Assessing bias and uncertainty in the HadAT-adjusted radiosonde climate record

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from tem-perature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quan-tifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combi-nation of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homog-enization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radio-sondes. 1

Critically Reassessing Tropospheric Temperature Trends from Radiosondes Using Realistic Validation Experiments

Biases and uncertainties in large-scale radiosonde temperature trends in the troposphere are critically reassessed. Realistic validation experiments are performed on an automatic radiosonde homogenization system by applying it to climate model data with four distinct sets of simulated breakpoint profiles. Knowledge of the “truth” permits a critical assessment of the ability of the system to recover the large-scale trends and a reinterpretation of the results when applied to the real observations. The homogenization system consistently reduces the bias in the daytime tropical, global, and Northern Hemisphere (NH) extratropical trends but underestimates the full magnitude of the bias. Southern Hemisphere (SH) extratropical and all nighttime trends were less well adjusted owing to the sparsity of stations. The ability to recover the trends is dependent on the underlying error structure, and the true trend does not necessarily lie within the range of estimates. The implications are that tropical tropospheric trends in the unadjusted daytime radiosonde observations, and in many current upper-air datasets, are biased cold, but the degree of this bias cannot be robustly quantified. Therefore, remaining biases in the radiosonde temperature record may account for the apparent tropical lapse rate discrepancy between radiosonde data and climate models. Furthermore, the authors find that the unadjusted global and NH extratropical tropospheric trends are biased cold in the daytime radiosonde observations. Finally, observing system experiments show that, if the Global Climate Observing System (GCOS) Upper Air Network (GUAN) were to make climate quality observations adhering to the GCOS monitoring principles, then one would be able to constrain the uncertainties in trends at a more comprehensive set of stations. This reaffirms the importance of running GUAN under the GCOS monitoring principles

Search for Dark Matter Annihilation in the Galactic Center with IceCube-79

The Milky Way is expected to be embedded in a halo of dark matter particles, with the highest density in the central region, and decreasing density with the halo-centric radius. Dark matter might be indirectly detectable at Earth through a flux of stable particles generated in dark matter annihilations and peaked in the direction of the Galactic Center. We present a search for an excess flux of muon (anti-) neutrinos from dark matter annihilation in the Galactic Center using the cubic-kilometer-sized IceCube neutrino detector at the South Pole. There, the Galactic Center is always seen above the horizon. Thus, new and dedicated veto techniques against atmospheric muons are required to make the southern hemisphere accessible for IceCube. We used 319.7 live-days of data from IceCube operating in its 79-string configuration during 2010 and 2011. No neutrino excess was found and the final result is compatible with the background. We present upper limits on the self-annihilation cross-section, \left, for WIMP masses ranging from 30 GeV up to 10 TeV, assuming cuspy (NFW) and flat-cored (Burkert) dark matter halo profiles, reaching down to $\simeq 4 \cdot 10^{-24}$ cm$^3$ s$^{-1}$, and $\simeq 2.6 \cdot 10^{-23}$ cm$^3$ s$^{-1}$ for the $\nu\overline{\nu}$ channel, respectively.Comment: 14 pages, 9 figures, Submitted to EPJ-C, added references, extended limit overvie

Heterogeneity of scaling of the observed global temperature data

We investigated the scaling properties of two datasets of the observed near-surface global temperature data anomalies: the Met Office and the University of East Anglia Climatic Research Unit HadCRUT4 dataset and the NASA GISS Land-Ocean Temperature Index (LOTI) dataset. We used detrended fluctuation analysis of second-order (DFA2) and wavelet-based spectral (WTS) analysis to investigate and quantify the global pattern of scaling in two datasets and to better understand cyclic behavior as a possible underlying cause of the observed forms of scaling. We found that, excluding polar and parts of subpolar regions because of their substantial data inhomogeneity, the global temperature pattern is long-range autocorrelated. Our results show a remarkable heterogeneity in the long-range dynamics of the global temperature anomalies in both datasets. This finding is in agreement with previous studies. We additionally studied the DFA2 and the WTS behavior of the local station temperature anomalies and satellite-based temperature estimates and found that the observed diversity of global scaling can be attributed both to the intrinsic variability of data and to the methodology-induced variations that arise from deriving the global temperature gridded data from the original local sources. Finally, we found differences in global temperature scaling patterns of the two datasets and showed instances where spurious scaling is introduced in the global datasets through a spatial infilling procedure or the optimization of integrated satellite records

A quantification of uncertainties in historical tropical tropospheric temperature trends from radiosondes

The consistency of tropical tropospheric temperature trends with climate model expectations remains contentious. A key limitation is that the uncertainties in observations from radiosondes are both substantial and poorly constrained. We present a thorough uncertainty analysis of radiosonde‐based temperature records. This uses an automated homogenization procedure and a previously developed set of complex error models where the answer is known a priori. We perform a number of homogenization experiments in which error models are used to provide uncertainty estimates of real‐world trends. These estimates are relatively insensitive to a variety of processing choices. Over 1979–2003, the satellite‐equivalent tropical lower tropospheric temperature trend has likely (5–95% confidence range) been between −0.01 K/decade and 0.19 K/decade (0.05–0.23 K/decade over 1958–2003) with a best estimate of 0.08 K/decade (0.14 K/decade). This range includes both available satellite data sets and estimates from models (based upon scaling their tropical amplification behavior by observed surface trends). On an individual pressure level basis, agreement between models, theory, and observations within the troposphere is uncertain over 1979 to 2003 and nonexistent above 300 hPa. Analysis of 1958–2003, however, shows consistent model‐data agreement in tropical lapse rate trends at all levels up to the tropical tropopause, so the disagreement in the more recent period is not necessarily evidence of a general problem in simulating long‐term global warming. Other possible reasons for the discrepancy since 1979 are: observational errors beyond those accounted for here, end‐point effects, inadequate decadal variability in model lapse rates, or neglected climate forcings