scholarly journals Conserving Land–Atmosphere Synthesis Suite (CLASS)

2020 ◽  
Vol 33 (5) ◽  
pp. 1821-1844 ◽  
Author(s):  
Sanaa Hobeichi ◽  
Gab Abramowitz ◽  
Jason Evans
Keyword(s):  
Surface Water ◽  
In Situ Measurements ◽  
Energy Budgets ◽  
Weighting Method ◽  
Uncertainty Estimates ◽  
Terrestrial Water ◽  
In Situ Observations ◽  
The Individual ◽  
Class Variable

AbstractAccurate estimates of terrestrial water and energy cycle components are needed to better understand climate processes and improve models’ ability to simulate future change. Various observational estimates are available for the individual budget terms; however, these typically show inconsistencies when combined in a budget. In this work, a Conserving Land–Atmosphere Synthesis Suite (CLASS) of estimates of simultaneously balanced surface water and energy budget components is developed. Individual CLASS variable datasets, where possible, 1) combine a range of existing variable product estimates, and hence overcome the limitations of estimates from a single source; 2) are observationally constrained with in situ measurements; 3) have uncertainty estimates that are consistent with their agreement with in situ observations; and 4) are consistent with each other by being able to solve the water and energy budgets simultaneously. First, available datasets of a budget variable are merged by implementing a weighting method that accounts both for the ability of datasets to match in situ measurements and the error covariance between datasets. Then, the budget terms are adjusted by applying an objective variational data assimilation technique (DAT) that enforces the simultaneous closure of the surface water and energy budgets linked through the equivalence of evapotranspiration and latent heat. Comparing component estimates before and after applying the DAT against in situ measurements of energy fluxes and streamflow showed that modified estimates agree better with in situ observations across various metrics, but also revealed some inconsistencies between water budget terms in June over the higher latitudes. CLASS variable estimates are freely available via https://doi.org/10.25914/5c872258dc183.

Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure

2020 ◽  
Vol 21 (5) ◽  
pp. 989-1009 ◽  
Author(s):  
Sanaa Hobeichi ◽  
Gab Abramowitz ◽  
Steefan Contractor ◽  
Jason Evans
Keyword(s):  
Surface Water ◽  
Energy Budgets ◽  
Testing Performance ◽  
Out Of Sample ◽  
Precipitation Estimates ◽  
Spatial Level ◽  
Sample Testing ◽  
In Situ Observations ◽  
The Tropics

AbstractEvaluation of global gridded precipitation datasets typically entails using the in situ or satellite-based data used to derive them, so that out-of-sample testing is usually not possible. Here we detail a methodology that incorporates the physical balance constraints of the surface water and energy budgets to evaluate gridded precipitation estimates, providing the capacity for out-of-sample testing. Performance conclusions are determined by the ability of precipitation products to achieve closure of the linked budgets using adjustments that are within their prescribed uncertainty bounds. We evaluate and compare five global gridded precipitation datasets: IMERG, GPCP, GPCC, REGEN, and MERRA-2. At the spatial level, we show that precipitation is best estimated by GPCC over the high latitudes, by GPCP over the tropics, and by REGEN over North Africa and the Middle East. IMERG and REGEN appear best over Australia and South Asia. Furthermore, our results give insight into the adequacy of prescribed uncertainties of these products and shows that MERRA-2, while being less competent than the other four products in estimating precipitation, has the best representation of uncertainties in its precipitation estimates. The spatial extent of our results is not only limited to grid cells with in situ observations. Therefore, the approach enables a robust evaluation of precipitation estimates and goes some way to addressing the challenge of validation over observation scarce regions.

scholarly journals Estimating long-term groundwater storage and its controlling factors in Alberta, Canada

2018 ◽  
Vol 22 (12) ◽  
pp. 6241-6255 ◽  
Author(s):  
Soumendra N. Bhanja ◽  
Xiaokun Zhang ◽  
Junye Wang
Keyword(s):  
Groundwater Recharge ◽  
Environmental Sustainability ◽  
Land Surface ◽  
Water Withdrawal ◽  
Groundwater Storage ◽  
Budget Analysis ◽  
Terrestrial Water ◽  
The Individual ◽  
Gravity Recovery

Abstract. Groundwater is one of the most important natural resources for economic development and environmental sustainability. In this study, we estimated groundwater storage in 11 major river basins across Alberta, Canada, using a combination of remote sensing (Gravity Recovery and Climate Experiment, GRACE), in situ surface water data, and land surface modeling estimates (GWSAsat). We applied separate calculations for unconfined and confined aquifers, for the first time, to represent their hydrogeological differences. Storage coefficients for the individual wells were incorporated to compute the monthly in situ groundwater storage (GWSAobs). The GWSAsat values from the two satellite-based products were compared with GWSAobs estimates. The estimates of GWSAsat were in good agreement with the GWSAobs in terms of pattern and magnitude (e.g., RMSE ranged from 2 to 14 cm). While comparing GWSAsat with GWSAobs, most of the statistical analyses provide mixed responses; however the Hodrick–Prescott trend analysis clearly showed a better performance of the GRACE-mascon estimate. The results showed trends of GWSAobs depletion in 5 of the 11 basins. Our results indicate that precipitation played an important role in influencing the GWSAobs variation in 4 of the 11 basins studied. A combination of rainfall and snowmelt positively influences the GWSAobs in six basins. Water budget analysis showed an availability of comparatively lower terrestrial water in 9 of the 11 basins in the study period. Historical groundwater recharge estimates indicate a reduction of groundwater recharge in eight basins during 1960–2009. The output of this study could be used to develop sustainable water withdrawal strategies in Alberta, Canada.

Comparison of GRACE Level-3 Data with Super Conducting Gravimeters in Europe By Means of Signal Decomposition Analysis

2020 ◽  
Author(s):  
Miguel Angel Izquierdo Perez ◽  
Christian Voigt ◽  
Elmas Sinem Ince ◽  
Frank Flechtner
Keyword(s):  
Decomposition Analysis ◽  
Decomposition Methods ◽  
Component Analysis ◽  
In Situ Measurements ◽  
Alternative Methods ◽  
Earth Tides ◽  
Grace Data ◽  
The Individual ◽  
The Impact

<p>With the launch of the Gravity Recovery and Climate Experiment (GRACE) mission in 2002 and continued with GRACE Follow-on (GRACE-FO) since 2018, it is nowadays possible to monitor important mass variations in the Earth system. Nevertheless, validating these observations is a challenging task due to the lack of alternative methods to obtain directly comparable in-situ measurements. The most appropriate approach for this endeavor consists of comparing the GRACE derived Total Water Storage (TWS) residuals against Superconducting Gravimeter (SG) residuals, which provide long term stability.</p> <p>The in-situ data used for this project are the gravity residuals obtained after removing the effects of solid Earth tides and ocean tidal loading, atmospheric loading, instrumental drift, polar motion and length‐of‐day induced gravity changes, from nine SG stations between January 2010 and March 2017. Such residuals were then compared with GRACE retrieved TWS residuals obtained from the Gravity Information System (GravIS) portal (gravis.gfz-potsdam.de).</p> <p>In this project, three decomposition methods were used for the comparisons: Principal Component Analysis (PCA), Spatiotemporal Independent Component Analysis (stICA) and Multivariate Singular Spectral Analysis (MSSA). The main aim was to assess the impact of the GRACE data corrections applied by GravIS to the coefficient C20, the coefficients of degree/order one, and the Glacial Isostatic Adjustment (GIA) effect. Moreover, the Gaussian, DDK and VDK filtering techniques were evaluated as well.</p> <p>The tested methods proved to cope with the residual hydrological effects on SG measurements up to an extend that allows an objective evaluation of the data. The results obtained from this analysis indicate that the most optimal solution is achieved by correcting the C20 and degree/order 1 coefficients. The most effective filters are DDK1, VDK2 and Gaussian with a 500 km bandwidth, in that order. Furthermore, the GIA correction demonstrates to be relevant for northern locations like Onsala.</p> <p>Concerning the decomposition methods, MSSA demonstrates to be a powerful tool, synthesizing the most important common trends among the in-situ measurements of different stations, and displaying the local differences of the signals. The common signals extracted from PCA represent a good overview of the trends from the data but is not detailed at the individual locations. Finally, the stICA decomposition is not able to extract these common signals when the input data is significantly different across the individual variables for SG data. This is explained by the Blind Source Separation (BSS) nature of the methodology, which intends to identify differences among the signals, and is not useful in this case where the signals are affected by the local hydrology.</p> <p>The importance of this study lies in the versatility that the successfully tested methods show for the purpose of GRACE data comparison. Furthermore, the methodology applied in this project can be extended to analyze the current GRACE-FO mission as well other gravimetric satellite missions in the future.</p>

scholarly journals Remote sensed and in situ constraints on processes affecting tropical tropospheric ozone

2007 ◽  
Vol 7 (3) ◽  
pp. 815-838 ◽  
Author(s):  
B. Sauvage ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
X. Liu ◽  
K. Chance ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Tropospheric Ozone ◽  
In Situ Measurements ◽  
Model Bias ◽  
Top Down ◽  
Upper Troposphere ◽  
In Situ Observations ◽  
Tropospheric O3 ◽  
Bias Versus

Abstract. We use a global chemical transport model (GEOS-Chem) to evaluate the consistency of satellite measurements of lightning flashes and ozone precursors with in situ measurements of tropical tropospheric ozone. The measurements are tropospheric O3, NO2, and HCHO columns from the GOME satellite instrument, lightning flashes from the OTD and LIS satellite instruments, profiles of O3, CO, and relative humidity from the MOZAIC aircraft program, and profiles of O3 from the SHADOZ ozonesonde network. We interpret these multiple data sources with our model to better understand what controls tropical tropospheric ozone. Tropical tropospheric ozone is mainly affected by lightning NOx and convection in the upper troposphere and by surface emissions in the lower troposphere. Scaling the spatial distribution of lightning in the model to the observed flashes improves the simulation of O3 in the upper troposphere by 5–20 ppbv versus in situ observations and by 1–4 Dobson Units versus GOME retrievals of tropospheric O3 columns. A lightning source strength of 6±2 Tg N/yr best represents in situ observations from aircraft and ozonesonde. Tropospheric NO2 and HCHO columns from GOME are applied to provide top-down constraints on emission inventories of NOx (biomass burning and soils) and VOCs (biomass burning). The top-down biomass burning inventory is larger than the bottom-up inventory by a factor of 2 for HCHO and alkenes, and by a factor of 2.6 for NOx over northern equatorial Africa. These emissions increase lower tropospheric O3 by 5–20 ppbv, improving the simulation versus aircraft observations, and by 4 Dobson Units versus GOME observations of tropospheric O3 columns. Emission factors in the a posteriori inventory are more consistent with a recent compilation from in situ measurements. The ozone simulation using two different dynamical schemes (GEOS-3 and GEOS-4) is evaluated versus observations; GEOS-4 better represents O3 observations by 5–15 ppbv, reflecting enhanced convective detrainment in the upper troposphere. Heterogeneous uptake of HNO3 on aerosols reduces simulated O3 by 5–7 ppbv, reducing a model bias versus in situ observations over and downwind of deserts. Exclusion of HO2 uptake on aerosols increases O3 by 5 ppbv in biomass burning regions, reducing a model bias versus MOZAIC aircraft measurements.

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 Comparison of Snow Cover from Satellite and Numerical Weather Prediction Models in the Northern Hemisphere and Northern Europe

2009 ◽  
Vol 48 (6) ◽  
pp. 1199-1216 ◽  
Author(s):  
Otto Hyvärinen ◽  
Kalle Eerola ◽  
Niilo Siljamo ◽  
Jarkko Koskinen
Keyword(s):  
Snow Cover ◽  
Prediction Models ◽  
Weather Prediction ◽  
Ground Truth ◽  
In Situ Measurements ◽  
Lower Atmosphere ◽  
Limited Area ◽  
In Situ Observations ◽  
Using Data

Abstract Snow cover has a strong effect on the surface and lower atmosphere in NWP models. Because the progress of in situ observations has stalled, satellite-based snow analyses are becoming increasingly important. Currently, there exist several products that operationally map global or continental snow cover. In this study, satellite-based snow cover analyses from NOAA, NASA, and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and NWP snow analyses from the High-Resolution Limited-Area Model (HIRLAM) and ECMWF, were compared using data from January to June 2006. Because no analyses were independent and since available in situ measurements were already used in the NWP analyses, no independent ground truth was available and only the consistency between analyses could be compared. Snow analyses from NOAA, NASA, and ECMWF were similar, but the analysis from NASA was greatly hampered by clouds. HIRLAM and EUMETSAT deviated most from other analyses. Even though the analysis schemes of HIRLAM and ECMWF were quite similar, the resulting snow analyses were quite dissimilar, because ECMWF used the satellite information of snow cover in the form of NOAA analyses, while HIRLAM used none. The differences are especially prominent in areas around the snow edge where few in situ observations are available. This suggests that NWP snow analyses based only on in situ measurements would greatly benefit from inclusion of satellite-based snow cover information.

In situ observations of predatory feeding behaviour of the galatheid squat lobster Munida sarsi using a remotely operated vehicle

2003 ◽  
Vol 83 (3) ◽  
pp. 463-464 ◽  
Author(s):  
Ian R. Hudson ◽  
Benjamin D. Wigham
Keyword(s):  
Feeding Strategy ◽  
Remotely Operated Vehicle ◽  
The West ◽  
Squat Lobster ◽  
Video Footage ◽  
Benthic Crustacean ◽  
In Situ Observations ◽  
The Individual ◽  
The Uk

During remotely operated vehicle operations on the UK continental shelf to the west of Shetland (60°6′N 4°4′W) at a depth of 400 m, Munida sarsi, a common benthic crustacean was observed actively preying on the northern krill Meganyctiphanes norvegica. Video footage shows the individual using its chelipeds to catch prey items as they swarm around its burrow. These initial observations indicate that predation forms a new feeding strategy for a species previously believed to be an active scavenger.

Comparison of MTI satellite-derived surface water temperatures and in-situ measurements

2002 ◽  
Author(s):  
Robert J. Kurzeja ◽  
Malcolm M. Pendergast ◽  
Eliel Villa-Aleman ◽  
Alfred J. Garrett
Keyword(s):  
Surface Water ◽  
In Situ Measurements

scholarly journals Modelling the water balance of Lake Victoria (East Africa) – Part 1: Observational analysis

2018 ◽  
Vol 22 (10) ◽  
pp. 5509-5525 ◽  
Author(s):  
Inne Vanderkelen ◽  
Nicole P. M. van Lipzig ◽  
Wim Thiery
Keyword(s):  
Water Balance ◽  
Lake Level ◽  
Lake Victoria ◽  
Balance Model ◽  
Lake Victoria Basin ◽  
Lake Level Fluctuations ◽  
Lake Evaporation ◽  
In Situ Observations ◽  
The Individual

Abstract. Lake Victoria is the largest lake in Africa and one of the two major sources of the Nile river. The water level of Lake Victoria is determined by its water balance, consisting of precipitation on the lake, evaporation from the lake, inflow from tributary rivers and lake outflow, controlled by two hydropower dams. Due to a scarcity of in situ observations, previous estimates of individual water balance terms are characterized by substantial uncertainties, which means that the water balance is often not closed independently. In this first part of a two-paper series, we present a water balance model for Lake Victoria, using state-of-the-art remote sensing observations, high-resolution reanalysis downscaling and outflow values recorded at the dam. The uncalibrated computation of the individual water balance terms yields lake level fluctuations that closely match the levels retrieved from satellite altimetry. Precipitation is the main cause of seasonal and interannual lake level fluctuations, and on average causes the lake level to rise from May to July and to fall from August to December. Finally, our results indicate that the 2004–2005 drop in lake level can be about half attributed to a drought in the Lake Victoria Basin and about half to an enhanced outflow, highlighting the sensitivity of the lake level to human operations at the outflow dam.

Sign in / Sign up

Export Citation Format

Share Document