Evaluating Observational Constraints on Intermodel Spread in Cloud, Temperature, and Humidity Feedbacks
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A one-dimensional time marching radiative transfer model has been used to investigate the potential effects of polar stratospheric clouds (PSCs) on winter and spring temperatures in the Antarctic lower stratosphere. High, middle, and low PSC amounts were specified from lidar backscatter profiles and were chosen to represent the likely range of PSC amounts present in the Antarctic region. The computed effects of the PSCs on temperatures depend strongly on the surface temperature and on the extent of tropospheric cloudiness, and range from a maximum increase of 6 K for a high amount of PSCs over a warm surface and clear troposphere to a maximum decrease of 2 K for a high amount of PSCs over a cold surface and a troposphere with high clouds. The average effect is unlikely to be more than a 1 or 2 K temperature change.
The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.
A new approach is developed for the parameterization of the radiative transfer in the atmosphere involving cirrus clouds. The parameterization scheme integrates in a coherent manner the delta-four-stream approximation for radiative transfer, the correlated k-distribution method for nongray gaseous absorption, and the scattering and absorption properties of hexagonal ice crystal. It was found that the present scheme is well suited for incorporation in numerical models for studies of the climatic effects of cirrus clouds as well as for investigations of interactions and feedbacks between cloud microphysics and radiation.
The Experimental Cloud Lidar Pilot Study (ECLIPS) project has now had two active phases in 1989 and 1991. A number of laboratories around the world have taken part in the study. The observations have yielded new data on cloud height and structure, and have yielded some useful new information on the retrieval of cloud optical properties, together with the uncertainties involved. Clouds have a major impact on the climate of the earth. They have the effect of reducing the mean surface temperature from 30 C for a cloudless planet to a value of about 15 C for present cloud conditions. However, it is not at all certain how clouds would react to a change in the planetary temperature in the event of climate change due to a radiative forcing from greenhouse gases. Clouds both reflect out sunlight (negative feedback) and enhance the greenhouse effect (positive feedback), but the ultimate sign of cloud feedback is unknown. Because of these uncertainties, campaigns to study clouds intensely were initiated. The International Satellite Cloud Climatology (ISCPP) and the FIRE Campaigns (cirrus and stratocumulus) are examples. The ECLIPS was set up similarly to the above experiments to obtain information specifically on cloud base, but also cloud top (where possible), optical properties, and cloud structure. ECLIPS was designed to allow as many laboratories as possible globally to take part to get the largest range of clouds. It involves observations with elastic backscatter lidar, supported by infrared fluxes at the ground and radiosonde data, as basic instrumentation. More complex experiments using beam filter radiometers, solar pyranometers, and satellite data and often associated with other campaigns were also encouraged to join ECLIPS. Two periods for observation were chosen, Sep. - Dec. 1989 and Apr. - Jul. 1992 into which investigators were requested to fit 30 days of observations. These would be either continuous, or arranged to coincide with NOAA satellite overpasses to obtain AVHRR data. The distribution of the ECLIPS international effort as in 1991 is shown. The main gaps in the global distribution are in the tropics and the Southern Hemisphere.
Three studies of the relative albedo to the IR components of cloud amount feedback are reviewed, and an approach to the seasonal variability in low-level cloud numbers is presented. Comparisons are made and uncertainties calculated for the predictions of cloud amounts from satellite data sets for outgoing IR flux. IR data is used directly for a linear regression analysis and seasonal and latitudinal variations are considered in terms of monthly-annual means for particular latitude zones. Investigations of NOAA-NESS satellite data revealed that cirrus clouds are transparent in the 10.5-12.5 microns range and cloud albedos decrease at wavelengths greater than 0.7 micron, which suggests a possibility of cloud-sky and clear-sky albedo comparisons at 0.5-0.7 micron. The inclusion of Rayleigh scattering and atmospheric water vapor absorption of sunlight is recommended to test the effects on observed contracts.
A three-dimensional numerical cloud model is utilized to study the collective feedback effects of cloud systems on the large-scale environment. The characteristic features of the cloud ensemble model are described. The model is applied to a case of a well-defined ITCZ rainband over the eastern tropical Atlantic ocean. The location, number, and configuration of the clouds that formed in the model during the simulations are examined. The cloud heating and moistening, environmental wind shear, and vertical transports of momentum are analyzed. The collective feedbacks of cloud systems on the large-scale temperature, moisture, and horizontal momentum fields are computed after each simulation. The effect of the pressure gradient force on the v-momentum flux is investigated. It is observed that there is good correlation between the model simulations and the observed data.
An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.
The following provides the final report on NASA IDP Project NAGW-1840 'Differentiating the Role of Land Surface Variability on Global Energy Transport within the Atmosphere and Oceans'. The project was designed to investigate the role of regional perturbations in the earth radiation budget on atmospheric and oceanic energy transports on an interannual basis. We proposed a modeling strategy based on an entropy extremum principle that could be used to separate the transports into oceanic and atmospheric components so as to better understand the effects of regional perturbations at the distinct atmospheric and oceanic time scales. The original focus was to consider the maintenance and year-to-year modulation of a large-scale, low-latitude North African-West Pacific Ocean net radiation dipole, which we had detected in the Nimbus 6 and 7 record of earth radiation budget measurements, and which necessitated significant cross-meridional energy transports to maintain global equilibrium. In addition, perturbations in the radiation balance term were to be partitioned into cloud-induced and surface-induced components to better understand the feedbacks between clouds and surface boundary conditions on interannual variability of the radiation balance.
Aura MLS provides the first vertical upper tropospheric cloud profiling from space, enabling global survey of the vertical structure of cloud systems, with seasonal and geographical variations, needed to evaluate the way clouds are parameterized in global models, thereby contributing to the understanding of cloud-climate feedbacks, and improved weather and climate predictions. The vertical structure of cloud systems is fundamentally important for understanding how clouds affect both their regional and large-scale atmospheric and radiative environments. The regional cloud profiles provide a critical tests of important parameterizations that enable the calculation of radiative flux profiles and heating rates throughout the atmospheric column, which in turn also regulates the water and energy cycles in the upper troposphere
Radiative kernels derived from CloudSat/CALIPSO measurements are used to diagnose radiative feedbacks induced by the Madden-Julian oscillation (MJO). Over the Indo-Pacific warm pool, positive cloud and water vapor feedbacks are coincident with the convective envelope of the MJO during its active phases, whereas the lapse rate feedback shows less obvious correlation to the propagating disturbance. During phase 2/3, when the convective envelope is over the Indian Ocean, water vapor exhibits a vertically coherent response, with the largest anomalies and strongest feedback in the middle troposphere. Though spatial structures of the feedbacks vary, the most prominent difference lies in the magnitude. Cloud changes induce the largest radiative perturbations associated with the MJO. We also find that for individual MJO events, cloud feedback and precipitation are highly correlated, suggesting that the strength of individual MJO events is largely dictated by the magnitude of cloud radiative heating of the atmosphere. In addition, stronger radiative heating due to water vapor and clouds helps the MJO survive the barrier effect of the Maritime Continent, leading to further eastward propagation. These results offer process-oriented metrics that could help to improve model simulations and predictions of the MJO in the future.
We analyze the atmospheric processes that explain the large changes in radiative feed-backs between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate-change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme; and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the pre-existing shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present-day, thereby reducing the radiative effciency of the increase of LWP in the warmer climate. It also enhances a strong, pre-existing, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations, and discuss avenues that could help constrain the relevant processes.
The Pilot Climate Data System (PCDS) affords an opportunity to analyze data from different but highly complementary data sets. Two of these highly complementary data sets supported by the PCDS are the International Satellite Cloud Climatology Project (ISCCP) and the Earth Radiation Budget Experiment (ERBE). Both data set sponsors are aware of the utility of one data set to the other, and both projects utilize gridded data on a 2.5 deg by 2.5 deg grid. The ISCCP data have been collected since July 1983, and the NOAA-9 data for ERBE have been collected for more than a year. Therefore, there is a good chance to use these temporally overlapping data sets to investigate hypothesized relationships. Changes in cloudiness affect both cloud albedo feedback (shortwave) and the greenhouse effect (longwave). The relative importance of the effects of clouds on albedo versus outgoing longwave radiation (OLR) in determining the radiation balance has long been a matter of controversy. Now, however, changes in cloud amount as observed by the ISCCPO can be correlated to corresponding changes in the albedo and changes in the OLR from ERBE. Monthly means can be utilized in all instances.
The idea of a habitable Venus epoch has gained traction in recent years via 1-D and 3-D General Circulation Modeling (GCM) efforts [1,2,3]. Although recent work has supported an alternative permanent hot and dry scenario [4]. However, the habitable scenario presents us with a conundrum - how does a terrestrial planet transform from temperate to hot-house? For decades it was proposed that the gradual brightening of the sun was the probable cause [5]. Yet 4 billion years ago Venus was receiving nearly 1.4 times the insolation that Earth receives today, and many studies have put Earth at the inner boundary of the habitable zone today [6]. The newer 3-D GCM efforts have demonstrated that if Venus had an early habitable period, that the cloud-albedo feedback responsible for maintaining temperate surface conditions [7] could still be in operation today. From this perspective increasing insolation through time cannot be an answer to the transition from habitable to hot-house. We propose that the 'Great Climate Transition' (GCT) was trigged by simultaneous large igneous provinces (LIPs) akin to those like the Siberian Traps responsible for the End Permian [8]. We have taken the most up to date LIP database for Earth [9] and characterized their distribution through time as random or nearly random. Next we initiate a large suite of Monte Carlo simulations based on this record and generate the likelihood for simultaneous, or environmentally overlapping events in this hypothetical setup. We find the probability of such events to be quite high, a probable cause for Venus' GCT, and a possible harbinger of things to come for Earth.
The diurnal variation of precipitation processes over the tropics is a well-known phenomenon and has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation. Recently, analyzed observations from Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) in the tropical western Pacific ocean to study the relevant mechanisms producing diurnal variation of precipitation. They found that the diurnal Sea surface temperature (SST) cycle is important for afternoon showers in the undisturbed periods and diurnal radiative processes for nocturnal rainfall. Cloud resolving models (CRMS) have been used to determine the mechanisms associated with diurnal variation of precipitating processes. CRMs allow explicit cloud-radiation and air-sea interactive processes. However, CRMs can be only used for idealized simulations (i.e., no feedback between clouds and their embedded large-scale environments; cyclic lateral boundary conditions and idealized initial conditions). In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (covers the TOGA COARE LSA/IFA with a 54 km grid and can nest down to 18, 6 and possibly even 2 km) will be adopted for studying the diurnal variations of rainfall. We will examine precipitation processes over open ocean and over land. We will also perform sensitivity tests to determine how the radiative forcing and diurnal SST cycle affects the development of convection.
Clouds play a central role in the global climate system through the modulation of Earth’s energy flows and as a mediator of precipitation. In the Arctic, clouds are also a major player; however, the processes that govern cloud evolution in the Arctic differ from most of the other regions of the globe. Thus, clouds are a key “wildcard” within the Arctic climate system that could have a substantial influence on the Arctic climate system response to anthropogenic forcing. What is the role of clouds within the phenomenon known as Arctic Amplification? This is question does not have a clear answer. Clouds seem to be a center to the important processes driving Arctic Amplification (e.g., the atmospheric response to sea ice loss and airmass transformation), however feedback analysis studies indicate that net cloud feedback in the Arctic is small. This seminar discusses the role of clouds within the Arctic Amplification processes reviewing aspects of what we know about Arctic clouds and the uncertainties that limit our ability to model them. Results from recently published and ongoing work are presented that provide an observationally-based estimate of the cloud-sea ice feedback and evaluate cloud properties within models. The goal of this presentation is to ignite a discussion and new collaborations around the best approaches to resolving uncertainties related to the role of clouds with the Arctic system and how to better represent Arctic clouds in models.
Whether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections.
The mission's primary goal is to furnish data needed to improve how cloud and cloud-climate feedbacks are parameterized in global circulation models (GCMs).