ALBERT

Description: A “hot start” technique is applied to the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) to dynamically assimilate cloud properties and humidity profiles retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board the NASA Earth Observing System polar-orbiting satellites. The assimilation approach has been studied through extensive numerical experimentation for high-latitude rain events to demonstrate the feasibility and the benefit of the approach on the model cloud and precipitation simulation/forecast. The ingestion of MODIS-retrieved cloud and clear-air humidity information impacts MM5 cloud fields on both a microphysical and macrophysical level. From short-term (6–12 h) forecast experiments conducted for a preliminary test case and 16 extensive summer and winter experiments, the following primary conclusions have been reached. 1) It is feasible to introduce MODIS-retrieved cloud-top properties and humidity profiles into the MM5 model in a hot start mode without disrupting model stability and evolutionary continuity. 2) The introduction of high-resolution MODIS information produced more accurate humidity fields and resulted in increased mesoscale structure in the cloud and precipitation fields. 3) The opportunistic ingestion of MODIS data at its observation time into the model leads to improved 6–12-h model precipitation forecasts with respect to not only the frequency of occurrences, but also the magnitude of precipitation amounts. 4) Verification with three-dimensional analyses indicates some improvement in model forecasts of temperature, wind, pressure perturbation, and sea level pressure as well. 5) Verification with surface station observations indicates that model forecasts of 2-m temperature, 2-m relative humidity, 10-m winds, and sea level pressure are also improved, most notably for the summer cases. The largest improvement in forecast skill is for 2-m relative humidity (12%).

Description: Simulated surface fluxes depend on one or more empirical plant or soil parameters that have a standard deviation (std dev). Thus, simulated fluxes will have a stochastic error (or std dev) resulting from the parameters’ std dev. Gaussian error propagation (GEP) principles are used to calculate the std dev for fluxes predicted by the hydro–thermodynamic soil–vegetation scheme to identify prediction limitations due to stochastic errors, parameterization weaknesses, and critical parameters, and to prioritize which parameters to measure with higher accuracy. Relative errors of net radiation, sensible, latent, and ground heat flux, on average, are 7%, 10%, 6%, and 26%, respectively. The analysis identified the parameterization of thermal conductivity as the dominant influence on the std dev of ground heat flux. For net radiation, critical parameters are vegetation fraction and ground emissivity; for sensible and latent heat fluxes, vegetation fraction. Minimum stomatal resistance and leaf area index dominate the std dev of stomatal resistance for most vegetation and soil types. The empirical parameters with the highest relative error are not necessarily the greatest contributors to the std dev of the predicted flux. Based on the analysis high priority should be given to measurements of vegetation fraction, ground emissivity, minimum stomatal resistance, leaf area index in general, and the permanent wilting point and field capacity for clay and clay loam. Moreover, further specification of clay-type soils and tundra-type vegetation may improve the accuracy of the lower boundary condition in Arctic numerical weather prediction. Since GEP showed itself able to identify critical parameters and (parts of) parameterizations, GEP analysis could form a basis for parameterization intercomparisons and for parameter determination aimed at improving models.

Description: Analysis of daily observations shows that wintertime (November–April) precipitation over Southwest Asia is modulated by Madden–Julian oscillation (MJO) activity in the eastern Indian Ocean, with strength comparable to the interannual variability. Daily outgoing longwave radiation (OLR) for 1979–2001 is used to provide a long and consistent, but indirect, estimate of precipitation, and daily records from 13 stations in Afghanistan reporting at least 50% of the time for 1979–85 are used to provide direct, but shorter and irregularly reported, precipitation data. In the station data, for the average of all available stations, there is a 23% increase in daily precipitation relative to the mean when the phase of the MJO is negative (suppressed tropical convection in the eastern Indian Ocean), and a corresponding decrease when the MJO is positive. The distribution of extremes is also affected such that the 10 wettest days all occur during the negative MJO phase. The longer record of OLR data indicates that the effect of the MJO is quite consistent from year to year, with the anomalies averaged over Southwest Asia more negative (indicating more rain) for the negative phase of the MJO for each of the 22 yr in the record. Additionally, in 9 of the 22 yr the average influence of the MJO is larger than the interannual variability (e.g., the relationship results in anomalously wet periods even in dry years and vice versa). Examination of NCEP–NCAR reanalysis data shows that the MJO modifies both the local jet structure and, through changes to the thermodynamic balance, the vertical motion field over Southwest Asia, consistent with the observed modulation of the associated synoptic precipitation. A simple persistence scheme for forecasting the sign of the MJO suggests that the modulation of Southwest Asia precipitation may be predictable for 3-week periods. Finally, analysis of changes in storm evolution in Southwest Asia due to the influence of the MJO shows a large difference in strength as the storms move over Afghanistan, with apparent relevance for the flooding event of 12–13 April 2002.

Description: Casey Station in East Antarctica is not often subject to strong southerly flow off the Antarctic continent but when such events occur, operations at the station are often adversely impacted. Not only are the dynamics of such events poorly understood, but the forecasting of such occurrences is difficult. The following study uses model output from a 12-month experiment using the Antarctic Limited-Area Prediction System (ALAPS) to advance the understanding of the dynamics of such events and postulates that what are often described as katabatic wind events are more likely to be synoptic in scale, with mid- and upper-level tropospheric dynamics forcing the surface layer flow. Strong surface layer flows that have a katabatic signature commonly develop on the steep Antarctic escarpment but rarely extend out over the coast in the Casey area, most probably as a result of cold air damming. However, the development of a strong south-southwesterly jet over Casey provides a mechanism whereby the katabatic can move out off the coast.

Description: In this brief contribution, photographic documentation is provided of a variety of small, tubular-shaped clouds and of a small funnel cloud pendant from a convective cloud that appears to have been modified by flow over high-altitude mountains in northeast Colorado. These funnel clouds are contrasted with others that have been documented, including those pendant from high-based cumulus clouds in the plains of the United States. It is suggested that the mountain funnel cloud is unique in that flow over high terrain is probably responsible for its existence; other types of small funnel clouds are seen both over elevated, mountainous terrain and over flat terrain at lower elevations.

Description: The subtropical west coast of South America is under the influence of the southeast Pacific anticyclone year-round, which induces persistent southerly winds along the coast of north-central Chile. These winds often take the form of a low-level coastal jet, in many aspects similar to the coastal jet existing off the California coast. Extensive diagnostics of mesoscale model results for a case in October 2000 are used here to describe the mean momentum budget supporting the coastal jet. The jet appears to occur when midlatitude synoptic conditions induce a northerly directed pressure gradient force along the coast of north-central Chile. The very steep coastal terrain precludes the development of a significant easterly low-level wind that would geostrophically balance the pressure gradient. Instead, the meridional flow accelerates until turbulent friction in the marine boundary layer balances the meridional pressure gradient. The resulting force balance is semigeostrophic, with geostrophy valid only in the zonal (cross shore) direction. At higher levels, the topographic inhibition of the easterlies relaxes, and a small easterly flow ensues, which turns out to be very important in the temperature and stability budgets of the layer capping the marine boundary layer.

Description: Ensemble data assimilation systems incorporate observations into numerical models via solution of the Kalman filter update equations, and estimates of forecast error covariances derived from ensembles of model integrations. In this paper, a particular algorithm, the ensemble square root filter (EnSRF), is tested in a limited-area, polar numerical weather prediction (NWP) model: the Antarctic Mesoscale Prediction System (AMPS). For application in the real-time AMPS, the number of model integrations that can be run to provide forecast error covariances is limited, resulting in an ensemble sampling error that degrades the analysis fit to observations. In this work, multivariate, climatologically plausible forecast error covariances are specified via averaged forecast difference statistics. Ensemble representations of the “true” forecast errors, created using randomized control variables of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) three-dimensional variational (3DVAR) data assimilation system, are then used to assess the dependence of sampling error on ensemble size, data density, and localization of covariances using simulated observation networks. Results highlight the detrimental impact of ensemble sampling error on the analysis increment structure of correlated, but unobserved fields—an issue not addressed by the spatial covariance localization techniques used to date. A 12-hourly cycling EnSRF/AMPS assimilation/forecast system is tested for a two-week period in December 2002 using real, conventional (surface, rawinsonde, satellite retrieval) observations. The dependence of forecast scores on methods used to maintain ensemble spread and the inclusion of perturbations to lateral boundary conditions are studied.

Description: The first step in the evolution of the diurnal circulation of grand plateaus is the matutinal buildup of inflow through mountain passes connecting the lowlands with the plateau proper. Maximum inward transport is attained in the afternoon. Corresponding observations at the Bolivian Altiplano are described in the first part of this paper. Here, both a linear model and the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) are used to better understand the dynamics of this process. First discussed is the solution to the linear sea-breeze problem where a heated fluid layer is restricted to the half plane x ≤ 0. Rapidly moving barotropic modes lead to surface pressure fall in the heated half plane and to pressure rise for x ≥ 0. Slow baroclinic modes describe the horizontally expanding inflow toward the heated layer near the ground with return flow aloft. This basic structure of the response carries over to more complicated topographies where a heated plateau with vertical sidewalls is separated from the lowlands by a barrier and a pass. The baroclinic modes are fanning out from the pass into the plateau’s interior in linear numerical calculations. These flow patterns hardly change when additional slopes connect the plains and the plateau. The restrictions imposed by the linear approach are removed step by step in simulations with MM5 in which an idealized plateau with an optional pass is prescribed. There is good agreement with respect to the basic flow pattern, but the linear theory is found to overestimate inflow velocities because of its neglect of momentum and perturbation temperature advection. Moreover, a front moves from the pass into the plateau’s interior where the stratification is neutral or even unstable, a situation that is beyond the scope of the linear theory. The upslope winds evolving at the slope connecting the plateau with the lowlands are unimportant for the thermal circulation of the plateau, a result also suggested by the linear theory. Finally, simulations of the diurnal cycle are performed for the real topography of the Altiplano. The presentation of results concentrates on the observation sites. It is demonstrated that the idealized calculations help to better understand the resulting flows as well as the observations reported in Part I. The total inflow to the Altiplano is discussed as well.

Description: A high-resolution atmosphere–sea ice model is used to investigate the interactions between cyclones and sea ice cover in polar regions. For this purpose, a cyclone passage observed during the 1999 Fram Strait Cyclone Experiment (FRAMZY) is simulated for two consecutive days. The results of the coupled mesoscale transport and stream model–mesoscale sea ice model (METRAS–MESIM) are compared with aircraft and ice drift measurements. With the exception of temperature, all atmospheric parameters are well simulated. Main reasons for discrepancies were found in large differences between the measurements and the forcing data taken from the results of the regional model (REMO). In addition, advection was slightly wrong as a result of a 17° deviation in wind directions. The altogether well simulated wind field is interactively used to force the sea ice model MESIM; results agree well with drift buoy measurements. Average deviations of simulated and measured ice drift are smaller than 8° for direction and smaller than 3.7 cm s−1 for speed, which is less than 10% of the average speed. The simulated ratio between ice drift and wind velocity increases slightly during cyclone passage from 2.6% to 2.9%, a tendency also known from observations. During a 36-h period, the simulated sea ice concentration locally decreases up to 20% in accordance with measurements. A neglect of changing sea ice cover causes a decrease of the heat flux to the atmosphere from 53 to 12 W m−2. The values correspond to averages over the evaluation region (approximately 228 000 km2) and period (36 h). Temperature and humidity are decreased by 2 K and 0.2 g kg−1, respectively, over the ice-covered region. In contrast, the effect on pressure and wind remains small, probably because the cyclone does not move in the vicinity of the ice edge.