scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: Retrievals of cloud microphysical properties

2019 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Steven Neshyba ◽  
Von P. Walden
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Effective Radius ◽  
Mixed Phase ◽  
The Arctic ◽  
Polar Regions ◽  
Microphysical Properties ◽  
Instrument Resolution ◽  
Retrieval Errors ◽  
Measurement Biases

Abstract. Improvements to climate model results in polar regions require improved knowledge of cloud microphysical properties. Surface-based infrared radiance spectrometers have been used to retrieve cloud microphysical properties in polar regions, but measurements are sparse. Reductions in cost and power requirements to allow more widespread measurements could be aided by reducing instrument resolution. Here we explore the effect of errors and instrument resolution on cloud microphysical property retrievals from downwelling infrared radiances for resolutions of 0.1 to 8 cm−1. Retrievals are tested on 331 radiance simulations characteristic of the Arctic, including mixed-phase, vertically inhomogeneous, and liquid-topped clouds and a variety of ice habits. Results indicate that measurement biases lead to biases in retrieved properties that are not represented by the retrieval error covariance matrix. Retrieval errors are high if mixed-phase is assumed throughout liquid-topped ice clouds. Errors due to assuming ice habit is spherical are progressively larger for solid columns, plates, and hollow bullet rosettes. Using retrieved cloud heights, particularly when errors are imposed, increases retrieval errors but decreases sensitivity to incorrect ice habits and vertical variation. Results indicate that retrieval accuracy is unaffected by resolution from 0.1 to 2 cm−1, after which it decreases only slightly. At a resolution of 4 cm−1, for typical errors expected in temperature (0.2 K) and water vapour (3 %), and assuming radiation bias and noise of 0.2 mW/(m2 sr cm−1), using retrieved cloud heights, error estimates are 0.1 ± 0.6 for optical depth, 0.0 ± 0.3 for ice fraction, 0 &plusmnl 2 μm for effective radius of liquid, and 2 ± 2 μm for effective radius of ice. These results indicate that a moderately low resolution, portable, surface-based infrared spectrometer could provide microphysical properties to help constrain climate models.

scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties

2019 ◽  
Vol 12 (9) ◽  
pp. 5071-5086 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Steven Neshyba ◽  
Von P. Walden
Keyword(s):  
Climate Model ◽  
Effective Radius ◽  
The Arctic ◽  
Polar Regions ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Instrument Resolution ◽  
Mean Square Errors ◽  
Ice Fraction

Abstract. Improvements to climate model results in polar regions require improved knowledge of cloud properties. Surface-based infrared (IR) radiance spectrometers have been used to retrieve cloud properties in polar regions, but measurements are sparse. Reductions in cost and power requirements to allow more widespread measurements could be aided by reducing instrument resolution. Here we explore the effects of errors and instrument resolution on cloud property retrievals from downwelling IR radiances for resolutions of 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulations characteristic of the Arctic, including mixed-phase, vertically inhomogeneous, and liquid-topped clouds and a variety of ice habits. Retrieval accuracy is found to be unaffected by resolution from 0.1 to 4 cm−1, after which it decreases slightly. When cloud heights are retrieved, errors in retrieved cloud optical depth (COD) and ice fraction are considerably smaller for clouds with bases below 2 km than for higher clouds. For example, at a resolution of 4 cm−1, with errors imposed (noise and radiation bias of 0.2 mW/(m2 sr cm−1) and biases in temperature of 0.2 K and in water vapor of −3 %), using retrieved cloud heights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to 0.18 for ice fraction (fice), and 10 to 7 µm for ice effective radius (errors remain at 2 µm for liquid effective radius). These results indicate that a moderately low-resolution, surface-based IR spectrometer could provide cloud property retrievals with accuracy comparable to existing higher-resolution instruments and that such an instrument would be particularly useful for low-level clouds.

scholarly journals Polar Cooling Effect Due to Increase of Phytoplankton and Dimethyl-Sulfide Emission

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 384 ◽  
Author(s):  
Ah-Hyun Kim ◽  
Seong Yum ◽  
Hannah Lee ◽  
Dong Chang ◽  
Sungbo Shim
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Models ◽  
Dimethyl Sulfide ◽  
Climate Model ◽  
Cloud Condensation Nuclei ◽  
Marine Phytoplankton ◽  
The Arctic ◽  
Polar Regions ◽  
Cloud Albedo

The effects of increased dimethyl-sulfide (DMS) emissions due to increased marine phytoplankton activity are examined using an atmosphere-ocean coupled climate model. As the DMS emission flux from the ocean increases globally, large-scale cooling occurs due to the DMS-cloud condensation nuclei (CCN)-cloud albedo interactions. This cooling increases as DMS emissions are further increased, with the most pronounced effect occurring over the Arctic, which is likely associated with a change in sea-ice fraction as sea ice mediates the air-sea exchange of the radiation, moisture and heat flux. These results differ from recent studies that only considered the bio-physical feedback that led to amplified Arctic warming under greenhouse warming conditions. Therefore, climate negative feedback from DMS-CCN-cloud albedo interactions that involve marine phytoplankton and its impact on polar climate should be properly reflected in future climate models to better estimate climate change, especially over the polar regions.

scholarly journals A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness

2020 ◽  
Vol 13 (1) ◽  
pp. 297-314 ◽  
Author(s):  
Salomon Eliasson ◽  
Karl-Göran Karlsson ◽  
Ulrika Willén
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Probability Of Detection ◽  
The Arctic ◽  
Small Scale ◽  
Polar Regions ◽  
Cloud Detection ◽  
Climate Data ◽  
Data Record ◽  
Climate Data Record

Abstract. This paper describes a new satellite simulator for the CLARA-A2 climate data record (CDR). This simulator takes into account the variable skill in cloud detection in the CLARA-A2 CDR by using a different approach to other similar satellite simulators to emulate the ability to detect clouds. In particular, the paper describes three methods to filter out clouds from climate models undetectable by observations. The first method is comparable to the current simulators in the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP), since it relies on a single visible cloud optical depth at 550 nm (τc) threshold applied globally to delineate cloudy and cloud-free conditions. Methods two and three apply long/lat-gridded values separated by daytime and nighttime conditions. Method two uses gridded varying τc as opposed to method one, which uses just a τc threshold, and method three uses a cloud probability of detection (POD) depending on the model τc. The gridded POD values are from the CLARA-A2 validation study by Karlsson and Håkansson (2018). Methods two and three replicate the relative ease or difficulty for cloud retrievals depending on the region and illumination. They increase the cloud sensitivity where the cloud retrievals are relatively straightforward, such as over midlatitude oceans, and they decrease the sensitivity where cloud retrievals are notoriously tricky, such as where thick clouds may be inseparable from cold snow-covered surfaces, as well as in areas with an abundance of broken and small-scale cumulus clouds such as the atmospheric subsidence regions over the ocean. The simulator, together with the International Satellite Cloud Climatology Project (ISCCP) simulator of the COSP, is used to assess Arctic clouds in the EC-Earth climate model compared to the CLARA-A2 and ISCCP H-Series (ISCCP-H) CDRs. Compared to CLARA-A2, EC-Earth generally underestimates cloudiness in the Arctic. However, compared to ISCCP and its simulator, the opposite conclusion is reached. Based on EC-Earth, this paper shows that the simulated cloud mask of CLARA-A2, using method three, is more representative of the CDR than method one used for the ISCCP simulator. The simulator substantially improves the simulation of the CLARA-A2-detected clouds, especially in the polar regions, by accounting for the variable cloud detection skill over the year. The approach to cloud simulation based on the POD of clouds depending on their τc, location, and illumination is the preferred one as it reduces cloudiness over a range of cloud optical depths. Climate model comparisons with satellite-derived information can be significantly improved by this approach, mainly by reducing the risk of misinterpreting problems with satellite retrievals as cloudiness features. Since previous studies found that the CLARA-A2 CDR performs well in the Arctic during the summer months, and that method three is more representative than method one, the conclusion is that EC-Earth likely underestimates clouds in the Arctic summer.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

The Impact of Mixed-Phase Microphysical Processes on the Turbulence in Low-level Clouds in the Arctic

2021 ◽  
Author(s):  
Jan Chylik ◽  
Roel Neggers
Keyword(s):  
Boundary Layer ◽  
Climate Models ◽  
Weather Forecast ◽  
Mixed Phase ◽  
The Arctic ◽  
Contributing Factors ◽  
Microphysics Scheme ◽  
Low Level ◽  
Microphysical Processes ◽  
The Impact

<p>The proper representation of Arctic mixed-phased clouds remains a challenge in both weather forecast and climate models. Amongst the contributing factors is the complexity of turbulent properties of clouds. While the effect of evaporating hydrometeors on turbulent properties of the boundary layer has been identified in other latitudes, the extent of similar studies in the Arctic has been so far limited.</p><p>Our study focus on the impact of heat release from mixed-phase microphysical processes on the turbulent properties of the convective low-level clouds in the Arctic. We  employ high-resolution simulations, properly constrained by relevant measurements.<br>Semi-idealised model cases are based on convective clouds observed during the recent campaign in the Arctic: ACLOUD, which took place May--June 2017 over Fram Strait. The simulations are performed in Dutch Atmospheric Large Eddy Simulation (DALES) with double-moment mixed-phase microphysics scheme of Seifert & Beheng.</p><p>The results indicate an enhancement of boundary layer turbulence is some convective regimes.<br>Furthermore, results are sensitive to aerosols concentrations. Additional implications for the role of mixed-phase clouds in the Arctic Amplification will be discussed.</p>

scholarly journals Arctic and Antarctic precipitation simulations produced by the NCAR community climate models

1995 ◽  
Vol 21 ◽  
pp. 117-122 ◽  
Author(s):  
David H. Bromwich ◽  
Biao Chen ◽  
Ren-Yow Tzeng
Keyword(s):  
Moisture Transport ◽  
Climate Models ◽  
Climate Model ◽  
Polar Regions ◽  
Moisture Budget ◽  
Atmospheric Moisture ◽  
Atmospheric Moisture Budget ◽  
Antarctic Precipitation ◽  
Climatic Characteristics ◽  
Community Climate

Precipitation predictions from globai-climate models (GCMs) for the ice-covered Arctic Ocean and the ice sheets of Antarctica are among the most important aspects of the inferred response of the polar areas to climate change. It is generally recognized that the atmospheric hydrologic cycle, which includes precipitation as a key part, is one of the components of the climate system that GCMs do not handle particularly well. The present-day atmospheric-moisture budget poleward of 70° latitude in both hemispheres, as represented by two versions of the NCAR (U.S. National Center for Atmospheric Research) community climate model (CCM1 and CCM2), is compared with observational analyses. The quantities examined on the seasonal and annual timescales are precipitation, evaporation/sublimation and atmospheric poleward moisture transport. The results are discussed in terms of the physiographic and climatic characteristics of both polar regions and how the particular models handle moisture transport: CCM1 uses the positive-moisture fixer and CCM2 the semi- Lagrangian transport. A particularly important test both for models and for observations is the degree to which the independently determined moisture-budget quantities actually balance. Deficiencies of both observations and models are discussed.

scholarly journals Impact of ocean circulation on regional polar climate simulations using the Arctic Region Climate System Model

1997 ◽  
Vol 25 ◽  
pp. 203-207 ◽  
Author(s):  
David A. Bailey ◽  
Amanda H. Lynch ◽  
Katherine S. Hedström
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Models ◽  
Regional Climate ◽  
The Arctic ◽  
Water Runoff ◽  
Polar Regions ◽  
Ice Dynamics ◽  
Climate System Model ◽  
Ice Model

Global climate models have pointed to the polar regions as very sensitive areas in response to climate change. However, these models often do not contain representations of processes peculiar to the polar regions such as dynamic sea ice, permafrost, and Arctic stratus clouds. Further, global models do not have the resolution necessary to model accurately many of the important processes and feedbacks. Thus, there is a need for regional climate models of higher resolution. Our such model (ARCSy M) has been developed by A. Lynch and W. Chapman. This model incorporates the NCAR Regional Climate Model (RegCM2) with the addition of Flato–Hibler cavitating fluid sea-ice dynamics and Parkinson–Washington ice thermodynamic formulation. Recently work has been conducted to couple a mixed-layer ocean to the atmosphere–ice model, and a three-dimensional (3-D) dynamical ocean model, in this case the S-Coordinate Primitive Equation Model (SPEM), to the ice model. Simulations including oceanic circulation will allow investigations of the feedbacks involved in fresh-water runoff from sea-ice melt and sea-ice transport. Further, it is shown that the definition of the mixed-layer depth has significant impact on ice thermodynamics.

scholarly journals Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

2019 ◽  
Author(s):  
Fernanda Casagrande ◽  
Ronald Buss de Souza ◽  
Paulo Nobre ◽  
Andre Lanfer Marquez
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Initial Conditions ◽  
The Arctic ◽  
Climate Simulation ◽  
Polar Regions ◽  
High Latitudes ◽  
Polar Amplification

Abstract. The numerical climate simulation from Brazilian Earth System Model (BESM) are used here to investigate the response of Polar Regions to a forced increase of CO2 (Abrupt-4xCO2) and compared with Coupled Model Intercomparison Project 5 (CMIP5) simulations. Polar Regions are described as the most climatically sensitive areas of the globe, with an enhanced warming occurring during the cold seasons. The asymmetry between the two poles is related to the thermal inertia and the coupled ocean atmosphere processes involved. While in the northern high latitudes the amplified warming signal is associated to a positive snow and sea ice albedo feedback, for southern high latitudes the warming is related to a combination of ozone depletion and changes in the winds pattern. The numerical experiments conducted here demonstrated a very clear evidence of seasonality in the polar amplification response. In winter, for the northern high latitudes (southern high latitudes) the range of simulated polar warming varied from 15 K to 30 K (2.6 K to 10 K). In summer, for northern high latitudes (southern high latitudes) the simulated warming varies from 3 K to 15 K (3 K to 7 K). The vertical profiles of air temperature indicated stronger warming at surface, particularly for the Arctic region, suggesting that the albedo-sea ice feedback overlaps with the warming caused by meridional transport of heat in atmosphere. The latitude of the maximum warming was inversely correlated with changes in the sea ice within the model’s control run. Three climate models were identified as having high polar amplification for cold season in both poles: MIROC-ESM, BESM-OA V2.5 and GFDL-ESM2M. We suggest that the large BIAS found between models can be related to the differences in each model to represent the feedback process and also as a consequence of the distinct sea ice initial conditions of each model. The polar amplification phenomenon has been observed previously and is expected to become stronger in coming decades. The consequences for the atmospheric and ocean circulation are still subject to intense debate in the scientific community.

scholarly journals Impact of ocean circulation on regional polar climate simulations using the Arctic Region Climate System Model

1997 ◽  
Vol 25 ◽  
pp. 203-207 ◽  
Author(s):  
David A. Bailey ◽  
Amanda H. Lynch ◽  
Katherine S. Hedström
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Models ◽  
Regional Climate ◽  
The Arctic ◽  
Water Runoff ◽  
Polar Regions ◽  
Ice Dynamics ◽  
Climate System Model ◽  
Ice Model

Global climate models have pointed to the polar regions as very sensitive areas in response to climate change. However, these models often do not contain representations of processes peculiar to the polar regions such as dynamic sea ice, permafrost, and Arctic stratus clouds. Further, global models do not have the resolution necessary to model accurately many of the important processes and feedbacks. Thus, there is a need for regional climate models of higher resolution. Our such model (ARCSy M) has been developed by A. Lynch and W. Chapman. This model incorporates the NCAR Regional Climate Model (RegCM2) with the addition of Flato–Hibler cavitating fluid sea-ice dynamics and Parkinson–Washington ice thermodynamic formulation. Recently work has been conducted to couple a mixed-layer ocean to the atmosphere–ice model, and a three-dimensional (3-D) dynamical ocean model, in this case the S-Coordinate Primitive Equation Model (SPEM), to the ice model. Simulations including oceanic circulation will allow investigations of the feedbacks involved in fresh-water runoff from sea-ice melt and sea-ice transport. Further, it is shown that the definition of the mixed-layer depth has significant impact on ice thermodynamics.

scholarly journals Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

2017 ◽  
Vol 17 (9) ◽  
pp. 5973-5989 ◽  
Author(s):  
Yinghui Liu ◽  
Matthew D. Shupe ◽  
Zhien Wang ◽  
Gerald Mace
Keyword(s):  
Vertical Distribution ◽  
Climate Models ◽  
Cloud Fraction ◽  
The Arctic ◽  
Active Sensors ◽  
Annual Cycles ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Cloud Water Content ◽  
Vertical Distributions

Abstract. Detailed and accurate vertical distributions of cloud properties (such as cloud fraction, cloud phase, and cloud water content) and their changes are essential to accurately calculate the surface radiative flux and to depict the mean climate state. Surface and space-based active sensors including radar and lidar are ideal to provide this information because of their superior capability to detect clouds and retrieve cloud microphysical properties. In this study, we compare the annual cycles of cloud property vertical distributions from space-based active sensors and surface-based active sensors at two Arctic atmospheric observatories, Barrow and Eureka. Based on the comparisons, we identify the sensors' respective strengths and limitations, and develop a blended cloud property vertical distribution by combining both sets of observations. Results show that surface-based observations offer a more complete cloud property vertical distribution from the surface up to 11 km above mean sea level (a.m.s.l.) with limitations in the middle and high altitudes; the annual mean total cloud fraction from space-based observations shows 25–40 % fewer clouds below 0.5 km than from surface-based observations, and space-based observations also show much fewer ice clouds and mixed-phase clouds, and slightly more liquid clouds, from the surface to 1 km. In general, space-based observations show comparable cloud fractions between 1 and 2 km a.m.s.l., and larger cloud fractions above 2 km a.m.s.l. than from surface-based observations. A blended product combines the strengths of both products to provide a more reliable annual cycle of cloud property vertical distributions from the surface to 11 km a.m.s.l. This information can be valuable for deriving an accurate surface radiative budget in the Arctic and for cloud parameterization evaluation in weather and climate models. Cloud annual cycles show similar evolutions in total cloud fraction and ice cloud fraction, and lower liquid-containing cloud fraction at Eureka than at Barrow; the differences can be attributed to the generally colder and drier conditions at Eureka relative to Barrow.

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