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At least 127 records · Page 7

Synoptic Weather Regime Classifications for June, July, August, from 2000 to 2024

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A).

node_som_ml↗

Synoptic Weather Regime Classifications for March, April and May, from 2000 to 2025

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A).

node_som_ml↗

Synoptic Weather Regime Classifications for June, July and August, from 2000 to 2025

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A).

node_som_ml↗

Synoptic Weather Regime Classifications for December, January and February, from 2000 to 2025

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A).

{node_som_ml,synop_wea_reg}↗

Synoptic Weather Regime Classifications for September, October and November, from 2000 to 2025

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A).

node_som_ml↗

Low-frequency cloud-radiation interactions

The observed 30 to 60 day oscillation of the tropical winds, often referred to as the Madden Julian (MJ) oscillation, has excited lots of interest in recent years, because its existence suggests the possibility that the behavior of the atmosphere is at least partially predictable on such relatively long time scales. Most theories of the MJ oscillation have been based on the wave instability theories, such as wave-CISK (conditional instability of second kind). As discussed by Hu and Stevens (HS), these theories have not yet satisfactorily explained the observations. Recently, HS have suggested that the MJ oscillation is actually a forced response to periodic heating. They suggest that the forced oscillations originates in the hydrologic cycle, without the active participation of large scale dynamics. According to their model, the oscillation originates in a progressive build up of atmospheric water vapor, which continues until a (prescribed) threshold is reached, after which precipitation begins and rapidly dries the atmosphere. The drying due to a precipitation episode is followed by renewed gradual moistening, and the cycle continues indefinitely in this way. Preliminary results are presented from a 1-D version of the Randall et al. GCM, which lends further support to the ideas of HS. The present 1-D results also differ in important ways from those of HS, however. In particular, cloud radiation effects are essential for the oscillatory behavior of the model, although they are not essential in the model of HS.

Randall, David A.↗

Sensitivity of Precipitation in Coupled Land-Atmosphere Models

The project objective was to understand mechanisms by which atmosphere-land-ocean processes impact precipitation in the mean climate and interannual variations, focusing on tropical and subtropical regions. A combination of modeling tools was used: an intermediate complexity land-atmosphere model developed at UCLA known as the QTCM and the NASA Seasonal-to-Interannual Prediction Program general circulation model (NSIPP GCM). The intermediate complexity model was used to develop hypotheses regarding the physical mechanisms and theory for the interplay of large-scale dynamics, convective heating, cloud radiative effects and land surface feedbacks. The theoretical developments were to be confronted with diagnostics from the more complex GCM to validate or modify the theory.

Neelin, David↗

The Regional Influence of the Arctic Oscillation and Arctic Dipole on the Wintertime Arctic Surface Radiation Budget and Sea Ice Growth

An analysis of 2000-2015 monthly Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled (CERES-EBAF) and Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) data reveals statistically significant fall and wintertime relationships between Arctic surface longwave (LW) radiative flux anomalies and the Arctic Oscillation (AO) and Arctic Dipole (AD). Signifying a substantial regional imprint, a negative AD index corresponds with positive downwelling clear-sky LW flux anomalies (greater than10W m(exp -2)) north of western Eurasia (0 deg E-120 deg E) and reduced sea ice growth in the Barents and Kara Seas in November-February. Conversely, a positive AO index coincides with negative clear-sky LW flux anomalies and minimal sea ice growth change in October-November across the Arctic. Increased (decreased) atmospheric temperature and water vapor coincide with the largest positive (negative) clear-sky flux anomalies. Positive surface LW cloud radiative effect anomalies also accompany the negative AD index in December-February. The results highlight a potential pathway by which Arctic atmospheric variability influences the regional surface radiation budget over areas of Arctic sea ice growth.

Hegyi, Bradley M.↗

LongRunMIP - Motivation and Design for a Large Collection of Millennial-Length AO-GCM Simulations

LongRunMIP is the first collection of millennial-length simulations of complex coupled climate models and enables investigations of how these models equilibrate in response to radiative perturbations.We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1000+ year) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time-and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1000 years. LongRunMIP is a MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields, and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of summer 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submission of more simulations in the future.

Maria Rugenstein↗

TPSAS-NF1676L-23246-DND

The Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) was conducted from Fairbanks, Alaska during the September transition in the Beaufort-Chukchi Seas. Fifteen missions were flown with a NASA C-130 to characterize clouds, sea-ice, and associated radiative properties over a wide range of conditions. The advanced instrumentation payload included broadband and spectral radiometers, in-situ cloud probes, a laser altimeter and digital camera system. The flight profiles were tightly coordinated with multiple intersecting satellite overpasses allowing for a thorough evaluation of the Clouds and the Earth's Radiant Energy System (CERES) satellite climate data products. Thus, a rich dataset was acquired to help better understand cloud radiative effects as sea-ice conditions are changing due to arctic warming. The mission also acquired measurements to supplement the ongoing Operation Icebridge campaign. An overview of the mission operations, preliminary results, and a description of the datasets now available to the scientific community, will be presented.

William L Smith, Jr↗

Describing Seasonal Mixtures of Cloud Regimes Via “Regimes of Regimes”

We propose a new type of cloud classification, relevant to monthly or longer time scales, but which inherently still encompasses cloud subgrid variability information at ~100 km scales. Our proposed classification partitions frequencies of occurrence over these scales of previously defined cloud regimes (CRs). We call the resulting distinct cloud entities regimes of regimes (RORs). While the CRs have been previously shown to successfully classify daily mesoscale subgrid variability via distributions of cloud fraction within distinct combinations of cloud top pressure and cloud optical thickness, the RORs essentially represent the prevalent seasonal mixtures of these CRs. RORs thus embody the seasonal cloudiness of a mesoscale region. We show that each ROR can still be associated with more traditional cloud classifications via composites of coincident active (lidar and cloud radar) cloud views. In a first application that gauges the potential utility of RORs, we pair them with CERES EBAF radiative fluxes to gain insight into recent trends of the cloud radiative effect. The ROR corresponding to an environment of shallow convection stands out in this analysis largely because of its declining population. Our study demonstrates the potential of RORs to categorize globally mesoscale cloudiness at monthly/seasonal scales and to serve as proxies of different atmospheric states at these scales.

Nayeong Cho↗

A Somewhat Detailed Overview of Cloud Impact on the Earth's Radiation Budget

Using a recent edition of CERES EBAF data I will provide an overview of how present-day clouds affect the shortwave and longwave radiation budget of the planet as a whole, and separately its surface and atmosphere. The overview will make the point that different classes of clouds have distinct radiative effects which are also seasonally varying to a substantial degree. I will then show results from my recent work where cloud classes have been defined from active observations according to their vertical stratification. The observed contribution of the various classes to cloud radiative effect components will be detailed, followed by a comparison with a global model where a similar cloud decomposition yields mixed results about the verisimilitude of its cloud-radiation coupling. Time permitting, I will show how cloud classes allow us to build a framework to study the various factors that contribute to cloud radiative effect anomalies.

cloud radiative effect↗

Modeling the Radiative Effect on Microphysics in Cirrus Clouds against Satellite Observations

The radiative effect on microphysics 23 (REM) plays an important role in the dew/frost formation near the surface. How REM impacts cirrus clouds is investigated in this paper, using bin microphysical model simulations and coincident data of the CloudSat and Global Precipitation Measurement (GPM) satellites. REM affects ice crystal spectrum with two types: radiative cooling and warming. Radiative cooling, as predicted by the bin model simulations, favors the formation of horizontally oriented ice crystals (HOICs), but radiative warming does not. Hence, a test of REM can be transformed to a test of HOICs, because HOICs can be measured by the microwave polarization observations of the GPM Microwave Imager (GMI) at 166 GHz. To analyze the GMI data for their HOIC distribution, clouds are sorted into four groups with different optical depth and altitude, based on the radiative cooling/warming ratio (or eta) computed with satellite-retrieved ice water content. Their HOIC distributions (e.g., the mid-level thick clouds have more HOICs than the high-level ones) agree well with those predicted by the bin model simulations. The general agreement between the GMI observations and bin model simulations suggests that REM is common in cirrus clouds and impacts cirrus clouds significantly.

microphysics↗

Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

Varnai, Tamas↗

The Martian polar cap - Radiative effects of ozone, clouds, and airborne dust

The solar and thermal flux striking the polar cap of Mars is computed for various ozone, dust, and cloud abundances and for three solar zenith angles. Ozone does not significantly affect the total energy budget of the polar cap. Hence the observed hemispherical asymmetry in ozone abundance causes only an insignificant hemispherical asymmetry in the polar caps. Vertical optical depths of dust and cloud ranging from zero to 1 cause little change in the total flux absorbed by the polar cap near its edge but increase the absorbed flux significantly as one travels poleward. Hemispherical asymmetries in dust abundance, cloud cover, and surface pressure combine to cause a significant hemispherical asymmetry in the total flux absorbed by the residual polar caps, which helps to explain the dichotomy in the residual polar caps on Mars. Other processes which affect the energy budget of the polar cap are proposed and reviewed, particularly with respect to their interaction with the radiative effects of clouds and dust.

Lindner, Bernhard Lee↗

Inferring Cloud Properties from Passive Solar Sensors

The most common approach for retrieving cloud optical depth from ground-based observations uses downwelling fluxes measured by pyranometers and Multi-Filter Rotating Shadowband Radiometers (MFRSR). The key element in both retrieval techniques is the one-to-one mapping of the "observed" fluxes into cloud optical depth through plane-parallel radiative transfer. Both methods are expected to work well only for completely overcast clouds giving an effective optical depth for the whole sky. To infer cloud optical depth locally one can assume to use a narrow-field-of view radiometer that measures radiances instead of fluxes. However, lack of one-to-one relationships between radiance and cloud optical depth, prevents the direct use of radiances either. Here we discuss a new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (NIR) spectral regions. In addition to an algebraic combinations of spectral radiances such as Normalized Difference Cloud Index (NDCI) that largely removes nonuniqueness and the radiative effects of cloud inhomogeneity but can result in poor retrievals due to its insensitivity to cloud fraction, both RED and NIR radiances as points on the "RED vs. NIR" plane are proposed to be used for retrieval. The proposed retrieval method is applied to a multi- channel sunphotometer (as a part of AERONET) measurements at the ARM site in Oklahoma. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and MFRSR. In addition to cloud optical depth, the new retrieval method also infers a "radiatively effective" cloud fraction.

Marshak, A.↗

The Mars Dust Cycle: Investigating the Effects of Radiatively Active Water Ice Clouds on Surface Stresses and Dust Lifting Potential with the NASA Ames Mars General Circulation Model

The dust cycle is a critically important component of Mars' current climate system. Dust is present in the atmosphere of Mars year-round but the dust loading varies with season in a generally repeatable manner. Dust has a significant influence on the thermal structure of the atmosphere and thus greatly affects atmospheric circulation. The dust cycle is the most difficult of the three climate cycles (CO2, water, and dust) to model realistically with general circulation models. Until recently, numerical modeling investigations of the dust cycle have typically not included the effects of couplings to the water cycle through cloud formation. In the Martian atmosphere, dust particles likely provide the seed nuclei for heterogeneous nucleation of water ice clouds. As ice coats atmospheric dust grains, the newly formed cloud particles exhibit different physical and radiative characteristics. Thus, the coupling between the dust and water cycles likely affects the distributions of dust, water vapor and water ice, and thus atmospheric heating and cooling and the resulting circulations. We use the NASA Ames Mars GCM to investigate the effects of radiatively active water ice clouds on surface stress and the potential for dust lifting. The model includes a state-of-the-art water ice cloud microphysics package and a radiative transfer scheme that accounts for the radiative effects of CO2 gas, dust, and water ice clouds. We focus on simulations that are radiatively forced by a prescribed dust map, and we compare simulations that do and do not include radiatively active clouds. Preliminary results suggest that the magnitude and spatial patterns of surface stress (and thus dust lifting potential) are substantial influenced by the radiative effects of water ice clouds.

Kahre, Melinda A.↗

Radiative effects of the smoke clouds from the Kuwait oil fires

The radiative effects of the smoke from the Kuwait oil fires were assessed by measuring downwelling and upwelling solar flux, as well as spectral solar extinction beneath, above, and within the smoke plume. Seven radiation flight missions were undertaken between May 16 and June 2, 1991, to characterize the plume between the source region in Kuwait and approximately 200 km south, near Manama, Bahrain. Results are presented from one flight representative of conditions of the composite plume. On May 18, 1991, in a homogeneous, well-mixed region of smoke approximately 100 km downstream of the fires, visible optical depths as high as 2 were measured, at which time transmission to the surface was 8 percent, while 78 percent of the solar radiation was absorbed by the smoke. The calculated instantaneous heating rate inside the plume reached 24 K/d. While these effects are probably typical of those regions in the Persian Gulf area directly covered by the smoke, there is no evidence to suggest significant climatic effects in other regions.

Pilewskie, Peter↗