scholarly journals SimSphere model sensitivity analysis towards establishing its use for deriving key parameters characterising land surface interactions

2014 ◽  
Vol 7 (5) ◽  
pp. 1873-1887 ◽  
Author(s):  
G. P. Petropoulos ◽  
H. M. Griffiths ◽  
T. N. Carlson ◽  
P. Ioannou-Katidis ◽  
T. Holt
Keyword(s):  
Sensitivity Analysis ◽  
Land Surface ◽  
Water Cycle ◽  
Surface Interactions ◽  
Distribution Functions ◽  
Probability Distribution Functions ◽  
Surface Models ◽  
Significant Step ◽  
Key Variables ◽  
Edge Sensitivity

Abstract. Being able to accurately estimate parameters characterising land surface interactions is currently a key scientific priority due to their central role in the Earth's global energy and water cycle. To this end, some approaches have been based on utilising the synergies between land surface models and Earth observation (EO) data to retrieve relevant parameters. One such model is SimSphere, the use of which is currently expanding, either as a stand-alone application or synergistically with EO data. The present study aimed at exploring the effect of changing the atmospheric sounding profile on the sensitivity of key variables predicted by this model assuming different probability distribution functions (PDFs) for its inputs/outputs. To satisfy this objective and to ensure consistency and comparability to analogous studies conducted previously on the model, a sophisticated, cutting-edge sensitivity analysis (SA) method adopting Bayesian theory was implemented on SimSphere. Our results did not show dramatic changes in the nature or ranking of influential model inputs in comparison to previous studies. Model outputs examined using SA were sensitive to a small number of the inputs; a significant amount of first-order interactions between the inputs was also found, suggesting strong model coherence. Results showed that the assumption of different PDFs for the model inputs/outputs did not have an important bearing on mapping the most responsive model inputs and interactions, but only the absolute SA measures. This study extends our understanding of SimSphere's structure and further establishes its coherence and correspondence to that of a natural system's behaviour. Consequently, the present work represents a significant step forward in the global efforts on SimSphere verification, especially those focusing on the development of global operational products from the model synergy with EO data.

scholarly journals SimSphere model sensitivity analysis towards establishing its use for deriving key parameters characterising land surface interactions

2014 ◽  
Vol 7 (1) ◽  
pp. 1-32 ◽  
Author(s):  
G. P. Petropoulos ◽  
H. M. Griffiths ◽  
T. N. Carlson ◽  
P. Ioannou-Katidis ◽  
T. Holt
Keyword(s):  
Sensitivity Analysis ◽  
Land Surface ◽  
Water Cycle ◽  
Surface Interactions ◽  
Distribution Functions ◽  
Surface Models ◽  
Significant Step ◽  
Key Variables ◽  
Edge Sensitivity ◽  
Significant Bearing

Abstract. Being able to accurately estimate parameters characterising land surface interactions is of key scientific priority today due to their central role in the Earth's global energy and water cycle. To this end, some approaches have been based on utilising the synergies between land surface models and Earth Observation (EO) data to retrieve relevant parameters. One such model is SimSphere, the use of which is currently expanding, either as a stand-alone application or synergistically with EO data. The present study aims at exploring the effect of changing the atmospheric sounding profile to the sensitivity of key variables predicted by this model assuming different probability distribution functions (PDFs) for its inputs/outputs. To satisfy this objective and to ensure consistency and comparability to analogous studies conducted previously on the model, a sophisticated, cutting edge sensitivity analysis (SA) method adopting Bayesian theory is implemented herein on SimSphere. Our results did not show dramatic changes in the nature or ranking of influential model inputs in comparison to previous studies. Model outputs of which the SA was examined were sensitive to a small number of the inputs; a significant amount of first order interactions between the inputs was also found, suggesting strong model coherence. Results obtained suggest that the assumption of different PDFs for the model inputs/outputs did not have significant bearing on mapping the most responsive model inputs and interactions, but only the absolute SA measures. All in all, this study extends our understanding of SimSphere's structure and further establishes its coherence and correspondence to that of a natural system's behaviour. Consequently, the present work represents a significant step forward in the efforts globally on SimSphere verification, especially those focusing towards the development of global operational products from the synergy of SimSphere with EO data.

scholarly journals Discontinuous Daily Temperatures in the WATCH Forcing Datasets

2015 ◽  
Vol 16 (1) ◽  
pp. 465-472 ◽  
Author(s):  
Henning W. Rust ◽  
Tim Kruschke ◽  
Andreas Dobler ◽  
Madlen Fischer ◽  
Uwe Ulbrich
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Monthly Means ◽  
Tropical Africa ◽  
Average Temperature ◽  
Surface Models ◽  
The Tropics

Abstract The Water and Global Change (WATCH) forcing datasets have been created to support the use of hydrological and land surface models for the assessment of the water cycle within climate change studies. They are based on 40-yr ECMWF Re-Analysis (ERA-40) or ECMWF interim reanalysis (ERA-Interim) with temperatures (among other variables) adjusted such that their monthly means match the monthly temperature dataset from the Climatic Research Unit. To this end, daily minimum, maximum, and mean temperatures within one calendar month have been subjected to a correction involving monthly means of the respective month. As these corrections can be largely different for adjacent months, this procedure potentially leads to implausible differences in daily temperatures across the boundaries of calendar months. We analyze day-to-day temperature fluctuations within and across months and find that across-months differences are significantly larger, mostly in the tropics and frigid zones. Average across-months differences in daily mean temperature are typically between 10% and 40% larger than their corresponding within-months average temperature differences. However, regions with differences up to 200% can be found in tropical Africa. Particularly in regions where snowmelt is a relevant player for hydrology, a few degrees Celsius difference can be decisive for triggering this process. Daily maximum and minimum temperatures are affected in the same regions, but in a less severe way.

scholarly journals WATCH: Current Knowledge of the Terrestrial Global Water Cycle

2011 ◽  
Vol 12 (6) ◽  
pp. 1149-1156 ◽  
Author(s):  
Richard Harding ◽  
Martin Best ◽  
Eleanor Blyth ◽  
Stefan Hagemann ◽  
Pavel Kabat ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Current Knowledge ◽  
Water Model ◽  
Grand Challenge ◽  
Global Water Cycle ◽  
Wide Range ◽  
Surface Models ◽  
Intercomparison Project ◽  
Global Water

Abstract Water-related impacts are among the most important consequences of increasing greenhouse gas concentrations. Changes in the global water cycle will also impact the carbon and nutrient cycles and vegetation patterns. There is already some evidence of increasing severity of floods and droughts and increasing water scarcity linked to increasing greenhouse gases. So far, however, the most important impacts on water resources are the direct interventions by humans, such as dams, water extractions, and river channel modifications. The Water and Global Change (WATCH) project is a major international initiative to bring together climate and water scientists to better understand the current and future water cycle. This paper summarizes the underlying motivation for the WATCH project and the major results from a series of papers published or soon to be published in the Journal of Hydrometeorology WATCH special collection. At its core is the Water Model Intercomparison Project (WaterMIP), which brings together a wide range of global hydrological and land surface models run with consistent driving data. It is clear that we still have considerable uncertainties in the future climate drivers and in how the river systems will respond to these changes. There is a grand challenge to the hydrological and climate communities to both reduce these uncertainties and communicate them to a wider society.

scholarly journals The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements

2011 ◽  
Vol 15 (5) ◽  
pp. 1675-1698 ◽  
Author(s):  
W. A. Dorigo ◽  
W. Wagner ◽  
R. Hohensinn ◽  
S. Hahn ◽  
C. Paulik ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Water Cycle ◽  
Soil Moisture Data ◽  
Time Period ◽  
Surface Models ◽  
Different Depths ◽  
Operational Networks

Abstract. In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol. To overcome many of these limitations, the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu) was initiated to serve as a centralized data hosting facility where globally available in situ soil moisture measurements from operational networks and validation campaigns are collected, harmonized, and made available to users. Data collecting networks share their soil moisture datasets with the ISMN on a voluntary and no-cost basis. Incoming soil moisture data are automatically transformed into common volumetric soil moisture units and checked for outliers and implausible values. Apart from soil water measurements from different depths, important metadata and meteorological variables (e.g., precipitation and soil temperature) are stored in the database. These will assist the user in correctly interpreting the soil moisture data. The database is queried through a graphical user interface while output of data selected for download is provided according to common standards for data and metadata. Currently (status May 2011), the ISMN contains data of 19 networks and more than 500 stations located in North America, Europe, Asia, and Australia. The time period spanned by the entire database runs from 1952 until the present, although most datasets have originated during the last decade. The database is rapidly expanding, which means that both the number of stations and the time period covered by the existing stations are still growing. Hence, it will become an increasingly important resource for validating and improving satellite-derived soil moisture products and studying climate related trends. As the ISMN is animated by the scientific community itself, we invite potential networks to enrich the collection by sharing their in situ soil moisture data.

scholarly journals Global-scale analysis of satellite-derived time series of naturally inundated areas as a basis for floodplain modeling

2010 ◽  
Vol 27 ◽  
pp. 45-50 ◽  
Author(s):  
L. Adam ◽  
P. Döll ◽  
C. Prigent ◽  
F. Papa
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Water Cycle ◽  
Open Water ◽  
Global Scale ◽  
Irrigated Rice ◽  
Surface Models ◽  
Terrestrial Water ◽  
Inundation Extent ◽  
And Storage

Abstract. Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993–2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges.

scholarly journals Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities

2019 ◽  
Vol 16 (19) ◽  
pp. 3747-3775 ◽  
Author(s):  
Paul C. Stoy ◽  
Tarek S. El-Madany ◽  
Joshua B. Fisher ◽  
Pierre Gentine ◽  
Tobias Gerken ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Carbonyl Sulfide ◽  
Analytical Techniques ◽  
Atmospheric Composition ◽  
Reasonable Assumption ◽  
Canopy Conductance ◽  
Land Surface Models ◽  
Surface Models ◽  
Ecosystem Water Use Efficiency

Abstract. Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. It is difficult to partition ecosystem-scale evapotranspiration (ET) measurements into E and T, which makes it difficult to validate satellite data and land surface models. Here, we review current progress in partitioning E and T and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques create new opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. For example, many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but more analysis is necessary to determine the conditions for which this assumption holds. Another critical assumption for many partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T can exceed 95 % of ET from certain ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon–water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water fluxes and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

scholarly journals Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities

2019 ◽  
Author(s):  
Paul C. Stoy ◽  
Tarek El-Madany ◽  
Joshua B. Fisher ◽  
Pierre Gentine ◽  
Tobias Gerken ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Water Flux ◽  
Carbonyl Sulfide ◽  
Analytical Techniques ◽  
Atmospheric Composition ◽  
Reasonable Assumption ◽  
Canopy Conductance ◽  
Land Surface Models ◽  
Surface Models

Abstract. Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. Our ability to partition evapotranspiration (ET) into E and T is limited at the ecosystem scale, which renders the validation of satellite data and land surface models incomplete. Here, we review current progress in partitioning E and T, and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques provide additional opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. Many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency (EWUE) exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but the conditions under which this assumption holds require further analysis. Another critical assumption for many ET partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T frequently exceeds 95 % of ET from some ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon-water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water flux and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

Sign in / Sign up

Export Citation Format

Share Document