MoCo.m is a Matlab program (written using Matlab 7.0.0. (R2008b)) to estimate the standard and systematic errors of paleotemperature reconstruction based on mollusc or coral geochemistry.
Aims and experimental design were detailed in:
Carr, M., Sachs, J.P., Wallace, J.M., Exploring errors in paleoclimate proxy reconstructions: Paleotemperature from molluscs and corals geochemistry. Climate of the Past, 2012.

Tu use MoCo.m, 


1. Open Matlab and clear the workspace
2. Download MoCo.m and MoCo_param.mat and copy them in your Matlab current directory.
3. Load your reference climate timeseries as a 1 column txt file into the MATLAB current directory;
   name it "modern_monthly_timeseries.txt"
   the time series must be monthly and only contain complete years.
4. open MoCo_param.mat. The variable "param" appears in the workspace
5. param is a vector compiling all the parameters used by MoCo.m. 
   If you want to change a parameter value, you only need to change the corresponding coordinate in the "param" vector.
   Default values are indicated in [..];
   Adapt the parameter values to your experiment.

the first 7 values are related to the dataset of the proxy linear model calibraton (temperature T, proxy P, T=alpha.P + beta)
Default values correspond to the Grossmann and Ku's (Chemical Geology, 1986, v.59, p59-74) paleotemperature for aragonite (All data), with delta18O(water) expressed versus SMOW.
param(1)= alpha		[-4.34]
param(2)= beta		[19.73]
param(3)= sigma(Ti) 	[5.7]	: standard deviation of temperature values in calibration dataset
param(4)= sigma(Pi)	[1.04]	: standard deviation of proxy values in calibration dataset
param(5)= R		[0.969]	: correlation coefficient of Ti and Pi
param(6)= Ncalib	[80]	: number of calibration data points
param(7)= T0		[10.48]	: mean value of T in calibration dataset

The following 17 parameters are related to biological properties of the archive
default values correspond to Mesodesma donacium mollusc shells
param(8)= Ny 		[1]	: (integer) number of years spanned by individual records
param(9)= N		[20]	: (integer) number of shells per sample
param(10)= gap 		[1]	: How many random 1-month growth gap per year? 
param(11)= Tls		[22]	: biological superior temperature limit for skeletal growth
param(12)= Tli		[6]	: biological inferior temperature limit for skeletal growth
param(13)= gb(1) (0/1)	[1]	: is the skeleton usually growing in january? 1 for yes, 0 for no.
param(14)= gb(2) (0/1)	[1]	: idem for february
param(15)= gb(3) (0/1)	[1]	: idem for march
param(16)= gb(4) (0/1)	[1]	: idem for april
param(17)= gb(5) (0/1)	[1]	: idem for may
param(18)= gb(6) (0/1)	[1]	: idem for june
param(19)= gb(7) (0/1)	[1]	: idem for july
param(20)= gb(8) (0/1)	[1]	: idem for august
param(21)= gb(9) (0/1)	[1]	: idem for september
param(22)= gb(10) (0/1)	[1]	: idem for october
param(23)= gb(11) (0/1)	[1]	: idem for november
param(24)= gb(12) (0/1)	[1]	: idem for december

the following 3 parameters are related to the statistical gaussian noises:
param(25)= sigma(w)		[0.1]	: standard deviation of weather monthly noise (proxy unit)
param(26)= sigma(c)		[0.1]	: standard deviation of the effect of skeletal micro-heterogeneity at the microsampling scale (diagenesis, vital effect...) (proxy unit)
param(27)= sigma(a)		[0.08]: proxy analytical error (1 sigma) (proxy unit)
param(28)= sigma(s)		[1.5]: spatial std deviation of annual mean(T) in the studied area (C)

param(29)= Niter	[5000]: number of iteration of the Monte Carlo analysis

6. open and run MoCo.m
7. If you encounter a problem or need to customize MoCo.m, contact me at matthieu.carre@univ-montp2.fr
