ALBERT

Description: A statistical study is presented of the errors in sodium Doppler lidar measurements of wind and temperature in the mesosphere that arise from the statistics of the photon-counting process that is inherent in the technique. The authors use data from the Colorado State University (CSU) sodium Doppler wind-temperature lidar, acquired at a midlatitude site, to define the statistics of the lidar measurements in different seasons under both daytime and nighttime conditions. The CSU lidar measurements are scaled, based on a 35-cm-diameter receiver telescope, to the use of large-aperture telescopes (i.e., 1-, 1.8-, and 3.5-m diameters). The expected biases in vertical heat flux measurements at a resolution of 480 m and 150 s are determined and compared to Gardner and Yang’s reported geophysical values of 2.3 K m s−1. A cross-correlation coefficient of 2%–7% between the lidar wind and temperature estimates is found. It is also found that the biases vary from −4 × 10−3 K m s−1 for wintertime measurements at night with a 3.5-m telescope to −61 K m s−1 for summertime measurements at midday with a 1-m telescope. During winter, at night, the three telescope systems yield biases in their heat flux measurements that are less than 10% of the reported value of the heat flux; and during summer, at night, the 1.8- and 3.5-m systems yield biases in their heat flux measurements that are less than 10% of the geophysical value. While during winter at midday the 3.5-m system yields biases in their heat flux measurements that are less than 10% of the geophysical value, during summer at midday all of the systems yield flux biases that are greater than the geophysical value of the heat flux. The results are discussed in terms of current lidar measurements and proposed measurements at high-latitude sites.

Description: A global TRMM database of tropical cloud system precipitation features (PFs), which provides useful observational constraints on cloud system properties, is used to evaluate the bulk microphysics schemes in a cloud-resolving model (CRM). The simulation of the Mesoscale Convective System (MCS) of 11–12 August 1999 during the Kwajalein Experiment (KWAJEX) is executed using the 3D University of Utah CRM, which employs a one-moment bulk, three-ice category microphysical parameterization. The simulated precipitation features are compared with climatological “norms” for Kwajalein locations from the TRMM PF database to evaluate the precipitation microphysics of the cloud model simulation. The model-simulated reflectivities are also compared with vertical profiles of radar reflectivity obtained from a ground-based precipitation radar. Comparison of simulation results with the TRMM observation statistics indicates that the model tends to underestimate microwave brightness temperatures at ice-scattering frequencies and overestimate radar reflectivities, especially for those associated with larger ice particles. The differences between the statistics of KWAJEX simulation and available ground-based precipitation radar observations are relatively small at the levels below 5 km. Above 6 km, the differences increase with height and reach a maximum near 9 km. The simulated radar reflectivities are statistically 5–13 dBZ higher than those from radar observations at levels between 7 and 10.5 km, where graupel is the dominant simulated ice species. The largest graupel mixing ratios, as high as 8 g kg−1, are the most likely reason for the unrealistically high simulated radar reflectivity. Comparison of model-simulated graupel mixing ratio with available microphysics data from the Citation aircraft indicates that the model overestimates graupel content at the level the Citation flew (about 6.4 km).

Description: This study describes and demonstrates a new method for identifying deficiencies in how cloud processes are represented in large-scale models. Kilometer-scale-resolving cloud radar observations and cloud-resolving model (CRM) simulations were used to evaluate the representation of cirrus clouds in the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model for a 29-day period during June and July 1997 at the Atmospheric Radiation Measurement Program site in Oklahoma. To produce kilometer-scale cirrus statistics from the SCM results, synthetic subgrid-scale (SGS) cloud fields were generated using the SCM’s cloud fraction and hydrometeor content profiles, and the SCM’s cloud overlap and horizontal inhomogeneity assumptions. Three sets of SCM synthetic SGS cloud fields were analyzed. Two NOSNOW sets were produced in which clouds did not include snow; one set used random overlap, the other, maximum/random. In the SNOW set, clouds included snow and random overlap was used. The three sets were sampled in the same way as the cloud-radar-detected cloud fields and the CRM-simulated cloud fields. The mean cirrus cloud occurrence frequency for the SCM NOSNOW cloud fields agrees with the observed value as well as the CRM’s does, while that for SCM SNOW cloud fields is only half that observed. In most aspects, the SCM’s cirrus properties differ significantly from the cloud radar’s and the CRM’s, which generally agree. In comparison, there are too many physically thin SCM NOSNOW cirrus layers (most occupy only a single model layer) and too many physically thick SCM SNOW cirrus layers (most are thicker than 4 km). For the optically thin subset of cirrus layers, 1) the mean, mode, and median ice water path, and layer-mean ice water content (IWC) values for the SCM are significantly larger than the observed and CRM values; 2) the SCM layer-mean IWCs decrease with cloud physical thickness, opposite to the observations and CRM results; and 3) the range of layer-mean effective radii in the SCM thin cirrus is too narrow.

Description: This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement Program and output from the University of California, Los Angeles/Colorado State University cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties analyzed by applying the SCM’s assumptions about cloud vertical overlap and horizontal homogeneity to its profiles of cloud water/ice mixing ratio, cloud fraction, and snow flux differed from the cloud radar observations while the CRM simulation reproduced most of the observed cirrus properties. The present study evaluates, through a comparison with the CRM, the SCM’s representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. This study finds that, although the SCM’s detrainment rate profile averaged over the entire simulation period is comparable to the CRM’s, detrainment in the SCM is comparatively sporadic and vertically localized. Too much detrained ice is sublimated when first detrained. Snow formed from detrained cloud ice falls through too deep of a layer. These aspects of the SCM’s parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM), and suggest several possible improvements for the SCM: 1) allowing multiple coexisting cumulus cloud types as in the original Arakawa–Schubert scheme, 2) prognostically determining the stratiform cloud fraction, and 3) explicitly predicting the snow mixing ratio. These would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow flux.

Description: A strong midwinter warming occurred in the Southern Hemisphere (SH) stratosphere in September 2002. Based on experiences from the Northern Hemisphere (NH), this event can be defined as a major warming with a breakdown of the polar vortex in midwinter, which has never been detected so far in the SH since observations began at the earliest in the 1940s. Minor midwinter warmings occasionally occurred in the SH, but a strong interannual variability, as is present in winter and spring in the NH, has been explicitly associated with the spring reversals. A detailed analysis of this winter reveals the dominant role of eastward-traveling waves and their interaction with quasi-stationary planetary waves forced in the troposphere. Such wave forcing, finally leading to the sudden breakdown of the vortex, is a familiar feature of the northern winter stratosphere. Therefore, the unusual development of this Antarctic winter is described in the context of more than 50 Arctic winters, concentrating on winters with similar wave perturbations. The relevance of preconditioning of major warmings by traveling and quasi-stationary planetary waves is discussed for both hemispheres.

Description: Several meteorological datasets, including U.K. Met Office (MetO), European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and NASA’s Goddard Earth Observation System (GEOS-4) analyses, are being used in studies of the 2002 Southern Hemisphere (SH) stratospheric winter and Antarctic major warming. Diagnostics are compared to assess how these studies may be affected by the meteorological data used. While the overall structure and evolution of temperatures, winds, and wave diagnostics in the different analyses provide a consistent picture of the large-scale dynamics of the SH 2002 winter, several significant differences may affect detailed studies. The NCEP–NCAR reanalysis (REAN) and NCEP–Department of Energy (DOE) reanalysis-2 (REAN-2) datasets are not recommended for detailed studies, especially those related to polar processing, because of lower-stratospheric temperature biases that result in underestimates of polar processing potential, and because their winds and wave diagnostics show increasing differences from other analyses between ∼30 and 10 hPa (their top level). Southern Hemisphere polar stratospheric temperatures in the ECMWF 40-Yr Re-analysis (ERA-40) show unrealistic vertical structure, so this long-term reanalysis is also unsuited for quantitative studies. The NCEP/Climate Prediction Center (CPC) objective analyses give an inferior representation of the upper-stratospheric vortex. Polar vortex transport barriers are similar in all analyses, but there is large variation in the amount, patterns, and timing of mixing, even among the operational assimilated datasets (ECMWF, MetO, and GEOS-4). The higher-resolution GEOS-4 and ECMWF assimilations provide significantly better representation of filamentation and small-scale structure than the other analyses, even when fields gridded at reduced resolution are studied. The choice of which analysis to use is most critical for detailed transport studies (including polar process modeling) and studies involving synoptic evolution in the upper stratosphere. The operational assimilated datasets are better suited for most applications than the NCEP/CPC objective analyses and the reanalysis datasets (REAN/REAN-2 and ERA-40).

Description: Cloud water sedimentation and drizzle in a stratocumulus-topped boundary layer are the focus of an intercomparison of large-eddy simulations. The context is an idealized case study of nocturnal stratocumulus under a dry inversion, with embedded pockets of heavily drizzling open cellular convection. Results from 11 groups are used. Two models resolve the size distributions of cloud particles, and the others parameterize cloud water sedimentation and drizzle. For the ensemble of simulations with drizzle and cloud water sedimentation, the mean liquid water path (LWP) is remarkably steady and consistent with the measurements, the mean entrainment rate is at the low end of the measured range, and the ensemble-average maximum vertical wind variance is roughly half that measured. On average, precipitation at the surface and at cloud base is smaller, and the rate of precipitation evaporation greater, than measured. Including drizzle in the simulations reduces convective intensity, increases boundary layer stratification, and decreases LWP for nearly all models. Including cloud water sedimentation substantially decreases entrainment, decreases convective intensity, and increases LWP for most models. In nearly all cases, LWP responds more strongly to cloud water sedimentation than to drizzle. The omission of cloud water sedimentation in simulations is strongly discouraged, regardless of whether or not precipitation is present below cloud base.

Description: This study evaluates the performance of the National Centers for Environmental Prediction Global Forecast System (GFS) against observations made by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program at the southern Great Plains site for the years 2001–04. The spatial and temporal scales of the observations are examined to search for an optimum approach for comparing grid-mean model forecasts with single-point observations. A single-column model (SCM) based upon the GFS was also used to aid in understanding certain forecast errors. The investigation is focused on the surface energy fluxes and clouds. Results show that the overall performance of the GFS model has been improving, although certain forecast errors remain. The model overestimated the daily maximum latent heat flux by 76 W m−2 and the daily maximum surface downward solar flux by 44 W m−2, and underestimated the daily maximum sensible heat flux by 44 W m−2. The model’s surface energy balance was reached by a cancellation of errors. For clouds, the GFS was able to capture the observed evolutions of cloud systems during major synoptic events. However, on average, the model largely underestimated cloud fraction in the lower and midtroposphere, especially for daytime nonprecipitating low clouds because shallow convection in the GFS does not produce clouds. Analyses of surface radiative fluxes revealed that the diurnal cycle of the model’s surface downward longwave flux (SDLW) was not in phase with that of the ARM-observed SDLW. SCM experiments showed that this error was caused by an inaccurate scaling factor, which was a function of ground skin temperature and was used to adjust the SDLW at each model time step to that computed by the model’s longwave radiative transfer routine once every 3 h. A method has been proposed to correct this error in the operational forecast model. It was also noticed that the SDLW biases changed from mostly negative in 2003 to slightly positive in 2004. This change was traced back to errors in the near-surface air temperature. In addition, the SDLW simulated with the newly implemented Rapid Radiative Transfer Model longwave routine in the GFS is usually 5–10 W m−2 larger than that simulated with the previous routine. The forecasts of surface downward shortwave flux (SDSW) were relatively accurate under clear-sky conditions. The errors in SDSW were primarily caused by inaccurate forecasts of cloud properties. Results from this study can be used as guidance for the further development of the GFS.

Description: Data collected in situ as part of the second field study of the Dynamics and Chemistry of Marine Stratocumulus field program are used to evaluate the state of the atmosphere in the region of field operations near 30°N, 120°W during July 2001, as well as its representation by a variety of routinely available data. The routine data include both the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and NCEP–NCAR reanalyses, forecasts from their respective forecast systems (the Integrated and Global Forecast Systems), the 30-km archive from the International Satellite Cloud Climatology Project (ISCCP), the Quick Scatterometer surface winds, and remotely sensed fields derived from radiances measured by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), the Advanced Microwave Sounding Unit, and the Advanced Very High Resolution Radiometer. The analysis shows that outside of the boundary layer the state of the lower troposphere is reasonably represented by the reanalysis and forecast products, with the caveat of a slight warm bias at 850 hPa in the NCEP–NCAR products. Within the planetary boundary layer (PBL) the agreement is not as good: both the boundary layer depth and cloud amount are underpredicted, and the boundary layer temperature correlates poorly with the available data, which may be related to a poor representation of SSTs in this region of persistent cloud cover. ERA-40 also suffers from persistently weak zonal winds within the PBL. Among the satellite records the ISCCP data are found to be especially valuable, evincing skill in both predicting boundary layer depth (from cloud-top temperatures and TMI surface temperatures) and cloud liquid water paths (from cloud optical depths). An analysis of interannual variability (among Julys) based on ERA-40 and the 1983–2001 ISCCP record suggests that thermodynamic quantities show similar interannual and synoptic variability, principally concentrated just above the PBL, while dynamic quantities vary much more on synoptic time scales. Furthermore, the analysis suggests that the correlation between stratocumulus cloud amount and lower-tropospheric stability exhibits considerable spatial structure and is less pronounced than previously thought.