Sea surface warming patterns drive hydrological sensitivity uncertainties

The increase in global-mean precipitation with global-mean temperature (hydrological sensitivity; η) is constrained by the atmospheric energy budget, but its magnitude remains uncertain. Here we apply warming patch experiments to a climate model to demonstrate that the spatial pattern of sea surface warming can explain a wide range of η. Warming in tropical strongly ascending regions produces η values even larger than suggested by the Clausius–Clapeyron relationship (7% K−1), as the warming and moisture increases can propagate vertically and be transported globally through atmospheric dynamics. Differences in warming patterns are as important as different treatments of atmospheric physics in determining the spread of η in climate models. By accounting for the pattern effect, the global-mean precipitation over the past decades can be well reconstructed in terms of both magnitude and variability, indicating the vital role of the pattern effect in estimating future intensification of the hydrological cycle

An investigation of microphysics and subgrid-scale variability in warm-rain clouds using the A-Train observations and a multiscale modeling framework

A common problem in climate models is that they are likely to produce rain at a faster rate than is observed and therefore produce too much light rain (e.g., drizzle). Interestingly, the Pacific Northwest National Laboratory (PNNL) multiscale modeling framework (MMF), whose warm-rain formation process is more realistic than other global models, has the opposite problem: the rain formation process in PNNL-MMF is less efficient than the real world. To better understand the microphysical processes in warm cloud, this study documents the model biases in PNNL-MMF and evaluates warm cloud properties, subgrid variability, and microphysics, using A-Train satellite observations to identify sources of model biases in PNNL-MMF. Like other models PNNL-MMF underpredicts the warm cloud fraction with compensating large optical depths. Associated with these compensating errors in cloudiness are compensating errors in the precipitation process. For a given liquid water path, clouds in the PNNL-MMF are less likely to produce rain than are real-world clouds. However, when the model does produce rain it is able to produce stronger precipitation than reality. As a result PNNL-MMF produces about the correct mean rain rate with an incorrect distribution of rates. The subgrid variability in PNNL-MMF is also tested, and results are fairly consistent with observations, suggesting that the possible sources of model biases are likely to be due to errors in its microphysics or dynamics rather than errors in the subgrid-scale variability produced by the embedded cloud resolving model

Strong Precipitation Suppression by Aerosols in Marine Low Clouds

The adjustment of cloud amount to aerosol effects occurs to a large extent in response to the aerosol effect on precipitation. Here the marine boundary layer clouds were studied by analyzing the dependence of rain intensity measured by Global Precipitation Measurement on cloud properties. We showed that detectable rain initiates when the drop effective radius at the cloud top (re) exceeds 14 μm, and precipitation is strongly suppressed with increasing cloud drop concentration (Nd), which contributes to the strong dependence of cloud amount on aerosols. The rain rate increases sharply with cloud thickness (CGT) and re when re > 14 μm. The dependence of rain rate on re and CGT presents a simple framework for precipitation susceptibility to aerosols, which explains other previously observed relationships. We showed that sorting data by CGT and using alternative cloud condensation nuclei proxy rather than aerosol optical depth are critical for studying aerosol‐cloud‐precipitation interactions.Plain Language SummaryAerosol‐cloud interaction remains the greatest uncertainty in future climate projection. Precipitation is a key process that mediates how the cloud amount responds to aerosol perturbations. Here we combined precipitation measured by the radar onboard the satellite of Global Precipitation Measurement (GPM) and cloud properties retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua satellite for studying the dependence of rain intensity on cloud properties for marine boundary layer water clouds over the Southern Hemisphere Ocean. Our results showed that rain is sharply intensified when droplets at the cloud top grow larger than 14 μm, and precipitation decreases with increasing cloud drop number concentration (Nd). A simple framework to explain the relationship between precipitation and aerosols is proposed here by showing the dependence of precipitation on Nd and cloud geometric thickness. We also discussed why using aerosol optical depth (AOD) as CCN proxy in previous studies could lead to great uncertainties and why sorting cloud geometrical thickness is necessary.Key PointsPrecipitation is strongly suppressed with increasing cloud drop concentrationSorting data by cloud thickness and using alternative CCN proxy rather than AOD are critical for studying aerosol‐cloud interactionsDetectable rain initiates when the drop effective radius at the cloud top exceeds 14 μmPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154630/1/grl60407.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154630/2/grl60407_am.pd

Uncertainties in global aerosol simulations: Assessment using three meteorological data sets

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94950/1/jgrd13664.pd

Aerosol-driven droplet concentrations dominate coverage and water of oceanic low level clouds

A lack of reliable estimates of cloud condensation nuclei (CCN) aerosols over oceans has severely limited our ability to quantify their effects on cloud properties and extent of cooling by reflecting solar radiation—a key uncertainty in anthropogenic climate forcing. We introduce a methodology for ascribing cloud properties to CCN and isolating the aerosol effects from meteorological effects. Its application showed that for a given meteorology, CCN explains three-fourths of the variability in the radiative cooling effect of clouds, mainly through affecting shallow cloud cover and water path. This reveals a much greater sensitivity of cloud radiative forcing to CCN than previously reported, which means too much cooling if incorporated into present climate models. This suggests the existence of compensating aerosol warming effects yet to be discovered, possibly through deep clouds

Aerosol-driven droplet concentrations dominate coverage and water of oceanic low level clouds

A lack of reliable estimates of cloud condensation nuclei (CCN) aerosols over oceans has severely limited our ability to quantify their effects on cloud properties and extent of cooling by reflecting solar radiation—a key uncertainty in anthropogenic climate forcing. We introduce a methodology for ascribing cloud properties to CCN and isolating the aerosol effects from meteorological effects. Its application showed that for a given meteorology, CCN explains three-fourths of the variability in the radiative cooling effect of clouds, mainly through affecting shallow cloud cover and water path. This reveals a much greater sensitivity of cloud radiative forcing to CCN than previously reported, which means too much cooling if incorporated into present climate models. This suggests the existence of compensating aerosol warming effects yet to be discovered, possibly through deep clouds

A Simple Model of Global Aerosol Indirect Effects

Most estimates of the global mean indirect effect of anthropogenic aerosol on the Earth's energy balance are from simulations by global models of the aerosol lifecycle coupled with global models of clouds and the hydrologic cycle. Extremely simple models have been developed for integrated assessment models, but lack the flexibility to distinguish between primary and secondary sources of aerosol. Here a simple but more physically based model expresses the aerosol indirect effect (AIE) using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of AIEs that are comparable to those from some global aerosol models using the same global mean aerosol properties, the estimates by the simple model are sensitive to preindustrial cloud condensation nuclei concentration, preindustrial accumulation mode radius, width of the accumulation mode, size of primary particles, cloud thickness, primary and secondary anthropogenic emissions, the fraction of the secondary anthropogenic emissions that accumulates on the coarse mode, the fraction of the secondary mass that forms new particles, and the sensitivity of liquid water path to droplet number concentration. Estimates of present-day AIEs as low as 5 W/sq m and as high as 0.3 W/sq m are obtained for plausible sets of parameter values. Estimates are surprisingly linear in emissions. The estimates depend on parameter values in ways that are consistent with results from detailed global aerosol-climate simulation models, which adds to understanding of the dependence on AIE uncertainty on uncertainty in parameter values

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and long-wave cloud radiative forcing at the top of atmosphere are changed by -2.5 and +1.3 W m(-2), respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors' knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000335798000044&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Multidisciplinary SciencesSCI(E)[email protected]; [email protected]

Constraining cloud lifetime effects of aerosols using A‐Train satellite observations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95434/1/grl29404.pd