Scripps Institution of Oceanography，University of California，La Jolla, Califorma
INTRODUCTION
As a result of wartime research on ocean surface waves a methbd has been
available since 1943 for the prediction of wave characteristics of interest to
engineers (O'Brien and Johnson, 1947). The initial stimulus for the development
came during the planning of the invasion of North Africa, and the methods subsequently devised were later used in a number of amphibious operations (Bates, 1949).
The same techniques have found useful peacetime application in problems connected
with coastal engineering. Much of the application to date has consisted in applying wave prediction techniques to historical rather than current meteorological
A hindcast is a way of testing a mathematical model. Known or closely estimated inputs for past events are entered into the model to see how well the output matches the known results. Hindcasting is also known as backtesting.
An example of hindcasting would be entering climate forcings (events that force change) into a climate model. If the hindcast showed reasonably accurate climate response, the model would be considered successful.
In oceanography[1] and meteorology,[2] hindcasting usually refers to a numerical model integration of a historical period where no observations have been assimilated. This distinguishes a hindcast run from a reanalysis. Oceanographic observations of salinity and temperature as well as observations of surface wave parameters such as the significant wave height are much scarcer than meteorological observations, making hindcasting more common in oceanography than in meteorology. Also, since surface waves represent a forced system where the wind is the only generating force,wave hindcasting is often considered adequate for generating a reasonable representation of the wave climate with little need for a full reanalysis. Hindcasting is also used in hydrology for model stream flows.[3]
The ECMWF re-analysis is an example of a combined atmospheric reanalysis coupled with a wave model integration where no wave parameters were assimilated, making the wave part a hindcast run.
Earth’s changing environment and rapidly growing population are pushing plants and animals out of their native habitats, but current models that predict how this will affect the ecosystem are little more than educated guesses. And when the models have been tested, they’ve been wildly inaccurate.
A large and diverse group of scientists at UC Berkeley has launched a unique program, the Berkeley Initiative in Global Change Biology (BiGCB), to improve the reliability and accuracy of these models. The experts are employing hindcasting — “predicting” what happened during past episodes of climate change — to help them develop and test new models that will improve forecasting.
“The only way to test a model and improve forecasting is through hindcasting,” said Charles Marshall, director of the University of California Museum of Paleontology and a UC Berkeley professor of integrative biology. “Once we have a tested model that accurately tells us what is likely to happen to biological systems, we can construct policies to minimize unwanted impacts.”
Hindcasting the continuum of Dansgaard–Oeschger variability: mechanisms, patterns and timing
L. Menviel1,2, A. Timmermann3, T. Friedrich3, and M. H. England1,2 1Climate Change Research Centre, University of New South Wales, Sydney, Australia 2ARC Centre of Excellence in Climate System Science, Australia 3International Pacific Research Center, School of Ocean and Earth Sciences and Technology, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA
Abstract. Millennial-scale variability associated with Dansgaard–Oeschger (DO) and Heinrich events (HE) is arguably one of the most puzzling climate phenomena ever discovered in paleoclimate archives. Here, we set out to elucidate the underlying dynamics by conducting a transient global hindcast simulation with a 3-dimensional intermediate complexity Earth system model covering the period 50 ka BP to 30 ka BP. The model is forced by time-varying external boundary conditions (greenhouse gases, orbital forcing, and ice sheet orography and albedo) and anomalous North Atlantic freshwater fluxes, which mimic the effects of changing Northern Hemisphere ice-volume on millennial timescales. Together these forcings generate a realistic global climate trajectory, as demonstrated by an extensive model/paleo data comparison. Our analysis is consistent with the idea that variations in ice sheet calving and related changes of the Atlantic Meridional Overturning Circulation were the main drivers for the continuum of DO and HE variability seen in paleorecords across the globe.
