Inter-comparison of satellite rainfall products for representing rainfall diurnal cycle over the Nile basin

In this study, the authors inter-compared the performance of three satellite-rainfall products in representing the diurnal cycle of rain occurrence and rain rate over the Nile basin in eastern Africa. These products are the real time (RT) and post-real-time (PRT) (bias adjusted) versions of Tropical Rainfall Measuring Mission (TRMM) and other sources product known as TRMM-3B42 and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) product which is based on the CPC morphing technique (CMORPH). The rainfall diurnal cycles are re-produced using these products with specific focus on assessing effects of geographic location and topographic features. The performance of the satellite products in representing rainfall diurnal cycle shows large variation over the Nile basin. The products overestimate rain occurrence over the lakes, islands, and shores and underestimate occurrence over mountain tops. Overall, CMORPH performs better than TRMM-3B42 RT and TRMM-3B42 PRT in capturing the diurnal cycle of rain rate in Lake Tana basin. However, the difference between the two products is very small for Lake Victoria basin, where both products perform more favorably. Over most of the Nile basin areas, the use of fine versus coarse temporal and spatial resolution of the CMORPH product showed large differences for diurnal cycle of rain occurrence than that of rain rate. Results also show that the bias adjustment of TRMM-3B42 product does not necessarily bring improvements probably since the adjustments are not performed based on local rain gauge data

Evaluation of TRMM rainfall products for hydrological uses at different scales

The principal objectives of the thesis are two: firstly to study the accuracy of the satellite rainfall products in climatologically distinctive places at different scales and secondly to find the possibility of using satellite-rain gauge blended rainfall products for hydrological purposes. Three case study areas Catalunya, Bangladesh, and South Africa have been chosen for the analysis using the satellite rainfall products (TMPA) and rain gauge records for the period from January 2005 to December 2009. The areal pattern of rainfall has been presented using satellite rainfall products over the case study areas. Both daily and monthly products are showing good agreement with rain gauge records although it is highly variable with space and seasonality. From the results, it can be shown that TRMM satellite identified the seasonal variability of rainfall. Moreover, the mean TRMM rainfall products show same pattern as like mean rain gauge observations in daily and monthly scale in all case study areas.Finally, a blending technique is applied (originally used for radar-rain gauge blending) to conform satellite rainfall products to rain gauge observations. This blended product is also tested against the rain gauge records to verify the improvement of the blended rainfall products over the original satellite products. Results of blended rainfall products enlightens few aspects or issues that should consider before applying blending technique including density of rain gauge network and resolution of TRMM pixel

Utilización de sensores de humedad del suelo en la implementación de modelos climáticos en zonas de montaña mediterránea

Resumen: En esta tesis se presenta la utilización de sensores de humedad del suelo en la implementación de los modelos climáticos ECHAM5 MPI y GFDL M2-1 para la predicción de la respuesta de la humedad del suelo frente a los escenarios de cambio climático A1B, A2 y B1 en la cuenca de la Ribera Salada (España), para los períodos (2046-2065) y (2081-2100). Los datos de humedad de suelo fueron recolectados a escala horaria, por un periodo de nueve años, en ocho unidades experimentales seleccionadas por tipos y usos del suelo más representativos. Los datos de humedad del suelo simulados fueron obtenidos de los modelos hidrológicos semi-distribuido HBV y distribuido SHIA, calibrados a partir de un año de datos y validados para todo el periodo de estudio (2003-2011). Los resultados muestran que tanto HBV como SHIA simulan adecuadamente la dinámica de la humedad del suelo observada en la cuenca. Los diferentes escenarios evaluados proyectan una disminución en el contenido de agua en el suelo en todas las unidades experimentales de la cuenca.Abstract: In this thesis, the use of soil moisture sensors in the implementation of climate models ECHAM5 MPI and GFDL M2-1 for predicting the response of soil moisture versus climate change scenarios A1B, A2 and B1 in the Ribera Salada basin (Spain), for the periods (2046-2065) and (2081-2100), is presented. The soil moisture data were collected in an hourly basis for a period of nine years in eight experimental units selected by type of soil and use. Soil moisture simulated data were obtained from the semi-distributed hydrological model HBV and distributed model SHIA, calibrated from one year data and validated for the entire period of study (2003-2011). The results show that both HBV and SHIA adequately simulate the dynamics of the observed soil moisture data in the basin. Different scenarios evaluated expect a reduction of soil moisture in all experimental units in the basin.Maestrí

Weather and crop dynamics in a complex terrain, the Gamo Highlands – Ethiopia : Towards a high-resolution and model-observation based approach

Motivation: Ethiopia is one of the Sub-Saharan countries that are strongly influenced by climate fluctuations. These meteorological changes directly affect agriculture and consequently cause disturbances on the regional and local economy. To pinpoint a few crucial issues: (1) the agricultural sector in Ethiopia accounts for 80% of the employment and contributes 45% of the GDP. A relevant factor in relation to this PhD thesis is that the country’s agriculture is by 95% rainfed agronomy. (2) The Ethiopian landscape is composed of complex terrains of the East African mountain system – the Ethiopian Highlands (40% of the Ethiopia’s landmass is elevated more than 1500 m above sea level). This complex orography modulates weather and climate at scales ranging from local to regional. In the region, weather dynamics are mainly driven by both synoptic (e.g. Intertropical Convergence Zone – ITCZ) and mesoscale flows (e.g. lake and mountain breezes). These weather scales ultimately influence the way crops grow. The aim of this study was to evaluate how weather and crop growth vary in a complex terrain and heterogeneous landscape. I focus on the Gamo Highlands, south-west Ethiopia, a mountainous region with two large Rift-Valley lakes in Ethiopia. The crop of interest was potato – a crop that has become popular in Ethiopia, significantly contributing to food security and income, but sensitive to climatic variations. As a research method, I deployed a high-resolution weather and crop modelling approach to describe how the growth and yield of the potato crop depend on the variations in weather. For observation-based studies and for testing the models’ performance, six automatic weather stations were installed and field crop experiments were conducted near the stations. More specifically, this thesis addresses the role of meteorological crop drivers (e.g. the incoming shortwave radiation (SW↓), maximum temperature (Tmax), minimum temperature (Tmin) and precipitation (PPT)) and edaphic variables (soil moisture and soil temperature) on the yield and growth of the Ethiopian potato cultivars. Research methods and findings: In Chapter 1, I reviewed the contemporary global environmental challenge, the Anthropocene geologic era, in relation to the food system in perspective. In this chapter, I cascaded the problem from the global to the local scale. The chapter argued that the global weather models need to be downscaled to the local scales in order to study weather and climate impacts on crop dynamics in complex topographic landscapes such as Ethiopia. In Chapters 2 and 3, I presented the model-observation combined research strategy implemented in this thesis. The temporal and spatial variations in weather and crop dynamics are analysed using data from 2001 to 2010. To this end, the Weather Research and Forecasting (WRF) model is used to simulate weather at coarse (54 × 54 km2) and fine (2 × 2 km2) resolutions during the 10-years. The model is validated with in situ data. The meteorological crop growth drivers (SW↓, Tmax, Tmin, PPT, vapour pressure deficit and wind speed) and soil data from the ISRIC soil database are supplied as inputs to a process-based crop model called GECROS. The 10-year belg seasons WRF model analysis is showed large temporal and spatial variabilities in SW↓, Tmax, Tmin and PPT in the Gamo Highlands. For example, Tmax ranged from 10 °C on the summit of mount Guge to 30 °C in the valley around Lake Abaya and Lake Chamo. Temporally, the belg season of 2006 is identified as climatologically normal whilst the 2008 (driest) and 2010 (wettest) belg seasons are categorized as anomalous years. The temporal variations in simulated attainable potato yield showed a high yield (~20 to 30 t ha-1) during the normal belg season whereas the yield was lower (5 to 10 t ha-1 less than in the normal year) for the anomalous belg seasons (Chapter 2). As compared to the coarse resolution domain, the fine resolution domain is better represented topography and weather variations. Because of the improved representation of topography and weather in the fine resolution domain, the leaf area index (LAI) and the length of the growing season (LGS) simulated by the GECROS model were in the recommended range for potato (LAI of 3 m2 m-2 and LGS of 120 days are simulated). For comparison, modelled values were unacceptably low in the coarse resolution domain (LAI of 1.0 m2 m-2 and LGS of 60 days). It is also interesting to see that temperature and precipitation played opposing roles in the modelled yield, a phenomenon I called a compensating effect. To explain the term, moving up the mountains, the temperature decreases – with a positive effect on yield, and precipitation increases with a negative effect on yield. The lower temperature at higher elevation increases the LGS; as a result, more carbon is allocated to the tubers than in a shorter growing season. The higher precipitation at higher elevation may give rise to soil nutrient loss caused by leaching. Aloft the highlands, temperature and PPT are showed opposite trends, but their effects are balanced out in the ultimate yield (Chapter 3). Chapter 4 presented the Gamo Highlands Meteorological Stations (GEMS) – a network of six automatic weather stations, which were operational since April 2016 in two transects of the highlands. Near to the GEMS network, potato field trials are conducted. I used the GEMS data to study both the mesoscale and synoptic weather scales influencing the Gamo Highlands. Furthermore, I deployed the in situ data to the GECROS crop model. The GEMS data are analysed for belg-2017 showed major differences between the start (February) and the end (May) of the belg season. February and May are more mesoscale and synoptic scale weather system dominated months, respectively. During February, the day-night wind sources showed strong variation. Strong south to south-easterly lake breezes are observed during daytime; whereas, weak and more localised mountain winds are identified during the night-time. In May, the day-night flow contrast was small and the dominant flows were southerly. The location of ITCZ calculated by the NOAA (National Oceanic and Atmospheric Administration) and the GEMS observed sea-level-pressure (SLP) data showed strong correlation. My analysis showed that the low-pressure system (ITCZ) and the rainbelt are not coincided in the Gamo Highlands. The maximum PPT is received in May where the ITCZ is located on average nearly 6° (north) away from Gamo Highlands. During the maximum PPT in May 2017, the southerly moist air masses from the moisture sources (e.g. Indian Ocean) may move to the low-pressure system located to the north of the study area. During the daytime, PPT is less probable as cloud formation was less likely due to the enhanced solar radiation. However, during night-time, the southerly moisture can be trapped in the highlands and orographic PPT can be triggered. This PPT is locally modulated due to the presence of the Gamo Highlands and presence of the lakes. The moisture is crucial for potato agronomy during the belg season. The GECROS model sensitivity analysis, using the GEMS data, showed that model input of constant PPT (belg-averaged) gave the highest crop yield due to improved soil moisture throughout the growing season. Chapter 5 dealt with investigating the role of environmental factors on potato yield and growth in the Gamo Highlands. Here, the GEMS weather and edaphic data are correlated with crop growth variables such as plant height, canopy cover, yield and yield traits. The GEMS and crop observation datasets showed that plant height and canopy cover are strongly correlated with temperature sum (Tsum) with an r2 > 0.95 during the canopy buildup phase (P1). Tsum (d °C) is defined as the sum of the daily average temperatures during the growing season. The crop growth - Tsum correlation is further explained in terms of SW↓ and soil moisture, in which an improved (Gudene) and a local (Suthalo) cultivar showed different responses to SW↓ and soil moisture regimes. Data also showed that tuber yield is poorly explained by meteorological and edaphic data, suggesting further research activity in this regard. When the number of days to crop maturity was between 100-110 days, an optimal tuber yield is obtained. Chapter 6 presented the main findings of the thesis in perspective. Finally, Chapter 7 discussed the key findings in-line with the research questions stated in Chapter 1. Conclusions and perspectives: In complex terrain, weather/climate varies over short distances affecting crop growth. To describe crop growth and yield in the region, a high-resolution weather model, coupled to a crop model is needed. The weather model outputs can be used as input to the crop model. A dense station network installed in a complex topographic region can give us insights on mesoscale flows (e.g. lake-mountain flows), synoptic systems (e.g. south-north movement of the ITCZ) and crop growth (e.g. LGS and LAI). Additional weather stations (e.g. on the lee-side of the Gamo Highlands and east of the Lakes Abaya and Chamo) can give us improved understanding of weather scales and crop growth. Tsum during the P1 is found to be a good predictor of plant height and canopy cover for the Ethiopian potato cultivars. The poor correlation between environmental variables and yield and yield traits suggests more dedicated field experiments should be designed. One of the suggested field experiments is continuous monitoring of the partitioning of dry matter to the tubers to study how crop yield varies as a function of elevation and meteorology.</p