scholarly journals A kriging-based analysis of cloud Liquid Water Content using CloudSat data

2021 ◽  
Author(s):  
Jean-Marie Lalande ◽  
Guillaume Bourmaud ◽  
Pierre Minvielle ◽  
Jean-François Giovannelli
Keyword(s):  
Climate Models ◽  
Liquid Water Content ◽  
Prediction Algorithm ◽  
Parameter Distribution ◽  
Satellite Orbits ◽  
Actual Measurement ◽  
Spatiotemporal Model ◽  
Microphysical Properties ◽  
The Mean ◽  
Ice Content

Abstract. Spatiotemporal statistical learning has received increased attention in the past decade, due to spatially and temporally indexed data proliferation, especially collected from satellite remote sensing. In the mean time, observational studies of clouds are recognized as an important step to improve cloud representation in weather and climate models. Since 2006, the satellite CloudSat of NASA carries a 94 GHz cloud profiling radar and is able to retrieve, from radar reflectivity, microphysical parameter distribution such as water or ice content. The collected data is piled up with the successive satellite orbits of nearly two hours, leading to a large compressed database of 2 Tb (http://cloudsat.atmos.colostate.edu/). These observations give the opportunity to extend the cloud microphysical properties beyond the actual measurement locations using an interpolation and prediction algorithm. In order to do so, we introduce a statistical estimator based on the spatiotemporal covariance and mean of the observations known as kriging. An adequate parametric model for the covariance and the mean is chosen from an exploratory data analysis. Beforehand, it is necessary to estimate the parameters of this spatiotemporal model; This is performed in a Bayesian setting. The approach is then applied to a subset of the CloudSat dataset.

scholarly journals The evolution of cloud microphysics upon aerosol interaction at the summit of Mt. Tai, China

2019 ◽  
Author(s):  
Jiarong Li ◽  
Chao Zhu ◽  
Hui Chen ◽  
Defeng Zhao ◽  
Likun Xue ◽  
...  
Keyword(s):  
Climate Models ◽  
Cloud Condensation Nuclei ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Life Cycles ◽  
Cloud Droplets ◽  
Climate Effect ◽  
Local Climate ◽  
The North ◽  
Microphysical Properties

Abstract. The influence of aerosols, both natural and anthropogenic, remains a major area of uncertainty when predicting the properties and behaviour of clouds and their influence on climate. In an attempt to understand better the microphysical properties of cloud droplets, the aerosol-cloud interactions, and the corresponding climate effect during cloud life cycles in the North China Plain, an intensive observation took place from 17 June to 30 July 2018 at the summit of Mt. Tai. Cloud microphysical parameters were monitored simultaneously with number concentrations of cloud condensation nuclei (NCCN) at different supersaturations, PM2.5 mass concentrations, particle size distributions and meteorological parameters. Number concentrations of cloud droplets (NC), liquid water content (LWC) and effective radius of cloud droplets (reff) show large variations among 40 cloud events observed during the campaign. Perturbations of aerosols will significantly increase the NC of cloud droplets and shift cloud droplets toward smaller size ranges. Clouds in clean days are more susceptible to the change in concentrations of particle number (NP). LWC shows positive correlation with reff. As NC increases, reff changes from a trimodal distribution to a unimodal distribution. By assuming a cloud thickness of 100 m, we find that the albedo can increase 36.4 % if the cloud gets to be disturbed by aerosols. This may induce a cooling effect on the local climate system. Our results contribute more information about regional cloud microphysics and will help to reduce the uncertainties in climate models when predicting climate responses to cloud-aerosol interactions.

scholarly journals The Microphysical Properties of a Sea-Fog Event along the West Coast of the Yellow Sea in Spring

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Shengkai Wang ◽  
Li Yi ◽  
Suping Zhang ◽  
Xiaomeng Shi ◽  
Xianyao Chen
Keyword(s):  
Distribution Function ◽  
Yellow Sea ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Mean Value ◽  
The Yellow Sea ◽  
Sea Fog ◽  
Microphysical Properties ◽  
The Mean ◽  
Microphysical Parameterization

The microphysics and visibility of a sea-fog event were measured at the Qingdao Meteorological Station (QDMS) (120°19′ E, 36°04′ N) from 5 April to 8 April 2017. The two foggy periods with low visibility (<200 m) lasted 31 h together. The mean value of the average liquid water content (LWC) was 0.057 g m−3, and the mean value of the number concentration (NUM) was 64.4 cm−3. We found that although large droplets only constituted a small portion of the total number of the concentration; they contributed the majority of the LWC and therefore determined ~76% of total extinction of the visibility. The observed droplet-size distribution (DSD) exhibited a new bimodal Gaussian (G-exponential) distribution function, rather than the well-accepted Gamma distribution. This work suggests a new distribution function to describe fog DSD, which may help to improve the microphysical parameterization for the Yellow Sea fog numerical forecasting.

scholarly journals Investigation of Regional and Seasonal Variations in Marine Boundary Layer Cloud Properties from MODIS Observations

2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Test Bed ◽  
Liquid Water Path ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Peak Versus

Abstract To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals Northern winter stratospheric temperature and ozone responses to ENSO inferred from an ensemble of Chemistry Climate Models

2009 ◽  
Vol 9 (22) ◽  
pp. 8935-8948 ◽  
Author(s):  
C. Cagnazzo ◽  
E. Manzini ◽  
N. Calvo ◽  
A. Douglass ◽  
H. Akiyoshi ◽  
...  
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Polar Vortex ◽  
Atmospheric Modeling ◽  
Residual Circulation ◽  
Model Simulations ◽  
Enso Events ◽  
Stratospheric Temperature ◽  
The Mean ◽  
Column Ozone

Abstract. The connection between the El Niño Southern Oscillation (ENSO) and the Northern polar stratosphere has been established from observations and atmospheric modeling. Here a systematic inter-comparison of the sensitivity of the modeled stratosphere to ENSO in Chemistry Climate Models (CCMs) is reported. This work uses results from a number of the CCMs included in the 2006 ozone assessment. In the lower stratosphere, the mean of all model simulations reports a warming of the polar vortex during strong ENSO events in February–March, consistent with but smaller than the estimate from satellite observations and ERA40 reanalysis. The anomalous warming is associated with an anomalous dynamical increase of column ozone north of 70° N that is accompanied by coherent column ozone decrease in the Tropics, in agreement with that deduced from the NIWA column ozone database, implying an increased residual circulation in the mean of all model simulations during ENSO. The spread in the model responses is partly due to the large internal stratospheric variability and it is shown that it crucially depends on the representation of the tropospheric ENSO teleconnection in the models.

scholarly journals Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 262 ◽  
Author(s):  
Coraline Wyard ◽  
Sébastien Doutreloup ◽  
Alexandre Belleflamme ◽  
Martin Wild ◽  
Xavier Fettweis
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Horizontal Resolution ◽  
Radiative Flux ◽  
Added Value ◽  
Historical Trends ◽  
The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

scholarly journals A variational approach for retrieving ice cloud properties from infrared measurements: application in the context of two IIR validation campaigns

2013 ◽  
Vol 13 (2) ◽  
pp. 5553-5599
Author(s):  
O. Sourdeval ◽  
L. C. Labonnote ◽  
G. Brogniez ◽  
O. Jourdan ◽  
J. Pelon ◽  
...  
Keyword(s):  
Climate Models ◽  
Infrared Imaging ◽  
Great Sensitivity ◽  
Global Climate Models ◽  
Radiation Balance ◽  
Strong Impact ◽  
Large Variability ◽  
Microphysical Properties ◽  
Infrared Measurements

Abstract. Cirrus are cloud types that are recognized to have a strong impact on the Earth-atmosphere radiation balance. This impact is however still poorly understood, due to the difficulties in describing the large variability of their properties in global climate models. Consequently, numerous airborne and space borne missions have been dedicated to their study in the last decades. The satellite constellation A-Train has proven to be particularly helpful to study cirrus on global scale due to such instruments as the Infrared Imaging Radiometer (IIR), which shows great sensitivity to the radiative and microphysical properties of these clouds. This study presents an algorithm that uses thermal infrared measurements to retrieve the optical thickness of cirrus and the effective size of their ice crystals. This algorithm is based on an optimal estimation scheme, which possesses the advantage of attributing precise uncertainties to the retrieved parameters. Two IIR airborne validation campaigns have been chosen as case studies. It is observed that optical thicknesses could be accurately retrieved but that large uncertainties may occur on the effective diameters. Strong agreements have been found between the products of our algorithm when separately applied to the measurements of IIR and of the airborne radiometer CLIMAT-AV, which comforts the results of previous validations of IIR level-1 measurements. Comparisons with in situ observations and with operational products of IIR also show confidence in our results. However, we have found that the quality of our retrievals can be strongly impacted by uncertainties related to the choice of a pristine crystal model and by poor constraints on the properties of possible liquid cloud layers underneath cirrus. Simultaneous retrievals of liquid clouds radiative and microphysical properties or the use of different ice crystal models should therefore be considered to improve the quality of the results.

scholarly journals Reduced global warming from CMIP6 projections when weighting models by performance and independence

2020 ◽  
Vol 11 (4) ◽  
pp. 995-1012
Author(s):  
Lukas Brunner ◽  
Angeline G. Pendergrass ◽  
Flavio Lehner ◽  
Anna L. Merrifield ◽  
Ruth Lorenz ◽  
...  
Keyword(s):  
Climate Change ◽  
Retrospective Analysis ◽  
Climate Models ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Uncertainty Range ◽  
Future Warming ◽  
The Mean

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as the mean and likely range. Here, we use a model weighting approach, which accounts for the models' historical performance based on several diagnostics as well as model interdependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we use previous-generation CMIP5 models as pseudo-observations in the historical period. The performance of the distribution weighted in the abovementioned manner with respect to matching the pseudo-observations in the future is then evaluated, and we find a mean increase in skill of about 17 % compared with the unweighted distribution. In addition, we show that our independence metric correctly clusters models known to be similar based on a CMIP6 “family tree”, which enables the application of a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (the fifth generation of the European Centre for Medium-Range Weather Forecasts Retrospective Analysis – ERA5, and the Modern-Era Retrospective analysis for Research and Applications, version 2 – MERRA-2), to constrain CMIP6 projections under weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios (SSP refers to the Shared Socioeconomic Pathways). Our results show a reduction in the projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 ∘C, compared with 4.1 ∘C without weighting; the likely (66%) uncertainty range is 3.1 to 4.6 ∘C, which equates to a 13 % decrease in spread. For SSP1-2.6, the weighted end-of-century warming is 1 ∘C (0.7 to 1.4 ∘C), which results in a reduction of −0.1 ∘C in the mean and −24 % in the likely range compared with the unweighted case.

scholarly journals A Comprehensive Assessment of Tropical Stratospheric Upwelling in Specified Dynamics CESM1.2.2 (WACCM)

2019 ◽  
Author(s):  
Nicholas A. Davis ◽  
Sean M. Davis ◽  
Robert W. Portmann ◽  
Eric Ray ◽  
Karen H. Rosenlof ◽  
...  
Keyword(s):  
Best Practices ◽  
Climate Models ◽  
Climate Model ◽  
Meridional Circulation ◽  
Trace Gas ◽  
Mean Meridional Circulation ◽  
Community Earth System Model ◽  
Free Running ◽  
The Mean ◽  
Wave Momentum

Abstract. Specified dynamics (SD) schemes relax the circulation in climate models toward a reference meteorology to simulate historical variability. These simulations are widely used to isolate the dynamical contributions to variability and trends in trace gas species. However, it is not clear if trends in the stratospheric overturning circulation are properly reproduced by SD schemes. This study assesses numerous SD schemes and modeling choices in the Community Earth System Model (CESM) Whole Atmosphere Chemistry Climate Model (WACCM) to determine a set of best practices for reproducing interannual variability and trends in tropical stratospheric upwelling estimated by reanalyses. Nudging toward the reanalysis meteorology as is typically done in SD simulations expectedly changes the model’s mean upwelling compared to its free-running state, but does not accurately reproduce upwelling trends present in the underlying reanalysis. In contrast, nudging to anomalies from the climatological winds or from the zonal mean winds and temperatures preserves WACCM’s climatology and better reproduces trends in stratospheric upwelling. An SD scheme’s performance in simulating the acceleration of the shallow branch of the mean meridional circulation from 1980–2017 hinges on its ability to simulate the downward shift of subtropical lower stratospheric wave momentum forcing. Key to this is not nudging the zonal-mean temperature field. Gravity wave momentum forcing, which drives a substantial fraction of the upwelling in WACCM, cannot be constrained by nudging and presents an upper-limit on the performance of these schemes.

scholarly journals Total aerosol effect: radiative forcing or radiative flux perturbation?

2009 ◽  
Vol 9 (6) ◽  
pp. 25633-25661 ◽  
Author(s):  
U. Lohmann ◽  
L. Rotstayn ◽  
T. Storelvmo ◽  
A. Jones ◽  
S. Menon ◽  
...  
Keyword(s):  
Global Warming ◽  
Radiative Forcing ◽  
Climate Models ◽  
Radiative Flux ◽  
Radiative Forcings ◽  
Microphysical Properties ◽  
Aerosol Effect ◽  
Rain Formation ◽  
Aerosol Radiative ◽  
Flux Perturbation

Abstract. Uncertainties in aerosol radiative forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. In former assessments of aerosol radiative forcings, these effects have not been quantified. Also, with global aerosol-climate models simulating interactively aerosols and cloud microphysical properties, a quantification of the aerosol forcings in the traditional way is difficult to properly define. Here we argue that fast feedbacks should be included because they act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Based on our results, we recommend RFP as a valid option to compare different forcing agents, and to compare the effects of particular forcing agents in different models.

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