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.

On the use of weather radar for mesoscale applications in northern conditions

Mesoscale weather phenomena, such as the sea breeze circulation or lake effect snow bands, are typically too large to be observed at one point, yet too small to be caught in a traditional network of weather stations. Hence, the weather radar is one of the best tools for observing, analyzing and understanding their behavior and development. A weather radar network is a complex system, which has many structural and technical features to be tuned, from the location of each radar to the number of pulses averaged in the signal processing. These design parameters have no universal optimal values, but their selection depends on the nature of the weather phenomena to be monitored as well as on the applications for which the data will be used. The priorities and critical values are different for forest fire forecasting, aviation weather service or the planning of snow ploughing, to name a few radar-based applications. The main objective of the work performed within this thesis has been to combine knowledge of technical properties of the radar systems and our understanding of weather conditions in order to produce better applications able to efficiently support decision making in service duties for modern society related to weather and safety in northern conditions. When a new application is developed, it must be tested against ground truth . Two new verification approaches for radar-based hail estimates are introduced in this thesis. For mesoscale applications, finding the representative reference can be challenging since these phenomena are by definition difficult to catch with surface observations. Hence, almost any valuable information, which can be distilled from unconventional data sources such as newspapers and holiday shots is welcome. However, as important as getting data is to obtain estimates of data quality, and to judge to what extent the two disparate information sources can be compared. The presented new applications do not rely on radar data alone, but ingest information from auxiliary sources such as temperature fields. The author concludes that in the future the radar will continue to be a key source of data and information especially when used together in an effective way with other meteorological data.

Stone Weathering in the Monastic Building Complex on Mountain of St Aaron in Petra, Jordan.

Since 1997 the Finnish Jabal Haroun Project (FJHP) has studied the ruins of the monastery and pilgrimage complex (Gr. oikos) of Aaron located on a plateau of the Mountain of Prophet Aaron, Jabal an-Nabi Harûn, ca. 5 km to the south-west of the UNESCO World Heritage site of Petra in Jordan. The state of conservation and the damaging processes affecting the stone structures of the site are studied in this M.A. thesis. The chapel was chosen as an example, as it represents the phasing and building materials of the entire site. The aim of this work is to act as a preliminary study with regards to the planning of long-term conservation at the site. The research is empirical in nature. The condition of the stones in the chapel walls was mapped using the Illustrated Glossary on Stone Deterioration, by the ICOMOS International Scientific Committee for Stone. This glossary combines several standards and systems of damage mapping used in the field. Climatic conditions (temperature and RH %) were monitored for one year (9/2005-8/2006) using a HOBO Microstation datalogger. The measurements were compared with contemporary measurements from the nearest weather station in Wadi Musa. Salts in the stones were studied by taking samples from the stone surfaces by scraping and with the “Paper Pulp”-method; with a poultice of wet cellulose fiber (Arbocel BC1000) and analyzing what main types of salts were to be found in the samples. The climatic conditions on the mountain were expected to be rapidly changing and to differ clearly from conditions in the neighboring areas. The rapid changes were confirmed, but the values did not differ as much as expected from those nearby: the 12 months monitored had average temperatures and were somewhat drier than average. Earlier research in the area has shown that the geological properties of the stone material influence its deterioration. The damage mapping showed clearly, that salts are also a major reason for stone weathering. The salt samples contained several salt combinations, whose behavior in the extremely unstable climatic conditions is difficult to predict. Detailed mapping and regular monitoring of especially the structures, that are going remain exposed, is recommended in this work.

Fuel conditions and fire behavior characteristics of managed Picea abies and Pinus sylvestris forests in Finland

The objectives of this study were to analyze the impact of structural stand characteristics on ignition potential, surface fuel moisture, and fire behavior in Pinus sylvestris L. and Picea abies (L.) Karst stands in Finland and to explain stand-specific fire danger using the Canadian Fire Weather Index System and the Finnish Fire Risk Index. Additionally, the study analyzes the relationship between observed fire activity and fire weather indices at different stages of growing season. Field experiments were carried out in Pinus sylvestris or Picea abies dominated stands during fire seasons 2001 and 2002. Observations on ignition potential, fuel moisture, and fire behavior were analyzed in relation to stand structure and the outputs of the Finnish and Canadian fire weather indices. Seasonal patterns of fire activity were examined based on national fire statistics 1996 2003, effective temperature sum, and the fire weather indices. Point fire ignition potential was highest in Pinus clear-cuts and lowest in closed Picea stands. Moss-dominated surface fuels were driest in clear-cut and sapling stage stands and presented the highest moisture content under closed Picea canopy. Pinus sylvestris stands carried fire under a wide range of fire weather conditions under which Picea abies stands failed to sustain fire. In the national fire records, the daily number of reported ignitions presented its highest value during late fire season whereas the daily area burned peaked most substantially during early season. The fire weather indices correlated significantly with ignition potential and fuel moisture but were unable to explain fire behavior in the experimental fires. During the initial and final stages of the growing season, fire activity was disconnected from weather-based fire danger ratings. Information on stand structure and season stage would benefit the assessment of fire danger in Finnish forest landscape for fire suppression and controlled burning purposes.

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.

Wind drift of snowfall between the radar volume and ground

This study evaluates how the advection of precipitation, or wind drift, between the radar volume and ground affects radar measurements of precipitation. Normally precipitation is assumed to fall vertically to the ground from the contributing volume, and thus the radar measurement represents the geographical location immediately below. In this study radar measurements are corrected using hydrometeor trajectories calculated from measured and forecasted winds, and the effect of trajectory-correction on the radar measurements is evaluated. Wind drift statistics for Finland are compiled using sounding data from two weather stations spanning two years. For each sounding, the hydrometeor phase at ground level is estimated and drift distance calculated using different originating level heights. This way the drift statistics are constructed as a function of range from radar and elevation angle. On average, wind drift of 1 km was exceeded at approximately 60 km distance, while drift of 10 km was exceeded at 100 km distance. Trajectories were calculated using model winds in order to produce a trajectory-corrected ground field from radar PPI images. It was found that at the upwind side from the radar the effective measuring area was reduced as some trajectories exited the radar volume scan. In the downwind side areas near the edge of the radar measuring area experience improved precipitation detection. The effect of trajectory-correction is most prominent in instant measurements and diminishes when accumulating over longer time periods. Furthermore, measurements of intensive and small scale precipitation patterns benefit most from wind drift correction. The contribution of wind drift on the uncertainty of estimated Ze (S) - relationship was studied by simulating the effect of different error sources to the uncertainty in the relationship coefficients a and b. The overall uncertainty was assumed to consist of systematic errors of both the radar and the gauge, as well as errors by turbulence at the gauge orifice and by wind drift of precipitation. The focus of the analysis is error associated with wind drift, which was determined by describing the spatial structure of the reflectivity field using spatial autocovariance (or variogram). This spatial structure was then used with calculated drift distances to estimate the variance in radar measurement produced by precipitation drift, relative to the other error sources. It was found that error by wind drift was of similar magnitude with error by turbulence at gauge orifice at all ranges from radar, with systematic errors of the instruments being a minor issue. The correction method presented in the study could be used in radar nowcasting products to improve the estimation of visibility and local precipitation intensities. The method however only considers pure snow, and for operational purposes some improvements are desirable, such as melting layer detection, VPR correction and taking solid state hydrometeor type into account, which would improve the estimation of vertical velocities of the hydrometeors.

A Critical Assesment of Occluded Fronts

The aim of this work was the assessment about the structure and use of the conceptual model of occlusion in operational weather forecasting. In the beginning a survey has been made about the conceptual model of occlusion as introduced to operational forecasters in the Finnish Meteorological Institute (FMI). In the same context an overview has been performed about the use of the conceptual model in modern operational weather forecasting, especially in connection with the widespread use of numerical forecasts. In order to evaluate the features of the occlusions in operational weather forecasting, all the occlusion processes occurring during year 2003 over Europe and Northern Atlantic area have been investigated using the conceptual model of occlusion and the methods suggested in the FMI. The investigation has yielded a classification of the occluded cyclones on the basis of the extent the conceptual model has fitted the description of the observed thermal structure. The seasonal and geographical distribution of the classes has been inspected. Some relevant cases belonging to different classes have been collected and analyzed in detail: in this deeper investigation tools and techniques, which are not routinely used in operational weather forecasting, have been adopted. Both the statistical investigation of the occluded cyclones during year 2003 and the case studies have revealed that the traditional classification of the types of the occlusion on the basis of the thermal structure doesn t take into account the bigger variety of occlusion structures which can be observed. Moreover the conceptual model of occlusion has turned out to be often inadequate in describing well developed cyclones. A deep and constructive revision of the conceptual model of occlusion is therefore suggested in light of the result obtained in this work. The revision should take into account both the progresses which are being made in building a theoretical footing for the occlusion process and the recent tools and meteorological quantities which are nowadays available.