Research

Agriculture
We examine the impact of climate and weather extremes on agriculture, from perennial crops like almonds to annual specialty crops like strawberries and lettuce, by developing and applying data-driven and processed-based crop models.
Irrigation
We estimate irrigation demand in California by analyzing high-resolution gridded daily reference evapotranspiration data and by developing and applying a processed-based crop model to estimate the water demand of key specialty crops across the State.
Wildfire
We collaborate with the U.S. Forest Service to improve wildfire modeling to better inform forest management and we use observational analysis and modeling to understand the role of wildfire on human health, the global carbon cycle, and biodiversity.
Air Quality
We study the impact of air pollution on the health of society and the environment, including the interactions between climate, air quality, and health, and the impacts of compound heat waves and wildfire smoke on the health of communities across California.
Terrestrial Ecosystems
We examine the role of terrestrial ecosystems, from biocrusts to forests, in the global biogeochemical cycles and the fate of the natural land system in the face of land-use change, and climate and weather extremes.
Marine Ecosystems
We collaborate with marine ecosystem and biogeochemical cycle experts to examine the fate of marine ecosystems under global environmental change, from climate impacts to mercury pollution.

Our Lab is involved in several interdisciplinary research project aimed at better understanding the drivers and consequences of global environmental change. Some of these research projects are highlighted below:

  • Agriculture
  • We recently developed a novel perennial crop modeling framework that links agro-climate indices, which represent the main optimal and damaging environmental conditions associated with the various almond growth stages, to county-level almond yield data. The modeling framework also represents innovation gains derived from past historical trends in yields, which can be used to test various scenarios of future innovation and contrast these potential gains with climate damages. Currently in press in Earth's Future, this work projects an almond yield decline by 17% under medium warming and 49% under high warming by the end of the century, with future climate damages primarily driven by higher minimum temperature and humidity during bloom and higher heat stress during the growth stage. However, we also find that future agronomic innovation and targeted adaptation strategies can offset these climate damages and even result in future yield gains.

    We have also been developing a gridded process-based crop model based on the FAO AquaCrop model. This efforts has focused on conducting a global sensitivity analysis to identify the most sensitive model parameters that require precise calibration. This includes the development of a calibration approach using the shuffled complex evolution algorithm and county-level yield data, using U.S. maize as a case study, and the evaluation of the model's performance against observation and model simulations from the Global Gridded Crop Modeling Intercomparison (GGCMI). A manuscript is in preparation for the Journal of Advances in Modeling Earth Systems.

    In addition, we have been developing agro-climate indices for California perennial tree crops other than almonds, focusing primarily on tree fruits including cherries, peaches, nectarines and olives. Our plan is to examine climate impacts on tree fruits production in California, to develop economic models of tree fruits to better understand the economic consequences of climate-driven yield changes and to identify potential migration responses. Finally, we plan to work with farmers to better understanding the decision making process driving their responses to climatic and extreme weather shocks.
  • Irrigation
  • Our Lab has been leading an overview and evaluation of the high-resolution gridded daily reference evapotranspiration (ETo) developed for the California Irrigation Management Information System (CIMIS) program by a collaboration between the California Department of Water Resources (DWR) and UC Davis. CIMIS manages a network of over 145 automated weather stations in California that produces estimates of reference evapotranspiration (ETo) for the station locations and their immediate surroundings, which is designed to assist irrigators in managing their water resources more efficiently. The evaluation compares Spatial CIMIS dataset to the station data and to another well-used gridded dataset of reference evapotranspiration, namely GridMET. We have also conducted an analysis of the Spatial CIMIS users, which include agribusinesses, government agencies, researchers, and individual farmers, and reviewed the academic literature to better understand the main usage of this dataset. A manuscript is in preparation for the Scientific Data journal.

    We have also been updating the ETo zones map that was developed by DWR and UC Davis in the 1990s and divides the State into 18 zones based on long-term monthly average ETo. The ETo zones map has been used to help in urban and agricultural water management planning and water budgeting, as well as designing irrigation systems, planning irrigation schedules, and designing open water evaporation systems. We have been using Spatial CIMIS ETo data and machine learning techniques to develop the new ETo zones map.
  • Wildfires
  • We are collaborating with the U.S. Fire Service to examine the main differences between three major global wildfire models, namely MCFire, the wildfire submodel within the MC2 dynamic global vegetation model developed by the U.S. Forest Service Pacific Northwest (PNW) Research Station, SPITFIRE (SPread and InTensity of FIRE in LPJmL), a wildfire model that has been implemented in several dynamic global vegetation models in Europe, and RESFire (REgion-Specific ecosystem feedback Fire model), the fire model implemented in the Community Earth System Model (CESM). The objetive of this work is to provide directions for future improvements of the representation of wildfire in MC2.
  • Air Quality
  • We have been collaborating with atmospheric chemists, civil and environmental engineers, epidemiologists, and air quality experts to investigate the impact of air pollution on the health of society and the environment. We have examined the interactions between climate, air quality and human health using integrated modeling frameworks linking economic models, climate models and atmospheric chemistry models. He have also contributed to observational analyses of the exposure of California communities to compound heat waves and wildfire smoke and the consequences on hospitalization in vulnerable communities across California.
  • Terrestrial Ecosystems
  • Our Lab is collaborating with Prof Ben Felzer at Lehigh University, lead developer of the Global Dynamical Structural Terrestrial Ecosystem Model (GDSTEM), to evaluate and improve the model to become part of the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project, an international ensemble of Dynamic Global Vegetation Models (DGVMs). TRENDY quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project.

    We are also developing a large ensemble of GDSTEM simulations under future climate projections using different climate models and under different climate and land-use change scenarios. The aim of this work is to identify the uncertainty in future projections of the terrestrial carbon cycle.

    We are also working on quantifying the contributions of biocrusts, communities of organisms that include cyanobacteria, algae, lichens, and mosses, to the global carbon and nitrogen cycles and on understanding the environmental drivers of carbon and nitrogen fluxes from biocrusts.
  • Marine Ecosystems
  • Our Lab has been collaborating with marine ecosystem and biogeochemical cycle experts and modelers to examine the fate of marine ecosystems focusing under global environmental change. These collaborations range from modeling the climate impacts on phytoplankton, which form the foundation of the marine food web and are crucial in the carbon cycle, to modeling the biomagnification of Methylmercury, a highly toxic organic mercury compound, in phytoplankton and zooplankton and investigating the climate impacts on Methylmercury exposure in the marine food webs.

 

We invite you to learn more about our publications.