Parsa Gooya

ORCID: 0000-0003-2539-263X
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About
Contact & Profiles
Research Areas
  • Atmospheric and Environmental Gas Dynamics
  • Climate variability and models
  • Marine and coastal ecosystems
  • Oceanographic and Atmospheric Processes
  • Methane Hydrates and Related Phenomena
  • Health, Environment, Cognitive Aging
  • Ocean Acidification Effects and Responses
  • Cryospheric studies and observations

Climate Centre
2023-2024

University of Victoria
2022-2023

Environment and Climate Change Canada
2022-2023

Improving our understanding of how the ocean absorbs carbon dioxide is critical to climate change mitigation efforts. We, a group early career professionals working in Canada, summarize current research and identify steps forward improve marine sink Canadian national offshore waters. We have compiled an extensive collection reported surface air–sea exchange values within each Canada's three adjacent basins. review fluxes major challenges limiting Pacific, Arctic, Atlantic Ocean. focus on...

10.1139/facets-2022-0214 article EN cc-by FACETS 2023-01-01

Abstract. As a major sink for anthropogenic carbon, the oceans slow increase in carbon dioxide atmosphere and regulate climate change. Future changes ocean sink, its uncertainty at global regional scale, are key to understanding future evolution of climate. Here we report on uncertainties historical using output from Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble compare an observation-based product. We show that concentrated highly active regions – 70 % total...

10.5194/esd-14-383-2023 article EN cc-by Earth System Dynamics 2023-04-11

We implement an encoder-decoder artificial neural network (ANN) to post-process decadal predictions of gridded air-sea CO2 flux produced with Earth system model (ESM) prescribed emissions. Decadal are initialized by constraining the ESM observational data and drift toward unconstrained climatology. The resulting biased forecasts require adjustments make usable. By leveraging flexibility ANN learn complex nonlinear relationship between raw verifying data, its ability from non-local spatial...

10.22541/essoar.172798936.65411263/v2 preprint EN Authorea (Authorea) 2024-10-15

Abstract An essential step toward meeting agreed climate targets and policies is the ability to understand predict near‐term changes in global carbon cycle, importantly, ocean uptake. Initialized model simulations have proven skillful for predictability of key physical variables, example, temperature, precipitation, etc. By comparison, predictions biogeochemical fields like flux, are still emerging. Initial studies indicate possible lead‐times up 6 years at scale some CMIP6 models. However,...

10.1029/2023ef004204 article EN cc-by-nc-nd Earth s Future 2024-12-01

Initialized climate model simulations have proven skillful for near-term predictability of the key physical variables. By comparison, predictions biogeochemical fields like ocean carbon flux, are still emerging. Initial studies indicate possible lead-times up to six years at global scale some CMIP6 models. However, unlike core variables, variables not directly initialized in existing decadal preciction systems, and extensive empirical parametrization ocean-biogeochemistry Earth System Models...

10.22541/essoar.169945414.42550583/v1 preprint EN Authorea (Authorea) 2023-11-08

Initialized climate model simulations have proven skillful for near-term predictability of the key physical variables. By comparison, predictions biogeochemical fields like ocean carbon flux, are still emerging. Initial studies indicate possible lead-times up to six years at global scale some CMIP6 models. However, unlike core variables, variables not directly initialized in existing decadal preciction systems, and extensive empirical parametrization ocean-biogeochemistry Earth System Models...

10.22541/essoar.169945380.07415268/v1 preprint EN Authorea (Authorea) 2023-11-08

Abstract. As a major sink for anthropogenic carbon, the oceans slow increase of carbon dioxide in atmosphere and regulate climate change. Future changes ocean sink, its uncertainty at global regional scale, are key to understanding future evolution climate. Here, we conduct multimodel analysis uncertainties historical using output data from latest phase Coupled Model Intercomparison Project: CMIP6, observations. We show that is concentrated highly active regions – 70 percent total occurs...

10.5194/esd-2022-19 preprint EN cc-by 2022-05-18
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