Characterization of Ethiopian mega hydrogeological regimes using GRACE, TRMM and GLDAS Datasets

Understanding the spatio-temporal characteristics of water storage changes is crucial for Ethiopia, a country that is facing a range of challenges in water management caused by anthropogenic impacts as well as climate variability. In addition to this, the scarcity of in situ measurements of soil moisture and groundwater, combined with intrinsic ‘‘scale limitations’’ of traditional methods used in hydrological characterization are further limiting the ability to assess water resource distribution in the region. The primary objective of this study is therefore to apply remotely sensed and model data over Ethiopia in order to (i) test the performance of models and remotely sensed data in modeling water resources distribution in un-gauged arid regions of Ethiopia, (ii) analyze the inter-annual and seasonal variability as well as changes in total water storage (TWS) over Ethiopia, (iii) understand the relationship between TWS changes, rainfall, and soil moisture anomalies over the study region, and (iv) identify the relationship between the characteristics of aquifers and TWS changes. The data used in this study includes; monthly gravity field data from the Gravity Recovery And Climate Experiment (GRACE) mission, rainfall data from the Tropical Rainfall Measuring Mission (TRMM), and soil moisture from the Global Land Data Assimilation System (GLDAS) model. Our investigation covers a period of 8 years from 2003 to 2011.The results of the study show that the western part and the north-eastern lowlands of Ethiopia experienced decrease in TWS water between 2003–2011, whereas all the other regions gained water during the study period. The impact of rainfall seasonality was also seen in the TWS changes. Applying the statistical method of Principal Component Analysis (PCA) to TWS, soil moisture and rainfall variations identified the dominant annual water variability in the western, north-western, northern, and central regions, and the dominant seasonal variability in the western, north-western, and the eastern regions. A correlation analysis between TWS and rainfall indicated a minimum time lag of zero to a maximum of six months, whereas no lag is noticeable between soil moisture anomalies and TWS changes. The delay response and correlation coefficient between rainfall and TWS appears to be related to recharge mechanisms, revealing that most regions of Ethiopia receive indirect recharge. Our results also show that the magnitude of TWS changes is higher in the western region and lower in the north-eastern region, and that the elevation influences soil moisture as well as TWS

Potential impacts of climate and environmental change on the stored water of Lake Victoria Basin and economic implications

The changing climatic patterns and increasing human population within the Lake Victoria Basin (LVB), together with overexploitation of water for economic activities call for assessment of water management for the entire basin. This study focused on the analysis of a combination of available in situ climate data, Gravity Recovery and Climate Experiment (GRACE), Tropical Rainfall Measuring Mission (TRMM) observations, and high resolution Regional Climate simulations during recent decade(s) to assess the water storage changes within LVB that may be linked to recent climatic variability/changes and anomalies. We employed trend analysis, principal component analysis (PCA), and temporal/spatial correlations to explore the associations and covariability among LVB stored water, rainfall variability, and large-scale forcings associated with El-Niño/Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Potential economic impacts of human and climate-induced changes in LVB stored water are also explored.Overall, observed in situ rainfall from lake-shore stations showed a modest increasing trend during the recent decades. The dominant patterns of rainfall data from the TRMM satellite estimates suggest that the spatial and temporal distribution of precipitation have not changed much during the period of 1998–2012 over the basin consistent with in situ observations. However, GRACE-derived water storage changes over LVB indicate an average decline of 38.2 mm/yr for 2003–2006, likely due to the extension of the Owen Fall/Nalubale dam, and an increase of 4.5 mm/yr over 2007–2013, likely due to two massive rainfalls in 2006–2007 and 2010–2011. The temporal correlations between rainfall and ENSO/IOD indices during the study period, based on TRMM and model simulations, suggest significant influence of large-scale forcing on LVB rainfall, and thus stored water. The contributions of ENSO and IOD on the amplitude of TRMM-rainfall and GRACE-derived water storage changes, for the period of 2003–2013, are estimated to be ~2.5 cm and ~1.5 cm, respectively

Quantifying the impacts of ENSO and IOD on rain gauge and remotely sensed precipitation products over Australia

Large-scale ocean-atmospheric phenomena like the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) have significant influence on Australia's precipitation variability. In this study, multi-linear regression (MLR) and complex empirical orthogonal function (CEOF) analyses were applied to isolate (i) the continental precipitation variations likely associated with ENSO and IOD, here referred to as 'ENSO/IOD mode', and (ii) the variability not associated with ENSO/IOD (the 'non-ENSO/IOD mode'). The first is of interest due to its dominant influence on inter-annual variability, while the second may reveal lower frequency variability or trends. Precipitation products used for this study included gridded rainfall estimates derived by interpolation of rain gauge data from the Australian Bureau of Meteorology (BoM), two satellite remote sensing products (CHIRP and TRMM TMPA version 7), and two weather forecast model re-analysis products (ERA-Interim and MERRA). The products covered the period 1981-2014 except TMPA (1998-2014). Statistical and frequency-based inter-comparisons were performed to evaluate the seasonal and long-term skills of various rainfall products against the BoM product. The results indicate that linear trends in rainfall during 1981-2014 were largely attributable to ENSO and IOD. Both intra-annual and seasonal rainfall changes associated with ENSO and IOD increased from 1991 to 2014. Among the continent's 13 major river basins, the greatest precipitation variations associated with ENSO/IOD were found over the Northern and North East Coast, while the smallest contributions were for Tasmania and the South West Coast basins. We also found that although the assessed products show comparable spatial variability of rainfall over Australia, systematic seasonal differences exist that were more pronounced during the ENSO and IOD events

Indian Ocean Dipole drives malaria resurgence in East African highlands

Malaria resurgence in African highlands in the 1990s has raised questions about the underlying drivers of the increase in disease incidence including the role of El-Niño-Southern Oscillation (ENSO). However, climatic anomalies other than the ENSO are clearly associated with malaria outbreaks in the highlands. Here we show that the Indian Ocean Dipole (IOD), a coupled ocean-atmosphere interaction in the Indian Ocean, affected highland malaria re-emergence. Using cross-wavelet coherence analysis, we found four-year long coherent cycles between the malaria time series and the dipole mode index (DMI) in the 1990s in three highland localities. Conversely, we found a less pronounced coherence between malaria and DMI in lowland localities. The highland/lowland contrast can be explained by the effects of mesoscale systems generated by Lake Victoria on its climate basin. Our results support the need to consider IOD as a driving force in the resurgence of malaria in the East African highlands

Scientific understanding of East African climate change from the HyCRISTAL project

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic

Scientific understanding of East African climate change from the HyCRISTAL project

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic

Basin-Scale Control on the Phytoplankton Biomass in Lake Victoria, Africa

The relative bio-optical variability within Lake Victoria was analyzed through the spatio-temporal decomposition of a 1997–2004 dataset of remotely-sensed reflectance ratios in the visible spectral range. Results show a regular seasonal pattern with a phase shift (around 2 months) between the south and north parts of the lake. Interannual trends suggested a teleconnection between the lake dynamics and El-Niño phenomena. Both seasonal and interannual patterns were associated to conditions of light limitation for phytoplankton growth and basin-scale hydrodynamics on phytoplankton access to light. Phytoplankton blooms developed during the periods of lake surface warming and water column stability. The temporal shift apparent in the bio-optical seasonal cycles was related to the differential cooling of the lake surface by southeastern monsoon winds. North-south differences in the exposure to trade winds are supported by the orography of the Eastern Great Rift Valley. The result is that surface layer warming begins in the northern part of the lake while the formation of cool and dense water continues in the southern part. The resulting buoyancy field is sufficient to induce a lake-wide convective circulation and the tilting of the isotherms along the north-south axis. Once surface warming spreads over the whole lake, the phytoplankton bloom dynamics are subjected to the internal seiche derived from the relaxation of thermocline tilting. In 1997–98, El-Niño phenomenon weakened the monsoon wind flow which led to an increase in water column stability and a higher phytoplankton optical signal throughout the lake. This suggests that phytoplankton response to expected climate scenarios will be opposite to that proposed for nutrient-limited great lakes. The present analysis of remotely-sensed bio-optical properties in combination with environmental data provides a novel basin-scale framework for research and management strategies in Lake Victoria

Lateral terrestrial water flow contribution to summer precipitation at continental scale – A comparison between Europe and West Africa with WRF‐Hydro‐tag ensembles

It is well accepted that summer precipitation can be altered by soil moisture condition. Coupled land surface – atmospheric models have been routinely used to quantify soil moisture – precipitation feedback processes. However, most of the land surface models (LSMs) assume a vertical soil water transport and neglect lateral terrestrial water flow at the surface and in the subsurface, which potentially reduces the realism of the simulated soil moisture – precipitation feedback. In this study, the contribution of lateral terrestrial water flow to summer precipitation is assessed in two different climatic regions, Europe and West Africa, for the period June–September 2008. A version of the coupled atmospheric-hydrological model WRF-Hydro with an option to tag and trace land surface evaporation in the modelled atmosphere, named WRF-Hydro-tag, is employed. An ensemble of 30 simulations with terrestrial routing and 30 simulations without terrestrial routing is generated with random realizations of turbulent energy with the stochastic kinetic energy backscatter scheme, for both Europe and West Africa. The ensemble size allows to extract random noise from continental-scale averaged modelled precipitation. It is found that lateral terrestrial water flow increases the relative contribution of land surface evaporation to precipitation by 3.6% in Europe and 5.6% in West Africa, which enhances a positive soil moisture – precipitation feedback and generates more uncertainty in modelled precipitation, as diagnosed by a slight increase in normalized ensemble spread. This study demonstrates the small but non-negligible contribution of lateral terrestrial water flow to precipitation at continental scale

Assessing regional climate simulations of the last 30 years (1982–2012) over Ganges–Brahmaputra–Meghna River Basin

The Ganges–Brahmaputra–Meghna (GBM) River Basin presents a spatially diverse hydrological regime due to it’s complex topography and escalating demand for freshwater resources. This presents a big challenge in applying the current state-of-the-art regional climate models (RCMs) for climate change impact studies in the GBM River Basin. In this study, several RCM simulations generated by RegCM4.4 and PRECIS are assessed for their seasonal and interannual variations, onset/withdrawal of the Indian monsoon, and long-term trends in precipitation and temperature from 1982 to 2012. The results indicate that in general, RegCM4.4 and PRECIS simulations appear to reasonably reproduce the mean seasonal distribution of precipitation and temperature across the GBM River Basin, although the two RCMs are integrated over a different domain size. On average, the RegCM4.4 simulations overestimate monsoon precipitation by (Formula presented.) and (Formula presented.) in the Ganges and Brahmaputra–Meghna River Basin, respectively, while PRECIS simulations underestimate (overestimate) the same by (Formula presented.) ((Formula presented.)). Both RegCM4.4 and PRECIS simulations indicate an intense cold bias (up to (Formula presented.)) in the Himalayas, and are generally stronger in the RegCM4.4 simulations. Additionally, they tend to produce high precipitation between April and May in the Ganges (RegCM4.4 simulations) and Brahmaputra–Meghna (PRECIS simulations) River Basins, resulting in early onset of the Indian monsoon in the Ganges River Basin. PRECIS simulations exhibit a delayed monsoon withdrawal in the Brahmaputra–Meghna River Basin. Despite large spatial variations in onset and withdrawal periods across the GBM River Basin, the basin-averaged results agree reasonably well with the observed periods. Although global climate model (GCM) driven simulations are generally poor in representing the interannual variability of precipitation and winter temperature variations, they tend to agree well with observed precipitation anomalies when driven by perfect boundary conditions. It is also seen that all GCM driven simulations feature significant positive surface temperature trends consistent with the observed datasets

Understanding linkages between global climate indices and terrestrial water storage changes over Africa using GRACE products

Africa, a continent endowed with huge water resources that sustain its agricultural activities is increasingly coming under threat from impacts of climate extremes (droughts and floods), which puts the very precious water resource into jeopardy. Understanding the relationship between climate variability and water storage over the continent, therefore, is paramount in order to inform future water management strategies. This study employs Gravity Recovery And Climate Experiment (GRACE) satellite data and the higher order (fourth order cumulant) statistical independent component analysis (ICA) method to study the relationship between terrestrial water storage (TWS) changes and five global climate-teleconnection indices; El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Madden-Julian Oscillation (MJO), Quasi-Biennial Oscillation (QBO) and the Indian Ocean Dipole (IOD) over Africa for the period 2003–2014. Pearson correlation analysis is applied to extract the connections between these climate indices (CIs) and TWS, from which some known strong CI-rainfall relationships (e.g., over equatorial eastern Africa) are found. Results indicate unique linear-relationships and regions that exhibit strong linkages between CIs and TWS. Moreover, unique regions having strong CI-TWS connections that are completely different from the typical ENSO-rainfall connections over eastern and southern Africa are also identified. Furthermore, the results indicate that the first dominant independent components (IC) of the CIs are linked to NAO, and are characterized by significant reductions of TWS over southern Africa. The second dominant ICs are associated with IOD and are characterized by significant increases in TWS over equatorial eastern Africa, while the combined ENSO and MJO are apparently linked to the third ICs, which are also associated with significant increase in TWS changes over both southern Africa, as well as equatorial eastern Africa