Shahzad Sultan added an answer:How can I calculate climatological significance of trends?
Usually we use Mann-Kendall test for calculate statistical significance of analysed trends. I'm wonder, if exist same method to find out climatological significance.
Well I think I understand little bit what he is asking.
In my experience it is really hard to find the climatology significance.
But you still can find variability and it's significance. Please provide the context as well.
Wim Van den Berg added an answer:Can I use the same baseline value for the first 20 yrs for my temperature data?
I have temperature data for 29 yrs, using first 20 yrs as baseline period I have calculated anomaly for the rest 9 years, can I use the same baseline value for the first 20 yrs?
A baseline of 20 years is already quite close to the "climate" standard of 30 years.
When you use this baseline, you can easily see warmer and cooler "than average" periods in your data. When you continu to use the same baseline for the next 9 years, you still will able to analyse whether the new data have periods that are warm or cold compared to your baseline period.
The baseline is what it is: a baseline. It is not "current climate". When climate is changing, the 10-y or 20-y or 30y-averages also will change. Because of decadal slow weather phenomena and oscillations, climatologists prefer to define "climate" as the average over 30y (not 10 or 20y). Current climate should then be the weather of 1985-2014. As changes are small, climate averages are only updated every 10y; in the Netherlands we now use 1981-2010 for our current climate.Following
Ansar Khan added an answer:How can I calculate snow cover anomaly?
I have a time series of daily snow cover area for certain years. How can i calculate daily,monthly and seasonal snow cover anomalies? I want to make histogram of snow cover anomalies vs number of occurrences.
DAILY DATA: Snow falls in season. You need to make the daily data into seasonal data. The rationale here is that normal snow fall in the winter may be larger than in the summer (if it is an area where snow falls in the summer or non-winter season). Find the mean for each season to be used as a reference value.
COVERAGE AREA BY FIX REFERENCE NUMBER: Define what is considered normal area of coverage? You past data would tell you: "normally, this month has this much snow coverage." If this is the case, this is your reference coverage area value. Any value above or below, you may designate as anomaly according to Z score:
Z = (Xobs - X^) / S
... where Z = critical value from the Z table; Xobs = observed area of snow covered; X^ = predetermine reference area of coverage; and S = standard deviation of observations.
ASSUME THERE IS NO REFERENCE NUMBER: If there is no reference number, use the mean observe value as the reference, thus in the equation X ^ = mean observed value. Here, group the data set by season (months).Following
Philippe Keckhut added an answer:Was the Sudden Stratospheric Warming event of December 2012 the main cause for March 2013 anomalous weather over the North Atlantic Ocean?An unprecedented negative anomaly in the sea level pressure field over the North Atlantic Ocean was found last March in the NCEP/NCAR operational data, some months before a major SSW was also found.
Are these two events related ?
We found some connections between Major SSW occurences and temperature at surface in south of France (http://onlinelibrary.wiley.com/doi/10.1029/2012JD017631/abstract), and still this winter shows 16 days fluctuations in relation between ground and the stratospheric behavior (http://www.pole-ether.fr/etherTypo/fileadmin/files/SSW-2014-2015.pdf).
However, I agree with previous comments the challenge consists in understanding the causality; maybe quite complex.Following
Lucian Sfîcă added an answer:Where could I find daily data for Scandinavian Pattern and West Atlantic/East Russia indexes?
From here I could get only monthly data:http://www.cpc.ncep.noaa.gov/data/teledoc/scand.shtml
Thank you very much Laurent!Following
Anastasia Yanchilina added an answer:What is the most agreed on calendar date of the onset and end of the Heinrich 1 event and reference?
I am looking for the most agreed on date (onset and end) of the Heinrich 1 event, have read many papers and many give different ages.
Thank you! It is very interesting. My work is currently on the European side of things and it seems there is prior evidence that deglaciation of Europe may have started before that of North America (in the form of the Heinrich event).Following
Paul C. Lyons added an answer:What are the most reliable ways of determining the paleoclimate during the Pennsylvanian (ex Upper Carboniferous) and Permian?
We know that there were great paleoclimatic changes during the Pennsylvanian and Permian. the Pennsylvanian in Euramerica is characterized by great peat (coal) swamps, widespread changes in sea level occurred during the Pennsylvanian, continental glaciation during both periods, and great aridity particularly in the Permian.
Hi Ronny, This is a very astute answwer.I give you a thumps up on your answer. Best wishes, Paul.Following
Ansar Khan added an answer:Where do I find research studies that apply (and critique) CPC's Seasonal Climate Forecasts in agriculture?
For a literature review on advances in long-range forecasting for agriculture, I am looking for research studies that applied and critiqued seasonal climate forecasts from the US Climate Prediction Center (CPC). Can anyone help? Publications should ideally (but not necessarily) come from Agriculture? I appreciate your comments!
You can find your solution from here-under link:
Kenneth M Towe added an answer:How can I get total ozone column data over Bihar, India?
I want to use to TOC data to study how meteorological parameters affect the concentration of tropospheric ozone in Bihar.Following
Sandra Schwegmann added an answer:Where can I download data "ice thickness" (observed or reanalysis)?
I am working with models of intermediate complexity and want to compare the climatology of the results of "ice thickness" with some reanalysis or observed data.
http://www.meereisportal.de/datenportal.html (select Meereisdicke)
Here you can find sea ice thickness data for the Arctic, out of CryoSat-2 elevation measurements.Following
Paul C. Lyons added an answer:Does anyone know if the Pennsylvanian fossil-plant Annularia asteris Bell extends either below or above the Duckmantian?In the Pennsylvanian of Atlantic Maritime Canada this species has a restricted range. I am wondering if this species is a good index fossil.
Thank you Sysfrizal for your answer, which does not essentially answer the question.However, it is very instructive so I am voting you heads up on your response.Following
D. Singh added an answer:What value of Heidke Skill Score is practically good for categorical precipitation forecast? And what is the same for avalanche forecast?
my values vary form .15 to .45 for different stations over Himalaya......
HSS.is a skill score relative to random forecast. A valuev above .3 can be said relatively good score for sample of reasonable size for binary forecast. I am not aware that any one has reported HSS greater than .5 for reasonable sample size for binary forecasts when predicted event is rare like precipitation days vs no precipitation days in the Himalaya during winter. Climatological event probability can also be taken as reference for hssFollowing
Antônio Carlos Santana dos Santos added an answer:If i have mean monthly temp value for 30 lat/long pixels for a region over about 20 years how do i go about calculating SST Climatology for my region?
Can i take average of temperature at each lat/long values for each year for particular month and then calculate average of those 20 yrs values can this be considered as SST climatology for that region
the ideal would be 30 years, according to omm.Following
Craig Dremann added an answer:Who know how to move the new founded error growth mechanism in climate models?
Recently, I found a new error growth mechanism in climate models due to the incorrectly calculating the concentration of water vapor,carbon dioxide and heat etc under the pre-condition of uniform continuity condition for variables. I have developed an index to identify the non-uniform degree in the fields. But how to move this kind of error remain unknown. Any ideas are welcome to discuss here!
I love all of your questions, and want to add a very important factor that I do not think has been included in many climate models so far, especially regarding predictions of monsoon flooding and droughts--atmospheric dust, especially the Pakistan-Arabia Dust Cloud. Not including its effect can potentially cause a huge error in any climate model.Following
Marcel Severijnen added an answer:How can one download a time series of a certain variable (say, Net Longwave Radiaition) from GLDAS repository ?
I need to download meteorological forcing data from GLDAS (http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings). However, I could not find any option to download a time series. While subsetting the 3-hourly data (Noah V2.7) for my study area for one year time period, I am getting some 2920 files, each file contains 3-hourly averaged data i.e., one value for each parameter. Having these many file makes it very difficult to prepare a time series.
Is there any way to download a time series ?
There might be another way to access the desired data. Starting at the link you gave, switch to the Giovanni column and choose your file. Then, zoom in for the region you choose or fill in the coordinates of the area to be studied. Keep it a bit small, otherwise the server will take a lot of calculating time in the preprocessor. Make the choice for your parameter and select time series under "Select Visualisation". After processing you get a graph, but the data can be downloaded too. You can download the data as batch in HDF, CDF or ASC format. Even if you select one parameter, the files can be large still.Following
Milo E Hoffman added an answer:Is there a bio-climatic index including the effect of winds when T > 37C or so ?
I would like to know if any simple bioclimatic index has been proposed (as Humidex or Heat Index for mixing the effect of temperature and humidity) to include the deleterious effect of strong winds when T > 37°C or so. I know that some indices already include the cooling effect of strong winds (as net effective temperature) when T is low but I am rather interested by the warming effect of winds. I add that I am looking for a synthetic index (not as complex as UTCI for example).
Thank you in advance
My email address is:
Milo E. Hoffman <email@example.com> you will be welcomed
As I wrote above if you don't write to me to my email I will consider that you desisted..
The environmental conditions you exposed were taken into account in the design in hot humid and hot arid zones with mean Tmax 37 degC and above.
Above Givoni' s Book was reprinted in 1981.Following
Boris Winterhalter added an answer:How effective is carbon emission surtax in motor vehicles in mitigating climate change?I am looking for research articles or any write-ups on the subject of ‘Effectiveness of Carbon Emission Surtax in Mitigating Climate Change’ to help better shape my research proposal on this subject matter.
The addition of a surtax to traffic fuels is just one of many means for governments to tax people. If the tax is sufficiently high it may lower the consumption of automotive fuels and hence maybe improve the quality of air in congested urban areas, and thus have a positive effect on general health conditions.
However, its biggest effect will be in impoverishing many citizens who rely on affordable fuel in their everyday life. Regarding global climate this will have no or negligible affect, because an increase in emissions of carbon dioxide, will not have any appreciable effect on either regional nor global climate. CO2 is NOT the main climate driver - the SUN is!Following
Craig Dremann added an answer:Are Pseudomonas bacteria living on tropical trees creating monsoon rain clouds?
I have been observing that when monsoon moisture moves over certain tropical forests located in SE Asia or India, rain clouds with very long streaks form. Has anyone studied if this is caused by Pseudomonas bacteria that live on particular species of tropical trees, and if so which tree species produce the most rain clouds? Attached is a satellite image from August 2014 showing these particular clouds forming over the forests along the SW coast of India.
I got a clue about the Pseudomonas in the India-Pakistan area and the monsoon from Alexander Frater when he chased the India monsoon in his book “Chasing the Monsoon” in 1987 and wrote a diary of that year.
On June 2 he attended a meeting of Mrs. Das’ anti-deforestration committee, where he writes: …”India was once a sylvan country. When Alexander the Great invaded in 327 BC he encountered dense, close-canopied almost impenetrable forests. But peasants were already pursuing a slash-and-burn policy…Trees play a crucial role in the monsoon cycle. By SEEDING clouds they encourage the rain to fall; by trapping it they help recharge the aquifers and hold groundwater in store for the common good.”
I highlighted the word "seeding", because the Pseudomonas living on the trees creating the monsoon rainfall was unknown by science in the 1980s, but the local people knew something like cloud seeding was going on, from their observations.Following
Neil Martin Elfrink added an answer:Why can the meander river in humid subtropical climates be considered more stable than meander rivers in dry climate?
Lateral migration of meanders in arid climate is a potential threat to bridge scour. In a preliminary assessment of channel stability in a humid subtropical climate, it is possible to consider meandering alluvial rivers less dangerous to the bridges structures.
Discharging groundwater can contribute to the stability of a meandering channel. Many rivers meander simply because it is a more efficient way to drain adjoining aquifers and remove groundwater discharge from the landscape. Without a humid climate to feed groundwater discharge, there is less need for the 'effective drainage length' that a single-thread meander channel provides (Pederson, 2009).
Groundwater preferentially discharges along the concave banks of meander bends (Linderfelt and Turner, 2001). Outflowing groundwater weakens the stream bank, making it more susceptible to lateral erosion by the migrating river. Where groundwater discharge is an important factor in meander formation, streams can be pinned against the valley sides due to the larger, seepage-induced erodibility of banks aligned to the floodplain limits (van Balen et al, 08). This stabilizing “fixation effect” is likely to be more pronounced in humid regions, where groundwater flow systems are more active.
The stabilizing effect of bank vegetation has already been mentioned. High water tables can increase bank vegetation.
Linderfelt, William R., and Jeffrey V. Turner. "Interaction between shallow groundwater, saline surface water and nutrient discharge in a seasonal estuary: the Swan–Canning system." Hydrological Processes 15.13 (2001): 2631-2653.
PEDERSON, Darryll T. "GROUNDWATER EFFECTS ON EVOLUTION OF ENTRENCHED CHANNELS CAUSED BY CHANNELIZATION." 2009 Portland GSA Annual Meeting. https://gsa.confex.com/gsa/2009AM/finalprogram/abstract_160651.htm
van Balen, R.T., C. Kasse, and J. De Moor. 2008. Impact of groundwater flow on meandering: Example from the Geul River, the Netherlands. Earth Surf. Processes Landforms 33:2010–2028.Following
Chris Gueymard added an answer:How can I fill the missing climatological data?I have just worked on the dissertation thesis: "Bioclimatic characteristics of of Focsani city." I get climate data (temperature, atmospheric pressure, cloudiness and wind speed to calculate the bioclimatic indexes) for the period 2000-2012, but I am missing some values of all climatic parameters. For example, I am missing data on temperature and atmospheric pressure in a few months (in 2005 and 2006 - January and February) but data about wind speed.
Could you offer me more details about the your method work to fill the missing climatological data?
When using BSRN data (of solar radiation in particular), this most interesting study compared different techniques to derive unbiased averages when dealing with the missing data issue:
N. Pertsev added an answer:What is the role of Zonal and Meridional wavenumber in atmospheric waves?
What is their role in nonlinear interaction of waves?
What is meant by nonlinear interaction?
How do I calculate zonal and meridional wavenumbers for different waves?
What is the significance of different wavenumbers in the atmospheric waves and coupling processes?
Perhaps the question was about dimensionless zonal and meridional wavenumbers.
Then zonal wavenumber is equal to number of crests along the latitude circle, meridional wavenumber is a number of eigenvalue corresponding to one of the eigenfunctions (Hough function) for Laplace tidal equation, describing meridional structure of wave. This structure is not sinusoidal, so there is no direct analogy between the zonal and meridional wavenumbers. The role of these numbers serves almost as a role of given name and family name-they identify a wave like a person identification.Following
Flavien Gouillon added an answer:How can I compute Nakamura's effective diffusivity?
Nakamura (1996, JAS) propsed an effective diffusivity using tracer contour coordinate. How to compute this diffusivity using gridded tracer values without contour information? Is it necessary to incorporate the plot software such as Matlab to get contour information first? It seems that different interpolation schemes produce different contours.
The tracer flux method by Griffies works great indeed and it will give you the magnitude of the effective (=physical+numerical) mixing but you will lose any information on where it occurs... You can check the work by Mehmet Ilıcak (http://folk.uib.no/mil021/), the work by Florian Lemarié (http://www-ljk.imag.fr/membres/Florian.Lemarie/) which developed on the work by Winters and D'Asaro and Griffies and allow to know the effective diffusivity (mixing) in a globally and local way. Best.Following
Jose A. Guijarro added an answer:How to find a correction factor for meteorological data between neighboring meteorological stations?I aim to calculate a long term data series (1990-2011) for a newly established meteorological station (2011) to be used as lead time for modelling. The data series should be statistically derived form neighboring meteorological stations. Is there a standard procedure (as I am new to it) or am I fine with a regression analysis in the first approach?
Homogenisation of meteorological data, as my first assumption, doesn't seem to me the right procedure.
Meteorological data: air temperature, solar radiation, windspeed, relative humidity and precipitation
calculation with excel
Yes, there are many methods out there, although they often share similar underlying techniques. My R package available at http://www.climatol.eu/ tries to make things easy: It does not yield a correction factor (or term), but gives you a reconstruction of your problem series with all missing data filled in.Altitude differences are overcome by using normalized data. It is mainly conceived for monthly data, but can be applied to daily data as well.
Comparison of freely available homogenization computer packages can be seen at http://www.climatol.eu/DARE/Following
Didin Agustian added an answer:Is there any approach to predict thunderstorms at the micro community scale?
Annually, thunderstorms have destroyed housing in many areas of Thailand, particularly during February-May. Warnings have been announced from the meteorological department but less concerning among the people since they didn't know exactly where and when it would happen. Also, preparation and coping plan have not yet clearly found from not only people but also governmental sectors. Annually, the government have to pay some amount of compensated money to suffered people for fixing their housing. It would be better if we can predict the magnitude of near-real time thunderstorm at the community scale and rise public concern. Is there any approach to understand and predict thunderstorms for the micro community scale?
In wrf there is "idealized case" to run for storms, maybe be suitable for the purpose :)Following
Balakrishnan Manikiam added an answer:How can we evaluate the ratio (dy/dx) to be applied according to location in WRF-NMM Model?
I have one doubt regarding WRF-NMM Model. The calculation needed depends on location (tropics, mid-latitudes etc) for dy/dx ratio. Generally we use dy=0.95*dx, (DX is set to be slightly larger than DY to counter the effect of meridional convergence).
I need suggestions regarding this.
Waiting for your reply,
Thanks & Regards,
The dx/dy at any point depends on its distance from the centre of Earth . this is due to Earth being a spherical object. For tropics the value 0.95 is taken.Following
P.P. Sarthi added an answer:Is there any recent regional climate model for Africa?
There are a number of regional climate models for different regions. I am interested to downscale global climate models based on regional climate mode for dynamical downscaling. Any suggestion is appreciated.
You may use PRECIS model output for African region. As suggested by other CORDEX data is the best choice. We are working on Indian Summer Monsoon Rainfall. If you need more, may write mail to me on
Nalaka Geekiyanage added an answer:Does anyone know some native experimental methods for predicting drought?
Due to low rainfall, people in central Iran have some amazing ways.
These methods have been developed over several thousand years and may have a higher accuracy than the current academic methods.
For example, in some days of September and October, they put cotton on their roofs in order to check weight change due to wetting. They use this method to determine whether the current year is going to be dry or wet.
In Sri Lanka farmers use many observational predictions to predict drought. Many biological clues have higher probability to be correct. There are many locally published literature unfortunately not widely available online. refer to this link for some clue. http://archives.dailynews.lk/2004/01/30/fea02.htmlFollowing
Charles-Alexis Asselineau added an answer:What is the best programming language for solar radiation data processing?
I just programmed macros in Excel, but I realize that sometimes (when the databases are very large and I would like to calculate many specific variables ) consumes many resources and computing time. I hear of people using Python, Fortran, C++, etc., but what is the best?
I am currently working with the "Tracer", an open source Python-based ray-tracing program. The program is originally from Yosef Meller and I continue its development while I develop my PhD work.
It uses Numpy and consequently runs faster than could be expected with Python only. The big advantage is that you can do what you want with your ray-tracing because the program is completely open. I personnally use it coupled with hydrodynamic models to optimise concentrated solar receiver designs, something that is quite uneasy to do with commercial softwares for example.Following
Climatology is the study of climate, scientifically defined as weather conditions averaged over a period of time, and is a branch of the atmospheric sciences.