scholarly journals The Surface Longwave Cloud Radiative Effect derived from Space Lidar Observations

2021 ◽  
Author(s):  
Assia Arouf ◽  
Hélène Chepfer ◽  
Thibault Vaillant de Guélis ◽  
Marjolaine Chiriaco ◽  
Matthew D. Shupe ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Global Scale ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Time Period ◽  
Cloud Radiative Effect ◽  
Long Time ◽  
Thin Cloud ◽  
Global Surface ◽  
Lidar Observations

Abstract. Clouds warm the surface in the longwave (LW) and this warming effect can be quantified through the surface LW cloud radiative effect (CRE). The global surface LW CRE is estimated using long-term observations from space-based radiometers (2000–2021) but has some bias over continents and icy surfaces. It is also estimated globally using the combination of radar, lidar and space-based radiometer over the 5–year period ending in 2011. To develop a more reliable long time series of surface LW CRE over continental and icy surfaces, we propose new estimates of the global surface LW CRE from space-based lidar observations. We show from 1D atmospheric column radiative transfer calculations, that surface LW CRE linearly decreases with increasing cloud altitude. These computations allow us to establish simple relationships between surface LW CRE, and five cloud properties that are well observed by the CALIPSO space-based lidar: opaque cloud cover and altitude, and thin cloud cover, altitude, and emissivity. We use these relationships to retrieve the surface LW CRE at global scale over the 2008–2020 time period (27 Wm−2). We evaluate this new surface LW CRE product by comparing it to existing satellite-derived products globally on instantaneous collocated data at footprint scale and on global averages, as well as to ground-based observations at specific locations. Our estimate appears to be an improvement over others as it appropriately capture the surface LW CRE annual variability over bright polar surfaces and it provides a dataset of more than 13 years long.

The Surface Longwave Cloud Radiative Effect from Space Lidar Observations

2021 ◽  
Author(s):  
Assia Arouf
Keyword(s):  
Cloud Cover ◽  
Temporal Variations ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Long Time ◽  
The One ◽  
Natural Climate ◽  
The Impact ◽  
Lidar Observations

<p>Clouds exert important effects on Earth's surface energy balance through their effects on longwave (LW) and shortwave (SW) radiation. Indeed, clouds radiatively warm the surface in the LW domain by emitting LW radiation back to the ground. The surface LW cloud radiative effect (CRE) quantifies this warming effect. To study the impact of clouds on the interanual natural climate variability, we need to observe them on a long time scale over all kinds of surfaces. The CALIPSO space lidar provides these observations by sampling the atmosphere along its track over all kinds of surfaces for over than 14 years (2006-2020).</p><p>In this work, we propose new estimates of the surface LW CRE from space-based lidar observations only. Indeed, we show from 1D atmospheric column radiative transfer calculations, that surface LW CRE at sea level linearly decreases with the cloud altitude. Thus, these computations allow to establish simple relationships between the surface LW CRE, and five cloud properties observed by the CALIPSO space lidar: the opaque cloud cover and altitude, the thin cloud cover, altitude, and emissivity. Over the 2008–2011, CALIPSO-based retrieval (27.7 W m<sup>-2</sup>) is 1.2 W m<sup>-2</sup> larger than the one derived from combined space radar, lidar, and radiometer observations. Over the 2008–2018 period, the global mean CALIPSO-based retrieval (27.5 W m<sup>-2</sup>) is 0.1 W m<sup>-2</sup> larger than the one derived from CERES space radiometer. Our estimates show that globally, opaque clouds warm the surface by 23.3 W m<sup>-2</sup> and thin clouds contribute only by 4.2 W m<sup>-2</sup>. At high latitudes North and South over oceans, the largest surface LW opaque CRE occurs in fall (40.4 W m<sup>-2</sup>, 31.6 W m<sup>-2</sup>) due to the formation of additional opaque low clouds after sea ice melting over a warmer ocean.</p><p>To quantify the cloud property that drives the temporal variations of the surface LW CRE, the surface LW CRE needs to be related by simple relationships to a finite number of cloud properties such as cloud opacity, cloud altitude and cloud cover. This study allows a decomposition and attribution approach of the surface LW CRE variations and shows that they are driven by the variations occurring in the opaque cloud properties. Moreover, opaque cloud cover drives over than 73% of global surface LW CRE interannual variations.</p>

scholarly journals How Well Are Clouds Simulated over Greenland in Climate Models? Consequences for the Surface Cloud Radiative Effect over the Ice Sheet

2018 ◽  
Vol 31 (22) ◽  
pp. 9293-9312 ◽  
Author(s):  
A. Lacour ◽  
H. Chepfer ◽  
N. B. Miller ◽  
M. D. Shupe ◽  
V. Noel ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ground Level ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Primary Driver ◽  
Cloud Radiative Effects

Using lidar and radiative flux observations from space and ground, and a lidar simulator, we evaluate clouds simulated by climate models over the Greenland ice sheet, including predicted cloud cover, cloud fraction profile, cloud opacity, and surface cloud radiative effects. The representation of clouds over Greenland is a central concern for the models because clouds impact ice sheet surface melt. We find that over Greenland, most of the models have insufficient cloud cover during summer. In addition, all models create too few nonopaque, liquid-containing clouds optically thin enough to let direct solar radiation reach the surface (−1% to −3.5% at the ground level). Some models create too few opaque clouds. In most climate models, the cloud properties biases identified over all Greenland also apply at Summit, Greenland, proving the value of the ground observatory in model evaluation. At Summit, climate models underestimate cloud radiative effect (CRE) at the surface, especially in summer. The primary driver of the summer CRE biases compared to observations is the underestimation of the cloud cover in summer (−46% to −21%), which leads to an underestimated longwave radiative warming effect (CRELW = −35.7 to −13.6 W m−2 compared to the ground observations) and an underestimated shortwave cooling effect (CRESW = +1.5 to +10.5 W m−2 compared to the ground observations). Overall, the simulated clouds do not radiatively warm the surface as much as observed.

scholarly journals Trends in surface radiation and cloud radiative effect at four Swiss sites for the 1996–2015 period

2019 ◽  
Vol 19 (20) ◽  
pp. 13227-13241 ◽  
Author(s):  
Stephan Nyeki ◽  
Stefan Wacker ◽  
Christine Aebi ◽  
Julian Gröbner ◽  
Giovanni Martucci ◽  
...  
Keyword(s):  
Longwave Radiation ◽  
Ground Temperature ◽  
Surface Radiation ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Downward Longwave Radiation ◽  
Integrated Water Vapour

Abstract. The trends of meteorological parameters and surface downward shortwave radiation (DSR) and downward longwave radiation (DLR) were analysed at four stations (between 370 and 3580 m a.s.l.) in Switzerland for the 1996–2015 period. Ground temperature, specific humidity, and atmospheric integrated water vapour (IWV) trends were positive during all-sky and cloud-free conditions. All-sky DSR and DLR trends were in the ranges of 0.6–4.3 W m−2 decade−1 and 0.9–4.3 W m−2 decade−1, respectively, while corresponding cloud-free trends were −2.9–3.3 W m−2 decade−1 and 2.9–5.4 W m−2 decade−1. Most trends were significant at the 90 % and 95 % confidence levels. The cloud radiative effect (CRE) was determined using radiative-transfer calculations for cloud-free DSR and an empirical scheme for cloud-free DLR. The CRE decreased in magnitude by 0.9–3.1 W m−2 decade−1 (only one trend significant at 90 % confidence level), which implies a change in macrophysical and/or microphysical cloud properties. Between 10 % and 70 % of the increase in DLR is explained by factors other than ground temperature and IWV. A more detailed, long-term quantification of cloud changes is crucial and will be possible in the future, as cloud cameras have been measuring reliably at two of the four stations since 2013.

scholarly journals Link between opaque cloud properties and atmospheric dynamics in observations and simulations of current climate in the Tropics, and impact on future predictions

2021 ◽  
Author(s):  
Miguel Perpina ◽  
Vincent Noel ◽  
Helene Chepfer ◽  
Rodrigo Guzman ◽  
Artem Feofilov
Keyword(s):  
Vertical Distribution ◽  
Climate Models ◽  
Orthogonal Polarization ◽  
Radiative Effect ◽  
Climate Conditions ◽  
Cloud Properties ◽  
Current Climate ◽  
Cloud Radiative Effect ◽  
The Future ◽  
Tropical Clouds

<p><span>Climate models predict a weakening of the tropical atmospheric circulation, more specifically a slowdown of Hadley and Walker circulations. Many climate models predict that global warming will have a major impact on cloud properties, including their geographic and vertical distribution. Climate feedbacks from clouds, which amplify warming when positive, are today the main source of uncertainty in climate forecasts. Tropical clouds play a key role in the redistribution of solar energy and their evolution will likely affect climate. Therefore, it is crucial to better understand how tropical clouds will evolve in a changing climate. Among cloud properties, the vertical distribution is sensitive to climate change. Active sensors integrated into satellites, such as CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization), make it possible to obtain a detailed vertical distribution of clouds. CALIOP measurements and calibration are more stable over time and more precise than passive remote sensing satellite detectors. CALIOP observations can be simulated in the atmospheric conditions predicted by climate models using lidar simulators such as COSP (</span><span>CFMIP Observation Simulator Package). Moreover, </span><span>cloud properties directly drive the Cloud Radiative Effect (CRE). Understanding how models predict cloud vertical distribution will evolve in the future has implications for how models predict the Cloud Radiative Effect (CRE) at the Top of the Atmosphere (TOA) will evolve in the future. </span></p><p><span>The purpose of our study is to compare, firstly, based on satellite observations (GOCCP) and reanalyzes (ERA5), we will establish the relationship between atmospheric dynamic circulation, opaque cloud properties and TOA CRE. Then, we will compare this observed relationship with the one found in climate model simulations of current climate conditions (CESM1 and IPSL-CM6). Finally, we will identify how model biases in present climate conditions influence the cloud feedback spread between models in a warmer climate.</span></p>

scholarly journals Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations

2020 ◽  
Vol 59 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Kerstin Ebell ◽  
Tatiana Nomokonova ◽  
Marion Maturilli ◽  
Christoph Ritter
Keyword(s):  
Remote Sensing ◽  
The Arctic ◽  
Radiative Effect ◽  
Liquid Water Path ◽  
Ice Clouds ◽  
Surface Warming ◽  
Clear Sky ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
The Difference

AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.

Impacts of Ice Cloud Particle Size Uncertainty on Radiation, and Precipitation and Climate Sensitivity and the Significance of Future Satellite-Based Constraints

2020 ◽  
Author(s):  
Hui Su ◽  
Yuan Wang ◽  
Jonathan Jiang ◽  
Feng Xu ◽  
Yuk Yung
Keyword(s):  
Particle Size ◽  
Climate Sensitivity ◽  
Climate Models ◽  
Global Scale ◽  
Radiative Effect ◽  
Cloud Particle ◽  
Ice Cloud ◽  
Cloud Radiative Effect ◽  
Fall Speed ◽  
Radiation Scheme

&lt;p&gt;Ice cloud particle size is important to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (R&lt;sub&gt;ei&lt;/sub&gt;) observation on the global scale and the parameterization of R&lt;sub&gt;ei&lt;/sub&gt; in climate models is poorly constrained. We conduct a modeling study to assess the sensitivity of climate simulations to R&lt;sub&gt;ei&lt;/sub&gt;. Perturbations to R&lt;sub&gt;ei&lt;/sub&gt; are represented in ice fall speed parameterization and radiation scheme, respectively, in NCAR CESM1 model with a slab ocean configuration. We show that an increase in ice fall speed due to a larger R&lt;sub&gt;ei&lt;/sub&gt; results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. Similar longwave and shortwave cloud radiative effect changes occur when R&lt;sub&gt;ei&lt;/sub&gt; is perturbed in the radiation scheme. Perturbing falling snow particle size (R&lt;sub&gt;es&lt;/sub&gt;) results in much smaller changes in the climate responses. We further show that varying R&lt;sub&gt;ei&lt;/sub&gt; and R&lt;sub&gt;es&lt;/sub&gt; by 50% to 200% relative to the control experiment can cause climate sensitivity to differ by +12.3% to &amp;#8722;6.2%. A future mission under design with combined multi-frequency microwave radiometers and cloud radar can reduce the uncertainty ranges of R&lt;sub&gt;ei&lt;/sub&gt; and R&lt;sub&gt;es&lt;/sub&gt; from a factor of 2 to &amp;#177;25%, which would help reducing the climate sensitivity uncertainty pertaining to ice cloud particle size by approximately 60%.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

A Climatology of Clouds in Marine Cold Air Outbreaks in Both Hemispheres

2016 ◽  
Vol 29 (18) ◽  
pp. 6677-6692 ◽  
Author(s):  
Jennifer K. Fletcher ◽  
Shannon Mason ◽  
Christian Jakob
Keyword(s):  
Climate Models ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Radiative Effect ◽  
Cold Air ◽  
Cloud Properties ◽  
Cold Air Outbreak ◽  
Cloud Radiative Effect ◽  
Cold Air Outbreaks

Abstract A climatology of clouds within marine cold air outbreaks, primarily using long-term satellite observations, is presented. Cloud properties between cold air outbreaks in different regions in both hemispheres are compared. In all regions marine cold air outbreak clouds tend to be low level with high cloud fraction and low-to-moderate optical thickness. Stronger cold air outbreaks have clouds that are optically thicker, but not geometrically thicker, than those in weaker cold air outbreaks. There is some evidence that clouds deepen and break up over the course of a cold air outbreak event. The top-of-the-atmosphere longwave cloud radiative effect in cold air outbreaks is small because the clouds have low tops. However, their surface longwave cloud radiative effect is considerably larger. The rarity of cold air outbreaks in summer limits their shortwave cloud radiative effect. They do not contribute substantially to global shortwave cloud radiative effect and are, therefore, unlikely to be a major source of shortwave cloud radiative effect errors in climate models.

scholarly journals A Detailed Cloud Fraction Climatology of the Upper Indus Basin and Its Implications for Near-Surface Air Temperature*

2015 ◽  
Vol 28 (9) ◽  
pp. 3537-3556 ◽  
Author(s):  
N. Forsythe ◽  
A. J. Hardy ◽  
H. J. Fowler ◽  
S. Blenkinsop ◽  
C. G. Kilsby ◽  
...  
Keyword(s):  
Air Temperature ◽  
Cloud Cover ◽  
Large Fraction ◽  
Surface Air Temperature ◽  
Indus Basin ◽  
Radiative Effect ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Cloud Radiative Effect ◽  
Seasonal And Diurnal Variations

Abstract Clouds play a key role in hydroclimatological variability by modulating the surface energy balance and air temperature. This study utilizes MODIS cloud cover data, with corroboration from global meteorological reanalysis (ERA-Interim) cloud estimates, to describe a cloud climatology for the upper Indus River basin. It has specific focus on tributary catchments in the northwest of the region, which contribute a large fraction of basin annual runoff, including 65% of flow originating above Besham, Pakistan or 50 km3 yr−1 in absolute terms. In this region there is substantial cloud cover throughout the year, with spatial means of 50%–80% depending on the season. The annual cycles of catchment spatial mean daytime and nighttime cloud cover fraction are very similar. This regional diurnal homogeneity belies substantial spatial variability, particularly along seasonally varying vertical profiles (based on surface elevation). Correlations between local near-surface air temperature observations and MODIS cloud cover fraction confirm the strong linkages between local atmospheric conditions and near-surface climate variability. These correlations are interpreted in terms of seasonal and diurnal variations in apparent cloud radiative effect and its influence on near-surface air temperature in the region. The potential role of cloud radiative effect in recognized seasonally and diurnally asymmetrical temperature trends over recent decades is also assessed by relating these locally observed trends to ERA-Interim-derived trends in cloud cover fraction. Specifically, reduction in nighttime cloud cover fraction relative to daytime conditions over recent decades appears to provide a plausible physical mechanism for the observed nighttime cooling of surface air temperature in summer months.

scholarly journals Cirrus cloud radiative effect on surface-level shortwave and longwave irradiances at regional and global scale

2009 ◽  
Vol 9 (6) ◽  
pp. 26777-26832 ◽  
Author(s):  
J.-C. Dupont ◽  
M. Haeffelin ◽  
C. N. Long
Keyword(s):  
Regional Scale ◽  
Ground Level ◽  
Global Scale ◽  
Cirrus Cloud ◽  
Radiative Effect ◽  
Atmospheric Conditions ◽  
Emissive Power ◽  
Atmospheric Turbidity ◽  
Cloud Radiative Effect ◽  
Abstract Data

Abstract. Data collected at four ground-level sites are analyzed (1) to determine the surface cloud radiative effect (CRE) induced by cirrus clouds at regional scale for shortwave (CRESW) and longwave (CRELW) fluxes and (2) to derive the sensitivity of surface CRESW to the cloud optical thickness (COT) modulated by the solar zenith angle and the atmospheric turbidity (noted CRESW*) and the sensitivity of surface CRELW to the infrared emissive power of cirrus cloud modulated by the water vapor content (noted CRELW*). The average CRESW* is −120 W m−2 COT−1 but it ranges from −80 to −140 m−2 COT−1 depending on the solar illumination with a residual variability ranges from +40 and −40 W m−2 COT−1 from pristine to turbid conditions, respectively. The CRELW*, that corresponds to the infrared transmissivity of the atmosphere, ranges from 3% to 40% from dry to wet atmospheric conditions, respectively. The subvisible cirrus class (COT<0.03) over mid-latitude sites, that represents 20% of the population, induces a significant increase in surface LW irradiance at the 2–7 W m−2 level. The semi-transparent cirrus class (0.03<COT<0.3), that represents 45% of the population, will affect the surface SW irradiance by −12 to −25 W m−2. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and the Atmospheric Infrared Sounder (AIRS) are used here to estimate the surface radiative effect at global scale. Global CRE estimations show very significant zonal and seasonal variability of each component of the CRENET. CRENET is 0.4 W m−2 during winter/autumn for 15–75° N and 1 W m−2 for 45–75° S whereas it is near −3 W m−2 for 15° S–15° N. The summer period shows a cirrus cloud global cooling at all the latitudes except for 75–45° S with a quasi null effect and a peak at −3.6 W m−2 for 15° S–45° N. The global average cumulative CRE is −2.8, 1.7 and −1.1 W m−2 for CRESW, CRELW, and CRENET, respectively.

Optically thin clouds in the winter trades

2021 ◽  
Author(s):  
Theresa Mieslinger ◽  
Tobias Kölling ◽  
Manfred Brath ◽  
Bjorn Stevens ◽  
Stefan A. Buehler
Keyword(s):  
Trade Wind ◽  
Radiative Effect ◽  
Cloud Optical Depth ◽  
Feedback Analysis ◽  
Clear Sky ◽  
Cloud Radiative Effect ◽  
Thin Cloud ◽  
High Bias ◽  
High Resolution Satellite Imagery ◽  
Ocean Observations

&lt;p&gt;We investigate the abundance and radiative effect of small and optically thin clouds in trade wind cumulus cloud fields from high-resolution satellite imagery. Using radiative transfer calculations to simulate clear-sky observations, we can identify optically thin cloud areas in ASTER images, a signal that is undetected by the satellite products that are commonly used for cloud radiative effect and cloud feedback analysis. Results from the analysis within the EUREC4A campaign suggest that the area covered by optically thin clouds is approximately as big as the area covered by clouds that are detected by common cloud masking algorithms. Compared to clear-sky ocean observations, the enhanced radiance from optically thin clouds leads to a high-bias in clear-sky estimates and hence a low-bias in the estimated radiative effect of trade wind cumuli.&amp;#160;Next to the radiative effect, we discuss further implications that a broad cloud optical depth distribution might have on modelling results of a perturbed climate.&lt;/p&gt;

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