Tag Archives: Climate Models

‘Climate science’ in its current state is not self-correcting

“Many problems plagued climatology since climate science took over in the 1980s. Each specialist in a different area suddenly became an expert in climate and climate change. They brought their different perspectives, sometimes helpful, but usually unhelpful and even distorting. Most came for funding opportunities, but many for the political objectives. They all lack awareness that climatology is a generalist discipline. It involves putting together, in a systems approach manner, all the studies from specialists who, because they get involved in climate studies, call themselves climate scientists. This piecemeal approach reflects the problems of creating computer climate models. Modellers assemble as many facts as they think apply, or will achieve their result and then, with improper or inadequate connecting mechanisms, put together what they think represents global climate.” click here

Paris agreement is not based on the best available science

Antero Ollila. Challenging the scientific basis of the Paris climate agreement. International Journal of Climate Change Strategies and Management. https://doi.org/10.1108/IJCCSM-05-2017-0107

The purpose of this paper is to analyze the scientific basis of the Paris climate agreement.

The analyses are based on the IPCC’s own reports, the observed temperatures versus the IPCC model-calculated temperatures and the warming effects of greenhouse gases based on the critical studies of climate sensitivity (CS).

The future emission and temperature trends are calculated according to a baseline scenario by the IPCC, which is the worst-case scenario RCP8.5. The selection of RCP8.5 can be criticized because the present CO2 growth rate 2.2 ppmy−1 should be 2.8 times greater, meaning a CO2 increase from 402 to 936 ppm. The emission target scenario of COP21 is 40 GtCO2equivalent, and the results of this study confirm that the temperature increase stays below 2°C by 2100 per the IPCC calculations. The IPCC-calculated temperature for 2016 is 1.27°C, 49 per cent higher than the observed average of 0.85°C in 2000.

Two explanations have been identified for this significant difference in the IPCC’s calculations: The model is too sensitive for CO2 increase, and the positive water feedback does not exist. The CS of 0.6°C found in some critical research studies means that the temperature increase would stay below the 2°C target, even though the emissions would follow the baseline scenario. This is highly unlikely because the estimated conventional oil and gas reserves would be exhausted around the 2060s if the present consumption rate continues.

Global models underestimate decadal water storage trends

Bridget R. Scanlon, Zizhan Zhang, Himanshu Save, Alexander Y. Sun, Hannes Müller Schmied, Ludovicus P. H. van Beek, David N. Wiese, Yoshihide Wada, Di Long, Robert C. Reedy, Laurent Longuevergne, Petra Döll, and Marc F. P. Bierkens. Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data. PNAS January 22, 2018. 201704665; https://doi.org/10.1073/pnas.1704665115.

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated.

Observed warming a factor of two less than model projections

John R. Christy, Roy W. Spencer, William D. Braswell & Robert Junod. Examination of space-based bulk atmospheric temperatures used in climate research. International Journal of Remote Sensing
Volume 39, 2018 – Issue 11

The Intergovernmental Panel on Climate Change Assessment Report 5 (IPCC AR5, 2013) discussed bulk atmospheric temperatures as indicators of climate variability and change. We examine four satellite datasets producing bulk tropospheric temperatures, based on microwave sounding units (MSUs), all updated since IPCC AR5. All datasets produce high correlations of anomalies versus independent observations from radiosondes (balloons), but differ somewhat in the metric of most interest, the linear trend beginning in 1979. The trend is an indicator of the response of the climate system to rising greenhouse gas concentrations and other forcings, and so is critical to understanding the climate. The satellite results indicate a range of near-global (+0.07 to +0.13°C decade−1) and tropical (+0.08 to +0.17°C decade−1) trends (1979–2016), and suggestions are presented to account for these differences. We show evidence that MSUs on National Oceanic and Atmospheric Administration’s satellites (NOAA-12 and −14, 1990–2001+) contain spurious warming, especially noticeable in three of the four satellite datasets.

Comparisons with radiosonde datasets independently adjusted for inhomogeneities and Reanalyses suggest the actual tropical (20°S-20°N) trend is +0.10 ± 0.03°C decade−1. This tropical result is over a factor of two less than the trend projected from the average of the IPCC climate model simulations for this same period (+0.27°C decade−1).

Climate models are theoretical; Underlying mechanisms are poorly understood

Matthew Collins, Shoshiro Minobe, Marcelo Barreiro, Simona Bordoni,
Yohai Kaspi, Akira Kuwano-Yoshida, Noel Keenlyside, Elisa Manzini, Christopher H. O’Reilly, Rowan Sutton, Shang-Ping Xie, Olga Zolina. Challenges and opportunities for improved understanding of regional climate dynamics. Nature Climate Change, volume 8, pages 101–108 (2018).

Dynamical processes in the atmosphere and ocean are central to determining the large-scale drivers of regional climate change, yet their predictive understanding is poor. Here, we identify three frontline challenges in climate dynamics where significant progress can be made to inform adaptation: response of storms, blocks and jet streams to external forcing; basin-to-basin and tropical–extratropical teleconnections; and the development of non-linear predictive theory. We highlight opportunities and techniques for making immediate progress in these areas, which critically involve the development of high-resolution coupled model simulations, partial coupling or pacemaker experiments, as well as the development and use of dynamical metrics and exploitation of hierarchies of models.

A singular focus on trying to limit “global warming” ignores critical factors essential for community sustainability; Such a narrow focus is simply self-defeating.

“While Transactions is a leading scientific journal, these special issue articles are anything but scientific. There are no experiments or tests, or even carefully constructed real world observations. It is all just speculation and computer modeling. This is what alarmist so-called science looks like. It is all about the UN Paris Agreement, not science.” click here

Why Not Apply Occam’s Razor to Climate Modeling?

“A 1D forcing-feedback model with two equivalent-ocean layers is used to model monthly global average surface temperatures from 1880 through 2017. Reflected shortwave (SW) and thermally emitted longwave (LW) forcings and feedbacks are included in an attempt to obtain the closest match between the model and HadCRUT4 surface temperatures based upon correlation and long-term trends.” click here