diff --git a/DESCRIPTION b/DESCRIPTION
index 4ef19ef..c1ae61b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: transformeR
 Depends:
-    R(>= 3.5.0)
+    R(>= 3.5.0) 
 Imports:
     abind,
     akima,
@@ -22,8 +22,8 @@ Suggests:
     visualizeR
 Type: Package
 Title: A climate4R package for general climate data manipulation and transformation
-Version: 1.7.1
-Date: 2020-01-31
+Version: 1.7.2
+Date: 2020-02-14
 Authors@R: c(person("Bedia", "Joaquín", email = "bediaj@unican.es", role = c("aut","cre","dtc"), comment = c(ORCID = "0000-0001-6219-4312")),
              person("Jorge", "Baño Medina", email = "bmedina@ifca.unican.es", role = "ctb"),
              person("Ana", "Casanueva", email = "ana.casanueva@unican.es", role = "ctb"),
diff --git a/NEWS b/NEWS
index 4a19ea6..dfc9b40 100644
--- a/NEWS
+++ b/NEWS
@@ -88,3 +88,8 @@ See the [Releases section](https://github.com/SantanderMetGroup/transformeR/rele
  * Allow type = NULL in `dataSplit' function.
  * Add zenodo badge in documentation
  * Other minor documentation issues.
+
+## 1.7.2 (14 Feb 2020)
+ * Update longname attribute in cluster-type grids
+ * Other minor changes
+ 
diff --git a/R/clusterGrid.R b/R/clusterGrid.R
index 78f250a..a6da124 100644
--- a/R/clusterGrid.R
+++ b/R/clusterGrid.R
@@ -86,7 +86,7 @@ clusterGrid <- function(grid,
                         ...) {
  
   type <- match.arg(type, choices = c("kmeans", "hierarchical", "som", "lamb"))
-  #browser()
+  
   if (is.null(newdata)){
     #Checking grid dimensions
     if (!is.na(suppressMessages(getShape(grid, "member"))) && getShape(grid, "member") > 1){
@@ -105,9 +105,9 @@ clusterGrid <- function(grid,
         stop("For lamb, only 'psl' variable is required Use subsetGrid to extract it")
       }
       if (!is.null(centers)) {
-        message("Lamb WT was choosen, so the number of clusters will be forced to 27. Arg. 'centers' will be ignored.")
+        message("Lamb WT was choosen, so the number of clusters will be forced to 26. Arg. 'centers' will be ignored.")
       }
-      centers <- 27
+      centers <- 26
       arg.list <- list(...)
       arg.list[["grid"]] <- grid
       lamb.wt <- do.call("lambWT", arg.list)
@@ -158,24 +158,38 @@ clusterGrid <- function(grid,
     if(is.null(attr(grid, "wt.index"))){
       stop("'grid' is not a clustering object.")
     }
-    #Checking grid dimensions for newdata and var.names/n.mem matches with grid
-    if (getShape(newdata, "member") > 1){
+    if (!is.na(suppressMessages(getShape(newdata, "member"))) && getShape(newdata, "member") > 1){
       message("Clustering analysis will be done after Ensemble mean...")
       newdata <- suppressMessages(aggregateGrid(grid = newdata, aggr.mem = list(FUN = "mean", na.rm = TRUE)))
     }
+    #Checking consistency among input grids
     checkVarNames(newdata, grid)
-    checkDim(newdata, grid, dimensions = "var")
+    if (getGridUnits(grid) != getGridUnits(newdata)){
+      stop("Inconsistent variable units among 'grid' and 'newdata'")
+    }
+    checkDim(newdata, grid, dimensions = c("var", "lat", "lon"))
+    checkSeason(grid, newdata)
+    if (getTimeResolution(grid) != getTimeResolution(newdata)){
+      stop("Inconsistent time resolution among 'grid' and 'newdata'")
+    }
     n.var <- suppressMessages(getShape(grid, "var")) 
-    #Pre-processing in order to do clustering to ref CT's: 
     arg.list <- list(...)
     base <- arg.list[["base"]]
     if (!is.null(base)){ 
-      if (getShape(base, "member") > 1){
+      if (!is.na(suppressMessages(getShape(base, "member"))) && getShape(base, "member") > 1){
         base <- suppressMessages(aggregateGrid(grid = base, aggr.mem = list(FUN = "mean", na.rm = TRUE)))
       }
       checkVarNames(newdata, base)
-      checkDim(newdata, base, dimensions = "var")
+      if (getGridUnits(base) != getGridUnits(newdata)){
+        stop("Inconsistent variable units among 'base' and 'newdata'")
+      }
+      checkDim(newdata, base, dimensions = c("var", "lat", "lon"))
+      checkSeason(base, newdata)
+      if (getTimeResolution(base) != getTimeResolution(newdata)){
+        stop("Inconsistent time resolution among 'base' and 'newdata'")
+      }
     }
+    #Pre-processing in order to do clustering to ref CT's: 
     if (n.var != 1){
       mat.newdata <- comb.vars(grid = newdata, base = base, ref = NULL, var.names = getVarNames(newdata))
     } else {
@@ -189,8 +203,8 @@ clusterGrid <- function(grid,
       checkTemporalConsistency(newdata, y)
       out.grid <- y
     }
-    attr(out.grid, "cluster.type") <- type
-    attr(out.grid, "centers") <- centers
+    attr(out.grid, "cluster.type") <- attr(grid, "cluster.type")
+    attr(out.grid, "centers") <- attr(grid, "centers")
     attr(out.grid, "wt.index") <- wt.index
     attr(out.grid, "centroids") <- attr(grid, "centroids")
     if (type == "kmeans") {
diff --git a/R/lambWT.R b/R/lambWT.R
index cd29136..fe618a9 100644
--- a/R/lambWT.R
+++ b/R/lambWT.R
@@ -21,7 +21,7 @@
 #' @param center.point A two value vector that must include lon and lat from a location that will work as center point for the Lamb WT.
 #' See details. 
 #' @details According to Trigo and daCamara (2000), Int J Climatol, Lamb WT is only applied on North Atlantic domain. 
-#' The input grid units must be Pa, not hPa/mbar. If it is not in Pa, the units will be converted automatically.
+#' The input grid units must be Pa, not hPa/mbar. If it is not in Pa, the units must be converted.
 #' A center location point must be specified by the user. Then, the function calculates from left to right and from first to 16st 
 #' the rest of the location point from the grid specified by Trigo and daCamara (2000):
 #'  
@@ -33,7 +33,8 @@
 #'     \tab  \tab  \tab    \tab  \tab  \tab 15 \tab  \tab  \tab 16 \tab  \tab  \tab    
 #' }  
 #'
-#' where the north-south distance is 5º and the west-east distance is 10º.
+#' where the north-south distance is 5º and the west-east distance is 10º. 26 different WTs are defined, 10 pure types (NE, E, SE, S, SW, 
+#' W, NW, N, C and A) and 16 hybrid types (8 for each C and A hybrid). 
 #' @return The Lamb WT circulation index (and members, if applicable) with:
 #' \itemize{
 #' \item index: vector with the corresponding weather type from each point of the series, that is defined as follows:
@@ -97,15 +98,8 @@ lambWT <- function(grid, center.point = c(-5, 55)) {
     lon.array <- rep(centerlon, times=16)+c(-5, 5, -15, -5, 5, 15, -15, -5, 5, 15, -15, -5, 5, 15, -5, 5)
     lat.array <- rep(centerlat, times=16)+c(10, 10, 5, 5, 5, 5, 0, 0, 0, 0, -5, -5, -5, -5, -10, 10)
     
-    subgrid <- grid.member
-    l <- lapply(1:16, function(i){
-      subgrid$xyCoords$x <- lon.array[i]
-      subgrid$xyCoords$y <- lat.array[i]
-      grid.inter<-intersectGrid(grid.member, subgrid, type = c("spatial"), which.return = 1)
-      return(grid.inter)
-    }) 
-    list.grid<-bindGrid(l, dimension = "loc")
-    X<-list.grid$Data[1,1, , ]
+    grid.inter <- interpGrid(grid.member, new.coordinates = list(x = lon.array, y = lat.array), method = "nearest")
+    X <- grid.inter$Data
     
     sf.const<-1/cospi(centerlat/180)
     zw.const1<-sinpi(centerlat/180)/sinpi((centerlat-5)/180)
@@ -148,14 +142,20 @@ lambWT <- function(grid, center.point = c(-5, 55)) {
     nind <- which(d > 337.5 | d <= 22.5) #N
     d[neind] = 10; d[eind] = 11; d[seind] = 12; d[soind] = 13
     d[swind] = 14; d[wind] = 15; d[nwind] = 16; d[nind] = 17
+    names(d)[neind] <- "NE"; names(d)[eind] <- "E"; names(d)[seind] <- "SE"; names(d)[soind] <- "S"
+    names(d)[swind] <- "SW"; names(d)[wind] <- "W"; names(d)[nwind] <- "NW"; names(d)[nind] <- "N"
+    
     
     #Define discrete wt series, codes similar to http://www.cru.uea.ac.uk/cru/data/hulme/uk/lamb.htm
     pd <- which(abs(z) < f) 
     wtseries[pd] <- d[pd] #purely directional type
+    names(wtseries)[pd] <- names(d)[pd]
     pcyc <- which(abs(z) >= (2*f) & z >= 0) 
     wtseries[pcyc] <- 18 #purely cyclonic type
+    names(wtseries)[pcyc] <- "C"
     pant <- which(abs(z) >= (2*f) & z < 0) 
     wtseries[pant] <- 1 #purely anticyclonic type
+    names(wtseries)[pant] <- "A"
     hyb <- which(abs(z) >= f & abs(z) < (2*f)) #hybrid type
     hybant <- intersect(hyb, which(z < 0)) #anticyclonic
     hybcyc <- intersect(hyb, which(z >= 0)) #cyclonic
@@ -164,11 +164,19 @@ lambWT <- function(grid, center.point = c(-5, 55)) {
       wtseries[intersect(hybant, which(d == i))] <- i-8
       #mixed cyclonic
       wtseries[intersect(hybcyc, which(d == i))] <- i+9
+      if(i == 10){names(wtseries)[intersect(hybant, which(d == i))] <- "ANE"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CNE"}
+      else if(i == 11){names(wtseries)[intersect(hybant, which(d == i))] <- "AE"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CE"}
+      else if(i == 12){names(wtseries)[intersect(hybant, which(d == i))] <- "ASE"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CSE"}
+      else if(i == 13){names(wtseries)[intersect(hybant, which(d == i))] <- "AS"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CS"}
+      else if(i == 14){names(wtseries)[intersect(hybant, which(d == i))] <- "ASW"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CSW"}
+      else if(i == 15){names(wtseries)[intersect(hybant, which(d == i))] <- "AW"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CW"}
+      else if(i == 16){names(wtseries)[intersect(hybant, which(d == i))] <- "ANW"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CNW"}
+      else {names(wtseries)[intersect(hybant, which(d == i))] <- "AN"; names(wtseries)[intersect(hybcyc, which(d == i))] <- "CN"}
     }
-    #indFlow <- which(abs(z) < 6 & f < 6) 
+    #indFlow <- which(abs(z) < 6 & f < 6)     
     #wtseries[indFlow] <- 27 #indeterminate 
     
-    wtseries.2<-wtseries[1:n[[1]]]
+    wtseries.2 <- wtseries[1:n[[1]]]
     
     lamb.list <- lapply(1:26, function(y){
       lamb.pattern <- which(wtseries.2 == y)
diff --git a/R/subsetGrid.R b/R/subsetGrid.R
index a2cd3e5..59b421c 100644
--- a/R/subsetGrid.R
+++ b/R/subsetGrid.R
@@ -22,7 +22,7 @@
 #' multigrid, as returned by \code{makeMultiGrid}, or other types of multimember grids
 #' (possibly multimember grids) as returned e.g. by \code{loadeR.ECOMS::loadECOMS}.
 #' @param var Character vector indicating the variables(s) to be extracted. (Used for multigrid subsetting). See details.
-#' @param cluster An integer indicating \strong{the cluster} to be subset.
+#' @param cluster An integer vector indicating \strong{the clusters} to be subset.
 #' @param members An integer vector indicating \strong{the position} of the members to be subset.
 #' @param runtime An integer vector indicating \strong{the position} of the runtimes to be subset.
 #' @param years The years to be selected. Note that this can be either a continuous or discontinuous
@@ -225,12 +225,14 @@ subsetCluster <- function(grid, cluster) {
             call. = FALSE)
     return(grid)
   }
-  if (!all(cluster %in% attr(grid, "index"))) {
+  if (!all(cluster %in% attr(grid, "wt.index"))) {
     stop("'cluster' index out of bounds", call. = FALSE)
   }
-  grid <- subsetDimension(grid, dimension = "time", indices = which(attr(grid, "index") == cluster))
-  attr(grid$Variable, "longname") <- paste0(getVarNames(grid), "_cluster", cluster) 
-  grid$Variable$varName <- paste0(getVarNames(grid), "_cluster", cluster)
+  indices = which(!is.na(match(attr(grid, "wt.index"), cluster))) 
+  grid <- subsetDimension(grid, dimension = "time", indices = indices)
+  attr(grid$Variable, "longname") <- paste0(getVarNames(grid), "_cluster", cluster)
+  attr(grid, "wt.index") <- attr(grid, "wt.index")[indices]
+  attr(grid$Variable, "subset") <- "subsetCluster"
   return(grid)
 }
 # End
diff --git a/man/example/CTs_comparison.png b/man/example/CTs_comparison.png
new file mode 100644
index 0000000..e6942dd
Binary files /dev/null and b/man/example/CTs_comparison.png differ
diff --git a/man/example/clustering_lamb.png b/man/example/clustering_lamb.png
index 07aa808..623ad04 100644
Binary files a/man/example/clustering_lamb.png and b/man/example/clustering_lamb.png differ
diff --git a/man/lambWT.Rd b/man/lambWT.Rd
index b2c603b..fed7b76 100644
--- a/man/lambWT.Rd
+++ b/man/lambWT.Rd
@@ -36,7 +36,7 @@ Calculate automated Lamb WT as defined in Trigo and daCamara (2000), Int J Clima
 }
 \details{
 According to Trigo and daCamara (2000), Int J Climatol, Lamb WT is only applied on North Atlantic domain. 
-The input grid units must be Pa, not hPa/mbar. If it is not in Pa, the units will be converted automatically.
+The input grid units must be Pa, not hPa/mbar. If it is not in Pa, the units must be converted.
 A center location point must be specified by the user. Then, the function calculates from left to right and from first to 16st 
 the rest of the location point from the grid specified by Trigo and daCamara (2000):
  
@@ -48,7 +48,8 @@ the rest of the location point from the grid specified by Trigo and daCamara (20
     \tab  \tab  \tab    \tab  \tab  \tab 15 \tab  \tab  \tab 16 \tab  \tab  \tab    
 }  
 
-where the north-south distance is 5º and the west-east distance is 10º.
+where the north-south distance is 5º and the west-east distance is 10º. 26 different WTs are defined, 10 pure types (NE, E, SE, S, SW, 
+W, NW, N, C and A) and 16 hybrid types (8 for each C and A hybrid).
 }
 \examples{
 \dontrun{
diff --git a/man/subsetGrid.Rd b/man/subsetGrid.Rd
index 9b23724..0dc38c9 100644
--- a/man/subsetGrid.Rd
+++ b/man/subsetGrid.Rd
@@ -16,7 +16,7 @@ multigrid, as returned by \code{makeMultiGrid}, or other types of multimember gr
 
 \item{var}{Character vector indicating the variables(s) to be extracted. (Used for multigrid subsetting). See details.}
 
-\item{cluster}{An integer indicating \strong{the cluster} to be subset.}
+\item{cluster}{An integer vector indicating \strong{the clusters} to be subset.}
 
 \item{runtime}{An integer vector indicating \strong{the position} of the runtimes to be subset.}