The scale dependency of variance of total water mixing ratio is explored by analyzing data from a general circulation model (GCM), a numerical weather prediction model (NWP), and large-eddy simulations (LESs). For clarification, direct numerical simulation (DNS) data are additionally included, but the focus is placed on defining a general scaling behavior for scales ranging from global down to cloud resolving. For this, appropriate power-law exponents are determined by calculating and approximating the power density spectrum. The large-scale models (GCM and NWP) show a consistent scaling with a power-law exponent of approximately 22. For the high-resolution LESs, the slope of the power density spectrum shows evidence of being somewhat steeper, although the estimates are more uncertain. Also the transition between resolved and parameterized scales in a current GCM is investigated. Neither a spectral gap nor a strong scale break is found, but a weak scale break at high wavenumbers cannot be excluded. The evaluation of the parameterized total water variance of a state-of-the-art statistical scheme shows that the scale dependency is underestimated by this parameterization. This study and the discovered general scaling behavior emphasize the need for a development of scale-dependent parameterizations.

This study explores the viability of parameter estimation in the comprehensive general circulation model ECHAM6 using ensemble Kalman filter data assimilation techniques. Four closure parameters of the cumulus-convection scheme are estimated using increasingly less idealized scenarios ranging from perfect-model experiments to the assimilation of conventional observations. Updated parameter values from experiments with real observations are used to assess the error of the model state on short 6 h forecasts and on climatological timescales. All parameters converge to their default values in single parameter perfect-model experiments. Estimating parameters simultaneously has a neutral effect on the success of the parameter estimation, but applying an imperfect model deteriorates the assimilation performance. With real observations, single parameter estimation generates the default parameter value in one case, converges to different parameter values in two cases, and diverges in the fourth case. The implementation of the two converging parameters influences the model state: Although the estimated parameter values lead to an overall error reduction on short timescales, the error of the model state increases on climatological timescales.

In this paper we analyse aerosol loading and its direct radiative effects over the Bay of Bengal (BoB) and Arabian Sea (AS) regions for the Integrated Campaign on Aerosols, gases and Radiation Budget (ICARB) undertaken during 2006, using satellite data from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, the Aerosol Index from the Ozone Monitoring Instrument (OMI) on board the Aura satellite, and the European-Community Hamburg (ECHAM5.5) general circulation model extended by Hamburg Aerosol Module (HAM). By statistically comparing with large-scale satellite data sets, we firstly show that the aerosol properties measured during the ship-based ICARB campaign and simulated by the model are representative for the BoB and AS regions and the pre-monsoon season. In a second step, the modelled aerosol distributions were evaluated by a comparison with the measurements from the ship-based sunphotometer, and the satellite retrievals during ICARB. It is found that the model broadly reproduces the observed spatial and temporal variability in aerosol optical depth (AOD) over BoB and AS regions. However, AOD was systematically underestimated during high-pollution episodes, especially in the BoB leg. We show that this underprediction of AOD is mostly because of the deficiencies in the coarse mode, where the model shows that dust is the dominant component. The analysis of dust AOD along with the OMI Aerosol Index indicate that missing dust transport that results from too low dust emission fluxes over the Thar Desert region in the model caused this deficiency. Thirdly, we analysed the spatio-temporal variability of AOD comparing the ship-based observations to the large-scale satellite observations and simulations. It was found that most of the variability along the track was from geographical patterns, with a minor influence by single events. Aerosol fields were homogeneous enough to yield a good statistical agreement between satellite data at a 1° spatial, but only twice-daily temporal resolution, and the shipbased sunphotometer data at a much finer spatial, but dailyaverage temporal resolution. Examination of the satellite data further showed that the year 2006 is representative for the five-year period for which satellite data were available. Finally, we estimated the clear-sky solar direct aerosol radiative forcing (DARF). We found that the cruise represents well the regional-seasonal mean forcings. Constraining simulated forcings using the observed AOD distributions yields a robust estimate of regional-seasonal mean DARF of −8.6, −21.4 and +12.9Wm−2 at the top of the atmosphere (TOA), at the surface (SUR) and in the atmosphere (ATM), respectively, for the BoB region, and over the AS, of, −6.8, −12.8, and +6Wm−2 at TOA, SUR, and ATM, respectively.

Observations from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud Feedback Model Intercomparison Project’s Observation Simulator Package are used. Comparison of ECHAM5 with CALIPSO and CloudSat found large-scale features resolved by the model, such as the Hadley circulation, are captured well. The lidar simulator demonstrated ECHAM5 overestimates the amount of high-level clouds, particularly optically thin clouds. High-altitude clouds in ECHAM5 consistently produced greater lidar scattering ratios compared with CALIPSO. Consequently, the lidar signal in ECHAM5 frequently attenuated high in the atmosphere. The large scattering ratios were due to an underestimation of effective ice crystal radii in ECHAM5. Doubling the effective ice crystal radii improved the scattering ratios and frequency of attenuation. Additionally, doubling the effective ice crystal radii improved the detection of ECHAM5’s highest-level clouds by the radar simulator, in better agreement with CloudSat. ECHAM5 was also shown to significantly underestimate midlevel clouds and (sub)tropical low-level clouds. The low-level clouds produced were consistently perceived by the lidar simulator as too optically thick. The radar simulator demonstrated ECHAM5 overestimates the frequency of precipitation, yet underestimates its intensity compared with CloudSat observations. These findings imply compensating mechanisms inECHAM5 balance out the radiative imbalance caused by incorrect optical properties of clouds and consistently large hydrometeors in the atmosphere.

The 2013 meeting of the Intergovernmental Panel on Climate Change concluded that the coupling of clouds to the Earth's climate is one of the biggest uncertainties faced in predicting climate change today. Cirrus clouds are of particular interest because the extensive variability in particle size, shape and complexity poses a number of challenges in the accurate modelling of optical properties. The dependence of the single-scattering properties on particle shape demand accurate representation of the crystal geometries in scattering models, geometries which can vary from simple hexagonal prisms to complex multi-branched aggregates. This work, presented as a series of papers, uses laboratory studies to investigate the single scattering properties of ice crystals. Of particular focus here are columns with internal cavities. The first paper investigates the phase function, P11 and asymmetry parameter, g of varying crystal habits, whilst the second paper focuses on polarised scattering. One of the main findings is the difference in internal structure between hollow columns grown at warmer temperatures (-7 degrees C) and those grown at colder temperatures (-30 degrees C). Measurements were used to create new particle geometries for use in scattering models. The third paper makes use of findings from papers 1 & 2 to create an optical parametrization for cirrus, utilizing the new particle geometry.

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Cette thèse porte sur l'agrégation de la convection dans le modèle de circulation générale LMDZ5A à l'équilibre radiatif-convectif (RCE). L'instabilité du RCE mise en évidence nous permet d'étudier les mécanismes d'initiation de l'agrégation et leur dépendance à la température de surface océanique (SST). A basse SST, l'agrégation résulte d'un couplage entre la circulation grande-échelle et les effets radiatifs des nuages bas. A haute SST, elle provient d'un couplage entre la circulation de grande-échelle et les flux turbulents à la surface. Le couplage de l'atmosphère avec une couche de mélange océanique rend l'initiation de l'agrégation moins dépendante de la SST et des mécanismes d'initiation, à l'exception des effets radiatifs des nuages hauts. L'impact de l'agrégation sur la sensibilité climatique et la température de surface est aussi analysé. En favorisant la formation de zones ciel clair sèches, l'agrégation refroidit fortement le système climatique. Toutefois, cet effet est limité par l'effet des changements de gradients de SST et de fraction de nuages bas qui tendent au contraire à faire augmenter la sensibilité climatique. Aux plus courtes échelles temporelles, en revanche, le couplage entre océan et agrégation de la convection est à l'origine d'une boucle de rétroaction stabilisatrice qui contrôle l'agrégation et renverse complètement son effet. Ainsi, l'effet de l'agrégation sur la sensibilité climatique est assez faible par rapport à ce que laissent penser les simulations où le couplage océan-atmosphère est absent. Ces résultats montrent l'importance de considérer le couplage océan-atmosphère dans l'étude du rôle de l'agrégation dans le climat. / This thesis focuses on the study of convective aggregation in LMDZ5A general circulation model, used in Radiative-Convective Equilibrium (RCE) configuration. The instability of the RCE allows us to look at the mechanisms controlling the initiation of convective aggregation and its dependence on sea surface temperatures (SST). At low SSTs, a coupling between the large-scale circulation and the radiative effects of low clouds is needed to trigger self-aggregation. At high SSTs, the coupling between the large-scale circulation and the surface fluxes controls this initiation. When the atmosphere is coupled to a slab ocean mixed layer, SST gradients facilitate the initiation of convective aggregation. Except for the high-cloud radiative effects, triggering mechanisms are less crucial. Convection also becomes less dependent on the SST.The impact of convective aggregation on the climate sensitivity and surface temperature is also analyzed. Convective aggregation is found to increase the area of dry clear-sky zones. Thus, it tends to cool the system very efficiently. However, the negative feedback associated with an increase in aggregation is generally balanced by offsetting changes in SST gradients and low clouds that tend to increase the climate sensitivity. In contrast, at shorter timescales, the coupling between ocean and convective aggregation also controls the strength of convective aggregation and overturn its effect. Thus the impact of convective aggregation may not be as strong as what can be inferred from experiments with uniform SSTs.These results emphasize the importance of considering ocean-atmosphere coupling when studying the role of aggregation in climate.

This thesis is dedicated to communication with lost mobile device throw the Internet with its owner because of the possibility of finding, return or lock the device. It focused on analysis existing solution and draft own mobile application for Android platform with supportive web application, This thesis also summary basic principles of creating application for Android OS and communication with cloud base service Google Cloud Messaging.

With increasing awareness of potential security threats there is a growing interest in communication security for spacecraft control and data. Traditionally commercial and scientific missions have relied on their uniqueness to prevent security breaches. During time the market has changed with open systems for mission control and data distribution, increased connectivity and the use of existing and shared infrastructure. Therefore security layers are being introduced to protect spacecraft communication. In order to mitigate the perceived threats, the Consultative Committee for Space Data Systems (CCSDS) has proposed the addition of communication security in the various layers of the communication model. This thesis describes and discuss their proposal and look into how this application should be implemented into the data link layer of the communication protocol to protect from timing attacks. An implementation of AES-CTR+GMAC is constructed in software to compare different key lengths and another implementation is constructed in synthesized VHDL for use on hardware to investigate the impact on area consumption on the FPGA as well as if it is possible to secure it from cache-timing attacks.

In the present work, we investigate the capacity of machine learning to reconstruct simulated large scale surface temperature anomalies given a sparse observation field. Several methods are combined: self-organizing maps and recurrent neural networks of the temporal trajectory. To evaluate our global scale reconstruction, we base our validation on global climate indices time series and EOF analysis. In our experiments, the obtained reconstructions of the global surface temperature anomalies provide a good correlation (over 90%) with the target values when considering scarce available observations sampling about 0.5% of the globe. We reconstruct the surface temperature anomaly fields from 0.05% of total number of data points. We obtain an RMSE of 0.39°C. We further validate the quality of the results calculating a correlation of 0.92, 0.97 and 0.98 between the reconstructed and target indices of AMO, ENSO and IPO. / Klimatsystemet består av olika komponenter inklusive atmosfären, havet och jorden. Som ett öppet system utbyter det hela tiden energi med resten av universum. Det är också ett dynamiskt system vars utveckling kan förutsägas av kända fysiska lagar. Interaktionen mellan dess olika komponenter leder till en så kallad naturlig variation. Denna variabilitet återspeglas i form av svängningslägen, inklusive AMO, ENSO och IPO. För att studera dessa variationer har vi klimatmodeller som representerar de olika krafterna och deras effekt på klimatförändringar på lång sikt. I detta sammanhang är variationerna i det förflutna klimatet särskilt intressanta och tillåter oss en bättre förståelse av klimatförändringar och bättre förutsäga den framtida utvecklingen. Men för att studera det förflutna klimatet eller paleoklimat är den enda tillgängliga informationen endast fullständig under de senaste 150 åren. Innan dess är de enda tillgängliga indikatorerna naturliga, kallad klimatproxy, som trädringar eller iskärnor. Vi kan härleda tidsserier med klimatdata, till exempel temperatur. Denna information är emellertid knappast tillfälligt såväl som över hela världen. Återskapa det globala klimatet från sådana data hanteras fortfarande dåligt. Länken mellan lokal information och global klimat studeras här med hjälp av statistiska metoder, inklusive neurala nätverk. Det långsiktiga målet med denna studie är att bygga en metod för att rekonstruera paleoklimatet från data om klimatproxy, vi fokuserar inledningsvis på rekonstruktionen av ett så kallat perfekt klimat, det vill säga en modell som endast tar hänsyn till naturlig variation, från rumsligt sällsynta tidsserier. De studerade uppgifterna är de från globala yttemperaturutgångar från den havsatmosfärkopplade IPSL-modellen. Uppgifterna förbehandlas för att ta bort säsongens genomsnittliga cykel och omvandlas till temperaturavvikelser. Dessutom väljs rutnätpunkter som representerar information om proxyer pseudo-slumpmässigt, med respekt för den verkliga dispositionen av dessa, övervägande i norr på kontinenterna. Uppgifterna delas upp i träningsdata (150 år), validering (30 år) och testdata (120 år). De metoder som används kombinerar (1) självorganiserande kartor och hierarkisk stigande klassificering, användbara för att producera en reducerad storlek av inmatningsdata, här baserat på tidskorrelationen mellan temperaturutvecklingen under 150 år, (2) ItCompSOM använder korrelationen mellan klasser erhållna genom självorganiserande kartor för att rekonstruera obevakad data, (3) återkommande nervnätverk för att förklara den temporära komponenten i data och förbättra den tidigare rekonstruktionen. Slutligen är definitionen av nya mätvärden nödvändig för att validera de föreslagna modellerna. Utvärderingen av produkterna görs således genom temporär rekonstruktion av AMO, ENSO, IPO klimatlägen samt genom projicering av huvudkomponenterna i analysen av huvudkomponenterna i inputdata. Således konstrueras en reducerad modell av globala temperaturdata baserad på 150 års fullständiga data först, vilket reducerar den rumsliga informationen från 9216 rutnätpunkter till 191 regioner associerade med 1 medelvärde vardera. För att ansluta denna modell till tidssekvenser av sällsynta temperaturer i världen antas det att varje klass som innefattar minst en observerad proxy-data är känd. Rekonstruktionen av globala yttemperaturutvecklingar med ItCompSOM ger en korrelation till indexen på mer än 90% för endast 0,5% av de initiala observationerna. Detta resultat förbättras kraftigt tack vare återkommande nervnätverk, vilket leder till en korrelation av 0,92, 0,97 respektive 0,98 för AMO, ENSO och IPO med endast 0,05% av observationerna. Dessa poäng förklaras med den använda metoden, regionaliseringen hjälper till att koncentrera informationen. Medan 0,5% av rutpunkterna är lika med 43 poäng, om de är korrekt fördelade, representerar de 22% av informationen om regionerna (43 av 191). Dessa mycket uppmuntrande resultat återstår att tillämpas på verkliga klimatproblem, det vill säga med hänsyn till å ena sidan den externa och antropologiska kraften, osäkerheterna relaterade till de verkliga uppgifterna om ombud å andrasidan.