>500, respectively). N>500 shows stronger positive correlations with ice spatial ratios compared with N>100. This result indicates that larger aerosols potentially contain ice-nucleating particles (INPs), which facilitate the formation of ice crystals in mixed-phase clouds. The impact of N>500 is also more significant in phase 2 when ice crystals just start to appear in the mixed phase compared with phase 3 when pure ICRs have formed, possibly due to the competing aerosol indirect effects on primary and secondary ice production in phase 3. The thermodynamic and dynamic conditions are quantified for each phase. The results show stronger in-cloud turbulence and higher updraughts in phases 2 and 3 when liquid and ice coexist compared with pure liquid or ice (phases 1 and 4, respectively). The highest updraughts and turbulence are seen in phase 3 when supercooled liquid droplets are surrounded by ice crystals. These results indicate both updraughts and turbulence support the maintenance of supercooled liquid water amongst ice crystals. Overall, these results illustrate the varying effects of aerosols, thermodynamics, and dynamics through various stages of mixed-phase cloud evolution based on this new method that categorizes cloud phases.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2

The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5°C) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new CESM2 schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time-step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed-phase clouds, which leads to an increase in cloud ice content and a weaker shortwave cloud feedback over mid-to-high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate-calibrated CESM2 (PaleoCalibr), which simulates well the observed twentieth century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (∼4°C) and a 20% weaker aerosol-cloud interaction than CESM2. PaleoCalibr represents a physically more consistent treatment of cloud microphysics than CESM2 and is a valuable tool in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

equilibrium climate sensitivity↗
NASA NTRS2020

Linkage among Ice Crystal Microphysics, Mesoscale Dynamics and Cloud and Precipitation Structures Revealed By Collocated Microwave Radiometer and Multi-Frequency Radar Observations

Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth’s radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and orientation) are not only influenced by ambient environment’s dynamic and thermodynamic conditions, but also intimately connect to the cloud radiative effects and particle fall speeds, which therefore impact up to the future climate projection and down to the details of the surface precipitation (e.g., onset-time, location, type and strength). Our previous work revealed that high-frequency Polarimetric radiance Difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that are often occur inside anvil clouds and/or stratiform precipitations. In this current work, we further investigate the dynamic/thermodynamic mechanisms and cloud/precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM-DPR, Ku/Ka bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally-oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or super-cooled water. Further, high (low) PD scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers respectively, suggesting the potential usefulness of PD as a proxy of stratiform/convective precipitation flag, as well as a proxy of convection life stage.

Ice crystal microphysics↗
NASA NTRS2015

IceCube: CubeSat 883-GHz Radiometry for Future Ice Cloud Remote Sensing

Ice clouds play a key role in the Earth's radiation budget, mostly through their strong regulation of infrared radiation exchange. Accurate observations of global cloud ice and its distribution have been a challenge from space, and require good instrument sensitivities to both cloud mass and microphysical properties. Despite great advances from recent spaceborne radar and passive sensors, uncertainty of current ice water path (IWP) measurements is still not better than a factor of 2. Submillimeter (submm) wave remote sensing offers great potential for improving cloud ice measurements, with simultaneous retrievals of cloud ice and its microphysical properties. The IceCube project is to enable this cloud ice remote sensing capability in future missions, by raising 874-GHz receiver technology TRL from 5 to 7 in a spaceflight demonstration on 3-U CubeSat in a low Earth orbit (LEO) environment. The NASAs Goddard Space Flight Center (GSFC) is partnering with Virginia Diodes Inc (VDI) on the 874-GHz receiver through its Vector Network Analyzer (VNA) extender module product line, to develop an instrument with precision of 0.2 K over 1-second integration and accuracy of 2.0 K or better. IceCube is scheduled to launch to and subsequent release from the International Space Station (ISS) in mid-2016 for nominal operation of 28 plus days. We will present the updated design of the payload and spacecraft systems, as well as the operation concept. We will also show the simulated 874-GHz radiances from the ISS orbits and cloud scattering signals as expected for the IceCube cloud radiometer.

cloud ice remote sensing↗
NASA NTRS2014

MLS and CALIOP Cloud Ice Measurements in the Upper Troposphere: A Constraint from Microwave on Cloud Microphysics

This study examines the consistency and microphysics assumptions among satellite ice water content (IWC) retrievals in the upper troposphere with collocated A-Train radiances from Microwave Limb Sounder (MLS) and lidar backscatters from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). For the cases in which IWC values are small (less than 10mg m(exp-23)), the cloud ice retrievals are constrained by both MLS 240- and 640- GHz radiances and CALIOP 532-nm backscatter beta(532). From the observed relationships between MLS cloud-induced radiance T(sub cir) and the CALIOP backscatter integrated gamma532 along the MLS line of sight, an empirical linear relation between cloud ice and the lidar backscatter is found: IWC/beta532=0.58+/-0.11. This lidar cloud ice relation is required to satisfy the cloud ice emission signals simultaneously observed at microwave frequencies, in which ice permittivity is relatively well known. This empirical relationship also produces IWC values that agree well with the CALIOP, version 3.0, retrieval at values, less than 10mg m(exp-3). Because the microphysics assumption is critical in satellite cloud ice retrievals, the agreement found in the IWC-beta532 relationships increase fidelity of the assumptions used by the lidar and microwave techniques for upper-tropospheric clouds.

ice water content↗
DOE OSTI2025

Advancing the Understanding of Cloud Microphysical Processes and Aerosol Indirect Effects in High-Latitude Mixed-Phase Clouds by Linking ARM Measurements with Climate Model Simulations (Final Report)

The key objectives of this project were to advance our understanding of cloud microphysical characteristics and aerosol indirect effects on mixed-phase clouds in high latitudes. To improve the representation of ice and mixed-phase clouds in Earth System Models (ESMs), we propose an integrated observation and modeling study of cloud macro- and microphysical properties, including spatial heterogeneities, mass partitioning between ice crystals and supercooled liquid water, effects of ice nucleating particles (INPs), and efficiency of secondary ice production (SIP), etc. Specifically, we took four main approaches in this project: (1) examining macro- and microphysical properties of ice and mixed-phase clouds based on in-situ and ground-based observations from multiple field campaigns funded by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program, including the Mixed-Phase Arctic Cloud Experiment (M-PACE), Indirect and Semi-Direct Aerosol Campaign (ISDAC), Ice Nucleating Particle Sources at Oliktok Point (INPOP), ARM West Antarctic Radiation Experiment (AWARE), Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS), and Macquarie Island Cloud and Radiation Experiment (MICRE); (2) evaluating the DOE Energy Exascale Earth System Model (E3SM) simulations based on observations, particularly for ice and mixed-phase cloud microphysical properties; (3) examining the impacts of INPs on ice and mixed-phase clouds. Specifically, a series of comparisons were conducted using observations over the Arctic, Southern Ocean, and Antarctica, including comparisons between the lower and higher southern latitudes as well as comparisons between the northern and southern hemispheres. In addition, aerosol indirect effects from distinct sources of dust particles were examined; and (4) investigating the impacts of SIP. Ultimately, these results helped to improve cloud microphysics and aerosol-cloud interaction parameterizations in the E3SM model. Overall, the project provided improved understanding regarding various factors, including thermodynamic, dynamic, and aerosol conditions, on the micro- and macrophysical properties of ice and mixed-phase clouds in the high latitudes. Resulting analysis helped to provide an improved physical basis for refining the current cloud microphysics parameterizations related to ice and mixed-phase clouds in E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Uncertainty quantification and optimization of precipitating hydrometeor parameters for winter precipitation in a cloud microphysics scheme

The precipitating hydrometeor parameters used in cloud microphysics schemes carry inherent uncertainties. The quantification of these uncertainties, together with parameter optimization, can significantly improve precipitation forecasts. This study investigates the effects of 13 parameters in the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme, which define the hydrometeor characteristics such as fall velocity–diameter and mass–diameter relationships, as well as the shape parameter of the drop size distribution for precipitating particles such as rain, snow, and graupel on simulated winter precipitation. A comparison between the model's pre-defined parameters and observations from the International Collaborative Experiments for the PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign reveals that the fall velocity–diameter relationship for rain, the mass–diameter relationships for snow and graupel, and the shape parameters for all precipitating particles in the WDM6 scheme deviate from the median values observed by the two-dimensional video disdrometer (2DVD). To quantify parameter sensitivities, a perturbed parameter ensemble (PPE) of 256 simulations was conducted within parameter ranges constrained by 2DVD observations for three winter precipitation cases. Bayesian optimization was then applied to identify parameter sets that minimized the root mean square error (RMSE) for each case, achieving reductions of up to 30.2 %. These results demonstrate that ensemble-based uncertainty quantification and parameter optimization can help identify key parameters and provide a pathway to improving precipitation simulation performance. In addition, measurement sites can be strategically selected based on regions that show high sensitivity to variations in hydrometeor characteristic parameters.

Bayesian optimization↗
NASA NTRS2006

An Intercomparison of Microphysical Retrieval Algorithms for Upper Tropospheric Ice Clouds

The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth's radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth's future climate. A number of passive and active remote sensing retrieval algorithms exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade, however, there is room for improvement. Members of the Atmospheric Radiation measurement program (ARM) Cloud properties Working Group are involved in an intercomparison of optical depth(tau), ice water path, and characteristic particle size in clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement.

Comstock, Jennifer M.↗
NASA NTRS2015

Incorporation of New Convective Ice Microphysics into the NASA GISS GCM and Impacts on Cloud Ice Water Path (IWP) Simulation

The CMIP5 configurations of the GISS Model-E2 GCM simulated a mid- and high latitude ice IWP that decreased by 50 relative to that simulated for CMIP3 (Jiang et al. 2012; JGR). Tropical IWP increased by 15 in CMIP5. While the tropical IWP was still within the published upper-bounds of IWP uncertainty derived using NASA A-Train satellite observations, it was found that the upper troposphere (200 mb) ice water content (IWC) exceeded the published upper-bound by a factor of 2. This was largely driven by IWC in deep-convecting regions of the tropics.Recent advances in the model-E2 convective parameterization have been found to have a substantial impact on tropical IWC. These advances include the development of both a cold pool parameterization (Del Genio et al. 2015) and new convective ice parameterization. In this presentation, we focus on the new parameterization of convective cloud ice that was developed using data from the NASA TC4 Mission. Ice particle terminal velocity formulations now include information from a number of NASA field campaigns. The new parameterization predicts both an ice water mass weighted-average particle diameter and a particle cross sectional area weighted-average size diameter as a function of temperature and ice water content. By assuming a gamma-distribution functional form for the particle size distribution, these two diameter estimates are all that are needed to explicitly predict the distribution of ice particles as a function of particle diameter.GCM simulations with the improved convective parameterization yield a 50 decrease in upper tropospheric IWC, bringing the tropical and global mean IWP climatologies into even closer agreement with the A-Train satellite observation best estimates.

tropical regions↗