Eunjin Han

On the Use of a Water Balance to Evaluate Interannual Terrestrial ET Variability

AbstractAccurately measuring interannual variability in terrestrial evapotranspiration ET is a major challenge for efforts to detect trends in the terrestrial hydrologic cycle. Based on comparisons with annual values of terrestrial evapotranspiration derived from a terrestrial water balance analysis, past research has cast doubt on the ability of existing products to accurately capture variability. Using a variety of estimates, this analysis reexamines this conclusion and finds that estimates of variations obtained from a land surface model are more strongly correlated with independently acquired from thermal infrared remote sensing than derived from water balance considerations. This tendency is attributed to significant interannual variations in terrestrial water storage neglected by the water balance approach. Overall, results demonstrate the need to reassess perceptions concerning the skill of estimates derived from land surface models and show the value of accurate remotely sensed ET products for the...

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

AbstractDespite considerable interest in the application of land surface data assimilation systems (LDASs) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model, and a sequential data assimilation filter) against a series of linear models that perform the same function (i.e., have the same basic input/output structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moisture/NDVI correlations obtained using individual LDAS components versus their linear analo...

Climate-Agriculture-Modeling and Decision Tool (CAMDT): A software framework for climate risk management in agriculture

Seasonal climate forecasts (SCFs) have received a lot of attention for climate risk management in agriculture. The question is, how can we use SCFs for informing decisions in agriculture? SCFs are provided in formats not so conducive for decision-making. The commonly issued tercile probabilities of most likely rainfall categories i.e., below normal (BN), near normal (NN) and above normal (AN), are not easy to translate into metrics useful for decision support. Linking SCF with crop models is one way that can produce useful information for supporting strategic and tactical decisions in crop production e.g., crop choices, management practices, insurance, etc. Here, we developed a decision support system (DSS) tool, Climate-Agriculture-Modeling and Decision Tool (CAMDT), that aims to facilitate translations of probabilistic SCFs to crop responses that can help decision makers adjust crop and water management practices that may improve outcomes given the expected climatic condition of the growing season.

The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation

The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications.

Designing and Implementing Weather Generators as Web Services

Climate and weather realizations are essential inputs for simulating crop growth and yields to analyze the risks associated with future conditions. To simplify the procedure of generating weather realizations and make them available over the Internet, we implemented novel mechanisms for providing weather generators as web services, as well as a mechanism for sharing identical weather realizations given a climatological information. A web service for preparing long-term climate data was implemented based on an international standard, Sensor Observation Service (SOS). The weather generator services, which are the core components of the framework, analyze climatological data, and can take seasonal climate forecasts as inputs for generating weather realizations. The generated weather realizations are encoded in a standard format, which are ready for use to crop modeling. All outputs are generated in SOS standard, which broadens the extent of data sharing and interoperability with other sectoral applications, e.g., water resources management. These services facilitate the development of other applications requiring input weather realizations, as these can be obtained easily by just calling the service. The workload of analysts related to data preparation and handling of legacy weather generator programs can be reduced. The architectural design and implementation presented here can be used as a prototype for constructing further services on top of an interoperable sensor network system.