Climatic Properties of Tropical Precipitating Convection under Varying Environmental Conditions

A clustering algorithm is used to define the radiative, hydrological, and microphysical properties of precipitating convective events in the equatorial region observed by the Tropical Rainfall Measuring Mission (TRMM) satellite. Storms are separated by surface type, size, and updraft strength, the latter defined by the presence or absence of lightning. SST data and global reanalysis products are used to explore sensitivity to changes in environmental conditions. Small storms are much more numerous than mesoscale convective systems, and account for fairly little of the total rainfall but contribute significantly to reflection of sunlight. Lightning storms rain more heavily, have greater cloud area, extend to higher altitude, and have higher albedos than storms without lightning. Lightning is favored by a steep lower-troposphere lapse rate and moist mid-level humidity. Storms occur more often at ≥28°C and with strong upward 500-mb mean vertical velocity. In general, storms over warmer ocean waters rain more heavily, are larger, and have higher cloud tops, but they do not have noticeably higher albedos than storms over cooler ocean waters. Mesoscale convective system properties are more sensitive to SST. Rain rates and cloud-top heights increase statistically significantly with mean upward motion. Rain rates increase with albedo and cloud-top height over ocean, but over land there are also storms with cloud-top temperatures >-35°C whose rain rates decrease with increasing albedo. Both the fraction of available moisture that rains out and the fraction that detrains as ice increase with SST, the former faster than the latter. TRMM ice water paths derived from cloud-resolving models but constrained by observed microwave radiances are only weakly correlated with observed albedo. The results are inconsistent with the ‘‘adaptive iris’’ hypothesis and suggest feedbacks due primarily to increasing convective cloud cover with warming, but more weakly than predicted by the ‘‘thermostat’’ hypothesis

CLIMATE LECTURE 5: The Role of Clouds in Climate

David Rind has played a central role in the science of the modeling of climate change. He was the scientific driving force behind the development and evaluation of the first Goddard Institute for Space Studies (GISS) global climate model (GCM), Model II. Model II was one of the three original GCMs whose projections of climate change in response to a doubling of CO2 concentration were the basis for the influential Charney Report that produced the first assessment of global climate sensitivity. David used Model II to pioneer the scientific field of climate dynamics, performing a broad range of investigations of processes controlling individual elements of the general circulation and how they changed over a wide range of past and potential future climates. The defining characteristic of Davids papers is his unique talent for tracking down the myriad links and causal chains among different parts of the nonlinear climate system. Rather than viewing climate using a simple forcing-and-response paradigm, David showed that the global energy, water, and even momentum cycles are coupled via the general circulation and its transports

Constraining the Models' Response of Tropical Clouds to SST Forcings Using CALIPSO Observations

Here we present preliminary results from the analysis of the low cloud cover (LCC) and cloud radiative effect (CRE) interannual changes in response to sea surface temperature (SST) forcings in two GISS climate models, and 12 other climate models. We further classify them as a function of their ability to reproduce the vertical structure of the cloud response to SST change against 10 years of CALIPSO observations: the constrained models, which match the observation constraint, and the unconstrained models. The constrained models replicate the observed interannual LCC change particularly well (LCC(sub con)=-3.49 1.01 %/K vs. LCC(sub obs)=-3.59 0.28 %/K) as opposed to the unconstrained models, which largely underestimate it (LCC(sub unc) = -1.32 1.28 %/K). As a result, the amount of short-wave warming simulated by the constrained models (CRE(sub con)=2.60 1.13 W/m2/K) is in better agreement with the observations (CRE(sub obs)=3.05 0.28 W/m2/K) than the unconstrained models (CRE(sub con)=0.87 2.63 W/m2/K). Depending on the type of low cloud, the observed relationship between cloud/radiation and surface temperature varies. Over the stratocumulus regions, increasing SSTs generate higher cloud top height along with a large decrease of the cloud fraction below as opposed to a slight decrease of the cloud fraction at each level over the trade cumulus regions. Our results suggest that the models must generate sustainable stratocumulus decks and moist processes in the planetary boundary layer to reproduce these observed features. Future work will focus on defining a method to objectively discriminate these cloud types that can be applied consistently in both the observations and the models

The Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSatCALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and ScCu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness as used in passive-sensor observations is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing ScCu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019)

Chapter 3: Evaluating the impacts of carbonaceous aerosols on clouds and climate

Any attempt to reconcile observed surface temperature changes within the last 150 years to changes simulated by climate models that include various atmospheric forcings is sensitive to the changes attributed to aerosols and aerosol-cloud-climate interactions, which are the main contributors that may well balance the positive forcings associated with greenhouse gases, absorbing aerosols, ozone related changes, etc. These aerosol effects on climate, from various modeling studies discussed in Menon (2004), range from +0.8 to -2.4 W m{sup -2}, with an implied value of -1.0 W m{sup -2} (range from -0.5 to -4.5 W m{sup -2}) for the aerosol indirect effects. Quantifying the contribution of aerosols and aerosol-cloud interactions remain complicated for several reasons some of which are related to aerosol distributions and some to the processes used to represent their effects on clouds. Aerosol effects on low lying marine stratocumulus clouds that cover much of the Earth's surface (about 70%) have been the focus of most of prior aerosol-cloud interaction effect simulations. Since cumulus clouds (shallow and deep convective) are short lived and cover about 15 to 20% of the Earth's surface, they are not usually considered as radiatively important. However, the large amount of latent heat released from convective towers, and corresponding changes in precipitation, especially in biomass regions due to convective heating effects (Graf et al. 2004), suggest that these cloud systems and aerosol effects on them, must be examined more closely. The radiative heating effects for mature deep convective systems can account for 10-30% of maximum latent heating effects and thus cannot be ignored (Jensen and Del Genio 2003). The first study that isolated the sensitivity of cumulus clouds to aerosols was from Nober et al. (2003) who found a reduction in precipitation in biomass burning regions and shifts in circulation patterns. Aerosol effects on convection have been included in other models as well (cf. Jacobson, 2002) but the relative impacts on convective and stratiform processes were not separated. Other changes to atmospheric stability and thermodynamical quantities due to aerosol absorption are also known to be important in modifying cloud macro/micro properties. Linkages between convection and boreal biomass burning can also impact the upper troposphere and lower stratosphere, radiation and cloud microphysical properties via transport of tropospheric aerosols to the lower stratosphere during extreme convection (Fromm and Servranckx 2003). Relevant questions regarding the impact of biomass aerosols on convective cloud properties include the effects of vertical transport of aerosols, spatial and temporal distribution of rainfall, vertical shift in latent heat release, phase shift of precipitation, circulation and their impacts on radiation. Over land surfaces, a decrease in surface shortwave radiation ({approx} 3-6 W m{sup -2} per decade) has been observed between 1960 to 1990, whereas, increases of 0.4 K in land temperature during the same period that occurred have resulted in speculations that evaporation and precipitation should also have decreased (Wild et al. 2004). However, precipitation records for the same period over land do not indicate any significant trend (Beck et al. 2005). The changes in precipitation are thought to be related to increased moisture advection from the oceans (Wild et al. 2004), which may well have some contributions from aerosol-radiation-convection coupling that could modify circulation patterns and hence moisture advection in specific regions. Other important aspects of aerosol effects, besides the direct, semi-direct, microphysical and thermodynamical impacts include alteration of surface albedos, especially snow and ice covered surfaces, due to absorbing aerosols. These effects are uncertain (Jacobson, 2004) but may produce as much as 0.3 W m{sup -2} forcing in the Northern hemisphere that could contribute to melting of ice and permafrost and change in the length of the season (e.g. early arrival of Spring) (Hansen and Nazarenko, 2004). Besides the impacts of aerosols on the surface albedos in the polar regions, and the thermodynamical impacts of Arctic haze (composed of water soluble sulfates, nitrates, organic and black carbon (BC)), the dynamical response to Arctic haze (through the radiation-circulation feedbacks that cause changes in pressure patterns) is thought to have the potential to modify the mode and strength of large-scale teleconnection patterns such as the Barrents Sea Oscillation that could affect other climate regimes (mainly Europe) (Rinke et al. 2004). Additionally, via the Asian monsoon, wind patterns over the eastern Mediterranean and lower stratospheric pollution at higher latitudes (Lelieveld et al. 2002) are thought to be linked to the pollutants found in Asia, indicating the distant climate impacts of aerosols