393 Matching Annotations
  1. Jun 2025
  2. notebooksharing.space notebooksharing.space
    1. Less studies about the hydrological characteristics and projections for the Brewster basin can be found than for the Zugspitze basin.

      But you also said above you could not found any study regarding the hydrological characteristics, only glacier projections. I am wondering what is less than nothing

    2. demonstrates a highly climate-sensitive hydrological and mass balance response due to its maritime setting and high annual precipitation.

      Have you concluded this from your analysis, or from another reference. Be more precise about your sources

    3. Shannon et al., 2019; Radic et al., 2013

      Does both studies give the same numbers? I doubt it. You should be more precise which study says what.

      Further i could not find your numbers in any of the two studies, this hints at that you made this analysis with something like ChatGPT, without checking the facts.

    4. Both basins have quite different runoff characteristics

      according to your analysis, they are similar that the peak shifts earlier in the 'melting-season' for higher temperature scenarios

    5. with both the mean and median well within the ±0.2°C tolerance range

      this is expected as we only select realizations within this range. The interesting question is, if our selection is close to our target (e.g. the 2.7°C selection deviates 0.01°C in the mean and 0.02°C in the median)

    1. Zhang et al. (2012), "A modified monthly degree-day model for evaluating glacier runoff changes in China. Part I: model development," Journal of Glaciology.

      You cite here only the model development part of the work (Part I: model development). Their is also "Part II: application", however it is only concentrating on two basins, and neither of them is Yarla Shampo. Further this paper only deals with the past and do not make projections into the future.

      As your reference is wrong, and also the text written below does not align with your reference, I suspect you used something like ChatGPT for the analysis, without checking if the facts are true.

    2. Drenkhan et al. (2018), "The changing water cycle: The eco-hydrological consequences of shrinking glaciers in the Andes," Hydrology and Earth System Sciences.

      I can not find this study with your citation. Maybe you have not correctly cited it, or it is a made up study from ChatGPT. As I also could not find any Article with Drenkhan as an Author in 'Hydrology and Earth System Sciences', also I can not find the title of the paper using a search engin.

      Without a correct reference, I can not give any points, as I can not check if you made a correct comparision

    3. Larger runoff volumes (~5–10x Yarla Shampo)

      In this analysis you should only concentrate on each basin separately, and not comparing your specific basins (this was a previous task)

    4. April–November

      what about the rest of the year? For this glacier the main runoff season is going from Sep - April, which is the more interesting period to concentrate your analysis on

    5. The 1.5°C scenario’s stable

      Actually from your plots, 1.5°C shows a decline in total annual runoff until around 2060 and stabilizes afterwards. The other scenarios have a larger total annual runoff in 2100

    6. Findings from Analysis

      Have you mixed the labels of your plot in this analysis? It looks like what you are describing under 1.5°C is shown for 4°C in the plot

    7. indicating peak water ~2060 and severe glacier depletion.

      you are mixing here seasonal (monthly) analysis, with annual runoff peak water. I do not understand how you can conclude from the first part or your sentence to this part.

    8. 2.7°C Scenario: Both basins show slight 2060 increase, reduced by 2100, suggesting peak water ~2060, less severe than 4°C. 1.5°C Scenario:

      I do not see strong differences between warming levels, regarding peak water (see also my comments above)

    9. Higher, prolonged 2060 runoff, reduced by 2100, peak water ~2060.

      for salcca also hard to see any peak water, but it looks like it is around 2020-2030 or was already passed earlier

    10. Nearly identical runoff magnitude and seasonality, wide uncertainty bands, indicating high glacier stability.

      and what about the reduction of runoff from October to December in 2060 and 2100 compared to 2020?

    11. Yarla Shampo Basin

      this is not enough, to just give bullet points about the evolution of curves. You should also write your findings down in full sentences (e.g. the seasonal peak runoff for 4°C is reached in ..., where as this peak is shifted for 1.5°C to ... .

    12. glaciers[i].sum(dim='rgi_id')[r].to_array(dim="variable").sum(dim="variable")

      the runoff is already available in the dataset and you do not need to recalculate it

    13. closely aligning with their respective targets, especially for 4°C and 2.7°C. The slight positive deviation for the 1.5°C target is minor but notable

      Here it would be good to also add some numbers you have found (e.g. for 4°C the selection has an mean temperature of 4.06°C and a median tempreture of …)

  3. notebooksharing.space notebooksharing.space
    1. largest number of realizations,

      Nice analysis. One thing you could have look at is the spread in precipitation of the different realizations, as we only looked at temperature for grouping.

    2. Annual runoff at three time steps (e.g. 2020, 2060, 2100), showing median and interquartile range, one plot per temperature scenario

      Their I wanted you to plot the monthly runoff evolution as done in the second plot of this section: https://edu-notebooks.oggm.org/oggm-edu/glacier_water_resources_projections.html#monthly-runoff

      However, after reading my instructions and seeing your plot, I completely understand why you created this plot. I will try to be more clear the next time.

    3. 2000,2100

      nice to show also the historical runoff from 2000 to 2020, however it would be good to use a different color for this period (e.g. black), to visually distinguish between historical and future data.

    4. 1%

      given absolute numbers for temperature deviations is easier to understand, as a 1% deviation of 2.7°C is a different absolute number than 1% deviation of 4°C. (and how do you express a deviation from 0°C in %?)

    5. Thus we do not need to further reduce the number of realizations for any of the target temperatures by reducing the ranges.

      This is not true generally. If for example all realizations are below the target temperature, you will also not get closer by reducing the ranges. If you want to use such statements you also should analyze the distribution of the available realizations.

    1. with different timing and magnitude for the 3 scenarios analysed. After that, scenarios converge again until 2050, when warmer scenarios show a larger decline in annual runoff. The runoff peaks also shift about 1-2 months earlier, more for the warmer scenarios

      for what is this sentence here?

    2. the missing regional forcing calibrated by local measurements

      I do not understand this sentence, what is different between your model and the one from the paper?

    3. Rofental Basin

      you should try to bring all studies together, and do not first compare study 1 with our findings, followed by study 2. Instead you should first concentrate on one aspect (e.g. we found that peak runoff ..., study 1 and study 2 found the same, but...)

    4. August runoffs will decrease further, and also July runoffs will start to decrease for the 2.7°C and 4°C scenarios As a result of this shift, June (and for 4°C warming also May) runoff show an increase towards the end of the century

      You should bring this closer together in the text. You just mention above in bullet points what the study says and here you mention what you found. A sentence connecting the two would be nice (e.g. Rets et al. (2020) found ..., which is the same as we found ...)

    5. Context and literature

      general comparisons good, but bullet points alone are not a good structure for a discussion section. You should use full sentences and be a bit more specific what you are talking about

    6. sns.color_palette("rocket")[i]

      not a mistake: but if the data is grouped for different temperatures it is often a convention to use blue for colder temperatures and red for warmer temperatures, to make it easier to understand the plots

    7. df_runoff = ds_all[basin_id][temp_scenario][runoff_vars].sum(dim='rgi_id').median(dim='gcm_scena

      runoff is already provided in the dataset, you do not need to recompute

    8. higher temperature scenarios (e.g. 4°C) lead to faster glacier volume and area loss compared to lower temperature scenarios (e.g. 1.5°C)

      but 2.7 and 4 are almost indistinguishable, this is not discussed

    9. most models, which might offer better statistical reliability while the 4°C scenario is supported by the fewest.

      also provide the exact numbers in your discussion. "most" and "fewest" is not quantitative

    1. precipitation shows an increasing trend

      it reads as you have analyzed the precipitation trend of our used climate data. If so, show a plot, if not be clear about what you have done and what not.

    2. very similar

      similar to what, are they using the same temperature scenarios as we do? I do not think so, therefor you need to be precise what are you comparing here

    3. Contextualize

      Good comparisons, however your analysis should be able to be understood without reading the papers (e.g. if you use special terms from the papers, define them or use your own words instead of those terms)

    4. Strasser, U.,

      You are not using this citation in your comparison below, you only mention that it exists but do not compare it. either you should not mention this citation here, or you should include it in your analysis

    5. reflecting earlier snowmelt and glacier melt as a consequence of rising temperatures

      also reflecting that at some point no glaciers are left which can melt later in the season

    6. runoff.

      Another interesting finding would be that the seasonal peak is shifting to earlier months in Rofental, whereas their is no change of the seasonal runoff peak for Langtang visible.

    1. 4°C and 2.7°C. The slight positive deviation for the 1.5°C target is minor but notable

      Here it would be good to also add some numbers you have found (e.g. for 4°C the selection has an mean temperature of 4.06°C and a median tempreture of ...)

  4. Jan 2025
  5. notebooksharing.space notebooksharing.space
    1. However, other factors also influence temperature changes, such as variations in solar energy during cycles like the Sun’s 11-year cycle, volcanic eruptions that release particles to cool the planet by reflecting sunlight, and land use changes like deforestation, which alter how much heat the Earth absorbs or reflects.

      references?

    2. The annual cycle is related to seaonal cycle of vegetation abosrbing CO2 when the pertinent hemisphere is in summer through photosynthe

      Correct, but could you provide a reference for this?

    1. Question: What was the CO2 concentration in the atmosphere in the pre-industrial era? Compute the annual increase in CO2 concentration (unit: ppm per year) between 1980 and 1985 and between 2016 and 2021.

      You have not answered this

    1. Describe the relationship between global temperatures and CO22_2 concentrations. Beside CO22_2, name three processes that can influence temperature variability and change at the global scale.

      Correct, but could you find some references for the other processes you are mentioning?

    2. etween 1980 and 1985 the average CO2-Concentration increased by around 6.6 ppm as computed below. This means an annual increase of around 1.33 ppm per year. In the time between 2016 and 2021 the concentration increased by about 11.6 ppm which corresponds to an annual increase of around 2.32 ppm every year. It is important to keep in mind, that this is only a simple average over the years. It may be, that the increase was stronger in one year than in another, but the almost linear graph from the plot suggests, that our method is appropriate.

      Where is the calculation of these values. This should also be included in the notebook.

    3. n the preindustrial area (1750), before the industrial revolution changed the life of humans on the planet, a CO2-Concentration of 278ppm is estimated, according to ice-core measurments.

      Correct, but please provide a reference

    1. El Niño leads to global warming (due to heat release from the Pacific Ocean). La Niña causes global cooling.

      Important to give references for such statements

    2. Describe the relationship between global temperatures and CO22_2 concentrations. Beside CO22_2, name three processes that can influence temperature variability and change at the global scale.

      Correct, could you find references

  6. notebooksharing.space notebooksharing.space
    1. Describe the relationship between global temperatures and CO22_2 concentrations. Beside CO22_2, name three processes that can influence temperature variability and change at the global scale.

      Correct, could you find references for the three other processe?

  7. notebooksharing.space notebooksharing.space
    1. In the "annual average time series of global CO₂ concentration and global 2m temperature" plot, we can clearly see that the global temperature increase is directly proportional to the rise in atmospheric CO₂ concentrations.

      Correct, but you can not see this in the plot shown above

    2. What was the CO22_2 concentration in the atmosphere in the pre-industrial era? Compute the annual increase in CO22_2 concentration (unit: ppm per year) between 1980 and 1985 and between 2016 and 2021.

      Correct

    3. plot the annual average timeseries of global CO22_2 concentration and of global 2m temperature from ERA5 on the same plot (using a secondary y axis for temperature).

      the temperature in the plot does not use the same timestamp as the co2 concentration, therefore you can not see their relation

    4. plot the monthly global CO22_2 concentration as a function of time.

      You should have plotted on the x-axis the date and on the y-axis the co2 concentration. You plotted the mean monthly concentration.

    1. he anual cycle is caused by the seasons which influence the plants photogenysis. As Mauna loa is on the northern hemisphere it has high concentrations in the start of spring before photogenysis picks up again

      Correct, could you find a reference for this?