Climate sensitivity and relative humidity changes in global storm-resolving model simulations of climate change

The climate simulation frontier of a global storm-resolving model (GSRM; or k-scale model because of its kilometer-scale horizontal resolution) is deployed for climate change simulations. The climate sensitivity, effective radiative forcing, and relative humidity changes are assessed in multiyear atmospheric GSRM simulations with perturbed sea-surface temperatures and/or carbon dioxide concentrations. Our comparisons to conventional climate model results can build confidence in the existing climate models or highlight important areas for additional research. This GSRM's climate sensitivity is within the range of conventional climate models, although on the lower end as the result of neutral, rather than amplifying, shortwave feedbacks. Its radiative forcing from carbon dioxide is higher than conventional climate models, and this arises from a bias in climatological clouds and an explicitly simulated high-cloud adjustment. Last, the pattern and magnitude of relative humidity changes, simulated with greater fidelity via explicitly resolving convection, are notably similar to conventional climate models.

Increasingly Sophisticated Climate Models Need the Out-Of-Sample Tests Paleoclimates Provide

Climate models are becoming increasingly sophisticated as climate scientists continually work to improve the realism with which the processes influencing Earth's climate are represented. One example is the treatment of cloud microphysics: as complexity is added to cloud microphysical schemes, Earth's energy budget can respond to changes in climate forcings, such as carbon dioxide or aerosols, in new ways. This increase in degrees of freedom has illuminated larger spread in climate sensitivity across the latest generation of climate models participating Coupled Model Intercomparison Project, Phase 6, with more high climate sensitivity models (Zelinka et al., 2020, https://doi.org/10.1029/2019gl085782). Whilst the historical record gives us just over a century of data to apply toward climate sensitivity constraints (e.g., Nijsse et al., 2020, https://doi.org/10.5194/esd-11-737-2020), the ocean is still taking up much of the heat trapped by anthropogenic greenhouse gas emissions and the climate system is far from equilibrium which limits our understanding how climate sensitivity might change in response to long-term forced climate change. Here we discuss the valuable tests that paleoclimate reconstructions can provide the latest generation of climate models, as demonstrated by the recent study of Zhu et al., 2022, https://doi.org/10.1029/2021ms002776. Their study provides an example of the benefits for climate model development when climate models are confronted with simulating climates very different from today. Ideally the climate model development stage under future iterations of CMIP will involve such tests as an effort to constrain global climate sensitivity and the regional patterns of climate, such as polar amplification and subtropical aridification.

Episodic deluges in simulated hothouse climates

Earth's distant past and potentially its future include extremely warm 'hothouse'¹ climate states, but little is known about how the atmosphere behaves in such states. One distinguishing characteristic of hothouse climates is that they feature lower-tropospheric radiative heating, rather than cooling, due to the closing of the water vapour infrared window regions². Previous work has suggested that this could lead to temperature inversions and substantial changes in cloud cover^3-6, but no previous modelling of the hothouse regime has resolved convective-scale turbulent air motions and cloud cover directly, thus leaving many questions about hothouse radiative heating unanswered. Here we conduct simulations that explicitly resolve convection and find that lower-tropospheric radiative heating in hothouse climates causes the hydrologic cycle to shift from a quasi-steady regime to a 'relaxation oscillator' regime, in which precipitation occurs in short and intense outbursts separated by multi-day dry spells. The transition to the oscillatory regime is accompanied by strongly enhanced local precipitation fluxes, a substantial increase in cloud cover, and a transiently positive (unstable) climate feedback parameter. Our results indicate that hothouse climates may feature a novel form of 'temporal' convective self-organization, with implications for both cloud coverage and erosion processes.

Intra-seasonal contrasting trends in clouds due to warming induced circulation changes

Quantification of long term changes in cloud distribution and properties is critical for the proper assessment of future climate. We show contrasting trends in cloud properties and cloud radiative effects over Northwest Indian Ocean (NWIO) in south Asian summer monsoon. Cloud top height (CTH) decreases in June (− 69 ± 3 myr⁻¹) and July (− 44 ± 3 myr⁻¹), whereas it increases in August (106 ± 2 myr⁻¹) and September (37 ± 1 myr⁻¹). These contrasting trends are investigated to be due to the changes in upper tropospheric winds and atmospheric circulation pattern. Strengthening of upper tropospheric easterlies and changes in vertical wind dampen the vertical development of clouds in June and July. In contrast, weakening of upper tropospheric winds over NWIO and strengthening of updraft favour the vertical growth of clouds in August. Further, changes in horizontal winds at 450–350 hPa and strengthening of Indian Ocean Walker cell favour the westward spread of high level clouds, contributing to the increase in CTH over NWIO in August. Decrease of cloud cover and altitude in June and July and increase of the same in subsequent months would affect the monsoon rainfall over the Indian region. Proper representation of these intra-seasonal contrasting trends of clouds in climate models is important for the better prediction of regional weather.

Influence of climate change on the predicted distributions of the genus Tympanoctomys (Rodentia, Hystricomorpha, Octodontidae), and their conservation implications

Viscacha rats (genus Tympanoctomys Yepes, 1942) are ecologically, physiologically, and behaviorally unusual octodontid rodents endemic to the Monte and Patagonian desert biomes of Argentina. The geographic ranges of the different species of Tympanoctomys have been described in general terms but have not been associated with spatial and climate data. Within species, populations are patchily distributed and genetically distinct. We investigated the predicted distribution of Tympanoctomys and the influence of climate fluctuations on their geographic range in historical, current, and future, scenarios. Our objectives were to characterize the environmental niche of the genus, propose a paleoclimatic context for the oldest fossils, characterize the environmental niches for T. barrerae and T. kirchnerorum, and forecast potential future distributions for these taxa. Ecological niche models were constructed using occurrence records from 1941 to the present wherein we identified several precipitation and temperature variables as important predictors of the geographic distributions of the genus, and the species T. barrerae and T. kirchnerorum. Based on our models’ results, we hypothesize that the distribution of Tympanoctomys has contracted from historical to modern times. At the species level, T. kirchnerorum likely experienced the most dramatic change, suffering a large contraction of its historical distribution resulting in its limited present distribution. Given these findings, projected future climate fluctuations and global warming are expected to affect the distributions and persistence of these species.

Three-Dimensional Cloud Structure Reconstruction from the Directional Polarimetric Camera

Clouds affect radiation transmission through the atmosphere, which impacts the Earth’ s energy balance and climate. Currently, the study of clouds is mostly based on a two-dimensional (2-D) plane rather than a three-dimensional (3-D) space. However, 3-D cloud reconstruction is playing an important role not only in a radiation transmission calculation but in forecasting climate change as well. Currently, the study of clouds is mostly based on 2-D single angle satellite observation data while the importance of a 3-D structure of clouds in atmospheric radiation transmission is ignored. 3-D structure reconstruction would improve the radiation transmission accuracy of the cloudy atmosphere based on multi-angle observations data. Characterizing the 3-D structure of clouds is crucial for an extensive study of this complex intermediate medium in the atmosphere. In addition, it is also a great carrier for visualization of its parameters. Special attributes and the shape of clouds can be clearly illustrated in a 3-D cloud while these are difficult to describe in a 2-D plane. It provides a more intuitive expression for the study of complex cloud systems. In order to reconstruct a 3-D cloud structure, we develop and explore a ray casting algorithm applied to data from the Directional Polarimetric Camera (DPC), which is onboard the GF-5 satellite. In this paper, we use DPC with characteristics of imaging multiple angles of the same target, and characterize observations of clouds from different angles in 3-D space. This feature allows us to reconstruct 3-D clouds from different angles of observations. In terms of verification, we use cloud profile data provided by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to compare with the results of reconstructed 3-D clouds based on DPC data. This shows that the reconstruction method has good accuracy and effectiveness. This 3-D cloud reconstruction method would lay a scientific reference for future analysis on the role of clouds in the atmosphere and for the construction of 3-D structures of aerosols.

Cloud scattering impact on thermal radiative transfer and global longwave radiation

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800-1250 cm^-1). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300-600 cm^-1) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ~3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important. The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%-4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m², and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m² and 1.8 W/m², respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6W/m², -1.1 W/m², and -2.5 W/m², respectively. The global scattering impact of 2.7 W/m² on the OLR is small when compared to the typical global OLR value of 240W/m², but it is significant when compared to cloud LW radiative forcing (30W/m²) and net cloud forcing (-14W/m²). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO₂.

Retrieval and Validation of Cloud Top Temperature from the Geostationary Satellite INSAT-3D

Investigation of cloud top temperature (CTT) and its diurnal variation is highly reliant on high spatial and temporal resolution satellite data, which is lacking over the Indian region. An algorithm has been developed for detection of clouds and retrieval of CTT from the geostationary satellite INSAT-3D. These retrievals are validated (inter-compared) with collocated in-situ (satellite) measurements with specific intent to generate climate-quality data. The cloud detection algorithm employs nine different tests, in accordance with solar illumination, satellite angle and surface type conditions to generate pixel-resolution cloud mask. Validation of cloud mask with cloud-aerosol lidar with orthogonal polarization (CALIOP) shows that probability of detection (POD) of cloudy (clear) sky is 81% (85%), with 83% hit rate. The algorithm is also implemented on similar channels of moderate resolution imaging spectroradiometer (MODIS), which provides 88% (83%) POD of cloudy (clear) sky, with 86% hit rate. CTT retrieval is done at the pixel level, for all cloud pixels, by employing appropriate methods for various types of clouds. Comparison of CTT with radiosonde and cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO) shows mean absolute error less than 3%. The study also examines sensitivity of retrieved CTT to the cloud classification scheme and retrieval criteria. Validation results and their close agreements with those of similar satellites demonstrate the reliability of the retrieved product for climate studies.

Effects of Biomass Burning on Stratocumulus Droplet Characteristics, Drizzle Rate, and Composition

This study reports on airborne measurements of stratocumulus cloud properties under varying degrees of influence from biomass burning (BB) plumes off the California coast. Data are reported from five total airborne campaigns based in Marina, California, with two of them including influence from wildfires in different areas along the coast of the western United States. The results indicate that subcloud cloud condensation nuclei number concentration and mass concentrations of important aerosol species (organics, sulfate, nitrate) were better correlated with cloud droplet number concentration (N d) as compared to respective above-cloud aerosol data. Given that the majority of BB particles resided above cloud tops, this is an important consideration for future work in the region as the data indicate that the subcloud BB particles likely were entrained from the free troposphere. Lower cloud condensation nuclei activation fractions were observed for BB-impacted clouds as compared to non-BB clouds due, at least partly, to less hygroscopic aerosols. Relationships between N d and either droplet effective radius or drizzle rate are preserved regardless of BB influence, indicative of how parameterizations can exhibit consistent skill for varying degrees of BB influence as long as N d is known. Lastly, the composition of both droplet residual particles and cloud water changed significantly when clouds were impacted by BB plumes, with differences observed for different fire sources stemming largely from effects of plume aging time and dust influence.

Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3

We analyze the atmospheric processes that explain the large changes in radiative feedbacks 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 preexisting 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 and reduces the increase in LWP with warming. Both changes contribute to reducing the negative radiative feedback of the increase of LWP in the warmer climate. The mixed-phase scheme also enhances a strong, preexisting, 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.

Climates of Warm Earth-like Planets I: 3-D Model Simulations

We present a large ensemble of simulations of an Earth-like world with increasing insolation and rotation rate. Unlike previous work utilizing idealized aquaplanet configurations we focus our simulations on modern Earth-like topography. The orbital period is the same as modern Earth, but with zero obliquity and eccentricity. The atmosphere is 1 bar N2-dominated with CO2=400 ppmv and CH4=1 ppmv. The simulations include two types of oceans; one without ocean heat transport (OHT) between grid cells as has been commonly used in the exoplanet literature, while the other is a fully coupled dynamic bathtub type ocean. The dynamical regime transitions that occur as day length increases induce climate feedbacks producing cooler temperatures, first via the reduction of water vapor with increasing rotation period despite decreasing shortwave cooling by clouds, and then via decreasing water vapor and increasing shortwave cloud cooling, except at the highest insolations. Simulations without OHT are more sensitive to insolation changes for fast rotations while slower rotations are relatively insensitive to ocean choice. OHT runs with faster rotations tend to be similar with gyres transporting heat poleward making them warmer than those without OHT. For slower rotations OHT is directed equator-ward and no high latitude gyres are apparent. Uncertainties in cloud parameterization preclude a precise determination of habitability but do not affect robust aspects of exoplanet climate sensitivity. This is the first paper in a series that will investigate aspects of habitability in the simulations presented herein. The datasets from this study are opensource and publicly available.

Decadal Changes of Earth’s Outgoing Longwave Radiation

The Earth Radiation Budget (ERB) at the top of the atmosphere quantifies how the earth gains energy from the sun and loses energy to space. Its monitoring is of fundamental importance for understanding ongoing climate change. In this paper, decadal changes of the Outgoing Longwave Radiation (OLR) as measured by the Clouds and Earth’s Radiant Energy System from 2000 to 2018, the Earth Radiation Budget Experiment from 1985 to 1998, and the High-resolution Infrared Radiation Sounder from 1985 to 2018 are analysed. The OLR has been rising since 1985, and correlates well with the rising global temperature. An observational estimate of the derivative of the OLR with respect to temperature of 2.93 +/− 0.3 W/m 2 K is obtained. The regional patterns of the observed OLR change from 1985–2000 to 2001–2017 show a warming pattern in the Northern Hemisphere in particular in the Arctic, as well as tropical cloudiness changes related to a strengthening of La Niña.

Potential of Cost-Efficient Single Frequency GNSS Receivers for Water Vapor Monitoring

Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). The density of existing GNSS monitoring networks is insufficient to capture small-scale water vapor variations that are especially important for extreme weather forecasting. A densification with geodetic-grade dual-frequency receivers is not economically feasible. Cost-efficient single-frequency receivers offer a possible alternative. This paper studies the feasibility of using low-cost receivers to increase the density of GNSS networks for retrieval of PWV. We processed one year of GNSS data from an IGS station and two co-located single-frequency stations. Additionally, in another experiment, the Radio Frequency (RF) signal from a geodetic-grade dual-frequency antenna was split to a geodetic receiver and two low-cost receivers. To process the single-frequency observations in Precise Point Positioning (PPP) mode, we apply the Satellite-specific Epoch-differenced Ionospheric Delay (SEID) model using two different reference network configurations of 50–80 km and 200–300 km mean station distances, respectively. Our research setup can distinguish between the antenna, ionospheric interpolation, and software-related impacts on the quality of PWV retrievals. The study shows that single-frequency GNSS receivers can achieve a quality similar to that of geodetic receivers in terms of RMSE for ZTD estimations. We demonstrate that modeling of the ionosphere and the antenna type are the main sources influencing the ZTD precision.

An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified Representation of Subgrid-Scale Turbulence and Convection

Large-scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid-scale turbulence and convection-such as that they adjust instantaneously to changes in resolved-scale dynamics-cease to be justifiable. Additionally, the common practice of representing boundary-layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large-scale models. Here we lay the theoretical foundations for an extended eddy-diffusivity mass-flux (EDMF) scheme that has explicit time-dependence and memory of subgrid-scale variables and is designed to represent all subgrid-scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross-sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large-scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time-dependent life cycle.

Diurnal cloud cycle biases in climate models

Clouds' efficiency at reflecting solar radiation and trapping the terrestrial radiation is strongly modulated by the diurnal cycle of clouds (DCC). Much attention has been paid to mean cloud properties due to their critical role in climate projections; however, less research has been devoted to the DCC. Here we quantify the mean, amplitude, and phase of the DCC in climate models and compare them with satellite observations and reanalysis data. While the mean appears to be reliable, the amplitude and phase of the DCC show marked inconsistencies, inducing overestimation of radiation in most climate models. In some models, DCC appears slightly shifted over the ocean, likely as a result of tuning and fortuitously compensating the large DCC errors over the land. While this model tuning does not seem to invalidate climate projections because of the limited DCC response to global warming, it may potentially increase the uncertainty of climate predictions.

Differences in the Hydrological Cycle and Sensitivity Between Multiscale Modeling Frameworks with and without a Higher-order Turbulence Closure

Current conventional global climate models (GCMs) produce a weak increase in global mean precipitation with anthropogenic warming in comparison with the lower-tropospheric moisture increases. The motive of this study is to understand the differences in the hydrological sensitivity between two multiscale modeling frameworks (MMFs) that arise from the different treatments of turbulence and low clouds in order to aid to the understanding of the model spread among conventional GCMs. We compare the hydrological sensitivity and its energetic constraint from MMFs with (SPCAM-IPHOC) or without (SPCAM) an advanced higher-order turbulence closure. SPCAM-IPHOC simulates higher global hydrological sensitivity for the slow response but lower sensitivity for the fast response than SPCAM. Their differences are comparable to the spreads of conventional GCMs. The higher sensitivity in SPCAM-IPHOC is associated with the higher ratio of the changes in latent heating to those in net atmospheric radiative cooling, which is further related to a stronger decrease in the Bowen ratio with warming than in SPCAM. The higher sensitivity of cloud radiative cooling resulting from the lack of low clouds in SPCAM is another major factor in contributing to the lower precipitation sensitivity. The two MMFs differ greatly in the hydrological sensitivity over the tropical lands, where the simulated sensitivity of surface sensible heat fluxes to surface warming and CO₂ increase in SPCAM-IPHOC is weaker than in SPCAM. The difference in divergences of dry static energy flux simulated by the two MMFs also contributes to the difference in land precipitation sensitivity between the two models.

Practice and philosophy of climate model tuning across six U.S. modeling centers

Model calibration (or "tuning") is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major U.S. climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present day radiative imbalance vs. the implied balance in the pre-industrial as a target.

Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds

Stratocumulus clouds are the most common type of boundary layer cloud; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus clouds often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the cloud top. The challenge posed to LES by stratocumulus clouds is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS-II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS-II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid-scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS-II observations are identified. The results show that using weighted essentially non-oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest-fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high-quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest-fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the cloud tops through the interaction of numerical error in the momentum field with the scalar SGS model.

Spread in model climate sensitivity traced to atmospheric convective mixing

Equilibrium climate sensitivity refers to the ultimate change in global mean temperature in response to a change in external forcing. Despite decades of research attempting to narrow uncertainties, equilibrium climate sensitivity estimates from climate models still span roughly 1.5 to 5 degrees Celsius for a doubling of atmospheric carbon dioxide concentration, precluding accurate projections of future climate. The spread arises largely from differences in the feedback from low clouds, for reasons not yet understood. Here we show that differences in the simulated strength of convective mixing between the lower and middle tropical troposphere explain about half of the variance in climate sensitivity estimated by 43 climate models. The apparent mechanism is that such mixing dehydrates the low-cloud layer at a rate that increases as the climate warms, and this rate of increase depends on the initial mixing strength, linking the mixing to cloud feedback. The mixing inferred from observations appears to be sufficiently strong to imply a climate sensitivity of more than 3 degrees for a doubling of carbon dioxide. This is significantly higher than the currently accepted lower bound of 1.5 degrees, thereby constraining model projections towards relatively severe future warming.

Radar observations of individual rain drops in the free atmosphere

Atmospheric remote sensing has played a pivotal role in the increasingly sophisticated representation of clouds in the numerical models used to assess global and regional climate change. This has been accomplished because the underlying bulk cloud properties can be derived from a statistical analysis of the returned microwave signals scattered by a diverse ensemble comprised of numerous cloud hydrometeors. A new Doppler radar, previously used to track small debris particles shed from the NASA space shuttle during launch, is shown to also have the capacity to detect individual cloud hydrometeors in the free atmosphere. Similar to the traces left behind on film by subatomic particles, larger cloud particles were observed to leave a well-defined radar signature (or streak), which could be analyzed to infer the underlying particle properties. We examine the unique radar and environmental conditions leading to the formation of the radar streaks and develop a theoretical framework which reveals the regulating role of the background radar reflectivity on their observed characteristics. This main expectation from theory is examined through an analysis of the drop properties inferred from radar and in situ aircraft measurements obtained in two contrasting regions of an observed multicellular storm system. The observations are placed in context of the parent storm circulation through the use of the radar's unique high-resolution waveforms, which allow the bulk and individual hydrometeor properties to be inferred at the same time.

Multicompartmental fate of persistent substances. Comparison of predictions from multi-media box models and a multicompartment chemistry-atmospheric transport model

BACKGROUND, AIM AND SCOPE

Modelling of the fate of environmental chemicals can be done by relatively simple multi-media box models or using complex atmospheric transport models. It was the aim of this work to compare the results obtained for both types of models using a small set of non-ionic and non-polar or moderately polar organic chemicals, known to be distributed over long distances.

MATERIALS AND METHODS

Predictions of multimedia exposure models of different types, namely three multimedia mass-balance box models (MBMs), two in the steady state and one in the non-steady state mode, and one non-steady state multicompartment chemistry-atmospheric transport model (MCTM), are compared for the first time. The models used are SimpleBox, Chemrange, the MPI-MBM and the MPI-MCTM. The target parameters addressed are compartmental distributions (i.e. mass fractions in the compartments), overall environmental residence time (i.e. overall persistence and eventually including other final sinks, such as loss to the deep sea) and a measure for the long-range transport potential. These are derived for atrazine, benz-[a]-pyrene, DDT, alpha and gamma-hexachlorocyclohexane, methyl parathion and various modes of substance entry into the model world.

RESULTS AND DISCUSSION

Compartmental distributions in steady state were compared. Steady state needed 2-10 years to be established in the MCTM. The highest fraction of the substances in air is predicted by the MCTM. Accordingly, the other models predict longer substance persistence in most cases. The results suggest that temperature affects the compartmental distribution more in the box models, while it is only one among many climate factors acting in the transport model. The representation of final sinks in the models, e.g. burial in the sediment, is key for model-based compartmental distribution and persistence predictions. There is a tendency of MBMs to overestimate substance sinks in air and to underestimate atmospheric transport velocity as a consequence of the neglection of the temporal and spatial variabilities of these parameters. Therefore, the long-range transport potential in air derived from MCTM simulations exceeds the one from Chemrange in most cases and least for substances which undergo slow degradation in air.

CONCLUSIONS AND PERSPECTIVES

MBMs should be improved such as to ascertain that the significance of the atmosphere for the multicompartmental cycling is not systematically underestimated. Both types of models should be improved such as to cover degradation in air in the particle-bound state and transport via ocean currents. A detailed understanding of the deviations observed in this work and elsewhere should be gained and multimedia fate box models could then be 'tuned in' to match better the results of comprehensive multicompartmental transport models.

The radiative signature of upper tropospheric moistening

Climate models predict that the concentration of water vapor in the upper troposphere could double by the end of the century as a result of increases in greenhouse gases. Such moistening plays a key role in amplifying the rate at which the climate warms in response to anthropogenic activities, but has been difficult to detect because of deficiencies in conventional observing systems. We use satellite measurements to highlight a distinct radiative signature of upper tropospheric moistening over the period 1982 to 2004. The observed moistening is accurately captured by climate model simulations and lends further credence to model projections of future global warming.

The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy

Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

Global cooling after the eruption of Mount Pinatubo: a test of climate feedback by water vapor

The sensitivity of Earth's climate to an external radiative forcing depends critically on the response of water vapor. We use the global cooling and drying of the atmosphere that was observed after the eruption of Mount Pinatubo to test model predictions of the climate feedback from water vapor. Here, we first highlight the success of the model in reproducing the observed drying after the volcanic eruption. Then, by comparing model simulations with and without water vapor feedback, we demonstrate the importance of the atmospheric drying in amplifying the temperature change and show that, without the strong positive feedback from water vapor, the model is unable to reproduce the observed cooling. These results provide quantitative evidence of the reliability of water vapor feedback in current climate models, which is crucial to their use for global warming projections.