Tsuyoshi Koshiro

Origins of the solar radiation biases over the Southern Ocean in CFMIP2 models

AbstractCurrent climate models generally reflect too little solar radiation over the Southern Ocean, which may be the leading cause of the prevalent sea surface temperature biases in climate models. The authors study the role of clouds on the radiation biases in atmosphere-only simulations of the Cloud Feedback Model Intercomparison Project phase 2 (CFMIP2), as clouds have a leading role in controlling the solar radiation absorbed at those latitudes. The authors composite daily data around cyclone centers in the latitude band between 40° and 70°S during the summer. They use cloud property estimates from satellite to classify clouds into different regimes, which allow them to relate the cloud regimes and their associated radiative biases to the meteorological conditions in which they occur. The cloud regimes are defined using cloud properties retrieved using passive sensors and may suffer from the errors associated with this type of retrievals. The authors use information from the Cloud–Aerosol Lidar and I...

The impact of parametrized convection on cloud feedback.

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.

Evaluating the diurnal cycle of upper-tropospheric ice clouds in climate models using SMILES observations

AbstractUpper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S–40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by −4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both lan...

Evaluation of the Warm Rain Formation Process in Global Models with Satellite Observations

AbstractThis study examines the warm rain formation process over the global ocean in global climate models. Methodologies developed to analyze CloudSat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations are employed to investigate the cloud-to-precipitation process of warm clouds and are applied to the model results to examine how the models represent the process for warm stratiform clouds. Despite a limitation of the present study that compares the statistics for stratiform clouds in climate models with those from satellite observations, including both stratiform and (shallow) convective clouds, the statistics constructed with the methodologies are compared between the models and satellite observations to expose their similarities and differences. A problem common to some models is that they tend to produce rain at a faster rate than is observed. These model characteristics are further examined in the context of cloud microphysics parameterizations using a simplified one-dim...

Robustness, uncertainties, and emergent constraints in the radiative responses of stratocumulus cloud regimes to future warming

Future responses of cloud regimes are analyzed for five CMIP5 models forced with observed SSTs and subject to a patterned SST perturbation. Correlations between cloud properties in the control climate and changes in the warmer climate are investigated for each of a set of cloud regimes defined using a clustering methodology. The only significant (negative) correlation found is in the in-regime net cloud radiative effect for the stratocumulus regime. All models overestimate the in-regime albedo of the stratocumulus regime. Reasons for this bias and its relevance to the future response are investigated. A detailed evaluation of the models’ daily-mean contributions to the albedo from stratocumulus clouds with different cloud cover fractions reveals that all models systematically underestimate the relative occurrence of overcast cases but overestimate those of broken clouds. In the warmer climate the relative occurrence of overcast cases tends to decrease while that of broken clouds increases. This suggests a decrease in the climatological in-regime albedo with increasing temperature (a positive feedback); this is opposite to the feedback suggested by the analysis of the bulk in-regime albedo. Furthermore we find that the inter-model difference in the sign of the in-cloud albedo feedback is consistent with the difference in sign of the in-cloud liquid water path response, and there is a strong positive correlation between the in-regime liquid water path in the control climate and its response to warming. We therefore conclude that further breakdown of the in-regime properties into cloud cover and in-cloud properties is necessary to better understand the behavior of the stratocumulus regime. Since cloud water is a physical property and is independent of a model’s radiative assumptions, it could potentially provide a useful emergent constraint on cloud feedback.

Interpretation of Factors Controlling Low Cloud Cover and Low Cloud Feedback Using a Unified Predictive Index

AbstractThis paper reports a new index for low cloud cover (LCC), the Estimated Cloud-Top Entrainment Index (ECTEI), which is a modification of estimated inversion strength (EIS) and takes into account a cloud top entrainment (CTE) criterion. Shipboard cloud observation data confirm that the index is strongly correlated with LCC. We argue here that changes in LCC cannot be fully determined from changes in EIS only, but can be better determined from changes in both EIS and sea surface temperature (SST) based on the ECTEI. Furthermore, we argue that various proposed predictors of LCC change, including the moist static energy vertical gradient, SST, and mid-level clouds, can be better understood from the perspective of the ECTEI.

A multi-model study on warm precipitation biases in global models compared to satellite observations

The cloud-to-precipitation transition process in warm clouds simulated by state-of-the-art global climate models (GCMs), including both traditional climate models and a high-resolution model, is evaluated against A-Train satellites observations. The models and satellite observations are compared in the form of the statistics obtained from combined analysis of multiple satellite observables that probe signatures of the cloud-to-precipitation transition process. One common problem identified among these models is the too frequent occurrence of warm precipitation. The precipitation is found to form when the cloud particle size and the liquid water path (LWP) are both much smaller than those in observations. The too efficient formation of precipitation is found to be compensated for by errors of cloud microphysical properties, such as underestimated cloud particle size and LWP, to an extent that varies among the models. However, this does not completely cancel the precipitation formation bias. Robust errors are also found in the evolution of cloud microphysical properties from non-precipitating to drizzling and then to raining clouds in some GCMs, implying unrealistic interaction between precipitation and cloud water. Nevertheless, auspicious information is found for future improvement of warm precipitation representations: the adoption of more realistic autoconversion scheme in the high-resolution model improves the triggering of precipitation, and the introduction of a sophisticated subgrid variability scheme in a traditional model improves the simulated precipitation frequency over subtropical eastern ocean. However, deterioration in other warm precipitation characteristics is also found accompanying these improvements, implying the multi-source nature of warm precipitation biases in GCMs.

Interannual Variability in Low Stratiform Cloud Amount over the Summertime North Pacific in Terms of Cloud Types

AbstractUsing long-term (1958–2008) ship-based cloud observations and reanalysis data, interannual variability in the low stratiform cloud (LSC) amount of stratocumulus (Sc), stratus (St), and sky-obscuring fog (FOG) is examined over the summertime North Pacific. The correlation between the LSC amount and the estimated inversion strength is positive but relatively weak, compared with the well-known linear relationship for their seasonal variabilities. This reflects the regional contrast: the correlations are stronger in the southeastern North Pacific (SE NP) and weaker in the northwestern North Pacific (NW NP). Regarding the LSC types, variations in Sc amount are large over the SE NP and correlated with the inferred capping inversion strength. Variations in FOG amount are large over the NW NP and correlated with the inferred surface-based inversion strength. The compensating variations between the Sc and FOG amounts result in an apparent small variation in the total LSC amount in this region. Variations i...

Stratomesospheric CO measured by a ground- based Fourier transform spectrometer over Poker Flat, Alaska: Comparisons with Odin/SMR and a 2-D model

The interseasonal variability of stratomesospheric CO is reported from Poker Flat, Alaska, using spectra from a ground-based Fourier Transform Spectrometer (gb-FTS) for the time period from 2000 to 2004. The CO spectra were analyzed using an optimal estimation technique that separates the tropospheric and stratospheric/mesospheric components into partial columns. The distribution of CO in the polar winter is such that the gb-FTS retrieved partial column is weighted to the mesosphere. The gb-FTS data are compared with measurements of partial column CO from the Sub-Millimeter Radiometer on board the Odin satellite and shown to be in very good agreement despite the relatively small sample size. The mean difference of the two data sets indicates a small positive bias (7.6 ± 6%) in favor of the Odin data, with a correlation coefficient, r2 = 0.91. The gb-FTS data indicate that there is a strong seasonal dependence of the CO partial column that is consistent with known winter polar thermospheric descent of CO enriched air. Year-to-year variability is explained in terms of mesospheric wind dynamics, which show 2004 and components of 2002 were affected by earlier than expected breakdown (30 ± 13 d) of the winter polar circulation compared with 2000 to 2003. Finally, the measured CO data is compared with a 2-D chemical transport model that gives support to the idea that springtime polar mesospheric CO is driven by meridional winds.