Session Description

Global and regional climate SST reanalyses and climate data records are essential for monitoring and characterisation of the climate system and its change. Sustained monitoring provides an observational basis for our understanding of climate change and variability, and enables us to place current events into the context of the past. It draws upon information from in situ and satellite observations as well as dynamical reanalyses and climate models. This session aims to highlight the recent advancements in SST climate data records and reanalyses with a particular focus on the observed trends, variabilities and the corresponding uncertainties. This session also welcomes contributions on the use of SST products in climate models for assimilation as well as model evaluations. Comparison and validation of climate simulations using different SST datasets are welcome, in order to provide information to producers to enable them to improve their products for specific applications.

The session will focus on the following: 

  • Advances in observational climate and reanalysis SST products
  • Applications of SST observations and reanalyses in global and regional assessments of climate change and variability
  • Applications of SST observations for assimilation, evaluation and inter-comparisons of climate models and dynamical reanalyses. 
  • Comparison and validation of climate simulations using different SST datasets

Keywords: Climate monitoring, climate data records and reanalyses, climate change and variability, trends, climate-indicators, dynamical reanalyses, climate model simulations.

Keynote

Impact of resolution on observed SST climatology and variability

Cristina González Haro, Institut de Ciències del Mar (ICM), Barcelona Expert Center (BEC) on Remote Sensing Spanish National Research Council (CSIC)

Dr. Cristina González Haro has a multi-disciplinary background having studied Electronic and Telecommunications Engineering BsC, having specialized in remote sensing of the ocean during her MSc and acquiring fundamental understanding of physical oceanography during her PhD. She is currently a contracted researcher at the Institut de Ciències del Mar (ICM-CSIC) in the Barcelona Expert Center (BEC) group. Her research activity is centered in Ocean Remote Sensing, with special emphasis in the exploitation of remote sensing data to study and investigate the dynamics of the ocean’s upper layers. She is a science team member of the Group for High Resolution Sea Surface Temperature (GHRSST) and was co-chair of the task team on Feature Fidelity (F2T2) from 2021-2023.

Talks

A new global, combined SST and IST CDR from 1982 to 2024, for the Copernicus Climate Change Service

Ioanna Karagali, Danish Meteorological Institute

Dr. Karagali handles the production and dissemination of Copernicus Marine Service SST and IST products for the North Sea/Baltic Sea and the Arctic. She holds a PhD in Remote Sensing for Meteorology and Oceanography and is currently a Senior Consultant at the Danish Meteorological Institute where she is responsible for research, dissemination, coordination, and project management. Prior to DMI, Ioanna held positions as a Post-Doc and Senior Researcher at the Danish Technological University in Copenhagen. With a strong focus on satellite-based sea surface temperature (SST) research, Dr. Karagali has an extensive background in analyzing L4 products, mostly regional and high-resolution data, for validation with in-situ measurements, analysis of diurnal warming and climate trends. A crucial aspect of Dr. Karagali’s expertise lies in understanding of L4p roducts are generated from L2 and L3 data, as well as having interest in SST, IST, winds, oceanography, remote sensing, and ocean and atmopsheric modelling.

The strange case of the persisting Mediterranean heatwave

Salvatore Marullo, Italian National Agency for new Technologies, Energy and Sustainable Economic Development (ENEA). Diagnostics and Metrology Laboratory, Frascati (Italy)

Laurea in physics, University of Rome – La Sapienza. Sea going oceanographer, working on Ocean Color, SST and air-sea interaction. See https://scholar.google.com/citations?hl=en&user=p25mLRsAAAAJ for more information on publications.

Exceptional global sea surface temperatures associated with the 2023 and 2024 El Nino

Christopher Merchant, National Centre for Earth Observation and University

Christopher Merchant is a Professor of Ocean and Earth Observation at the University of Reading in the UK. He leads an active research group in thermal remote sensing of sea surface temperature, including leading the European Space Agency Climate Change Initiative project for sea surface temperature. Chris Merchant has a BA in Physics from Oxford University, and a PhD in Space and Climate Physics from University College London. His expertise and research interests are within Earth observation for climate science, including the theory and practice of climate data record creation.

Analysis of the Global Marine Heat waves based on CMA Ocean Data Analysis System for Sea Surface Temperature (CODAS-SST) Datasets

Zhihong Liao, National Meteorological Information Centre, China Meteorological  Administration

Posters

Covariation of long-term trends in surface water temperature and bio-optical indicators across the Great Lakes

Prasanjit Dash, NOAA/NESDIS/STAR/SOCD and Colorado State University/CIRA

Prasanjit Dash has 20+ years of experience in terrestrial infrared satellite applications. He has contributed to space-based projects across the USA, Europe, and India. Since 2006, Dash has been with NOAA/NESDIS and the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University (CSU). He also had an interim association with EUMETSAT from mid-2016 to end-2017. Dash holds a PhD in Physics from KIT (Germany, 2004), an MTech from IIT-Kanpur (India, 1999), and an MBA from CSU (USA, 2017). He is a CIRA Research Scientist III and the site area manager for the CIRA NESDIS Environmental Application Team.

https://www.linkedin.com/in/prasanjitdash/

https://www.star.nesdis.noaa.gov/star/Dash_P.php

A 42-year Sea Surface Temperature Climate Data Record from the ESA Climate Change Initiative

Owen Embury, University of Reading and National Centre for Earth Observation

Owen has worked on generating SST Climate Data Records (CDRs) for the ATSR Reprocessing for Climate and ESA Climate Change Initiative for SST projects.

The record-high sea surface temperature and marine heatwaves in 2023

Boyin Huang, NOAA NCEI

Boyin received an M.Sc degree from the Institute of Atmospheric Physics, Chinese Academy of Sciences, China. He later received a Ph.D. degree from the University of Wisconsin-Madison, USA. Dr. Huang's research interests include sea surface temperature analysis from in situ and satellite observations, global surface temperature (sea surface temperature in oceans and surface air temperature over continents) analysis, and climate change.

Verification of CMIP6 SST data against gridded observations over the ocean regions around Canada

Housseyni Sankare, ECCC

Inter-Comparisons of Long-term Global Trend of Sea Surface Temperatures for the Past Four Decades (1982-2021)

Kyung-Ae Park, Seoul National University

Kyung-Ae Park is a professor at the Department of Earth Science Education, Seoul National Univeristy in Korea. Her research activities are related to sea surface temperature (SST) variability, retrieval of SST and surface current from Korean geostationary satellites (COMS, GK-2A) and near-polar orbiting satellites, and oceanic applications of diverse satellite data.

Enhanced Driving Data for Regional Climate Models: Assessing the Systematic Improvements with GCM Run-time Empirical Bias Correction

Marie-Pier Labonté, Ouranos

Marie-Pier Labonté holds a PhD in Atmospheric and Oceanic Sciences from McGill University, where she studied the atmospheric water cycle using an idealized climate model. She is part of Ouranos, a consortium on regional climatology and adaptation to climate change. Her current research focuses on the impact of bias correction of regional climate model's driving data (e.g., SST) on regional climate.