Monday, July 19, 2021



Not 2 Green  |  How Hot was it ? 


United States Climate Reference Network
USCRN regional NorthWest USA  data,  July 1 thru July 7 2021


                                  USCRN - John Day OR site - courtesy NOAA

My question has always been " how hot is it " ?  Thus, when the Pacific Northwest experienced it's once in a thousand years, possibly influenced by " climate change " heatwave I was left wondering what did actually occur across the region.  Unlike the media, I went into the USCRN's website to look at data for 6 Northwest field stations, 3 in Washington, 1 in Idaho and 2 in Oregon.  I selected a one week period, starting on July 1, 2021 to overlap the days of this heat event.  Each station collects a wealth of surface data, and there are many reference notes located in a README text file :  README.txt, located in the data file directory.  Perhaps, an easier introduction for the reader is to go to the USCRN home page and follow certain links to reach the page that lists all stations in the network.  So, go to the station directory now and look, or wait until you have had a chance to digest the extracted data I show below, for these 6 stations.

On the above page, under the Datasets column, select More Data
select the " Current observations " choice at page top
Scroll down to the three Washington state sites ( or ID or OR ), and select  WA Spokane 17 SSW ( or other)
On the Sensor data page, select, under SummarizeThis Month    
On the Monthly Summary page, first ( radio button )  Display Units as  US Customary ( unless you want degrees C )
See in the Temperature column, the Temp data for Day 1 ( July 1st ) thru 7

I have included the relevant sections from the README text file here.  Link to the entire file is below.

E.  There are no quality flags for these derived quantities. When the
            raw data are flagged as erroneous, these derived values are not
            calculated, and are instead reported as missing. Therefore, these
            fields may be assumed to always be good (unflagged) data, except
            when they are reported as missing.
F.  The daily values reported in this dataset are calculated using
            multiple independent measurements for temperature ....  .
            USCRN/USRCRN stations have multiple co-located temperature sensors
            that make 10-second independent measurements which are used to
            produce max/min/avg temperature values at 5-minute intervals.
G.  On 2013-01-07 at 1500 UTC, USCRN began reporting corrected surface
            temperature measurements for some stations. These changes  
            impact previous users of the data because the corrected values
            differ from uncorrected values. To distinguish between uncorrected
            (raw) and corrected surface temperature measurements, a surface
            temperature type field was added to the daily product. The
            possible values of the this field are "R" to denote raw surface
            temperature measurements, "C" to denote corrected surface
            temperature measurements, and "U" for unknown/missing.

Day       Max T(F)  time  Min T(F)  time ( local standard time 24 hr )
*** infrared surface temperature, in degrees F.
WA = Washington,  ID = Idaho,  OR = Oregon

WA Spokane 17 SSW                                        WA Darrington 21 NNE
US Fish & Wildlife Service, Turnbull NWR

1 July    92.9     14:25     59.6     23:15            1 July    73.9     13:45     62.1     05:20
2            90.3     15:10     50.6     23:40            2           77.5     13:55     61.5     04:00
3            93.4     14:35     45.1     03:35            3           84.1     14:10     57.3     23:50
4            91.0     14:35     45.3     04:05            4           83.6     14:00     52.9     04:50
5            90.8     15:55     44.8     03:45            5           79.9     14:05     53.2     03:55
6            94.7     14:15     44.3     03:20            6           83.3     14:55     53.5     04:05
7            92.5     14:00     50.1     03:20            7           72.2     16:05     55.1     03:35

WA Quinault 4 NE                                            ID Murphy 10 W
Olympic National Park

1 July    67.3     16:30     59.3     00:35            1 July    97.1     13:30     62.1     04:10
2            71.4     14:30     56.4     23:50            2           96.5     14:55     60.9     04:10
3            75.3     15:25     54.7     01:10            3           99.5     14:10     63.4     05:40
4            68.1     15:50     55.5     21:00            4           96.4     15:30     61.7     05:25
5            70.6     15:20     51.8     22:55            5           94.5     14:00     63.8     03:35
6            78.9     14:15     53.6     00:05            6           99.8     15:20     57.9     05:40
7            65.8     14:35     53.1     00:00            7           97.2     14:20     62.6     05:00

OR Corvallis 10 SSW                                       OR John Day 35 WNW
 John Day Fossil Beds Nat'l. Mon.

1 July    75.3     18:05     61.0     03:45            1 July  101.1     16:15     74.4     04:20
2            85.6     16:10     59.2     03:15            2         100.9     15:30     62.0     04:30
3            88.0     15:25     53.8     05:15            3         100.7     16:20     59.8     04:45
4            86.4     14:45     53.2     05:00            4           99.5     16:10     55.8     04:40
5            87.5     15:45     49.5     04:55            5           99.0     15:50     56.5     05:10
6            92.0     15:05     52.1     04:40            6         104.3     16:00     56.4     04:05
7            76.2     16:05     54.1     02:10            7           95.2     14:40     67.3     23:40

Note F above, may help to  explain  as to why the mean and average T may not be equal for the FIRST ( and only first ) day of any month ( if you look at the FULL data set ).  Otherwise see the README file for all sorts of detailed information.

Going forward the USCRN will be the gold standard to answering a very important question, for the 48 contiguous states, Alaska and Hawaii.

As a part of the broader NCDC/NCEI transition, the USCRN website is migrating to  .


Thursday, January 2, 2020


Since we don’t know future atmospheric CO2, volcanic eruptions, and whatever “ other climate drivers ” should be put into the IPCC models,  why are we using these models to set policy ?

1992  IPCC Supplement, Policymaker Summary of Working Group I
          (First Scientific Assessment of Climate Change)
Section 5.2, page 75

Although  scientists  are  reluctant  to give a single best estimate in this range,  it is necessary  for  the  presentation  of climate predictions  for  a choice of best estimate to  be  made. Taking into account  the model  results,  together with  observational  evidence  over  the  last  century  which is suggestive  of  the  climate  sensitivity being  in the  lower half of  the  range,   (see   section: " Has  man  already  begun  to change global climate ? ")  a value of climate sensitivity of 2.5°C  has  been  chosen  as  the  best  estimate ( for a doubling of CO2 ).
In   this  Assessment,   we  have  also  used  much  simpler  models,  which  simulate  the  behaviour  of  GCMs,   to  make  predictions  of  the  evolution  with  time  of global temperature  from  a  number  of emission  scenarios.   These  so-called  box-diffusion  models  contain  highly simplified  physics  but  give similar results  to GCMs  when  globally  averaged. 

1996  IPCC Second Assessment Full Report, The Science of Climate Change,
          Section 6, page 24

In particular, to reduce uncertainties further work is needed on the following priority topics:
Representation of climate processes in models, especially feedbacks associated  with  clouds,  oceans,  sea  ice  and  vegetation,  in  order  to improve projections of rates and regional patterns of climate change.

2001  IPCC Third Assessment Report, The Scientific Basis
          14 - Advancing Our Understanding
Page 774, 2nd column, top : Balancing the need for finer scales and the need for ensembles

In sum, a strategy must recognize what is possible. In climate research and modelling, we should recognize that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system’s future possible states by the generation  of  ensembles  of  model  solutions.

2007  IPCC Fourth  Assessment Report, The Physical Science Basis
          8  Climate Models and their Evaluation
Frequently Asked Questions  8.1,   Page  601  bottom of 1st column

Nevertheless, models still show significant errors. Although these  are  generally  greater  at  smaller  scales,  important  large-scale  problems  also  remain.  For  example,  deficiencies  remain  in  the  simulation  of  tropical  precipitation,  the  El  NiƱo-Southern  Oscillation  and  the  Madden-Julian  Oscillation  (an  observed  variation  in  tropical  winds  and  rainfall  with  a  time  scale  of  30  to  90  days).  The  ultimate  source  of  most  such  errors is that many important small-scale processes cannot be represented  explicitly  in  models,  and  so  must  be  included  in  approximate  form  as  they  interact  with  larger-scale  features.  This is partly due to limitations in computing power, but also results  from  limitations  in  scientific  understanding  or  in  the  availability of detailed observations of some physical processes. Significant uncertainties, in particular, are associated with the representation of clouds, and in the resulting cloud responses to climate change. Consequently, models continue to display a substantial range of global temperature change in response to specified greenhouse gas forcing  (see Chapter 10). Despite such uncertainties, however, models are unanimous in their prediction of substantial climate warming under greenhouse gas increases,  and  this  warming  is  of  a  magnitude  consistent  with  independent estimates derived from other sources, such as from observed climate changes and past climate reconstructions.

2013  IPCC Fifth Assessment Report, The Physical Science Basis
          9 Evaluation of Climate Models
Frequently Asked Questions  9.1,  Page 824, 3rd paragraph

Are Climate Models Getting Better, and How Would We Know ?
Climate models of today are, in principle, better than their predecessors. However, every bit of added complexity, while intended to improve some aspect of simulated climate, also introduces new sources of possible error ( e.g., via uncertain parameters ) and new interactions between model components that may, if only temporarily, degrade a model’s simulation of other aspects of the climate system. Furthermore, despite the progress that has been made, scientific uncertainty regarding the details of many processes remains.

Wednesday, November 13, 2019

Not 2 Green  |  is nothing new

The Polar Vortex  is nothing new - in fact, it's thought that the term first appeared in an 1853 issue of E. Littell's  Living Age .   NOAA

NOAA Speaks

Rather, cold-air outbreaks are most directly related to transient, localized displacements of the edge of the tropospheric polar vortex that may, in some circumstances, be related to the stratospheric polar vortex, but there is no known one-to-one connection between these phenomena.

Learn More

NASA Graphic example

if-the-polar-vortex-is-due-to-global-warming-why-are-US-cold-waves-decreasing ?