Time of emergence of climate signals
نویسندگان
چکیده
The time at which the signal of climate change emerges from the noise of natural climate variability (Time of Emergence, ToE) is a key variable for climate predictions and risk assessments. Here we present a methodology for estimating ToE for individual climate models, and use it to make maps of ToE for surface air temperature (SAT) based on the CMIP3 global climate models. Consistent with previous studies we show that the median ToE occurs several decades sooner in low latitudes, particularly in boreal summer, than in midlatitudes. We also show that the median ToE in the Arctic occurs sooner in boreal winter than in boreal summer. A key new aspect of our study is that we quantify the uncertainty in ToE that arises not only from inter-model differences in the magnitude of the climate change signal, but also from large differences in the simulation of natural climate variability. The uncertainty in ToE is at least 30 years in the regions examined, and as much as 60 years in some regions. Alternative emissions scenarios lead to changes in the both the median ToE (by a decade or more) and its uncertainty. The SRES B1 scenario is associated with a very large uncertainty in ToE in some regions. Our findings have important implications for climate modelling and climate policy which we discuss.
منابع مشابه
Forecasting of rainfall using different input selection methods on climate signals for neural network inputs
Long-term prediction of precipitation in planning and managing water resources, especially in arid and semi-arid countries such as Iran, has a great importance. In this paper, a method for predicting long-term precipitation using weather signals and artificial neural networks is presented. For this purpose, climatic data (large-scale signals) and meteorological data (local precipitation and tem...
متن کاملEmergence timescales for detection of anthropogenic climate change in US tropical cyclone loss data
Recent reviews have concluded that efforts to date have yet to detect or attribute an anthropogenic climate change influence on Atlantic tropical cyclone (of at least tropical storm strength) behaviour and concomitant damage. However, the possibility of identifying such influence in the future cannot be ruled out. Using projections of future tropical cyclone activity from a recent prominent stu...
متن کاملThe Effect of Climate Changes on human Bacterial infectious diseases
A growing body of documents shows that rising average global temperatures can be one of several causes of disease emergence and reemergence among human and animal populations. In this regard, climate mostly affects diseases caused by pathogens that spend part of their lifecycle outside of the host, exposed to the environment like water-borne diseases, food-borne pathogens, and vector-borne zoon...
متن کاملProper integration time of polarization signals of internetwork regions using Sunrise/IMaX data
Distribution of magnetic fields in the quiet-Sun internetwork areas has been affected by weak polarization (in particular Stokes Q and U) signals. To improve the signal-to-noise ratio (SNR) of the weak polarization signals, several approaches, including temporal integrations, have been proposed in the literature. In this study, we aim to investigate a proper temporal-integration time with which...
متن کاملWindowing Effects of Short Time Fourier Transform on Wideband Array Signal Processing Using Maximum Likelihood Estimation
During the last two decades, Maximum Likelihood estimation (ML) has been used to determine Direction Of Arrival (DOA) and signals propagated by the sources, using narrowband array signals. The algorithm fails in the case of wideband signals. As an attempt by the present study to overcome the problem, the array outputs are transformed into narrowband frequency bins, using short time Fourier tran...
متن کامل