Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–Č Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-1501 PEER REVIEWED ARTICLE 2018 Laura E. Revell , Andrea Stenke , Fiona Tummon , Aryeh Feinberg , Eugene Rozanov , Thomas Peter , N. Luke Abraham , Hideharu Akiyoshi , Alexander T. A Tropospheric ozone in CCMI models and Gaussian process emulation to understand biases in the SOCOLv3 chemistry–climate model 10.5194/acp-18-16155-2018 Simulation & Modeling Precipitation & Ecological Systems Abstract. Previous multi-model intercomparisons have shown that chemistry–climate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARC–IGAC (Stratosphere–troposphere Processes And their Role in Climate–International Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %–50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to ∌30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU – approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, “SOCOLv3.1”, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NOx), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NOx than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistry–climate models. 603557
publications-1502 PEER REVIEWED ARTICLE 2019 Erik Romanowsky , Dörthe Handorf , Ralf Jaiser , Ingo Wohltmann , Wolfgang Dorn , Jinro Ukita , Judah Cohen , Klaus Dethloff , Markus Rex The role of stratospheric ozone for Arctic-midlatitude linkages 10.1038/s41598-019-43823-1 Simulation & Modeling Precipitation & Ecological Systems AbstractArctic warming was more pronounced than warming in midlatitudes in the last decades making this region a hotspot of climate change. Associated with this, a rapid decline of sea-ice extent and a decrease of its thickness has been observed. Sea-ice retreat allows for an increased transport of heat and momentum from the ocean up to the tropo- and stratosphere by enhanced upward propagation of planetary-scale atmospheric waves. In the upper atmosphere, these waves deposit the momentum transported, disturbing the stratospheric polar vortex, which can lead to a breakdown of this circulation with the potential to also significantly impact the troposphere in mid- to late-winter and early spring. Therefore, an accurate representation of stratospheric processes in climate models is necessary to improve the understanding of the impact of retreating sea ice on the atmospheric circulation. By modeling the atmospheric response to a prescribed decline in Arctic sea ice, we show that including interactive stratospheric ozone chemistry in atmospheric model calculations leads to an improvement in tropo-stratospheric interactions compared to simulations without interactive chemistry. This suggests that stratospheric ozone chemistry is important for the understanding of sea ice related impacts on atmospheric dynamics. 603557
publications-1503 PEER REVIEWED ARTICLE 2019 Marta Abalos , Lorenzo Polvani , Natalia Calvo , Douglas Kinnison , Felix Ploeger , William Randel , Susan Solomon New Insights on the Impact of Ozone‐Depleting Substances on the Brewer‐Dobson Circulation 10.1029/2018jd029301 Simulation & Modeling Precipitation & Ecological Systems AbstractIt has recently been recognized that, in addition to greenhouse gases, anthropogenic emissions of ozone‐depleting substances (ODS) can induce long‐term trends in the Brewer‐Dobson circulation (BDC). Several studies have shown that a substantial fraction of the residual circulation acceleration over the last decades of the twentieth century can be attributed to increasing ODS. Here the mechanisms of this influence are examined, comparing model runs to reanalysis data and evaluating separately the residual circulation and mixing contributions to the mean age of air trends. The effects of ozone depletion in the Antarctic lower stratosphere are found to dominate the ODS impact on the BDC, while the direct radiative impact of these substances is negligible over the period of study. We find qualitative agreement in austral summer BDC trends between model and reanalysis data and show that ODS are the main driver of both residual circulation and isentropic mixing trends over the last decades of the twentieth century. Moreover, aging by isentropic mixing is shown to play a key role on ODS‐driven age of air trends. 603557
publications-1504 PEER REVIEWED ARTICLE 2014 Luca Brocca , Luca Ciabatta , Christian Massari , Tommaso Moramarco , Sebastian Hahn , Stefan Hasenauer , Richard Kidd , Wouter Dorigo , Wolfgang Wagn Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data 10.1002/2014jd021489 Simulation & Modeling Precipitation & Ecological Systems AbstractMeasuring precipitation intensity is not straightforward; and over many areas, ground observations are lacking and satellite observations are used to fill this gap. The most common way of retrieving rainfall is by addressing the problem “top‐down” by inverting the atmospheric signals reflected or radiated by atmospheric hydrometeors. However, most applications are interested in how much water reaches the ground, a problem that is notoriously difficult to solve from a top‐down perspective. In this study, a novel “bottom‐up” approach is proposed that, by doing “hydrology backward,” uses variations in soil moisture (SM) sensed by microwave satellite sensors to infer preceding rainfall amounts. In other words, the soil is used as a natural rain gauge. Three different satellite SM data sets from the Advanced SCATterometer (ASCAT), the Advanced Microwave Scanning Radiometer (AMSR‐E), and the Microwave Imaging Radiometer with Aperture Synthesis are used to obtain three new daily global rainfall products. The “First Guess Daily” product of the Global Precipitation Climatology Centre (GPCC) is employed as main benchmark in the validation period 2010–2011 for determining the continuous and categorical performance of the SM‐derived rainfall products by considering the 5 day accumulated values. The real‐time version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis product, i.e., the TRMM‐3B42RT, is adopted as a state‐of‐the‐art satellite rainfall product. The SM‐derived rainfall products show good Pearson correlation values (R) with the GPCC data set, mainly in areas where SM retrievals are found to be accurate. The global median R values (in the latitude band ±50°) are equal to 0.54, 0.28, and 0.31 for ASCAT‐, AMSR‐E‐, and SMOS‐derived products, respectively. For comparison, the median R for the TRMM‐3B42RT product is equal to 0.53. Interestingly, the SM‐derived products are found to outperform TRMM‐3B42RT in terms of average global root‐mean‐square error statistics and in terms of detection of rainfall events. The regions for which the SM‐derived products perform very well are Australia, Spain, South and North Africa, India, China, the Eastern part of South America, and the central part of the United States. The SM‐derived products are found to estimate accurately the rainfall accumulated over a 5 day period, an aspect particularly important for their use for hydrological applications, and that address the difficulties of estimating light rainfall from TRMM‐3B42RT. 603608
publications-1505 PEER REVIEWED ARTICLE 2015 E.I. Nikolopoulos , N. Bartsotas , E. N. Anagnostou , G. Kallos Using high-resolution numerical weather forecasts to improve remotely sensed rainfall estimates: The case of the 2013 Colorado flash flood. 10.1175/jhm-d-14-0207.1 Simulation & Modeling Precipitation & Ecological Systems AbstractThe September 2013 flash flood–triggering rainfall event in Colorado highlighted the strong underestimation of remote sensing techniques over mountainous terrain. In this work, the use of high-resolution rainfall forecasts for adjusting weather radar– [Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation (Q3)] and satellite-based [CPC morphing technique (CMORPH) and TRMM 3B42RT] rainfall estimates is examined. Evaluation of the adjustment procedures is based on the NCEP Stage IV product. Results show that 1-km-grid-resolution rainfall forecasts provided by a numerical weather prediction model [Regional Atmospheric Modeling System and Integrated Community Limited Area Modeling System (RAMS-ICLAMS)] adequately captured total rainfall amounts during the event and could therefore be used to adjust biases in radar and satellite rainfall estimates. Two commonly used adjustment procedures according to 1) mean field bias and 2) probability density function matching are examined. Findings indicate that both procedures are successful in improving the original radar and satellite rainfall estimates, with the first method consistently providing the highest bias reduction while the second exhibits higher improvement in RMSE and correlation. 603608
publications-1506 PEER REVIEWED ARTICLE 2015 Veldkamp, T. I. E., Wada, Y., de Moel, H., Kummu, M., Eisner, S., Aerts, J. C. J. H., & Ward, P. J. Changing mechanism of global water scarcity events: Impacts of socioeconomic changes and inter-annual hydro-climatic variability. 10.1016/j.gloenvcha.2015.02.011 Uncategorized Precipitation & Ecological Systems No abstract available 603608
publications-1507 PEER REVIEWED ARTICLE 2015 Anne H. A. de Nijs , Robert M. Parinussa , Richard A. M. de Jeu , Jaap Schellekens , Thomas R. H. Holmes A Methodology to Determine Radio-Frequency Interference in AMSR2 Observations 10.1109/tgrs.2015.2417653 Uncategorized Precipitation & Ecological Systems No abstract available 603608
publications-1508 PEER REVIEWED ARTICLE 2014 Filipe Aires , Fabrice Papa , Catherine Prigent , Jean-François CrĂ©taux , Muriel Berge-Nguyen Characterization and Space–Time Downscaling of the Inundation Extent over the Inner Niger Delta Using GIEMS and MODIS Data 10.1175/jhm-d-13-032.1 Simulation & Modeling Precipitation & Ecological Systems Abstract The objective in this work is to develop downscaling methodologies to obtain a long time record of inundation extent at high spatial resolution based on the existing low spatial resolution results of the Global Inundation Extent from Multi-Satellites (GIEMS) dataset. In semiarid regions, high-spatial-resolution a priori information can be provided by visible and infrared observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). The study concentrates on the Inner Niger Delta where MODIS-derived inundation extent has been estimated at a 500-m resolution. The space–time variability is first analyzed using a principal component analysis (PCA). This is particularly effective to understand the inundation variability, interpolate in time, or fill in missing values. Two innovative methods are developed (linear regression and matrix inversion) both based on the PCA representation. These GIEMS downscaling techniques have been calibrated using the 500-m MODIS data. The downscaled fields show the expected space–time behaviors from MODIS. A 20-yr dataset of the inundation extent at 500 m is derived from this analysis for the Inner Niger Delta. The methods are very general and may be applied to many basins and to other variables than inundation, provided enough a priori high-spatial-resolution information is available. The derived high-spatial-resolution dataset will be used in the framework of the Surface Water Ocean Topography (SWOT) mission to develop and test the instrument simulator as well as to select the calibration validation sites (with high space–time inundation variability). In addition, once SWOT observations are available, the downscaled methodology will be calibrated on them in order to downscale the GIEMS datasets and to extend the SWOT benefits back in time to 1993. 603608
publications-1509 PEER REVIEWED ARTICLE 2015 Jean-François Rysman , Chantal Claud , Jean-Pierre Chaboureau , Julien DelanoĂ« , Beatriz M. Funatsu Severe convection in the Mediterranean from microwave observations and a convection-permitting model 10.1002/qj.2611 Data Management & Analytics Precipitation & Ecological Systems This study investigates severe convection in the Mediterranean during the first Special Observation Period (SOP‐1; 5 September to 6 November 2012) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX) with the objectives of providing novel information about severe convection on its vertical structure, spatio‐temporal variability as well as evaluating the ability of a convection‐permitting model to reproduce this variability. Two criteria, namely deep convection (DC) and convective overshooting (COV), are computed using the water vapour channels of the Microwave Humidity Sounder (MHS). Special attention is paid to the COV as it is associated with particularly severe weather. For the first time, the COV criterion was assessed in the Mediterranean, using two case‐studies conjointly observed by the airborne RASTA radar and MHS. COV is characterised by high ice water content (up to 2 g m−3) in the mid and upper troposphere (up to 12.5 km in the stratosphere). During the SOP‐1, DC and COV occurred about 0.1 and 0.03% of the total observation time, respectively. The Atlantic weather regimes appear to affect the temporal distribution of these convective events. Most of the DC and COV occurrences were found along the western coasts of Italy and Greece, mainly during the 10–15 October and 25 October–3 November episodes. These two episodes, for which severe meteorological events (e.g. tornadoes) were reported, are significant when compared with the 2002–2013 climatology (above the 75th percentile). Both criteria are also employed to assess the current ability of the Meso‐NH model to forecast severe convection using a model‐to‐satellite approach. The forecast DC and COV are found to be highly correlated in time with the observations, but are strongly underestimated. This suggests that the model missed a significant part of the most intense convective events and their associated hazards, and underlines the need for better characterisation of model uncertainties associated with severe convection. 603608
publications-1510 PEER REVIEWED ARTICLE 2015 Alexander Gruber , Wade Crow , Wouter Dorigo , Wolfgang Wagner The potential of 2D Kalman filtering for soil moisture data assimilation 10.1016/j.rse.2015.10.019 Data Management & Analytics Precipitation & Ecological Systems No abstract available 603608