Search Results

You are looking at 1 - 8 of 8 items for

  • Author or Editor: N. A. Rayner x
  • All content x
Clear All Modify Search
A. G. O'Carroll, J. G. Watts, L. A. Horrocks, R. W. Saunders, and N. A. Rayner

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.

Full access
C. K. Folland, M. J. Salinger, N. Jiang, and N. A. Rayner

Abstract

An analysis of temperature variability and trends in the South Pacific, mainly in the twentieth century, using data from 40 island stations and optimally interpolated sea surface and night marine air temperature data is presented. The last-named dataset is new and contains improved corrections for changes in the height of thermometer screens as ships have become larger. It is shown that the South Pacific convergence zone plays a pivotal role in both variability and trends in all three datasets. Island, collocated sea surface temperature, and night marine air temperature time series for four large constituent regions are created and analyzed. These have been corrected for artificial changes in variance due to changes in the availability of constituent island stations whose intrinsic variance varies from station to station. The method is described in detail. Objective estimates of uncertainty in the sea surface temperature data are also provided. The results extend previous work, showing that annual and seasonal surface ocean and island air temperatures have increased throughout the South Pacific. Variations in trends in the island and marine data show reasonable consistency, with distinctly different patterns of multidecadal change in the four regions. However, a notable inconsistency is the recent lack of warming in night marine air temperature in one of the tropical regions relative to sea surface temperature, with signs of this effect in a second tropical region. Another tropical region near the South Pacific convergence zone shows recent strong warming in the island data but not in the marine data.

Full access
J. M. Gregory, R. J. Stouffer, S. C. B. Raper, P. A. Stott, and N. A. Rayner

Abstract

A probability distribution for values of the effective climate sensitivity, with a lower bound of 1.6 K (5th percentile), is obtained on the basis of the increase in ocean heat content in recent decades from analyses of observed interior-ocean temperature changes, surface temperature changes measured since 1860, and estimates of anthropogenic and natural radiative forcing of the climate system. Radiative forcing is the greatest source of uncertainty in the calculation; the result also depends somewhat on the rate of ocean heat uptake in the late nineteenth century, for which an assumption is needed as there is no observational estimate. Because the method does not use the climate sensitivity simulated by a general circulation model, it provides an independent observationally based constraint on this important parameter of the climate system.

Full access
N. A. Rayner, P. Brohan, D. E. Parker, C. K. Folland, J. J. Kennedy, M. Vanicek, T. J. Ansell, and S. F. B. Tett

Abstract

A new flexible gridded dataset of sea surface temperature (SST) since 1850 is presented and its uncertainties are quantified. This analysis [the Second Hadley Centre Sea Surface Temperature dataset (HadSST2)] is based on data contained within the recently created International Comprehensive Ocean–Atmosphere Data Set (ICOADS) database and so is superior in geographical coverage to previous datasets and has smaller uncertainties. Issues arising when analyzing a database of observations measured from very different platforms and drawn from many different countries with different measurement practices are introduced. Improved bias corrections are applied to the data to account for changes in measurement conditions through time. A detailed analysis of uncertainties in these corrections is included by exploring assumptions made in their construction and producing multiple versions using a Monte Carlo method. An assessment of total uncertainty in each gridded average is obtained by combining these bias-correction-related uncertainties with those arising from measurement errors and undersampling of intragrid box variability. These are calculated by partitioning the variance in grid box averages between real and spurious variability. From month to month in individual grid boxes, sampling uncertainties tend to be most important (except in certain regions), but on large-scale averages bias-correction uncertainties are more dominant owing to their correlation between grid boxes. Changes in large-scale SST through time are assessed by two methods. The linear warming between 1850 and 2004 was 0.52° ± 0.19°C (95% confidence interval) for the globe, 0.59° ± 0.20°C for the Northern Hemisphere, and 0.46° ± 0.29°C for the Southern Hemisphere. Decadally filtered differences for these regions over this period were 0.67° ± 0.04°C, 0.71° ± 0.06°C, and 0.64° ± 0.07°C.

Full access
C. Donlon, I. Robinson, K. S. Casey, J. Vazquez-Cuervo, E. Armstrong, O. Arino, C. Gentemann, D. May, P. LeBorgne, J. Piollé, I. Barton, H. Beggs, D. J. S. Poulter, C. J. Merchant, A. Bingham, S. Heinz, A. Harris, G. Wick, B. Emery, P. Minnett, R. Evans, D. Llewellyn-Jones, C. Mutlow, R. W. Reynolds, H. Kawamura, and N. Rayner

A new generation of integrated sea surface temperature (SST) data products are being provided by the Global Ocean Data Assimilation Experiment (GODAE) High-Resolution SST Pilot Project (GHRSST-PP). These combine in near-real time various SST data products from several different satellite sensors and in situ observations and maintain the fine spatial and temporal resolution needed by SST inputs to operational models. The practical realization of such an approach is complicated by the characteristic differences that exist between measurements of SST obtained from subsurface in-water sensors, and satellite microwave and satellite infrared radiometer systems. Furthermore, diurnal variability of SST within a 24-h period, manifested as both warm-layer and cool-skin deviations, introduces additional uncertainty for direct intercomparison between data sources and the implementation of data-merging strategies. The GHRSST-PP has developed and now operates an internationally distributed system that provides operational feeds of regional and global coverage high-resolution SST data products (better than 10 km and ~6 h). A suite of online satellite SST diagnostic systems are also available within the project. All GHRSST-PP products have a standard format, include uncertainty estimates for each measurement, and are served to the international user community free of charge through a variety of data transport mechanisms and access points. They are being used for a number of operational applications. The approach will also be extended back to 1981 by a dedicated reanalysis project. This paper provides a summary overview of the GHRSST-PP structure, activities, and data products. For a complete discussion, and access to data products and services see the information online at www.ghrsst-pp.org.

Full access
P. Friedlingstein, P. Cox, R. Betts, L. Bopp, W. von Bloh, V. Brovkin, P. Cadule, S. Doney, M. Eby, I. Fung, G. Bala, J. John, C. Jones, F. Joos, T. Kato, M. Kawamiya, W. Knorr, K. Lindsay, H. D. Matthews, T. Raddatz, P. Rayner, C. Reick, E. Roeckner, K.-G. Schnitzler, R. Schnur, K. Strassmann, A. J. Weaver, C. Yoshikawa, and N. Zeng

Abstract

Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C.

All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.

Full access
T. J. Ansell, P. D. Jones, R. J. Allan, D. Lister, D. E. Parker, M. Brunet, A. Moberg, J. Jacobeit, P. Brohan, N. A. Rayner, E. Aguilar, H. Alexandersson, M. Barriendos, T. Brandsma, N. J. Cox, P. M. Della-Marta, A. Drebs, D. Founda, F. Gerstengarbe, K. Hickey, T. Jónsson, J. Luterbacher, Ø. Nordli, H. Oesterle, M. Petrakis, A. Philipp, M. J. Rodwell, O. Saladie, J. Sigro, V. Slonosky, L. Srnec, V. Swail, A. M. García-Suárez, H. Tuomenvirta, X. Wang, H. Wanner, P. Werner, D. Wheeler, and E. Xoplaki

Abstract

The development of a daily historical European–North Atlantic mean sea level pressure dataset (EMSLP) for 1850–2003 on a 5° latitude by longitude grid is described. This product was produced using 86 continental and island stations distributed over the region 25°–70°N, 70°W–50°E blended with marine data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The EMSLP fields for 1850–80 are based purely on the land station data and ship observations. From 1881, the blended land and marine fields are combined with already available daily Northern Hemisphere fields. Complete coverage is obtained by employing reduced space optimal interpolation. Squared correlations (r2) indicate that EMSLP generally captures 80%–90% of daily variability represented in an existing historical mean sea level pressure product and over 90% in modern 40-yr European Centre for Medium-Range Weather Forecasts Re-Analyses (ERA-40) over most of the region. A lack of sufficient observations over Greenland and the Middle East, however, has resulted in poorer reconstructions there. Error estimates, produced as part of the reconstruction technique, flag these as regions of low confidence. It is shown that the EMSLP daily fields and associated error estimates provide a unique opportunity to examine the circulation patterns associated with extreme events across the European–North Atlantic region, such as the 2003 heat wave, in the context of historical events.

Full access
P. W. Thorne, R. J. Allan, L. Ashcroft, P. Brohan, R. J. H Dunn, M. J. Menne, P. R. Pearce, J. Picas, K. M. Willett, M. Benoy, S. Bronnimann, P. O. Canziani, J. Coll, R. Crouthamel, G. P. Compo, D. Cuppett, M. Curley, C. Duffy, I. Gillespie, J. Guijarro, S. Jourdain, E. C. Kent, H. Kubota, T. P. Legg, Q. Li, J. Matsumoto, C. Murphy, N. A. Rayner, J. J. Rennie, E. Rustemeier, L. C. Slivinski, V. Slonosky, A. Squintu, B. Tinz, M. A. Valente, S. Walsh, X. L. Wang, N. Westcott, K. Wood, S. D. Woodruff, and S. J. Worley

Abstract

Observations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional, and national holdings for different variables and time scales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across essential climate variables (ECVs) and across time scales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multitiered user support. The present paper provides a high-level overview, based upon broad community input, of the steps that are required to bring about this integration. The significant challenge is to find a sustained means to realize this vision. This requires a long-term international program. The database that results will transform our collective ability to provide societally relevant research, analysis, and predictions in many weather- and climate-related application areas across much of the globe.

Open access