Experimental Investigation of Turbulent Momentum Transfer in a Neutral Boundary Layer over a Rough Surface

The turbulent characteristics of the neutral boundary layer developing over rough surfaces are not well predicted with operational weather-forecasting models. The problem is attributed to inadequate mixing-length models, to the anisotropy of the flow and to a lack of controlled experimental data against which to validate numerical studies. Therefore, in order to address directly the modelling difficulties for the development of a neutral boundary layer over rough surfaces, and to investigate the turbulent momentum transfer of such a layer, a set of hydraulic flume experiments were carried out. In the experiments, the mean and turbulent quantities were measured by a particle image velocimetry (PIV) technique. The measured velocity variances and fluxes \({(\overline{{u_{i}^{\prime}}{u_{j}^{\prime}}})}\) in longitudinal vertical planes allowed the vertical and longitudinal gradients (?/?z and ?/?x) of the mean and turbulent quantities (fluxes, variances and third-order moments) to be evaluated and the terms of the evolution equations for ?e/?t, \({\partial \overline{u^{\prime 2}}/\partial t}\), \({\partial \overline{w^{\prime 2}}/\partial t}\) and \({\partial \overline{{u^{\prime}}{w^{\prime}}}/\partial t}\) to be quantified, where e is the turbulent kinetic energy. The results show that the pressure-correlation terms allow the turbulent energy to be transferred equitably from \({\overline{{u^{\prime}}^{2}}}\) to \({\overline{{w^{\prime}}^{2}}}\). It appears that the repartition between the constitutive terms of the budget of e, \({\overline{{u^{\prime}}^{2}}}\), \({\overline{{w^{\prime}}^{2}}}\) and \({\overline{{u^{\prime}}{w^{\prime}}}}\) is not significantly affected by the development of the rough neutral boundary layer. For the whole evolution, the transfers of energy are governed by the same terms that are also very similar to the smooth-wall case. The PIV measurements also allowed the spatial integral scales to be computed directly and to be compared with the dissipative and mixing length scales, which were also computed from the data.     

Scaling of Wall-Normal Turbulence Intensity and Vertical Eddy Structures in the Atmospheric Surface Layer

Adequate high-quality data on three-dimensional velocities in the atmospheric surface layer (height \(\delta \)) were acquired in the field at the Qingtu Lake Observation Array. The measurement range occupies nearly the entire logarithmic layer from approximately \(0.006\delta \)–\(0.2\delta \). The turbulence intensity and eddy structures of the velocity fluctuations in the logarithmic region were primarily analyzed, and their variations in the z (wall-normal) direction were revealed. The primary finding was that the turbulent intensity of wall-normal velocity fluctuations exhibits a sharp upswing in the logarithmic region, which differs from classic scaling law and laboratory results. The upswing of the wall-normal turbulence intensity in the logarithmic region is deemed to be linear based on an ensemble of 20 sets of data. In addition, the wall-normal extent of the correlated structures and wall-normal spectra were compared to low Reynolds number results in the laboratory.     

Real Data Assimilation Using the Local Ensemble Transform Kalman Filter (LETKF) System for a Global Non-hydrostatic NWP model on the Cubed-sphere

An ensemble data assimilation system using the 4-dimensional Local Ensemble Transform Kalman Filter is implemented to a global non-hydrostatic Numerical Weather Prediction model on the cubed-sphere. The ensemble data assimilation system is coupled to the Korea Institute of Atmospheric Prediction Systems Package for Observation Processing, for real observation data from diverse resources, including satellites. For computational efficiency in a parallel computing environment, we employ some advanced software engineering techniques in the handling of a large number of files. The ensemble data assimilation system is tested in a semi-operational mode, and its performance is verified using the Integrated Forecast System analysis from the European Centre for Medium-Range Weather Forecasts. It is found that the system can be stabilized effectively by additive inflation to account for sampling errors, especially when radiance satellite data are additionally used.     

Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.     

A dynamic link between the basin-scale and zonal modes in the Tropical Indian Ocean

Summary The interannual variability of sea surface temperature (SST) anomalies in the tropical Indian Ocean is dominated mainly by a basin-scale mode (BM) and partly by an east–west contrast mode (zonal mode, ZM). The BM reflects the basin-scale warming or cooling and is highly correlated with El Nino with 3- to 6-month lags, while the ZM is marginally correlated with El Nino with 9-month lags.During an El Nino, large-scale anomalous subsidence over the maritime continent occurs as a result of an eastward shift in the rising branch of the Walker circulation suppresses convection over the eastern Indian Ocean, allowing more solar radiation over the eastern Indian Ocean. At the same time, the anomalous southeasterly wind over the equatorial Indian Ocean forces the thermocline over the western Indian Ocean to deepen, especially in the southern part. As a result, SST over the whole basin increases. As El Nino decays, the subsidence over the maritime continent ceases and so does the anomalous southeasterly wind. However, the thermocline perturbation does not quickly shoal back to normal because of inertia and it disperses as Rossby waves. These Rossby waves are reflected back as an equatorial Kelvin wave, causing deepening of the thermocline in the eastern Indian Ocean, and preventing SSTs from cooling in that region. Moreover, the weaker wind speed of the monsoon circulation results in less latent heat loss, and thus warms the eastern Indian Ocean. These two processes therefore help to maintain warm SSTs over the eastern Indian Ocean until fall. During the fall, the warm SST over the eastern Indian Ocean and the cold SST over the western Indian Ocean are enhanced by air–sea interaction and the ZM returns. The ZM dissipates through the seasonal reversal of the monsoon atmospheric circulation and the boundary-reflected Kelvin wave. In the same manner, a basin-scale cooling in the tropical Indian Ocean can induce the ZM warming in the west and cooling in the east.     

Interdecadal variations of cold air activities in Northeast China during springtime

Based on the daily mean temperature data of CN05.2 from 1961 to 2012, cold events (CEs) are first divided into two categories according to their duration: strong cold events (SCEs) and weak cold events (WCEs). Then, the characteristics of CEs, SCEs, and WCEs during springtime are investigated. The results indicate that in the pre-1990s epoch, ENSO and Arctic Oscillation events in the previous winter are closely related to SCEs in the following spring. The multidecadal variations of CEs, SCEs, and WCEs are obvious. The intensity trend for SCEs is significantly negative, but it seems less apparent for WCEs. Further analysis reveals that when both SCEs and WCEs occur, a typical East Asian trough in the 850- hPa wind field, whose northwesterly wind component invades Northeast China (NEC) and causes freezing days, can be found in every decade. For the SCEs, a cold vortex, with its center located over Okhotsk and northeasterly current affecting NEC, is found as an additional feature. For the WCEs, the cold vortex is located in Karafuto and its northwesterly airflow intrudes into NEC. As for the difference between SCEs and WCEs, the northwestern flow is weaker while the northeastern counterpart is stronger during the SCEs, in all decades. In the Takaya–Nakamura flux and divergence fields, for the SCEs, a divergence center exists over NEC; and over its downstream regions, a stronger divergence center appears, not like a wave train. However, the opposite is the case for the WCEs; moreover, the wave train appears clearly during the WCEs, which means that the wave energy can propagate and dissipate more easily during WCEs.     

The 2001 Mesoscale Convective Systems over Iberia and the Balearic Islands

Summary This paper characterizes Mesoscale Convective Systems (MCSs) during 2001 over Iberia and the Balearic Islands and their meteorological settings. Enhanced infrared Meteosat imagery has been used to detect their occurrence over the Western Mediterranean region between June and December 2001 according to satellite-defined criteria based on the MCS physical characteristics. Twelve MCSs have been identified. The results show that the occurrence of 2001 MCSs is limited to the August–October period, with September being the most active period. They tend to develop during the late afternoon or early night, with preferred eastern Iberian coast locations and eastward migrations. A cloud shield area of 50.000 km² is rarely exceeded. When our results are compared with previous studies, it is possible to assert that though 2001 MCS activity was moderate, the convective season was substantially less prolonged than usual, with shorter MCS life cycles and higher average speeds. The average MCS precipitation rate was 3.3 mm·h⁻¹ but a wide range of values varying from scarce precipitation to intense events of 130 mm·24 h⁻¹ (6 September) were collected. The results suggest that, during 2001, MCS rainfall was the principal source of precipitation in the Mediterranean region during the convective season, but its impact varied according to the location. Synoptic analysis based on NCEP/NCAR reanalysis show that several common precursors could be identified over the Western Mediterranean Sea when the 2001 MCSs occurred: a low-level tongue of moist air and precipitable water (PW) exceeding 25 mm through the southern portion of the Western Mediterranean area, low-level zonal warm advection over 2 °C·24 h⁻¹ towards eastern Iberia, a modest 1000–850 hPa equivalent potential temperature (θ_e) difference over 20 °C located close to the eastern Iberian coast, a mid level trough (sometimes a cut-off low) over Northern Africa or Southern Spain and high levels geostrophic vorticity advection exceeding 12·10⁻¹⁰ s⁻² over eastern Iberia and Northern Africa. Finally, the results suggest that synoptic, orographic and a warm-air advection were the most relevant forcing mechanisms during 2001.     

Influence of coastal wind on surface ozone and nitrogen oxides in suburban Shanghai

Surface ozone, NO, NO₂, and NO _x were measured at a coastal site (Shihua) and a nearby inland site (Zhujing) in suburban Shanghai for the whole year of 2009. More days with ozone pollution in a longer time range were observed at the coastal site than the inland site. The diurnal variations of NO _x concentrations were obviously higher at Zhujing station, while those of ozone concentrations were higher at Shihua station, indicating their different air pollution conditions. Coastal wind has significant influence on the levels and characteristics of the air pollutants. The ozone concentrations during maritime winds (MW) were much higher than those during continental winds (CW) at each of the site, while the NO and NO₂ concentrations were both opposite. The ozone concentrations at Shihua station were much higher than those at Zhujing station, while the NO and NO₂ concentrations were both opposite. The ozone concentrations at both of the two sites showed a distinct “weekend effects” and “weekdays effects” patterns during CW and MW, respectively. Correlation analysis of the pollutants showed that, the compounds during MW were more age than those during CW, and the compounds at Shihua were more age than those at Zhujing. The air pollutions at both of the two sites are mainly associated with the pollutants emitted in this region instead of long range transport.     

Vertical distributions of aerosol optical properties during haze and floating dust weather in Shanghai

A comparative study on the vertical distributions of aerosol optical properties during haze and floating dust weather in Shanghai was conducted based on the data obtained from a micro pulse lidar.There was a distinct difference in layer thickness and extinction coefficient under the two types of weather conditions.Aerosols were concentrated below 1 km and the aerosol extinction coefficients ranged from 0.25 to 1.50km^-1 on haze days.In contrast,aerosols with smaller extinction coefficients(0.20 0.35 km^-1) accumulated mainly from the surface to 2 km on floating dust days.The seasonal variations of extinction and aerosol optical depth（AOD） for both haze and floating dust cases were similar greatest in winter,smaller in spring,and smallest in autumn.More than 85%of the aerosols appeared in the atmosphere below 1 km during severe haze and floating dust weather.The diurnal variation of the extinction coefficient of haze exhibited a bimodal shape with two peaks in the morning or at noon,and at nightfall,respectively.The aerosol extinction coefficient gradually increased throughout the day during floating dust weather.Case studies showed that haze aerosols were generated from the surface and then lifted up,but floating dust aerosols were transported vertically from higher altitude to the surface.The AOD during floating dust weather was higher than that during haze.The boundary layer was more stable during haze than during floating dust weather.     

A Climate Prediction Method Based on EMD and Ensemble Prediction Technique

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.