scholarly journals Evaluation of polar stratospheric clouds in the global chemistry-climate model SOCOLv3.1 by comparison with CALIPSO spaceborne lidar measurements

2020 ◽  
Author(s):  
Michael Steiner ◽  
Beiping Luo ◽  
Thomas Peter ◽  
Michael C. Pitts ◽  
Andrea Stenke
Keyword(s):  
Optical Properties ◽  
Climate Models ◽  
Climate Model ◽  
Particle Radius ◽  
Process Models ◽  
Number Density ◽  
Polar Stratospheric Clouds ◽  
Microphysical Process ◽  
Stratospheric Clouds ◽  
The Antarctic

Abstract. Polar Stratospheric Clouds (PSCs) contribute to catalytic ozone destruction by providing surfaces for the conversion of inert chlorine species into active forms and by denitrification of the stratosphere. Therefore, an accurate representation of PSCs in chemistry-climate models (CCMs) is of great importance to correctly simulate polar ozone concentrations. Here, we evaluate PSCs as simulated by the CCM SOCOLv3.1 for the Antarctic winter 2007 by comparison with backscatter measurements by CALIOP onboard the CALIPSO satellite. The model considers supercooled ternary solution (STS) droplets, nitric acid trihydrate (NAT) particles, water ice particles, and mixtures thereof. PSCs are parametrized in terms of temperature and partial pressures of HNO3 and H2O, assuming equilibrium between gas and particulate phase. We use the CALIOP measurements to optimize three prescribed microphysical parameters of the PSC scheme, namely ice number density, NAT particle radius and maximum NAT number density. The choice of the prescribed value of the ice number density affects simulated optical properties and dehydration, while modifying the maximum NAT number density or the NAT particle radius impacts stratospheric composition by enhancing the HNO3-uptake and denitrification. Best agreement with the CALIOP optical properties and observed denitrification was for this case study found with the ice number density increased from the hitherto used value of 0.01 to 0.05 cm−3 and the maximum NAT number density from 5×10−4 to 1×10−3 cm−3. The NAT radius was kept at the original value of 5 µm. The new parametrization reflects the higher importance attributed to heterogeneous nucleation of ice and NAT particles, e.g. on meteoric dust, following recent new data evaluations of the state-of-the-art CALIOP measurements. A cold temperature bias in the polar lower stratosphere results in an overestimated PSC areal coverage in SOCOLv3.1 by up to 100 %. Furthermore, the occurrence of mountain-wave induced ice, as observed mainly over the Antarctic Peninsula, is continuously underestimated in the model due to the coarse model resolution and the fixed ice number density. However, overall we find a good temporal and spatial agreement between modeled and observed PSC occurrence and composition, as well as reasonable modeled denitrification and ozone loss. Based on constraining three important parameters by means of the CALIOP measurements, this work demonstrates that also a simplified PSC scheme, which describes STS, NAT, ice and mixtures thereof with equilibrium assumptions and avoids nucleation and growth calculations in sophisticated, but time-consuming microphysical process models, may achieve good approximations of fundamental properties of PSCs needed in CCMs.

scholarly journals Evaluation of polar stratospheric clouds in the global chemistry–climate model SOCOLv3.1 by comparison with CALIPSO spaceborne lidar measurements

2021 ◽  
Vol 14 (2) ◽  
pp. 935-959
Author(s):  
Michael Steiner ◽  
Beiping Luo ◽  
Thomas Peter ◽  
Michael C. Pitts ◽  
Andrea Stenke
Keyword(s):  
Optical Properties ◽  
Climate Models ◽  
Climate Model ◽  
Process Models ◽  
Cold Bias ◽  
Number Density ◽  
Polar Stratospheric Clouds ◽  
Microphysical Process ◽  
Stratospheric Clouds ◽  
The Antarctic

Abstract. Polar stratospheric clouds (PSCs) contribute to catalytic ozone destruction by providing surfaces for the conversion of inert chlorine species into active forms and by denitrification. The latter describes the removal of HNO3 from the stratosphere by sedimenting PSC particles, which hinders chlorine deactivation by the formation of reservoir species. Therefore, an accurate representation of PSCs in chemistry–climate models (CCMs) is of great importance to correctly simulate polar ozone concentrations. Here, we evaluate PSCs as simulated by the CCM SOCOLv3.1 for the Antarctic winters 2006, 2007 and 2010 by comparison with backscatter measurements by CALIOP on board the CALIPSO satellite. The year 2007 represents a typical Antarctic winter, while 2006 and 2010 are characterized by above- and below-average PSC occurrence. The model considers supercooled ternary solution (STS) droplets, nitric acid trihydrate (NAT) particles, water ice particles and mixtures thereof. PSCs are parameterized in terms of temperature and partial pressures of HNO3 and H2O, assuming equilibrium between the gas and particulate phase. The PSC scheme involves a set of prescribed microphysical parameters, namely ice number density, NAT particle radius and maximum NAT number density. In this study, we test and optimize the parameter settings through several sensitivity simulations. The choice of the value for the ice number density affects simulated optical properties and dehydration, while modifying the NAT parameters impacts stratospheric composition via HNO3 uptake and denitrification. Depending on the NAT parameters, reasonable denitrification can be modeled. However, its impact on ozone loss is minor. The best agreement with the CALIOP optical properties and observed denitrification was for this case study found with the ice number density increased from the hitherto used value of 0.01 to 0.05 cm−3 and the maximum NAT number density from 5×10-4 to 1×10-3 cm−3. The NAT radius was kept at the original value of 5 µm. The new parameterization reflects the higher importance attributed to heterogeneous nucleation of ice and NAT particles following recent new data evaluations of the state-of-the-art CALIOP measurements. A cold temperature bias in the polar lower stratosphere results in an overestimated PSC areal coverage in SOCOLv3.1 by up to 40 %. Offsetting this cold bias by +3 K delays the onset of ozone depletion by about 2 weeks, which improves the agreement with observations. Furthermore, the occurrence of mountain-wave-induced ice, as observed mainly over the Antarctic Peninsula, is continuously underestimated in the model due to the coarse model resolution (T42L39) and the fixed ice number density. Nevertheless, we find overall good temporal and spatial agreement between modeled and observed PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes, which avoid nucleation and growth calculations in sophisticated but time-consuming microphysical process models, may also achieve good approximations of the fundamental properties of PSCs needed in CCMs.

scholarly journals Mountain-wave induced polar stratospheric clouds and their representation in the global chemistry model ICON-ART

2020 ◽  
Author(s):  
Michael Weimer ◽  
Jennifer Buchmüller ◽  
Lars Hoffmann ◽  
Ole Kirner ◽  
Beiping Luo ◽  
...  
Keyword(s):  
Antarctic Peninsula ◽  
Climate Models ◽  
Hot Spot ◽  
Heterogeneous Reactions ◽  
Polar Stratospheric Clouds ◽  
Mountain Wave ◽  
Mountain Waves ◽  
Stratospheric Clouds ◽  
Wave Induced ◽  
The Antarctic

Abstract. Polar stratospheric clouds (PSCs) are a driver for ozone depletion in the lower polar stratosphere. They provide surfaces for heterogeneous reactions activating chlorine and bromine reservoir species during the polar night. PSCs are represented in current global chemistry-climate models, but one process is still a challenge: the representation of PSCs formed locally in conjunction with unresolved mountain waves. In this study, we present simulations with the ICOsahedral Nonhydrostatic modelling framework (ICON) with its extension for Aerosols and Reactive Trace gases (ART) that include local grid refinements (nesting) with two-way interaction. Here, the nesting is set up around the Antarctic Peninsula which is a well-known hot spot for the generation of mountain waves in the southern hemisphere. We compare our model results with satellite measurements from the Cloud-Aerosol LIdar with Orthogonal Polarisation (CALIOP) and the Atmospheric InfraRed Sounder (AIRS). We study a mountain wave event that took place from 19 to 29 July 2008 and find similar structures of PSCs as well as a fairly realistic development of the mountain wave in the Antarctic Peninsula nest. We compare a global simulation without nesting with the nested configuration to show the benefit. Although the mountain waves cannot be resolved adequately in the used global resolution (about 160 km), their effect from the nested regions (about 80 and 40 km) on the global domain is represented. Thus, we show in this study that by using the two-way nesting technique the gap between directly resolved mountain-wave induced PSCs and their representation and effect on chemistry in coarse global resolutions can be bridged by the ICON-ART model.

scholarly journals Can gravity waves significantly impact PSC occurrence in the Antarctic?

2009 ◽  
Vol 9 (22) ◽  
pp. 8825-8840 ◽  
Author(s):  
A. J. McDonald ◽  
S. E. George ◽  
R. M. Woollands
Keyword(s):  
Antarctic Peninsula ◽  
Gravity Waves ◽  
Clustering Algorithm ◽  
Small Scale ◽  
Temperature Threshold ◽  
Aerosol Extinction ◽  
Polar Stratospheric Clouds ◽  
Mountain Wave ◽  
Stratospheric Clouds ◽  
The Antarctic

Abstract. A combination of POAM III aerosol extinction and CHAMP RO temperature measurements are used to examine the role of atmospheric gravity waves in the formation of Antarctic Polar Stratospheric Clouds (PSCs). POAM III aerosol extinction observations and quality flag information are used to identify Polar Stratospheric Clouds using an unsupervised clustering algorithm. A PSC proxy, derived by thresholding Met Office temperature analyses with the PSC Type Ia formation temperature (TNAT), shows general agreement with the results of the POAM III analysis. However, in June the POAM III observations of PSC are more abundant than expected from temperature threshold crossings in five out of the eight years examined. In addition, September and October PSC identified using temperature thresholding is often significantly higher than that derived from POAM III; this observation probably being due to dehydration and denitrification. Comparison of the Met Office temperature analyses with corresponding CHAMP observations also suggests a small warm bias in the Met Office data in June. However, this bias cannot fully explain the differences observed. Analysis of CHAMP data indicates that temperature perturbations associated with gravity waves may partially explain the enhanced PSC incidence observed in June (relative to the Met Office analyses). For this month, approximately 40% of the temperature threshold crossings observed using CHAMP RO data are associated with small-scale perturbations. Examination of the distribution of temperatures relative to TNAT shows a large proportion of June data to be close to this threshold, potentially enhancing the importance of gravity wave induced temperature perturbations. Inspection of the longitudinal structure of PSC occurrence in June 2005 also shows that regions of enhancement are geographically associated with the Antarctic Peninsula; a known mountain wave "hotspot". The latitudinal variation of POAM III observations means that we only observe this region in June–July, and thus the true pattern of enhanced PSC production may continue operating into later months. The analysis has shown that early in the Antarctic winter stratospheric background temperatures are close to the TNAT threshold (and PSC formation), and are thus sensitive to temperature perturbations associated with mountain wave activity near the Antarctic peninsula (40% of PSC formation). Later in the season, and at latitudes away from the peninsula, temperature perturbations associated with gravity waves contribute to about 15% of the observed PSC (a value which corresponds well to several previous studies). This lower value is likely to be due to colder background temperatures already achieving the TNAT threshold unaided. Additionally, there is a reduction in the magnitude of gravity waves perturbations observed as POAM III samples poleward of the peninsula.

Regional Climate Model Inter-Comparison for Antarctica within a Data Science Framework

2021 ◽  
Author(s):  
Jeremy Carter ◽  
Amber Leeson ◽  
Andrew Orr ◽  
Christoph Kittel ◽  
Melchior van Wessem
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate Change ◽  
Near Surface ◽  
Virtual Lab ◽  
Model Variability ◽  
The Antarctic

<p>Understanding the surface climatology of the Antarctic ice sheet is essential if we are to adequately predict its response to future climate change. This includes both primary impacts such as increased ice melting and secondary impacts such as ice shelf collapse events. Given its size, and inhospitable environment, weather stations on Antarctica are sparse. Thus, we rely on regional climate models to 1) develop our understanding of how the climate of Antarctica varies in both time and space and 2) provide data to use as context for remote sensing studies and forcing for dynamical process models. Given that there are a number of different regional climate models available that explicitly simulate Antarctic climate, understanding inter- and intra model variability is important.</p><p>Here, inter- and intra-model variability in Antarctic-wide regional climate model output is assessed for: snowfall; rainfall; snowmelt and near-surface air temperature within a cloud-based virtual lab framework. State-of-the-art regional climate model runs from the Antarctic-CORDEX project using the RACMO, MAR and MetUM models are used, together with the ERA5 and ERA-Interim reanalyses products. Multiple simulations using the same model and domain boundary but run at either different spatial resolutions or with different driving data are used. Traditional analysis techniques are exploited and the question of potential added value from more modern and involved methods such as the use of Gaussian Processes is investigated. The advantages of using a virtual lab in a cloud based environment for increasing transparency and reproducibility, are demonstrated, with a view to ultimately make the code and methods used widely available for other research groups.</p>

scholarly journals A closer look at Arctic ozone loss and polar stratospheric clouds

2010 ◽  
Vol 10 (17) ◽  
pp. 8499-8510 ◽  
Author(s):  
N. R. P. Harris ◽  
R. Lehmann ◽  
M. Rex ◽  
P. von der Gathen
Keyword(s):  
Nitric Acid ◽  
Climate Models ◽  
Empirical Relationship ◽  
Early Spring ◽  
Aerosol Formation ◽  
Polar Stratospheric Clouds ◽  
Ozone Loss ◽  
Relationship Analysis ◽  
Near Ultraviolet ◽  
Stratospheric Clouds

Abstract. The empirical relationship found between column-integrated Arctic ozone loss and the potential volume of polar stratospheric clouds inferred from meteorological analyses is recalculated in a self-consistent manner using the ERA Interim reanalyses. The relationship is found to hold at different altitudes as well as in the column. The use of a PSC formation threshold based on temperature dependent cold aerosol formation makes little difference to the original, empirical relationship. Analysis of the photochemistry leading to the ozone loss shows that activation is limited by the photolysis of nitric acid. This step produces nitrogen dioxide which is converted to chlorine nitrate which in turn reacts with hydrogen chloride on any polar stratospheric clouds to form active chlorine. The rate-limiting step is the photolysis of nitric acid: this occurs at the same rate every year and so the interannual variation in the ozone loss is caused by the extent and persistence of the polar stratospheric clouds. In early spring the ozone loss rate increases as the solar insolation increases the photolysis of the chlorine monoxide dimer in the near ultraviolet. However the length of the ozone loss period is determined by the photolysis of nitric acid which also occurs in the near ultraviolet. As a result of these compensating effects, the amount of the ozone loss is principally limited by the extent of original activation rather than its timing. In addition a number of factors, including the vertical changes in pressure and total inorganic chlorine as well as denitrification and renitrification, offset each other. As a result the extent of original activation is the most important factor influencing ozone loss. These results indicate that relatively simple parameterisations of Arctic ozone loss could be developed for use in coupled chemistry climate models.

scholarly journals Maintenance of polar stratospheric clouds in a moist stratosphere

2008 ◽  
Vol 4 (1) ◽  
pp. 69-78 ◽  
Author(s):  
D. B. Kirk-Davidoff ◽  
J.-F. Lamarque
Keyword(s):  
Water Vapor ◽  
Particle Number Density ◽  
Water Vapor Transport ◽  
Number Density ◽  
Radiative Effects ◽  
Polar Stratospheric Clouds ◽  
Substantial Impact ◽  
Stratospheric Water Vapor ◽  
Microphysical Parameters ◽  
Stratospheric Clouds

Abstract. Previous work has shown that polar stratospheric clouds (PSCs) could have acted to substantially warm high latitude regions during past warm climates such as the Eocene (55 Ma). Using a simple model of stratospheric water vapor transport and polar stratospheric cloud (PSC) formation, we investigate the dependence of PSC optical depth on tropopause temperature, cloud microphysical parameters, stratospheric overturning, and tropospheric methane. We show that PSC radiative effects can help slow removal of water from the stratosphere via self-heating. However, we also show that the ability of PSCs to have a substantial impact on climate depends strongly on the PSC particle number density and the strength of the overturning circulation. Thus even a large source of stratospheric water vapor (e.g. from methane oxidation) will not result in substantial PSC radiative effects unless PSC ice crystal number density is high compared to most current observations, and stratospheric overturning (which modulates polar stratospheric temperatures) is low. These results are supported by analysis of a series of runs of the NCAR WACCM model with methane concentrations varying up to one thousand times present levels.

scholarly journals Comparison of warming trends over the last century around Antarctica from three coupled models

1998 ◽  
Vol 27 ◽  
pp. 565-570 ◽  
Author(s):  
William M. Connolley ◽  
Siobhan P. O'Farrell
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Atmospheric Model ◽  
Global Climate Models ◽  
Large Temperature ◽  
Coupled Models ◽  
Temperature Changes ◽  
Model Variability ◽  
The Antarctic

We compare observed temperature variations in Antarctica with climate-model runs over the last century. The models used are three coupled global climate models (GCMs) — the UKMO, the CSIRO and the MPI forced by the CO2 increases observed over the last century, and an atmospheric model experiment forced with observed sea-surface temperatures and sea-ice extents over the last century. Despite some regions of agreement, in general the GCM runs appear to be incompatible with each other and with the observations, although the short observational record and high natural variability make verification difficult. One of the best places for a more detailed study is the Antarctic Peninsula where the density of stations is higher and station records are longer than elsewhere in Antarctica. Observations show that this area has seen larger temperature rises than anywhere else in Antarctica. None of the three GCMs simulate such large temperature changes in the Peninsula region, in either climate-change runs radiatively forced by CO2 increases or control runs which assess the level of model variability.

scholarly journals Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

2019 ◽  
Vol 13 (11) ◽  
pp. 3023-3043
Author(s):  
Julien Beaumet ◽  
Michel Déqué ◽  
Gerhard Krinner ◽  
Cécile Agosta ◽  
Antoinette Alias
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Model ◽  
Sea Surface ◽  
Coupled Climate Model ◽  
Surface Climate ◽  
Late 21St Century ◽  
The Antarctic

Abstract. Owing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynamical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981–2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanalyses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs. For the simulation using SSCs from NorESM1-M, no significantly different climate change signals over Antarctica as a whole are found when bias-corrected SSCs are used. For the simulation driven by MIROC-ESM SSCs, a significant additional increase in precipitation and in winter temperatures for the Antarctic Ice Sheet is obtained when using bias-corrected SSCs. For the range of Antarctic warming found (+3 to +4 K), we confirm that snowfall increase will largely outweigh increases in melt and rainfall. Using the end members of sea ice trends from the CMIP5 RCP8.5 projections, the difference in warming obtained (∼ 1 K) is much smaller than the spread of the CMIP5 Antarctic warming projections. This confirms that the errors in representing the Southern Hemisphere atmospheric circulation in climate models are also determinant for the diversity of their projected late 21st century Antarctic climate change.

An evaluation of the surface climatology over the Totten region (Antarctica) using COSMO-CLM2

2020 ◽  
Author(s):  
Samuel Helsen ◽  
Sam Vanden Broucke ◽  
Alexandra Gossart ◽  
Niels Souverijns ◽  
Nicole van Lipzig
Keyword(s):  
High Resolution ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Ocean Model ◽  
Precipitation Pattern ◽  
Outlet Glacier ◽  
The Antarctic

<p>The Totten glacier is a highly dynamic outlet glacier, situated in E-Antarctica, that contains a potential sea level rise of about 3.5 meters. During recent years, this area has been influenced by sub-shelf intrusion of warm ocean currents, contributing to higher basal melt rates. Moreover, most of the ice over this area is grounded below sea level, which makes the ice shelf potentially vulnerable to the marine ice sheet instability mechanism. It is expected that, as a result of climate change, the latter mechanisms may contribute to significant ice losses in this region within the next decades, thereby contributing to future sea level rise. Up to now, most studies have been focusing on sub-shelf melt rates and the influence of the ocean, with much less attention for atmospheric processes (often ignored), which also play a key-role in determining the climatic conditions over this region. For example: surface melt is important because it contributes to hydrofracturing, a process that may lead to ice cliff instabilities. Also precipitation is an important atmospheric process, since it determines the input of mass to the ice sheet and contributes directly to the surface mass balance. In order to perform detailed studies on these processes, we need a well-evaluated climate model that represents all these processes well. Recently, the COSMO-CLM<sup>2</sup> (CCLM<sup>2</sup>) model was adapted to the climatological conditions over Antarctica. The model was evaluated by comparing a 30 year Antarctic-wide hindcast run (1986-2016) at 25 km resolution with meteorological observational products (Souverijns et al., 2019). It was shown that the model performance is comparable to other state-of-the-art regional climate models over the Antarctic region. We now applied the CCLM<sup>2</sup> model in a regional configuration over the Totten glacier area (E-Antarctica) at 5 km resolution and evaluated its performance over this region by comparing it to climatological observations from different stations. We show that the performance for temperature in the high resolution run is comparable to the performance of the Antarctic-wide run. Precipitation is, however, overestimated in the high-resolution run, especially over dome structures (Law-Dome). Therefore, we applied an orographic smoothening, which clearly improves the precipitation pattern with respect to observations. Wind speed is overestimated in some places, which is solved by increasing the surface roughness. This research frames in the context of the PARAMOUR project. Within PARAMOUR, CCLM<sup>2 </sup>is currently being coupled to an ocean model (NEMO) and an ice sheet model (f.ETISh/BISICLES) in order to understand decadal predictability over this region.</p>

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