scholarly journals Vertical Dependence of Horizontal Variation of Cloud Microphysics: Observations from the ACE-ENA field campaign and implications for warm rain simulation in climate models

2020 ◽  
Author(s):  
Zhibo Zhang ◽  
Qianqian Song ◽  
David Mechem ◽  
Vincent Larson ◽  
Jian Wang ◽  
...  
Keyword(s):  
Climate Models ◽  
Marine Boundary Layer ◽  
Global Climate ◽  
Cloud Microphysics ◽  
Global Climate Models ◽  
Strong Positive Correlation ◽  
Field Campaign ◽  
Warm Rain ◽  
Cloud Water Content ◽  
Warm Rain Process

Abstract. In the current global climate models (GCM), the nonlinearity effect of subgrid cloud variations on the parameterization of warm rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm ran process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in-situ measurements from a recent field campaign, and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that makes tends to make EF 

scholarly journals Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

2021 ◽  
Vol 21 (4) ◽  
pp. 3103-3121
Author(s):  
Zhibo Zhang ◽  
Qianqian Song ◽  
David B. Mechem ◽  
Vincent E. Larson ◽  
Jian Wang ◽  
...  
Keyword(s):  
Climate Models ◽  
Marine Boundary Layer ◽  
Global Climate ◽  
Cloud Microphysics ◽  
Global Climate Models ◽  
Strong Positive Correlation ◽  
Field Campaign ◽  
Warm Rain ◽  
Cloud Water Content ◽  
Warm Rain Process

Abstract. In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that tends to make EF < 1. This effect is especially strong at cloud top, where the qc and Nc correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of qc and Nc is significantly smaller than its counterpart that accounts only for the subgrid variation of qc, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of Nc and its correlation with qc both need to be considered for an accurate simulation of the autoconversion process in GCMs.

scholarly journals Improving the treatment of subgrid cloud variability in warm rain simulation in CESM2

2021 ◽  
Author(s):  
Hao Wang ◽  
Minghuai Wang ◽  
Daniel Rosenfeld ◽  
Yannian Zhu ◽  
Zhibo Zhang
Keyword(s):  
Liquid Water ◽  
Climate Models ◽  
Global Climate ◽  
Liquid Water Content ◽  
Global Climate Models ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Warm Rain ◽  
Rain Simulation ◽  
Warm Rain Process

&lt;p&gt;Representing subgrid variability of cloud properties has always been a challenge in global climate models (GCMs). In microphysics schemes, the effects of subgrid cloud variability on warm rain process rates calculated based on mean cloud properties are usually accounted for by scaling process rates by an enhancement factor (EF) that is derived from the subgrid variance of cloud water. In our study, we find that the EF derived from Cloud Layers Unified by Binormals (CLUBB) in Community Earth System Model Version 2 (CESM2) is severely overestimated in most of the oceanic areas, which leads to the strong overestimation in the autoconversion rate. Through an EF formula based on empirical fitting of MODIS, we improve the EF in the liquid phase clouds. Results show that the model has a more reasonable relationship between autoconversion rate, cloud liquid water content (LWC), and droplet number concentration (CDNC) in warm rain simulation. The annual mean liquid cloud fraction (LCF), liquid water path (LWP), and CDNC show obvious increases for marine stratocumulus, where the probability of precipitation (POP) shows an obvious decrease. The annual mean LCF, cloud optical thickness (COT), and shortwave cloud forcing (SWCF) match better with observation. The sensitivity of LWP to aerosol decreases obviously. The sensitivities of LCF, LWP, cloud top droplet effective radius (CER), and COT to aerosol are in better agreement with MODIS, but the model still underestimates the response of cloud albedo to aerosol. These results indicate the importance of representing reasonable subgrid cloud variabilities in the simulation of cloud properties and aerosol-cloud interaction in climate models.&lt;/p&gt;

scholarly journals Aircraft measurements of aerosol and trace gas chemistry in the Eastern North Atlantic

2020 ◽  
Author(s):  
Maria A. Zawadowicz ◽  
Kaitlyn Suski ◽  
Jiumeng Liu ◽  
Mikhail Pekour ◽  
Jerome Fast ◽  
...  
Keyword(s):  
Mass Spectrometer ◽  
North Atlantic ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
Global Climate ◽  
Cloud Condensation Nuclei ◽  
Proton Transfer Reaction ◽  
Global Climate Models ◽  
Aerosol Mass ◽  
Eastern North Atlantic

Abstract. The Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) investigated properties of aerosols and subtropical marine boundary layer (MBL) clouds. Low subtropical marine clouds can have a large effect on Earth's radiative budget, but they are poorly represented in global climate models. In order to understand their radiative effects, it is imperative to understand the composition and sources of the MBL cloud condensation nuclei (CCN). The campaign consisted of two intensive operation periods (IOP) (June–July, 2017 and January–February, 2018) during which a fully instrumented G-1 aircraft was deployed from Lajes Field on Terceira Island in the Azores, Portugal. The G-1 conducted research flights in the vicinity of the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) atmospheric observatory on Graciosa Island. An Aerodyne HR-ToF Aerosol Mass Spectrometer (AMS) and Ionicon Proton-Transfer-Reaction Mass Spectrometer (PTR-MS) were deployed aboard the aircraft, characterizing chemistry of non-refractory aerosol and trace gases, respectively. The Eastern North Atlantic region was found to be very clean, with average non-refractory aerosol mass loading of 0.6 μg m−3 in the summer and 0.1 μg m

scholarly journals Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes

2020 ◽  
Vol 6 (22) ◽  
pp. eaaz6433 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Christine Nam ◽  
Marc Salzmann ◽  
Jan Kretzschmar ◽  
Tristan S. L’Ecuyer ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Observational Constraints ◽  
Observational Constraint ◽  
Liquid Water Path ◽  
Anthropogenic Aerosols ◽  
Aerosol Forcing ◽  
Warm Rain ◽  
Atmospheric State

Global climate models (GCMs) disagree with other lines of evidence on the rapid adjustments of cloud cover and liquid water path to anthropogenic aerosols. Attempts to use observations to constrain the parameterizations of cloud processes in GCMs have failed to reduce the disagreement. We propose using observations sensitive to the relevant cloud processes rather than only to the atmospheric state and focusing on process realism in the absence of aerosol perturbations in addition to the process susceptibility to aerosols. We show that process-sensitive observations of precipitation can reduce the uncertainty on GCM estimates of rapid cloud adjustments to aerosols. The feasibility of an observational constraint depends on understanding the precipitation intensity spectrum in both observations and models and also on improving methods to compare the two.

scholarly journals A New Perspective on Coastally Trapped Disturbances Using Data from the Satellite Era

2019 ◽  
Vol 100 (4) ◽  
pp. 631-651 ◽  
Author(s):  
Timothy W. Juliano ◽  
Zachary J. Lebo ◽  
Gregory Thompson ◽  
David A. Rahn
Keyword(s):  
Climate Models ◽  
Marine Boundary Layer ◽  
Global Climate ◽  
Warm Season ◽  
Cloud Droplet ◽  
Global Climate Models ◽  
Spatial Inhomogeneity ◽  
Radiation Budget ◽  
Stratiform Clouds ◽  
New Perspective

Abstract The ability of global climate models to simulate accurately marine stratiform clouds continues to challenge the atmospheric science community. These cloud types, which account for a large uncertainty in Earth’s radiation budget, are generally difficult to characterize due to their shallowness and spatial inhomogeneity. Previous work investigating marine boundary layer (MBL) clouds off the California coast has focused on clouds that form under the typical northerly flow regime during the boreal warm season. From about June through September, however, these northerly winds may reverse and become southerly as part of a coastally trapped disturbance (CTD). As the flow surges northward, it is accompanied by a broad cloud deck. Because these events are difficult to forecast, in situ observations of CTDs are few and far between, and little is known about their cloud physical properties. A climatological perspective of 23 CTD events—spanning the years from 2004 to 2016—is presented using several data products, including model reanalyses, buoys, and satellites. For the first time, satellite retrievals suggest that CTD cloud decks may play a unique role in the radiation budget due to a combination of aerosol sources that enhance cloud droplet number concentration and reduce cloud droplet effective radius. This particular type of cloud regime should therefore be treated differently than that which is more commonly found in the summertime months over the northeast Pacific Ocean. The potential influence of a coherent wind stress cycle on sea surface temperatures and sea salt aerosol is also explored.

scholarly journals Assessing the potential for simplification in global climate model cloud microphysics

2021 ◽  
Author(s):  
Ulrike Proske ◽  
Sylvaine Ferrachat ◽  
David Neubauer ◽  
Martin Staab ◽  
Ulrike Lohmann
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Cloud Microphysics ◽  
Global Climate Models ◽  
Ice Crystals ◽  
Model Output ◽  
Radiative Balance ◽  
The Impact

Abstract. Cloud properties and their evolution influence Earth's radiative balance. The cloud microphysical (CMP) processes that shape these properties are therefore important to be represented in global climate models. Historically, parameterizations in these models have grown more detailed and complex. However, a simpler formulation of CMP processes may leave the model results mostly unchanged while enabling an easier interpretation of model results and helping to increase process understanding. This study employs sensitivity analysis on an emulated perturbed parameter ensemble of the global aerosol-climate model ECHAM-HAM to illuminate the impact of selected CMP cloud ice processes on model output. The response to the phasing of a process thereby serves as a proxy for the effect of a simplification. Aggregation of ice crystals is found to be the dominant CMP process in influencing key variables such as the ice water path or cloud radiative effects, while riming of cloud droplets on snow influences mostly the liquid phase. Accretion of ice and snow and self-collection of ice crystals have a negligible influence on model output and are therefore identified as suitable candidates for future simplifications. In turn, the dominating role of aggregation suggests that this process has the greatest need to be represented correctly. A seasonal and spatially resolved analysis employing a spherical harmonics expansion of the data corroborates the results. This study introduces a new framework to evaluate a processes' impact in a complex numerical model, and paves the way for simplifications of CMP processes leading to more interpretable climate models.

scholarly journals Evaluation of the Warm Rain Formation Process in Global Models with Satellite Observations

2015 ◽  
Vol 72 (10) ◽  
pp. 3996-4014 ◽  
Author(s):  
Kentaroh Suzuki ◽  
Graeme Stephens ◽  
Alejandro Bodas-Salcedo ◽  
Minghuai Wang ◽  
Jean-Christophe Golaz ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Satellite Observations ◽  
Dimensional Model ◽  
One Dimensional ◽  
Warm Rain ◽  
Stratiform Clouds ◽  
The One ◽  
Rain Formation

Abstract This study examines the warm rain formation process over the global ocean in global climate models. Methodologies developed to analyze CloudSat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations are employed to investigate the cloud-to-precipitation process of warm clouds and are applied to the model results to examine how the models represent the process for warm stratiform clouds. Despite a limitation of the present study that compares the statistics for stratiform clouds in climate models with those from satellite observations, including both stratiform and (shallow) convective clouds, the statistics constructed with the methodologies are compared between the models and satellite observations to expose their similarities and differences. A problem common to some models is that they tend to produce rain at a faster rate than is observed. These model characteristics are further examined in the context of cloud microphysics parameterizations using a simplified one-dimensional model of warm rain formation that isolates key microphysical processes from full interactions with other processes in global climate models. The one-dimensional model equivalent statistics reproduce key characteristics of the global model statistics when corresponding autoconversion schemes are assumed in the one-dimensional model. The global model characteristics depicted by the statistics are then interpreted as reflecting behaviors of the autoconversion parameterizations adopted in the models. Comparisons of the one-dimensional model with satellite observations hint at improvements to the formulation of the parameterization scheme, thus offering a novel way of constraining key parameters in autoconversion schemes of global models.

Study of thermodynamic properties of trade-wind cumulus clouds with Remotely Piloted Aircrafts during the EUREC4A field campaign

2021 ◽  
Author(s):  
Nicolas Maury ◽  
Gregory Roberts ◽  
Fleur Couvreux ◽  
Titouan Verdu ◽  
Pierre Narvor ◽  
...  
Keyword(s):  
Thermodynamic Properties ◽  
Adaptive Sampling ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Three Dimensions ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Field Campaign ◽  
Radiative Balance

&lt;p&gt;Trade wind cumulus clouds have a significant impact on the earth's radiative balance, due to their extensive coverage in subtropical regions but due to their characteristic size are still parameterized.&lt;br&gt;The feedback of low clouds on the climate system as well as biases still existing in their representation of Global Climate Models (GCMs) results in a climatic response with relatively large uncertainty and induce a significant divergence in GCMs. Many studies and campaigns have focused on a better understanding of the thermodynamic and macroscopic properties of cumulus clouds with ground-based and satellite-based remote sensing&lt;br&gt;and also in-situ observations from aircraft flights, but few provide information on the three-dimensional properties of individual cumulus clouds. Our understanding of cumulus clouds is also based on high-resolution numerical simulations (LES: 25m, 5m of resolution) that reproduce the&lt;br&gt;average characteristics of cumulus clouds fairly reliably, yet these simulations still depend on parametrizations (turbulence and microphysics).&lt;br&gt;The development of a fleet the sampling of RPAs (Remotely Piloted Aircraft) contributes to the increase in the resolution of the sampling of the evolution of cloud microphysical properties. Recent studies have permitted to have an autonomous adaptive sampling and a mapping using Gaussian&lt;br&gt;Process Regression to interpolate missed values during exploration.&lt;br&gt;An experimental strategy has been developed and tested in a cumulus cloud field simulated in a LES simulation with the Meso-NH model by implementing a simulator of RPA flights. During the EUREC4A field campaign in Barbados in January-February, more than forty RPAs flights have been conducted and thermodynamic properties of cumulus clouds were studied in three dimensions using miniaturized instruments installed on-board (PTU probe, cloud sensor). We validate first the results of cloud sensor with an other microphysics instrument. Several clouds were followed for about ten minutes and their thermodynamic evolution have been compared to cumulus clouds simulated in the LES.&lt;/p&gt;

Implementation and evaluation of a double-plume convective parameterization in NCAR CAM5

2021 ◽  
pp. 1-51
Author(s):  
Wenchao Chu ◽  
Yanluan Lin ◽  
Ming Zhao
Keyword(s):  
Climate Models ◽  
Marine Boundary Layer ◽  
Cloud Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Shallow Convection ◽  
Unified Framework ◽  
Monsoon Period ◽  
Tropical Precipitation ◽  
Single Column

AbstractPerformance of global climate models (GCMs) is strongly affected by their cumulus parameterizations (CP) used. Similar to the approach in GFDL AM4, a double-plume CP, which unifies the deep and shallow convection in one framework, is implemented and tested in NCAR Community Atmospheric Model version 5 (CAM5). Based on the University of Washington (UW) shallow convection scheme, an additional plume was added to represent the deep convection. The shallow and deep plumes share the same cloud model, but use different triggers, fractional mixing rates and closures. The scheme was tested in single column, short-term hindcast and AMIP simulations. Compared with the default combination of Zhang-McFarlane scheme and UW scheme in CAM5, the new scheme tends to produce a top-heavy mass flux profile during the active monsoon period in the single column simulations. The scheme increases the intensity of tropical precipitation, closer to TRMM observations. The new scheme increased subtropical marine boundary layer clouds and high clouds over the deep tropics, both in better agreement with observations. Sensitivity tests indicate that regime dependent fractional entrainment rates of the deep plume are desired to improve tropical precipitation distribution and upper troposphere temperature. This study suggests that a double-plume approach is a promising way to combine shallow and deep convections in a unified framework.

scholarly journals Elucidating ice formation pathways in the aerosol–climate model ECHAM6-HAM2

2019 ◽  
Vol 19 (14) ◽  
pp. 9061-9080 ◽  
Author(s):  
Remo Dietlicher ◽  
David Neubauer ◽  
Ulrike Lohmann
Keyword(s):  
Temperature Regime ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Cloud Amount ◽  
Supercooled Liquid ◽  
Cloud Microphysics ◽  
Global Climate Models ◽  
Ice Formation ◽  
Total Cloud Amount

Abstract. Cloud microphysics schemes in global climate models have long suffered from a lack of reliable satellite observations of cloud ice. At the same time there is a broad consensus that the correct simulation of cloud phase is imperative for a reliable assessment of Earth's climate sensitivity. At the core of this problem is understanding the causes for the inter-model spread of the predicted cloud phase partitioning. This work introduces a new method to build a sound cause-and-effect relation between the microphysical parameterizations employed in our model and the resulting cloud field by analysing ice formation pathways. We find that freezing processes in supercooled liquid clouds only dominate ice formation in roughly 6 % of the simulated clouds, a small fraction compared to roughly 63 % of the clouds governed by freezing in the cirrus temperature regime below −35 ∘C. This pathway analysis further reveals that even in the mixed-phase temperature regime between −35 and 0 ∘C, the dominant source of ice is the sedimentation of ice crystals that originated in the cirrus regime. The simulated fraction of ice cloud to total cloud amount in our model is lower than that reported by the CALIPSO-GOCCP satellite product. This is most likely caused by structural differences of the cloud and aerosol fields in our model rather than the microphysical parametrizations employed.

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