Relative importance of acid coating on ice nuclei in the deposition and contact modes for wintertime Arctic clouds and radiation

Aerosols emitted from volcanic activities and polluted mid-latitudes regions are efficiently transported over the Arctic during winter by the large-scale atmospheric circulation. These aerosols are highly acidic. The acid coating on ice nuclei, which are present among these aerosols, alters their ability to nucleate ice crystals. In this research, the effect of acid coating on deposition and contact ice nuclei on the Arctic cloud and radiation is evaluated for January 2007 using a regional climate model. Results show that the suppression of contact freezing by acid coating on ice nuclei leads to small changes of the cloud microstructure and has no significant effect on the cloud radiative forcing (CRF) at the top of the atmosphere when compared with the effect of the alteration of deposition ice nucleation by acid coating on deposition ice nuclei. There is a negative feedback by which the suppression of contact freezing leads to an increase of the ice crystal nucleation rate by deposition ice nucleation. As a result, the suppression of contact freezing leads to an increase of the cloud ice crystal concentration. Changes in the cloud liquid and ice water contents remain small and the CRF is not significantly modified. The alteration of deposition ice nucleation by acid coating on ice nuclei is dominant over the alteration of contact freezing.     

The simulation of Arctic clouds and their influence on the winter surface temperature in present-day climate in the CMIP3 multi-model dataset

We investigate the influence of clouds on the surface energy budget and surface temperature in the sea-ice covered parts of the ocean north of the Arctic circle in present-day climate in nine global climate models participating in the Coupled Model Intercomparison Project phase 3, CMIP3. Monthly mean simulated surface skin temperature, radiative fluxes and cloud parameters are evaluated using retrievals from the extended AVHHR Polar Pathfinder (APP-x) product. We analyzed the annual cycle but the main focus is on the winter, in which large parts of the region experience polar night. We find a smaller across-model spread as well as better agreement with observations during summer than during winter in the simulated climatological annual cycles of total cloudiness and surface skin temperature. The across-model spread in liquid and ice water paths is substantial during the whole year. These results qualitatively agree with earlier studies on the present-day Arctic climate in GCMs. The climatological ensemble model mean annual cycle of surface cloud forcing shows good agreement with observations in summer. However, during winter the insulating effect of clouds tends to be underestimated in models. During winter, most of the models as well as the observations show higher monthly mean total cloud fractions, associated with larger positive surface cloud forcing. Most models also show good correlation between the surface cloud forcing and the vertically integrated ice and liquid cloud condensate. The wintertime ensemble model mean total cloud fraction (69%) shows excellent agreement with observations. The across-model spread in the winter mean cloudiness is substantial (36?C94%) however and several models significantly underestimate the cloud liquid water content. If the two models not showing any relationship between cloudiness and surface cloud forcing are disregarded, a tentative across-model relation exists, in such a way that models that simulate large winter mean cloudiness also show larger surface cloud forcing. Even though the across-model spread in wintertime surface cloud forcing is large, no clear relation to the surface temperature is found. This indicates that other processes, not explicitly cloud related, are important for the simulated across-model spread in surface temperature.     

Sensitivity of simulated wintertime Arctic atmosphere to vertical resolution in the ARPEGE/IFS model

The current state-of-the-art general circulation models, including several of those used by the IPCC, show considerable biases in the simulated present day high-latitude climate compared to observations and reanalysis data. These biases are most pronounced during the winter season. We here employ ideal vertical profiles of temperature and wind from turbulence-resolving simulations to perform a priori studies of the first-order eddy-viscosity closure scheme employed in the ARPEGE/IFS model. This reveals that the coarse vertical resolution (31 layers) of the model cannot be expected to realistically resolve the Arctic stable boundary layer. The curvature of the Arctic inversion and thus also the vertical turbulent-exchange processes cannot be reproduced by the coarse vertical mesh employed. To investigate how turbulent vertical exchange processes in the Arctic boundary layer are represented by the model parameterization, a simulation with high vertical resolution (90 layers in total) in the lower troposphere is performed. Results from the model simulations are validated against data from the ERA-40 reanalysis. The dependence of the surface air temperature on surface winds, surface energy fluxes, free atmosphere stability and boundary layer height is investigated. The coarse-resolution run reveals considerable biases in these parameters, and in their physical relations to surface air temperature. In the simulation with fine vertical resolution, these biases are clearly reduced. The physical relation between governing parameters for the vertical turbulent-exchange processes improves in comparison with ERA-40 data.     

Arctic aerosol and Arctic climate: Results from an energy budget model

An energy budget model is used to study the effect on Arctic climate of optically active aerosol in the Arctic atmosphere. The dependence of the change in surface temperature on the vertical distribution of the aerosol and on the radiative properties of the aerosol-free atmosphere, the Arctic surface, and the aerosol, itself, are calculated. An extensive sensitivity analysis is performed to assess the degree to which the results of the model are dependent upon the assumptions underlying it.List of Symbols Used I ₀ Solar flux at the top of the Arctic Atmosphere (Arctic here means 70° N latitude to the pole) - a _S Surface albedo of the Arctic (a _S ^c is the value of surface albedo at which the sign of the surface temperature perturbation changes) - Reflection coefficient of the aerosol-free Arctic atmosphere - Absorption coefficient of the aerosol-free Arctic atmosphere - Transmission coefficient of the aerosol-free Arctic atmosphere - RI ₀ Total flux of sunlight reflected from the Arctic - A _A I ₀ Total flux of sunlight absorbed in the Arctic atmosphere - A _S I ₀ Total flux of sunlight absorbed at the Arctic surface - A _aer I ₀ Total flux of sunlight absorbed in the Arctic aerosol - Q _A Net atmospheric flow of energy, per unit of Arctic surface area, north across 70° N latitude - Q _S Net oceanic flow of energy, per unit of Arctic surface area, north across 70° N latitude - E Convective plus latent heat fluxes from surface to atmosphere - F _A Net flow of energy to the Arctic atmosphere - F _S Net flow of energy to the Arctic surface - T _A An effective temperature of the Arctic atmosphere - T _S Surface temperature of the Arctic - w Single-scattering albedo of the aerosol - t Optical depth of the aerosol - g Fraction of incident radiation scattered forward by the aerosol - Reflection coefficient of the aerosol - Absorption coefficient of the aerosol - Transmission coefficient of the aerosol - p,q Number of atmospheric layers and the inverse of the fraction of incident IR absorbed in each layer in the energy budget model - F,G,H Measures of the amount of IR-active atmosphere above the surface, the aerosol, and the clouds     

Estimation of urban heat island intensity using biases in surface air temperature simulated by a nonhydrostatic regional climate model

This study demonstrates that urban heat island (UHI) intensity can be estimated by comparing observational data and the outputs of a well-developed high-resolution regional climate model. Such an estimate is possible because the observations include the effects of UHI, whereas the model used does not include urban effects. Therefore, the errors in the simulated surface air temperature, defined as the difference between simulated and observed temperatures (simulated minus observed), are negative in urban areas but 0 in rural areas. UHI intensity is estimated by calculating the difference in temperature error between urban and rural areas. Our results indicate that overall UHI intensity in Japan is 1.5 K and that the intensity is greater in nighttime than in daytime, consistent with the previous studies. This study also shows that root mean square error and the magnitude of systematic error for the annual mean temperature are small (within 1.0 K).     

Boundary-layer modification in wintertime cold-air outbreaks from the Arctic sea ice

During the field experiment ARKTIS 1993 ten cases of boundary-layer modification in wintertime cold-air outbreaks from the Arctic sea ice in the Spitsbergen region were observed by aircraft over a distance ranging from about 50 km over the ice to about 300 km over the water. The modification depends decisively on the initial conditions over the ice, the boundary conditions at the bottom and top of the boundary layer and on the conditions of the large-scale flow. The modification of the bulk boundary-layer characteristics in relation to these conditions is presented.Besides the air-sea temperature contrast, the most important role for the boundary-layer modification is played by the stability on top of the boundary layer and by the divergence of the large-scale flow. According to the high variability of these conditions the observed boundary-layer modifications were very variable ranging from 100 to 300 m thick boundary layers with air temperatures between -32 and -22 °C over the ice to thicknesses between 900 and 2200 m and air temperatures between -15 and -5 °C after 300 km fetch over the open water. In most cases the large-scale flow was anticyclonic and divergent over the ice and changed to cyclonic and convergent over the water and an ice-sea breeze was superimposed on it.The sensible and latent heat fluxes are the dominant terms in the surface energy budget over the open water and ranged between 200 and 700 W m^-2 whereas the net longwave radiation is the dominating term over the ice with the heat fluxes only about 10 W m^-2.     

Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model

The relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for Arctic interannual climate variability has been estimated with the help of a regional Arctic coupled ocean-ice-atmosphere model. The study focuses on sea ice and surface climate during the 1980s and 1990s. Simulations agree reasonably well with observations. Correlations between the winter North Atlantic Oscillation index and the summer Arctic sea ice thickness and summer sea ice extent are found. Spread of sea ice extent within an ensemble of model runs can be associated with a surface pressure gradient between the Nordic Seas and the Kara Sea. Trends in the sea ice thickness field are widely significant and can formally be attributed to large scale forcing outside the Arctic model domain. Concerning predictability, results indicate that the variability generated by the external forcing is more important in most regions than the internally generated variability. However, both are in the same order of magnitude. Local areas such as the Northern Greenland coast together with Fram Straits and parts of the Greenland Sea show a strong importance of internally generated variability, which is associated with wind direction variability due to interaction with atmospheric dynamics on the Greenland ice sheet. High predictability of sea ice extent is supported by north-easterly winds from the Arctic Ocean to Scandinavia.     

Mechanisms of tropical precipitation biases in climate models

Climate Dynamics - We investigate the possible causes for inter-model spread in tropical zonal-mean precipitation pattern, which is divided into hemispherically symmetric and anti-symmetric modes...     

A Boolean delay equation model of an interdecadal Arctic climate cycle

A Boolean delay equation (BDE) model is presented for the interdecadal Arctic and Greenland Sea climate cycle recently proposed by Mysak, Manak and Marsden. It is shown that 15- to 20-year oscillations can occur in the model for a variety of time delays in the BDEs. However, both the period and structure of the oscillations are sensitive to the initial conditions. In an extended model, in which the convection in the Greenland Sea is dependent upon the ice conditions during each of several previous years as well as the current year, the solution structure is more realistic, with two jumps per period of oscillation.     

A simple model perturbed physics study of the simulated climate sensitivity uncertainty and its relation to control climate biases

In this study the relationship between climate model biases in the control climate and the simulated climate sensitivity are discussed on the basis of perturbed physics ensemble simulations with a globally resolved energy balance (GREB) model. It is illustrated that the uncertainties in the simulated climate sensitivity (estimated by the transient response to CO₂ forcing scenarios in the twenty first century or idealized 2 × CO₂ forcing experiments) can be conceptually split into two parts: a direct effect of the perturbed physics on the climate sensitivity independent of the control mean climate and an indirect effect of the perturbed physics by changing the control mean climate, which in turn changes the climate sensitivity, as the climate sensitivity itself is depending on the control climate. Biases in the control climate are negatively correlated with the climate sensitivity (colder climates have larger sensitivities), if no physics are perturbed. Perturbed physics that lead to warmer control climate, would in average also lead to larger climate sensitivities, if the control climate is held at the observed reference climate by flux corrections. Thus the effects of control biases and perturbed physics are opposing each other and are partially cancelling each other out. In the GREB model the biases in the control climate are the more important effect for the regional climate sensitivity uncertainties, but for the global mean climate sensitivity both, the biases in the control climate and the perturbed physics, are equally important.     

Implications of CMIP3 model biases and uncertainties for climate projections in the western tropical Pacific

Regional climate projections in the Pacific region are potentially sensitive to a range of existing model biases. This study examines the implications of coupled model biases on regional climate projections in the tropical western Pacific. Model biases appear in the simulation of the El Niño Southern Oscillation, the location and movement of the South Pacific Convergence Zone, rainfall patterns, and the mean state of the ocean–atmosphere system including the cold tongue bias and erroneous location of the edge of the Western Pacific warm pool. These biases are examined in the CMIP3 20th century climate models and used to provide some context to the uncertainty in interpretations of regional-scale climate projections for the 21st century. To demonstrate, we provide examples for two island nations that are located in different climate zones and so are affected by different biases: Nauru and Palau. We discuss some of the common approaches to analyze climate projections and whether they are effective in reducing the effect of model biases. These approaches include model selection, calculating multi model means, downscaling and bias correcting.     

Sensitivity of tropical climate to low-level clouds in the NCEP climate forecast system

In this work, we examine the sensitivity of tropical mean climate and seasonal cycle to low clouds and cloud liquid water path (CLWP) by prescribing them in the NCEP climate forecast system (CFS). It is found that the change of low cloud cover alone has a minor influence on the amount of net shortwave radiation reaching the surface and on the warm biases in the southeastern Atlantic. In experiments where CLWP is prescribed using observations, the mean climate in the tropics is improved significantly, implying that shortwave radiation absorption by CLWP is mainly responsible for reducing the excessive surface net shortwave radiation over the southern oceans in the CFS. Corresponding to large CLWP values in the southeastern oceans, the model generates large low cloud amounts. That results in a reduction of net shortwave radiation at the ocean surface and the warm biases in the sea surface temperature in the southeastern oceans. Meanwhile, the cold tongue and associated surface wind stress in the eastern oceans become stronger and more realistic. As a consequence of the overall improvement of the tropical mean climate, the seasonal cycle in the tropical Atlantic is also improved. Based on the results from these sensitivity experiments, we propose a model bias correction approach, in which CLWP is prescribed only in the southeastern Atlantic by using observed annual mean climatology of CLWP. It is shown that the warm biases in the southeastern Atlantic are largely eliminated, and the seasonal cycle in the tropical Atlantic Ocean is significantly improved. Prescribing CLWP in the CFS is then an effective interim technique to reduce model biases and to improve the simulation of seasonal cycle in the tropics.     

Identifying uncertainties in Arctic climate change projections

Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO₂ doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.     

Changes in Arctic clouds during intervals of rapid sea ice loss

We investigate the behavior of clouds during rapid sea ice loss events (RILEs) in the Arctic, as simulated by multiple ensemble projections of the 21st century in the Community Climate System Model (CCSM3). Trends in cloud properties and sea ice coverage during RILEs are compared with their secular trends between 2000 and 2049 during summer, autumn, and winter. The results suggest that clouds promote abrupt Arctic climate change during RILEs through increased (decreased) cloudiness in autumn (summer) relative to the changes over the first half of the 21st century. The trends in cloud characteristics (cloud amount, water content, and radiative forcing) during RILEs are most strongly and consistently an amplifying effect during autumn, the season in which RILEs account for the majority of the secular trends. The total cloud trends in every season are primarily due to low clouds, which show a more robust response than middle and high clouds across RILEs. Lead-lag correlations of monthly sea ice concentration and cloud cover during autumn reveal that the relationship between less ice and more clouds is enhanced during RILEs, but there is no evidence that either variable is leading the other. Given that Arctic cloud projections in CCSM3 are similar to those from other state-of-the-art GCMs and that observations show increased autumn cloudiness associated with the extreme 2007 and 2008 sea ice minima, this study suggests that the rapidly declining Arctic sea ice will be accentuated by changes in polar clouds.