scholarly journals Comparison between Satellite Water Vapour Observations and Atmospheric Models’ Predictions of the Upper Tropospheric Thermal Radiation

2011 ◽  
Vol 2011 ◽  
pp. 1-15
Author(s):  
J. R. Dim ◽  
T. Y. Nakajima ◽  
T. Takamura ◽  
N. Kikuchi
Keyword(s):  
Water Vapour ◽  
Lower Troposphere ◽  
Satellite Observations ◽  
Department Of Energy ◽  
Atmospheric Models ◽  
Effective Emissivity ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Low Clouds ◽  
The Impact

Atmospheric profiles (temperature, pressure, and humidity) are commonly used parameters for aerosols and cloud properties retrievals. In preparation of the launch of the Global Change Observation Mission-Climate/Second-Generation GLobal Imager (GCOM-C/SGLI) satellite, an evaluation study on the sensitivity of atmospheric models to variations of atmospheric conditions is conducted. In this evaluation, clear sky and above low clouds water vapour radiances of the upper troposphere obtained from satellite observations and those simulated by atmospheric models are compared. The models studied are the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) and the National Center for Environmental Protection/Department Of Energy (NCEP/DOE). The satellite observations are from the Terra/Moderate Resolution Imaging Spectroradiometer (Terra/MODIS) satellite. The simulations performed are obtained through a forward radiative transfer calculation procedure. The resulting radiances are transformed into the upper tropospheric brightness temperature (UTBT) and relative humidity (UTRH). The discrepancies between the simulated data and the observations are analyzed. These analyses show that both the NICAM and the NCEP/DOE simulated UTBT and UTRH have comparable distribution patterns. However the simulations’ differences with the observations are generally lower with the NCEP/DOE than with the NICAM. The NCEP/DOE model outputs very often overestimate the UTBT and therefore present a drier upper troposphere. The impact of the lower troposphere instability (dry convection) on the upper tropospheric moisture and the consequences on the models’ results are evaluated through a thunderstorm and moisture predictor (the K-stability index). The results obtained show a positive relation between the instability and the root mean square error (RMSE: observation versus models). The study of the impact of convective clouds shows that the area covered by these clouds increases with the humidity of the upper troposphere in clear sky and above low clouds, and at the same time, the error between the observations and the models also increases. The impact of the above low clouds heat distribution on the models is studied through the relation between the low clouds cover and their effective emissivity. The models’ error appears to be high at midrange effective emissivity clouds.

scholarly journals The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

2011 ◽  
Vol 11 (3) ◽  
pp. 9705-9742
Author(s):  
A. M. Aghedo ◽  
K. W. Bowman ◽  
D. T. Shindell ◽  
G. Faluvegi
Keyword(s):  
Climate Change ◽  
Boundary Layer ◽  
Carbon Monoxide ◽  
Water Vapour ◽  
Climate Models ◽  
Atmospheric Temperature ◽  
Satellite Observations ◽  
Vertical Resolution ◽  
Upper Troposphere ◽  
The Impact

Abstract. Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC) assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI) and the observations from the Tropospheric Emission Spectrometer (TES) satellite from January 2005 to December 2008. The results show that sampling and monthly averaging of the observation operators produce biases of less than ±3% for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling biases were also within the insignificant range of ±3% (that is ±0.14 g kg−1) in both models. Sampling led to a temperature bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to −1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper troposphere, respectively. Up to 8% bias was calculated in the upper troposphere water vapour due to monthly-mean operators, which may impact the detection of water vapour feedback in response to global warming. Our results reveal the importance of using the averaging kernel and the a priori profiles to account for the limited vertical resolution of a nadir observation during model application. Neglecting the observation operators resulted in large biases, which are more than 60% for ozone, ±30% for carbon monoxide, and range between −1.5 K and 5 K for atmospheric temperature, and between −60% and 100% for water vapour.

scholarly journals The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

2011 ◽  
Vol 11 (13) ◽  
pp. 6493-6514 ◽  
Author(s):  
A. M. Aghedo ◽  
K. W. Bowman ◽  
D. T. Shindell ◽  
G. Faluvegi
Keyword(s):  
Climate Change ◽  
Boundary Layer ◽  
Carbon Monoxide ◽  
Water Vapour ◽  
Climate Models ◽  
Atmospheric Temperature ◽  
Satellite Observations ◽  
Vertical Resolution ◽  
Upper Troposphere ◽  
The Impact

Abstract. Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC) assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI) and the observations from the Tropospheric Emission Spectrometer (TES) instrument on board the NASA-Aura satellite from January 2005 to December 2008. The results show that sampling and monthly averaging of the observation operators produce zonal-mean biases of less than ±3 % for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling zonal-mean biases were also within the insignificant range of ±3 % (that is ±0.14 g kg−1) in both models. Sampling led to a temperature zonal-mean bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to −1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper troposphere, respectively. Up to 8 % bias was calculated in the upper troposphere water vapour due to monthly-mean operators, which may impact the detection of water vapour feedback in response to global warming. Our results reveal the importance of using the averaging kernel and the a priori profiles to account for the limited vertical resolution and clouds of a nadir observation during model application. Neglecting the observation operators resulted in large biases, which are more than 60 % for ozone, ±30 % for carbon monoxide, and range between −1.5 K and 5 K for atmospheric temperature, and between −60 % and 100 % for water vapour.

scholarly journals Representation of tropical deep convection in atmospheric models – Part 1: Meteorology and comparison with satellite observations

2011 ◽  
Vol 11 (6) ◽  
pp. 2765-2786 ◽  
Author(s):  
M. R. Russo ◽  
V. Marécal ◽  
C. R. Hoyle ◽  
J. Arteta ◽  
C. Chemel ◽  
...  
Keyword(s):  
Water Vapour ◽  
Seasonal Cycle ◽  
Lower Stratosphere ◽  
Weather Prediction ◽  
Tropical Convection ◽  
Satellite Observations ◽  
Radiative Heating ◽  
Atmospheric Models ◽  
Upper Troposphere ◽  
The Tropics

Abstract. Fast convective transport in the tropics can efficiently redistribute water vapour and pollutants up to the upper troposphere. In this study we compare tropical convection characteristics for the year 2005 in a range of atmospheric models, including numerical weather prediction (NWP) models, chemistry transport models (CTMs), and chemistry-climate models (CCMs). The model runs have been performed within the framework of the SCOUT-O3 (Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere) project. The characteristics of tropical convection, such as seasonal cycle, land/sea contrast and vertical extent, are analysed using satellite observations as a benchmark for model simulations. The observational datasets used in this work comprise precipitation rates, outgoing longwave radiation, cloud-top pressure, and water vapour from a number of independent sources, including ERA-Interim analyses. Most models are generally able to reproduce the seasonal cycle and strength of precipitation for continental regions but show larger discrepancies with observations for the Maritime Continent region. The frequency distribution of high clouds from models and observations is calculated using highly temporally-resolved (up to 3-hourly) cloud top data. The percentage of clouds above 15 km varies significantly between the models. Vertical profiles of water vapour in the upper troposphere-lower stratosphere (UTLS) show large differences between the models which can only be partly attributed to temperature differences. If a convective plume reaches above the level of zero net radiative heating, which is estimated to be ~15 km in the tropics, the air detrained from it can be transported upwards by radiative heating into the lower stratosphere. In this context, we discuss the role of tropical convection as a precursor for the transport of short-lived species into the lower stratosphere.

scholarly journals Effect of tropical cyclones on the stratosphere–troposphere exchange observed using satellite observations over the north Indian Ocean

2016 ◽  
Vol 16 (13) ◽  
pp. 8581-8591 ◽  
Author(s):  
M. Venkat Ratnam ◽  
S. Ravindra Babu ◽  
S. S. Das ◽  
G. Basha ◽  
B. V. Krishnamurthy ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Water Vapour ◽  
Tropical Cyclones ◽  
Lower Stratosphere ◽  
North Indian Ocean ◽  
Satellite Observations ◽  
Upper Troposphere ◽  
The North ◽  
The Impact ◽  
Cyclonic Storms

Abstract. Tropical cyclones play an important role in modifying the tropopause structure and dynamics as well as stratosphere–troposphere exchange (STE) processes in the upper troposphere and lower stratosphere (UTLS) region. In the present study, the impact of cyclones that occurred over the north Indian Ocean during 2007–2013 on the STE processes is quantified using satellite observations. Tropopause characteristics during cyclones are obtained from the Global Positioning System (GPS) radio occultation (RO) measurements, and ozone and water vapour concentrations in the UTLS region are obtained from Aura Microwave Limb Sounder (MLS) satellite observations. The effect of cyclones on the tropopause parameters is observed to be more prominent within 500 km of the centre of the tropical cyclone. In our earlier study, we observed a decrease (increase) in the tropopause altitude (temperature) up to 0.6 km (3 K), and the convective outflow level increased up to 2 km. This change leads to a total increase in the tropical tropopause layer (TTL) thickness of 3 km within 500 km of the centre of cyclone. Interestingly, an enhancement in the ozone mixing ratio in the upper troposphere is clearly noticed within 500 km from the cyclone centre, whereas the enhancement in the water vapour in the lower stratosphere is more significant on the south-east side, extending from 500 to 1000 km away from the cyclone centre. The cross-tropopause mass flux for different intensities of cyclones is estimated and it is found that the mean flux from the stratosphere to the troposphere for cyclonic storms is 0.05 ± 0.29 × 10−3 kg m−2, and for very severe cyclonic storms it is 0.5 ± 1.07 × 10−3 kg m−2. More downward flux is noticed on the north-west and south-west side of the cyclone centre. These results indicate that the cyclones have significant impact in effecting the tropopause structure, ozone and water vapour budget, and consequentially the STE in the UTLS region.

scholarly journals Effect of tropical cyclones on the Stratosphere-Troposphere Exchange observed using satellite observations over north Indian Ocean

2016 ◽  
Author(s):  
M. Venkat Ratnam ◽  
S. Ravindra Babu ◽  
S. S. Das ◽  
Ghouse Basha ◽  
B. V. Krishnamurthy ◽  
...  
Keyword(s):  
Water Vapor ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
Lower Stratosphere ◽  
North Indian Ocean ◽  
Satellite Observations ◽  
Upper Troposphere ◽  
North West ◽  
The North ◽  
The Impact

Abstract. Tropical cyclones play an important role in modifying the tropopause structure and dynamics as well as stratosphere-troposphere exchange (STE) process in the Upper Troposphere and Lower Stratosphere (UTLS) region. In the present study, the impact of cyclones that occurred over the North Indian Ocean during 2007–2013 on the STE process is quantified using satellite observations. Tropopause characteristics during cyclones are obtained from the Global Positioning System (GPS) Radio Occultation (RO) measurements and ozone and water vapor concentrations in UTLS region are obtained from Aura-Microwave Limb Sounder (MLS) satellite observations. The effect of cyclones on the tropopause parameters is observed to be more prominent within 500 km from the centre of cyclone. In our earlier study we have observed decrease (increase) in the tropopause altitude (temperature) up to 0.6 km (3 K) and the convective outflow level increased up to 2 km. This change leads to a total increase in the tropical tropopause layer (TTL) thickness of 3 km within the 500 km from the centre of cyclone. Interestingly, an enhancement in the ozone mixing ratio in the upper troposphere is clearly noticed within 500 km from cyclone centre whereas the enhancement in the water vapor in the lower stratosphere is more significant on south-east side extending from 500–1000 km away from the cyclone centre. We estimated the cross-tropopause mass flux for different intensities of cyclones and found that the mean flux from stratosphere to troposphere for cyclonic stroms is 0.05 ± 0.29 × 10−3 kg m−2 and for very severe cyclonic stroms it is 0.5 ± 1.07 × 10−3 kg m−2. More downward flux is noticed in the north-west and south-west side of the cyclone centre. These results indicate that the cyclones have significant impact in effecting the tropopause structure, ozone and water vapour budget and consequentially the STE in the UTLS region.

scholarly journals The impact of organic pollutants from Indonesian peatland fires on the tropospheric and lower stratospheric composition

2021 ◽  
Vol 21 (14) ◽  
pp. 11257-11288
Author(s):  
Simon Rosanka ◽  
Bruno Franco ◽  
Lieven Clarisse ◽  
Pierre-François Coheur ◽  
Andrea Pozzer ◽  
...  
Keyword(s):  
Biomass Burning ◽  
El Niño ◽  
Lower Stratosphere ◽  
El Nino ◽  
Lower Troposphere ◽  
Atmospheric Composition ◽  
Voc Emissions ◽  
Upper Troposphere ◽  
Upward Transport ◽  
The Impact

Abstract. The particularly strong dry season in Indonesia in 2015, caused by an exceptionally strong El Niño, led to severe peatland fires resulting in high volatile organic compound (VOC) biomass burning emissions. At the same time, the developing Asian monsoon anticyclone (ASMA) and the general upward transport in the Intertropical Convergence Zone (ITCZ) efficiently transported the resulting primary and secondary pollutants to the upper troposphere and lower stratosphere (UTLS). In this study, we assess the importance of these VOC emissions for the composition of the lower troposphere and the UTLS and investigate the effect of in-cloud oxygenated VOC (OVOC) oxidation during such a strong pollution event. This is achieved by performing multiple chemistry simulations using the global atmospheric model ECHAM/MESSy (EMAC). By comparing modelled columns of the biomass burning marker hydrogen cyanide (HCN) and carbon monoxide (CO) to spaceborne measurements from the Infrared Atmospheric Sounding Interferometer (IASI), we find that EMAC properly captures the exceptional strength of the Indonesian fires. In the lower troposphere, the increase in VOC levels is higher in Indonesia compared to other biomass burning regions. This has a direct impact on the oxidation capacity, resulting in the largest regional reduction in the hydroxyl radical (OH) and nitrogen oxides (NOx). While an increase in ozone (O3) is predicted close to the peatland fires, simulated O3 decreases in eastern Indonesia due to particularly high phenol concentrations. In the ASMA and the ITCZ, the upward transport leads to elevated VOC concentrations in the lower stratosphere, which results in the reduction of OH and NOx and the increase in the hydroperoxyl radical (HO2). In addition, the degradation of VOC emissions from the Indonesian fires becomes a major source of lower stratospheric nitrate radicals (NO3), which increase by up to 20 %. Enhanced phenol levels in the upper troposphere result in a 20 % increase in the contribution of phenoxy radicals to the chemical destruction of O3, which is predicted to be as large as 40 % of the total chemical O3 loss in the UTLS. In the months following the fires, this loss propagates into the lower stratosphere and potentially contributes to the variability of lower stratospheric O3 observed by satellite retrievals. The Indonesian peatland fires regularly occur during El Niño years, and the largest perturbations of radical concentrations in the lower stratosphere are predicted for particularly strong El Niño years. By activating the detailed in-cloud OVOC oxidation scheme Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC), we find that the predicted changes are dampened. Global models that neglect in-cloud OVOC oxidation tend to overestimate the impact of such extreme pollution events on the atmospheric composition.

scholarly journals Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

2015 ◽  
Vol 8 (10) ◽  
pp. 10755-10792
Author(s):  
A. M. Dzambo ◽  
D. D. Turner ◽  
E. J. Mlawer
Keyword(s):  
Water Vapor ◽  
Statistical Significance ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Microwave Radiometers ◽  
The Impact ◽  
Dry Bias ◽  
Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km MSL), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, mid-latitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RH are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

scholarly journals Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

2016 ◽  
Vol 9 (4) ◽  
pp. 1613-1626 ◽  
Author(s):  
Andrew M. Dzambo ◽  
David D. Turner ◽  
Eli J. Mlawer
Keyword(s):  
Water Vapor ◽  
Statistical Significance ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Microwave Radiometers ◽  
The Impact ◽  
Dry Bias ◽  
Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

scholarly journals Retrieval of MetOp-A/IASI CO profiles and validation with MOZAIC data

2012 ◽  
Vol 5 (3) ◽  
pp. 3271-3301
Author(s):  
E. De Wachter ◽  
B. Barret ◽  
E. Le Flochmoën ◽  
E. Pavelin ◽  
M. Matricardi ◽  
...  
Keyword(s):  
Lower Troposphere ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Upper Troposphere ◽  
Retrieval Algorithms ◽  
Good Reproduction ◽  
The Impact ◽  
Good Agreement ◽  
Limited Sensitivity

Abstract. The IASI nadir looking thermal infrared sounder onboard MetOp-A enables the monitoring of atmospheric constituents on a global scale. This paper presents a quality assessment of IASI CO profiles retrieved by the two different retrieval algorithms SOFRID and FORLI, by an intercomparison with airborne in-situ CO profiles from the MOZAIC program. A statistical analysis shows a very good agreement between the two retrieval algorithms and smoothed MOZAIC data for the lower troposphere (surface-480 hPa) with correlation coefficients r ~ 0.8, and a good agreement in the upper troposphere (480–225 hPa) with r ~ 0.7. Closer investigation of the temporal variation of the CO profiles at the airports of Frankfurt and Windhoek demonstrates that on the overall a very good agreement is found between the IASI products and smoothed MOZAIC data in terms of seasonal variability. At Frankfurt SOFRID (resp. FORLI) is positively biased by 10.5% (resp. 13.0%) compared to smoothed MOZAIC in the upper (resp. lower) troposphere, and the limited sensitivity of the IASI instrument to the boundary layer when thermal contrast is low is identified. At Windhoek, we find a good reproduction of the impact of the vegetation fires in Southern Africa from July to November by both SOFRID and FORLI, with an overestimation of the CO background values (resp. fire maxima) by SOFRID (resp. FORLI) by 12.8% (resp. ~10%). Profile comparisons at Frankfurt and Windhoek identify a reduced performance of the nighttime retrievals of both products compared to daytime retrievals.

scholarly journals Summertime low clouds mediate the impact of the large-scale circulation on Arctic sea ice

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Yiyi Huang ◽  
Qinghua Ding ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Ian Baxter
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Models ◽  
Lower Troposphere ◽  
Arctic Sea Ice ◽  
Albedo Feedback ◽  
Ice Melt ◽  
Low Clouds ◽  
Arctic Sea ◽  
The Impact

AbstractThe rapid Arctic sea ice retreat in the early 21st century is believed to be driven by several dynamic and thermodynamic feedbacks, such as ice-albedo feedback and water vapor feedback. However, the role of clouds in these feedbacks remains unclear since the causality between clouds and these processes is complex. Here, we use NASA CERES satellite products and NCAR CESM model simulations to suggest that summertime low clouds have played an important role in driving sea ice melt by amplifying the adiabatic warming induced by a stronger anticyclonic circulation aloft. The upper-level high pressure regulates low clouds through stronger downward motion and increasing lower troposphere relative humidity. The increased low clouds favor more sea ice melt via emitting stronger longwave radiation. Then decreased surface albedo triggers a positive ice-albedo feedback, which further enhances sea ice melt. Considering the importance of summertime low clouds, accurate simulation of this process is a prerequisite for climate models to produce reliable future projections of Arctic sea ice.

Sign in / Sign up

Export Citation Format

Share Document