Climate Research

1910 Submissions

[4] viXra:1910.0502 [pdf] submitted on 2019-10-24 21:21:36

Causal Inference for Climate Change Events from Satellite Image Time Series Using Computer Vision and Deep Learning

Authors: Vikas Ramachandra
Comments: 16 Pages.

We propose a method for causal inference using satellite image time series, in order to determine the treatment effects of interventions which impact climate change, such as deforestation. Simply put, the aim is to quantify the 'before versus after' effect of climate related human driven interventions, such as urbanization; as well as natural disasters, such as hurricanes and forest fires. As a concrete example, we focus on quantifying forest tree cover change/ deforestation due to human led causes. The proposed method involves the following steps. First, we use computer vision and machine learning/deep learning techniques to detect and quantify forest tree coverage levels over time, at every time epoch. We then look at this time series to identify changepoints. Next, we estimate the expected (forest tree cover) values using a Bayesian structural causal model and projecting/forecasting the counterfactual. This is compared to the values actually observed post intervention, and the difference in the two values gives us the effect of the intervention (as compared to the non intervention scenario, i.e. what would have possibly happened without the intervention). As a specific use case, we analyze deforestation levels before and after the hyperinflation event (intervention) in Brazil (which ended in 1993-94), for the Amazon rainforest region, around Rondonia, Brazil. For this deforestation use case, using our causal inference framework can help causally attribute change/reduction in forest tree cover and increasing deforestation rates due to human activities at various points in time.
Category: Climate Research

[3] viXra:1910.0102 [pdf] replaced on 2019-12-02 14:35:58

The Lack of Substantiation of the Green House Model

Authors: Sjaak Uitterdijk
Comments: 2 Pages.

This article shows a short and convincing, to the opinion of the author, proof of the invalidity of the greenhouse model.
Category: Climate Research

[2] viXra:1910.0091 [pdf] submitted on 2019-10-07 03:47:09

Short Review of Climate Change in Support of Greta Thunberg and Fridays for Future

Authors: Rainer W. kühne
Comments: 5 Pages.

I review the evidence of natural climate change as given by the Greenland ice core data of the past 120,000 years and the Antarctica ice core data of the past 900,000 years. These data show that the atmospheric carbon dioxide concentration never exceeded 300 ppm (parts per million by volume) during the 650,000 years which preceded AD 1900. Only around 1900 did the concentration reach 300 ppm. Afterwards it increased continuously until the present value of over 400 ppm, where since AD 2000 it increases by 2 ppm per year. I predict that within the next one hundred years the global temperature will increase by further 3.6°C only because of the carbon dioxide concentration that is already at present in the atmosphere.
Category: Climate Research

[1] viXra:1910.0002 [pdf] replaced on 2019-12-11 10:13:38

Hydro-Hotspots Global Warming - Human Forcing of Humidity Change

Authors: Alec Feinberg
Comments: 16 Pages.

Understanding root causes is always needed to find proper solutions. In climate change, we must ask, what has historically changed? Besides CO2, we have a change in the specific and relative humidity, slight decrease in land albedo, and yearly growth of Hydro-HotSpots (HHS) and its effect on Human Forcing of Humidity change (HFH). We denote hydro-hotspot as water evaporation and bulk heating from low albedo manmade type roads and cities surfaces, including cars and engine hoods. This includes both Highly Evaporating Surfaces (HES) and bulk warm Rain Water Management (RWM). Most significant is land albedo change. An Earth albedo change from 0.29 to 0.288, corresponds to a 0.32oF rise, due to growth in cities and roads. This feeds most of the HHS’ which are concentrated hot areas (not include hot combustive areas). We show in this article that such surfaces, while covering less than 2% of the Earth, can have very large effective areas, many times the size of the HES and RWM area itself compared with higher albedo absorbing vegetative areas that also include transpiration. This is significant since water vapor is the most potent greenhouse gas. City surfaces can prove to be enormous when tall buildings are considered. In addition, Hydro-hotspots generate high kinetic energy molecules in the troposphere which can decrease relative humidity while increasing specific humidity. It is thought that global warming ocean evaporation-CO2 feedback is the key contributor, but in this paper other issues are considered. For example, we find that it is nontrivial to look at changing the albedo of cities and roads as possibly a major solution to global warming. Also alarming is warm rain water management. For example, New York City dumps an estimated 27 billion gallons of waste water into the ocean each year. This pattern is followed by cities all over the world. This water is often warmed by hot city streets and buildings having high heat capacities. This is also lost land water storage as urban impermeable surfaces increase. Numerous concerns are pointed out: 1) warmer runoff to streams/ocean water, 2) loss of wetland storage in vegetative areas, 3) loss of land evaporation and precipitation, 4) increase in ocean precipitation creating higher land temperatures, and 5) dryer drought-prone regions. This is key as change in global warming goes as the change in specific and relative humidity which are functions of CO2, other GHGs, and as described here, HHS.
Category: Climate Research