Thanks Hanlie, But I'm not sure about the meaning of the PCS acronym..
El 31/08/2011, a las 01:25, ping <[email protected]> escribió: > Hi jpaulinin, > > I agree with Tyler that one can work in any coordinate system, as long > as you're using the same one for the gauge and the satellite data. > > I used a Transverse Mercator projected coordinate system for various > reasons that were not connected with the rainfall. > > In the PCS, the TRMM grid cells are not all of equal size and they are > no longer squares. > > If you'll need the area of the grid cells for some reason, I think > you'll have to work in a PCS. > > Regards > Hanlie > > > > On Aug 30, 9:48 pm, jpaulini <[email protected]> wrote: >> Thanks Tyler >> >> Well. I've found that the readme of TRMM file (3B42): >> >> The *grid* on which each field of values is presented is a 0.25°x0.25° >> lat./lon. (Cylindrical >> Equal Distance) global array of points. It is size 1440x400, with X >> (longitude) incrementing >> most rapidly West to East from the Dateline, and then Y (latitude) >> incrementing South to North >> from the southern edge. Quarter-degree latitude and longitude values >> are at grid edges: >> First point center (49.875°S,179.875°W) >> Second point center (49.875°S,179.625°W) >> Last point center (49.875°N,179.875°E) >> The reference datum is WGS84. >> >> It is the same datum used for gauges georeference. So I think that its >> ok to compare the x,y coordinates. >> >> I've not compared the gauges information against the satellite >> information yet, but I'll have this in mind. >> >> Thanks again for your help. >> >> On Aug 30, 2:18 pm, Tyler Erickson <[email protected]> wrote: >> >>> jpaulini, >> >>> A few thoughts: >> >>> - Precipitation is usually measured in units of length/time, so if the >>> area of the grid cell changes with latitute it doesn't matter. If it is >>> reported as a volume per grid cell (which I doubt it would be) then it >>> does >>> matter. >>> - If you are comparing point gauge data to a gridded spatial variable, >>> you will need to reproject one of the other to match projections (and >>> datums). Because reprojecting a raster will alter the cell values (by >>> some >>> interpolation method, whether explicitly known or not), I would suggest >>> reprojecting the point data. If the datums are not actually the same and >>> you assume they are, you could easily be misaligned by 10km (the error >>> varies by latitude). >> >>> - Tyler >> >>> On Tue, Aug 30, 2011 at 6:51 AM, jpaulini <[email protected]> wrote: >>>> Hi all, >> >>>> This question goes mainly for Hanlie, but everyone is welcome.. >> >>>> I'm thinking on doing some similar to you, Hanlie, comparing satellite >>>> information vs rain gauges. But I had the following doubt: >> >>>> Do you need to change the projection of the satellite information to >>>> match the projection of the rain gauges georeferenced localization? I >>>> see that you are assuming 28 sq. km grid, but depending on the >>>> latitude that you are, it can be a different surface, right? >> >>>> On Aug 15, 12:27 pm, Andy Wilson <[email protected]> wrote: >>>>> If you calculate Thiessen polygons for your 6 gauges and clip them to >>>> your >>>>> grid cell boundary then you'll be able to see how much each gauge would >>>>> contribute to the interpolated mean grid cell value. So you can just use >>>> the >>>>> areas of the polygons as weights for a weighted mean, and that should >>>> come >>>>> out the same as interpolating and then aggregating. If the position of >>>> the >>>>> gauges doesn't change, then the weights don't change so you only have to >>>> do >>>>> that once. Then you just apply your weighted mean function 730 times. >> >>>>> Does that make sense or did I misunderstand something? >> >>>>> On Mon, Aug 15, 2011 at 2:03 AM, Hanlie Pretorius < >> >>>>> [email protected]> wrote: >>>>>> Hi, >> >>>>>> I have rainfall measurements from 6 gauges that I want to interpolate >>>>>> to an areal value (a 'surface'), so that I can compare the >>>>>> interpolated gauge values to a satellite rainfall estimate that covers >>>>>> a grid cell of 28kmx28km. Two of the gauges are outside, but close to >>>>>> the border of the grid cell. Therefore, I also need to clip the >>>>>> interpolated surface to the grid cell and to get the average of the >>>>>> surface value in this clipped surface. >> >>>>>> However, for each rain gauge I have 730 values representing a daily >>>>>> measurement over two years. As output, I need a text file >>>>>> with the interpolated rainfall values for each day in my time series. >>>>>> So, I was wondering if there is an 'easy' way to get my output without >>>>>> creating 730 GIS layers? >> >>>>>> Regards >>>>>> Hanlie
