Matthias Demuzere

The Impact of the African Great Lakes on the Regional Climate

AbstractAlthough the African Great Lakes are important regulators for the East African climate, their influence on atmospheric dynamics and the regional hydrological cycle remains poorly understood. This study aims to assess this impact by comparing a regional climate model simulation that resolves individual lakes and explicitly computes lake temperatures to a simulation without lakes. The Consortium for Small-Scale Modelling model in climate mode (COSMO-CLM) coupled to the Freshwater Lake model (FLake) and Community Land Model (CLM) is used to dynamically downscale a simulation from the African Coordinated Regional Downscaling Experiment (CORDEX-Africa) to 7-km grid spacing for the period of 1999–2008. Evaluation of the model reveals good performance compared to both in situ and satellite observations, especially for spatiotemporal variability of lake surface temperatures (0.68-K bias), and precipitation (−116 mm yr−1 or 8% bias). Model integrations indicate that the four major African Great Lakes almos...

Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

World Urban Database and Access Portal Tools (WUDAPT), an urban weather, climate and environmental modeling infrastructure for the Anthropocene

Capsule Summary:WUDAPT, an International community generated urban canopy information and modeling infrastructure (Portal) to facilitate urban focused climate, weather, air quality, and energy use modeling application studies.

Beyond the urban mask

Despite the great importance of cities, relatively little consistent information about their internal configuration (structure, cover and materials) is available. The World Urban Database and Access Portal Tools (WUDAPT) initiative aims at the acquisition, storage and dissemination of data on the form and function of cities indifferent levels. At the lowest level, the Local Climate Zone (LCZ) scheme provides a basic description of urban structure. This scheme is a climate-based typology of urban and natural landscapes that also provides relevant information on basic physical properties of the landscape, which can be used in modelling and observational studies. The LCZ scheme has large potential as a standard generic description of urban areas. In this paper the scheme and our standard mapping approach are presented, followed by recent improvements and research on object-based image analysis, transferability of trained LCZ classifiers, quality of crowd contributions, and the use of other data sources and methods.

Evaluation of an urban land surface scheme over a tropical suburban neighborhood

The present study evaluates the performance of the SURFEX (TEB/ISBA) urban land surface parametrization scheme in offline mode over a suburban area of Singapore. Model performance (diurnal and seasonal characteristics) is investigated using measurements of energy balance fluxes, surface temperatures of individual urban facets, and canyon air temperature collected during an 11-month period. Model performance is best for predicting net radiation and sensible heat fluxes (both are slightly overpredicted during daytime), but weaker for latent heat (underpredicted during daytime) and storage heat fluxes (significantly underpredicted daytime peaks and nighttime storage). Daytime surface temperatures are generally overpredicted, particularly those containing horizontal surfaces such as roofs and roads. This result, together with those for the storage heat flux, point to the need for a better characterization of the thermal and radiative characteristics of individual urban surface facets in the model. Significant variation exists in model behavior between dry and wet seasons, the latter generally being better predicted. The simple vegetation parametrization used is inadequate to represent seasonal moisture dynamics, sometimes producing unrealistically dry conditions.

The microscale cooling effects of water sensitive urban design and irrigation in a suburban environment

Prolonged drought has threatened traditional potable urban water supplies in Australian cities, reducing capability to adapt to climate change and mitigate against extreme. Integrated urban water management (IUWM) approaches, such as water sensitive urban design (WSUD), reduce the reliance on centralised potable water supply systems and provide a means for retaining water in the urban environment through stormwater harvesting and reuse. This study examines the potential for WSUD to provide cooling benefits and reduce human exposure and heat stress and thermal discomfort. A high-resolution observational field campaign, measuring surface level microclimate variables and remotely sensed land surface characteristics, was conducted in a mixed residential suburb containing WSUD in Adelaide, South Australia. Clear evidence was found that WSUD features and irrigation can reduce surface temperature (Ts) and air temperature (Ta) and improve human thermal comfort (HTC) in urban environments. The average 3 pm Ta near water bodies was found to be up to 1.8 °C cooler than the domain maximum. Cooling was broadly observed in the area 50 m downwind of lakes and wetlands. Design and placement of water bodies were found to affect their cooling effectiveness. HTC was improved by proximity to WSUD features, but shading and ventilation were also effective at improving thermal comfort. This study demonstrates that WSUD can be used to cool urban microclimates, while simultaneously achieving other environmental benefits, such as improved stream ecology and flood mitigation.

A non-linear data-driven approach to reveal global vegetation sensitivity to climate

Following a Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main spatiotemporal drivers of monthly vegetation variability globally. Results based on 1981–2010 indicate that water availability is the most dominant factor driving vegetation globally. This overall dependency of vegetation on water availability is larger than previously reported, partly owed to the ability of the framework to disentangle the co-linearites between climate drivers and to quantify non-linear impacts of climate on vegetation. This is a first step towards a quantitative comparison of the resistance and resilience of different ecosystems, and can be used to benchmark climate model representation of vegetation sensitivity.

The Air-temperature Response to Green/blue-infrastructureEvaluation Tool (TARGET v1.0): an efficient and user-friendlymodel of city cooling

This study presents a simple urban climate numerical model aimed at being used as decision support tool by urban planners. The paper first presents the principles and equations of the model, then an evaluation of simulated surface temperatures and air temperatures against remote-sensed observations and in situ measurements, and finally an example of application for urban planning scenarios evaluation. The model

Analyzing Granger Causality in Climate Data with Time Series Classification Methods

Attribution studies in climate science aim for scientifically ascertaining the influence of climatic variations on natural or anthropogenic factors. Many of those studies adopt the concept of Granger causality to infer statistical cause-effect relationships, while utilizing traditional autoregressive models. In this article, we investigate the potential of state-of-the-art time series classification techniques to enhance causal inference in climate science. We conduct a comparative experimental study of different types of algorithms on a large test suite that comprises a unique collection of datasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested.