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  • 1
    Publication Date: 2020-07-01
    Description: Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning Systems Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multimodel, remote sensing–based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage), and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean–land–atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multimodel ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its 1–5-month hindcasts successfully capture known historic drought events, and it has improved skill over benchmark-type hindcasts. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy, and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
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  • 2
    Publication Date: 2017-01-25
    Description: Closing and balancing Earth’s global water cycle remains a challenge for the climate community. Observations are limited in duration, global coverage, and frequency, and not all water cycle terms are adequately observed. Reanalyses aim to fill the gaps through the assimilation of as many atmospheric water vapor observations as possible. Former generations of reanalyses have demonstrated a number of systematic problems that have limited their use in climate studies, especially regarding low-frequency trends. This study characterizes the NASA Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) water cycle relative to contemporary reanalyses and observations. MERRA-2 includes measures intended to minimize the spurious global variations related to inhomogeneity in the observational record. The global balance and cycling of water from ocean to land is presented, with special attention given to the water vapor analysis increment and the effects of the changing observing system. While some systematic regional biases can be identified, MERRA-2 produces temporally consistent time series of total column water and transport of water from ocean to land. However, the interannual variability of ocean evaporation is affected by the changing surface-wind-observing system, and precipitation variability is closely related to the evaporation. The surface energy budget is also strongly influenced by the interannual variability of the ocean evaporation. Furthermore, evaluating the relationship of temperature and water vapor indicates that the variations of water vapor with temperature are weaker in satellite data reanalyses, not just MERRA-2, than determined by observations, atmospheric models, or reanalyses without water vapor assimilation.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 3
    Publication Date: 2019-07-30
    Description: This article describes one of the first successful examples of multisensor, multivariate land data assimilation, encompassing a large suite of soil moisture, snow depth, snow cover, and irrigation intensity environmental data records (EDRs) from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), Advanced Scatterometer (ASCAT), Moderate-Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Soil Moisture Ocean Salinity (SMOS) mission, and Soil Moisture Active Passive (SMAP) mission. The analysis is performed using the NASA Land Information System (LIS) as an enabling tool for the U.S. National Climate Assessment (NCA). The performance of the NCA Land Data Assimilation System (NCA-LDAS) is evaluated by comparing it to a number of hydrological reference data products. Results indicate that multivariate assimilation provides systematic improvements in simulated soil moisture and snow depth, with marginal effects on the accuracy of simulated streamflow and evapotranspiration. An important conclusion is that across all evaluated variables, assimilation of data from increasingly more modern sensors (e.g., SMOS, SMAP, AMSR2, ASCAT) produces more skillful results than assimilation of data from older sensors (e.g., SMMR, SSM/I, AMSR-E). The evaluation also indicates the high skill of NCA-LDAS when compared with other LSM products. Further, drought indicators based on NCA-LDAS output suggest a trend of longer and more severe droughts over parts of the western United States during 1979–2015, particularly in the southwestern United States, consistent with the trends from the U.S. Drought Monitor, albeit for a shorter 2000–15 time period.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 4
    Publication Date: 2017-02-15
    Description: To prepare for the next-generation North American Land Data Assimilation System (NLDAS), three advanced land surface models [LSMs; i.e., Community Land Model, version 4.0 (CLM4.0); Noah LSM with multiphysics options (Noah-MP); and Catchment LSM-Fortuna 2.5 (CLSM-F2.5)] were run for the 1979–2014 period within the NLDAS-based framework. Unlike the LSMs currently executing in the operational NLDAS, these three advanced LSMs each include a groundwater component. In this study, the model simulations of monthly terrestrial water storage anomaly (TWSA) and its individual water storage components are evaluated against satellite-based and in situ observations, as well as against reference reanalysis products, at basinwide and statewide scales. The quality of these TWSA simulations will contribute to determining the suitability of these models for the next phase of the NLDAS. Overall, it is found that all three models are able to reasonably capture the monthly and interannual variability and magnitudes of TWSA. However, the relative contributions of the individual water storage components to TWSA are very dependent on the model and basin. A major contributor to the TWSA is the anomaly of total column soil moisture content for CLM4.0 and Noah-MP, while the groundwater storage anomaly is the major contributor for CLSM-F2.5. Other water storage components such as the anomaly of snow water equivalent also play a role in all three models. For each individual water storage component, the models are able to capture broad features such as monthly and interannual variability. However, there are large intermodel differences and quantitative uncertainties, which are motivating follow-on investigations in the NLDAS Science Testbed developed by the NASA and NCEP NLDAS teams.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 5
    Publication Date: 2016-02-12
    Description: Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. This method is extended with a “large sample” approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in 1) forcing data, 2) model parameters, and 3) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in phase 2 of the North American Land Data Assimilation System (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of NLDAS-2. In particular, continued work toward refining the parameter maps and lookup tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 6
    Publication Date: 2016-07-01
    Description: The objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin-averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 7
    Publication Date: 2017-03-28
    Description: While investigating linkages between afternoon peak rainfall amount and land–atmosphere coupling strength, a statistically significant trend in phase 2 of the North American Land Data Assimilation System (NLDAS-2) warm season (April–September) afternoon (1700–2259 UTC) precipitation was noted for a large fraction of the conterminous United States, namely, two-thirds of the area east of the Mississippi River, during the period from 1979 to 2015. To verify and better characterize this trend, a thorough statistical analysis is undertaken. The analysis focuses on three aspects of precipitation: amount, frequency, and intensity at 6-hourly time scale and for each calendar month separately. At the NLDAS-2 native resolution of 0.125° × 0.125°, Kendall’s tau and Sen’s slope estimators are used to detect and estimate trends and the Pettitt test is used to detect breakpoints. Parallel analyses are conducted on both NARR and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), subdaily precipitation estimates. Widespread breakpoints of field significance at the α = 0.05 level are detected in the NLDAS-2 frequency and intensity series for all months and 6-h periods that are absent from the analogous NARR and MERRA-2 datasets. These breakpoints are shown to correspond with a July 1996 NLDAS-2 transition away from hourly 2° × 2.5° NOAA/CPC precipitation estimates to hourly 4-km stage II Doppler radar precipitation estimates in the temporal disaggregation of CPC daily gauge analyses. While NLDAS-2 may provide the most realistic diurnal precipitation cycle overall, users should be aware of this discontinuity and its direct effect on long-term trends in subdaily precipitation and indirect effects on trends in modeled soil moisture, surface temperature, surface energy and water fluxes, snow cover, snow water equivalent, and runoff/streamflow.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2018-11-01
    Description: Since the second phase of the North American Land Data Assimilation System (NLDAS-2) was operationally implemented at NOAA/NCEP as part of the production suite in August 2014, developing the next phase of NLDAS has been a key focus of the NCEP and NASA NLDAS teams. The Variable Infiltration Capacity (VIC) model is one of the four land surface models of the NLDAS system. The current operational NLDAS-2 uses version 4.0.3 (VIC403), the research NLDAS-2 used version 4.0.5 (VIC405), and the NASA Land Information System (LIS)-based NLDAS uses version 4.1.2.l (VIC412). The purpose of this study is to evaluate VIC403 and VIC412 and check if the latter version has better performance for the next phase of NLDAS. Toward this, a comprehensive evaluation was conducted, targeting multiple variables and using multiple metrics to assess the performance of different model versions. The evaluation results show large and significant improvements in VIC412 over the southeastern United States when compared with VIC403 and VIC405. In other regions, there are very limited improvements or even deterioration to some degree. This is partially due to 1) the sparseness of USGS streamflow observations for model parameter calibration and 2) a deterioration of VIC model performance in the Great Plains (GP) region after a model upgrade to a newer version. Overall, the model upgrade enhances model performance and skill scores for most parts of the continental United States; exceptions include the GP and western mountainous regions, as well as the daily soil moisture simulation skill, suggesting that VIC model development is on the right path. Further efforts are needed for scientific understanding of land surface physical processes in the GP, and a recalibration of VIC412 using reasonable reference datasets is recommended.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 9
    Publication Date: 2019-07-30
    Description: Terrestrial hydrologic trends over the conterminous United States are estimated for 1980–2015 using the National Climate Assessment Land Data Assimilation System (NCA-LDAS) reanalysis. NCA-LDAS employs the uncoupled Noah version 3.3 land surface model at 0.125° × 0.125° forced with NLDAS-2 meteorology, rescaled Climate Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth, and irrigation products. Mean annual trends are reported using the nonparametric Mann–Kendall test at p 〈 0.1 significance. Results illustrate the interrelationship between regional gradients in forcing trends and trends in other land energy and water stores and fluxes. Mean precipitation trends range from +3 to +9 mm yr−1 in the upper Great Plains and Northeast to −1 to −9 mm yr−1 in the West and South, net radiation flux trends range from +0.05 to +0.20 W m−2 yr−1 in the East to −0.05 to −0.20 W m−2 yr−1 in the West, and U.S.-wide temperature trends average about +0.03 K yr−1. Trends in soil moisture, snow cover, latent and sensible heat fluxes, and runoff are consistent with forcings, contributing to increasing evaporative fraction trends from west to east. Evaluation of NCA-LDAS trends compared to independent data indicates mixed results. The RMSE of U.S.-wide trends in number of snow cover days improved from 3.13 to 2.89 days yr−1 while trend detection increased 11%. Trends in latent heat flux were hardly affected, with RMSE decreasing only from 0.17 to 0.16 W m−2 yr−1, while trend detection increased 2%. NCA-LDAS runoff trends degraded significantly from 2.6 to 16.1 mm yr−1 while trend detection was unaffected. Analysis also indicated that NCA-LDAS exhibits relatively more skill in low precipitation station density areas, suggesting there are limits to the effectiveness of satellite data assimilation in densely gauged regions. Overall, NCA-LDAS demonstrates capability for quantifying physically consistent, U.S. hydrologic climate trends over the satellite era.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 10
    Publication Date: 2015-05-01
    Description: The assimilation of observations in reanalyses incurs the potential for the physical terms of budgets to be balanced by a term relating the fit of the observations relative to a forecast first guess analysis. This may indicate a limitation in the physical processes of the background model or perhaps assimilating data from an inconsistent observing system. In the MERRA reanalysis, an area of long-term moisture flux divergence over land has been identified over the central United States. Here, the water vapor budget is evaluated in this region, taking advantage of two unique features of the MERRA diagnostic output: 1) a closed water budget that includes the analysis increment and 2) a gridded diagnostic output dataset of the assimilated observations and their innovations (e.g., forecast departures). In the central United States, an anomaly occurs where the analysis adds water to the region, while precipitation decreases and moisture flux divergence increases. This is related more to a change in the observing system than to a deficiency in the model physical processes. MERRA’s Gridded Innovations and Observations (GIO) data narrow the observations that influence this feature to the ATOVS and Aqua satellites during the 0600 and 1800 UTC analysis cycles, when radiosonde information is not prevalent. Observing system experiments further narrow the instruments that affect the anomalous feature to AMSU-A (mainly window channels) and Atmospheric Infrared Sounder (AIRS). This effort also shows the complexities of the observing system and the reactions of the regional water budgets in reanalyses to the assimilated observations.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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