Search Results

You are looking at 1 - 10 of 10 items for

  • Author or Editor: Matthew D. Palmer x
  • All content x
Clear All Modify Search
Matthew D. Palmer and Keith Haines

Abstract

This paper presents a new analysis of ocean heat content changes over the last 50 yr using isotherms by calculating the mean temperature above the 14°C isotherm and the depth of the 14°C isotherm as separate variables. A new quantity called the “relative heat content” (“RHC”) is introduced, which represents the minimum local heat content change over time, relative to a fixed isotherm. It is shown how mean temperature and isotherm depth changes make separable and additive contributions to changes in RHC.

Maps of RHC change between 1970 and 2000 show similar spatial patterns to a traditional fixed-depth ocean heat content change to 220 m. However, the separate contributions to RHC suggest a more spatially uniform contribution from warming above the isotherm, while isotherm depth changes show wind-driven signals, of which some are identifiable as being related to the North Atlantic Oscillation. The time series show that the warming contribution to RHC dominates the global trend, while the depth contribution only dominates on the basin scale in the North Atlantic. The RHC shows minima associated with the major volcanic eruptions (particularly in the Indian Ocean), and these are entirely contributed by mean temperature changes rather than isotherm depth changes. The depth change contributions to RHC are strongly affected by the recently reported XBT fall-rate bias, whereas the mean temperature contributions are not. Therefore, only the isotherm depth change contributions to RHC will need to be reassessed as fall-rate-corrected data become available.

Full access
Will Hobbs, Matthew D. Palmer, and Didier Monselesan

Abstract

Climate model simulations of changes to Earth’s energy budget are fundamental to improve understanding of both historical and future climate change. However, coupled models are prone to “drift” (i.e., they contain spurious unforced trends in state variables) due to incomplete spinup or nonclosure of the energy budget. This work assesses the globally integrated energy budgets of 25 models in phase 5 of CMIP (CMIP5). It is shown that for many of the models there is a significant disagreement between ocean heat content changes and net top-of-atmosphere radiation. The disagreement is largely time-constant and independent of forcing scenario. Furthermore, most of the nonconservation seems to occur as a result of energy leaks external to the ocean model realm. After drift correction, the time-varying energy budget is consistent at decadal time scales, and model responses to climate forcing are not sensitive to the magnitude of their drift. This demonstrates that, although drift terms can be significant, model output can be corrected post hoc without biasing results.

Full access
Matthew D. Palmer, Alberto C. Naveira Garabato, John D. Stark, Joël J-M. Hirschi, and Jochem Marotzke

Abstract

A regional general circulation model (GCM) of the Indian Ocean is used to investigate the influence of prescribed diapycnal diffusivity (Kd) on quasi-steady states of the meridional overturning circulation (MOC). The model has open boundaries at 35°S and 123°E where velocity, temperature, and salinity are prescribed at each time step. The results suggest that quasi-steady overturning states in the Indian Ocean are reached on centennial time scales. The size and structure of the MOC are controlled by the distribution of Kd and the southern boundary conditions. The distribution of Kd required to support an overturning circulation in the model interior of a magnitude equal to that prescribed at the southern boundary is estimated using a 1D advection–diffusion balance in isopycnal layers. Implementing this approach, 70%–90% of the prescribed deep inflow can be supported in quasi-steady state. Thus one is able to address the systematic discrepancy between past estimates of the deep MOC based on hydrographic sections and those based on GCM results. However, the Kd values required to support a substantial MOC in the model are much larger than current observation-based estimates, particularly for the upper 3000 m. The two estimates of the flow field near 32°S used to force the southern boundary imply a highly nonuniform distribution of Kd, as do recent estimates of Kd based on hydrographic observations. This work highlights the need to improve and implement realistic estimates of (nonuniform) Kd in ocean and coupled ocean–atmosphere GCMs when investigating quasi-equilibrium model states.

Full access
David J. Bodine, Matthew R. Kumjian, Robert D. Palmer, Pamela L. Heinselman, and Alexander V. Ryzhkov

Abstract

This study investigates the use of tornadic debris signature (TDS) parameters to estimate tornado damage severity using Norman, Oklahoma (KOUN), polarimetric radar data (polarimetric version of the Weather Surveillance Radar-1988 Doppler radar). Several TDS parameters are examined, including parameters based on the 10th or 90th percentiles of polarimetric variables (lowest tilt TDS parameters) and TDS parameters based on the TDS volumetric coverage (spatial TDS parameters). Two highly detailed National Weather Service (NWS) damage surveys are compared to TDS parameters. The TDS parameters tend to be correlated with the enhanced Fujita scale (EF) rating. The 90th percentile reflectivity, TDS height, and TDS volume increase during tornado intensification and decrease during tornado dissipation. For 14 tornado cases, the maximum or minimum TDS parameter values are compared to the tornado’s EF rating. For tornadoes with a higher EF rating, higher maximum values of the 90th percentile Z HH, TDS height, and volume, as well as lower minimum values of 10th percentile ρ HV and Z DR, are observed. Maxima in spatial TDS parameters are observed after periods of severe, widespread tornado damage for violent tornadoes. This paper discusses how forecasters could use TDS parameters to obtain near-real-time information about tornado damage severity and spatial extent.

Full access
Thomas P. Leahy, Francesc Pons Llopis, Matthew D. Palmer, and Niall H. Robinson

Abstract

Biases in expendable bathythermograph (XBT) instruments have emerged as a leading uncertainty in reconstructions of historical ocean heat content change and therefore climate change. Corrections for these biases depend on the type of XBT used; however, this is unspecified for 52% of the historical XBT profiles in the World Ocean Database. Here, we use profiles of known XBT type to train a neural network that can classify probe type based on three covariates: profile date, maximum recorded depth, and country of origin. Whereas previous studies have shown an average classification skill of 77%, falling below 50% for some periods, our new algorithm maintains an average skill of 90%, with a minimum of 70%. Our study illustrates the potential for successfully applying machine learning approaches in a wide variety of instrument classification problems in order to promote more homogeneous climate data records.

Full access
Jon Robson, Rowan Sutton, Katja Lohmann, Doug Smith, and Matthew D. Palmer

Abstract

In the mid-1990s, the subpolar gyre of the North Atlantic underwent a remarkable rapid warming, with sea surface temperatures increasing by around 1°C in just 2 yr. This rapid warming followed a prolonged positive phase of the North Atlantic Oscillation (NAO) but also coincided with an unusually negative NAO index in the winter of 1995/96. By comparing ocean analyses and carefully designed model experiments, it is shown that this rapid warming can be understood as a delayed response to the prolonged positive phase of the NAO and not simply an instantaneous response to the negative NAO index of 1995/96. Furthermore, it is inferred that the warming was partly caused by a surge and subsequent decline in the meridional overturning circulation and northward heat transport of the Atlantic Ocean. These results provide persuasive evidence of significant oceanic memory on multiannual time scales and are therefore encouraging for the prospects of developing skillful predictions.

Full access
Matthew D. Palmer, Tim Boyer, Rebecca Cowley, Shoichi Kizu, Franco Reseghetti, Toru Suzuki, and Ann Thresher

Abstract

Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key uncertainty in estimates of historical ocean heat content variability and change. One of the challenges in the development of XBT bias corrections is the lack of metadata in ocean profile databases. Approximately 50% of XBT profiles in the World Ocean database (WOD) have no information about manufacturer or probe type. Building on previous research efforts, this paper presents a deterministic algorithm for assigning missing XBT manufacturer and probe type for individual temperature profiles based on 1) the reporting country, 2) the maximum reported depth, and 3) the record date. The criteria used are based on bulk analysis of known XBT profiles in the WOD for the period 1966–2015. A basic skill assessment demonstrates a 77% success rate at correctly assigning manufacturer and probe type for profiles where this information is available. The skill rate is lowest during the early 1990s, which is also a period when metadata information is particularly poor. The results suggest that substantive improvements could be made through further data analysis and that future algorithms may benefit from including a larger number of predictor variables.

Open access
Blair Trewin, Anny Cazenave, Stephen Howell, Matthias Huss, Kirsten Isensee, Matthew D. Palmer, Oksana Tarasova, and Alex Vermeulen

Abstract

The World Meteorological Organization has developed a set of headline indicators for global climate monitoring. These seven indicators are a subset of the existing set of essential climate variables (ECVs) established by the Global Climate Observing System and are intended to provide the most essential parameters representing the state of the climate system. These indicators include global mean surface temperature, global ocean heat content, state of ocean acidification, glacier mass balance, Arctic and Antarctic sea ice extent, global CO2 mole fraction, and global mean sea level. This paper describes how well each of these indicators are currently monitored, including the number and quality of the underlying datasets; the health of those datasets; observation systems used to estimate each indicator; the timeliness of information; and how well recent values can be linked to preindustrial conditions. These aspects vary widely between indicators. While global mean surface temperature is available in close to real time and changes from preindustrial levels can be determined with relatively low uncertainty, this is not the case for many other indicators. Some indicators (e.g., sea ice extent) are largely dependent on satellite data only available in the last 40 years, while some (e.g., ocean acidification) have limited underlying observational bases, and others (e.g., glacial mass balance) with data only available a year or more in arrears.

Full access
Robert D. Palmer, David Bodine, Matthew Kumjian, Boonleng Cheong, Guifu Zhang, Qing Cao, Howard B. Bluestein, Alexander Ryzhkov, Tian-You Yu, and Yadong Wang

A tornado outbreak occurred in central Oklahoma on 10 May 2010, including two tornadoes with enhanced Fujita scale ratings of 4 (EF-4). Tragically, three deaths were reported along with significant property damage. Several strong and violent tornadoes occurred near Norman, Oklahoma, which is a major hub for severe storms research and is arguably one of the best observed regions of the country with multiple Doppler radars operated by both the federal government and the University of Oklahoma (OU). One of the most recent additions to the radars in Norman is the high-resolution OU Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME). As the name implies, the radar is used as a platform for research and education in both science and engineering studies using polarimetric radar. To facilitate usage of the system by students and faculty, OU-PRIME was constructed adjacent to the National Weather Center building on the OU research campus. On 10 May 2010, several tornadoes formed near the campus while OU researchers were operating OU-PRIME in a sector scanning mode, providing polarimetric radar data with unprecedented resolution and quality. In this article, the environmental conditions leading to the 10 May 2010 outbreak will be described, an overview of OU-PRIME will be provided, and several examples of the data and possible applications will be summarized. These examples will highlight supercell polarimetric signatures during and after tornadogenesis, and they will describe how the polarimetric signatures are related to observations of reflectivity and velocity.

Full access
Aimée B. A. Slangen, Benoit Meyssignac, Cecile Agosta, Nicolas Champollion, John A. Church, Xavier Fettweis, Stefan R. M. Ligtenberg, Ben Marzeion, Angelique Melet, Matthew D. Palmer, Kristin Richter, Christopher D. Roberts, and Giorgio Spada

Abstract

Sea level change is one of the major consequences of climate change and is projected to affect coastal communities around the world. Here, global mean sea level (GMSL) change estimated by 12 climate models from phase 5 of the World Climate Research Programme’s Climate Model Intercomparison Project (CMIP5) is compared to observational estimates for the period 1900–2015. Observed and simulated individual contributions to GMSL change (thermal expansion, glacier mass change, ice sheet mass change, landwater storage change) are analyzed and compared to observed GMSL change over the period 1900–2007 using tide gauge reconstructions, and over the period 1993–2015 using satellite altimetry estimates. The model-simulated contributions explain 50% ± 30% (uncertainties 1.65σ unless indicated otherwise) of the mean observed change from 1901–20 to 1988–2007. Based on attributable biases between observations and models, a number of corrections are proposed, which result in an improved explanation of 75% ± 38% of the observed change. For the satellite era (from 1993–97 to 2011–15) an improved budget closure of 102% ± 33% is found (105% ± 35% when including the proposed bias corrections). Simulated decadal trends increase over the twentieth century, both in the thermal expansion and the combined mass contributions (glaciers, ice sheets, and landwater storage). The mass components explain the majority of sea level rise over the twentieth century, but the thermal expansion has increasingly contributed to sea level rise, starting from 1910 onward and in 2015 accounting for 46% of the total simulated sea level change.

Full access