Quantifying global trends and variability in sea surface temperature (SST) is of fundamental importance to understanding changes in the Earth's climate. One approach to observing SST is via remote ...sensing. Here we use a 37-year gap-filled, daily-mean analysis of satellite SSTs to quantify SST trends, variability and persistence between 1981-2018. The global mean warming trend is 0.09 K per decade globally, with 95% of local trends being between -0.1 K and + 0.35 K. Excluding perennial sea-ice regions, the mean warming trend is 0.11 K per decade. After removing the long-term trend we calculate the SST power spectra over different time periods. The maximum variance in the SST power spectra in the equatorial Pacific is 1.9 K
on 1-5 year timescales, dominated by ENSO processes. In western boundary currents characterised by an intense mesoscale activity, SST power on sub-annual timescales dominates, with a maximum variance of 4.9 K
. Persistence timescales tend to be shorter in the summer hemisphere due to the shallower mixed layer. The median short-term persistence length is 11-14 days, found over 71-79% of the global ocean area, with seasonal variations. The mean global correlation between monthly SST anomalies with a three-month time-lag is 0.35, with statistically significant correlations over 54.0% of the global oceans, and notably in the northern and equatorial Pacific, and the sub-polar gyre south of Greenland. At six months, the mean global SST anomaly correlation falls to 0.18. The satellite data record enables the detailed characterisation of temporal changes in SST over almost four decades.
Summer lake surface water temperatures (LSWTs) have previously been shown to respond more rapidly to climatic warming compared to local summer surface air temperatures (SATs). In a global-scale ...analysis, we explore the factors underpinning the observation of an amplified response of summer LSWT to SAT variability using 20 years of satellite-derived temperatures from 144 lakes. We demonstrate that the degree of amplification in inter-annual summer LSWT is variable, and is greater for cold lakes (e.g. high latitude and high altitude), which are characterised by a short warming season, and deep lakes, that exhibit long correlation timescales of temperature anomalies due to increased thermal inertia. Such lakes are more likely to display responses in excess of local inter-annual summer SAT variability. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems, so quantifying this amplified response at a global scale is important.
Lake surface water temperatures (LSWTs) are sensitive to climate change, but previous studies have typically focused on temperatures from only the last few decades. Thus, while there is good ...appreciation of LSWT warming in recent decades, our understanding of longer-term temperature change is comparatively limited. In this study, we use a mechanistically based open-source model (
air2water
), driven by air temperature from a state-of-the-art global atmospheric reanalysis (ERA-20C) and calibrated with satellite-derived LSWT observations (ARC-Lake v3), to investigate the long-term change in LSWT worldwide. The predictive ability of the model is tested across 606 lakes, with 91% of the lakes showing a daily root mean square error smaller than 1.5 °C. Model performance was better at mid-latitudes and decreased towards the equator. The results illustrated highly variable mean annual LSWT trends during the twentieth century and across climatic regions. Substantial warming is evident after ~ 1980 and the most responsive lakes to climate change are located in the temperate regions.
Water temperature is critical for the ecology of lakes. However, the ability to predict its spatial and seasonal variation is constrained by the lack of a thermal classification system. Here we ...define lake thermal regions using objective analysis of seasonal surface temperature dynamics from satellite observations. Nine lake thermal regions are identified that mapped robustly and largely contiguously globally, even for small lakes. The regions differed from other global patterns, and so provide unique information. Using a lake model forced by 21
century climate projections, we found that 12%, 27% and 66% of lakes will change to a lower latitude thermal region by 2080-2099 for low, medium and high greenhouse gas concentration trajectories (Representative Concentration Pathways 2.6, 6.0 and 8.5) respectively. Under the worst-case scenario, a 79% reduction in the number of lakes in the northernmost thermal region is projected. This thermal region framework can facilitate the global scaling of lake-research.
Lake surface water temperature (LSWT) measurements from various sources illustrate that lakes are warming in response to climate change. Most previous studies of geographical distributions of lake ...warming have tended to utilize data with limited spatial resolution of LSWTs, including single‐point time series. Spatially resolved LSWT time series are now available from satellite observations, and some studies have investigated previously the intralake warming patterns in specific lakes (e.g., North American Great Lakes). However, across‐lake comparisons of intralake warming differences have not yet been investigated at a large, across‐continental scale, thus limiting our understanding of how intralake warming patterns differ more broadly. In this study, we analyze up to 20 years of satellite data from 19 lakes situated across the Northern Hemisphere, to investigate how LSWT changes vary across different lake surfaces. We find considerable intralake variability in warming trends across many lakes. The deepest areas of large lakes are characterized by a later onset of thermal stratification, a shorter stratified warming season and exhibit longer correlation timescales of LSWT anomalies. We show that deep areas of large lakes across the Northern Hemisphere as a result tend to display higher rates of warming of summer LSWT, arising from a greater temporal persistence in deep areas of the temperature anomalies associated with an earlier onset of thermal stratification. Utilization of single‐point LSWT trends to represent changes in large lakes therefore suppresses important aspects of lake responses to climate change, whereas spatially resolved LSWT measurements can be exploited to provide more comprehensive understanding.
Key Points
Large lakes experience considerable intralake heterogeneity of thermal responses to climate change
The deep areas of large lakes tend to display higher rates of summer temperature warming
Single‐point lake temperature trends suppress important aspects of lake responses to climate change
Atmospheric desert-dust aerosol, primarily from north Africa, causes negative biases in remotely sensed climate data records of sea surface temperature (SST). Here, large-scale bias adjustments are ...deduced and applied to the v2 climate data record of SST from the European Space Agency Climate Change Initiative (CCI). Unlike SST from infrared sensors, SST measured in situ is not prone to desert-dust bias. An in-situ-based SST analysis is combined with column dust mass from the Modern-Era Retrospective analysis for Research and Applications, Version 2 to deduce a monthly, large-scale adjustment to CCI analysis SSTs. Having reduced the dust-related biases, a further correction for some periods of anomalous satellite calibration is also derived. The corrections will increase the usability of the v2 CCI SST record for oceanographic and climate applications, such as understanding the role of Arabian Sea SSTs in the Indian monsoon. The corrections will also pave the way for a v3 climate data record with improved error characteristics with respect to atmospheric dust aerosol.
A climate data record of global sea surface temperature (SST) spanning 1981-2016 has been developed from 4 × 10
satellite measurements of thermal infra-red radiance. The spatial area represented by ...pixel SST estimates is between 1 km
and 45 km
. The mean density of good-quality observations is 13 km
yr
. SST uncertainty is evaluated per datum, the median uncertainty for pixel SSTs being 0.18 K. Multi-annual observational stability relative to drifting buoy measurements is within 0.003 K yr
of zero with high confidence, despite maximal independence from in situ SSTs over the latter two decades of the record. Data are provided at native resolution, gridded at 0.05° latitude-longitude resolution (individual sensors), and aggregated and gap-filled on a daily 0.05° grid. Skin SSTs, depth-adjusted SSTs de-aliased with respect to the diurnal cycle, and SST anomalies are provided. Target applications of the dataset include: climate and ocean model evaluation; quantification of marine change and variability (including marine heatwaves); climate and ocean-atmosphere processes; and specific applications in ocean ecology, oceanography and geophysics.
Lake surface water temperatures (LSWTs) are sensitive to atmospheric warming and have previously been shown to respond to regional changes in the climate. Using a combination of in situ and simulated ...surface temperatures from 20 Central European lakes, with data spanning between 50 and ∼100 years, we investigate the long-term increase in annually averaged LSWT. We demonstrate that Central European lakes are warming most in spring and experience a seasonal variation in LSWT trends. We calculate significant LSWT warming during the past few decades and illustrate, using a sequential
t
test analysis of regime shifts, a substantial increase in annually averaged LSWT during the late 1980s, in response to an abrupt shift in the climate. Surface air temperature measurements from 122 meteorological stations situated throughout Central Europe demonstrate similar increases at this time. Climatic modification of LSWT has numerous consequences for water quality and lake ecosystems. Quantifying the response of LSWT increase to large-scale and abrupt climatic shifts is essential to understand how lakes will respond in the future.
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