Low-level cloud feedbacks in CMIP6 models and EUREC4A observations

2020 ◽  
Author(s):  
Anna Lea Albright ◽  
Sandrine Bony ◽  
Jean-Louis Dufresne ◽  
Jessica Vial
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Simple Model ◽  
Vertical Structure ◽  
Controlling Factors ◽  
Cloud Feedbacks ◽  
Low Level ◽  
Low Cloud ◽  
Profile Changes ◽  
Cloud Response

<p>How will low-level clouds respond to global warming? We approach this question by first investigating the spread of climate sensitivity and cloud feedbacks in CMIP6 models. We stratify the cloud response by circulation regime and focus in greater detail on the cloud response in tropical regimes of subsidence and weak ascent  (i.e., their vertical structure in the present-day and future climate, how cloud profile changes relate to changes in cloud-controlling factors). This CMIP6 model analysis dovetails with an observational analysis of low cloud responses from the EUREC4A field campaign. We seek to employ a simple model of low cloud behavior, constrained with observations from EUREC4A and longer time series from the Barbados Cloud Observatory, to better constrain the range of low cloud behavior spanned by CMIP6 models. </p>

scholarly journals Drivers of the Low-Cloud Response to Poleward Jet Shifts in the North Pacific in Observations and Models

2018 ◽  
Vol 31 (19) ◽  
pp. 7925-7947 ◽  
Author(s):  
Mark D. Zelinka ◽  
Kevin M. Grise ◽  
Stephen A. Klein ◽  
Chen Zhou ◽  
Anthony M. DeAngelis ◽  
...  
Keyword(s):  
Surface Temperature ◽  
North Pacific ◽  
Low Level ◽  
Cloud Coverage ◽  
The North ◽  
Low Clouds ◽  
Temperature Advection ◽  
Low Cloud ◽  
The North Pacific ◽  
Cloud Response

The long-standing expectation that poleward shifts of the midlatitude jet under global warming will lead to poleward shifts of clouds and a positive radiative feedback on the climate system has been shown to be misguided by several recent studies. On interannual time scales, free-tropospheric clouds are observed to shift along with the jet, but low clouds increase across a broad expanse of the North Pacific Ocean basin, resulting in negligible changes in total cloud fraction and top-of-atmosphere radiation. Here it is shown that this low-cloud response is consistent across eight independent satellite-derived cloud products. Using multiple linear regression, it is demonstrated that the spatial pattern and magnitude of the low-cloud-coverage response is primarily driven by anomalous surface temperature advection. In the eastern North Pacific, anomalous cold advection by anomalous northerly surface winds enhances sensible and latent heat fluxes from the ocean into the boundary layer, resulting in large increases in low-cloud coverage. Local increases in low-level stability make a smaller contribution to this low-cloud increase. Despite closely capturing the observed response of large-scale meteorology to jet shifts, global climate models largely fail to capture the observed response of clouds and radiation to interannual jet shifts because they systematically underestimate how sensitive low clouds are to surface temperature advection, and to a lesser extent, low-level stability. More realistic model simulations of cloud–radiation–jet interactions require that parameterizations more accurately capture the sensitivity of low clouds to surface temperature advection.

scholarly journals Observed Sensitivity of Low-Cloud Radiative Effects to Meteorological Perturbations over the Global Oceans

2020 ◽  
Vol 33 (18) ◽  
pp. 7717-7734
Author(s):  
Ryan C. Scott ◽  
Timothy A. Myers ◽  
Joel R. Norris ◽  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Relative Humidity ◽  
Surface Temperature ◽  
Sea Surface ◽  
Cloud Feedbacks ◽  
Low Level ◽  
Low Clouds ◽  
Low Cloud ◽  
Global Oceans

AbstractUnderstanding how marine low clouds and their radiative effects respond to changing meteorological conditions is crucial to constrain low-cloud feedbacks to greenhouse warming and internal climate variability. In this study, we use observations to quantify the low-cloud radiative response to meteorological perturbations over the global oceans to shed light on physical processes governing low-cloud and planetary radiation budget variability in different climate regimes. We assess the independent effect of perturbations in sea surface temperature, estimated inversion strength, horizontal surface temperature advection, 700-hPa relative humidity, 700-hPa vertical velocity, and near-surface wind speed. Stronger inversions and stronger cold advection greatly enhance low-level cloudiness and planetary albedo in eastern ocean stratocumulus and midlatitude regimes. Warming of the sea surface drives pronounced reductions of eastern ocean stratocumulus cloud amount and optical depth, and hence reflectivity, but has a weaker and more variable impact on low clouds in the tropics and middle latitudes. By reducing entrainment drying, higher free-tropospheric relative humidity enhances low-level cloudiness. At low latitudes, where cold advection destabilizes the boundary layer, stronger winds enhance low-level cloudiness; by contrast, wind speed variations have weak influence at midlatitudes where warm advection frequently stabilizes the marine boundary layer, thus inhibiting vertical mixing. These observational constraints provide a framework for understanding and evaluating marine low-cloud feedbacks and their simulation by models.

scholarly journals Observed Relationships between Cloud Vertical Structure and Convective Aggregation over Tropical Ocean

2017 ◽  
Vol 30 (6) ◽  
pp. 2187-2207 ◽  
Author(s):  
T. H. M. Stein ◽  
C. E. Holloway ◽  
I. Tobin ◽  
S. Bony
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Vertical Structure ◽  
Vertical Motion ◽  
Sea Surface ◽  
Precipitation Rate ◽  
Aggregation Index ◽  
Tropical Ocean ◽  
Low Level ◽  
Low Cloud

Abstract Using the satellite-infrared-based Simple Convective Aggregation Index (SCAI) to determine the degree of aggregation, 5 years of CloudSat–CALIPSO cloud profiles are composited at a spatial scale of 10 degrees to study the relationship between cloud vertical structure and aggregation. For a given large-scale vertical motion and domain-averaged precipitation rate, there is a large decrease in anvil cloud (and in cloudiness as a whole) and an increase in clear sky and low cloud as aggregation increases. The changes in thick anvil cloud are proportional to the changes in total areal cover of brightness temperatures below 240 K [cold cloud area (CCA)], which is negatively correlated with SCAI. Optically thin anvil cover decreases significantly when aggregation increases, even for a fixed CCA, supporting previous findings of a higher precipitation efficiency for aggregated convection. Cirrus, congestus, and midlevel clouds do not display a consistent relationship with the degree of aggregation. Lidar-observed low-level cloud cover (where the lidar is not attenuated) is presented herein as the best estimate of the true low-level cloud cover, and it is shown that it increases as aggregation increases. Qualitatively, the relationships between cloud distribution and SCAI do not change with sea surface temperature, while cirrus clouds are more abundant and low-level clouds less at higher sea surface temperatures. For the observed regimes, the vertical cloud profile varies more evidently with SCAI than with mean precipitation rate. These results confirm that convective scenes with similar vertical motion and rainfall can be associated with vastly different cloudiness (both high and low cloud) and humidity depending on the degree of convective aggregation.

scholarly journals Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

2017 ◽  
Vol 38 (6) ◽  
pp. 1307-1329 ◽  
Author(s):  
Stephen A. Klein ◽  
Alex Hall ◽  
Joel R. Norris ◽  
Robert Pincus
Keyword(s):  
Controlling Factors ◽  
Cloud Feedbacks ◽  
Low Cloud

scholarly journals Business Days Time Series Weekly Trend and Seasonality

2021 ◽  
Vol 5 (1) ◽  
pp. 26
Author(s):  
Karlis Gutans
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Exchange Rates ◽  
Temperature Data ◽  
Adjustment Method ◽  
Currency Exchange ◽  
Currency Exchange Rates ◽  
Time Series Decomposition ◽  
The World

The world changes at incredible speed. Global warming and enormous money printing are two examples, which do not affect every one of us equally. “Where and when to spend the vacation?”; “In what currency to store the money?” are just a few questions that might get asked more frequently. Knowledge gained from freely available temperature data and currency exchange rates can provide better advice. Classical time series decomposition discovers trend and seasonality patterns in data. I propose to visualize trend and seasonality data in one chart. Furthermore, I developed a calendar adjustment method to obtain weekly trend and seasonality data and display them in the chart.

A Standard Aggregative Model for the Jordanian Economy

1985 ◽  
Vol 17 (1) ◽  
pp. 67-88
Author(s):  
W. M. Mikhail
Keyword(s):  
Time Series ◽  
Simple Model ◽  
Structural Changes ◽  
Time Series Model ◽  
National Accounts ◽  
Macroeconomic Variables

The simple model presented in this paper is an econometric time-series model which was designed to use the available Jordanian national accounts statistics. It aims at explaining the structural changes in the Jordanian economy in the 1970s as well as projecting values of certain macroeconomic variables for the year 1985, that being the terminal year in the current 5-year plan.

How do polar clouds and precipitation affect global warming?

2021 ◽  
Author(s):  
Jennifer Kay
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Research Problem ◽  
Cloud Feedback ◽  
Polar Regions ◽  
Unsolved Research Problem ◽  
Cloud Feedbacks ◽  
Surface Warming ◽  
Polar Clouds ◽  
Radiative Feedbacks

<p>Understanding the influence of clouds and precipitation on global warming remains an important unsolved research problem. This talk presents an overview of this topic, with a focus on recent observations, theory, and modeling results for polar clouds. After a general introduction, experiments that disable cloud radiative feedbacks or “lock the clouds” within a state‐of‐the‐art,  well‐documented, and observationally vetted climate model will be presented. Through comparison of idealized greenhouse warming experiments with and without cloud locking, the sign and magnitude cloud feedbacks can be quantified. Global cloud feedbacks increase both global and Arctic warming by around 25%. In contrast, disabling Arctic cloud feedbacks has a negligible influence on both Arctic and global surface warming. Do observations and theory support a positive global cloud feedback and a weak Arctic cloud feedback?  How does precipitation affect polar cloud feedbacks? What are the implications especially for climate change in polar regions?  </p>

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