A single-column model ensemble approach applied to the TWP-ICE experiment

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

Comparison of stochastic parametrization approaches in a single-column model

We discuss and test the potential usefulness of single-column models (SCMs) for the testing of stchastic physics schemes that have been proposed for use in general circulation models (GCMs). We argue that although single column tests cannot be definitive in exposing the full behaviour of a stochastic method in the full GCM, and although there are differences between SCM testing of deterministic and stochastic methods, nonetheless SCM testing remains a useful tool. It is necessary to consider an ensemble of SCM runs produced by the stochastic method. These can be usefully compared to deterministic ensembles describing initial condition uncertainty and also to combinations of these (with structural model changes) into poor man's ensembles. The proposed methodology is demonstrated using an SCM experiment recently developed by the GCSS community, simulating the transitions between active and suppressed periods of tropical convection.

Comparison of stochastic parameterisation approaches in a single-column model

We discuss and test the potential usefulness of single-column models (SCMs) for the testing of stochastic physics schemes that have been proposed for use in general circulation models (GCMs). We argue that although single column tests cannot be definitive in exposing the full behaviour of a stochastic method in the full GCM, and although there are differences between SCM testing of deterministic and stochastic methods, SCM testing remains a useful tool. It is necessary to consider an ensemble of SCM runs produced by the stochastic method. These can be usefully compared to deterministic ensembles describing initial condition uncertainty and also to combinations of these (with structural model changes) into poor man's ensembles. The proposed methodology is demonstrated using an SCM experiment recently developed by the GCSS (GEWEX Cloud System Study) community, simulating transitions between active and suppressed periods of tropical convection.

Modelling convective processes during the suppressed phase of the a Madden-Julian Oscillation: Comparing single-column models with cloud resolving models

The role of convective processes in moistening the atmosphere during suppressed periods of the suppressed phase of a Madden-Julian oscillation is investigated in cloud-resolving model (CRM) simulations, and the impact of moistening on the subsequent evolution of convection is assessed as part of a Global Energy and Water Cycle Experiment Cloud System Study (GCSS) intercomparison project. The ability of single-column model (SCM) versions of a number of state-of-the-art climate and numerical weather prediction models to capture these convective processes is also evaluated. During the suppressed periods, the CRMs are found to simulate a maximum moistening around 3 km, which is associated with a predominance of shallow convection. All SCMs produce adequate amounts of shallow convection during the suppressed periods, comparable to that seen in CRMs, but the relatively drier SCMs have higher precipitation rates than the relatively wetter SCMs and CRMs. The relatively drier SCMs dry, rather than moisten, the lower troposphere below the melting level. During the transition periods, convective processes act to moisten the atmosphere above the level at which mean advection changes from moistening to drying, despite an overall drying effect for the column. The SCMs capture some essence of this moistening at upper levels. A gradual transition from shallow to deep convection is simulated by the CRMs and the wetter SCMs during the transition periods, but the onset of deep convection is delayed in the drier SCMs. This results in lower precipitation rates for these SCMs during the active periods, although much better agreement exists between the models at this time.

Overview of observations from the RADAGAST experiment in Niamey, Niger: 2. Radiative fluxes and divergences

Broadband shortwave and longwave radiative fluxes observed both at the surface and from space during the Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA Stations (RADAGAST) experiment in Niamey, Niger, in 2006 are presented. The surface fluxes were measured by the Atmospheric Radiation Measurement (ARM) Program Mobile Facility (AMF) at Niamey airport, while the fluxes at the top of the atmosphere (TOA) are from the Geostationary Earth Radiation Budget (GERB) instrument on the Meteosat-8 satellite. The data are analyzed as daily averages, in order to minimize sampling differences between the surface and top of atmosphere instruments, while retaining the synoptic and seasonal changes that are the main focus of this study. A cloud mask is used to identify days with cloud versus those with predominantly clear skies. The influence of temperature, water vapor, aerosols, and clouds is investigated. Aerosols are ubiquitous throughout the year and have a significant impact on both the shortwave and longwave fluxes. The large and systematic seasonal changes in temperature and column integrated water vapor (CWV) through the dry and wet seasons are found to exert strong influences on the longwave fluxes. These influences are often in opposition to each other, because the highest temperatures occur at the end of the dry season when the CWV is lowest, while in the wet season the lowest temperatures are associated with the highest values of CWV. Apart from aerosols, the shortwave fluxes are also affected by clouds and by the seasonal changes in CWV. The fluxes are combined to provide estimates of the divergence of radiation across the atmosphere throughout 2006. The longwave divergence shows a relatively small variation through the year, because of a partial compensation between the seasonal variations in the outgoing longwave radiation (OLR) and surface net longwave radiation. A simple model of the greenhouse effect is used to interpret this result in terms of the dependence of the normalized greenhouse effect at the TOA and of the effective emissivity of the atmosphere at the surface on the CWV. It is shown that, as the CWV increases, the atmosphere loses longwave energy to the surface with about the same increasing efficiency with which it traps the OLR. When combined with the changes in temperature, this maintains the atmospheric longwave divergence within the narrow range that is observed. The shortwave divergence is mainly determined by the CWV and aerosol loadings and the effect of clouds is much smaller than on the component fluxes.

A GCSS model intercomparison for a tropical squall line observed during toga-coare. II: Intercomparison of single-column models and a cloud-resolving model

This paper presents single-column model (SCM) simulations of a tropical squall-line case observed during the Coupled Ocean-Atmosphere Response Experiment of the Tropical Ocean/Global Atmosphere Programme. This case-study was part of an international model intercomparison project organized by Working Group 4 ‘Precipitating Convective Cloud Systems’ of the GEWEX (Global Energy and Water-cycle Experiment) Cloud System Study. Eight SCM groups using different deep-convection parametrizations participated in this project. The SCMs were forced by temperature and moisture tendencies that had been computed from a reference cloud-resolving model (CRM) simulation using open boundary conditions. The comparison of the SCM results with the reference CRM simulation provided insight into the ability of current convection and cloud schemes to represent organized convection. The CRM results enabled a detailed evaluation of the SCMs in terms of the thermodynamic structure and the convective mass flux of the system, the latter being closely related to the surface convective precipitation. It is shown that the SCMs could reproduce reasonably well the time evolution of the surface convective and stratiform precipitation, the convective mass flux, and the thermodynamic structure of the squall-line system. The thermodynamic structure simulated by the SCMs depended on how the models partitioned the precipitation between convective and stratiform. However, structural differences persisted in the thermodynamic profiles simulated by the SCMs and the CRM. These differences could be attributed to the fact that the total mass flux used to compute the SCM forcing differed from the convective mass flux. The SCMs could not adequately represent these organized mesoscale circulations and the microphysicallradiative forcing associated with the stratiform region. This issue is generally known as the ‘scale-interaction’ problem that can only be properly addressed in fully three-dimensional simulations. Sensitivity simulations run by several groups showed that the time evolution of the surface convective precipitation was considerably smoothed when the convective closure was based on convective available potential energy instead of moisture convergence. Finally, additional SCM simulations without using a convection parametrization indicated that the impact of a convection parametrization in forced SCM runs was more visible in the moisture profiles than in the temperature profiles because convective transport was particularly important in the moisture budget.

Establishing Lagrangian connections between observations within air masses crossing the Atlantic during the International Consortium for Atmospheric Research on Transport and Transformation experiment

The ITCT-Lagrangian-2K4 (Intercontinental Transport and Chemical Transformation) experiment was conceived with an aim to quantify the effects of photochemistry and mixing on the transformation of air masses in the free troposphere away from emissions. To this end, attempts were made to intercept and sample air masses several times during their journey across the North Atlantic using four aircraft based in New Hampshire (USA), Faial (Azores) and Creil (France). This article begins by describing forecasts from two Lagrangian models that were used to direct the aircraft into target air masses. A novel technique then identifies Lagrangian matches between flight segments. Two independent searches are conducted: for Lagrangian model matches and for pairs of whole air samples with matching hydrocarbon fingerprints. The information is filtered further by searching for matching hydrocarbon samples that are linked by matching trajectories. The quality of these "coincident matches'' is assessed using temperature, humidity and tracer observations. The technique pulls out five clear Lagrangian cases covering a variety of situations and these are examined in detail. The matching trajectories and hydrocarbon fingerprints are shown, and the downwind minus upwind differences in tracers are discussed.

An observing system simulation experiment for climate monitoring with GNSS radio occulation data: setup and testbed study

The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

Seasonal variations of the physical and optical characteristics of Saharan Dust: results from the Dust outflow and Deposition to the Ocean (DODO) experiment

North African dust is important for climate through its direct radiative effect on solar and terrestrial radiation and its role in the biogeochemical system. The Dust Outflow and Deposition to the Ocean project (DODO) aimed to characterize the physical and optical properties of airborne North African dust in two seasons and to use these observations to constrain model simulations, with the ultimate aim of being able to quantify the deposition of iron to the North Atlantic Ocean. The in situ properties of dust from airborne campaigns measured during February and August 2006, based at Dakar, Senegal, are presented here. Average values of the single scattering albedo (0.99, 0.98), mass specific extinction (0.85 m^2 g^-1 , 1.14 m^2 g^-1 ), asymmetry parameter (0.68, 0.68), and refractive index (1.53--0.0005i,1.53--0.0014i) for the accumulation mode were found to differ by varying degrees between the dry and wet season, respectively. It is hypothesized that these differences are due to different source regions and transport processes which also differ between the DODO campaigns. Elemental ratios of Ca/Al were found to differ between the dry and wet season (1.1 and 0.5, respectively). Differences in vertical profiles are found between seasons and between land and ocean locations and reflect the different dynamics of the seasons. Using measurements of the coarse mode size distribution and illustrative Mie calculations, the optical properties are found to be very sensitive to the presence and amount of coarse mode of mineral dust, and the importance of accurate measurements of the coarse mode of dust is highlighted.