The land surface is a key component of the climate system and exchanges energy, water and carbon with the overlying atmosphere. It is the location of the terrestrial carbon sink and changes in the land surface can impact weather and climate at various time and spatial scales. It's ability to act as a source or a sink can influence atmospheric CO2 concentrations. Both models and observations have shown the reduced ability of the land surface to absorb increased anthropogenic CO2 emissions with results from the Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) and phase 5 of the Coupled Model Intercomparison Project (CMIP5) have shown that the terrestrial carbon cycle is a major source of model uncertainty. Land surface models (LSMs) represent the interaction between the biosphere and atmosphere in earth system models (ESMs) and are important for simulating the terrestrial carbon cycle. In the context of land surface modelling, uncertainty arises from an incomplete understanding of land surface processes and the inability to model these processes correctly. As LSMs become more advanced, there is a need to understand their accuracy. In this thesis, the ability of the Joint UK Land Environment Simulator (JULES), the land surface scheme of the UK Met Office United Model, to simulate Gross Primary Productivity (GPP) fluxes is evaluated at various spatial scales (point, regional and global) in order to identify and quantify sources of uncertainty in the model. This thesis has three main objectives. Firstly, JULES is evaluated at the point scale across a range of biomes and climatic conditions using local (site-specific), global and satellite datasets. It was found that JULES is biased with total annual GPP underestimated by 16% and 30% across all sites compared to observations when using local and global data, respectively. The model's phenology module was tested by comparing results from simulations using the default phenology model to those forced with leaf area index (LAI) from the MODIS sensor. Model parameters were found to be a minor source of uncertainty compared to the meteorological driving data at the point scale as was the default phenology module in JULES. Secondly, in addition to evaluating simulated GPP fluxes at the point scale, the ability of JULES to simulate GPP at the global and regional scale for 2000-2010 was investigated with being able to simulate interannual variability and simulated global GPP estimates were found to be greater than the observation-based estimates, FLUXNET-MTE and MODIS, by 8% and 25%, respectively. At the regional scale, differences in GPP between JULES, FLUXNET-MTE and MODIS were observed mostly in the tropics and this was the reason for differences at the global scale. Simulating tropical GPP was found to be a major source of uncertainty in JULES. JULES was found to be insensitive to spatial resolution and when driven with the PRINCETON meteorological dataset, differences between model simulations driven using WFDEI-GPCC and PRINCETON occurred in the tropics (at 5°N-5°S) and extratropics (at 30°N-60°N). Finally, the response of JULES to changes in climate (surface air temperature, precipitation, atmospheric CO2 concentrations) was explored at the global and regional scale. Simulated GPP was found to have greater sensitivity to changes in precipitation and CO2 concentrations than air temperature at the global scale while LAI was sensitive only to changes in temperature and insensitive to changes in precipitation and CO2 concentrations. It was found that model sensitivity to climate at the global scale was determined by its behaviour at the regional scale.

This thesis research consists of two separate studies. The first study presents the assessment and representation of the effects of soil macropores on the soil hydraulic properties in land surface models for more accurate simulations of soil moisture and surface hydrology. Hydraulic properties determine the soil water content and its transport in the soil. They are provided in most current climate models as empirical formulas by functions of the soil texture. Such is not realistic if the soil contains a substantial amount of macropores. A two-mode soil pore size distribution is incorporated into a land surface model and tested using an observational dataset at a tropical forest site with aggregated soils. The result showed that the existence of macropores greatly affects the estimation of hydraulic properties. Their influence can be included in land models by adding a second function to the pore-size distribution. A practical hydraulic scheme with macropore considerations was proposed given that the existing schemes are not applicable for large-scale simulations. The developed scheme was based on the physical attributes of the water in soil capillary pores and the statistics of several global soil databases. The preliminary test showed that it captures part of soil macropore hydraulic features without sacrificing the estimation accuracy of hydraulic properties of water in soil matrix. The second study presents the development of an integrated land/ecosystem model by combining the advanced features of a biophysically based land model, the Community Land Model, and an ecosystem biochemical model. The results from tests of the integrated model at four forest sites showed that the model reasonably captures the seasonal and interannual dynamics of leaf area index and leaf nitrogen control on carbon assimilation across different environments. With being coupled to an atmospheric general circulation model (AGCM), the integrated model showed a strong ability to simulate terrestrial ecosystem carbon fluxes together with heat and water fluxes. Its simulated land surface physical variables are reasonable in both geographic distribution and temporal variation with considering the interactive vegetation parameters.

Atmospheric inversion has recently become an important tool in estimating CO2 sinks and sources albeit that the existing inversion results are often uncertain and differ considerably in terms of the spatiotemporal variations of the inverted carbon flux. More measurements combined with terrestrial ecosystem information are expected to improve the estimates of global surface carbon fluxes which are used to understand the relationships between variabilities of the terrestrial carbon cycle and anomalies of climatic factors. Inversions using more observations have often been hampered by the intense diurnal variations of CO2 concentrations at continental sites. Diurnal variations of the surface flux are included with atmospheric boundary dynamics in order to improve the atmospheric inversion accuracy. Modeling experiments conducted in this study show that inverse estimates of the carbon flux are more sensitive to the variation of the atmospheric boundary layer dynamics than to the diurnal variation in the surface flux. It is however generally better to consider both diurnal variations in the inversion than to consider only either of them. Forest carbon dynamics is closely related to stand age. This useful terrestrial ecosystem information has been used as an additional constraint to the atmospheric inversion. The inverse estimates with this constraint over North America exhibit an improved correlation with carbon sink estimates derived from eddy-covariance measurements and remotely-sensed data, indicating that the use of age information can improve the accuracy of atmospheric inversions. Terrestrial carbon uptake is found mainly in northern land, and a strong flux density is revealed in southeastern North America in an improved multi-year inversion from 2002 to 2007. The global interannual variability of the flux is dominated by terrestrial ecosystems. The interannual variabilities of regional terrestrial carbon cycles could be mostly explained by monthly anomalies of climatic conditions or short-time extreme meteorological events. Monthly anomalies of the inverted fluxes have been further analyzed against the monthly anomalies of temperature and precipitation to quantitatively assess the responses of the global terrestrial carbon cycle to climatic variabilities and to determine the dominant mechanisms controlling the variations of terrestrial carbon exchange.

Atmospheric inversion has recently become an important tool in estimating CO2 sinks and sources albeit that the existing inversion results are often uncertain and differ considerably in terms of the spatiotemporal variations of the inverted carbon flux. More measurements combined with terrestrial ecosystem information are expected to improve the estimates of global surface carbon fluxes which are used to understand the relationships between variabilities of the terrestrial carbon cycle and anomalies of climatic factors. Inversions using more observations have often been hampered by the intense diurnal variations of CO2 concentrations at continental sites. Diurnal variations of the surface flux are included with atmospheric boundary dynamics in order to improve the atmospheric inversion accuracy. Modeling experiments conducted in this study show that inverse estimates of the carbon flux are more sensitive to the variation of the atmospheric boundary layer dynamics than to the diurnal variation in the surface flux. It is however generally better to consider both diurnal variations in the inversion than to consider only either of them. Forest carbon dynamics is closely related to stand age. This useful terrestrial ecosystem information has been used as an additional constraint to the atmospheric inversion. The inverse estimates with this constraint over North America exhibit an improved correlation with carbon sink estimates derived from eddy-covariance measurements and remotely-sensed data, indicating that the use of age information can improve the accuracy of atmospheric inversions. Terrestrial carbon uptake is found mainly in northern land, and a strong flux density is revealed in southeastern North America in an improved multi-year inversion from 2002 to 2007. The global interannual variability of the flux is dominated by terrestrial ecosystems. The interannual variabilities of regional terrestrial carbon cycles could be mostly explained by monthly anomalies of climatic conditions or short-time extreme meteorological events. Monthly anomalies of the inverted fluxes have been further analyzed against the monthly anomalies of temperature and precipitation to quantitatively assess the responses of the global terrestrial carbon cycle to climatic variabilities and to determine the dominant mechanisms controlling the variations of terrestrial carbon exchange.

Climate variability and the carbon cycle (C-cycle) are tied together in complex feedback loops and due to these complexities there are still knowledge-gaps of this coupling. However, to make accurate predictions of future climate, profound understanding of the C-cycle and climate variability is essential. To gain more knowledge of climate variability, the study aims to identify recurring spatial patterns of the variability of precipitation anomalies over Scandinavia during spring and summer respectively between 1981 to 2014. These patterns will be related to the C-cycle through changes in summer vegetation greenness, measured as normalized difference vegetation index (NDVI). Finally, the correlation between the patterns of precipitation variability in summer and the teleconnection patterns over the North Atlantic will be investigated. The precipitation data was obtained from ERA5 from the European Centre for Medium-Range Weather Forecasts and the patterns of variability were found through empirical orthogonal function (EOF) analysis. The first three EOFs of the spring and the summer precipitation anomalies together explained 73.5 % and 65.5 % of the variance respectively. The patterns of precipitation variability bore apparent similarities when comparing the spring and summer patterns and the Scandes were identified to be important for the precipitation variability in Scandinavia during both seasons. Anomalous events of the spring EOFs indicated that spring precipitation variability had little impact on anomalies of summer NDVI. Contradictory, summer precipitation variability seemed to impact anomalies of summer NDVI in central- and northeastern Scandinavia, thus indicating that summer precipitation variability modulates some of the terrestrial C-cycle in these regions. Correlations were found between a large part of the summer precipitation variability and the Summer North Atlantic Oscillation and the East Atlantic pattern. Hence, there is a possibility these teleconnections have some impact, through the summer precipitation variability, on the terrestrial C-cycle. / Förändringar och variation i klimatet är sammankopplade med kolcykeln genom komplexa återkopplingsmekanismer. På grund av denna komplexitet är kunskapen om kopplingen mellan klimatvariation och kolcykeln fortfarande bristande, men för att möjliggöra precisa prognoser om framtida klimat är det viktigt att ha kunskap om denna koppling. För att få mer kunskap om klimatvariation syftar därför denna studie till att identifiera återkommande strukturer av nederbördsvariation över Skandinavien under vår respektive sommar från 1981 till 2014. Dessa relateras till förändringar i sommarväxtlighetens grönhet, uppmätt som skillnaden i normaliserat vegetationsindex (NDVI). Även korrelationen mellan sommarstrukturerna av nederbördsvariationen och storskaliga atmosfäriska svängningar, s.k. "teleconnections", över Nordatlanten undersöks. Nederbördsdatan erhölls från ERA5 analysdata från Europacentret för Medellånga Väderprognoser och strukturer av nederbördsvariationen identifierades genom empirisk ortogonal funktionsanalys (EOF) av nederbördsavvikelser. De tre första EOF av vår- respektive sommarnederbördsavvikelser förklarade tillsammans 73,5 % respektive 65,5 % av nederbördsvariationen. Strukturerna av nederbördsvariation under vår respektive sommar uppvisade tydliga likheter sinsemellan. Dessutom identifierades Skanderna vara av stor vikt för nederbördsvariationen i Skandinavien under båda årstider. Avvikande år av nederbördsvariation under våren indikerade att sagda nederbördsvariation haft liten påverkan på NDVI-avvikelser under sommaren. Emellertid verkade nederbördsvariationen under sommaren påverkat NDVI-avvikelser under sommaren i centrala och nordöstra Skandinavien. Detta indikerar att nederbördsvariationen under sommaren till viss del styr den terrestra kolcykeln i dessa regioner. För nederbördsvariationen under sommaren fanns korrelation mellan både Nordatlantiska sommaroscillationen och Östatlantiska svängningen. Det finns således en möjlighet att dessa "teleconnections" har en viss påverkan på den terrestra kolcykeln genom nederbördsvariationen under sommaren.