Need urgent help in multivariate analysis

Hi, i need urgent help to validate this data. I'm trying to used meshgrid to plot but the figure is somehow kind of weird. please help..thanks.;

x1=[28.1000000000000;28.3100000000000;28.7700000000000;29.9200000000000;29.9800000000000;29.7300000000000;29.4500000000000;29.4500000000000;29.3000000000000;30.1900000000000;29.0300000000000;28.8300000000000];

x2=[15.9800000000000;2.93000000000000;0.930000000000000;1.46000000000000;3.89000000000000;2.57000000000000;5.66000000000000;9.92000000000000;8.57000000000000;4.45000000000000;37.9700000000000;34.3300000000000];

y=[28.2000000000000;29.0800000000000;30.5300000000000;32.2100000000000;32.3000000000000;32.1300000000000;31.4200000000000;31.4400000000000;31.0100000000000;31.4200000000000;29.3700000000000;28.6800000000000];

X = [ones(size(x1)) x1 x2 x1.*x2];

b = regress(y,X) % Removes NaN data

b =

-9.5805

1.3901

-1.3429

0.0449

>> [~,~,~,~,stats] = regress(y,X)

stats =

0.9269 33.8380 0.0001 0.2126

>> sin(X)

ans =

0.8415 0.1735 -0.2687 0.2082

0.8415 -0.0357 0.2100 0.9542

0.8415 -0.4756 0.8016 0.9986

0.8415 -0.9972 0.9939 -0.2947

0.8415 -0.9909 -0.6805 -0.3740

0.8415 -0.9934 0.5410 0.8457

0.8415 -0.9229 -0.5836 -0.1816

0.8415 -0.9229 -0.4752 0.0241

0.8415 -0.8551 0.7544 -0.2245

0.8415 -0.9411 -0.9658 0.6765

0.8415 -0.6858 0.2676 0.4168

0.8415 -0.5275 0.2256 -0.1318

>> y = sin(X);

X = linspace(0,0.5*pi);

>> y = X';

z = X .* exp(-X.^2 - y.^2);

surf(X,y,z)

>> xlabel('air temperature')

ylabel('total rainfall')

ylabel('total rainfall')

zlabel('water temperature')

view(50,10)

[Aquatris]

What do you mean by weird? what is the exact question you have? Plot look ok.

And next time you might want to format your question correctly to help others understand your problem.

x1=[28.1000000000000;28.3100000000000;28.7700000000000;29.9200000000000;29.9800000000000;29.7300000000000;29.4500000000000;29.4500000000000;29.3000000000000;30.1900000000000;29.0300000000000;28.8300000000000];
x2=[15.9800000000000;2.93000000000000;0.930000000000000;1.46000000000000;3.89000000000000;2.57000000000000;5.66000000000000;9.92000000000000;8.57000000000000;4.45000000000000;37.9700000000000;34.3300000000000];
y=[28.2000000000000;29.0800000000000;30.5300000000000;32.2100000000000;32.3000000000000;32.1300000000000;31.4200000000000;31.4400000000000;31.0100000000000;31.4200000000000;29.3700000000000;28.6800000000000];
X = [ones(size(x1)) x1 x2 x1.*x2];
b = regress(y,X)    % Removes NaN data

b = 4x1

-9.5805 1.3901 -1.3429 0.0449

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[~,~,~,~,stats] = regress(y,X)

stats = 1x4

0.9269 33.8380 0.0001 0.2126

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sin(X)

ans = 12x4

0.8415 0.1735 -0.2687 0.2082 0.8415 -0.0357 0.2100 0.9542 0.8415 -0.4756 0.8016 0.9986 0.8415 -0.9972 0.9939 -0.2947 0.8415 -0.9909 -0.6805 -0.3740 0.8415 -0.9934 0.5410 0.8457 0.8415 -0.9229 -0.5836 -0.1816 0.8415 -0.9229 -0.4752 0.0241 0.8415 -0.8551 0.7544 -0.2245 0.8415 -0.9411 -0.9658 0.6765

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y = sin(X);
X = linspace(0,0.5*pi);
y = X';
z = X .* exp(-X.^2 - y.^2);
surf(X,y,z)
 xlabel('air temperature')
 ylabel('total rainfall')
 ylabel('total rainfall')
zlabel('water temperature')
view(50,10)