<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=Windows-1252">
<style type="text/css" style="display:none;"> P {margin-top:0;margin-bottom:0;} </style>
</head>
<body dir="ltr">
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Dear all,</div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Please join us for the EOAS Colloquium this Friday, by Professor Ming Cai from our own department.</div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Location and Time: EOAS 1050, Friday September 6th, 3:00PM. </div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Abstract Details below.</div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
----</div>
<div style="direction: ltr; text-align: center; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
<b>A New Paradigm for Principles-Based Adept Predictions of Global Warming from Climate Mean States </b> </div>
<div style="direction: ltr; text-align: center; text-indent: 0px; white-space: pre-wrap; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Prof. Ming Cai </div>
<div style="direction: ltr; text-align: center; text-indent: 0px; white-space: pre-wrap; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Florida State University</div>
<div style="direction: ltr; text-align: center; text-indent: 0px; white-space: pre-wrap; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
</div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
<b>Abstract</b> </div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
<br>
</div>
<div style="direction: ltr; text-align: left; text-indent: 0px; white-space: pre-wrap; margin: 1em 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);" class="elementToProof">
Distinguishing anthropogenic warming from natural variability in observations and reducing uncertainty in global warming projections by climate models remain critical challenges for climate scientists. In our work, we present a groundbreaking principle-based
framework for adept predictions of the global mean warming and its spatial pattern in response to external energy perturbations from climate mean states without running climate models or relying on statistical trend analysis.
</div>
<div style="margin-top: 1em; margin-bottom: 1em; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
When applied to the observed climate mean state of 1980-2000, our framework accurately predicts the global warming observed from 1980-2000 to 2000-2020, with a prediction of 0.403 K compared to an observed value of 0.414 K. Our predictions from the preindustrial
mean climate states of individual CMPI6 models yields a similar median global mean warming to their warming projections under the abrupt 4×CO2 scenario (5.4 K versus 5.6 K), but with noticeably less inter-model spread. Our predictions not only exhibit a high
map correlation skill comparable to that of each individual CMIP6 model for the observed warming, but also capture the temporal pace of their warming projections under 1% annual CO2-increasing scenario.</div>
<div style="margin-top: 1em; margin-bottom: 1em; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
The success of our global warming prediction from climate mean states under any given scenarios of CO2 increasing without running climate models is built on the following two innovations. One of them is our recent discovery of nature’s climate feedback 'circuit'
associated with temperature feedback. The other is that we extract the information of surface energy amplification by non-temperature feedback from the ratio of downward longwave energy emission from the atmosphere to solar energy absorbed by the surface in
climate mean states. The product of amplification rates by temperature and non-temperature feedbacks corresponds to the total amplification of energy perturbations at the surface caused by CO2 increasing. Temperature feedback yields a 6.6-fold global mean
amplification, while non-temperature feedback contributes an another 2.3-fold amplification. This results in a total 15.8-fold increase in the global mean of CO2-induced energy perturbations at the surface. The energy balance between the enhanced thermal emission
from the surface and the total external energy input perturbations amplified by temperature and non-temperature feedback determines the global surface warming in response to CO2 increasing.</div>
<div style="text-align: left; text-indent: 0px; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
</div>
<div style="text-align: left; text-indent: 0px; margin: 0px; font-family: Aptos, Aptos_EmbeddedFont, Aptos_MSFontService, Calibri, Helvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
</div>
</body>
</html>