Engineering topics

Beaudoing, Hiroko Kato

Publications and source records attributed to Beaudoing, Hiroko Kato.

11 records

NASA NTRS2018

The Land Surface Data Toolkit (LDT v7.2) - A Data Fusion Environment for Land Data Assimilation Systems

The effective applications of land surface models (LSMs) and hydrologic models pose a varied set of data input and processing needs, ranging from ensuring consistency checks to more derived data processing and analytics. This article describes the development of the Land surface Data Toolkit (LDT), which is an integrated framework designed specifically for processing input data to execute LSMs and hydrological models. LDT not only serves as a preprocessor to the NASA Land Information System (LIS), which is an integrated framework designed for multi-model LSM simulations and data assimilation (DA) integrations, but also as a land-surface-based observation and DA input processor. It offers a variety of user options and inputs to processing datasets for use within LIS and stand-alone models. The LDT design facilitates the use of common data formats and conventions. LDT is also capable of processing LSM initial conditions and meteorological boundary conditions and ensuring data quality for inputs to LSMs and DA routines. The machine learning layer in LDT facilitates the use of modern data science algorithms for developing data-driven predictive models. Through the use of an object-oriented framework design, LDT provides extensible features for the continued development of support for different types of observational datasets and data analytics algorithms to aid land surface modeling and data assimilation.

droughts and floods↗

NASA NTRS2016

Large-Scale and Global Hydrology

Powered by the sun, water moves continuously between and through Earths oceanic, atmospheric, and terrestrial reservoirs. It enables life, shapes Earths surface, and responds to and influences climate change. Scientists measure various features of the water cycle using a combination of ground, airborne, and space-based observations, and seek to characterize it at multiple scales with the aid of numerical models. Over time our understanding of the water cycle and ability to quantify it have improved, owing to advances in observational capabilities, the extension of the data record, and increases in computing power and storage. Here we present some of the most recent estimates of global and continental ocean basin scale water cycle stocks and fluxes and provide examples of modern numerical modeling systems and reanalyses.Further, we discuss prospects for predicting water cycle variability at seasonal and longer scales, which is complicated by a changing climate and direct human impacts related to water management and agriculture. Changes to the water cycle will be among the most obvious and important facets of climate change, thus it is crucial that we continue to invest in our ability to monitor it.

land hydrology↗

NASA NTRS2014

LDAS Land Data Assimilation Systems

The land-surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. The characterization of the spatial and temporal variability of water and energy cycles is critical to improve our understanding of the land-surface-atmosphere interaction and the impact of land-surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land-surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes.

data↗

NASA NTRS2012

Identifying and Addressing Land Surface Model Deficiencies with Data Assimilation

Land surface models (LSMs) encapsulate our understanding of terrestrial water and energy cycle physics and provide estimates of land surface states and fluxes when and where measurement gaps exist. Gaps in our understanding of the physics are a different issue. Data assimilation can address that issue both directly, through updating of prognostic model variables, or indirectly, when the simulated world conflicts with observation, necessitating adjustment of the model. Here we will focus on the latter case and present several examples, including (1) depth to bedrock adjustment to accommodate assimilated GRACE terrestrial water storage data; (2) steps to prevent immediate melting of assimilated snow cover; (3) irrigation's contribution to evapotranspiration; (4) lessons learned from soil moisture data assimilation; (5) the potential impact of satellite based runoff observation

Rodell, Matthew↗

NASA NTRS2012

NASA GLDAS Evapotranspiration Data and Climatology

Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.

Rui, Hualan↗

NASA NTRS2012

The NEWS Water Cycle Climatology

NASA's Energy and Water Cycle Study (NEWS) program fosters collaborative research towards improved quantification and prediction of water and energy cycle consequences of climate change. In order to measure change, it is first necessary to describe current conditions. The goal of the first phase of the NEWS Water and Energy Cycle Climatology project was to develop "state of the global water cycle" and "state of the global energy cycle" assessments based on data from modern ground and space based observing systems and data integrating models. The project was a multi-institutional collaboration with more than 20 active contributors. This presentation will describe the results of the water cycle component of the first phase of the project, which include seasonal (monthly) climatologies of water fluxes over land, ocean, and atmosphere at continental and ocean basin scales. The requirement of closure of the water budget (i.e., mass conservation) at various scales was exploited to constrain the flux estimates via an optimization approach that will also be described. Further, error assessments were included with the input datasets, and we examine these in relation to inferred uncertainty in the optimized flux estimates in order to gauge our current ability to close the water budget within an expected uncertainty range.

Rodell, Matthew↗

NASA NTRS2011

NASA Giovanni Portals for NLDAS/GLDAS Online Visualization, Analysis, and Intercomparison

The North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) are generating a series of land surface forcing (e.g., precipitation, surface meteorology, and radiation), state (e.g., soil moisture and temperature, and snow), and flux (e.g., evaporation and sensible heat flux) products, simulated by several land surface models. To date, NLDAS and GLDAS have generated more than 30 (1979 - present) and 60 (1948 - present) years of data, respectively. To further facilitate data accessibility and utilization, three new portals in the NASA Giovanni system have been made available for NLDAS and GLDAS online visualization, analysis, and intercomparison.

Rui, Hualan↗

NASA NTRS2011

NEWS Climatology Project: The State of the Water Cycle at Continental to Global Scales

NASA's Energy and Water Cycle Study (NEWS) program fosters collaborative research towards improved quantification and prediction of water and energy cycle consequences of climate change. In order to measure change, it is first necessary to describe current conditions. The goal of the NEWS Water and Energy Cycle Climatology project is to develop "state of the global water cycle" and "state of the global energy cycle" assessments based on data from modern ground and space based observing systems and data integrating models. The project is a multiinstitutional collaboration with more than 20 active contributors. This presentation will describe results of the first stage of the water budget analysis, whose goal was to characterize the current state of the water cycle on mean monthly, continental scales. We examine our success in closing the water budget within the expected uncertainty range and the effects of forcing budget closure as a method for refining individual flux estimates.

Rodell, Matthew↗

NASA NTRS2010

New and Improved GLDAS and NLDAS Data Sets and Data Services at HDISC/NASA

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. Generating global fields of these variables, however, is still a challenge. The goal of a land data assimilation system (LDAS)is to ingest satellite-and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast.

Rui, Hualan↗

NASA NTRS2010

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

Beaudoing, Hiroko Kato↗

NASA NTRS2009

Simulating the Effects of Irrigation over the U.S. in a Land Surface Model Based on Satellite Derived Agricultural Data

A novel method is introduced for integrating satellite derived irrigation data and high-resolution crop type information into a land surface model (LSM). The objective is to improve the simulation of land surface states and fluxes through better representation of agricultural land use. Ultimately, this scheme could enable numerical weather prediction (NWP) models to capture land-atmosphere feedbacks in managed lands more accurately and thus improve forecast skill. Here we show that application of the new irrigation scheme over the continental US significantly influences the surface water and energy balances by modulating the partitioning of water between the surface and the atmosphere. In our experiment, irrigation caused a 12% increase in evapotranspiration (QLE) and an equivalent reduction in the sensible heat flux (QH) averaged over all irrigated areas in the continental US during the 2003 growing season. Local effects were more extreme: irrigation shifted more than 100 W/m from QH to QLE in many locations in California, eastern Idaho, southern Washington, and southern Colorado during peak crop growth. In these cases, the changes in ground heat flux (QG), net radiation (RNET), evapotranspiration (ET), runoff (R), and soil moisture (SM) were more than 3 W/m(sup 2), 20 W/m(sup 2), 5 mm/day, 0.3 mm/day, and 100 mm, respectively. These results are highly relevant to continental- to global-scale water and energy cycle studies that, to date, have struggled to quantify the effects of agricultural management practices such as irrigation. Based on the results presented here, we expect that better representation of managed lands will lead to improved weather and climate forecasting skill when the new irrigation scheme is incorporated into NWP models such as NOAA's Global Forecast System (GFS).

Ozdogan, Mutlu↗