scholarly journals Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

2013 ◽  
Vol 26 (19) ◽  
pp. 7734-7746 ◽  
Author(s):  
George Tselioudis ◽  
William Rossow ◽  
Yuanchong Zhang ◽  
Dimitra Konsta
Keyword(s):  
Clustering Algorithm ◽  
Dynamic Environment ◽  
Horizontal Distribution ◽  
Atmospheric Conditions ◽  
Fair Weather ◽  
Horizontal Structure ◽  
Cloud Optical Depth ◽  
Cloud Structure ◽  
Cloud Properties ◽  
Cloud Top Pressure

Abstract In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness–cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

EVALUATION OF CLOUDS, RADIATION, AND PRECIPITATION IN CMIP6 MODELS USING GLOBAL WEATHER STATES DERIVED FROM ISCCP-H CLOUD PROPERTY DATA

2021 ◽  
pp. 1-42
Author(s):  
George Tselioudis ◽  
William. B. Rossow ◽  
Christian Jakob ◽  
Jasmine Remillard ◽  
Derek Tropf ◽  
...  
Keyword(s):  
Cumulus Clouds ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Shallow Cumulus ◽  
Property Data ◽  
Ensemble Mean ◽  
Stratocumulus Clouds ◽  
Model Cloud ◽  
Adequate Representation ◽  
Cloud Top Pressure

AbstractA clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

scholarly journals Information content of OCO-2 oxygen A-band channels for retrieving marine liquid cloud properties

2018 ◽  
Vol 11 (3) ◽  
pp. 1515-1528 ◽  
Author(s):  
Mark Richardson ◽  
Graeme L. Stephens
Keyword(s):  
Information Content ◽  
Optical Depth ◽  
Marine Boundary Layer ◽  
Initial Conditions ◽  
High Spectral Resolution ◽  
Cloud Optical Depth ◽  
Boundary Layer Clouds ◽  
Cloud Properties ◽  
Cloud Top Pressure ◽  
Geometric Thickness

Abstract. Information content analysis is used to select channels for a marine liquid cloud retrieval using the high-spectral-resolution oxygen A-band instrument on NASA's Orbiting Carbon Observatory-2 (OCO-2). Desired retrieval properties are cloud optical depth, cloud-top pressure and cloud pressure thickness, which is the geometric thickness expressed in hectopascals. Based on information content criteria we select a micro-window of 75 of the 853 functioning OCO-2 channels spanning 763.5–764.6 nm and perform a series of synthetic retrievals with perturbed initial conditions. We estimate posterior errors from the sample standard deviations and obtain ±0.75 in optical depth and ±12.9 hPa in both cloud-top pressure and cloud pressure thickness, although removing the 10 % of samples with the highest χ2 reduces posterior error in cloud-top pressure to ±2.9 hPa and cloud pressure thickness to ±2.5 hPa. The application of this retrieval to real OCO-2 measurements is briefly discussed, along with limitations and the greatest caution is urged regarding the assumption of a single homogeneous cloud layer, which is often, but not always, a reasonable approximation for marine boundary layer clouds.

scholarly journals Information content of OCO-2 oxygen A-band channels for retrieving marine liquid cloud properties

2017 ◽  
Author(s):  
Mark Richardson ◽  
Graeme L. Stephens
Keyword(s):  
Information Content ◽  
Optical Depth ◽  
Marine Boundary Layer ◽  
Initial Conditions ◽  
High Spectral Resolution ◽  
Cloud Optical Depth ◽  
Boundary Layer Clouds ◽  
Cloud Properties ◽  
Atmospheric State ◽  
Cloud Top Pressure

Abstract. An information content analysis is used to select channels for a marine liquid cloud retrieval using the high-spectral-resolution oxygen A-band instrument on NASA’s Orbiting Carbon Observatory-2 (OCO-2). Desired retrieval properties are cloud optical depth, cloud pressure thickness and cloud-top pressure and the optimal channels depend on the atmospheric state, cloud properties and position within the OCO-2 swath. Based on information content criteria we select a micro-window of 75 of the 853 functioning OCO-2 channels spanning 763.5–764.6 nm and perform a series of synthetic retrievals with perturbed initial conditions. We estimate posterior errors from the sample standard deviations and obtain ±0.75 in optical depth, ±12.9 hPa in both cloud-top pressure and cloud pressure thickness, although removing the 10 % of samples with the highest χ2 reduces posterior error in cloud-top pressure to ±2.9 hPa and cloud pressure thickness to ±2.5 hPa. The application of this retrieval to real OCO-2 measurements is briefly discussed, along with limitations and the greatest caution is urged regarding the assumption of a single homogeneous cloud layer, which is often, but not always, a reasonable approximation for marine boundary layer clouds.

Employing Cluster Analysis to Detect Significant Cloud 3D RT Effect Indicators

2010 ◽  
Vol 67 (7) ◽  
pp. 2226-2239 ◽  
Author(s):  
Michael J. Foster ◽  
Dana E. Veron
Keyword(s):  
Cluster Analysis ◽  
Model Comparison ◽  
Clustering Algorithm ◽  
Climate Models ◽  
Three Dimensional ◽  
Vertical Wind Shear ◽  
Atmospheric Conditions ◽  
Climate System Model ◽  
Cloud Properties ◽  
Cloud Regimes

Abstract Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate models do not currently incorporate methods of identifying situations where this contribution is substantial. This work represents an effort to identify atmospheric conditions conducive to the formation of cloud field configurations that significantly affect shortwave radiative fluxes. Once identified, these characteristics may form the basis of a parameterization that accounts for radiative impact of complex cloud fields. A k-means clustering algorithm is applied to observed cloud properties taken from the Atmospheric Radiation Measurement Program tropical western Pacific sites to identify specific cloud regimes. Results from a stand-alone stochastic model, which statistically represents shortwave radiative transfer through broken cloud fields, are compared with those of a plane-parallel model. The aggregate scenes in each regime are examined to measure the bias in shortwave flux calculations due to neglected cloud field morphology. The results from the model comparison and cluster analysis suggest that cloud fraction, vertical wind shear, and spacing between cloudy layers are all important indicators of complex cloud field geometry and that these criteria are most often met in cloud regimes characterized by moderate to strong convection. The cluster criteria are applied to output from the Community Climate System Model (version 3.0) and it is found that the presence of persistent high cirrus cloud in model simulations inhibits identification of specific cloud regimes.

Cloud-Precipitation Hybrid Regimes and their Projection onto IMERG Precipitation Data

2021 ◽  
Author(s):  
Daeho Jin ◽  
Lazaros Oreopoulos ◽  
Dongmin Lee ◽  
Jackson Tan ◽  
Nayeong Cho
Keyword(s):  
Clustering Algorithm ◽  
Relative Weight ◽  
Heavy Precipitation ◽  
Optimal Number ◽  
Hybrid Regimes ◽  
Precipitation Regimes ◽  
Moderate Resolution ◽  
Application Potential ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure

AbstractIn order to better understand cloud-precipitation relationships, we extend the concept of cloud regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), to include precipitation information. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, we derive cloud-precipitation “hybrid” regimes by implementing a k-means clustering algorithm with advanced initialization and objective measures to determine the optimal number of clusters. By expressing the variability of precipitation rates within 1-degree grid cells as histograms and varying the relative weight of cloud and precipitation information in the clustering algorithm, we obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics.In the deep tropics, when precipitation is weighted weakly, the cloud part centroids of the hybrid regimes resemble their counterparts of cloud-only regimes, but combined clustering tightens the cloud-precipitation relationship by decreasing each regime’s precipitation variability. As precipitation weight progressively increases, the shape of the cloud part centroids becomes blunter, while the precipitation part sharpens. When cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct enough features in the precipitation parts of the centroids to allow us to project them onto the 30-min IMERG domain. Such a projection overcomes the temporal sparseness of MODIS cloud observations associated with substantial rainfall, suggesting great application potential for convection-focused studies where characterization of the diurnal cycle is essential.

scholarly journals The interdependence of continental warm cloud properties derived from unexploited solar background signals in ground-based lidar measurements

2014 ◽  
Vol 14 (16) ◽  
pp. 8389-8401 ◽  
Author(s):  
J. C. Chiu ◽  
J. A. Holmes ◽  
R. J. Hogan ◽  
E. J. O'Connor
Keyword(s):  
Optical Depth ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Warm Cloud ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Ground Based Lidar ◽  
Geometric Thickness

Abstract. We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signals that are previously unwanted and need to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40% and at least 10% higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds and a positive correlation in non-drizzling clouds, where, for large optical depths, it asymptotes to 10 μm. This asymptotic behaviour in non-drizzling clouds is found in both the droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.

scholarly journals Growth of nucleation mode particles in the summertime Arctic: a case study

2016 ◽  
Vol 16 (12) ◽  
pp. 7663-7679 ◽  
Author(s):  
Megan D. Willis ◽  
Julia Burkart ◽  
Jennie L. Thomas ◽  
Franziska Köllner ◽  
Johannes Schneider ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Methanesulfonic Acid ◽  
Lower Troposphere ◽  
Atmospheric Conditions ◽  
Aerosol Formation ◽  
Radiative Balance ◽  
Nucleation Mode ◽  
Cloud Properties ◽  
Marine Influence

Abstract. The summertime Arctic lower troposphere is a relatively pristine background aerosol environment dominated by nucleation and Aitken mode particles. Understanding the mechanisms that control the formation and growth of aerosol is crucial for our ability to predict cloud properties and therefore radiative balance and climate. We present an analysis of an aerosol growth event observed in the Canadian Arctic Archipelago during summer as part of the NETCARE project. Under stable and clean atmospheric conditions, with low inversion heights, carbon monoxide less than 80 ppbv, and black carbon less than 5 ng m−3, we observe growth of small particles,  <  20 nm in diameter, into sizes above 50 nm. Aerosol growth was correlated with the presence of organic species, trimethylamine, and methanesulfonic acid (MSA) in particles ∼ 80 nm and larger, where the organics are similar to those previously observed in marine settings. MSA-to-sulfate ratios as high as 0.15 were observed during aerosol growth, suggesting an important marine influence. The organic-rich aerosol contributes significantly to particles active as cloud condensation nuclei (CCN, supersaturation  =  0.6 %), which are elevated in concentration during aerosol growth above background levels of ∼ 100 to ∼ 220 cm−3. Results from this case study highlight the potential importance of secondary organic aerosol formation and its role in growing nucleation mode aerosol into CCN-active sizes in this remote marine environment.

scholarly journals The interdependence of continental warm cloud properties derived from unexploited solar background signal in ground-based lidar measurements

2014 ◽  
Vol 14 (7) ◽  
pp. 8963-8996
Author(s):  
J. C. Chiu ◽  
J. A. Holmes ◽  
R. J. Hogan ◽  
E. J. O'Connor
Keyword(s):  
Optical Depth ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Background Signal ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Lidar Measurements ◽  
Atmospheric Radiation Measurement ◽  
Ground Based Lidar ◽  
Geometric Thickness

Abstract. We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signal that is previously unwanted and needs to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40% and at least 10% higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds, while it increases with optical depth and reaches an asymptote of 10 μm in non-drizzling clouds. This asymptotic behaviour in non-drizzling clouds is found in both droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.

Simulating effects of the 774 AD solar proton event on atmospheric electricity

2021 ◽  
Author(s):  
Stergios Misios ◽  
Mads F. Knudsen ◽  
Christoffer Karoff
Keyword(s):  
Atmospheric Electricity ◽  
Circulation Model ◽  
High Energy ◽  
Solar Proton ◽  
Solar Proton Event ◽  
Proton Event ◽  
Atmospheric Conditions ◽  
Global Circulation Model ◽  
Fair Weather ◽  
Particle Radiation

&lt;p&gt;High energy cosmic rays of galactic and solar origin, natural radioactivity, lighting in thunderstorms and electrified shower clouds, produce ion clusters and charge the whole atmosphere causing a ubiquitous potential difference between the ionosphere and the surface. This Global Electric Circuit (GEC) allows the flow of charges to the surface in the fair-weather regions of the globe. Here, we simulate the effect of highly energetic particle radiation, in particular the 774 AD solar proton event, on the GEC with the aid of the global circulation model EMAC/MESSy. The simulations assume pre-industrial atmospheric conditions and the coupling of aerosol and atmospheric electricity schemes allows for ion-ion and ion-aerosol capture reactions. We discuss effects in fair weather current and atmospheric conductivity at different latitudinal bands. &lt;/p&gt;

Simulations of Föhn in Antarctica with WRF for the Antarctic Mesoscale Prediction System AMPS

2021 ◽  
Author(s):  
Amélie Kirchgaessner ◽  
John King ◽  
Alan Gadian ◽  
Phil Anderson
Keyword(s):  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Ice Shelf ◽  
Cloud Properties ◽  
Surface Melt ◽  
Mixed Phase Clouds ◽  
The Antarctic

&lt;p&gt;We examine the representation of F&amp;#246;hn events across the Antarctic Peninsula Mountains during 2011 as they were observed in measurements by an Automatic Weather Station, and in simulations with the Weather Research and Forecasting Model (WRF) as run for the Antarctic Mesoscale Prediction System (AMPS). On the Larsen Ice Shelf (LIS) in the lee of this mountain range F&amp;#246;hn winds are thought to provide the atmospheric conditions for significant warming over the ice shelf thus leading to the initial firn densification and subsequently providing the melt water for hydrofracturing. This process has led to the dramatic collapse of huge parts of the LIS in 1995 and 2002 respectively.&lt;/p&gt;&lt;p&gt;Measurements obtained at a crest AWS on the Avery Plateau (AV), and the analysis of conditions upstream using the Froude number help to put observations at CP into a wider context. We find that, while the model generally simulates meteorological parameters very well, and shows good skills in capturing the occurrence, frequency and duration of F&amp;#246;hn events realistically, it underestimates the temperature increase and the humidity decrease during the F&amp;#246;hn significantly, and may thus underestimate the contribution of F&amp;#246;hn to driving surface melt on the LIS.&lt;/p&gt;&lt;p&gt;Our results indicate that the misrepresentation of cloud properties and particularly the absence of mixed phase clouds in AMPS, affects the quality of weather simulation under normal conditions to some extent, and to a larger extent the model&amp;#8217;s capability to simulate the strength of F&amp;#246;hn conditions - and thus their contribution to driving surface melt on the LIS - adequately. Most importantly our data show that F&amp;#246;hn conditions can raise the air temperature to above freezing, and thus trigger melt/sublimation even in winter.&lt;/p&gt;

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