Mélanie Becker

Estimating ENSO Influence on the Global Mean Sea Level, 1993–2010

Interannual global mean sea level (GMSL) variations and El Nino-Southern Oscillation (ENSO) are highly correlated, with positive/negative GMSL anomalies during El Nino/La Nina events. In a previous study, we showed that interannual GMSL and total land water storage variations are inversely correlated, with lower-than-average total water storage on land and higher-than-average GMSL during El Nino. This result is in agreement with the observed rainfall deficit/excess over land/oceans during El Nino (and vice versa during La Nina). It suggests that the positive GMSL anomaly observed during El Nino is likely due to an ocean mass rather than thermal expansion increase. Here, we analyze the respective contribution of the Atlantic, Indian, and Pacific oceans to the interannual (ENSO-related) GMSL anomalies observed during the altimetry era (i.e., since 1993) with an emphasis on the 1997/1998 El Nino event. For each oceanic region, we compute the steric contribution, and remove it from the altimetry-based mean sea level to estimate the ocean mass component. We find that mass changes of the tropical Pacific Ocean, mainly in the region within 0–25°N, are mostly responsible for the observed 1997/1998 ENSO-related GMSL anomaly. The ocean mass excess of this region almost perfectly compensates the total land water deficit during the 1997/1998 El Nino. An estimate of the ocean-atmosphere water balance of this region shows that the time derivative of the ocean mass component is well correlated with net P-E (precipitation minus evaporation) over most of the study period, except during the 1997/1998 ENSO event, where there is a temporary ocean mass increase, not compensated by the net P-E. We thus propose that the 1997/1998 ocean mass increase of this north tropical Pacific area be linked to an imbalance between the inflow/outflow entering/leaving the north tropical Pacific. A preliminary qualitative analysis indicates that a significant reduction of the Makassar Strait transport, (about 80% of the total Indonesian throughflow), as previously reported in the literature during the strong 1997/1998 El Nino event, could explain the north tropical Pacific Ocean mass excess reported in this study, hence the observed positive GMSL anomaly.

Global surveys of reservoirs and lakes from satellites and regional application to the Syrdarya river basin

Large reservoirs along rivers regulate downstream flows to generate hydropower but may also store water for irrigation and urban sectors. Reservoir management therefore becomes critical, particularly for transboundary basins, where coordination between riparian countries is needed. Reservoir management is even more important in semiarid regions where downstream water users may be totally reliant on upstream reservoir releases. If the water resources are shared between upstream and downstream countries, potentially opposite interests arise as is the case in the Syrdarya river in Central Asia. In this case study, remote sensing data (radar altimetry and optical imagery) are used to highlight the potential of satellite data to monitor water resources: water height, areal extent and storage variations. New results from 20 years of monitoring using satellites over the Syrdarya basin are presented. The accuracy of satellite data is 0.6 km3 using a combination of MODIS data and satellite altimetry, and only 0.2 km3 with Landsat images representing 2–4% of average annual reservoir volume variations in the reservoirs in the Syrdarya basin. With future missions such as Sentinel-3A (S3A), Sentinel-3B (S3B) and surface water and ocean topography (SWOT), significant improvement is expected. The SWOT missions main payload (a radar interferometer in Ka band) will furthermore provide 2D maps of water height, reservoirs, lakes, rivers and floodplains, with a temporal resolution of 21 days. At the global scale, the SWOT mission will cover reservoirs with areal extents greater than 250 × 250 m with 20 cm accuracy.

Regional sea level change and variability in the Caribbean sea since 1950

Regional sea level change and variability in the Caribbean sea since 1950 We investigate the regional variability in sea level in the Caribbean Sea region over the past 60 years (1950-2009) using an Empirical Orthogonal Function (EOF)-based 2-dimensional past sea level reconstruction (a mean of 3 reconstructions based on few long tide gauge records and different sea level grids from satellite altimetry and ocean circulation models) and satellite altimetry data for the last two decades. We find that over the past 60 years, the mean rate of sea level rise in the region was similar to the global mean rise (~1.8 mm/yr). The interannual mean sea level of the placeCaribbean region appears highly correlated with El Nino-Southern Oscillation (ENSO) indices. Interpolation of the sea level reconstruction grid at different sites, in particular at the Caribbean Islands where tide gauge records are either very short or inexistent, shows that locally, the sea level trend is on the order of 2 mm/yr, i.e. only slightly larger than the mean trend over the region. Besides, correlation with ENSO is in general good, especially since the mid-1980s. We also find a significant correlation between the interannual variability in sea level and hurricane activity, especially over the past decade during which hurricane intensity and sea level interannual variability have both increased.

Water Level Fluctuations in the Congo Basin Derived from ENVISAT Satellite Altimetry

In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present the largest altimetry-based dataset of water levels ever constituted over the entire Congo Basin. This dataset of water levels illuminates the hydrological regimes of various tributaries of the Congo River. A total of 140 water level time series are extracted using ENVISAT altimetry over the period of 2003 to 2009. To improve the understanding of the physical phenomena dominating the region, we perform a K-means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. This analysis reveals nine distinct hydrological regions. The proposed regionalization scheme is validated and therefore considered reliable for estimating monthly water level variations in the Congo Basin. This result confirms the potential of satellite altimetry in monitoring spatio-temporal water level variations as a promising and unprecedented means for improved representation of the hydrologic characteristics in large ungauged river basins.

Temporal and Spatial Assessment of Four Satellite Rainfall Estimates over French Guiana and North Brazil

Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitation is therefore of great importance. Unfortunately, there are very few rain gauges available in the region. The objective of the study is then to compare satellite rainfall estimation products in order to complement the information available in situ and to perform a regional analysis of four operational precipitation estimates, by partitioning the whole area under study into a homogeneous hydro-climatic region. In this study, four satellite products have been tested, TRMM TMPA (Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis) V7 (Version 7) and RT (real time), CMORPH (Climate Prediction Center (CPC) MORPHing technique) and PERSIANN (Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network), for daily rain gauge data. Product performance is evaluated at daily and monthly scales based on various intensities and hydro-climatic regimes from 1 January 2001 to 30 December 2012 and using quantitative statistical criteria (coefficient correlation, bias, relative bias and root mean square error) and quantitative error metrics (probability of detection for rainy days and for no-rain days and the false alarm ratio). Over the entire study period, all products underestimate precipitation. The results obtained in terms of the hydro-climate show that for areas with intense convective precipitation, TMPA V7 shows a better performance than other products, especially in the estimation of extreme precipitation events. In regions along the Amazon, the use of PERSIANN is better. Finally, in the driest areas, TMPA V7 and PERSIANN show the same performance.

Improved bathymetric dataset and tidal model for the head Bay of Bengal

ABSTRACT The Bengal Delta is a highly complex and vulnerable environment where key dynamical features such as tides, storm surges, salinity, and sediment transport strongly depend on the accurate bottom topography representation. To curb the lack of accuracy of widely used global bathymetry databases in this shallow region, we produced an improved coastal bathymetry for the Bengal Delta through an exhaustive and thorough compilation of 70 nautical charts and river surveys. We merged this bathymetry dataset with a high-resolution digital evaluation model, resulting in a novel, consistent product with unprecedented coverage, from the deep parts of the ocean basin (north of 20°N) to the far upstream areas of the delta (around 24°N). This new bathymetry reduces errors in the tidal residuals by a factor of 2–3 for most coastal gauges as compared to global tidal models. The best results are obtained for the Hooghly River, where errors are as low as 6 cm. The improvement in the mouth of the Meghna is moderate, suggesting the possible rapid evolution of the bathymetry due to strong sediment transport. This new bathymetry is expected to significantly improve the modeling of coastal processes such as storm surges in the northern Bay of Bengal.

Calibration of TRMM 3B42 with Geographical Differential Analysis over North Amazonia

This study aimed to calibrate Tropical Rainfall Measuring Mission (TRMM) data over northern Amazonia with Geographical Differential Analysis (GDA) on daily and monthly scale. Assessment of calibrated satellite rainfall estimates are conducted and showed great improvement of statistical performances.

Contributions of a Strengthened Early Holocene Monsoon and Sediment Loading to Present‐Day Subsidence of the Ganges‐Brahmaputra Delta

The contribution of subsidence to relative sea level rise in the Ganges‐Brahmaputra delta (GBD) is largely unknown and may considerably enhance exposure of the Bengal Basin populations to sea level rise and storm surges. This paper focuses on estimating the present‐day subsidence induced by Holocene sediment in the Bengal Basin and by oceanic loading due to eustatic sea level rise over the past 18 kyr. Using a viscoelastic Earth model and sediment deposition history based on in situ measurements, results suggest that massive sediment influx initiated in the early Holocene under a strengthened South Asian monsoon may have contributed significantly to the present‐day subsidence of the GBD. We estimate that the Holocene loading generates up to 1.6 mm/yr of the present‐day subsidence along the GBD coast, depending on the rheological model of the Earth. This rate is close to the twentieth century global mean sea level rise (1.1–1.7 mm/yr). Thus, past climate change, by way of enhanced sedimentation, is impacting vulnerability of the GBD populations.

Satellite-based estimates of surface water dynamics in the Congo River Basin

In the Congo River Basin (CRB), due to the lack of contemporary in situ observations, there is a limited understanding of the large-scale variability of its present-day hydrologic components and their link with climate. In this context, remote sensing observations provide a unique opportunity to better characterize those dynamics. Analyzing the Global Inundation Extent Multi-Satellite (GIEMS) time series, we first show that surface water extent (SWE) exhibits marked seasonal patterns, well distributed along the major rivers and their tributaries, and with two annual maxima located: i) in the lakes region of the Lwalaba sub-basin and ii) in the “Cuvette Centrale”, including Tumba and Mai-Ndombe Lakes. At an interannual time scale, we show that SWE variability is influenced by ENSO and the Indian Ocean dipole events. We then estimate water level maps and surface water storage (SWS) in floodplains, lakes, rivers and wetlands of the CRB, over the period 2003-2007, using a multi-satellite approach, which combines the GIEMS dataset with the water level measurements derived from the ENVISAT altimeter heights. The mean annual variation in SWS in the CRB is 81±24 km3 and contributes to 19±5 % of the annual variations of GRACE-derived terrestrial water storage (33±7 % in the Middle Congo). It represents also ~6±2 % of the annual water volume that flows from the Congo River into the Atlantic Ocean.