scholarly journals Intercomparison of freshwater fluxes over ocean and investigations into water budget closure

2020 ◽  
Author(s):  
Marloes Gutenstein ◽  
Karsten Fennig ◽  
Marc Schröder ◽  
Tim Trent ◽  
Stephan Bakan ◽  
...  
Keyword(s):  
Water Vapor ◽  
Satellite Data ◽  
Water Budget ◽  
Water Cycle ◽  
Global Ocean ◽  
Freshwater Flux ◽  
Data Sets ◽  
Climate Data ◽  
The Difference ◽  
Global Water

Abstract. The development of algorithms for the retrieval of water cycle components from satellite data, such as total column water vapor content (TCWV), precipitation (P), latent heat flux, and evaporation (E) has seen much progress in the past three decades. In the present study, we compare six recent satellite-based retrieval algorithms and ERA5 (the European Centre for Medium-Range Weather Forecasts' fifth reanalysis) freshwater flux (E–P) data regarding global and regional, seasonal and inter-annual variation to assess the degree of correspondence among them. The compared data sets are recent, freely available and documented climate data records (CDRs), developed with a focus on stability and homogeneity of the time series, as opposed to instantaneous accuracy. One main finding of our study is the agreement of global ocean means of all E–P data sets within the uncertainty ranges of satellite-based data. Regionally, however, significant differences are found among the satellite data and with ERA5. Regression analyses of regional monthly means of E, P, and E–P against the statistical median of the satellite data ensemble (SEM) show that, despite substantial differences in global E patterns, deviations among E–P data are dominated by differences in P throughout the globe. E–P differences among data sets are spatially inhomogeneous. We observe that for ERA5 long-term global E–P is very close to 0 mm/day and that there is good agreement between land and ocean mean E–P, vertically integrated moisture divergence (VIMD), and global TCWV tendency. The fact that E and P are balanced globally provides an opportunity to investigate the consistency between E and P data sets. Over ocean, P (nearly) balances with E if the net transport of water vapor from ocean to land (over-ocean VIMD, i.e., ∇Qocean) is taken into account. Correlation of Eocean − ∇Qocean with Pocean yields R2 = 0.86 for ERA5, but smaller R2 are found for satellite data sets. Climatological global yearly totals of water cycle components (E, P, E–P, and net transport from ocean to land and vice versa) calculated from the data sets used in this study are in agreement with previous studies, with ERA5 E and P are occupying the upper part of the range. Over ocean, both the spread among satellite-based E and the difference between two satellite-based P data sets are greater than E–P and these remain the largest sources of uncertainty within the observed global water budget. We conclude that for a better understanding of the global water budget, the quality of E and P data sets themselves and their associated uncertainties need to be further investigated.

scholarly journals Intercomparison of freshwater fluxes over ocean and investigations into water budget closure

2021 ◽  
Vol 25 (1) ◽  
pp. 121-146
Author(s):  
Marloes Gutenstein ◽  
Karsten Fennig ◽  
Marc Schröder ◽  
Tim Trent ◽  
Stephan Bakan ◽  
...  
Keyword(s):  
Water Vapor ◽  
Satellite Data ◽  
Water Budget ◽  
Water Cycle ◽  
Global Ocean ◽  
Freshwater Flux ◽  
Data Sets ◽  
Climate Data ◽  
Flux Divergence ◽  
Global Water

Abstract. The development of algorithms for the retrieval of water cycle components from satellite data – such as total column water vapor content (TCWV), precipitation (P), latent heat flux, and evaporation (E) – has seen much progress in the past 3 decades. In the present study, we compare six recent satellite-based retrieval algorithms and ERA5 (the European Centre for Medium-Range Weather Forecasts' fifth reanalysis) freshwater flux (E−P) data regarding global and regional, seasonal and interannual variation to assess the degree of correspondence among them. The compared data sets are recent, freely available, and documented climate data records (CDRs), developed with a focus on stability and homogeneity of the time series, as opposed to instantaneous accuracy. One main finding of our study is the agreement of global ocean means of all E−P data sets within the uncertainty ranges of satellite-based data. Regionally, however, significant differences are found among the satellite data and with ERA5. Regression analyses of regional monthly means of E, P, and E−P against the statistical median of the satellite data ensemble (SEM) show that, despite substantial differences in global E patterns, deviations among E−P data are dominated by differences in P throughout the globe. E−P differences among data sets are spatially inhomogeneous. We observe that for ERA5 long-term global E−P is very close to 0 mm d−1 and that there is good agreement between land and ocean mean E−P, vertically integrated moisture flux divergence (VIMD), and global TCWV tendency. The fact that E and P are balanced globally provides an opportunity to investigate the consistency between E and P data sets. Over ocean, P (nearly) balances with E if the net transport of water vapor from ocean to land (approximated by over-ocean VIMD, i.e., ∇⋅(vq)ocean) is taken into account. On a monthly timescale, linear regression of Eocean-∇⋅(vq)ocean with Pocean yields R2=0.86 for ERA5, but smaller R2 values are found for satellite data sets. Global yearly climatological totals of water cycle components (E, P, E−P, and net transport from ocean to land and vice versa) calculated from the data sets used in this study are in agreement with previous studies, with ERA5 E and P occupying the upper part of the range. Over ocean, both the spread among satellite-based E and the difference between two satellite-based P data sets are greater than E−P, and these remain the largest sources of uncertainty within the observed global water budget. We conclude that, for a better understanding of the global water budget, the quality of E and P data sets needs to be improved, and the uncertainties more rigorously quantified.

scholarly journals The European 2015 drought from a hydrological perspective

2017 ◽  
Vol 21 (6) ◽  
pp. 3001-3024 ◽  
Author(s):  
Gregor Laaha ◽  
Tobias Gauster ◽  
Lena M. Tallaksen ◽  
Jean-Philippe Vidal ◽  
Kerstin Stahl ◽  
...  
Keyword(s):  
Water Cycle ◽  
Hydrological Drought ◽  
Low Flow ◽  
Drought Indices ◽  
Climate Indices ◽  
Climate Data ◽  
Spatial And Temporal Scales ◽  
Space And Time ◽  
Dynamic Development ◽  
The Difference

Abstract. In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future.

Ocean Salinity changes in the global ocean under global warming conditions Part 1: Mechanisms in a strong warming scenario

2021 ◽  
pp. 1-56
Author(s):  
Anju Sathyanarayanan ◽  
Armin Köhl ◽  
Detlef Stammer
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Spatial Scales ◽  
Sea Surface Salinity ◽  
Global Ocean ◽  
Dynamical Response ◽  
Freshwater Flux ◽  
Near Surface ◽  
Salinity Changes ◽  
Circulation Changes

AbstractWe investigate mechanisms underlying salinity changes projected to occur under strong representative concentration pathway (RCP) 8.5 forcing conditions. The study is based on output of the Max Planck Institute Earth System Model Mixed Resolution (MPI-ESM-MR) run with an ocean resolution of 0.4°. In comparison to the present-day oceanic conditions, sea surface salinity (SSS) increases towards the end of the 21st century in the tropical and the subtropical Atlantic. In contrast, a basin-wide surface freshening can be observed in the Pacific and Indian Oceans. The RCP8.5 scenario of the MPI-ESM-MR with a global surface warming of ~2.3°C marks a water cycle amplification of 19 %, which is equivalent to ~8%°C−1 and thus close to the water cycle amplification predicted according to the Clausius–Clapeyron (CC) relationship (~7%°C−1). Large scale global SSS changes are driven by adjustments of surface freshwater fluxes. On smaller spatial scales, it is predominantly advection related to circulation changes that affects near-surface SSS. With respect to subsurface salinity, it is changes in surface freshwater flux that drive their changes over the upper 500 m of the subtropical Pacific and Indian oceans by forcing changes in water mass formation (spice signal). In the subtropical Atlantic Ocean, in contrast, the dynamical response associated with wind stress, circulation changes and associated heaving of isopycnals is equally important in driving subsurface salinity changes over the upper 1000 m.

scholarly journals Asian water tower evinced in total column water vapor: a comparison among multiple satellite and reanalysis data sets

2019 ◽  
Vol 54 (1-2) ◽  
pp. 231-245 ◽  
Author(s):  
Yin Zhao ◽  
Tianjun Zhou
Keyword(s):  
Water Vapor ◽  
Satellite Data ◽  
Annual Cycle ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Data Sets ◽  
Important Indicator ◽  
Ensemble Mean ◽  
Asian Water ◽  
Total Column

Abstract The total column water vapor (TCWV) over the Tibetan Plateau (TP) is one important indicator of the Asian water tower, and the changes in the TCWV are vital to the climate and ecosystem in downstream regions. However, the observational data is insufficient to understand the changes in the TCWV due to the high elevation of the TP. Satellite and reanalysis data can be used as substitutes, but their quality needs to be evaluated. In this study, based on a homogenized radiosonde data set, a comprehensive evaluation of the TCWV over the TP derived from two satellite data sets (AIRS-only and AIRS/AMSU) and seven existing reanalysis data sets (MERRA, MERRA2, NCEP1, NCEP2, CFSR, ERA-I, JRA55) is performed in the context of the climatology, annual cycle and interannual variability. Both satellite data sets reasonably reproduce the characteristics of the TCWV over the TP. All reanalysis data sets perform well in reproducing the annual mean climatology of the TCWV over the TP (R = 0.99), except for NCEP1 (R = 0.96) and NCEP2 (R = 0.92). ERA-I is more reliable in capturing the spatial pattern of the annual cycle (R = 0.94), while NCEP1 shows the lowest skill (R = 0.72). JRA55 performs best in capturing the features of the interannual coherent variation (EOF1, R = 0.97). The skill-weighted ensemble mean of the reanalysis data performs better than the unweighted ensemble mean and most of the single reanalysis data sets. The evaluation provides essential information on both the strengths and weaknesses of the major satellite and reanalysis data sets in measuring the total column water vapor over the TP.

scholarly journals A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

2018 ◽  
Vol 22 (1) ◽  
pp. 241-263 ◽  
Author(s):  
Yu Zhang ◽  
Ming Pan ◽  
Justin Sheffield ◽  
Amanda L. Siemann ◽  
Colby K. Fisher ◽  
...  
Keyword(s):  
Water Budget ◽  
Water Cycle ◽  
Data Sources ◽  
Climate Data ◽  
Data Set ◽  
Data Record ◽  
Terrestrial Water ◽  
In Situ Observations ◽  
Climate Data Record

Abstract. Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R), and the total water storage change (TWSC) at 0.5∘ spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET-R-TWSC= 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5∘ resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

scholarly journals Water availability limits tree productivity, carbon stocks, and carbon residence time in mature forests across the western United States

2016 ◽  
Author(s):  
Logan T. Berner ◽  
Beverly E. Law ◽  
Tara W. Hudiburg
Keyword(s):  
Residence Time ◽  
Water Availability ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystems ◽  
Data Sets ◽  
Climate Data ◽  
Moisture Index ◽  
Western Us ◽  
The Difference ◽  
And Function

Abstract. Much of the western US is projected to become warmer and drier over the coming century, underscoring the need to understand how climate influences terrestrial ecosystems in this region. We quantified the response of tree net primary productivity (NPP), live biomass (BIO), and mean carbon residence time (CRT = BIO/NPP) to spatial variation in climatic water availability in the western US. We used forest inventory measurements from 1,953 mature stands (≥ 100 years) in Washington, Oregon, and California (WAORCA) along with satellite and climate data sets covering the western US. We summarized forest structure and function in both domains along a 400 cm yr−1 hydrologic gradient, quantified with a climate moisture index based on the difference between precipitation and reference evapotranspiration summed from October-September (i.e., water-year) and then averaged annually from 1985–2014 (CMIwy). Median NPP, BIO, and CRT computed at 10 cm yr−1 intervals along the CMIwy gradient increased monotonically with increasing CMIwy across both WAORCA (rs = 0.93–0.96, p 

scholarly journals Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

2011 ◽  
Vol 28 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Ian J. Barton
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Clear Correlation ◽  
Transfer Model ◽  
The Difference

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

scholarly journals Evaluation of HOAPS-3 Ocean Surface Freshwater Flux Components

2011 ◽  
Vol 50 (2) ◽  
pp. 379-398 ◽  
Author(s):  
Axel Andersson ◽  
Christian Klepp ◽  
Karsten Fennig ◽  
Stephan Bakan ◽  
Hartmut Grassl ◽  
...  
Keyword(s):  
Satellite Data ◽  
Storm Track ◽  
Ocean Surface ◽  
Satellite Observation ◽  
Reanalysis Data ◽  
Global Ocean ◽  
Freshwater Flux ◽  
Near Surface ◽  
Sampling Statistics

Abstract Today, latent heat flux and precipitation over the global ocean surface can be determined from microwave satellite data as a basis for estimating the related fields of the ocean surface freshwater flux. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) is the only generally available satellite-based dataset with consistently derived global fields of both evaporation and precipitation and hence of freshwater flux for the period 1987–2005. This paper presents a comparison of the evaporation E, precipitation P, and the resulting freshwater flux E − P in HOAPS with recently available reference datasets from reanalysis and other satellite observation projects as well as in situ ship measurements. In addition, the humidity and wind speed input parameters for the evaporation are examined to identify sources for differences between the datasets. Results show that the general climatological patterns are reproduced by all datasets. Global mean time series often agree within about 10% of the individual products, while locally larger deviations may be found for all parameters. HOAPS often agrees better with the other satellite-derived datasets than with the in situ or the reanalysis data. The agreement usually improves in regions of good in situ sampling statistics. The biggest deviations of the evaporation parameter result from differences in the near-surface humidity estimates. The precipitation datasets exhibit large differences in highly variable regimes with the largest absolute differences in the ITCZ and the largest relative biases in the extratropical storm-track regions. The resulting freshwater flux estimates exhibit distinct differences in terms of global averages as well as regional biases. In comparison with long-term mean global river runoff data, the ocean surface freshwater balance is not closed by any of the compared fields. The datasets exhibit a positive bias in E − P of 0.2–0.5 mm day−1, which is on the order of 10% of the evaporation and precipitation estimates.

Overview of the CCI+SSS project

2020 ◽  
Author(s):  
Jacqueline Boutin ◽  
Nicolas Reul ◽  
Julia Koehler ◽  
Adrien Martin ◽  
Rafael Catany ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Climate Variability ◽  
Satellite Data ◽  
Water Cycle ◽  
Global Ocean ◽  
Variable Regions ◽  
New Findings ◽  
Band Radiometer

<p>Sea Surface Salinity (SSS) is an Essential Climate Variable (ECV) that plays a fundamental role in the density-driven global ocean circulation, the water cycle, and climate. The satellite SSS observation from the Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) missions have provided an unprecedented opportunity to map SSS over the global ocean since 2010 at 40-150km scale with a revisit every 2 to 3 days. This observation capability has no historic precedent and has brought new findings concerning the monitoring of SSS variations related with climate variability such as El Niño-Southern Oscillation, Indian Ocean Dipole, and Madden-Julian Oscillation, and the linkages of the ocean with different elements of the water cycle such as evaporation and precipitation and continental runoff. It has enhanced the understanding of various ocean processes such as tropical instability waves, Rossby waves, mesoscale eddies and related salt transport, salinity fronts, hurricane haline wake, river plume variability, cross-shelf exchanges. There are also emerging use of satellite SSS to study ocean biogeochemistry, e.g. linked to air-sea CO<sub>2</sub> fluxes.</p><p>Following the success of the initial oceanographic studies implementing this new variable, the European Space Agency (ESA) Climate Change Initiative CCI+SSS project (2018-2020) aims at generating improved calibrated global SSS fields over 10 years period (2010-2019) from all available satellite L-band radiometer measurements, extended at regional scale to 2002-2019 from C-band radiometer measurements. It fully exploits the ESA/Earth explorer SMOS mission complemented with SMAP and AQUARIUS satellite missions. The project gathers teams involved in earth observation remote sensing, in the validation of satellite data and in climate variability study. In this presentation, we will present the first CCI+SSS product released to the scientific community (https://catalogue.ceda.ac.uk/uuid/9ef0ebf847564c2eabe62cac4899ec41). The comparisons with in situ ground truth indicate much better performances than the ones obtained with a single satellite data product, with global rmsd against in situ references of 0.16 pss. Large scale interannual variability is successfully reproduced and SSS variability in very variable regions like the Bay of Bengale and in river plumes in the Atlantic Ocean is very satisfactory, confirming the usefulness of these products for scientific studies. Nevertheless we also identify some caveats that will be discussed as well as the ways envisaged to resolve part of them in the next version of the product to be delivered publicly in Summer 2020.</p><p>The ESA CCI+SSS consortium gathers scientists and engineers from various European research institutes and companies (LOCEAN/IPSL, LOPS, University of Hamburg, NOC, ICM, ARGANS, ACRI-st, ODL) and is conducted in collaboration with US colleagues from NASA and Remote Sensing System.</p>

scholarly journals A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

2017 ◽  
Author(s):  
Yu Zhang ◽  
Ming Pan ◽  
Justin Sheffield ◽  
Amanda Siemann ◽  
Colby Fisher ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Water Budget ◽  
Water Cycle ◽  
Data Sources ◽  
Climate Data ◽  
Data Record ◽  
Terrestrial Water ◽  
In Situ Observations ◽  
Climate Data Record

Abstract. Closing the terrestrial water budget is necessary to providing consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in-situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g. in-situ observation, satellite remote sensing, land surface model and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. In this study, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R) and the total water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e. to enforce P − ET − R − TWSC = 0) through a Constrained Kalman Filter (CKF) data assimilation technique. The resulting long-term (1984–2010), monthly, 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) dataset is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This dataset serves to bridge the gap between sparsely gauged regions and the regions with sufficient in-situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in-situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS) and ET from FLUXNET. The dataset is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

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