Evaluation of globally gridded SST products from NOAA, CMC and UKMeto using AIRS and CrIS SST measurements.

2020 ◽  
Author(s):  
Hartmut Aumann ◽  
Evan Manning ◽  
Chris Wilson ◽  
Jorge Vasquez
Keyword(s):  
Standard Deviation ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Atmospheric Infrared Sounder ◽  
Climate Research ◽  
The Difference ◽  
Grid Points ◽  
Mean Differences ◽  
The Uk

<p>The Sea Surface Temperature (SST) is a key component of climate research and daily globally gridded SST products are a key input to this effort.  Here we evaluate the NOAA RTGSST, which goes back to 1996, the Canada Meteorological Center (CMC) SST, available since 2002, and the OSTIA SST by the UK MetOffice, available since 2012. The calibration of the three products is tied to the moored and floating buoys along the equator, but there are differences in the way all grid points are optimally filled. The 2016 annual mean between 30S and 30N, 299.7K, differed by only 8 mK. However zonal mean differences between the three products north of 30N and south of 30S latitude are  of the order of 150 mK, and of opposite signs. Even more puzzling is that during 2016 the CMC was on average 150 mK colder than the OSTIA at 280K, while being warmer by 150mK at 290K. Differences of this magnitude are of concern when measure warming of the oceans at the rate of 15 mK/year. We use the daily mean and standard deviation and trends of the difference between the SST measured with AIRS (Atmospheric Infrared Sounder) since 2002 and CrIS (Crosstrack Interferometer Sounder) since 2012 to evaluate the three products.         </p>

scholarly journals Can an Earth System Model simulate better climate change at mid-Holocene than an AOGCM? A comparison study of MIROC-ESM and MIROC3

2013 ◽  
Vol 9 (4) ◽  
pp. 1519-1542 ◽  
Author(s):  
R. Ohgaito ◽  
T. Sueyoshi ◽  
A. Abe-Ouchi ◽  
T. Hajima ◽  
S. Watanabe ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Earth System Model ◽  
Sea Surface ◽  
System Model ◽  
Earth System ◽  
Intercomparison Project ◽  
The Difference ◽  
Precipitation Enhancement

Abstract. The importance of evaluating models through paleoclimate simulations is becoming more recognized in efforts to improve climate projection. To evaluate an integrated Earth System Model, MIROC-ESM, we performed simulations in time-slice experiments for the mid-Holocene (6000 yr before present, 6 ka) and preindustrial (1850 AD, 0 ka) periods under the protocol of the Coupled Model Intercomparison Project 5/Paleoclimate Modelling Intercomparison Project 3. We first give an overview of the simulated global climates by comparing with simulations using a previous version of the MIROC model (MIROC3), which is an atmosphere–ocean coupled general circulation model. We then comprehensively discuss various aspects of climate change with 6 ka forcing and how the differences in the models can affect the results. We also discuss the representation of the precipitation enhancement at 6 ka over northern Africa. The precipitation enhancement at 6 ka over northern Africa according to MIROC-ESM does not differ greatly from that obtained with MIROC3, which means that newly developed components such as dynamic vegetation and improvements in the atmospheric processes do not have significant impacts on the representation of the 6 ka monsoon change suggested by proxy records. Although there is no drastic difference between the African monsoon representations of the two models, there are small but significant differences in the precipitation enhancement over the Sahara in early summer, which can be related to the representation of the sea surface temperature rather than the vegetation coupling in MIROC-ESM. Because the oceanic parts of the two models are identical, the difference in the sea surface temperature change is ultimately attributed to the difference in the atmospheric and/or land modules, and possibly the difference in the representation of low-level clouds.

Validation of the AATSR Meteo Product Sea Surface Temperature

2006 ◽  
Vol 23 (5) ◽  
pp. 711-726 ◽  
Author(s):  
A. G. O'Carroll ◽  
J. G. Watts ◽  
L. A. Horrocks ◽  
R. W. Saunders ◽  
N. A. Rayner
Keyword(s):  
Standard Deviation ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
European Space Agency ◽  
Tropical Rainfall Measuring Mission ◽  
Daily Basis ◽  
Mean Difference ◽  
Sea Surface ◽  
Lower Latitude

Abstract The Advanced Along Track Scanning Radiometer (AATSR) Sea Surface Temperature (SST) Meteo product, a fast-delivery level-2 product at 10 arc min spatial resolution, has been available from the European Space Agency (ESA) since 19 August 2002. Validation has been performed on these data at the Met Office on a daily basis, with a 2-day lag from data receipt. Meteo product skin SSTs have been compared with point measurements of buoy SST, a 1° climate SST analysis field compiled from in situ measurements and Advanced Very High Resolution Radiometer (AVHRR) SSTs, and a 5° latitude–longitude 5-day averaged in situ dataset. Comparisons of the AATSR Meteo product against Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SSTs are also presented. These validation results have confirmed the AATSR Meteo product skin SST to be within ±0.3 K of in situ data. Comparisons of the AATSR skin SSTs against buoy SSTs, from 19 August 2002 to 20 August 2003, give a mean difference (AATSR – buoy) of 0.04 K (standard deviation = 0.28 K) during nighttime, and a mean difference of 0.02 K (standard deviation = 0.39 K) during the day. Analyses of the buoy matchups have shown that there is no cool skin effect observed in the nighttime observations, implying that the three-channel AATSR product skin SST may be 0.1–0.2 K too warm. Comparisons with TMI SSTs confirm that the lower-latitude SSTs are not significantly affected by residual cloud contamination.

scholarly journals The Effect of Diurnal Sea Surface Temperature Warming on Climatological Air–Sea Fluxes

2013 ◽  
Vol 26 (8) ◽  
pp. 2546-2556 ◽  
Author(s):  
Carol Anne Clayson ◽  
Alec S. Bogdanoff
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Heat Budget ◽  
Longwave Radiation ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Diurnal Variability ◽  
Diurnal Warming ◽  
Yearly Average ◽  
The Difference

Abstract Diurnal sea surface warming affects the fluxes of latent heat, sensible heat, and upwelling longwave radiation. Diurnal warming most typically reaches maximum values of 3°C, although very localized events may reach 7°–8°C. An analysis of multiple years of diurnal warming over the global ice-free oceans indicates that heat fluxes determined by using the predawn sea surface temperature can differ by more than 100% in localized regions over those in which the sea surface temperature is allowed to fluctuate on a diurnal basis. A comparison of flux climatologies produced by these two analyses demonstrates that significant portions of the tropical oceans experience differences on a yearly average of up to 10 W m−2. Regions with the highest climatological differences include the Arabian Sea and the Bay of Bengal, as well as the equatorial western and eastern Pacific Ocean, the Gulf of Mexico, and the western coasts of Central America and North Africa. Globally the difference is on average 4.45 W m−2. The difference in the evaporation rate globally is on the order of 4% of the total ocean–atmosphere evaporation. Although the instantaneous, year-to-year, and seasonal fluctuations in various locations can be substantial, the global average differs by less than 0.1 W m−2 throughout the entire 10-yr time period. A global heat budget that uses atmospheric datasets containing diurnal variability but a sea surface temperature that has removed this signal may be underestimating the flux to the atmosphere by a fairly constant value.

scholarly journals Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

2011 ◽  
Vol 28 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Ian J. Barton
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Clear Correlation ◽  
Transfer Model ◽  
The Difference

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

scholarly journals A large set of potential past, present and future hydro-meteorological time series for the UK

2018 ◽  
Vol 22 (1) ◽  
pp. 611-634 ◽  
Author(s):  
Benoit P. Guillod ◽  
Richard G. Jones ◽  
Simon J. Dadson ◽  
Gemma Coxon ◽  
Gianbattista Bussi ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Model ◽  
Sea Surface ◽  
Large Set ◽  
Future Scenarios ◽  
High Precipitation ◽  
The Uk

Abstract. Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900–2006), (ii) five near-future scenarios (2020–2049) and (iii) five far-future scenarios (2070–2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period (>3 months) and shorter-duration high precipitation (1–30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK.

scholarly journals Evaluating the Evidence of a Global Sea Surface Temperature Threshold for Tropical Cyclone Genesis

2017 ◽  
Vol 30 (22) ◽  
pp. 9133-9145 ◽  
Author(s):  
Cécile L. Defforge ◽  
Timothy M. Merlis
Keyword(s):  
Tropical Cyclone ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Tropical Cyclone Genesis ◽  
Temperature Threshold ◽  
Global Threshold ◽  
The Difference ◽  
Thermodynamic Variables ◽  
Cyclone Genesis

Recent studies have reaffirmed a global threshold sea surface temperature (SST) of 26°C for tropical cyclone (TC) genesis. However, it is well understood that other thermodynamic variables influence TC genesis and that high SST in isolation is not a sufficient criterion for genesis. Here, a basin-by-basin analysis of the SST distributions in the five most active ocean basins is performed, which shows that there is no global SST threshold for TC genesis. The distributions of genesis SST show substantial variations between basins. Furthermore, analysis of the conditional probability of genesis for a given TC season main development region SST suggests that the SST bounds for TC genesis are largely determined by the climatological bounds of the basin and that the SST values within this environmental range have similar probabilities of genesis. The distribution of relative SST (the difference between local and tropical mean) and tropical cyclone potential intensity at TC genesis are more distinct from those of the TC season environment, consistent with their utility in TC genesis indices.

scholarly journals Three-Way Error Analysis between AATSR, AMSR-E, and In Situ Sea Surface Temperature Observations

2008 ◽  
Vol 25 (7) ◽  
pp. 1197-1207 ◽  
Author(s):  
Anne G. O’Carroll ◽  
John R. Eyre ◽  
Roger W. Saunders
Keyword(s):  
Standard Deviation ◽  
Error Analysis ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Data Sources ◽  
Independent Data ◽  
Earth Observing System ◽  
Along Track

Abstract Using collocations of three different observation types of sea surface temperatures (SSTs) gives enough information to enable the standard deviation of error on each observation type to be derived. SSTs derived from the Advanced Along-Track Scanning Radiometer (AATSR) and Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; AMSR-E) instruments are used, along with SST observations from buoys. Various assumptions are made within the error theory, including that the errors are not correlated, which should be the case for three independent data sources. An attempt is made to show that this assumption is valid and that the covariances between the different observations because of representativity error are negligible. Overall, the spatially averaged nighttime AATSR dual-view three-channel bulk SST observations for 2003 are shown to have a very small standard deviation of error of 0.16 K, whereas the buoy SSTs have an error of 0.23 K and the AMSR-E SST observations have an error of 0.42 K.

scholarly journals ANALISIS PENGGUNAAN PERSAMAAN MULTICHANNEL SEA SURFACE TEMPERATUR (MCSTT) SPLIT-WINDOW PADA SENSOR SATELIT NOAA-AVHRR UNTUK DETEKSI TEMPERATUR PERMUKAAN AIR LAUT

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Agung Mulyo Widodo ◽  
Nizirwan Anwar
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Normal Distribution ◽  
Great Influence ◽  
Weather Conditions ◽  
Sea Surface ◽  
Noaa Avhrr ◽  
Sensing Technology ◽  
Kolmogorov Smirnov ◽  
The Difference

<em> Sea surface temperatures have a great influence on weather conditions and terrestrial climates. The phenomena that occur in the oceans such as La Nina and El Nino also have a great impact on the changing world weather. For that required data of sea surface temperature up to date. The remote sensing technology can be used to monitor up-to-date seawater temperatures using NOAA's AVHRR-rated NOAA radios that have three thermal infrared channels, namely channel 3 (3.33-3.93μm), channel 4 (10.3 -11,3μm), and channel 5 (11,5 - 12μm) and by using Split-Window Multichannel Sea Surface Temperature (MCSTT) to calculate sea surface temperature. In this research will be an analysis of the accuracy of the use of these equations for tropical perariran in Indonesia. Field verification performed on the coast in Tuban region with geographical coordinates (6.83099<sup>o</sup>- 6.76149<sup>o</sup> SL and 112,029<sup>o</sup>-112,101<sup>o</sup>EL) by measuring the temperature at 30 points for comparison. The results of these measurements are then tested statistics Kolmogorov-Smirnov test and the results of temperature data obtained from the calculation and measurement of both normal distribution then because the normal distribution is done t test with 95% confidence level to compare between the temperature obtained from the calculation by using the value gray pixels with temperature measurements in the field turned out the average population is not the same or different significantly and the difference between the temperature shown image with temperature measurement results of 0.9886 <sup>o</sup>C</em>

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