ALBERT

Description: Biases in the depth estimation of expendable bathythermograph (XBT) measurements cause considerable errors in oceanic estimates of climate variables. Efforts are currently underway to improve XBT probes by including pressure switches. Information from these pressure measurements can be used to minimize errors in the XBT depth estimation. This paper presents a simple method to correct the XBT depth biases using a number of discrete pressure measurements. A blend of controlled simulations of XBT measurements and collocated XBT/CTD data is used along with statistical methods to estimate error parameters, and to optimize the use of pressure switches in terms of number of switches, optimal depth detection, and errors in the pressure switch measurements to most efficiently correct XBT profiles. The results show that given the typical XBT depth biases, using just two pressure switches is a reliable strategy for reducing depth errors, as it uses the least number of switches for an improved accuracy and reduces the variance of the resulting correction. Using only one pressure switch efficiently corrects XBT depth errors when the surface depth offset is small, its optimal location is at middepth (around or below 300 m), and the pressure switch measurement errors are insignificant. If two pressure switches are used, then results indicate that the measurements should be taken in the lower thermocline and deeper in the profile, at approximately 80 and 600 m, respectively, with an RMSE of approximately 1.6 m for pressure errors of 1 m.

Description: The authors examine recent changes in three agro-climate indices (frost days, thermal time, and heat stress index) in North America (centered around the continental United States) using observations from a historical climate network and an ensemble of 17 global climate models (GCMs) from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Agro-climate indices provide the basis for analyzing agricultural time series that are unbiased by long-term technological intervention. Observations from the last 60 years (1951–2010) confirm conclusions of previous studies showing continuing declines in the number of frost days and increases in thermal time. Increases in heat stress are largely confined to the western half of the continent. The authors do not observe accelerating agro-climate warming trends in the most recent decade of observations. The spatial variability of the temporal trends in GCMs is lower compared to the observed patterns, which still show some regional cooling trends. GCM skill, defined as the ability to reproduce observed patterns (i.e., correlation and error) and variability, is highest for frost days and lowest for heat stress patterns. Individual GCM skill is incorporated into two model weighting schemes to gauge their ability to reduce predictive uncertainty for agro-climate indices. The two weighted GCM ensembles do not substantially improve results compared to the unweighted ensemble mean. The lack of agreement between simulated and observed heat stress is relatively robust with respect to how the heuristic is defined and appears to reflect a weakness in the ability of this last generation of GCMs to reproduce this impact-relevant aspect of the climate system. However, it remains a question for future work as to whether the discrepancies between observed and simulated trends primarily reflect fundamental errors in model physics or an incomplete treatment of relevant regional climate forcings.

Description: A new anomaly coupling technique is introduced into a coarse-resolution dynamic climate model [the Liège Ocean Carbon Heteronomous model (LOCH)–Vegetation Continuous Description model (VECODE)–Earth System Models of Intermediate Complexity Climate deBilt (ECBILT)–Coupled Large-Scale Ice–Ocean model (CLIO)–Antarctic and Greenland Ice Sheet Model (AGISM) ensemble (LOVECLIM)], improving the model’s representation of eastern equatorial Pacific surface temperature variability. The anomaly coupling amplifies the surface diabatic atmospheric forcing within a Gaussian-shaped patch applied in the tropical Pacific Ocean. It is implemented with an improved predictive cloud scheme based on empirical relationships between cloud cover and key state variables. Results are presented from a perturbed physics ensemble systematically varying the parameters controlling the anomaly coupling patch size, location, and amplitude. The model’s optimal parameter combination is chosen through calibration against the observed power spectrum of monthly-mean surface temperature anomalies in the Niño-3 region. The calibrated model exhibits substantial improvement in equatorial Pacific interannual surface temperature variability and robustly reproduces El Niño–Southern Oscillation (ENSO)-like variability. The authors diagnose some of the key atmospheric and oceanic feedbacks in the model important for simulating ENSO-like variability, such as the positive Bjerknes feedback and the negative heat flux feedback, and analyze the recharge–discharge of the equatorial Pacific ocean heat content. They find LOVECLIM robustly captures important ocean dynamics related to thermocline adjustment and equatorial Kelvin waves. The calibrated model demonstrates some improvement in simulating atmospheric feedbacks, but the coupling between ocean and atmosphere is relatively weak. Because of the tractability of LOVECLIM and its consequent utility in exploring long-term climate variability and large ensemble perturbed physics experiments, improved representation of tropical Pacific ocean–atmosphere dynamics in the model may more readily allow for the investigation of the role of tropical Pacific ocean–atmosphere dynamics in past climate changes.