@BubSluggo

May God's will be done on earth as it is in heaven

 Alberta, Canada
Joined February 2022
  • Tweets4K
  • Following127
  • Followers212
589Media
Symbolic. A country in decline. Wrapped in a stifling identity destroying post national globalism. Weathering a geopolitical storm badly..... A province where freedom and identity still mean something.
37
To verify the warming claimed by the climate crisis proponents to have caused the Nepal landslide/"glacier collapse", I downloaded atmospheric temperature by elevation in the area (details in the "ALT" text for the graphics). I found negligible air temperature warming in the Nepal failure area, at the elevations of the glaciers over the period 2002 to 2026 for any month of the year. I was warned by @RARohde that these satellite measured air temperature by pressure level monthly averages aren't accurate where the land surface is close to the pressure level of the air temperature being reported, but I'm going to post my results anyway. I also downloaded time series of the geopotential height of these pressure levels to see what corrections (if any) were needed to correct the temperature trends for altitude change in the pressure level over the trend period. If requested I'll post those also, plus if you want to see night temperatures, I'll post those trends by month also.
A chart of 12 time series of the daytime air temperature in the area of Nepal (27.3N, 85.5E) where the recent landslide occurred, from 2002 to 2026, sourced from the NASA Giovanni data portal. These are satellite data, measured by the AIRS instrument on the Aqua satellite. Each series represents the annual data for one of the 12 months. The linear regression slope of each month is posted to the left. Slopes are in degrees C per year change. This chart is for the pressure level of 500 mb, which is about 5600 m above sea level, or slightly higher than the elevation the glacier above the landslide was at. Slopes are indistinguishable from zero for all months, meaning there is no observed air temperature warming in the 21st century at this location.

ALT A chart of 12 time series of the daytime air temperature in the area of Nepal (27.3N, 85.5E) where the recent landslide occurred, from 2002 to 2026, sourced from the NASA Giovanni data portal. These are satellite data, measured by the AIRS instrument on the Aqua satellite. Each series represents the annual data for one of the 12 months. The linear regression slope of each month is posted to the left. Slopes are in degrees C per year change. This chart is for the pressure level of 500 mb, which is about 5600 m above sea level, or slightly higher than the elevation the glacier above the landslide was at. Slopes are indistinguishable from zero for all months, meaning there is no observed air temperature warming in the 21st century at this location.

A chart of 12 time series of the daytime air temperature in the area of Nepal (27.3N,85.5E) where the recent landslide occurred, from 2002 to 2026, sourced from the NASA Giovanni data portal. These are satellite data, measured by the AIRS instrument on the Aqua satellite. Each series represents the annual data for one of the 12 months. The linear regression slope of each month is posted to the left. Slopes are in degrees C per year change. This chart is for the pressure level of 600 mb, which is about 4400 m above sea level, or slightly below the elevation the glacier above the landslide was at. Slopes are indistinguishable from zero for all months, meaning there is no observed air temperature warming in the 21st century at this location for this pressure level.

ALT A chart of 12 time series of the daytime air temperature in the area of Nepal (27.3N,85.5E) where the recent landslide occurred, from 2002 to 2026, sourced from the NASA Giovanni data portal. These are satellite data, measured by the AIRS instrument on the Aqua satellite. Each series represents the annual data for one of the 12 months. The linear regression slope of each month is posted to the left. Slopes are in degrees C per year change. This chart is for the pressure level of 600 mb, which is about 4400 m above sea level, or slightly below the elevation the glacier above the landslide was at. Slopes are indistinguishable from zero for all months, meaning there is no observed air temperature warming in the 21st century at this location for this pressure level.

2
1
3
256
To understand better what the actual rate of glacier shrinkage in the area of the recent Nepal landslide I downloaded a database which used images from the Aster instrument on the Terra satellite processed by photogrammetry to track changes in the thickness of Himalayan glaciers. Yellow on the images is negligible change, and you can see a lot of yellow in this area (white is no data, orange/pink is shrinkage and olive/blue is thickness gain). And yes there is some areas with thickness gain which you can see at higher scales. The 1975 baseline is from aerial photography, while the 2000 and 2016 surfaces are from the satellite measured topographic surface. The first image shows the rate of change from 1975 to 2000, and the second from 2000 to 2016. While there is some acceleration in the rate between 1975/2000 and 2000/2016, it appears to be the most prominent in the glaciers draining into the desert area to the north east. You be your own judge, but the amount of yellow on this map indicates to me the upper elevations of the glaciers in this area look relatively stable.
1
1
2
300
I've looked through some of the 3D Google Earth imagery and updated my rock/ice/failure zone interpretation of the recent Nepal landslide (see the 1st image). I don't think this failure had anything to do with climate change. 1: First of all the failure propagated mostly through rock. Granted it took the tip of the glacier tongue with it, but the glacier tongue on the south side of the rock knob stayed mostly intact, despite being shook by a 5.2 earthquake immediately below it. 2: Also the exposed failure plane shows it failed through a suture between 2 distinct rock types. Given we are in the Himalayan thrust belt, it's likely a fault, meaning a zone of structural weakness was under this failure block (see the 2nd image). 3: Finally, after looking through the Google Earth imagery back to 2008, the glacier in this area doesn't seem to have changed much in extent, so it doesn't appear a warming climate had much effect on this particular glacier.
6
2
2
13
975
I know I'm shouting into the news hurricane with this comment, but the Nepal #NepalFloodNews flood/landslide event was not a "glacial collapse". I've looked at pre and post satellite imagery, and transferred the interpreted failure area from the low-res current imagery to Google Earth hi-resolution imagery (all 3 shown below), and most of the failure (by area) was a rock knob/slab at the toe of the glacier, not the glacier itself although part of the glacier failed too. The rock was a buttress to the glacier at the toe, and it likely failed first, releasing the glacier. The rock was in an inherently unstable configuration with daylighted bedding dipping down into the valley. I know this doesn't quite fit the climate crisis narrative, but if you don't agree show me where I am wrong.
1
9
2
32
2,100
After looking at pre/post failure satellite images of the Nepal "glacier" slide, I think there was a substantial amount of rock that failed. In fact it was probably the rock that failed first and released the ice. See my interpretation below. Purple is the failure crest on both images, and orange marks the boundary at the surface of the glacier/rock interface.
1
1
9
2,457
The flood event in Nepal was a glacier landslide, not a glacial lake outburst as some are claiming. There are some large lakes at the toe of glaciers to the north east, maybe 20 km away, but they don't look to be ice dammed and they are on the other side of a major drainage divide, not in this basin.
1
1
750
The thing about the AI chatbots that annoyed me the most is that the tool reminds me of Jesus' parable of the hired hands working in the vineyard. Some came early and worked all day, through the heat of the day, but the vineyard owner kept hiring more, right up to the last hour of work. And when it came time to get paid, they all got a full day's pay. As you can imagine the workers who put in a full day were outraged, but the vineyard owner said its my choice to pay you all as I see fit. So it is with those that have worked to learn by doing, downloading data, plotting and analyzing it, trying out their ideas with these analyses. And with a short typed phrase, anyone can know as much or more as the doers have learned through many hours of trial and error. It's not quite that simple of course. AI is rapidly getting better but on a regular basis it seems to omit facets of a subject it is queried on, which the neophyte will miss but the doer will not. And of course, it cuts both ways. The scientist watches as AI gives away their trade secrets, so to speak, to the hobbyist who for all their work haven't spent 1/1000 of the time the scientist has spent trying to understand a subject. I've decided that, with the caveat that the AI agents all seem to have a progressive narrative bias, more knowledge is better. Embrace the tool for what it can do for you.
1
115
The climate crisis proponents seem to think if they repeat the mantra "climate change explains the increase in wildfire" enough times it will be true. The data beg to differ, especially the data before 1940. I previously looked at the trend in a key fireweather metric, the summer daytime vapor pressure deficit over the CONUS. I used the high resolution PRISM database which covers the CONUS. My first analysis included the whole CONUS, but most of that is not what wildfires burn, i.e. forests. To zero in on the trend in the VPD in just forested areas, I masked the PRISM data to create a summer daytime VPD trend analysis, but just covering the forested areas (see the first figure). I found the long term trend in the VPD for forested areas in the CONUS was flat, meaning there has been no increase in the propensity for wildfire over the last century and a quarter according to this metric (see the 2nd figure). It's true if you isolate just the last few decades it looks like fire weather is getting worse, but clearly the time series chart shows it can be just as bad or worse for wildfire propensity at much lower levels of CO2.
A pixel map of the contiguous US states, showing the forested areas by type from the NLCD_ConusV1 database, down sampled from the original resolution to approximately 3 km by 3 km.

ALT A pixel map of the contiguous US states, showing the forested areas by type from the NLCD_ConusV1 database, down sampled from the original resolution to approximately 3 km by 3 km.

A time series of the area weighted monthly average vapor pressure deficit for the monthly April to August, daytime maximum value. The trend is for those gridcells that are coded as conifer forest, deciduous forest, and mixed forest from the NLCD_ConusV1 database. Data source for the VPD is the PRISM database covering the CONUS. The time series shows that while there has been an increase in the VPD for summertime forested areas in the US, the overall trend since 1895 to 2026 is flat, maybe even slightly declining.

ALT A time series of the area weighted monthly average vapor pressure deficit for the monthly April to August, daytime maximum value. The trend is for those gridcells that are coded as conifer forest, deciduous forest, and mixed forest from the NLCD_ConusV1 database. Data source for the VPD is the PRISM database covering the CONUS. The time series shows that while there has been an increase in the VPD for summertime forested areas in the US, the overall trend since 1895 to 2026 is flat, maybe even slightly declining.

1
1
382
Because the alleged climate/wildfire link has been applied to recent fires in the US northwest, I generated a long term summer vapor pressure deficit maximum, forests-only time series for this area (see location map blue box and resulting time series below). As you can the trend in this key fire weather metric is flat in the NW USA forests since 1895
1
106
The people signing this would be outraged if the US tried to tell Canada who can or can't be our ambassador to their country. Hypocrisy at its most obvious. xitter.cf/RGBAtlantica/status/20…
@RGBAtlantica@RGBAtlanticaAug 13
41 million Canadians and we've only got 123,820 signatures? Let's go people, make your voices heard to expel the scumbag Pete Hoekstra, the guy Trump sent to divide us and destroy our sovereignty. Send this to all your friends, stand up for Canada 🇨🇦🇨🇦 ourcommons.ca/petitions/en/P…
97
What's happening?.....Clouds is what's happening for climate change. Clouds change absorbed shortwave (solar) radiation (ASR), and ASR changes climate. The evidence in 2 figures:
A global map of the R-squared coefficient from regression, by month, by grid cell of the upwelling shortwave radiation measured by the CERES satellite instruments at the top of the atmosphere, regressed against the total daytime cloud fraction measured by the AIRS satellite borne infrared scanner. The map shows the very strong correlation between the cloud cover anomaly and the upwelling shortwave anomaly. Not shown on this map is the relation, which is positive: more cloud = more upwelling shortwave radiation. The correlation is less strong in the polar latitudes since they are covered by sea ice and snow much of the time they get daylight, so cloud cover doesn't increase upwelling shortwave except for the short summer in the north. Antarctica is mostly snow covered year round so there, clouds don't make a difference, maybe even slightly decrease upwelling shortwave, as the clouds scatter the incoming solar shortwave.

ALT A global map of the R-squared coefficient from regression, by month, by grid cell of the upwelling shortwave radiation measured by the CERES satellite instruments at the top of the atmosphere, regressed against the total daytime cloud fraction measured by the AIRS satellite borne infrared scanner. The map shows the very strong correlation between the cloud cover anomaly and the upwelling shortwave anomaly. Not shown on this map is the relation, which is positive: more cloud = more upwelling shortwave radiation. The correlation is less strong in the polar latitudes since they are covered by sea ice and snow much of the time they get daylight, so cloud cover doesn't increase upwelling shortwave except for the short summer in the north. Antarctica is mostly snow covered year round so there, clouds don't make a difference, maybe even slightly decrease upwelling shortwave, as the clouds scatter the incoming solar shortwave.

A comparison chart of 2 time series: blue is the weighted average of the upwelling or reflected solar radiation from 2002 to 2026, compared to the changes in daytime total cloud fraction as detected by satellites. These are the monthly weighted by area averages over the oceans between 60N and 60S. This area was chosen since the oceans are where energy is absorbed and the 60S to 60N is where the incoming & outgoing radiation flux at the top of the atmosphere determine the radiation balance of the earth. The thick solid lines are rolling 12 month averages o the monthly anomalies which are the fine dash dot lines. The chart clearly shows by the strong correction between these 2 metrics that cloud cover changes are what is driving changes in reflected solar radiation, at least over the 21st century.

ALT A comparison chart of 2 time series: blue is the weighted average of the upwelling or reflected solar radiation from 2002 to 2026, compared to the changes in daytime total cloud fraction as detected by satellites. These are the monthly weighted by area averages over the oceans between 60N and 60S. This area was chosen since the oceans are where energy is absorbed and the 60S to 60N is where the incoming & outgoing radiation flux at the top of the atmosphere determine the radiation balance of the earth. The thick solid lines are rolling 12 month averages o the monthly anomalies which are the fine dash dot lines. The chart clearly shows by the strong correction between these 2 metrics that cloud cover changes are what is driving changes in reflected solar radiation, at least over the 21st century.

1
145
Wildfire is a topic this summer. Climate crisis proponents claim that it's the result of anthropogenic climate change. They base their claims on wildfire studies, but these all have a deficiency, they start after 1950. To look back further, I downloaded a key fire weather metric, the vapour pressure deficit (VPD) from the high resolution PRISM database from the U of Oregon. They have calculated the VPD monthly average maximum (the daytime number) for the CONUS all the way back to 1895 (see map for the average VPD by grid cell for the summer months, 1895 to 2026). You can see from the time series for the summer months, the CONUS VPD has actually declined, meaning a lower propensity for wildfire, at least compared to the 1930s. Be your own judge. And next time you see a claim about how much worse fire weather is now, ask the claimant what does the data before 1950 look like?
2
4
567
Despite the non-stop hyperbole on the strength of the 2026 El Nino by @WeatherProf & others, the subsurface temperatures in the Nino3.4 area as measured by the TAO buoy network, at least at the east end, are not (yet) above previous El Ninos. See the gif below. The black dashed line is 2026. Previous El Nino years are the colored lines. Grey traces are non-El Nino years. However, at the west end of the Nino3.4 area the subsurface temperatures are above previous El Ninos (155W). See my previous post showing that comparison (and the 140W TAO buoy) of 2026 subsurface ocean temperatures to previous big El Ninos.
160
There's a lot of hyperbole posted on the 2026 El Nino. I've been tracking the subsurface temperatures comparing TAO buoy data from this year to previous El Nino years. I had noted the subsurface temperatures were not above previous El Nino years at this point in the year. However, in the last week or 2, that has changed, not by as much as some of the more absurd claims like by @WeatherProf , but more than 1 C for sure above any other El Nino. See below. The black dashed line is 2026. Other El Nino years are colored, but there are a lot of gaps in the data so not all years always show up for any given time increment. The 155W buoy is not the best location, 140W would be more central to the Nino3.4 area but it doesn't go back as far time-wise.
1
117
I must correct my self. The 140W TAO buoy does have decent data. It shows the subsurface ocean temperatures are (so far) not higher than the 1997 El Nino, except below 100 m or so in the last week.
57
I did do the TOBS correction crosscheck on the hourly Ottawa airport data from 1953 to 2011. Just closing this topic off......both TMAX and TMIN....
74
Load more