Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for OPEN ACCESSRemote Sens. 2015, 7 1759 different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

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The CORE-CLIMAX project has delivered methods and assessments of the capability to provide climate data records, processes for deriving and validating these records, and opportunities to feed back the lessons learned from reanalysis.

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Although the importance of ENSO on hydrological anomalies has been recognized, variations in sediment fluxes caused by these extreme events are poorly documented. The effect of ENSO is not limited to changes in sediment mobilization. Since ENSO events can affect terrestrial ecosystems, they may have important effects on sediment production and transport in river basins over time spans that are longer than the duration of the event itself. The Catamayo-Chira basin is an interesting casestudy for investigating these geomorphic implications. The objectives were: (i) to study the effect of ENSO on stream flow and sediment yields in the basin, (ii) to investigate if ENSO events affect sediment yields in the post-ENSO period and (iii) to understand which factors control the ENSO and post-ENSO basin response. During strong negative ENSO periods, mean annual stream flow discharge at the inlet of the Poechos reservoir in the lower basin was 5.4 times higher than normal annual discharges, while average sediment fluxes exceeded those of normal years by a factor of about 11. In two heavily affected periods, 45.9% of the total sediment yield in the 29years observation period was generated. Sediment fluxes in the post-ENSO period are lower than expected, which proves post-ENSO event dynamics are significantly different from pre-event dynamics. Our analysis indicates the increase of vegetation growth in the lower basin is not the main reason explaining considerable sediment flux decrease in post-ENSO periods. During strong ENSO events, sediment in alluvial stores in the lower part of the basin is removed due to enlarging and deepening of channels. In post-ENSO periods, normal discharges and persisting sediment supplies from the middle/upper basin lead to river aggradation and storage of large amounts of sediment in alluvial plains. The decrease in sediment export will last for several years until the equilibrium is reestablished.

PROBA-V (PRoject for On-Board Autonomy-Vegetation) was launched in May-2013 as an operational continuation to the vegetation (VGT) instruments on-board the Système Pour l'Observation de la Terre (SPOT)-4 and -5 satellites. The first reprocessing campaign of the PROBA-V archive from Collection 0 (C0) to Collection 1 (C1) aims at harmonizing the time series, thanks to improved radiometric and geometric calibration and cloud detection. The evaluation of PROBA-V C1 focuses on (i) qualitative and quantitative assessment of the new cloud detection scheme; (ii) quantification of the effect of the reprocessing by comparing C1 to C0; and (iii) evaluation of the spatio-temporal stability of the combined SPOT/VGT and PROBA-V archive through comparison to METOP/advanced very high resolution radiometer (AVHRR). The PROBA-V C1 cloud detection algorithm yields an overall accuracy of 89.0%. Clouds are detected with very few omission errors, but there is an overdetection of clouds over bright surfaces. Stepwise updates to the visible and near infrared (VNIR) absolute calibration in C0 and the application of degradation models to the SWIR calibration in C1 result in sudden changes between C0 and C1 Blue, Red, and NIR TOC reflectance in the first year, and more gradual differences for short-wave infrared (SWIR). Other changes result in some bias between C0 and C1, although the root mean squared difference (RMSD) remains well below 1% for top-of-canopy (TOC) reflectance and below 0.02 for the normalized difference vegetation index (NDVI). Comparison to METOP/AVHRR shows that the recent reprocessing campaigns on SPOT/VGT and PROBA-V have resulted in a more stable combined time series.are widely used to monitor environmental change and the evolution of vegetation cover in different thematic domains [2], hence the relevance to the continuity of the service.On board the PROBA-V, the optical instrument provides data at 1 km, 300 m, and 100 m consistent with the 1 km resolution data products of SPOT/VGT [3]. To support the existing SPOT/VGT user community, the PROBA-V mission continues provision of projected segments (Level 2A, similar to the SPOT/VGT P-products), daily top-of-canopy (TOC) synthesis (S1-TOC) and 10-day synthesis (S10-TOC) products. In addition, top-of-atmosphere (TOA) daily synthesis (S1-TOA) products and radiometrically/geometrically corrected data (level 1C) products in raw resolution (up to 100 m) are provided for scientific use [4,5]. Since PROBA-V has no onboard propellant, the overpass time (10:45 h at launch) will decrease as a result of increasing atmospheric drag [6].In previous years, vegetation monitoring applications were built on PROBA-V data, e.g., on cropland mapping [7], crop identification [8], estimation of biophysical parameters [9,10], and crop yield forecasting [11]. A method was also developed to assimilate data of PROBA-V 100 and 300 m [12]. For the Copernicus Global Land Service, PROBA-V is one of the prime sensors for operational vegetation products [13,14]. Access to and exploitation of the SPOT/...

Environmental change is an important issue in the Andes region. The objectives of this research are to study NDVI dynamics in the Andes region based on time series analysis of SPOT-Vegetation and NOAA-AVHRR, and to recognize to which extent this variability can be attributed to either climatic variability or human induced impacts. Correlation analysis between NDVI and SPI were performed in order to identify the best lag per pixel. Trends in SDVI and SPI were investigated using linear least square regression. Significant vegetation trends are found in 46% of the area. Both NDVI time series lead to different results, but the coupling of vegetation and precipitation is more pronounced for the SPOT-Vegetation data.

To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR’s statistical and temporal consistency is high. iCOR AOT retrievals overestimate relative to AERONET, but less than SYN L2. iCOR and SYN L2 TOC reflectances exhibit a negative bias of ~−0.01 and −0.02, respectively, in the Blue bands compared to the simulations. This diminishes for RED and NIR, except for a +0.02 bias for SYN L2 in the NIR. The intercomparison with RadCalNet shows relative differences <±6%, except for bands Oa02 (Blue) and Oa21 (NIR), which is likely related to the reported OLCI “excess of brightness”. The intercomparison between iCOR and SYN L2 showed R2 = 0.80–0.93 and R2 = 0.92–0.96 for TOC reflectance and VIs, respectively. iCOR’s higher temporal smoothness compared to SYN L2 does not propagate into a significantly higher smoothness for TOC reflectance and VIs. Altogether, we conclude that iCOR is well suitable to retrieve statistically and temporally consistent AOT, TOC reflectance, and VIs over land surfaces from Sentinel-3/OLCI observations.