Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s

Teleconnections, Midlatitude Cyclones and Aegean Sea Turbulent Heat Flux Variability on Daily Through Decadal Time Scales

We analyze daily wintertime cyclone variability in the central and eastern Mediterranean during 1958-2001, and identify four distinct cyclone states, corresponding to the presence or absence of cyclones in each basin. Each cyclone state is associated with wind flows that induce characteristic patterns of cooling via turbulent (sensible and latent) heat fluxes in the eastern Mediterranean basin and Aegean Sea. The relative frequency of occurrence of each state determines the heat loss from the Aegean Sea during that winter, with largest heat losses occurring when there is a storm in the eastern but not central Mediterranean (eNOTc), and the smallest occurring when there is a storm in the central but not eastern Mediterranean (cNOTe). Time series of daily cyclone states for each winter allow us to infer Aegean Sea cooling for winters prior to 1985, the earliest year for which we have daily heat flux observations. We show that cyclone states conducive to Aegean Sea convection occurred in 1991/1992 and 1992/1993, the winters during which deep water formation was observed in the Aegean Sea, and also during the mid-1970s and the winters of 1963/1964 and 1968/1969. We find that the eNOTc cyclone state is anticorrelated with the North Atlantic Oscillation (NAO) prior to 1977/1978. After 1977/1978, the cNOTe state is anticorrelated with both the NAO and the North Caspian Pattern (NCP), showing that the area of influence of large scale atmospheric teleconnections on regional cyclone activity shifted from the eastern to the central Mediterranean during the late 1970s. A trend toward more frequent occurrence of the positive phase of the NAO produced less frequent cNOTe states since the late 1970s, increasing the number of days with strong cooling of the Aegean Sea surface waters

The Ozone Hole Indirect Effect: Cloud-Radiative Anomalies Accompanying the Poleward Shift of the Eddy-Driven Jet in the Southern Hemisphere

This study quantifies the response of the clouds and the radiative budget of the Southern Hemisphere (SH) to the poleward shift in the tropospheric circulation induced by the development of the Antarctic ozone hole. Single forcing climate model integrations, in which only stratospheric ozone depletion is specified, indicate that (1) high-level and midlevel clouds closely follow the poleward shift in the SH midlatitude jet and that (2) low-level clouds decrease across most of the Southern Ocean. Similar cloud anomalies are found in satellite observations during periods when the jet is anomalously poleward. The hemispheric annual mean radiation response to the cloud anomalies is calculated to be approximately +0.25 W m−2, arising largely from the reduction of the total cloud fraction at SH midlatitudes during austral summer. While these dynamically induced cloud and radiation anomalies are considerable and are supported by observational evidence, quantitative uncertainties remain from model biases in mean-state cloud-radiative processes

Use of Cloud Radar Doppler Spectra to Evaluate Stratocumulus Drizzle Size Distributions in Large-Eddy Simulations with Size-Resolved Microphysics

A case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely

Global warming in the pipeline

Improved knowledge of glacial-to-interglacial global temperature change implies that fast-feedback equilibrium climate sensitivity is at least ~4{\deg}C for doubled CO2 (2xCO2), with likely range 3.5-5.5{\deg}C. Greenhouse gas (GHG) climate forcing is 4.1 W/m2 larger in 2021 than in 1750, equivalent to 2xCO2 forcing. Global warming in the pipeline is greater than prior estimates. Eventual global warming due to today's GHG forcing alone -- after slow feedbacks operate -- is about 10{\deg}C. Human-made aerosols are a major climate forcing, mainly via their effect on clouds. We infer from paleoclimate data that aerosol cooling offset GHG warming for several millennia as civilization developed. A hinge-point in global warming occurred in 1970 as increased GHG warming outpaced aerosol cooling, leading to global warming of 0.18{\deg}C per decade. Aerosol cooling is larger than estimated in the current IPCC report, but it has declined since 2010 because of aerosol reductions in China and shipping. Without unprecedented global actions to reduce GHG growth, 2010 could be another hinge point, with global warming in following decades 50-100% greater than in the prior 40 years. The enormity of consequences of warming in the pipeline demands a new approach addressing legacy and future emissions. The essential requirement to "save" young people and future generations is return to Holocene-level global temperature. Three urgently required actions are: 1) a global increasing price on GHG emissions, 2) purposeful intervention to rapidly phase down present massive geoengineering of Earth's climate, and 3) renewed East-West cooperation in a way that accommodates developing world needs.Comment: 48 pages, 27 figures. Correction of formatting error on page 21, which messed up placement of all following figure

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.Keywords: Atmosphere-ocean interaction, Decadal variability, Spring season, La Nina, Meridional overturning circulation, Hadley circulationKeywords: Atmosphere-ocean interaction, Decadal variability, Spring season, La Nina, Meridional overturning circulation, Hadley circulatio

Does dynamical downscaling introduce novel information in climate model simulations of precipitation change over a complex topography region?

Current climate and future climate-warming runs with the RegCM Regional Climate Model (RCM) at 50 and 11 km-resolutions forced by the ECHAM GCM are used to examine whether the increased resolution of the RCM introduces novel information in the precipitation field when the models are run for the mountainous region of the Hellenic peninsula. The model results are inter-compared with the resolution of the RCM output degraded to match that of the GCM, and it is found that in both the present and future climate runs the regional models produce more precipitation than the forcing GCM. At the same time, the RCM runs produce increases in precipitation with climate warming even though they are forced with a GCM that shows no precipitation change in the region. The additional precipitation is mostly concentrated over the mountain ranges, where orographic precipitation formation is expected to be a dominant mechanism. It is found that, when examined at the same resolution, the elevation heights of the GCM are lower than those of the averaged RCM in the areas of the main mountain ranges. It is also found that the majority of the difference in precipitation between the RCM and the GCM can be explained by their difference in topographic height. The study results indicate that, in complex topography regions, GCM predictions of precipitation change with climate warming may be dry biased due to the GCM smoothing of the regional topography

A Study to Investigate Cloud Feedback Processes and Evaluate GCM Cloud Variations Using Statistical Cloud Property Composites From ARM Data

The representation of clouds in Global Climate Models (GCMs) remains a major source of uncertainty in climate change simulations. Cloud climatologies have been widely used to either evaluate climate model cloud fields or examine, in combination with other data sets, climate-scale relationships between cloud properties and dynamical or microphysical parameters. Major cloud climatologies have been based either on satellite observations of cloud properties or on surface observers views of cloud type and amount. Such data sets provide either the top-down view of column-integrated cloud properties (satellites) or the bottom-up view of the cloud field morphology (surface observers). Both satellite-based and surface cloud climatologies have been successfully used to examine cloud properties, to support process studies, and to evaluate climate and weather models. However, they also present certain limitations, since the satellite cloud types are defined using radiative cloud boundaries and surface observations are based on cloud boundaries visible to human observers. As a result, these data sets do not resolve the vertical distribution of cloud layers, an issue that is important in calculating both the radiative and the hydrologic effects of the cloud field. Ground-based cloud radar observations, on the other hand, resolve with good accuracy the vertical distribution of cloud layers and could be used to produce cloud type climatologies with vertical layering information. However, these observations provide point measurements only and it is not immediately clear to what extent they are representative of larger regimes. There are different methods that can be applied to minimize this problem and to produce cloud layering climatologies useful for both cloud process and model evaluation studies. If a radar system is run continuously over a number of years, it eventually samples a large number of dynamical and microphysical regimes. If additional data sets are used to put the cloud layering information into the context of large-scale dynamical regimes, such information can be used to study interactions among cloud vertical distributions and dynamical and microphysical processes and to evaluate the ability of models to simulate those interactions. The U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has established several Climate Research Facilities (ACRF) that provide continuous, long-term observations of clouds and radiation. ARM, with its overall goal of improving the treatment of radiation and clouds in climate models has provided unique observing systems for accelerating progress on the representation of cloud processes. In this project, six and a half years (January 1998 to June 2004) of cloud observations collected at the Southern Great Plains (SGP) Oklahoma ACRF were used to produce a cloud-type climatology. The climatology provides cloud amounts for seven different cloud types as well as information on the detailed structure of multi-layer cloud occurrences. Furthermore, the European Centre for Medium-Range Weather Forecasts (ECMWF) model output was used to define the dynamic regimes present during the observations of the cloud conditions by the vertically pointing radars at the SGP ACRF. The cloud-type climatology and the ECMWF SGP data set were then analyzed to examine and map dynamical conditions that favor the creation of single-layer versus multi-layer cloud structures as well as dynamical conditions that favor the occurrence of drizzle in continental stratus clouds. In addition, output from the ECMWF weather model forecasts was analyzed with the objective to compare model and radar derived cloud type statistics, in order to identify the major model deficiencies in cloud vertical distribution and map their seasonal variations. The project included two primary goals. The first was to create a cloud type climatology over the Southern Great Planes site that will show how cloud vertical distribution varies with dynamic and thermodynamic regime and how these variations would affect cloud climate feedbacks. The second was to compare this climatology to clouds derived by a numerical model in order to identify the major model deficiencies in cloud vertical distribution and map their seasonal variations

Introduction to Clouds

This site provides the user an opportunity to explore storm clouds and climate change through the use of NASA climate research data obtained through satellite imaging. The user is challenged to investigate actual scientific research data on clouds and storms, and make observations and interpretations available to NASA research scientists for review. Topics addressed by these investigations include the role of clouds in relation to the changing climate of Earth, the role of clouds in warming or cooling the planet, and the major types of clouds produced by storms. Educational levels: High school, Undergraduate lower division