Questions related to Climate Reconstruction
I would like to know your opinion about what are currently the greatest unsolved problems or opportunities for further research in palaeoclimatology.
Greetings, I was willing to reconstruct paleo-temperature of Last Glacial Maximum (LGM) from the oxygen isotope ( δ18O) or Mg/Ca ratio. Therefore. I obtained data from the Pangaea site and arranged them in 3 columns depth, time (Kyrs BP), parameters. The δ18O data were calculated based on G.ruber and benthic, planktonic foraminifera. While the Mg/Ca ratio was extracted from H. elegans.
Now, I am wondering whether I could use any equation(s) that would take the previously mentioned parameters into variables and reconstruct paleo-temperature. I studied some literature where I found the following equation published by McCrea (1950), which was subsequently revised by Epstein et al. (1953):
T(°C) = 16.5− 4.3(δ18Occ − δ18Osw) + 0.14(δ18Occ−δ18Osw)
where δ18Occ is the measured value in calcium carbonate and δ18Osw is the isotope ratio of the water from which it is precipitated. The slope of this relationship means that a 0.23‰ increase in δ18Occ corresponds to a difference of about 1°C (Paul N. Pearson, 2012). I understand that I would put the Isotope ratio's column in the δ18Occ variable, but what should I do about the δ18Osw variable ? As I am planning to derive the paleo-temperature of the LGM, I was wondering that if there's any standard δ18Osw value of that time or do I need separate dataset for that too?
Regarding the ratio of the water, there was something such as conversion of VSMOW/SMOW to VPDB/PDB scale, I would be grateful if someone clarified these with their expertise. Although I do believe my data is already converted to PDB when I downloaded from Pangaea. It also needs to be mentioned that these dataset are from cores in Bay of Bengal. Finally, I welcome any suggestion, advice or tips to reconstruct temperature from the data I gathered. If my approach is wrong, it would be a great help to me if you could me point me out to the right directions or the right equations. I am attaching some screenshot here as well. Thanks in advance.
I am planning to work with open source paleo-climate data for a thesis, so far the only source for these kind of data i know is : https://www.ncdc.noaa.gov/paleo-search/
Is there any other sources that provides a good amount of paleo-climate data or this the most available source currently ?
With that being said, would any paleo-scientist like to tell me what are some of the special things that you take into consideration while you are dealing with such data, especially because they are from past and mostly climatic reconstruction or proxies ? If you went through that link, you'd see most of them are in (.txt) files, therefore what would be some potential software or programming languages you have used or planning to use, that would be helpful in this regard ? or you'd process it like any usual data (e.g. netCDF are very popular in climatic studies but unfortunately i don't know whether (.nc) files exists for paleo-climate data)?
Any advice or suggestions, in addition to my question would be deeply appreciated.
I came through to the Canadian climate GCM data download portal (http://www.cccma.ec.gc.ca/data/cgcm4/CanESM2/rcp26/day/atmos/hfls/index.shtml ) in which some ensembles are given. I am not sure which one should be used. I am working on impacts of temperature changes and will be using downscaling techniques.
Urgent - trying to find a program that will convert a scanned pollen diagram into either graphs, a digital, clearer pollen diagram or data tables.
Backround research on climate reconstructions around pluvial lakes in the Great Basin, I am finding that a loose correlation between later glacial maxima for alpine glaciers in the southerly portions of western North America, as the continental ice sheets retreat. The alpine glacier retreats then correspond loosly in time to the rise in pluvial lake levels. How does this all relate to the rising sea levels with the retreat of continental ice, especially LIS? Does this increase in sea level in the Pacific have relation to what seems like an increase in moisture seen from the Sierra Nevadas, across the Great Basin, to the southern edge of the Yellowstone ice cap?
Are there any studies that link these? I find it interesting, and relates to my research via lake level to the Chewaucan Basin and the local biome ~15-9 ka.
I would like to see if anyone has studied the publication rate of climate change research in the biological sciences. I have found only one article by Pedersen et al. 2015 that shows the doubling of climate change research in the Nordic Region. I've also checked the IPCC 2014 report and found nothing. Thank you so much for you help.
As I am not familiar with ECMWF data. I have obtained daily Climate Reanalysis data from ECMWF ERA-Interim. I have converted it to the text file and excel file format. The data obtained for various parameters are as follow;
Temperature, Min, Max Temp. Solar radiation, DewPoint Temp, SnowDepth (Time:12 Step: 03), Precipitation (Time: 00 & 12 Step: 12), Sunshine duration(Time: 00 & 12 Step: 09).
The required input file format of the model, for example, is as;
2012--365--- and so on.....
The data obtained is not on daily format rather is a lot of data on time basis.
Would anybody help how to process this data to get daily data from day 1 to day 365 per year for each parameter?
Your guidance/help in this regard will highly be appreciated.
Thank you and regards,
I am dealing with the various climate proxy data (e.g. geochemistry, pollen, isotopes, etc.) from various locations. I would like to compare statistically (component analysis) all the proxy data, but the problem is missing points.
I am not an expert in the statistical analysis. Is it possible to fill the missing values with the median values and then do a component analysis?
Any help would be greatly appreciated.
Generally, it is warm/wet during MCA and cold/dry during LIA in monsoonal Asia. Many proxies show apparent different conditions of these two stages, i.e. lake sediments, speleothem. Questionablly, the proxies mainly relate to precipitaion changes and water vapor sources of a certain area. But the interpretations of speleothem isotopic records are still unclear. Thus we should conceivably consider impacts of water sources on isotope records and rainfall changes.
Some plant species living in particularly strong environmental stress show different level of 13C absorption as opposed to individuals from the same species living in normal conditions. May this have a reflection also on 14C content even beyond standard laboratory isotopic fractionation correction?
I am interested in the theories and evidence linking the AMO to Atlantic Meridional Overturning Circulation, solar forcing and possibly other causes in explaining this phenomenon. Is there literature reviewing these mechanisms? Do you have links to relevant net sources.
Some years ago I did a search and noticed that such a software were available only for Mac environment. Now I would like to know about any experiences with free multi-taper technique for PC users, preferably in R but not necessarily. I am working on long proxy climate time series.
I'm interested to know more about this field. Can someone help me to know more about paleoclimatology methods to reconstruction of past climate of the Earth?
I am looking for information on advanced courses in English that would be open for graduate or post-graduate level foreign students. This would be interesting for students specializing on climate reconstruction, past climate dynamics, current issues of climatology, and so on. Is there any web-sites listing such activities?
Proxies generally record frequency-dependent climate signals. I would think that this frequency aspect is perhaps handled by careful selection of proxies or by e.g. choosing proper indexing methods if tree-rings are concerned. Do any of the approaches called climate field reconstruction (CFR methodologies) have clear advantages in this respect? Opinions, views and relevant references welcome!
Transforming proxies into principal components (PCs) and using these PCs in building transfer models is usual in climate reconstruction. A common procedure before PCA is decentering (i.e. subtracting the mean) a group of e.g. tree-ring chronologies before principal components analysis. However, PCA and the resulting PCs seem to be sensitive to decentering. Presuming PCA is based on correlation matrix, what is the rationale behind this? Can anybody elaborate on this or point to a reference?
who have the skill that using the carbon isotope composition of loess sediments reconstruct the Precipitation, or who have the article papers that related to that knowledge.
I am seeking an advice on how to read CMORPH precipitation daily data and generate howmoller graphics. The detail specification is a high resolution 8km precipitation data at daily temporal scale. It's possible to use GrAds?
While substage MIS 5e (~120 ka) is considered to have been globally warmer than the second half of the Holocene, and sea-level was several meters above present datum (almost worldwide), a few regions seem to have experienced cooler SST than nowadays. Documenting and understanding this paradox is important for climate modeling efforts in the context of the on-going global warming, especially for these particular regions (eg. S Peru and N Chile).
I am also interested in evidence for Anthropocene cooling trends in coastal regions (like in Central Peru and N Chile).
I am trying to implement statistical analysis on some data. I have the NCEP2 data set for 4 climate variables and the ERA40 data set for the same variables for a region. Given a grid of 9x10, I have 90 locations and so I have 360 variables for a particular day. I have 12000+ such days. I've implemented PCA on this. What I cannot understand is :
- How can I get the predicted values of more than one location when I use all variables as the predictors for any location?
- Am I doing this right or am I missing something?
I don't need the exact implementation. I just want to be clear about how the data flows from the grid format to the output. I'm trying to implement the following papers:
Could some colleagues please suggest a place where I can find high resolution
climate simulations for South America?
I'm looking for something with a resolution of 0.25 x 0.25 or better, covering
southern South America.
I'm collaborating on a project to update the wind hazard map of Argentina using
climate simulations. I'd appreciate any tips regarding high resolution climate simulations to complete the project.
Augusto Sanabria, MSc. Ph.D
Facultad de Ingenieria (http://ing.unne.edu.ar)
Universidad Nacional del Nordeste (UNNE) Resistencia, Argentina
Can anyone help or provide data about the temp rates and climate change in the middle eastern countries, included Iraq, during the period between 1990 to the present?
I am looking for what changes in climate happened there, in particular changes in the temperature and humidity, which are related to drought.
From my study site I have only 6 years of instrumental records of precipitation and temperature. But I have time series data from 14 nearby climate stations (the farther is 40 Km) and I would like to make one for this region. All climate data are monthly. The time series are from 1963 to 2013. The problem is that not all the series are complete, and the available data in the series are from 10 to 50 years. Some series have only the last, intermediate or the first decades. But the mean monthly values from my study site have a high correlation with these series (r=0.70 to 0.97). I tried the Jones & Hulme 1996 method but it works with a common time period of 20-30 years with continuous values, and with the missing years of my time series I can't apply this method.
Any suggestions are useful.
Significant reorganization of atmospheric circulation, intense uplift of Himalaya-Tibetan Plateau, Significant mammal and floral changes in this time period, How to understand their interaction? I want to know what time witnessed the strongest change, 25 Ma, 23 Ma or 20 Ma? Welcome to discuss.
Most researchers pay attention on temperature and CO2 alternation during life evolution, I mean geological periods, like Paleozoic, Mesozoic and Cenozoic. Is there any authentic data expressing other environmental factors like light, water, and chemical atmosphere component druing the geological periods?