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DOE OSTI2024

Use of physics to improve solar forecast: Part III, impacts of different cloud types

Cloud-type impacts present a great challenge to solar forecasting due to diverse and complex cloud-radiation interactions. This third part of our paper sequence seeks to address this challenge by quantifying the forecast accuracies under eight cloud types: cumulus (Cu), stratified clouds (St), altocumulus (Ac), altostratus (As), cirrostratus/anvil (Cr), cirrus (Ci), congestus (Co), deep convective clouds (Dc) across four physics-informed persistence models reported in Part I. To generalize the cloud impacts, the eight cloud types are further grouped into three cloud categories based on their common features: weak convective clouds, stratiform clouds, and strong convective clouds. Here, the decade-long (2001 ~ 2014) collocated measurements of irradiances and cloud types at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program South Great Plain (SGP) Central Facility site are used for model evaluation. Results reveal a clear performance hierarchy for global horizontal irradiance (GHI) and direct normal irradiance (DNI): best for weak convective clouds and cirrus, intermediate for stratiform clouds, and worst for strong convective clouds. Performance for diffuse horizontal irradiance (DHI) is less influenced by cloud types. Cloud albedo dominates all three irradiances for Dc, while both cloud albedo and cloud fraction are influential for other cloud types. A 12 %~33 % improvement in accuracy at 6-hour lead time compared to the benchmark smart model confirms the effectiveness of incorporating physics into the models for various cloud types; further improvements are expected by directly integrating cloud type information into forecasting models by modifying the physical formulation of cloud-radiation interaction, and/or using more advanced machine learning models.

14 SOLAR ENERGY↗
NASA NTRS2017

Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

MODIS BRDF OMI clouds NO2 GLER↗
DOE OSTI2022

Exploring dimethyl sulfide (DMS) oxidation and implications for global aerosol radiative forcing

Abstract. Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway and the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and, hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions, based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden and the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg S (+29 %) and 582 Gg S (+8.8 %), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is −0.11 W m−2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (−2.2 W m−2 in standard versus −1.7 W m−2, with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (−2.3 W m−2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading and the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Observations of the CO J=6-5 transition in starburst galaxies

Over the past several years, short-submillimeter observations of carbon monoxide's (CO) mid-J rotational levels have revealed the presence of a large amount of excited molecular gas in luminous giant molecular clouds in our Galaxy. Submillimeter lines are specific probes of excited material: collisional excitation of the level energy of 116 K above ground, and 6-5 transition's critical density is approximately 10(exp 6) cm(exp -3) in optically thin gas. Radiative trapping effects reduce the excitation requirements to some extent, but detection of the CO J=6-5 line is nearly indisputable proof of the existence of gas that is both warm and dense. The excitation conditions also imply that cool (T less than 20 K) molecular clouds within the beam neither emit nor absorb in the short-submillimeter lines; in our Galaxy, clouds with active massive star formation emit the strongest short-submillimeter CO rotational lines. We used these properties to explore the distribution of excited molecular material and physical conditions within the star formation regions of several classical starburst nuclei: NGC253, M82, and IC342. We have used the 6-5 transition as a thermometer of warm molecular gas in starburst nuclei, unambiguously finding that the nuclear molecular gas in starburst galaxies is substantially warmer than in typical disk clouds.

Harris, A. I.↗
NASA NTRS2000

North Atlantic Aerosol Single Scattering Albedos: TARFOX and ACE-2 Results and Their Relation to Radiative Effects Derived from Satellite Optical Depths

Bergstrom and Russell estimated direct solar radiative flux changes caused by atmospheric aerosols over the mid-latitude North Atlantic Ocean under cloud-free and cloudy conditions. They excluded African dust aerosols, primarily by restricting calculations to latitudes 25-60 N. As inputs they used midvisible aerosol optical depth (AOD) maps derived from AVHRR satellite measurements and aerosol intensive properties determined primarily in the 1996 IGAC Troposheric Aerosol Radiative Forcing Observational Experiment (TARFOX). Those aerosol intensive properties, which included optical depth wavelength dependence and spectra of single scattering albedo (SSA) and scattering asymmetry parameter, were also checked against initial properties from the 1997 North Atlantic Aerosol Characterization Experiment (ACE 2). Bergstrom and Russell investigated the sensitivity of their derived flux changes to assumed input parameters, including midvisible AOD, SSA, and scattering asymmetry parameter. Although the sensitivity of net flux change at the tropopause to SSA was moderate over the ocean (e.g., a SSA uncertainty of 0.07 produced a flux-change uncertainty of 21%), the sensitivity over common land surfaces can be much larger. Also, flux changes within and below the aerosol layer, which affect atmospheric stability, heating rates, and cloud formation and persistence, are quite sensitive to aerosol SSA. Therefore, this paper focuses on the question: "What have we learned from TARFOX and ACE 2 regarding aerosol single scattering albedo?" Three techniques were used in TARFOX to determine midvisible SSA. One of these derived SSA as a best-fit parameter in comparing radiative flux changes measured by airborne pyranometer to those computed from aerosol properties. Another technique combined airborne measurements of aerosol scattering and absorption by nephelometer and absorption photometer. A third technique obtained SSA from best-fit complex refractive indices derived by comparing vertical profiles of lidar backscatter, sunphotometer extinction, and relative size distribution. In ACE 2 midvisible SSA was determined both as a best-fit parameter in comparing measured and calculated flux changes at the surface and by combining nephelometer and absorption photometer measurements. The nephelometer/absorption-photometer results were obtained on the ACE 2 ship (10 m asl), at the Sagres, Portugal site at 50 m asl, and also on the Pelican aircraft. This paper presents and compares the TARFOX and ACE 2 SSA results from the above techniques for different situations (e.g., marine vs continental flows, "clean" vs polluted conditions). It also discusses the strengths and limitations of the techniques, including whether they describe the aerosol in its ambient state or as perturbed by sampling processes; whether they describe the aerosol at the surface, as a function of altitude, or integrated over a column; the ease of acquiring representative data sets; results obtained in tests of consistency with radiative flux changes, and the likelihood of various artifacts and errors.

Russell, P. B.↗
DOE OSTI2021

Afterpulse correction for micro-pulse lidar to improve middle and upper tropospheric aerosol measurements

Micro-pulse lidar (MPL) measurements have been widely used in atmospheric research over the past few decades. However, the MPL afterpulse noise has a large impact on the MPL aerosol measurement in the middle and upper troposphere, and an effective correction method is still lacking. Here, a new afterpulse correction approach is presented by using measurements with low-level optically thick clouds to act as the lids blocking atmospheric signals beyond the clouds completely. Examples are provided to illustrate the effectiveness of this correction method. Using one-year 2014 MPL measurements at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site, the impact of the correction on the aerosol measurements is quantified. The relative error (RE, %) of attenuated backscattering ratio (ABR) without the afterpulse correction is 30% and 190% at the height of 1.00 km and 9.00 km (AGL), and the RE is larger for weaker aerosol signals (ABR<2). The RE of linear depolarization ratio (LDR), which is significantly higher than that of ABR for a given aerosol layer, is highly non-linear above 3.00 km, with a value of 300%-900% for weak aerosols (ABR<2) above 3.00 km. Therefore, the afterpulse correction is critical for the middle and upper tropospheric aerosol observations. We demonstrated that our afterpulse correction can provide reasonable particle depolarization ratio (PDR) to properly identify dust aerosols. The newly developed method can be applied to long-term MPL measurements to support aerosol and mixed-phase/ice cloud interaction study at the NSA site.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

cloud top height↗
NASA NTRS2001

Consistency Study of Enhanced Shortwave Cloud Absorption Using GEBA Data

Under the support of this project, we have obtained the following results:(1) Shortwave radiative fluxes in current atmospheric general circulation models (GCMs) cannot simultaneously match Earth Radiation Budget Experiment (ERBE) at the top of the atmosphere (TOA) and Global Energy Balance Archive (GEBA) at the surface. This inconsistency of model results with observation is a result of insufficient absorption of solar radiation in the model atmosphere; (2) Current state-of-the art global datasets describing the energy balance of the atmosphere cannot close the atmospheric energy budget if algorithm-derived surface shortwave radiative fluxes are used. The deficient amount of 20 W/sq m is similar to the recently reported enhanced absorption of solar radiation in the atmosphere; (3) We have clarified several sampling problems in the analysis of the collocated monthly GEBA/ERBE data sets which are germane to the interpretation of the clear-sky absorption of shortwave radiation in the atmosphere. As a result, the collocated monthly ERBE/GEBA data can be effectively used to infer enhanced absorption of atmospheric radiation in measurements relative to models, but it cannot be unambiguously used to answer whether the enhanced absorption is in clouds or in clear sky. Other field data are needed to resolve this issue; and (4) Analysis of aircraft measurements during Atmospheric Radiation Measurement Enhanced Shortwave Experiment (ARESE) field campaign supports the enhanced absorption of solar radiation in clouds.

Zhang, Ming-Hua↗
NASA NTRS1983

A numerical investigation of the effects of cloudiness on mesoscale atmospheric circulation

The development of a comprehensive scheme for computing radiative transfer in a cloudy, stratified atmosphere is described, and the interactions of radiation, clouds, surface heating, and frictional processes are investigated utilizing a three-dimensional numerical weather prediction model. This model is described along with the design of a reliable radiative transfer scheme which allows any vertical moisture and temperature stratifications occurring within a numerical weather prediction model to be taken into account. Some preliminary results of sensitivity tests for three 24-hour simulations are depicted in order to identify the forecast fields which respond to change in atmospheric radiation induced by cloudiness.

Wong, V. C.↗
DOE OSTI2020

Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM

FIDASIM is a code that models signals produced by charge-exchange reactions between neutrals and ions (both fast and thermal) in magnetically confined plasmas. With the ion distribution function as input, the code predicts the efflux to a neutral particle analyzer diagnostic and the photon radiance of Balmer-alpha light to a fast-ion D α diagnostic, in addition to many other related quantities. A new, parallelized version of the Monte Carlo code FIDASIM has been developed in Fortran90 that is substantially faster than the original interactive data language version. Modified algorithms include more accurate treatments of the time dependent collisional-radiative equations that describe neutral energy levels, of the cloud of ‘halo’ neutrals that surround the injected neutral beam, and of finite Larmor radius effects. Enhanced physics capabilities include modelling ‘passive’ signals from cold edge neutrals, the ability to treat general three-dimensional magnetic confinement configurations, and calculations of diagnostic-specific weight functions that enable tomographic reconstructions of the fast-ion distribution function. Neutral beam attenuation, beam emission, and fast-ion birth profiles are also modelled. Finally, the new algorithms have been successfully validated against experimental data and new features have been tested through benchmarks between two independently developed versions of the code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1971

Indirect sensing of atmospheric temperature and water vapor using microwaves.

A prototype of the Nimbus E microwave spectrometer was flown in an airplane over various atmospheric and surface conditions. Effects of clouds and the terrestrial surface on the data are discussed. Using a multiple-regression statistical method of inverting the equation of radiative transfer, estimates of temperature and integrated contents of water vapor and liquid water in the atmosphere below the aircraft were made from the microwave data obtained at high altitude. These estimates are compared with direct measurements made by other experiments on board the aircraft, in both clear atmospheres and in the presence of clouds.

Rosenkranz, P. W.↗
NASA NTRS1986

Reply

A reply is made on behalf of the authors of Wiscombe et al. (1984) to comments of Hegg (1986) to the effect that the optically effective cloud drop radius r(eff) values used by Wiscombe are shown by more recent data to be underestimated. It is presently noted that cloud radiation studies have often not just used comparably small r(eff) values, but ignored large drops in calculations altogether, on the grounds that large drops must fall out of clouds very rapidly. Attention is given to total shortwave absorptivity, spectral albedo, and IR cooling rate near cloud tops.

Wiscombe, W.↗
NASA NTRS2009

Sensitivity of Boreal-Summer Circulation and Precipitation to Atmospheric Aerosols in Selected Regions: The Americas - Part 2

Aerosol perturbations over selected land regions are imposed in Version-4 of the Goddard Earth Observing System (GEOS-4) general circulation model (GCM) to assess the influence of increasing aerosol concentrations on regional circulation patterns and precipitation in four selected regions: India, Africa, and North and South America. Part 1 of this paper addresses the responses to aerosol perturbations in India and Africa. This paper presents the same for aerosol perturbations over the Americas. GEOS-4 is forced with prescribed aerosols based on climatological data, which interact with clouds using a prognostic scheme for cloud microphysics including aerosol nucleation of water and ice cloud hydrometeors. In clear-sky conditions the aerosols interact with radiation. Thus the model includes comprehensive physics describing the aerosol direct and indirect effects on climate (hereafter ADE and AIE respectively). Each simulation is started from analyzed initial conditions for 1 May and was integrated through June-July-August of each of the six years: 1982 1987 to provide a 6-ensemble set. Results are presented for the difference between simulations with double the climatological aerosol concentration and one-half the climatological aerosol concentration for three experiments: two where the ADE and AIE are applied separately and one in which both the ADE and AIE are applied. The ADE and AIE both yield reductions in net radiation at the top of the atmosphere and surface while the direct absorption of shortwave radiation contributes a net radiative heating in the atmosphere. A large net heating of the atmosphere is also apparent over the subtropical North Atlantic Ocean that is attributable to the large aerosol perturbation imposed over Africa. This atmospheric warming and the depression of the surface pressure over North America contribute to a northward shift of the inter-Tropical Convergence Zone over northern America, an increase in precipitation over Central America and the Caribbean, and an enhancement of convergence in the North American monsoon region.

Wilcox, E. M.↗
NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS2005

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial-lkm scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard wlll be is presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗