Sensitivity of radiative flux simulations to ice cloud parameterization over the equatorial western Pacific Ocean region

Previous studies suggest explanations of the observed cancellation of shortwave (SW) and longwave (LW) cloud radiative effects (CREs) at the top of the atmosphere (TOA) over tropical oceans where deep convection prevails, such as interactions among cloud microphysics, radiation, and dynamics. However, simulations based on general circulation models (GCMs) show disagreement in terms of the net (SW + LW) CREs over tropical deep convective ocean regions. One of the GCM uncertainty sources is the parameterization of ice cloud bulk optical properties. In this study, a combination of active and passive satellite daytime cloud retrievals is used to study the sensitivity of radiation flux calculations to ice cloud parameterization over the equatorial western Pacific Ocean region. Three ice cloud schemes are tested. The first is a widely used scheme that assumes hexagonal column ice particles. The second scheme treats ice particles as aggregates of surface-roughened hexagonal columns. The third scheme best matches the cloud ice mass-dimension relation in the cloud microphysics scheme by assuming a mixture of two ice particle habits. The results show that the hexagonal-column-based scheme has the weakest SW CRE but strongest LW CRE among the three. In addition, cloud optical thickness and effective radius are used to cluster cold-top single-layer ice clouds into three types, which resemble thin cirrus, detrained anvil clouds, and deep convective cores, respectively. In agreement with previous studies, cloud SW heating overwhelms LW cooling in the upper portion of anvil-like clouds.

Uncertainty quantification based cloud parameterization sensitivity analysis in the NCAR community atmosphere model

Using uncertainty quantification techniques, we carry out a sensitivity analysis of a large number (17) of parameters used in the NCAR CAM5 cloud parameterization schemes. The LLNL PSUADE software is used to identify the most sensitive parameters by performing sensitivity analysis. Using Morris One-At-a-Time (MOAT) method, we find that the simulations of global annual mean total precipitation, convective, large-scale precipitation, cloud fractions (total, low, mid, and high), shortwave cloud forcing, longwave cloud forcing, sensible heat flux, and latent heat flux are very sensitive to the threshold-relative-humidity-for-stratiform-low-clouds ($$rhminl)$$ r h m i n l ) and the auto-conversion-size-threshold-for-ice-to-snow $$\left( {dcs} \right).$$ dcs . The seasonal and regime specific dependence of some parameters in the simulation of precipitation is also found for the global monsoons and storm track regions. Through sensitivity analysis, we find that the Somali jet strength and the tropical easterly jet associated with the south Asian summer monsoon (SASM) show a systematic dependence on $$dcs$$ dcs and $$rhminl$$ rhminl . The timing of the withdrawal of SASM over India shows a monotonic increase (delayed withdrawal) with an increase in $$dcs$$ dcs . Overall, we find that $$rhminl$$ rhminl , $$dcs$$ dcs , $$ai,$$ a i , and $$as$$ as are the most sensitive cloud parameters and thus are of high priority in the model tuning process, in order to reduce uncertainty in the simulation of past, present, and future climate.

Evaluation of the Diurnal Variation of Upper Tropospheric Humidity in Reanalysis Using Homogenized Observed Radiances from International Geostationary Weather Satellites

A near global dataset of homogenized clear-sky 6.5-μm brightness temperatures (BTs) from international geostationary (GEO) weather satellites has recently been generated and validated. In this study, these radiance measurements are used to construct the diurnal variation of upper tropospheric humidity (UTH) and to evaluate these diurnal variations simulated by five reanalysis datasets over the 45° N–45° S region. The features of the diurnal variation described by the new dataset are comparable with previous observational studies that a land–sea contrast in the diurnal variation of UTH is exhibited. Distinct diurnal variations are observed over the deep convective regions where high UTH exists. The evaluation of reanalysis datasets indicates that reanalysis systems still have considerable difficulties in capturing the observed features of the diurnal variation of UTH. All five reanalysis datasets present the largest wet biases in the afternoon when the observed UTH experiences a diurnal minimum. Reanalysis can roughly reproduce the day–night contrast of UTH but with much weaker amplitudes and later peak time over both land and ocean. Comparison of the geographical distribution of the diurnal variation shows that both ERA5 and MERRA-2 could capture the larger diurnal variations over convective regions. However, the diurnal amplitudes are widely underestimated, especially over convective land regions, while the phase biases are relatively larger over open oceans. These results suggest that some deficiencies may exist in convection and cloud parameterization schemes in reanalysis models.

Extratropical Cyclone Clouds in the GFDL Climate Model: Diagnosing Biases and the Associated Causes

The clouds in Southern Hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat, and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of “AM4,” a model GFDL that will utilize for CMIP6, and the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low levels (again by differing amounts), especially in the post–cold frontal (PCF) region, when compared with observations. In focusing only on the models, it is seen that their differences in high and midlevel clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud-parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting that other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach

Satellite observations are used to obtain vertical profiles of variance scaling of temperature (T) and specific humidity (q) in the atmosphere. A higher spatial resolution nadir retrieval at 13.5 km complements previous Atmospheric Infrared Sounder (AIRS) investigations with 45 km resolution retrievals and enables the derivation of power law scaling exponents to length scales as small as 55 km. We introduce a variable-sized circular-area Monte Carlo methodology to compute exponents instantaneously within the swath of AIRS that yields additional insight into scaling behavior. While this method is approximate and some biases are likely to exist within non-Gaussian portions of the satellite observational swaths of T and q, this method enables the estimation of scale-dependent behavior within instantaneous swaths for individual tropical and extratropical systems of interest. Scaling exponents are shown to fluctuate between β=-1 and −3 at scales ≥500 km, while at scales ≤500 km they are typically near β≈-2, with q slightly lower than T at the smallest scales observed. In the extratropics, the large-scale β is near −3. Within the tropics, however, the large-scale β for T is closer to −1 as small-scale moist convective processes dominate. In the tropics, q exhibits large-scale β between −2 and −3. The values of β are generally consistent with previous works of either time-averaged spatial variance estimates, or aircraft observations that require averaging over numerous flight observational segments. The instantaneous variance scaling methodology is relevant for cloud parameterization development and the assessment of time variability of scaling exponents.

On the Importance of a Consistent Treatment of Prognostic Moisture Variables between Convective and Microphysical Parameterizations

Analysis of WRF Model output from experiments using two double-moment microphysics schemes is carried out to demonstrate that there can be an inconsistency between the predicted mass and number concentrations when a single-moment convective parameterization is used together with a double-moment microphysics scheme. This inconsistency may arise because the grid-scale and subgrid-scale cloud schemes generally apply different levels of complexity to the parameterized microphysical processes. In particular, when a multimoment formulation is used in the microphysics scheme and other physical parameterizations modify only the mass-related moment while the values of the second (or higher) moment for individual hydrometeors remain unchanged, an unintended modification of the particle size distribution occurs. Simulated radar reflectivity is shown to be a valuable tool in diagnosing this inconsistency. In addition, potential ways to minimize the problem are explored by including number concentration calculations in the cumulus parameterization that are consistent with the assumptions of hydrometeor sizes in the microphysics parameterization. The results of this study indicate that it is physically preferable to unify microphysical assumptions between the grid-resolved and subgrid cloud parameterization schemes in weather and climate simulation models.

The path to CAM6: coupled simulations with CAM5.4 and CAM5.5

This paper documents coupled simulations of two developmental versions of the Community Atmosphere Model (CAM) towards CAM6. The configuration called CAM5.4 introduces new microphysics, aerosol, and ice nucleation changes, among others to CAM. The CAM5.5 configuration represents a more radical departure, as it uses an assumed probability density function (PDF)-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics in CAM. This assumed PDF method has been widely used in the last decade in atmosphere-only climate simulations but has never been documented in coupled mode. Here, we compare the simulated coupled climates of CAM5.4 and CAM5.5 and compare them to the control coupled simulation produced by CAM5.3. We find that CAM5.5 has lower cloud forcing biases when compared to the control simulations. Improvements are also seen in the simulated amplitude of the Niño-3.4 index, an improved representation of the diurnal cycle of precipitation, subtropical surface wind stresses, and double Intertropical Convergence Zone biases. Degradations are seen in Amazon precipitation as well as slightly colder sea surface temperatures and thinner Arctic sea ice. Simulation of the 20th century results in a credible simulation that ends slightly colder than the control coupled simulation. The authors find this is due to aerosol indirect effects that are slightly stronger in the new version of the model and propose a solution to ameliorate this. Overall, in these early coupled simulations, CAM5.5 produces a credible climate that is appropriate for science applications and is ready for integration into the National Center for Atmospheric Research's (NCAR's) next-generation climate model.

The Path to CAM6: Coupled Simulations with CAM5.4 and CAM5.5

This paper documents coupled simulations of two developmental versions of the Community Atmosphere Model (CAM) towards CAM6. The configuration called CAM5.4 introduces new microphysics, aerosol, and ice nucleation changes, among others to CAM. The CAM5.5 configuration represents a more radical departure as it uses an assumed PDF-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics in CAM. This assumed PDF method has been widely used in the last decade in atmosphere-only climate simulations, but has never been documented in coupled mode. Here we compare the simulated coupled climates of CAM5.4 and CAM5.5 and compare them to the control coupled simulation produced by CAM5.3. We find that CAM5.5 has lower cloud forcing biases when compared to the control simulations. Improvements are also seen in the simulated amplitude of the El Niño 3.4 index, an improved representation of the diurnal cycle of precipitation, sub-tropical surface wind stresses, and double Intertropical Convergence zone biases. Degradations are seen in Amazon precipitation as well as slightly colder sea surface temperatures and thinner Arctic Sea Ice. Simulation of the 20th century results in a credible simulation that ends slightly colder than the control coupled simulation. The authors find this is due to aerosol indirect effects that are slightly stronger in the new version of the model and propose a solution to ameliorate this. Overall, in these relatively untuned coupled simulations, CAM5.5 produces a credible climate that is appropriate for science applications and is ready for integration into the National Center for Atmospheric Research's (NCAR's) next generation climate model.