Observed Relationships between Arctic Longwave Cloud Forcing and Cloud Parameters Using a Neural Network

2006 ◽  
Vol 19 (16) ◽  
pp. 4087-4104 ◽  
Author(s):  
Yonghua Chen ◽  
Filipe Aires ◽  
Jennifer A. Francis ◽  
James R. Miller
Keyword(s):  
Neural Network ◽  
Climate Models ◽  
Heat Budget ◽  
Inversion Layer ◽  
The Arctic ◽  
Cloud Base ◽  
Base Temperature ◽  
Liquid Water Path ◽  
Cloud Forcing ◽  
Cloud Parameters

Abstract A neural network technique is used to quantify relationships involved in cloud–radiation feedbacks based on observations from the Surface Heat Budget of the Arctic (SHEBA) project. Sensitivities of longwave cloud forcing (CFL) to cloud parameters indicate that a bimodal distribution pattern dominates the histogram of each sensitivity. Although the mean states of the relationships agree well with those derived in a previous study, they do not often exist in reality. The sensitivity of CFL to cloud cover increases as the cloudiness increases with a range of 0.1–0.9 W m−2 %−1. There is a saturation effect of liquid water path (LWP) on CFL. The highest sensitivity of CFL to LWP corresponds to clouds with low LWP, and sensitivity decreases as LWP increases. The sensitivity of CFL to cloud-base height (CBH) depends on whether the clouds are below or above an inversion layer. The relationship is negative for clouds higher than 0.8 km at the SHEBA site. The strongest positive relationship corresponds to clouds with low CBH. The dominant mode of the sensitivity of CFL to cloud-base temperature (CBT) is near zero and corresponds to warm clouds with base temperatures higher than −9°C. The low and high sensitivity regimes correspond to the summer and winter seasons, respectively, especially for LWP and CBT. Overall, the neural network technique is able to separate two distinct regimes of clouds that correspond to different sensitivities; that is, it captures the nonlinear behavior in the relationships. This study demonstrates a new method for evaluating nonlinear relationships between climate variables. It could also be used as an effective tool for evaluating feedback processes in climate models.

scholarly journals A New Double-Moment Microphysics Parameterization for Application in Cloud and Climate Models. Part II: Single-Column Modeling of Arctic Clouds

2005 ◽  
Vol 62 (6) ◽  
pp. 1678-1693 ◽  
Author(s):  
H. Morrison ◽  
J. A. Curry ◽  
M. D. Shupe ◽  
P. Zuidema
Keyword(s):  
Climate Models ◽  
Heat Budget ◽  
Number Concentration ◽  
The Arctic ◽  
Liquid Water Path ◽  
Microphysics Scheme ◽  
Radiative Fluxes ◽  
Arctic Clouds ◽  
Single Column ◽  
Double Moment

Abstract The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April–15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud–aerosol–radiation interactions in arctic stratus.

scholarly journals How Well Do Regional Climate Models Reproduce Radiation and Clouds in the Arctic? An Evaluation of ARCMIP Simulations

2008 ◽  
Vol 47 (9) ◽  
pp. 2405-2422 ◽  
Author(s):  
Michael Tjernström ◽  
Joseph Sedlar ◽  
Matthew D. Shupe
Keyword(s):  
Heat Budget ◽  
Regional Climate ◽  
Cloud Water ◽  
Surface Radiation ◽  
The Arctic ◽  
Cloud Base ◽  
Base Temperature ◽  
Model Errors ◽  
Cloud Properties ◽  
Low Clouds

Abstract Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds.

scholarly journals Climatology of Warm Boundary Layer Clouds at the ARM SGP Site and Their Comparison to Models

2004 ◽  
Vol 17 (24) ◽  
pp. 4760-4782 ◽  
Author(s):  
Manajit Sengupta ◽  
Eugene E. Clothiaux ◽  
Thomas P. Ackerman
Keyword(s):  
Liquid Water ◽  
Solar Flux ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Cloud Forcing ◽  
Cloud Liquid Water Path ◽  
Ecmwf Model ◽  
Cloud Thickness

Abstract A 4-yr climatology (1997–2000) of warm boundary layer cloud properties is developed for the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) site. Parameters in the climatology include cloud liquid water path, cloud-base height, and surface solar flux. These parameters are retrieved from measurements produced by a dual-channel microwave radiometer, a millimeter-wave cloud radar, a micropulse lidar, a Belfort ceilometer, shortwave radiometers, and atmospheric temperature profiles amalgamated from multiple sources, including radiosondes. While no significant interannual differences are observed in the datasets, there are diurnal variations with nighttime liquid water paths consistently higher than daytime values. The summer months of June, July, and August have the lowest liquid water paths and the highest cloud-base heights. Model outputs of cloud liquid water paths from the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the Eta Model for 104 model output location time series (MOLTS) stations in the environs of the SGP central facility are compared to observations. The ECMWF and MOLTS median liquid water paths are greater than 3 times the observed values. The MOLTS data show lower liquid water paths in summer, which is consistent with observations, while the ECMWF data exhibit the opposite tendency. A parameterization of normalized cloud forcing that requires only cloud liquid water path and solar zenith angle is developed from the observations. The parameterization, which has a correlation coefficient of 0.81 with the observations, provides estimates of surface solar flux that are comparable to values obtained from explicit radiative transfer calculations based on plane-parallel theory. This parameterization is used to estimate the impact on the surface solar flux of differences in the liquid water paths between models and observations. Overall, there is a low bias of 50% in modeled normalized cloud forcing resulting from the excess liquid water paths in the two models. Splitting the liquid water path into two components, cloud thickness and liquid water content, shows that the higher liquid water paths in the model outputs are primarily a result of higher liquid water contents, although cloud thickness may a play a role, especially for the ECMWF model results.

scholarly journals Automated Mapping of Convective Clouds (AMCC) Thermodynamical, Microphysical, and CCN Properties from SNPP/VIIRS Satellite Data

2019 ◽  
Vol 58 (4) ◽  
pp. 887-902 ◽  
Author(s):  
Zhiguo Yue ◽  
Daniel Rosenfeld ◽  
Guihua Liu ◽  
Jin Dai ◽  
Xing Yu ◽  
...  
Keyword(s):  
Climate Models ◽  
Weather Forecasting ◽  
Meteorological Data ◽  
Cloud Condensation Nuclei ◽  
Convective Cloud ◽  
Cloud Base ◽  
Base Temperature ◽  
Cloud Drop ◽  
Automated Mapping ◽  
Convective Clouds

AbstractThe advent of the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi NPP (SNPP) satellite made it possible to retrieve a new class of convective cloud properties and the aerosols that they ingest. An automated mapping system of retrieval of some properties of convective cloud fields over large areas at the scale of satellite coverage was developed and is presented here. The system is named Automated Mapping of Convective Clouds (AMCC). The input is level-1 VIIRS data and meteorological gridded data. AMCC identifies the cloudy pixels of convective elements; retrieves for each pixel its temperature T and cloud drop effective radius re; calculates cloud-base temperature Tb based on the warmest cloudy pixels; calculates cloud-base height Hb and pressure Pb based on Tb and meteorological data; calculates cloud-base updraft Wb based on Hb; calculates cloud-base adiabatic cloud drop concentrations Nd,a based on the T–re relationship, Tb, and Pb; calculates cloud-base maximum vapor supersaturation S based on Nd,a and Wb; and defines Nd,a/1.3 as the cloud condensation nuclei (CCN) concentration NCCN at that S. The results are gridded 36 km × 36 km data points at nadir, which are sufficiently large to capture the properties of a field of convective clouds and also sufficiently small to capture aerosol and dynamic perturbations at this scale, such as urban and land-use features. The results of AMCC are instrumental in observing spatial covariability in clouds and CCN properties and for obtaining insights from such observations for natural and man-made causes. AMCC-generated maps are also useful for applications from numerical weather forecasting to climate models.

scholarly journals Implications of shortwave cloud forcing and feedbacks in the Southern Ocean

2006 ◽  
Vol 44 ◽  
pp. 15-22 ◽  
Author(s):  
Erica L. Key ◽  
Peter J. Minnett
Keyword(s):  
Southern Ocean ◽  
Radiative Forcing ◽  
Heat Budget ◽  
The Arctic ◽  
Cloud Forcing ◽  
Clear Sky ◽  
A Value ◽  
Atmospheric Transmissivity ◽  
The Antarctic ◽  
Surface Heat Budget

AbstractMeasurements of the incident solar radiation taken during the Antarctic Remote Ice Sensing Experiment (ARISE) aboard the R/V Aurora Australis in the Southern Ocean and springtime Antarctic ice pack are analyzed together with all-sky cloud imagery to determine the incident shortwave cloud radiative forcing at the surface. For most solar zenith angles (Z<82˚) in this dataset, the primary shortwave cloud effect is to induce cooling of the surface; as the sun approaches the horizon, however, the shortwave effects become negligible or even positive. The clear-sky atmospheric transmissivity over the length of the cruise is 0.91, a value comparable to those derived from measurements taken at various locations in the Arctic during daylight periods. Although the presence of clouds has a great effect on the surface heat budget and provides a negative shortwave feedback that may stabilize the polar atmosphere, the effect on the photosynthetically active radiation available to ice algae is relatively small in comparison to the effects of even small amounts of snow on sea ice.

scholarly journals Aggregate-area radiative flux biases

2002 ◽  
Vol 34 ◽  
pp. 101-105 ◽  
Author(s):  
Xuanji Wang ◽  
Jeffrey R. Key
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Heat Budget ◽  
Numerical Models ◽  
Radiative Flux ◽  
The Arctic ◽  
Radiative Fluxes ◽  
Cloud Properties ◽  
Model Cell ◽  
The Difference

AbstractMost climate models treat surface and atmospheric properties as being horizontally homogeneous and compute surface radiative fluxes with average gridcell properties. In this study it is found that large biases can occur if sub-gridcell variability is ignored, where bias is defined as the difference between the average of fluxes computed at high resolution within a model cell and the flux computed with the average surface and cloud properties within the cell. Data from the Advanced Very High Resolution Radiometer for the year-long Surface Heat Budget of the Arctic Ocean (SHEBA) experiment are used to determine biases in aggregate-area fluxes. A simple regression approach to correct for biases that result from horizontal variability was found to reduce the average radiative flux bias to near zero. The correction can be easily implemented in numerical models.

scholarly journals Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds

2014 ◽  
Vol 53 (12) ◽  
pp. 2775-2789 ◽  
Author(s):  
Joseph Sedlar
Keyword(s):  
Mixed Layer ◽  
Liquid Water ◽  
Heat Budget ◽  
Single Layer ◽  
Specific Humidity ◽  
The Arctic ◽  
Liquid Water Path ◽  
Stable Layer ◽  
Water Path ◽  
Low Level

AbstractObservations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP < 50 g m−2). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic–radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.

scholarly journals Secondary ice production in NorESM2 climate model: quantifying the impact on Arctic clouds

2021 ◽  
Author(s):  
Georgia Sotiropoulou ◽  
Anna Lewinschal ◽  
Annica Ekman ◽  
Athanasios Nenes
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
The Arctic ◽  
Liquid Water Path ◽  
Arctic Clouds ◽  
Radiative Balance ◽  
Microphysical Processes ◽  
Ice Production ◽  
Mixed Phase Clouds ◽  
The Impact

&lt;p&gt;Arctic clouds are among the largest sources of uncertainty in predictions of Arctic weather and climate. This is mainly due to errors in the representation of the cloud thermodynamic phase and the associated radiative impacts, which largely depends on the parameterization of cloud microphysical processes. Secondary ice processes (SIP) are among the microphysical processes that are poorly represented, or completely absent, in climate models. In most models, including the Norwegian Earth System Model -version 2 (NorESM2), Hallet-Mossop (H-M) is the only SIP mechanism available. In this study we further improve the description of H-M and include two additional SIP mechanisms (collisional break-up and drop-shattering) in NorESM2. Our results indicate that these additions improve the agreement between observed and modeled ice crystal number concentrations and liquid water path in mixed-phase clouds observed at Ny-Alesund in 2016-2017. We then conclude by quantifying the impact of these overlooked SIP mechanisms for cloud microphysical characteristics, properties and the radiative balance throughout the Arctic.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals A COMPARISON BETWEEN EXPERIENTIAL AND ECMWF REANALYZED CONDENSED MOISTURE PROFILE OVER THE NORTHEASTERN SPHERE

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 177-180
Author(s):  
X. Z. Wang ◽  
B. H. Hu ◽  
J. Wang ◽  
H. Huang ◽  
W. J. Zhang ◽  
...  
Keyword(s):  
Arctic Region ◽  
General Information ◽  
The Arctic ◽  
Cloud Base ◽  
Large Temperature ◽  
Height Distribution ◽  
Liquid Water Path ◽  
Moisture Profile ◽  
Warm Cloud ◽  
Condensed Moisture

Abstract. Base on January and July 4-times daily ECMWF Interim data from 2009 to 2018 over the Northeast Sphere (0–180E,0–90N), the condensed moisture profile of experiential methods and that of ECMWF analysis are compared. The result shows that, the meridional-height distribution of mean cloud condensed moisture has a maximum slab spreading near ground in the Arctic region in July, and the maximum takes a circular shape at 700 hPa above 30N latitude in January. The distribution feature unlike the universal profile, it distributes in a single or double peak function manner, instead of a constant value. The quick decreasing level height and thickness varies with latitude, especially in January. The second experiential profile concerning warm cloud assumes air parcel lifting adiabatically, the liquid water path (LWP) is compared for general information. The result shows that the experiential LWP is much larger than that of the reanalysis by 1 to 2 order, decreasing with latitudes. The possible reason of LWP difference is from the critic water content value of cloud boundary identification. If the value is small, the thickness of warm cloud will be large, temperature and pressure at the cloud base are both large too, results in a larger LWP. These results will enrich the knowledge of the condensed moisture characteristics of ECMWF reanalysis and the experiential moisture profile methods.

scholarly journals The effect of aerosol on surface cloud radiative forcing in the Arctic

2005 ◽  
Vol 5 (5) ◽  
pp. 9039-9063 ◽  
Author(s):  
R.-M. Hu ◽  
J.-P. Blanchet ◽  
E. Girard
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
High Surface ◽  
The Arctic ◽  
Cloud Radiative Forcing ◽  
Cloud Forcing ◽  
Aerosol Forcing ◽  
Albedo Effect

Abstract. Cloud radiative forcing is a very important concept to understand what kind of role the clouds play in climate change with thermal effect or albedo effect. In spite of that much progress has been achieved, the clouds are still poorly described in the climate models. Due to the complex aerosol-cloud-radiation interactions, high surface albedo of snow and ice cover, and without solar radiation in long period of the year, the Arctic strong warming caused by increasing greenhouse gases (as most GCMs suggested) has not been verified by the observations. In this study, we were dedicated to quantify the aerosol effect on the Arctic cloud radiative forcing by Northern Aerosol Regional Climate Model (NARCM). Major aerosol species such as Arctic haze sulphate, black carbon, sea salt, organics and dust have been included during our simulations. By inter-comparisons with the Atmospheric Radiation Measurement (ARM) data, we find surface cloud radiative forcing (SCRF) is −22 W/m2 for shortwave and 36 W/m2 for longwave. Total cloud forcing is 14 W/m2 with minimum of −35 W/m2 in early July. If aerosols are taken into account, the SCRF has been increased during winter while negative SCRF has been enhanced during summer. Our estimate of aerosol forcing is about −6 W/m2 in the Arctic.

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