Climate changes instead of global warming

Air temperature changes on Earth in recent years are the subject of numerous and increasingly interdisciplinary research. In contrast to, conditionally speaking, generally accepted views that these changes are conditioned primarily by anthropogenic activity, more results appear to suggest that it is dominant natural processes about. Whether because of the proven existence of areas in which downtrends are registered or the stagnation of air temperature, as opposed to areas where the increase is determined, in scientific papers, as well as the media, the increasingly present is the use of the term climate changes instead of the global warming. In this paper, we shall try to present arguments for the debate relating to the official view of the IPCC, as well as research indicating the opposite view

What Do Observational Datasets Say about Modeled Tropospheric Temperature Trends since 1979?

Updated tropical lower tropospheric temperature datasets covering the period 1979–2009 are presented and assessed for accuracy based upon recent publications and several analyses conducted here. We conclude that the lower tropospheric temperature (TLT) trend over these 31 years is +0.09 ± 0.03 °C decade−1. Given that the surface temperature (Tsfc) trends from three different groups agree extremely closely among themselves (~ +0.12 °C decade−1) this indicates that the “scaling ratio” (SR, or ratio of atmospheric trend to surface trend: TLT/Tsfc) of the observations is ~0.8 ± 0.3. This is significantly different from the average SR calculated from the IPCC AR4 model simulations which is ~1.4. This result indicates the majority of AR4 simulations tend to portray significantly greater warming in the troposphere relative to the surface than is found in observations. The SR, as an internal, normalized metric of model behavior, largely avoids the confounding influence of short-term fluctuations such as El Niños which make direct comparison of trend magnitudes less confident, even over multi-decadal periods

Research on Forecasting for the Manmade Global Warming Alarm: Testimony to Committee on Science, Space and Technology Subcommittee on Energy and Environment on Climate Change: Examining the processes used to create science and policy

The validity of the manmade global warming alarm requires the support of scientific forecasts of (1) a substantive long-term rise in global mean temperatures in the absence of regulations, (2) serious net harmful effects due to global warming, and (3) cost-effective regulations that would produce net beneficial effects versus alternatives policies, including doing nothing. Without scientific forecasts for all three aspects of the alarm, there is no scientific basis to enact regulations. In effect, the warming alarm is like a three-legged stool: each leg needs to be strong. Despite repeated appeals to global warming alarmists, we have been unable to find scientific forecasts for any of the three legs. We drew upon scientific (evidence-based) forecasting principles to audit the forecasting procedures used to forecast global mean temperatures by the Intergovernmental Panel on Climate Change (IPCC)—leg “1” of the stool. This audit found that the IPCC procedures violated 81% of the 89 relevant forecasting principles. We also audited forecasting procedures, used in two papers, that were written to support regulation regarding the protection of polar bears from global warming —leg “3” of the stool. On average, the forecasting procedures violated 85% of the 90 relevant principles. The warming alarmists have not demonstrated the predictive validity of their procedures. Instead, their argument for predictive validity is based on their claim that nearly all scientists agree with the forecasts. This count of “votes” by scientists is not only an incorrect tally of scientific opinion, it is also, and most importantly, contrary to the scientific method. We conducted a validation test of the IPCC forecasts that were based on the assumption that there would be no regulations. The errors for the IPCC model long-term forecasts (for 91 to 100 years in the future) were 12.6 times larger than those from an evidence-based “no change” model. Based on our own analyses and the documented unscientific behavior of global warming alarmists, we concluded that the global warming alarm is the product of an anti-scientific political movement. Having come to this conclusion, we turned to the “structured analogies” method to forecast the likely outcomes of the warming alarmist movement. In our ongoing study we have, to date, identified 26 similar historical alarmist movements. None of the forecasts behind the analogous alarms proved correct. Twenty-five alarms involved calls for government intervention and the government imposed regulations in 23. None of the 23 interventions was effective and harm was caused by 20 of them. Our findings on the scientific evidence related to global warming forecasts lead to the following recommendations: 1. End government funding for climate change research. 2. End government funding for research predicated on global warming (e.g., alternative energy; CO2 reduction; habitat loss). 3. End government programs and repeal regulations predicated on global warming. 4. End government support for organizations that lobby or campaign predicated on global warming

Assessment of Future Climate Change Projections Using Multiple Global Climate Models

Nowadays, the hydrological cycle which alters river discharge and water availability is affected by climate change. Therefore, the understanding of climate change is curial for the security of hydrologic conditions of river basins. The main purpose of this study is to assess the projections of future climate across the Upper Ayeyarwady river basin for its sustainable development and management of water sector for this area. Global Ten climate Models available from CMIP5 represented by the IPCC for its fifth Assessment Report were bias corrected using linear scaling method to generate the model error. Among the GCMs, a suitable climate model for each station is selected based on the results of performance indicators (R2 and RMSE). Future climate data are projected based on the selected suitable climate models by using future climate scenarios: RCP2.6, RCP4.5, and RCP8.5. According to this study, future projection indicates to increase in precipitation amounts in the rainy and winter season and diminishes in summer season under all future scenarios. Based on the seasonal temperature changes analysis for all stations,  the future temperature are  predicted to steadily increase with higher rates during summer than the other two seasons and it can also be concluded that the monthly minimum temperature rise is a bit larger than the maximum temperature rise in all seasons

Evidence-Based Forecasting for Climate Change

Following Green, Armstrong and Soon’s (IJF 2009) (GAS) naïve extrapolation, Fildes and Kourentzes (IJF 2011) (F&K) found that each of six more-sophisticated, but inexpensive, extrapolation models provided forecasts of global mean temperature for the 20 years to 2007 that were more accurate than the “business as usual” projections provided by the complex and expensive “General Circulation Models” used by the U.N.’s Intergovernmental Panel on Climate Change (IPCC). Their average trend forecast was .007°C per year, and diminishing; less than a quarter of the IPCC’s .030°C projection. F&K extended previous research by combining forecasts from evidence-based short-term forecasting methods. To further extend this work, we suggest researchers: (1) reconsider causal forces; (2) validate with more and longer-term forecasts; (3) adjust validation data for known biases and use alternative data; and (4) damp forecasted trends to compensate for the complexity and uncertainty of the situation. We have made a start in following these suggestions and found that: (1) uncertainty about causal forces is such that they should be avoided in climate forecasting models; (2) long term forecasts should be validated using all available data and much longer series that include representative variations in trend; (3) when tested against temperature data collected by satellite, naïve forecasts are more accurate than F&K’s longer-term (11-20 year) forecasts; and (4) progressive damping improves the accuracy of F&K’s forecasts. In sum, while forecasting a trend may improve the accuracy of forecasts for a few years into the future, improvements rapidly disappear as the forecast horizon lengthens beyond ten years. We conclude that predictions of dangerous manmade global warming and of benefits from climate policies fail to meet the standards of evidence-based forecasting and are not a proper basis for policy decisions

Evolution of the Maximum Upper Level Divergence Field in Gulf-Atlantic Tropical Cyclogenesis

Upper-level (horizontal) divergence (ULD) is an important variable in tropical weather systems. As part of the circulation within a tropical cyclone (TC), it carries air in the upper troposphere away from the center of circulation (COC). To date, most research assumes the 200 hPa pressure level (approximately 12 km, varying with latitude and time of year) as the height for maximum ULD in a TC, possibly because weather observation at the 200 hPa level by radiosonde have remained mandatory for aviation purposes. The more recent availability of gridded, high-spatial-resolution, global “reanalysis” data at multiple levels, along with improvements in spatial interpolation techniques, has allowed for more precise and accurate determination of the heights at which peak ULD actually occurs, how that level varies temporally prior to and after tropical cyclogenesis (TCG), and how the spatial and temporal attributes of the three-dimensional zone of the maximum ULD field vary by storm. This research addresses these questions. Prediction of TCs is improving rapidly as scientific understanding of the atmospheric and oceanic conditions that characterize TCG, along with tools available for measuring the associated variables, are becoming more advanced and widespread. Results using the 2005 Atlantic tropical cyclone season suggest peak mean ULD during TCG occurs predominantly at 175 hPa and is typically located in the northeastern quadrant of the storm, hundreds of kilometers from the COC. The mean conditions showed a steady increase in magnitude of ULD from TCG ‒12 hours to TCG +6 hours and levels off or reduces at TCG +12 hours. Mean ULD is less organized on most levels before TCG and becomes more organized and concentrated between 200 hPa and 150 hPa from TCG to TCG +12 hours. Peak ULD during individual cyclogenesis occurrences varies widely in magnitude, temporally, and vertically. Therefore, each cyclone should be evaluated individually. In general, this research supports the notion that confinement of ULD analysis to a single pressure level could diminish research or model outcome as ULD location is variable in four-dimensional space. These results may be useful in weather and climate modeling as evolution of TC outflow can be better understood

Climate change 2013: the physical science basis

This report argues that it is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century. This is an an unedited version of the Intergovernmental Panel on Climate Change\u27s Working Group I contribution to the Fifth Assessment Report following the release of its Summary for Policymakers on 27 September 2013.  The full Report is posted in the version distributed to governments on 7 June 2013 and accepted by Working Group I and the Panel on 27 September 2013. It includes the Technical Summary, 14 chapters and an Atlas of Global and Regional Climate Projections. Following copy-editing, layout, final checks for errors and adjustments for changes in the Summary for Policymakers, the full Report will be published online in January 2014 and in book form by Cambridge University Press a few months later