Wim Thiery

LakeMIP Kivu: evaluating the representation of a large, deep tropical lake by a set of one-dimensional lake models

The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the models performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible.

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...

Present-day irrigation mitigates heat extremes

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (−0.78xa0K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.

Hazardous thunderstorm intensification over Lake Victoria

Weather extremes have harmful impacts on communities around Lake Victoria, where thousands of fishermen die every year because of intense night-time thunderstorms. Yet how these thunderstorms will evolve in a future warmer climate is still unknown. Here we show that Lake Victoria is projected to be a hotspot of future extreme precipitation intensification by using new satellite-based observations, a high-resolution climate projection for the African Great Lakes and coarser-scale ensemble projections. Land precipitation on the previous day exerts a control on night-time occurrence of extremes on the lake by enhancing atmospheric convergence (74%) and moisture availability (26%). The future increase in extremes over Lake Victoria is about twice as large relative to surrounding land under a high-emission scenario, as only over-lake moisture advection is high enough to sustain Clausius–Clapeyron scaling. Our results highlight a major hazard associated with climate change over East Africa and underline the need for high-resolution projections to assess local climate change.

Reconstruction of a flash flood event through a multi-hazard approach: focus on the Rwenzori Mountains, Uganda

The increased use of complex and holistic modelling for multi-hazard analysis is in sharp contrast with a lacuna in hazard analysis in equatorial Africa. This study aims to increase understanding of multi-hazard events in poorly documented regions with low accessibility. We focus on the Nyamwamba catchment (107xa0km2) located in the Rwenzori Mountains (Uganda) where on May 1, 2013, a severe flash flood occurred. In this region, wildfires, earthquakes and landslides occur as well. Here we reconstruct the circumstances under which this flash flood event was triggered, characterize the different processes acting upon the catchment dynamics and estimate the damaging effects of the flash flood within the catchment. The combined occurrence of intense rainfall, a forest fire having burned 18xa0% of the catchment area and the occurrence of 29 landslides providing debris to the river system, induced a debris-rich and very destructive flash flood which caused several fatalities, the destruction of 70 buildings, several bridges, a hospital, a school, a tarmac road and several lifelines. Although the methodologies applied to estimate peak discharge, detect landslides and delineate wildfires are well established in their disciplines and sometimes limited in their precision, their combination is required to demonstrate the importance of the wildfire and landslides for the magnitude of this flood, unprecedented in decades but characterized by a low return period of the triggering rainfall event. This indicates that flash floods should not be considered as self-determined phenomena but as a result of several cascading and interacting hazard processes.

Can climate-effective land management reduce regional warming?

Limiting global warming to well below 2°C is an imminent challenge for humanity. However, even if this global target can be met, some regions are still likely to experience substantial warming relative to others. Using idealized global climate simulations, we examine the potential of land management options in affecting regional climate, with a focus on crop albedo enhancement and irrigation (climate-effective land management). The implementation is performed over all crop regions globally to provide an upper bound. We find that the implementation of both crop albedo enhancement and irrigation can reduce hot temperature extremes by more than 2°C in North America, Eurasia, and India over the 21st century relative to a scenario without management application. The efficacy of crop albedo enhancement scales with the magnitude, where a cooling response exceeding 0.5°C for hot temperature extremes was achieved with a large (i.e., ≥0.08) change in crop albedo. Regional differences were attributed to the surface energy balance response with temperature changes mostly explained by latent heat flux changes for irrigation and net shortwave radiation changes for crop albedo enhancement. However, limitations do exist, where we identify warming over the winter months when climate-effective land management is temporarily suspended. This was associated with persistent cloud cover that enhances longwave warming. It cannot be confirmed if the magnitude of this feedback is reproducible in other climate models. Our results overall demonstrate that regional warming of hot extremes in our climate model can be partially mitigated when using an idealized treatment of climate-effective land management.

Multi-year wind dynamics around Lake Tanganyika

Lake Tanganyika is the second largest freshwater lake in the world by volume and is of prime importance for the regional economy in East Africa. Although the lake is recognized as a key component of the regional climate system, little is known about atmospheric dynamics in its surroundings. To understand this role, we analyze winds around Lake Tanganyika as modeled by a high resolution (7xa0km) regional climate model (Consortium for Small-scale Modeling in Climate Mode) over the period 1999–2008. Modeled surface wind speed and direction are in very good agreement with high resolution (12.5xa0km) Quick Scatterometer (QuikSCAT) satellite wind observations during the dry season. Comparison of a control run with a model simulation where all lake pixels are replaced by representative land pixels indicates that mean surface wind speed over Lake Tanganyika almost doubles due to lake presence. Furthermore, a region of higher surface wind speed in the central part of the lake is identified and confirmed by QuikSCAT observations. A combination of wind channeling along valley mountains and wind confluence on the upwind side of the lake is responsible for this speed-up. The lower wind speeds in the rest of the lake result from blocked conditions due to more pronounced orography. Finally, the model captures a zone of higher wind speed at around 2xa0km height, associated with the low-level Somali jet. These results demonstrate that high resolution climate modeling allows a detailed understanding of wind dynamics in the vicinity of Lake Tanganyika.

Vegetation response to precipitation variability in East Africa controlled by biogeographical factors

Ecosystem sensitivity to climate variability varies across East Africa, and identifying the determinant factors of this sensitivity is crucial to assessing region-wide vulnerability to climate change and variability. Such assessment critically relies on spatiotemporal datasets with inherent uncertainty, on new processing techniques to extract interannual variability at a priori unknown time scales and on adequate statistical models to test for biogeographical effects on vegetation-precipitation relationships. In this study, interannual variability in long term records of Normalized Difference Vegetation Index (NDVI) and satellite-based precipitation estimates was detected using Ensemble Empirical Mode Decomposition (EEMD) and Standardized Precipitation Index (SPI) with varying accumulation periods. Environmental effect modeling using additive models with spatially correlated effects showed that ecosystem sensitivity is primarily predicted by biogeographical factors such as annual precipitation distribution (reaching maximum sensitivity at 500u2009mmu2009yr-1), vegetation type and structure, ocean-climate coupling and elevation. The threat of increasing climate variability and extremes impacting productivity and stability of ecosystems is most imminent in semi-arid grassland and mixed cropland ecosystems. The influence of oceanic phenomena such as El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) is foremost reflected in precipitation variability, but prolonged episodes also pose risks for long-term degradation of tree-rich ecosystems in the East African Great Lakes region.

Landslide inventory for hazard assessment in a data-poor context: a regional-scale approach in a tropical African environment

Landslide hazard remains poorly characterized on regional and global scales. In the tropics in particular, the lack of knowledge on landslide hazard is in sharp contrast with the high landslide susceptibility of the region. Moreover, landslide hazard in the tropics is expected to increase in the future in response to growing demographic pressure and climate and land use changes. With precipitation as the primary trigger for landslides in the tropics, there is a need for an accurate determination of rainfall thresholds for landslide triggering based on regional rainfall information as well as reliable data on landslide occurrences. Here, we present the landslide inventory for the central section of the western branch of the East African Rift (LIWEAR). Specific attention is given to the spatial and temporal accuracy, reliability, and geomorphological meaning of the data. The LIWEAR comprises 143 landslide events with known location and date over a span of 48xa0years from 1968 to 2016. Reported landslides are found to be dominantly related to the annual precipitation patterns and increasing demographic pressure. Field observations in combination with local collaborations revealed substantial biases in the LIWEAR related to landslide processes, landslide impact, and the remote context of the study area. In order to optimize data collection and minimize biases and uncertainties, we propose a three-phase, Search-Store-Validate, workflow as a framework for data collection in a data-poor context. The validated results indicate that the proposed methodology can lead to a reliable landslide inventory in a data-poor context, valuable for regional landslide hazard assessment at the considered temporal and spatial resolutions.

Evaluating TMPA rainfall over the sparsely gauged East African Rift

AbstractAccurate precipitation data are fundamental for understanding and mitigating the disastrous effects of many natural hazards in mountainous areas. Floods and landslides, in particular, are p...