An analysis of MONTBLEX data on heat and momentum flux at Jodhpur

Parameterization of sensible heat and momentum fluxes as inferred from an analysis of tower observations archived during MONTBLEX-90 at Jodhpur is proposed, both in terms of standard exchange coefficients C-H and C-D respectively and also according to free convection scaling. Both coefficients increase rapidly at low winds (the latter more strongly) and with increasing instability. All the sensible heat flux data at Jodhpur (wind speed at 10m <(U)over bar (10)>, < 8ms(-1)) also obey free convection scaling, with the flux proportional to the '4/3' power of an appropriate temperature difference such as that between 1 and 30 m. Furthermore, for <(U)over bar (10)> < 4 ms(-1) the momentum flux displays a linear dependence on wind speed.

Essays on socially optimal phosphorus policies in crop production

Phosphorus is a nutrient needed in crop production. While boosting crop yields it may also accelerate eutrophication in the surface waters receiving the phosphorus runoff. The privately optimal level of phosphorus use is determined by the input and output prices, and the crop response to phosphorus. Socially optimal use also takes into account the impact of phosphorus runoff on water quality. Increased eutrophication decreases the economic value of surface waters by Deteriorating fish stocks, curtailing the potential for recreational activities and by increasing the probabilities of mass algae blooms. In this dissertation, the optimal use of phosphorus is modelled as a dynamic optimization problem. The potentially plant available phosphorus accumulated in soil is treated as a dynamic state variable, the control variable being the annual phosphorus fertilization. For crop response to phosphorus, the state variable is more important than the annual fertilization. The level of this state variable is also a key determinant of the runoff of dissolved, reactive phosphorus. Also the loss of particulate phosphorus due to erosion is considered in the thesis, as well as its mitigation by constructing vegetative buffers. The dynamic model is applied for crop production on clay soils. At the steady state, the analysis focuses on the effects of prices, damage parameterization, discount rate and soil phosphorus carryover capacity on optimal steady state phosphorus use. The economic instruments needed to sustain the social optimum are also analyzed. According to the results the economic incentives should be conditioned on soil phosphorus values directly, rather than on annual phosphorus applications. The results also emphasize the substantial effects the differences in varying discount rates of the farmer and the social planner have on optimal instruments. The thesis analyzes the optimal soil phosphorus paths from its alternative initial levels. It also examines how erosion susceptibility of a parcel affects these optimal paths. The results underline the significance of the prevailing soil phosphorus status on optimal fertilization levels. With very high initial soil phosphorus levels, both the privately and socially optimal phosphorus application levels are close to zero as the state variable is driven towards its steady state. The soil phosphorus processes are slow. Therefore, depleting high phosphorus soils may take decades. The thesis also presents a methodologically interesting phenomenon in problems of maximizing the flow of discounted payoffs. When both the benefits and damages are related to the same state variable, the steady state solution may have an interesting property, under very general conditions: The tail of the payoffs of the privately optimal path as well as the steady state may provide a higher social welfare than the respective tail of the socially optimal path. The result is formalized and an applied to the created framework of optimal phosphorus use.

Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Contribution of geophysical surveys to groundwater modelling of a porous aquifer in semiarid Niger: An overview

Subsurface geophysical surveys were carried out using a large range of methods in an unconfined sandstone aquifer in semiarid south-western Niger for improving both the conceptual model of water flow through the unsaturated zone and the parameterization of numerical a groundwater model of the aquifer. Methods included: electromagnetic mapping, electrical resistivity tomography (ERT), resistivity logging, time domain electromagnetic sounding (TDEM), and magnetic resonance sounding (MRS). Analyses of electrical conductivities, complemented by geochemical measurements, allowed us to identify preferential pathways for infiltration and drainage beneath gullies and alluvial fans. The mean water content estimated by MRS (13%) was used for computing the regional groundwater recharge from long-term change in the water table. The ranges in permeability and water content obtained with MRS allowed a reduction of the degree of freedom of aquifer parameters used in groundwater modelling.

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.

Aerosol size distribution and its connection to cloud droplet number concentration

In order to predict the current state and future development of Earth s climate, detailed information on atmospheric aerosols and aerosol-cloud-interactions is required. Furthermore, these interactions need to be expressed in such a way that they can be represented in large-scale climate models. The largest uncertainties in the estimate of radiative forcing on the present day climate are related to the direct and indirect effects of aerosol. In this work aerosol properties were studied at Pallas and Utö in Finland, and at Mount Waliguan in Western China. Approximately two years of data from each site were analyzed. In addition to this, data from two intensive measurement campaigns at Pallas were used. The measurements at Mount Waliguan were the first long term aerosol particle number concentration and size distribution measurements conducted in this region. They revealed that the number concentration of aerosol particles at Mount Waliguan were much higher than those measured at similar altitudes in other parts of the world. The particles were concentrated in the Aitken size range indicating that they were produced within a couple of days prior to reaching the site, rather than being transported over thousands of kilometers. Aerosol partitioning between cloud droplets and cloud interstitial particles was studied at Pallas during the two measurement campaigns, First Pallas Cloud Experiment (First PaCE) and Second Pallas Cloud Experiment (Second PaCE). The method of using two differential mobility particle sizers (DMPS) to calculate the number concentration of activated particles was found to agree well with direct measurements of cloud droplet. Several parameters important in cloud droplet activation were found to depend strongly on the air mass history. The effects of these parameters partially cancelled out each other. Aerosol number-to-volume concentration ratio was studied at all three sites using data sets with long time-series. The ratio was found to vary more than in earlier studies, but less than either aerosol particle number concentration or volume concentration alone. Both air mass dependency and seasonal pattern were found at Pallas and Utö, but only seasonal pattern at Mount Waliguan. The number-to-volume concentration ratio was found to follow the seasonal temperature pattern well at all three sites. A new parameterization for partitioning between cloud droplets and cloud interstitial particles was developed. The parameterization uses aerosol particle number-to-volume concentration ratio and aerosol particle volume concentration as the only information on the aerosol number and size distribution. The new parameterization is computationally more efficient than the more detailed parameterizations currently in use, but the accuracy of the new parameterization was slightly lower. The new parameterization was also compared to directly observed cloud droplet number concentration data, and a good agreement was found.

Numerical approaches to new particle formation and growth in the atmosphere

Aerosols impact the planet and our daily lives through various effects, perhaps most notably those related to their climatic and health-related consequences. While there are several primary particle sources, secondary new particle formation from precursor vapors is also known to be a frequent, global phenomenon. Nevertheless, the formation mechanism of new particles, as well as the vapors participating in the process, remain a mystery. This thesis consists of studies on new particle formation specifically from the point of view of numerical modeling. A dependence of formation rate of 3 nm particles on the sulphuric acid concentration to the power of 1-2 has been observed. This suggests nucleation mechanism to be of first or second order with respect to the sulphuric acid concentration, in other words the mechanisms based on activation or kinetic collision of clusters. However, model studies have had difficulties in replicating the small exponents observed in nature. The work done in this thesis indicates that the exponents may be lowered by the participation of a co-condensing (and potentially nucleating) low-volatility organic vapor, or by increasing the assumed size of the critical clusters. On the other hand, the presented new and more accurate method for determining the exponent indicates high diurnal variability. Additionally, these studies included several semi-empirical nucleation rate parameterizations as well as a detailed investigation of the analysis used to determine the apparent particle formation rate. Due to their high proportion of the earth's surface area, oceans could potentially prove to be climatically significant sources of secondary particles. In the lack of marine observation data, new particle formation events in a coastal region were parameterized and studied. Since the formation mechanism is believed to be similar, the new parameterization was applied in a marine scenario. The work showed that marine CCN production is feasible in the presence of additional vapors contributing to particle growth. Finally, a new method to estimate concentrations of condensing organics was developed. The algorithm utilizes a Markov chain Monte Carlo method to determine the required combination of vapor concentrations by comparing a measured particle size distribution with one from an aerosol dynamics process model. The evaluation indicated excellent agreement against model data, and initial results with field data appear sound as well.

Parametrized actor-critic algorithms for finite-horizon MDPs

Due to their non-stationarity, finite-horizon Markov decision processes (FH-MDPs) have one probability transition matrix per stage. Thus the curse of dimensionality affects FH-MDPs more severely than infinite-horizon MDPs. We propose two parametrized 'actor-critic' algorithms to compute optimal policies for FH-MDPs. Both algorithms use the two-timescale stochastic approximation technique, thus simultaneously performing gradient search in the parametrized policy space (the 'actor') on a slower timescale and learning the policy gradient (the 'critic') via a faster recursion. This is in contrast to methods where critic recursions learn the cost-to-go proper. We show w.p 1 convergence to a set with the necessary condition for constrained optima. The proposed parameterization is for FHMDPs with compact action sets, although certain exceptions can be handled. Further, a third algorithm for stochastic control of stopping time processes is presented. We explain why current policy evaluation methods do not work as critic to the proposed actor recursion. Simulation results from flow-control in communication networks attest to the performance advantages of all three algorithms.

Factors controlling the surface energy budget over snow and ice

Polar Regions are an energy sink of the Earth system, as the Sun rays do not reach the Poles for half of the year, and hit them only at very low angles for the other half of the year. In summer, solar radiation is the dominant energy source for the Polar areas, therefore even small changes in the surface albedo strongly affect the surface energy balance and, thus, the speed and amount of snow and ice melting. In winter, the main heat sources for the atmosphere are the cyclones approaching from lower latitudes, and the atmosphere-surface heat transfer takes place through turbulent mixing and longwave radiation, the latter dominated by clouds. The aim of this thesis is to improve the knowledge about the surface and atmospheric processes that control the surface energy budget over snow and ice, with particular focus on albedo during the spring and summer seasons, on horizontal advection of heat, cloud longwave forcing, and turbulent mixing during the winter season. The critical importance of a correct albedo representation in models is illustrated through the analysis of the causes for the errors in the surface and near-surface air temperature produced in a short-range numerical weather forecast by the HIRLAM model. Then, the daily and seasonal variability of snow and ice albedo have been examined by analysing field measurements of albedo, carried out in different environments. On the basis of the data analysis, simple albedo parameterizations have been derived, which can be implemented into thermodynamic sea ice models, as well as numerical weather prediction and climate models. Field measurements of radiation and turbulent fluxes over the Bay of Bothnia (Baltic Sea) also allowed examining the impact of a large albedo change during the melting season on surface energy and ice mass budgets. When high contrasts in surface albedo are present, as in the case of snow covered areas next to open water, the effect of the surface albedo heterogeneity on the downwelling solar irradiance under overcast condition is very significant, although it is usually not accounted for in single column radiative transfer calculations. To account for this effect, an effective albedo parameterization based on three-dimensional Monte Carlo radiative transfer calculations has been developed. To test a potentially relevant application of the effective albedo parameterization, its performance in the ground-based retrieval of cloud optical depth was illustrated. Finally, the factors causing the large variations of the surface and near-surface temperatures over the Central Arctic during winter were examined. The relative importance of cloud radiative forcing, turbulent mixing, and lateral heat advection on the Arctic surface temperature were quantified through the analysis of direct observations from Russian drifting ice stations, with the lateral heat advection calculated from reanalysis products.

Carbon dioxide and methane exchange between a boreal pristine lake and the atmosphere

Lakes serve as sites for terrestrially fixed carbon to be remineralized and transferred back to the atmosphere. Their role in regional carbon cycling is especially important in the Boreal Zone, where lakes can cover up to 20% of the land area. Boreal lakes are often characterized by the presence of a brown water colour, which implies high levels of dissolved organic carbon from the surrounding terrestrial ecosystem, but the load of inorganic carbon from the catchment is largely unknown. Organic carbon is transformed to methane (CH4) and carbon dioxide (CO2) in biological processes that result in lake water gas concentrations that increase above atmospheric equilibrium, thus making boreal lakes as sources of these important greenhouse gases. However, flux estimates are often based on sporadic sampling and modelling and actual flux measurements are scarce. Thus, the detailed temporal flux dynamics of greenhouse gases are still largely unknown. ----- One aim here was to reveal the natural dynamics of CH4 and CO2 concentrations and fluxes in a small boreal lake. The other aim was to test the applicability of a measuring technique for CO2 flux, i.e. the eddy covariance (EC) technique, and a computational method for estimation of primary production and community respiration, both commonly used in terrestrial research, in this lake. Continuous surface water CO2 concentration measurements, also needed in free-water applications to estimate primary production and community respiration, were used over two open water periods in a study of CO2 concentration dynamics. Traditional methods were also used to measure gas concentration and fluxes. The study lake, Valkea-Kotinen, is a small, humic, headwater lake within an old-growth forest catchment with no local anthropogenic disturbance and thus possible changes in gas dynamics reflect the natural variability in lake ecosystems. CH4 accumulated under the ice and in the hypolimnion during summer stratification. The surface water CH4 concentration was always above atmospheric equilibrium and thus the lake was a continuous source of CH4 to the atmosphere. However, the annual CH4 fluxes were small, i.e. 0.11 mol m-2 yr-1, and the timing of fluxes differed from that of other published estimates. The highest fluxes are usually measured in spring after ice melt but in Lake Valkea-Kotinen CH4 was effectively oxidised in spring and highest effluxes occurred in autumn after summer stratification period. CO2 also accumulated under the ice and the hypolimnetic CO2 concentration increased steadily during stratification period. The surface water CO2 concentration was highest in spring and in autumn, whereas during the stable stratification it was sometimes under atmospheric equilibrium. It showed diel, daily and seasonal variation; the diel cycle was clearly driven by light and thus reflected the metabolism of the lacustrine ecosystem. However, the diel cycle was sometimes blurred by injection of hypolimnetic water rich in CO2 and the surface water CO2 concentration was thus controlled by stratification dynamics. The highest CO2 fluxes were measured in spring, autumn and during those hypolimnetic injections causing bursts of CO2 comparable with the spring and autumn fluxes. The annual fluxes averaged 77 (±11 SD) g C m-2 yr-1. In estimating the importance of the lake in recycling terrestrial carbon, the flux was normalized to the catchment area and this normalized flux was compared with net ecosystem production estimates of -50 to 200 g C m-2 yr-1 from unmanaged forests in corresponding temperature and precipitation regimes in the literature. Within this range the flux of Lake Valkea-Kotinen yielded from the increase in source of the surrounding forest by 20% to decrease in sink by 5%. The free water approach gave primary production and community respiration estimates of 5- and 16-fold, respectively, compared with traditional bottle incubations during a 5-day testing period in autumn. The results are in parallel with findings in the literature. Both methods adopted from the terrestrial community also proved useful in lake studies. A large percentage of the EC data was rejected, due to the unfulfilled prerequisites of the method. However, the amount of data accepted remained large compared with what would be feasible with traditional methods. Use of the EC method revealed underestimation of the widely used gas exchange model and suggests simultaneous measurements of actual turbulence at the water surface with comparison of the different gas flux methods to revise the parameterization of the gas transfer velocity used in the models.

Improved retrieval of aerosol size-resolved properties from moderate resolution imaging spectroradiometer over India: Role of aerosol model and surface reflectance

We have compared the total as well as fine mode aerosol optical depth (tau and tau(fine)) retrieved by Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua (2001-2005) with the equivalent parameters derived by Aerosol Robotic Network (AERONET) at Kanpur (26.45 degrees N, 80.35 degrees E), northern India. MODIS Collection 005 (C005)-derived tau(0.55) was found to be in good agreement with the AERONET measurements. The tau(fine) and eta (tau(fine)/tau) were, however, biased low significantly in most matched cases. A new set of retrieval with the use of absorbing aerosol model (SSA similar to 0.87) with increased visible surface reflectance provided improved tau and tau(fine) at Kanpur. The new derivation of eta also compares well qualitatively with an independent set of in situ measurements of accumulation mass fraction over much of the southern India. This suggests that though MODIS land algorithm has limited information to derive size properties of aerosols over land, more accurate parameterization of aerosol and surface properties within the existing C005 algorithm may improve the accuracy of size-resolved aerosol optical properties. The results presented in this paper indicate that there is a need to reconsider the surface parameterization and assumed aerosol properties in MODIS C005 algorithm over the Indian region in order to retrieve more accurate aerosol optical and size properties, which are essential to quantify the impact of human-made aerosols on climate.

Antarctic ice shelf melting and its impact on the global sea ice-ocean system

Earth s ice shelves are mainly located in Antarctica. They cover about 44% of the Antarctic coastline and are a salient feature of the continent. Antarctic ice shelf melting (AISM) removes heat from and inputs freshwater into the adjacent Southern Ocean. Although playing an important role in the global climate, AISM is one of the most important components currently absent in the IPCC climate model. In this study, AISM is introduced into a global sea ice-ocean climate model ORCA2-LIM, following the approach of Beckmann and Goosse (2003; BG03) for the thermodynamic interaction between the ice shelf and ocean. This forms the model ORCA2-LIM-ISP (ISP: ice shelf parameterization), in which not only all the major Antarctic ice shelves but also a number of minor ice shelves are included. Using these two models, ORCA2-LIM and ORCA2-LIM-ISP, the impact of addition of AISM and increasing AISM have been investigated. Using the ORCA2-LIM model, numerical experiments are performed to investigate the sensitivity of the polar sea ice cover and the Antarctic Circumpolar Current (ACC) transport through Drake Passage (DP) to the variations of three sea ice parameters, namely the thickness of newly formed ice in leads (h0), the compressive strength of ice (P*), and the turning angle in the oceanic boundary layer beneath sea ice (θ). It is found that the magnitudes of h0 and P* have little impact on the seasonal sea ice extent, but lead to large changes in the seasonal sea ice volume. The variation in turning angle has little impact on the sea ice extent and volume in the Arctic but tends to reduce them in the Antarctica when ignored. The magnitude of P* has the least impact on the DP transport, while the other two parameters have much larger influences. Numerical results from ORCA2-LIM and ORCA2-LIM-ISP are analyzed to investigate how the inclusion of AISM affects the representation of the Southern Ocean hydrography. Comparisons with data from the World Ocean Circulation Experiment (WOCE) show that the addition of AISM significantly improves the simulated hydrography. It not only warms and freshens the originally too cold and too saline bottom water (AABW), but also warms and enriches the salinity of the originally too cold and too fresh warm deep water (WDW). Addition of AISM also improves the simulated stratification. The close agreement between the simulation with AISM and the observations suggests that the applied parameterization is an adequate way to include the effect of AISM in a global sea ice-ocean climate model. We also investigate the models capability to represent the sea ice-ocean system in the North Atlantic Ocean and the Arctic regions. Our study shows both models (with and without AISM) can successfully reproduce the main features of the sea ice-ocean system. However, both tend to overestimate the ice flux through the Nares Strait, produce a lower temperature and salinity in the Hudson Bay, Baffin Bay and Davis Strait, and miss the deep convection in the Labrador Sea. These deficiencies are mainly attributed to the artificial enlargement of the Nares Strait in the model. In this study, the impact of increasing AISM on the global sea ice-ocean system is thoroughly investigated. This provides a first idea regarding changes induced by increasing AISM. It is shown that the impact of increasing AISM is global and most significant in the Southern Ocean. There, increasing AISM tends to freshen the surface water, to warm the intermediate and deep waters, and to freshen and warm the bottom water. In addition, increasing AISM also leads to changes in the mixed layer depths (MLD) in the deep convection sites in the Southern Ocean, deepening in the Antarctic continental shelf while shoaling in the ACC region. Furthermore, increasing AISM influences the current system in the Southern Ocean. It tends to weaken the ACC, and strengthen the Antarctic coastal current (ACoC) as well as the Weddell Gyre and the Ross Gyre. In addition to the ocean system, increasing AISM also has a notable impact on the Antarctic sea ice cover. Due to the cooling of seawater, sea ice concentration and thickness generally become higher. In austral winter, noticeable increases in sea ice concentration mainly take place near the ice edge. In regards with sea ice thickness, large increases are mainly found along the coast of the Weddell Sea, the Bellingshausen and Amundsen Seas, and the Ross Sea. The overall thickening of sea ice leads to a larger volume of sea ice in Antarctica. In the North Atlantic, increasing AISM leads to remarkable changes in temperature, salinity and density. The water generally becomes warmer, more saline and denser. The most significant warming occurs in the subsurface layer. In contrast, the maximum salinity increase is found at the surface. In addition, the MLD becomes larger along the Greenland-Scotland-Iceland ridge. Global teleconnections due to AISM are studied. The AISM signal is transported with the surface current: the additional freshwater from AISM tends to enhance the northward spreading of the surface water. As a result, more warm and saline water is transported from the tropical region to the North Atlantic Ocean, resulting in warming and salt enrichment there. It would take about 30 40 years to establish a systematic noticeable change in temperature, salinity and MLD in the North Atlantic Ocean according to this study. The changes in hydrography due to increasing AISM are compared with observations. Consistency suggests that increasing AISM is highly likely a major contributor to the recent observed changes in the Southern Ocean. In addition, the AISM might contribute to the salinity contrast between the North Atlantic and North Pacific, which is important for the global thermohaline circulation.

Sensitivity of the simulated precipitation to changes in convective relaxation time scale

The paper describes the sensitivity of the simulated precipitation to changes in convective relaxation time scale (TAU) of Zhang and McFarlane (ZM) cumulus parameterization, in NCAR-Community Atmosphere Model version 3 (CAM3). In the default configuration of the model, the prescribed value of TAU, a characteristic time scale with which convective available potential energy (CAPE) is removed at an exponential rate by convection, is assumed to be 1 h. However, some recent observational findings suggest that, it is larger by around one order of magnitude. In order to explore the sensitivity of the model simulation to TAU, two model frameworks have been used, namely, aqua-planet and actual-planet configurations. Numerical integrations have been carried out by using different values of TAU, and its effect on simulated precipitation has been analyzed. The aqua-planet simulations reveal that when TAU increases, rate of deep convective precipitation (DCP) decreases and this leads to an accumulation of convective instability in the atmosphere. Consequently, the moisture content in the lower-and mid-troposphere increases. On the other hand, the shallow convective precipitation (SCP) and large-scale precipitation (LSP) intensify, predominantly the SCP, and thus capping the accumulation of convective instability in the atmosphere. The total precipitation (TP) remains approximately constant, but the proportion of the three components changes significantly, which in turn alters the vertical distribution of total precipitation production. The vertical structure of moist heating changes from a vertically extended profile to a bottom heavy profile, with the increase of TAU. Altitude of the maximum vertical velocity shifts from upper troposphere to lower troposphere. Similar response was seen in the actual-planet simulations. With an increase in TAU from 1 h to 8 h, there was a significant improvement in the simulation of the seasonal mean precipitation. The fraction of deep convective precipitation was in much better agreement with satellite observations.

Perturbative growth of cosmological clustering. I: Formalism

Here we rederive the hierarchy of equations for the evolution of distribution functions of various orders using a convenient parameterization. We use this to obtain equations for two- and three-point correlation functions in powers of a small parameter, viz., the initial density contrast. The correspondence of the lowest order solutions of these equations to the results from the linear theory of density perturbations is shown for an OMEGA = 1 universe. These equations are then used to calculate, to the lowest order, the induced three-point correlation function that arises from Gaussian initial conditions in an OMEGA = 1 universe. We obtain an expression which explicitly exhibits the spatial structure of the induced three-point correlation function. It is seen that the spatial structure of this quantity is independent of the value of OMEGA. We also calculate the triplet momentum. We find that the induced three-point correlation function does not have the ''hierarchical'' form often assumed. We discuss possibilities of using the induced three-point correlation to interpret observational data. The formalism developed here can also be used to test a validity of different schemes to close the

The mean and turbulence structure simulation of the monsoon trough boundary layer using a one-dimensional model with e-l and e-epsilon closures

An attempt has been made here to study the sensitivity of the mean and the turbulence structure of the monsoon trough boundary layer to the choice of the constants in the dissipation equation for two stations Delhi and Calcutta, using one-dimensional atmospheric boundary layer model with e-epsilon turbulence closure. An analytical discussion of the problems associated with the constants of the dissipation equation is presented. It is shown here that the choice of the constants in the dissipation equation is quite crucial and the turbulence structure is very sensitive to these constants. The modification of the dissipation equation adopted by earlier studies, that is, approximating the Tke generation (due to shear and buoyancy production) in the epsilon-equation by max (shear production, shear + buoyancy production), can be avoided by a suitable choice of the constants suggested here. The observed turbulence structure is better simulated with these constants. The turbulence structure simulation with the constants recommended by Aupoix et al (1989) (which are interactive in time) for the monsoon region is shown to be qualitatively similar to the simulation obtained with the constants suggested here, thus implying that no universal constants exist to regulate dissipation rate. Simulations of the mean structure show little sensitivity to the type of the closure parameterization between e-l and e-epsilon closures. However the turbulence structure simulation with e-epsilon closure is far better compared to the e-l model simulations. The model simulations of temperature profiles compare quite well with the observations whenever the boundary layer is well mixed (neutral) or unstable. However the models are not able to simulate the nocturnal boundary layer (stable) temperature profiles. Moisture profiles are simulated reasonably better. With one-dimensional models, capturing observed wind variations is not up to the mark.