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Title: Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. Final Report

Abstract

This U.S-Brazil collaboration for GOAmazon has investigated a deceptively simple question: what controls the response of photosynthesis in Amazon tropical forests to seasonal variations in climate? In the past this question has been difficult to answer with modern earth system process models. We hypothesized that observed dry season increases in photosynthetic capacity are controlled by the phenology of leaf flush and litter fall, from which the seasonal pattern of LAI emerges. Our results confirm this hypothesis (Wu et al., 2016). Synthesis of data collected throughout the 3-year project period continues through December 31, 2017 under no-cost extensions granted to the project teams at University of Michigan and University of Arizona (Award 2). The USGS component (Award 1) ceased on the final date of the project performance period, December 31, 2016. This report summarizes the overall activities and achievements of the project, and constitutes the final project report for the USGS component. The University of Michigan will submit a separate final report that includes additional results and deliverables achieved during the period of their and the University of Arizona’s no-cost extension, which will end on December 31, 2017.

Authors:
 [1];  [2];  [3];  [4]
  1. U.S. Geological Survey, Menlo Park, CA (United States)
  2. Univ. of Michigan, Ann Arbor, MI (United States)
  3. Univ. of Arizona, Tucson, AZ (United States)
  4. Univ. of Arizona, Tucson, AZ (United States); Univ. of Technology, Sydney NSW (Australia)
Publication Date:
Research Org.:
US Geological Survey, Flagstaff, AZ (United States). Western Geographic Science Center
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1349260
Report Number(s):
DOE-SC0008383
ER65592
DOE Contract Number:
SC0008383
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Photosynthetic Metabolism; Tropical Forests; Seasonal Climate Variations

Citation Formats

Dye, Dennis, Ivanov, Valeriy, Saleska, Scott, and Huete, Alfredo. Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. Final Report. United States: N. p., 2017. Web. doi:10.2172/1349260.
Dye, Dennis, Ivanov, Valeriy, Saleska, Scott, & Huete, Alfredo. Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. Final Report. United States. doi:10.2172/1349260.
Dye, Dennis, Ivanov, Valeriy, Saleska, Scott, and Huete, Alfredo. Fri . "Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. Final Report". United States. doi:10.2172/1349260. https://www.osti.gov/servlets/purl/1349260.
@article{osti_1349260,
title = {Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. Final Report},
author = {Dye, Dennis and Ivanov, Valeriy and Saleska, Scott and Huete, Alfredo},
abstractNote = {This U.S-Brazil collaboration for GOAmazon has investigated a deceptively simple question: what controls the response of photosynthesis in Amazon tropical forests to seasonal variations in climate? In the past this question has been difficult to answer with modern earth system process models. We hypothesized that observed dry season increases in photosynthetic capacity are controlled by the phenology of leaf flush and litter fall, from which the seasonal pattern of LAI emerges. Our results confirm this hypothesis (Wu et al., 2016). Synthesis of data collected throughout the 3-year project period continues through December 31, 2017 under no-cost extensions granted to the project teams at University of Michigan and University of Arizona (Award 2). The USGS component (Award 1) ceased on the final date of the project performance period, December 31, 2016. This report summarizes the overall activities and achievements of the project, and constitutes the final project report for the USGS component. The University of Michigan will submit a separate final report that includes additional results and deliverables achieved during the period of their and the University of Arizona’s no-cost extension, which will end on December 31, 2017.},
doi = {10.2172/1349260},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Mar 31 00:00:00 EDT 2017},
month = {Fri Mar 31 00:00:00 EDT 2017}
}

Technical Report:

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  • This final report is organized in four sections. Section 1 is the project summary (below), Section 2 is a submitted manuscript that describes the offline, or spinup simulations in detail, Section 3 is also a submitted manuscript that describes the online, or fully-coupled simulations in detail and Section 3, which is report that describes work done via a subcontract with UC Berkeley. The goal of this project was to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, the land surface, and groundwater. Themore » project involved coupling three distinct submodels that are traditionally used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This coupled model lead to (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration and groundwater flow) at the watershed scale over a range of timeframes; (3) a simulation of hydrologic response of a characteristic watershed that will provide insight into the certainty of hydrologic forecasting, dominance and sensitivity of groundwater dynamics on land-surface fluxes; and (4) a more realistic model representation of weather predictions, precipitation and temperature, at the regional scale. Regional climate models are typically used for the simulation of weather, precipitation and temperature behavior over 10-1000 km domains for weather or climate prediction purposes, and are typically driven by boundary conditions derived from global climate models (GCMs), observations or both. The land or ocean surface typically represents a bottom boundary condition of these models, where important mass (water) and energy fluxes are approximated. The viability and influence of these approximations on the predictions is not well understood because of the detail and complexity in land and subsurface processes and the need for computational efficiency. However, theoretical and experimental data suggest that these interactions may have a profound impact upon hydrologic and climatic budgets and weather predictions. Conversely, land-surface and groundwater models are typically applied on smaller domains (< 10 km in scale) to analyze runoff, streamflow, infiltration, evapotranspiration behavior, but are still influenced in many ways by couplings with the atmosphere (as in precipitation and temperature). Atmospheric inputs to these classes of models are typically represented as simplified ''upper'' boundary conditions, derived, in part, from coarse observations, uncoupled simulations, or other idealized simplifications. In this project, we developed a framework to couple these models by developing a new land-surface/subsurface model and coupling it to a regional climate model at the same temporal and spatial scales. We focused the coupling to examine the role of important mass and energy couplings between these models as a means to understand the difference between traditional and detailed approaches to this interconnection. From this understanding of these interconnections, we were able to determine to what extent these connections need to be abstracted or preserved in modeling atmospheric, land-surface and groundwater interactions. We have found a strong connection between groundwater dynamics (i.e. aquifer storage) and energy fluxes at the land surface and in the Atmospheric Boundary Layer (ABL). The following papers outline this connection theoretically, demonstrate it with coupled modeling and propose strategies for better observing it in real settings.« less
  • Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biasesmore » in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.« less
  • Seed dispersal is a critical step in the natural regeneration of tropical forests. The pattern of dispersal of tree seeds is likely to have an important influence on the future tree species composition of the forests and hence on the natural diversity associated with those tree species. Animal seed-dispersers are considered to be important agents for the dispersal of the seeds of the majority of tropical tree species. This study is aimed at defining the role of several species of animal dispersers in the dispersal of the ecologically and economically important tree species of the Nyungwe Forest of Rwanda. Themore » Nyungwe Forest is an appropriate target for such a study since it is one of the richest remaining islands of montane forest in central Africa. However, the population and political pressure will require that the forest provide benefits in the form of forest products. A management plan is needed for Nyungwe which can allow exploitation while maintaining the natural biodiversity.« less