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THE ROLE OF THE LAND SURFACE IN THE CLIMATE SYSTEM Projects... PI: Robock Co-PI: None Agency: NOAA Title: Evaluation and Development of the Land Data Assimilation System (LDAS) Using Observations Abstract: The Land Data Assimilation System (LDAS) is a project to test state-of-the-art land surface models for use in data assimilation. Once we have a good model, we will develop a real-time land surface data assimilation system that uses in situ and remotely-sensed soil moisture, skin temperature, andsnow to produce (in real time and later in a reanalysis) an accurate soil moisture data set that can be used for retrospective land-memory predictability studies, and for real-time coupled model predictions of weather and seasonal climate. We are still in the stage of improving the models. In this project, we are continuing our participation as part of the North American LDAS (N-LDAS) Science Team, particularly in the validation aspects. We are gathering and quality controlling observations of soil moisture and surface forcing, and use them to evaluate the four land surface models participating in N-LDAS. As the models are improved, we will use the soil moisture observations in experiments in data assimilation, both as data to ingest for the procedures as well as for validation. In addition we will continue to gather global data as part of the Global Soil Moisture Data Bank, and participate in other projects, such as the Global Soil Wetness Project II and the Global LDAS
PI: Weaver Co-PI: Roni Avissar, Robert L. Walko Agency: NOAA Title: An Investigation of Persistence in the Coupled Land-Atmosphere System: The Role of Soil Moisture Abstract: A major focus of GAPP is improving our ability to predict hydrologic quantities such as evaporation, precipitation, and runoff at monthly, seasonal, and interannual timescales, and at spatial scales from continental to that of a local watershed. Persistence of anomalies in land-surface and atmospheric variables over such timescales is recognized as a possible aid to improving this predictability. Feedbacks between the land-surface and the atmosphere, such as local recycling of precipitation, are thought to enhance persistence in both surface and atmospheric variables, and a better understanding of how, when, where, and at what scales these feedback mechanisms operate is necessary for achieving desired predictability goals. In particular, mesoscale atmospheric circulations forced by subgrid-scale (to a GCM) heterogeneity in the underlying landscape may play a potentially significant role in how precipitation recycling operates in a given region. The interactions between heterogeneity in soil moisture, the induced mesoscale circulations, and the corresponding impact of the resulting clouds and precipitation on the surface energy and water balance, introduce the potential for complex, nonlinear feedbacks between the surface and the atmosphere. These feedbacks may provide a mechanism for lengthening the timescale of mesoscale land-atmosphere interaction, thus perhaps significantly influencing large-scale precipitation and soil moisture over time. How this mechanism operates in the real climate system, and how the effects would vary between regions that are climatologically very different, such as the continental U.S. and Amazonia, is not known. The objectives of the project proposed here are: (i) to investigate seasonal-scale persistence of anomalies in soil moisture and related variables, globally, though with a focus on the GAPP U.S. study area and the LBA Amazonian study area, using a sophisticated atmosphere/land/hydrology model; (ii) to uncover persistence mechanisms resulting from specific physical-dynamical processes and feedbacks in the coupled land-atmosphere system; (iii) to investigate the impact of subgrid-scale landscape heterogeneity in the GAPP and LBA study areas on large-scale precipitation recycling, the evolution of the soil moisture distribution over time, and large-scale persistence. This research is expected to address key aspects of the GAPP objectives, related to improving extended-range hydrologic predictability, as identified in the GAPP Science Plan.
PI: Weaver Co-PI: None Agency: NSF Title: Linkages Between Large-Scale and Mesoscale Dynamics, Land-Atmosphere Interactions, and Convective Rainfall Abstract: This proposal describes a project to investigate the role of mesoscale land-atmosphere interactionsboth their control by large-scale meteorological conditions and their aggregate impact at these large scalesin the coupled land-atmosphere system. The goal is to determine the impact of these scale interactions on warm season convective precipitation in the continental U.S., with a focus on links between soil moisture and rainfall. The underlying hypothesis is that nonlinear interactions between scales may be a source of important feedbacks that might help control the joint evolution of the land and atmosphere. The strategy will be to use a state-of-the-art, high-resolution coupled land-atmosphere modeling system to investigate the following primary research questions:
The results of this investigation are expected to contribute to a deeper and more unified picture of land-atmosphere coupling across spatial scales from mesoscale to synoptic, and across timescales from hourly to seasonal. Recent research suggests that land-atmosphere interactions and feedbacks, e.g., links between soil moisture and precipitation, are an important control on continental-scale hydrometeorlogy, and furthermore that the spatial heterogeneity of surface characteristics, not just their mean values, may also be important. Current large-scale models (e.g., GCMs) may not adequately capture all the relevant interactions, thus hampering their predictive ability. A possible factor is that processes associated with subgrid-scale surface heterogeneity in such models may be important. However, the extent to which small-scale surface heterogeneity, e.g., on the order of 10 km, plays a role at larger spatial scales is unknown, and is currently a topic of debate in the meteorological community. The work proposed here is intended to provide additional insight into this issue. Because the proposed model simulations incorporate both high resolution and seasonal run times, it is hoped that they will be able to bridge some of the gaps in space and time that are forced by the tradeoffs, arising from computing limitations, between domain size, resolution, and simulation length, that have so far hindered investigation of these questions. Improving our understanding of the factors that control continental rainfall, both its mean value and spatial and temporal variability, particularly at long lead times such as monthly to seasonal, is crucial for applications such as managing water resources and planning for weather-related emergencies. Furthermore, estimating changes in regional climate and hydrology resulting from the combined influence of changing atmospheric composition and natural or anthropogenic land cover change will require improved representations of land-atmosphere interactions in models. The improved understanding that it is hoped will emerge from the proposed work is expected to have broader implications in these areas. Finally, the work proposed here is expected to contribute to graduate study and graduate research opportunities, through the PIs affiliation with the Department of Environmental Sciences at Rutgers University, and to outreach to the general public, through the PIs affiliation with the Center for Environmental Prediction, also at Rutgers University.
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