Mark P. McCarthy

Revisiting radiosonde upper air temperatures from 1958 to 2002

HadAT is a new analysis of the global upper air temperature record from 1958 to 2002 based upon radiosonde data alone. This analysis makes use of a greater number of stations than previous radiosonde analyses, combining a number of digital data sources. Neighbor buddy checks are applied to ensure that both spatial and temporal consistency are maintained. A framework of previously quality controlled stations is used to define the initial station network to minimize the effects of any pervasive biases in the raw data upon the adjustments. The analysis is subsequently expanded to consider all remaining available long-term records. The final data set consists of 676 radiosonde stations, with a bias toward continental Northern Hemisphere midlatitudes. Temperature anomaly time series are provided on 9 mandatory reporting pressure levels from 850 to 30 hPa. The effects of sampling and adjustment uncertainty are calculated at all scales from the station series to the global mean and from seasonal to multidecadal. These estimates are solely parametric uncertainty, given our methodological choices, and not structural uncertainty which relates to sensitivity to choice of approach. An initial analysis of HadAT does not fundamentally alter our understanding of long-term changes in upper air temperature changes.

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.

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.

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 temperature 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 quantifying 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 combination of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade 1 )i n 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 homogenization 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 radiosondes.

An Analysis of Tropospheric Humidity Trends from Radiosondes

Abstract A new analysis of historical radiosonde humidity observations is described. An assessment of both known and unknown instrument and observing practice changes has been conducted to assess their impact on bias and uncertainty in long-term trends. The processing of the data includes interpolation of data to address known sampling bias from missing dry day and cold temperature events, a first-guess adjustment for known radiosonde model changes, and a more sophisticated ensemble of estimates based on 100 neighbor-based homogenizations. At each stage the impact and uncertainty of the process has been quantified. The adjustments remove an apparent drying over Europe and parts of Asia and introduce greater consistency between temperature and specific humidity trends from day and night observations. Interannual variability and trends at the surface are shown to be in good agreement with independent in situ datasets, although some steplike discrepancies are apparent between the time series of relative humi...

Observed Interannual Variability of Tropical Troposphere Relative Humidity

Abstract Relative humidity fields from the High-Resolution Infrared Radiation Sounder (HIRS) flown on NOAA series satellites since 1979 have been used to study the seasonal aspects of the interannual variability of relative humidity in the tropical troposphere. The El Nino–Southern Oscillation (ENSO) is the only statistically identifiable physical mechanism of such variability. Boreal winter (December–February) relative humidity variations during an ENSO event follow patterns of anomalous convection and large-scale upper-level circulation. During El Nino (La Nina) regions of large negative (positive) relative humidity anomalies exist at subtropical latitudes over the Pacific Ocean. These are not always balanced by increases (decreases) in humidity near the equator. NCEP– NCAR reanalysis temperatures are used to separate observed changes in relative humidity into contributions from tropospheric temperature versus the contribution from changes in water vapor content. The authors find that at subtropical lat...

Climate Impact Assessments

This chapter highlights key climate impacts, hazards and vulnerabilities and associated indicators that have been used to assess current (recent) climate impacts at each of the case-study sites. The aim is to illustrate some of the wide range of information available from individual case studies and highlight common themes that are evident across multiple case-study locations. This is used to demonstrate linkages and sensitivities between the specific climate impacts of relevance for each case-study type (urban, rural and coastal) and the key climate hazards and biogeophysical and social vulnerabilities representing the underlying drivers and site conditions. For some impacts, there are clear, direct links with climate events, such as heat stress and flooding, while for others, such as energy supply and demand, the causal relationships are more indirect, via a cascade of climate, social and economic influences. Water availability and extreme temperatures are common drivers of current climate impacts across all case studies, including, for example, freshwater supply and heat stress for urban populations; irrigation capacity and growing season length for agricultural regions; and saltwater intrusion of aquifers and tourist visitor numbers at coastal locations. At some individual case-study locations, specific impacts, hazards and/or vulnerabilities are observed, such as peri-urban fires in Greater Athens, infrastructure vulnerability to coastal flooding in Alexandria, groundwater levels in Tel Hadya and vector-borne diseases in the Gulf of Oran. Throughout this chapter, evidence of current climate impacts, hazards and vulnerabilities from each of the case studies is detailed and assessed relative to other case studies. This provides a foundation for considering the wider perspective of the Mediterranean region as a whole, and for providing a context from which to assess consequences of future climate projections and consider suitable adaptation options.