Martha Stewart with her “iceberg” cocktail and the chunk of ice it presumably came from. (Martha Stewart/Instagram)
Martha Stewart, the American home-and-hospitality retail businesswoman, television personality and writer, has been on a cruise around Greenland, where she had a chunk of ice (presumably calved from the Greenland ice sheet) brought aboard to provide ice for adult beverages.
Cue the climate alarmists, who considered such an action to be tone deaf regarding the seriousness of the climate crisis.
What, you might ask, does fishing a chunk of ice out of the ocean next to the Greenland ice cap have to do with the “climate crisis”?
Well, in some people’s minds (I know because I’ve met a few of them), ice calving off of the Greenland ice sheet is due to global warming.
Wrong.
The Antarctic and Greenland ice sheets are locations which are so cold for so much of the year, with enough snowfall, that come summer not all of the snowfall melts. This leads to a net accumulation of ice over the centuries and millennia. That’s what causes a “glacier” to form.
As the ice sheet deepens over the centuries, gravity starts to make the ice flow downhill, like very thick molasses. It then breaks off when it reaches the coast, floating away, and melting.
Everything I described above has nothing to do with global warming. Most scientists believe it has been going on for millions of years.
So, along comes Martha Stewart, at 82 years old just trying to enjoy life, and she gets global backlash for plucking a chunk of ice out of the ocean to cool her drink down.
What are they teaching kids in school these days???
One of the most fundamental requirements of any physics-based model of climate change is that it must conserve mass and energy. This is partly why I (along with Danny Braswell and John Christy) have been using simple 1-dimensional climate models that have simplified calculations and where conservation is not a problem.
Changes in the global energy budget associated with increasing atmospheric CO2 are small, roughly 1% of the average radiative energy fluxes in and out of the climate system. So, you would think that climate models are sufficiently carefully constructed so that, without any global radiative energy imbalance imposed on them (no “external forcing”), that they would not produce any temperature change.
It turns out, this isn’t true.
Back in 2014 our 1D model paper showed evidence that CMIP3 models don’t conserve energy, as evidenced by the wide range of deep-ocean warming (and even cooling) that occurred in those models despite the imposed positive energy imbalance the models were forced with to mimic the effects of increasing atmospheric CO2.
Now, I just stumbled upon a paper from 2021 (Irving et al., A Mass and Energy Conservation Analysis of Drift in the CMIP6 Ensemble) which describes significant problems in the latest (CMIP5 and CMIP6) models regarding not only energy conservation in the ocean but also at the top-of-atmosphere (TOA, thus affecting global warming rates) and even the water vapor budget of the atmosphere (which represents the largest component of the global greenhouse effect).
These represent potentially serious problems when it comes to our reliance on climate models to guide energy policy. It boggles my mind that conservation of mass and energy were not requirements of all models before their results were released decades ago.
One possible source of problems are the model “numerics”… the mathematical formulas (often “finite-difference” formulas) used to compute changes in all quantities between gridpoints in the horizontal, levels in the vertical, and from one time step to the next. Miniscule errors in these calculations can accumulate over time, especially if physically impossible negative mass values are set to zero, causing “leakage” of mass. We don’t worry about such things in weather forecast models that are run for only days or weeks. But climate models are run for decades or hundreds of years of model time, and tiny errors (if they don’t average out to zero) can accumulate over time.
The 2021 paper describes one of the CMIP6 models where one of the surface energy flux calculations was found to have missing terms (essentially, a programming error). When that was found and corrected, the spurious ocean temperature drift was removed. The authors suggest that, given the number of models (over 30 now) and number of model processes being involved, it would take a huge effort to track down and correct these model deficiencies.
I will close with some quotes from the 2021 J. of Climate paper in question.
“Our analysis suggests that when it comes to globally integrated OHC (ocean heat content), there has been little improvement from CMIP5 to CMIP6 (fewer outliers, but a similar ensemble median magnitude). This indicates that model drift still represents a nonnegligible fraction of historical forced trends in global, depth-integrated quantities…”
“We find that drift in OHC is typically much smaller than in time-integrated netTOA, indicating a leakage of energy in the simulated climate system. Most of this energy leakage occurs somewhere between the TOA and ocean surface and has improved (i.e., it has a reduced ensemble median magnitude) from CMIP5 to CMIP6 due to reduced drift in time-integrated netTOA. To put these drifts and leaks into perspective, the time-integrated netTOA and systemwide energy leakage approaches or exceeds the estimated current planetary imbalance for a number of models.“
“While drift in the global mass of atmospheric water vapor is negligible relative to estimated current trends, the drift in time-integrated moisture flux into the atmosphere (i.e., evaporation minus precipitation) and the consequent nonclosure of the atmospheric moisture budget is relatively large (and worse for CMIP6), approaching/exceeding the magnitude of current trends for many models.”
This is to remind folks about commenting controls here that might very well impact YOU…
I have quite a few banned terms that will get your comment ignored. These are meant to minimize bullying, although your use of such terms might not involve bullying at all.
Comments posted with an unrecognized name or email address will go to moderation, and depending upon how busy I am, I might not get to it for days. This means if you fat-finger either your name or your e-mail address (or, like me, accidentally include my middle name), the comment goes to moderation. Yes, I just had to approve my own comment.
July 2023 was an unusual month, with sudden warmth and a few record or near-record high temperatures.
Since the satellite record began in 1979, July 2023 was:
warmest July on record (global average)
warmest absolute temperature (since July is climatologically the warmest month)
tied with March 2016 for the 2nd warmest monthly anomaly (departure from normal for any month)
warmest Southern Hemisphere land anomaly
warmest July for tropical land (by a wide margin, +1.03 deg. C vs. +0.44 deg. C in 2017)
These results suggest something peculiar is going on. It’s too early for the developing El Nino in the Pacific to have much effect on the tropospheric temperature record. The Hunga Tonga sub-surface ocean volcano eruption and its “unprecedented” production of extra stratospheric water vapor could be to blame. There might be other record high temperatures regionally in the satellite data, but I don’t have time right now to investigate that.
Now, back to our regularly scheduled programming…
The Version 6 global average lower tropospheric temperature (LT) anomaly for July 2023 was +0.64 deg. C departure from the 1991-2020 mean. This is well above the June 2023 anomaly of +0.38 deg. C.
The linear warming trend since January, 1979 now stands at +0.14 C/decade (+0.12 C/decade over the global-averaged oceans, and +0.18 C/decade over global-averaged land).
Various regional LT departures from the 30-year (1991-2020) average for the last 19 months are:
YEAR
MO
GLOBE
NHEM.
SHEM.
TROPIC
USA48
ARCTIC
AUST
2022
Jan
+0.03
+0.06
-0.00
-0.23
-0.12
+0.68
+0.10
2022
Feb
-0.00
+0.01
-0.01
-0.24
-0.04
-0.30
-0.50
2022
Mar
+0.15
+0.28
+0.03
-0.07
+0.22
+0.74
+0.02
2022
Apr
+0.27
+0.35
+0.18
-0.04
-0.25
+0.45
+0.61
2022
May
+0.17
+0.25
+0.10
+0.01
+0.60
+0.23
+0.20
2022
Jun
+0.06
+0.08
+0.05
-0.36
+0.46
+0.33
+0.11
2022
Jul
+0.36
+0.37
+0.35
+0.13
+0.84
+0.56
+0.65
2022
Aug
+0.28
+0.32
+0.24
-0.03
+0.60
+0.50
-0.00
2022
Sep
+0.24
+0.43
+0.06
+0.03
+0.88
+0.69
-0.28
2022
Oct
+0.32
+0.43
+0.21
+0.04
+0.16
+0.93
+0.04
2022
Nov
+0.17
+0.21
+0.13
-0.16
-0.51
+0.51
-0.56
2022
Dec
+0.05
+0.13
-0.03
-0.35
-0.21
+0.80
-0.38
2023
Jan
-0.04
+0.05
-0.14
-0.38
+0.12
-0.12
-0.50
2023
Feb
+0.08
+0.17
0.00
-0.11
+0.68
-0.24
-0.12
2023
Mar
+0.20
+0.24
+0.16
-0.13
-1.44
+0.17
+0.40
2023
Apr
+0.18
+0.11
+0.25
-0.03
-0.38
+0.53
+0.21
2023
May
+0.37
+0.30
+0.44
+0.39
+0.57
+0.66
-0.09
2023
June
+0.38
+0.47
+0.29
+0.55
-0.35
+0.45
+0.06
2023
July
+0.64
+0.73
+0.56
+0.87
+0.53
+0.91
+1.43
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for July, 2023 and a more detailed analysis by John Christy of the unusual July conditions, should be available within the next several days here.
The global and regional monthly anomalies for the various atmospheric layers we monitor should be available in the next few days at the following locations:
Virginia O’Hanlon, a real girl, wrote a real letter, to Dr. Roy.
Dear Dr. Roy:
I am 8 years old. Some of my little friends say there is no Climate Crisis. My Papa says, “If you see it in Dr. Roy’s climate blog, it is so.”
“Please tell me the truth. Is there a Climate Crisis?“
Virginia, your little friends are wrong. They have been affected by the skepticism of a skeptical age. They do not believe except they see. They think that nothing can be which is not comprehensible by their little minds. All minds, Virginia, whether they be men’s or women’s or children’s or ze’s or transgender’s, are little. In this great universe of ours humans are mere insects, ants, in their intellect, as compared with the boundless world about him/her/they/them, as measured by the intelligence capable of grasping the whole truth and knowledge.
Yes, Virginia, there is a Climate Crisis. It exists as certainly as taxation and death and congressional favors and subsidies exist, and you know that they abound and give to some people’s life its highest riches! Alas! How dreary would be the world if there were no Climate Crisis! It would be as dreary as if there were no poor people. There would be no special favors, no bird-chopping windmills, no Teslas to give wealthy people a reason to exist! We should have no enjoyment, except in sense and sight. The eternal light with which affluence fills the world would be extinguished.
Not believe in the Climate Crisis! You might as well not believe in fairies! You might get your papa to hire persons to watch all the private jets on Earth Day to catch Al Gore, but even if they did not see Al Gore, what would that prove? Nobody sees Al Gore, but that is no sign that there is no Al Gore. The most real things in the world are those that neither conservatives nor Trumpers can see. Did you ever see Greta Thunberg dancing on the lawn? Of course not, but that’s no proof that she was not there. Nobody can conceive or imagine all the wonders there are unseen and unseeable in the world.
You tear apart the baby’s rattle and see what makes the noise inside, but there is a veil covering the unseen world which not the strongest man/woman/person, nor even the united strength of all the strongest men/women/persons that ever lived, could tear apart. Only faith, fancy, poetry, love, romance can push aside that curtain and view and picture the supernal beauty and glory beyond mere reality!
Is it all real? Ah, Virginia, in all this world there is nothing else real and abiding.
No Climate Crisis! Thank Gaia It lives and It lives forever! A thousand years from now, Virginia, nay 10 times 10 thousand years from now, It will continue to put fear into your heart!
It has been a while since I have posted progress on our DOE-funded research into the Urban Heat Island (UHI) effect in the GHCN station temperatures used to monitor land-based global warming. It should be remembered that everything I post on this subject is (as is usually the case) a work in progress.
What I am addressing is the existence of localized long-term warming associated with population increases which are over-and-above the large-scale warming due to humanity’s greenhouse gas emissions or nature. These urban-influenced changes are very localized, and yet they influence large-scale area averages and make the land areas look like they are warming faster than they really are. The problem is pervasive because virtually all thermometer locations are where people live, and since the 1800s even most rural locations have experienced population growth.
The bottom line is that there are UHI-based trend (warming) effects in the GHCN station temperatures; the only question is, how much have they affected reported temperature trends? Most previously published research on the subject has suggested the effects are small (Hausfather et al., 2013; Wickham et al., 2013; Hansen et al., 2010; Parker, 2010; Jones et al., 2008; Parker, 2006; Peterson & Owen, 2005; Peterson, 2003; Peterson et al., 1999; Gallo et al., 1999; Karl et al., 1988). As a result, you will find most who defend the “climate crisis” narrative will refer to one or more of those studies as showing the “science is settled”, and that GHCN-based land warming estimates are largely free of UHI warming effects.
I have argued that those studies involved methodologies that were not very good. Identifying the UHI effect is difficult. I’ve come up with a novel way of quantifying the average UHI effect, even at stations that would be considered “rural” with presumably no UHI effect. We have a paper in review in Nature Scientific Reports describing the methodology (my blog description of the methodology is here), but I have no idea what chance it has of being published.
I will get right to the results as they stand today. What I show below are for the all-station average of GHCN stations; they are NOT area averages, which are what is needed for climate monitoring. They just show how much the average GHCN station is influenced by spurious UHI warming. The stations cover the latitude bands from 20N to 80N, but are dominated by U.S. stations (about 80% of the total) due to the huge numbers of stations we have in this country.
The plots are for 4 classes of initial GHCN station population density (the first year those stations started operating) during the warm season (May/June/July), and give the cumulative year-on-year temperature increase averaged across all stations in each of the four initial station population classes. The adjusted (homogenized) GHCN station temperature changes are in green, and my calculated UHI effect is in red.
For the “wilderness to very rural” class (upper-left panel), the UHI effect on temperature trends turns out to be quite small, contrary to what I have recently argued. Since many of these low-population stations are at high northern latitudes, this would suggest that the UHI effects on the large warming trends reported there are small.
But as we progress to higher population stations, we find that UHI warming effect becomes larger. In the highest population density class (“suburban to urban”, lower-right panel) my calculation of UHI warming is virtually the entire GHCN-reported warming signal since 1880, but only a small part of the reported warming since 1980.
If these results stand, what will they mean for reported land warming trends?
I’m guessing that the UHI effect on area-average trends since 1980 (the period of most rapid temperature rise) will turn out to be relatively small. But before 1980 it looks like the UHI effect on GHCN temperatures could be substantial. This would change the nature of the global warming narrative, with little land-based warming for the first 100 years starting in 1880.
What could change these results? First, I do not account for increases in the UHI effect due to per-capita increases in infrastructure and energy use (buildings, vehicles, parking lots, electricity use and resulting waste heat). I assume the UHI effect is only a function of population density (partly because we have global gridpoint data on population extending back into the 1800s). Thus, my UHI warming estimates might be a little low for stations where population stopped growing but spurious sources of heat continued to increase, such as in Vienna, Austria (R. Bohm, Climatic Change, 1998).
In any event, I feel like I am finally converging on useful results. One aspect of this is that the record high temperatures now being reported in major population centers in the southwest U.S. and southern Europe need to be revisited based upon the very large urban heat island temperature increases seen in the lower-right panel of the above plot at suburban-to-urban stations.
The Version 6 global average lower tropospheric temperature (LT) anomaly for June 2023 was +0.38 deg. C departure from the 1991-2020 mean. This is statistically unchanged from the May 2023 anomaly of +0.37 deg. C.
The linear warming trend since January, 1979 remains at +0.13 C/decade (+0.12 C/decade over the global-averaged oceans, and +0.18 C/decade over global-averaged land).
Various regional LT departures from the 30-year (1991-2020) average for the last 18 months are:
YEAR
MO
GLOBE
NHEM.
SHEM.
TROPIC
USA48
ARCTIC
AUST
2022
Jan
+0.03
+0.06
-0.00
-0.23
-0.12
+0.68
+0.10
2022
Feb
-0.00
+0.01
-0.01
-0.24
-0.04
-0.30
-0.50
2022
Mar
+0.15
+0.28
+0.03
-0.07
+0.22
+0.74
+0.02
2022
Apr
+0.27
+0.35
+0.18
-0.04
-0.25
+0.45
+0.61
2022
May
+0.17
+0.25
+0.10
+0.01
+0.60
+0.23
+0.20
2022
Jun
+0.06
+0.08
+0.05
-0.36
+0.46
+0.33
+0.11
2022
Jul
+0.36
+0.37
+0.35
+0.13
+0.84
+0.56
+0.65
2022
Aug
+0.28
+0.32
+0.24
-0.03
+0.60
+0.50
-0.00
2022
Sep
+0.24
+0.43
+0.06
+0.03
+0.88
+0.69
-0.28
2022
Oct
+0.32
+0.43
+0.21
+0.04
+0.16
+0.93
+0.04
2022
Nov
+0.17
+0.21
+0.13
-0.16
-0.51
+0.51
-0.56
2022
Dec
+0.05
+0.13
-0.03
-0.35
-0.21
+0.80
-0.38
2023
Jan
-0.04
+0.05
-0.14
-0.38
+0.12
-0.12
-0.50
2023
Feb
+0.08
+0.17
0.00
-0.11
+0.68
-0.24
-0.12
2023
Mar
+0.20
+0.24
+0.16
-0.13
-1.44
+0.17
+0.40
2023
Apr
+0.18
+0.11
+0.25
-0.03
-0.38
+0.53
+0.21
2023
May
+0.37
+0.30
+0.44
+0.39
+0.57
+0.66
-0.09
2023
June
+0.38
+0.47
+0.29
+0.55
-0.36
+0.45
+0.06
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for June, 2023 should be available within the next several days here.
The global and regional monthly anomalies for the various atmospheric layers we monitor should be available in the next few days at the following locations:
For the last decade I’ve been providing long-range U.S. Corn Belt forecasts to a company that monitors and forecasts global grain production and market forces. My continuing theme has been, “don’t believe gloom and doom forecasts for the future of the U.S. Corn Belt”.
The climate models relied upon by the United Nations Intergovernmental Panel on Climate Change (IPCC) are known to overestimate warming compared to observations. Depending upon the region (global? U.S.?), temperature metric (surface? deep ocean? lower atmosphere?) and time period (last 150 years? last 50 years?) the average model over-estimate of warming can be either large or small.
But nowhere is it more dramatic than in the U.S. Corn Belt during the growing season (June, July, August).
The following plot shows the 50-year area-averaged temperature trend during 1973-2022 for the 12-state corn belt as observed with the official NOAA homogenized surface temperature product (blue bar) versus the same metric from 36 CMIP6 climate models (red bars, SSP245 emissions scenario, output here).
This kind of sanity check is needed because efforts to change U.S. energy policy are based upon climate model predictions, which are often wildly out of line with observed history. This is why environmentalists emphasize models (which can show dramatic change) over actual observations (which are usually unremarkable).
The paper starts out summarizing the supposed importance of their work, which is worth quoting in its entirety (bold emphasis added):
“Differences between tropospheric and lower stratospheric temperature trends have long been recognized as a “fingerprint” of human effects on climate. This fingerprint, however, neglected information from the mid to upper stratosphere, 25 to 50 km above the Earth’s surface. Including this information improves the detectability of a human fingerprint by a factor of five. Enhanced detectability occurs because the mid to upper stratosphere has a large cooling signal from human-caused CO2 increases, small noise levels of natural internal variability, and differing signal and noise patterns. Extending fingerprinting to the upper stratosphere with long temperature records and improved climate models means that it is now virtually impossible for natural causes to explain satellite-measured trends in the thermal structure of the Earth’s atmosphere.“
The authors are taking advantage of the public’s lack of knowledge concerning the temperature effect of increasing CO2 in the atmosphere, making it sound like stratospheric cooling is part of the fingerprint of global warming.
It isn’t. Cooling is not warming.
The researchers’ first mistake is to claim they are reporting something new. They aren’t. Observed stratospheric cooling, even in the middle and upper stratosphere, has been reported on for many years (e.g. here). Lower stratospheric cooling has been evident in our Lower Stratosphere (LS) temperature product for over 30 years (first published here). Dr. Richard Lindzen tells me he had references to stratospheric cooling in his 1964 PhD dissertation. So why haven’t we heard about this before in the news? Because it has virtually nothing to do with the subject of global warming and associated climate change.
So, why mention stratospheric cooling in the context of climate change?
Climate researchers have been searching for “human fingerprints” of climate change for decades, something measurable that cannot be reasonably explained by natural variations in the climate system.
I will agree with the authors that stratospheric cooling (especially in the mid- to upper-stratosphere) is probably the best evidence we have of a human fingerprint on global temperatures, at least up where there is very little air, where no one lives, and where there are no observable resulting impacts on weather down here where life exists. Water vapor remains an uncertainty here, because more water vapor would also cause cooling, and our understanding of natural variations in stratospheric water vapor is quite poor. But for the sake of argument, I will give the authors the benefit of the doubt and agree that most of the observed cooling is probably due to increasing CO2, which in turn is likely mostly due to burning of fossil fuels.
Infrared radiative cooling by water vapor and carbon dioxide has long been known to be the primary way the stratosphere (and even higher altitudes) lose heat energy (gained from sunlight absorption by ozone) to outer space. This cooling mechanism is part of the so-called greenhouse effect: greenhouse gases warm the lower altitudes of planetary atmospheres, and cool the higher altitudes. In fact, without the greenhouse effect, weather as we know it would not exist. The greenhouse effect is energetically analogous to adding insulation to a heated house in winter: for a given rate of energy input, the inside of the house becomes warmer, and the outside of the house becomes colder.
The stratospheric cooling effects of CO2 and water vapor was first described theoretically by Manabe and Strickler (1964). Adding more CO2 to the atmosphere enhances upper atmospheric cooling, lowering temperatures. The temperature effect up there is large, several degrees C, meaning it is easier to measure with current satellite methods, as the authors of the new study correctly point out.
But what then happens in the troposphere (where we live) in response to more CO2 is vastly more complex. Theoretically, adding more CO2 should warm the lower troposphere radiatively. This warming then gets mixed throughout the depth of the troposphere from convective overturning (basically, “weather”).
But just how much tropospheric warming will be caused by increasing CO2?
After 30 years and billions of dollars expended on the effort in research centers around the world, the latest crop of climate models (CMIP6) now disagree on the expected amount of tropospheric warming more than ever before. This is mostly because of the insufficiently understood effects of water, especially the response of clouds (the climate system’s sunshade) and precipitation processes (which limit the most abundant greenhouse gas, water vapor) to warming.
I consider it irresponsible to conflate stratospheric cooling with the global warming issue. Yes, strong cooling in the upper stratosphere is likely a fingerprint of increasing atmospheric CO2 (putatively due to fossil fuel burning), but for a variety of reasons, that is not reason to believe climate models in their predictions of tropospheric (and thus surface) warming trends. That is a very different matter, and the models themselves demonstrate they are not yet up to the task, now disagreeing with each other by a factor of three or more.
The Version 6 global average lower tropospheric temperature (LT) anomaly for May 2023 was +0.37 deg. C departure from the 1991-2020 mean. This is up from the April 2023 anomaly of +0.18 deg. C.
The linear warming trend since January, 1979 remains at +0.13 C/decade (+0.11 C/decade over the global-averaged oceans, and +0.18 C/decade over global-averaged land).
Various regional LT departures from the 30-year (1991-2020) average for the last 17 months are:
YEAR
MO
GLOBE
NHEM.
SHEM.
TROPIC
USA48
ARCTIC
AUST
2022
Jan
+0.03
+0.06
-0.00
-0.23
-0.12
+0.68
+0.10
2022
Feb
-0.00
+0.01
-0.01
-0.24
-0.04
-0.30
-0.50
2022
Mar
+0.15
+0.28
+0.03
-0.07
+0.22
+0.74
+0.02
2022
Apr
+0.27
+0.35
+0.18
-0.04
-0.25
+0.45
+0.61
2022
May
+0.17
+0.25
+0.10
+0.01
+0.60
+0.23
+0.20
2022
Jun
+0.06
+0.08
+0.05
-0.36
+0.46
+0.33
+0.11
2022
Jul
+0.36
+0.37
+0.35
+0.13
+0.84
+0.56
+0.65
2022
Aug
+0.28
+0.32
+0.24
-0.03
+0.60
+0.50
-0.00
2022
Sep
+0.24
+0.43
+0.06
+0.03
+0.88
+0.69
-0.28
2022
Oct
+0.32
+0.43
+0.21
+0.04
+0.16
+0.93
+0.04
2022
Nov
+0.17
+0.21
+0.13
-0.16
-0.51
+0.51
-0.56
2022
Dec
+0.05
+0.13
-0.03
-0.35
-0.21
+0.80
-0.38
2023
Jan
-0.04
+0.05
-0.14
-0.38
+0.12
-0.12
-0.50
2023
Feb
+0.08
+0.17
0.00
-0.11
+0.68
-0.24
-0.12
2023
Mar
+0.20
+0.24
+0.16
-0.13
-1.44
+0.17
+0.40
2023
Apr
+0.18
+0.11
+0.25
-0.03
-0.38
+0.53
+0.21
2023
May
+0.37
+0.30
+0.44
+0.39
+0.57
+0.66
-0.09
The full UAH Global Temperature Report, along with the LT global gridpoint anomaly image for May, 2023 should be available within the next several days here.
The global and regional monthly anomalies for the various atmospheric layers we monitor should be available in the next few days at the following locations:
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