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Abstract Understanding El Niño-Southern Oscillation (ENSO) response to past climate forcings is hindered by conflicting paleoclimate evidence. Records from the eastern Pacific show an intensification of ENSO variability from early to late Holocene, while records from the central Pacific show highly variable ENSO throughout the Holocene without an obvious relation to insolation forcing, which is the main climate driver during this interval. Here, we show via climate model simulations that conflicting Holocene records can be reconciled by considering changes in the relative frequency of the three preferred spatial patterns in which El Niño events occur (Eastern Pacific, Central Pacific, and Coastal) and in the strength of their hydroclimatic impacts. The relationship between ENSO diversity and variance is not only crucial for interpreting paleo-ENSO records and understanding ENSO response to external forcings but can also be used across climate model simulations to help evaluate the realism of ENSO projections in a changing climate.
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Tropical cyclone frequency: turning paleoclimate into projections
Abstract Future changes to tropical cyclone (TC) climate have the potential to dramatically impact the social and economic landscape of coastal communities. Paleoclimate modeling and paleohurricane proxy development offer exciting opportunities to understand how TC properties (like frequency) change in response to climate variability on long time scales. However, sampling biases in proxies make it difficult to ascertain whether signals in paleohurricane records are related to climate variability or just stochasticity. Short observations and simulation biases prevent TC models from capturing the full range of climate variability and TC characteristics. Integration of these two data types can help address these uncertainties. Robust data model comparison in paleotempestology will require (a) simulating TCs using new paleoclimate data assimilation products and climate model ensembles, (b) building a central repository of open access paleohurricane proxies, (c) compiling paleohurricane records, and (d) filling key gaps in the existing paleohurricane networks. Incorporating the combined information from both paleohurricane proxies and paleo TC simulations into risk assessments for coastal communities could help improve adaptation strategies.
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- Award ID(s):
- 2234815
- PAR ID:
- 10388219
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research: Climate
- Volume:
- 1
- Issue:
- 2
- ISSN:
- 2752-5295
- Page Range / eLocation ID:
- Article No. 023002
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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