Convective updraught evaluation in high-resolution NWP simulations using single-Doppler radar measurements

This study presents an evaluation of the size and strength of convective updraughts in high-resolution simulations by the UK Met Office Unified Model (UM). Updraught velocities have been estimated from range–height indicator (RHI) Doppler velocity measurements using the Chilbolton advanced meteorological radar, as part of the Dynamical and Microphysical Evolution of Convective Storms (DYMECS) project. Based on mass continuity and the vertical integration of the observed radial convergence, vertical velocities tend to be underestimated for convective clouds due to the undetected cross-radial convergence. Velocity fields from the UM at a resolution corresponding to the radar observations are used to scale such estimates to mitigate the inherent biases. The analysis of more than 100 observed and simulated storms indicates that the horizontal scale of updraughts in simulations tend to decrease with grid length; the 200 m grid length agreed most closely with the observations. Typical updraught mass fluxes in the 500 m grid length simulations were up to an order of magnitude greater than observed, and greater still in the 1.5 km grid length simulations. The effect of increasing the mixing length in the sub-grid turbulence scheme depends on the grid length. For the 1.5 km simulations, updraughts were weakened though their horizontal scale remained largely unchanged. Progressively more so for the sub-kilometre grid lengths, updraughts were broadened and intensified; horizontal scale was now determined by the mixing length rather than the grid length. In general, simulated updraughts were found to weaken too quickly with height. The findings were supported by the analysis of the widths of reflectivity patterns in both the simulations and observations.

Examining the predictability of the Stratospheric Sudden Warming of January 2013 using multiple NWP systems

The first multi-model study to estimate the predictability of a boreal Sudden Stratospheric Warming (SSW) is performed using five NWP systems. During the 2012-2013 boreal winter, anomalous upward propagating planetary wave activity was observed towards the end of December, which followed by a rapid deceleration of the westerly circulation around 2 January 2013, and on 7 January 2013 the zonal mean zonal wind at 60°N and 10 hPa reversed to easterly. This stratospheric dynamical activity was followed by an equatorward shift of the tropospheric jet stream and by a high pressure anomaly over the North Atlantic, which resulted in severe cold conditions in the UK and Northern Europe. In most of the five models, the SSW event was predicted 10 days in advance. However, only some ensemble members in most of the models predicted weakening of westerly wind when the models were initialized 15 days in advance of the SSW. Further dynamical analysis of the SSW shows that this event was characterized by the anomalous planetary wave-1 amplification followed by the anomalous wave-2 amplification in the stratosphere, which resulted in a split vortex occurring between 6 January 2013 and 8 January 2013. The models have some success in reproducing wave-1 activity when initialized 15 days in advance, they but generally failed to produce the wave-2 activity during the final days of the event. Detailed analysis shows that models have reasonably good skill in forecasting tropospheric blocking features that stimulate wave-2 amplification in the troposphere, but they have limited skill in reproducing wave-2 amplification in the stratosphere.

Atmospheric radiative transfer in multiple scattering conditions. Application to NWP models.

High spectral resolution radiative transfer (RT) codes are essential tools in the study of the radiative energy transfer in the Earth atmosphere and a support for the development of parameterizations for fast RT codes used in climate and weather prediction models. Cirrus clouds cover permanently 30% of the Earth's surface, representing an important contribution to the Earth-atmosphere radiation balance. The work has been focussed on the development of the RT model LBLMS. The model, widely tested in the infra-red spectral range, has been extended to the short wave spectrum and it has been used in comparison with airborne and satellite measurements to study the optical properties of cirrus clouds. A new database of single scattering properties has been developed for mid latitude cirrus clouds. Ice clouds are treated as a mixture of ice crystals with various habits. The optical properties of the mixture are tested in comparison to radiometric measurements in selected case studies. Finally, a parameterization of the mixture for application to weather prediction and global circulation models has been developed. The bulk optical properties of ice crystals are parameterized as functions of the effective dimension of measured particle size distributions that are representative of mid latitude cirrus clouds. Tests with the Limited Area Weather Prediction model COSMO have shown the impact of the new parameterization with respect to cirrus cloud optical properties based on ice spheres.

Benefit analysis of airborne GPS occultation approach : a case study for the Australian region

This paper aims to present a preliminary benefit analysis for airborne GPS occultation technique for the Australian region. The simulation studies are based on current domestic commercial flights between major Australian airports. With the knowledge of GPS satellite ephemeris data, occultation events for for any particular flight can be determined. Preliminary analysis shows a high resolution occultation observations can be achieved with this approach, for instance, about 15 occultation events for a Perth-to-Sydney flight. The simulation result agrees to the results published by other researchers for a different region. Of course, occultation observation during off-peak hours might be affected due to the limited flight activities. --------- High resolution occultation observations obtainable from airborne GPS occultation system provides an opportunity to improve the current global numerical weather prediction (NWP) models and ultimately improves the accuracy in weather forecasting. More intensive research efforts and experimental demonstrations are required in order to demonstrate the technical feasibility of the airborne GPS technology.

Feasibility of assimilating ASCAT surface winds into a Limited Area Model

Sea-surface wind observations of previous generation scatterometers have been successfully assimilated into Numerical Weather Prediction (NWP) models. Impact studies conducted with these assimilation implementations have shown a distinct improvement to model analysis and forecast accuracies. The Advanced Scatterometer (ASCAT), flown on Metop-A, offers an improved sea-surface wind accuracy and better data coverage when compared to the previous generation scatterometers. Five individual case studies are carried out. The effect of including ASCAT data into High Resolution Limited Area Model (HIRLAM) assimilation system (4D-Var) is tested to be neutral-positive for situations with general flow direction from the Atlantic Ocean. For northerly flow regimes the effect is negative. This is later discussed to be caused by problems involving modeling northern flows, and also due to the lack of a suitable verification method. Suggestions and an example of an improved verification method is presented later on. A closer examination of a polar low evolution is also shown. It is found that the ASCAT assimilation scheme improves forecast of the initial evolution of the polar low, but the model advects the strong low pressure centre too fast eastward. Finally, the flaws of the implementation are found small and implementing the ASCAT assimilation scheme into the operational HIRLAM suite is feasible, but longer time period validation is still required.

Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Exploiting ground-based measurements of the Global Positioning System for numerical weather prediction

Data assimilation provides an initial atmospheric state, called the analysis, for Numerical Weather Prediction (NWP). This analysis consists of pressure, temperature, wind, and humidity on a three-dimensional NWP model grid. Data assimilation blends meteorological observations with the NWP model in a statistically optimal way. The objective of this thesis is to describe methodological development carried out in order to allow data assimilation of ground-based measurements of the Global Positioning System (GPS) into the High Resolution Limited Area Model (HIRLAM) NWP system. Geodetic processing produces observations of tropospheric delay. These observations can be processed either for vertical columns at each GPS receiver station, or for the individual propagation paths of the microwave signals. These alternative processing methods result in Zenith Total Delay (ZTD) and Slant Delay (SD) observations, respectively. ZTD and SD observations are of use in the analysis of atmospheric humidity. A method is introduced for estimation of the horizontal error covariance of ZTD observations. The method makes use of observation minus model background (OmB) sequences of ZTD and conventional observations. It is demonstrated that the ZTD observation error covariance is relatively large in station separations shorter than 200 km, but non-zero covariances also appear at considerably larger station separations. The relatively low density of radiosonde observing stations limits the ability of the proposed estimation method to resolve the shortest length-scales of error covariance. SD observations are shown to contain a statistically significant signal on the asymmetry of the atmospheric humidity field. However, the asymmetric component of SD is found to be nearly always smaller than the standard deviation of the SD observation error. SD observation modelling is described in detail, and other issues relating to SD data assimilation are also discussed. These include the determination of error statistics, the tuning of observation quality control and allowing the taking into account of local observation error correlation. The experiments made show that the data assimilation system is able to retrieve the asymmetric information content of hypothetical SD observations at a single receiver station. Moreover, the impact of real SD observations on humidity analysis is comparable to that of other observing systems.

On the behaviour of some physical parameterization methods in high-resolution numerical weather prediction models

Modern-day weather forecasting is highly dependent on Numerical Weather Prediction (NWP) models as the main data source. The evolving state of the atmosphere with time can be numerically predicted by solving a set of hydrodynamic equations, if the initial state is known. However, such a modelling approach always contains approximations that by and large depend on the purpose of use and resolution of the models. Present-day NWP systems operate with horizontal model resolutions in the range from about 40 km to 10 km. Recently, the aim has been to reach operationally to scales of 1 4 km. This requires less approximations in the model equations, more complex treatment of physical processes and, furthermore, more computing power. This thesis concentrates on the physical parameterization methods used in high-resolution NWP models. The main emphasis is on the validation of the grid-size-dependent convection parameterization in the High Resolution Limited Area Model (HIRLAM) and on a comprehensive intercomparison of radiative-flux parameterizations. In addition, the problems related to wind prediction near the coastline are addressed with high-resolution meso-scale models. The grid-size-dependent convection parameterization is clearly beneficial for NWP models operating with a dense grid. Results show that the current convection scheme in HIRLAM is still applicable down to a 5.6 km grid size. However, with further improved model resolution, the tendency of the model to overestimate strong precipitation intensities increases in all the experiment runs. For the clear-sky longwave radiation parameterization, schemes used in NWP-models provide much better results in comparison with simple empirical schemes. On the other hand, for the shortwave part of the spectrum, the empirical schemes are more competitive for producing fairly accurate surface fluxes. Overall, even the complex radiation parameterization schemes used in NWP-models seem to be slightly too transparent for both long- and shortwave radiation in clear-sky conditions. For cloudy conditions, simple cloud correction functions are tested. In case of longwave radiation, the empirical cloud correction methods provide rather accurate results, whereas for shortwave radiation the benefit is only marginal. Idealised high-resolution two-dimensional meso-scale model experiments suggest that the reason for the observed formation of the afternoon low level jet (LLJ) over the Gulf of Finland is an inertial oscillation mechanism, when the large-scale flow is from the south-east or west directions. The LLJ is further enhanced by the sea-breeze circulation. A three-dimensional HIRLAM experiment, with a 7.7 km grid size, is able to generate a similar LLJ flow structure as suggested by the 2D-experiments and observations. It is also pointed out that improved model resolution does not necessary lead to better wind forecasts in the statistical sense. In nested systems, the quality of the large-scale host model is really important, especially if the inner meso-scale model domain is small.

Studies on orographic effects in a numerical weather prediction model

Numerical models, used for atmospheric research, weather prediction and climate simulation, describe the state of the atmosphere over the heterogeneous surface of the Earth. Several fundamental properties of atmospheric models depend on orography, i.e. on the average elevation of land over a model area. The higher is the models' resolution, the more the details of orography directly influence the simulated atmospheric processes. This sets new requirements for the accuracy of the model formulations with respect to the spatially varying orography. Orography is always averaged, representing the surface elevation within the horizontal resolution of the model. In order to remove the smallest scales and steepest slopes, the continuous spectrum of orography is normally filtered (truncated) even more, typically beyond a few gridlengths of the model. This means, that in the numerical weather prediction (NWP) models, there will always be subgridscale orography effects, which cannot be explicitly resolved by numerical integration of the basic equations, but require parametrization. In the subgrid-scale, different physical processes contribute in different scales. The parametrized processes interact with the resolved-scale processes and with each other. This study contributes to building of a consistent, scale-dependent system of orography-related parametrizations for the High Resolution Limited Area Model (HIRLAM). The system comprises schemes for handling the effects of mesoscale (MSO) and small-scale (SSO) orographic effects on the simulated flow and a scheme of orographic effects on the surface-level radiation fluxes. Representation of orography, scale-dependencies of the simulated processes and interactions between the parametrized and resolved processes are discussed. From the high-resolution digital elevation data, orographic parameters are derived for both momentum and radiation flux parametrizations. Tools for diagnostics and validation are developed and presented. The parametrization schemes applied, developed and validated in this study, are currently being implemented into the reference version of HIRLAM.

N-gamma for rough strip footing using the method of characteristics

By using the method of characteristics, the bearing capacity factor N-gamma was computed for a rough strip footing. The analysis was performed by considering a curved nonplastic wedge under the foundation base bounded by curved slip lines being tangential to the base of the footing at its either edge and inclined at an angle pi/4 - phi/2 with the vertical axis of symmetry. The existing theories in the literature for rough footings, which usually employ a triangular wedge below the footing base, were generally found to provide greater values of N-gamma as compared with the results obtained in this contribution.

Los herbarios: custodios de la biodiversidad.

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适用于GRAPES数值天气预报软件的ILU预条件子

探讨了一种适用于我国自主研发的数值天气预报模式软件GRAPES的不完全LU(ILU)分解预条件子。针对GRAPES模式所特有的具有对角优势结构的赫姆霍兹方程系数矩阵,提出了一种有效的ILU分解方案,并将分解得到的预条件子应用到模式核心的动力积分计算迭代算法中,从而达到加速算法收敛,提高模式软件整体性能的目的。

中国近海和西北太平洋温跃层时空变化分析、模拟及预报

温度跃层是反映海洋温度场的重要物理特性指标，对水下通讯、潜艇活动及渔业养殖、捕捞等有重要影响。本文利用中国科学院海洋研究所“中国海洋科学数据库”在中国近海及西北太平洋（110ºE-140ºE,10ºN-40ºN）的多年历史资料（1930-2002年，510143站次），基于一种改进的温跃层判定方法，分析了该海域温跃层特征量的时空分布状况。同时利用Princeton Ocean Model(POM)，对中国近海，特别是东南沿海的水文结构进行了模拟，研究了海洋水文环境对逆温跃层的影响。最后根据历史海温观测资料，利用EOF分解统计技术，提出了一种适于我国近海及毗邻海域，基于现场有限层实测海温数据，快速重构海洋水温垂直结构的统计预报方法，以达到对现场温跃层的快速估计。 历史资料分析结果表明，受太阳辐射和风应力的影响，20°N以北研究海域，温跃层季节变化明显，夏季温跃层最浅、最强，冬季相反，温跃层厚度的相位明显滞后于其他变量，其在春季最薄、秋季最厚。12月份到翌年3月份，渤、黄及东海西岸，呈无跃层结构，西北太平洋部分海域从1月到3月份，也基本无跃层结构。在黄海西和东岸以及台湾海峡附近的浅滩海域，由于风力搅拌和潮混合作用，温跃层出现概率常年较低。夏季，海水层化现象在近海陆架海域得到了加强，陆架海域温跃层强度季节性变化幅度(0.31°C/m)明显大于深水区(约0.05°C/m)，而前者温跃层深度和厚度的季节性变化幅度小于后者。20°N以南研究海域，温跃层季节变化不明显。逆温跃层主要出现在冬、春季节（10月-翌年5月）。受长江冲淡水和台湾暖流的影响，东南沿海区域逆温跃层持续时间最长，出现概率最大，而在山东半岛北及东沿岸、朝鲜半岛西及北岸，逆温跃层消长过程似乎和黄海暖流有关。多温跃层结构常年出现于北赤道流及对马暖流区。在黑潮入侵黄、东、南海的区域，多温跃层呈现明显不同的季节变化。在黄海中部，春季多温跃层发生概率高于夏季和秋季，在东海西部，多跃层主要出现在夏季，在南海北部，冬季和春季多温跃层发生概率大于夏季和秋季。这些变化可能主要受海表面温度变化和风力驱动的表层流的影响。 利用Princeton Ocean Model(POM)，对中国东南沿海逆温跃层结构进行了模拟，模拟结果显示，长江冲淡水的季节性变化以及夏季转向与实际结果符合较好，基本再现了渤、黄、东海海域主要的环流、温盐场以及逆温跃层的分布特征和季节变化。通过数值实验发现，若无长江、黄河淡水输入，则在整个研究海域基本无逆温跃层出现，因此陆源淡水可能是河口附近逆温跃层出现的基本因素之一。长江以及暖流（黑潮和台湾暖流）流量的增加，均可在不同程度上使逆温跃层出现概率及强度、深度和厚度增加，且暖流的影响更加明显。长江对东南沿海逆温跃层的出现，特别是秋季到冬季初期，有明显的影响，使长江口海域逆温跃层位置偏向东南。暖流对于中国东南沿海的逆温跃层结构，特别是初春时期，有较大影响，使长江口海域的逆温跃层位置向东北偏移。 通过对温跃层长期变化分析得出，黄海冷水团区域，夏季温跃层强度存在3.8年左右的年际变化及18.9年左右的年代际变化，此变化可能主要表现为对当年夏季和前冬东亚地区大气气温的热力响应。东海冷涡区域，夏季温跃层强度存在3.7年的年际变化，在El Nino年为正的强度异常，其可能主要受局地气旋式大气环流变异所影响。谱分析同时表明，该海域夏季温跃层强度还存在33.2年的年代际变化，上世纪70年代中期，温跃层强度由弱转强，而此变化可能与黑潮流量的年代际变化有关。 海洋水温垂直结构的统计预报结果显示，EOF分解的前四个主分量即能够解释原空间点温度距平总方差的95%以上，以海洋表层附近观测资料求解的特征系数推断温度垂直结构分布的结果最稳定。利用东海陆架区、南海深水区和台湾周边海域三个不同区域的实测CTD样本廓线资料，对重构模型的检验结果表明，重构与实测廓线的相关程度超过95%的置信水平。三个区重构与实测温度廓线值的平均误差分别为0.69℃，0.52℃，1.18℃，平均重构廓线误差小于平均气候偏差，统计模式可以很好的估算温度廓线垂直结构。东海陆架海区温度垂直重构廓线与CTD观测廓线获得的温跃层结果对比表明，重构温跃层上界、下界深度和强度的平均绝对误差分别为1.51m、1.36m和0.17℃/m，它们的平均相对误差分别为24.7%、8.9%和22.6%，虽然温跃层深度和强度的平均相对误差较大，但其绝对误差量值较小。而在南海海区，模型重构温跃层上界、下界和强度的平均绝对预报误差分别为4.1m、27.7m和0.007℃/m，它们的平均相对误差分别为16.1%、16.8%和9.5%，重构温跃层各特征值的平均相对误差都在20%以内。虽然南海区温跃层下界深度平均绝对预报误差较大，但相对于温跃层下界深度的空间尺度变化而言（平均温跃层下界深度为168m），平均相对误差仅为16.8%。因此说模型重构的温度廓线可以达到对我国陆架海域、深水区温跃层的较好估算。 基于对历史水文温度廓线观测资料的分析及自主温跃层统计预报模型，研制了实时可利用微机简单、快捷地进行温跃层估算及查询的可视化系统，这是迄今进行大范围海域温跃层统计与实时预报研究的较系统成果。