Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to estimate monthly changes in total water storage across the Middle East during February 2003 to December ...2012. The results show a large negative trend in total water storage centered over western Iran and eastern Iraq. Subtracting contributions from the Caspian Sea and two large lakes, Tharthar and Urmiah, and using output from a version of the CLM4.5 land surface model to remove contributions from soil moisture, snow, canopy storage, and river storage, we conclude that most of the long‐term water loss is due to a decline in groundwater storage. By dividing the region into seven mascons outlined along national boundaries and fitting them to the data, we find that the largest groundwater depletion is occurring in Iran, with a mass loss rate of 25 ± 3 Gt/yr during the study period. The conclusion of significant Iranian groundwater loss is further supported by in situ well data from across the country. Anthropogenic contributions to the groundwater loss are estimated by removing the natural variations in groundwater predicted by CLM4.5. These results indicate that over half of the groundwater loss in Iran (14 ± 3 Gt/yr) may be attributed to human withdrawals.
Key Point
Using satellite gravity data for groundwater monitoring across the Middle East
In this study, we estimate a time series of geocenter anomalies from a combination of data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission and the output from ocean models. ...A matrix equation is derived relating total geocenter variations to the GRACE coefficients of degrees two and higher and to the oceanic component of the degree one coefficients. We estimate the oceanic component from two state‐of‐the‐art ocean models. Results are compared to independent estimates of geocenter derived from other satellite data, such as satellite laser ranging and GPS. Finally, we compute degree one coefficients that are consistent with the processing applied to the GRACE Level‐2 gravity field coefficients. The estimated degree one coefficients can be used to improve estimates of mass variability from GRACE, which alone cannot provide them directly.
Gravity fields produced by the Gravity Recovery and Climate Experiment (GRACE) satellite mission require smoothing to reduce the effects of errors present in short wavelength components. As the ...smoothing radius decreases, these errors manifest themselves in maps of surface mass variability as long, linear features generally oriented north to south (i.e., stripes). The presence of stripes implies correlations in the gravity field coefficients. Here we examine the spectral signature of these correlated errors, and present a method to remove them. Finally, we apply the filter to a model of surface‐mass variability to show that the filter has relatively little degradation of the underlying geophysical signals we seek to recover.
Using satellite gravimetric and altimetric data, we examine trends in water storage and lake levels of multiple lakes in the Great Rift Valley region of East Africa for the years 2003–2008. GRACE ...total water storage estimates reveal that water storage declined in much of East Africa, by as much as
60
mm
year
, while altimetric data show that lake levels in some large lakes dropped by as much as 1–2
m. The largest declines occurred in Lake Victoria, the Earth’s second largest freshwater body. Because the discharge from the outlet of Lake Victoria is used to generate hydroelectric power, the role of human management in the lake’s decline has been questioned. By comparing catchment water storage trends to lake level trends, we confirm that climatic forcing explains only about 50decline. This analysis provides an independent means of assessing the relative impacts of climate and human management on the water balance of Lake Victoria that does not depend on observations of dam discharge, which may not be publically available. In the second part of the study, the individual components of the lake water balance are estimated. Satellite estimates of changes in lake level, precipitation, and evaporation are used with observed lake discharge to develop a parameterization for estimating subsurface inflows due to changes in groundwater storage estimated from satellite gravimetry. At seasonal timescales, this approach provides closure to Lake Victoria’s water balance to within
17
mm
month
. The third part of this study uses the water balance of a downstream water body, Lake Kyoga, to estimate the outflow from Lake Victoria remotely. Because Lake Kyoga is roughly 20 times smaller in area than Lake Victoria, its water balance is strongly influenced by inflow from Lake Victoria. Lake Kyoga has been shown to act as a linear reservoir, where its outflow is proportional to the height of the lake. This model can be used with satellite altimetric lake levels to estimate a time series of Lake Victoria discharge with an rms error of about
134
m
3
s
.
The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model ...developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.
Plain Language Summary
The Community Land Model (CLM) is the land component of the widely used Community Earth System Model (CESM). Here, we introduce model developments included in CLM version 5 (CLM5), the default land component for CESM2 which will be used for the Coupled Model Intercomparison Project (CMIP6). CLM5 includes many new and updated processes including (1) hydrology and snow features such as spatially explicit soil depth, canopy snow processes, a simple firn model, and a more mechanistic river model, (2) plant hydraulics and hydraulic redistribution, (3) revised nitrogen cycling with flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake, (4) expansion to six crop types (global) and time‐evolving irrigated areas and fertilization rates, (5) improved urban building energy model, and (6) carbon isotopes. New optional features include a demographically structured dynamic vegetation model, ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Model performance is generally improved for most assessed variables and metrics, though clear establishment of improvement or degradation is challenging due to model complexity as well as observational data limitations. Nonetheless, CLM5 is increasingly suited for research into a broad range of societally relevant scientific questions related to the terrestrial system.
Key Points
Updated Community Land Model has more hydrological and ecological process fidelity and more comprehensive representation of land management.
The model is systematically evaluated using International Land Model Benchmarking system and shows marked improvement over prior versions.
Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river ...basin, continent, and global scales. However, current large‐scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater‐surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.
Key Points:
Land model development can benefit from recent advances in hydrology
Accelerating modeling advances requires comprehensive benchmarking activities
Stronger collaboration is needed between the hydrology and ESM modeling communities
The Community Land Model version 4 (CLM4) overestimates gross primary production (GPP) compared with data‐driven estimates and other process models. We use global, spatially gridded GPP and latent ...heat flux upscaled from the FLUXNET network of eddy covariance towers to evaluate and improve canopy processes in CLM4. We investigate differences in GPP and latent heat flux arising from model parameterizations (termed model structural error) and from uncertainty in the photosynthetic parameter Vcmax (termed model parameter uncertainty). Model structural errors entail radiative transfer, leaf photosynthesis and stomatal conductance, and canopy scaling of leaf processes. Model structural revisions reduce global GPP over the period 1982–2004 from 165 Pg C yr−1 to 130 Pg C yr−1, and global evapotranspiration decreases from 68,000 km3 yr−1 to 65,000 km3 yr−1, within the uncertainty of FLUXNET‐based estimates. Colimitation of photosynthesis is a cause of the improvements, as are revisions to photosynthetic parameters and their temperature dependency. Improvements are seen in all regions and seasonally over the course of the year. Similar improvements occur in latent heat flux. Uncertainty in Vcmax produces effects of comparable magnitude as model structural errors, but of offsetting sign. This suggests that model structural errors can be compensated by parameter adjustment, and this may explain the lack of consensus in values for Vcmax used in terrestrial biosphere models. Our analyses show that despite inherent uncertainties global flux fields empirically inferred from FLUXNET data are a valuable tool to guide terrestrial biosphere model development and evaluation.
Key Points
FLUXNET diagnostic models guide terrestrial biosphere model development
Revisions to the Community Land Model (CLM4) improve gross primary production
Model structural errors can be compensated by parameter adjustment
The representation of permafrost and seasonally frozen ground and their projected twenty-first century trends is assessed in the Community Climate System Model, version 4 (CCSM4) and the Community ...Land Model version 4 (CLM4). The combined impact of advances in CLM and a better Arctic climate simulation, especially for air temperature, improve the permafrost simulation in CCSM4 compared to CCSM3. Present-day continuous plus discontinuous permafrost extent is comparable to that observed 12.5 × 10⁶ versus (11.8–14.6) × 10⁶ km², but active-layer thickness (ALT) is generally too thick and deep ground (>15 m) temperatures are too warm in CCSM4. Present-day seasonally frozen ground area is well simulated (47.5 × 10⁶ versus 48.1 × 10⁶ km²). ALT and deep ground temperatures are much better simulated in offline CLM4 (i.e., forced with observed climate), which indicates that the remaining climate biases, particularly excessive high-latitude snowfall biases, degrade the CCSM4 permafrost simulation.
Near-surface permafrost (NSP) and seasonally frozen ground (SFG) area are projected to decline substantially during the twenty-first century representative concentration projections (RCPs); RCP8.5: NSP by 9.0 × 10⁶ km², 72%, SFG by 7.1 × 10⁶, 15%; RCP2.6: NSP by 4.1 × 10⁶, 33%, SFG by 2.1 × 10⁶, 4%. The permafrost degradation rate is slower (2000–50) than in CCSM3 by ∼35% because of the improved soil physics. Under the low RCP2.6 emissions pathway, permafrost state stabilizes by 2100, suggesting that permafrost related feedbacks could be minimized if greenhouse emissions could be reduced. The trajectory of permafrost degradation is affected by CCSM4 climate biases. In simulations with this climate bias ameliorated, permafrost degradation in RCP8.5 is lower by ∼29%. Further reductions of Arctic climate biases will increase the reliability of permafrost projections and feedback studies in earth system models.
Key Points
Massive rate of groundwater depletion in the Middle East
Would not have been observable if not for space‐based methods.
New policies are required for peaceable, sustainable water ...management
In this study, we use observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to evaluate freshwater storage trends in the north‐central Middle East, including portions of the Tigris and Euphrates River Basins and western Iran, from January 2003 to December 2009. GRACE data show an alarming rate of decrease in total water storage of approximately −27.2±0.6 mm yr−1 equivalent water height, equal to a volume of 143.6 km3 during the course of the study period. Additional remote‐sensing information and output from land surface models were used to identify that groundwater losses are the major source of this trend. The approach used in this study provides an example of “best current capabilities” in regions like the Middle East, where data access can be severely limited. Results indicate that the region lost 17.3±2.1 mm yr−1 equivalent water height of groundwater during the study period, or 91.3±10.9 km3 in volume. Furthermore, results raise important issues regarding water use in transboundary river basins and aquifers, including the necessity of international water use treaties and resolving discrepancies in international water law, while amplifying the need for increased monitoring for core components of the water budget.
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