diff --git a/NAMESPACE b/NAMESPACE
index b3d6821c..f3cf51b4 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -29,6 +29,9 @@ S3method(check_night,pvol)
 S3method(check_night,vp)
 S3method(check_night,vpi)
 S3method(check_night,vpts)
+S3method(clean_mixture,default)
+S3method(clean_mixture,vp)
+S3method(clean_mixture,vpts)
 S3method(convert_legacy,vp)
 S3method(convert_legacy,vpts)
 S3method(dim,ppi)
@@ -86,6 +89,7 @@ S3method(summary,vpts)
 export("rcs<-")
 export("sd_vvp_threshold<-")
 export(apply_mistnet)
+export(as.vp)
 export(as.vpts)
 export(attribute_table)
 export(beam_distance)
@@ -99,6 +103,7 @@ export(calculate_param)
 export(calculate_vp)
 export(check_docker)
 export(check_night)
+export(clean_mixture)
 export(composite_ppi)
 export(convert_legacy)
 export(dbz_to_eta)
@@ -107,6 +112,7 @@ export(download_pvolfiles)
 export(download_vpfiles)
 export(doy)
 export(eta_to_dbz)
+export(filter_precip)
 export(filter_vpts)
 export(get_elevation_angles)
 export(get_iris_raw_task)
diff --git a/NEWS.md b/NEWS.md
index acf878c5..04be4d85 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,11 +1,20 @@
 # bioRad 0.8.1.9000
+## new features
 
-* Correct units specified in plot label for quantity VIR (#674).
+* new function `as.vp()` to convert data.frame to vertical profile object (#699)
 
-* Discard profiles with misspecified altitude bins in `as.vpts()` and `read_vpts()` (#684).
+* new function `clean_mixture(`) for partitioning bird and insect mixtures (#700)
+
+* new function `filter_precip()` for posthoc removal of precipitation in vp and vpts objects (#701)
 
 * New argument `zoomin` for function `bioRad::map()` to increase basemap resolution (#689).
 
+## bugfixes
+
+* Corrected units specified in plot label for quantity VIR (#674).
+
+* Discard profiles with misspecified altitude bins in `as.vpts()` and `read_vpts()` (#684).
+
 * Correct type of gap field in vpts objects for profiles stored in ODIM HDF5 format (.h5) (#635, #691).
 
 * Interpret NA values in field DBZH in `integrate_to_ppi()` as pixels that were not irradiated (#658).
diff --git a/R/as.vp.R b/R/as.vp.R
new file mode 100644
index 00000000..146a9b55
--- /dev/null
+++ b/R/as.vp.R
@@ -0,0 +1,19 @@
+#' Convert a dataframe into a vp object
+#'
+#' @param data a dataframe created from a VPTS CSV file
+#' @returns a bioRad vp object
+#' @examples
+#' # load vp data as a data.frame:
+#' df <- as.data.frame(example_vp)
+#' # convert the data.frame to a vp object:
+#' as.vp(df)
+#' @export
+as.vp <- function(data) {
+  assertthat::assert_that(inherits(data,"data.frame"))
+
+  vpts <- as.vpts(data)
+  
+  assertthat::assert_that(length(vpts$datetime) == 1, msg="multiple timestamps found, data is not a single vertical profile")
+  
+  vpts_to_vp(vpts)
+}
diff --git a/R/as.vpts.R b/R/as.vpts.R
index 9562678e..3530b210 100644
--- a/R/as.vpts.R
+++ b/R/as.vpts.R
@@ -16,13 +16,14 @@ as.vpts <- function(data) {
     data <- data %>%
       dplyr::rename(DBZH = "dbz_all")
   }
- 
+
   validate_vpts(data)
 
   # sort by datetime and height
   data <- dplyr::arrange(data, datetime, height)
 
   height <- datetime <- source_file <- radar <- NULL
+  bioRad_internal_levels <- bioRad_internal_interval <- NULL
 
   # Throw error if nrows per height are not identical
   # FIXME: first if statement is a weak check that could fail, could be improved.
@@ -30,16 +31,16 @@ as.vpts <- function(data) {
   if(!remainder_is_zero(dim(data)[1], length(unique(data$height)))){
     data %>%
       dplyr::group_by(radar, datetime) %>%
-      dplyr::mutate(bioRad_internal_interval = height-lag(height)) %>%
+      dplyr::mutate(bioRad_internal_interval = height-dplyr::lag(height)) %>%
       dplyr::add_count(name="bioRad_internal_levels") -> data
-    interval_median <- median(data$bioRad_internal_interval, na.rm=TRUE)
+    interval_median <- stats::median(data$bioRad_internal_interval, na.rm=TRUE)
     interval_unique <- unique(data$bioRad_internal_interval)
     interval_unique <- interval_unique[!is.na(interval_unique)]
     if(length(interval_unique)>1){
       warning(paste("profiles found with different altitude interval:",paste(sort(interval_unique),collapse=" ")), ", retaining ",interval_median, " only.")
       data <- dplyr::filter(data, bioRad_internal_interval == interval_median)
     }
-    levels_median <- median(data$bioRad_internal_levels)
+    levels_median <- stats::median(data$bioRad_internal_levels)
     levels_unique <- unique(data$bioRad_internal_levels)
     if(length(levels_unique)>1){
       warning(paste("profiles found with different number of height layers:",paste(sort(levels_unique),collapse=" ")), ", retaining ",levels_median, " only.")
diff --git a/R/clean_mixture.R b/R/clean_mixture.R
new file mode 100644
index 00000000..7184595b
--- /dev/null
+++ b/R/clean_mixture.R
@@ -0,0 +1,252 @@
+#' Partition mixtures of animals using assumptions on airspeeds.
+#'
+#' Partition mixtures of birds and insects using assumptions on their respective airspeeds,
+#' following the approach by Shi et al. (2025).
+#' @param x a `vp` or `vpts` object, or a mixture animal density or linear reflectivity eta in cm\eqn{^2}/km\eqn{^3}.
+#' @param ... `eta`, `u`, `v`, `U`, `V` arguments, taken from object for `vp` or `vpts` class.
+#' @param u the mixture's ground speed u component (west to east) in m/s.
+#' @param v the mixture's ground speed v component (south to north) in m/s.
+#' @param U the west to east wind component in m/s. In the case of `vp` and `vpts` objects
+#' the quantity name for the U-component of the wind.
+#' @param V the south to north wind component in m/s.  In the case of `vp` and `vpts` objects
+#' the quantity name for the V-component of the wind.
+#' @param fast the fast component's airspeed in m/s, typically the airspeed of insects.
+#' @param slow the slow component's airspeed in m/s, typically the airspeed of birds.
+#' @param drop_slow_component when TRUE (default) output density, ground speed and
+#' heading for fast component, when FALSE for slow component.
+#' @param drop_missing Values `eta` without an associated ground speed
+#' and wind speed are set to NA when `TRUE`, or returned unaltered when `FALSE` (default).
+#' @param keep_mixture When `TRUE` store original mixture reflectivity and speeds as
+#' renamed quantities with `mixture_` prefix
+#' @return a named list with cleaned densities and speeds.
+#' Output differs depending on whether the fast component is retained
+#' (`drop_slow_component`=`TRUE`, default) or the slow component (`drop_slow_component`=`FALSE`, default). Output quantities include:
+#'   * `eta`: cleaned reflectivity in cm^2/km^3.
+#'   only the fast component (default) or the slow component
+#'    (when `drop_slow_component` is `TRUE`).
+#'   * `u`: cleaned ground speed component west to east in m/s.
+#'   * `v`: cleaned ground speed component south to north in m/s.
+#'   * `airspeed`: the airspeed of the selected component in m/s.
+#'   * `airspeed_u`: the u-component (west to east) of the airspeed of the retained component in m/s.
+#'   * `airspeed_v`: the v-component (south to north) of the airspeed of the retained component in m/s.
+#'   * `heading`: the heading of the selected component in degrees clockwise from north.
+#'   * `f`: the reflectivity proportion of the slow component (0-1 range), typically the proportion of insects.
+#'
+#' For `vp` and `vpts` objects the quantities `eta`,`u`,`v` will be updated, and other
+#' quantities listed above will be added.
+#' @export
+#' @name clean_mixture
+#' @examples
+#' # convert profile object to data.frame
+#' df <- as.data.frame(example_vp, suntime=FALSE)
+#' # add wind u and v component wind data
+#' # (here a NW wind identical at all altitudes)
+#' df$u_wind=3
+#' df$v_wind=-3
+#' # convert back to vp object
+#' my_vp <- as.vp(df)
+#' # partition the mixture:
+#' my_vp_clean <- clean_mixture(my_vp)
+#'
+#' # drop the slow component (typically insects)
+#' clean_mixture(100,u=-13,v=13,U=-7,V=6, fast=8, slow=1)
+#' # drop the fast component (typically birds)
+#' clean_mixture(100,u=-13,v=13,U=-7,V=6, fast=8, slow=1, drop_slow_component=FALSE)
+#' # keep the original mixture reflectivity and speed components
+#' clean_mixture(100,u=-13,v=13,U=-7,V=6, fast=8, slow=1, keep_mixture=TRUE)
+#' # keep reflectivity unaltered when one of the speed components is not a number:
+#' clean_mixture(100,u=-13,v=13,U=NaN,V=6, fast=8, slow=1)["eta"]
+#' # set reflectivity to NaN when one of the speed components is not a number:
+#' clean_mixture(100,u=-13,v=13,U=NaN,V=6, fast=8, slow=1, drop_missing=TRUE)["eta"]
+#' @references
+#' * Shi X, Drucker J, Chapman JW, Sanchez Herrera M, Dokter AM
+#' Analysis of mixtures of birds and insects in weather radar data.
+#' Ornithological Applications. 2025 (in press).
+#' * Nussbaumer R, Schmid B, Bauer S, Liechti F.
+#' A Gaussian mixture model to separate birds and insects in
+#' single-polarization weather radar data. Remote Sensing. 2021 May 19;13(10):1989.
+#' @details
+#' For a detail description of the methodology see Shi et al. (2025).
+#' Most commonly the fast component refers to migrating birds, while
+#' the slow component refers to insects. The slow component is always
+#' oriented in the direction of the wind by definition.
+#' Note that for mixture airspeeds exceeding the airspeed of the fast component,
+#' all reflectivity is assigned to the fast component. Similarly, for mixture
+#' airspeeds below the airspeed of the slow component, all reflectivity
+#' will be assigned to the slow component. In both these limiting cases the
+#' 
+#'
+#' ## How to use this function?
+#' 1. To apply this function to `vp` or `vpts` data altitudinal wind data
+#' needs to be added to the vertical profile data first. This is most easily
+#' accomplished by first converting the objects to a `data.frame` with [as.vp()] or [as.vpts()].
+#' Wind data can then be added as a new columns to the data.frame.
+#' By default the wind data is expected to be named `u_wind` for the U component
+#' and `v_wind` for the V component of the wind.
+#' Alternatively, arguments `U` and `V` can be used to specify different names.
+#' 2. Realistic assumptions for the expected airspeed for the slow (insect)
+#' and fast (bird) components need to be provided, using arguments `slow` and `fast`.
+#' See Shi et al. 2025 for recommendations in choosing these values.
+#' 3. Use `drop_slow_component` to toggle between retaining the slow or fast component.
+#' When `TRUE` the fast (bird) component is retained. When `FALSE` the slow (insect)
+#' component is retained. Note that in this case the corrected ground speed direction will be
+#' identical to the wind direction, and the magnitude of the ground speed will be equal
+#' to the wind speed plus the value of `slow`, due to the underlying assumption
+#' of wind following by the slow component.
+NULL
+
+#' @rdname clean_mixture
+#'
+#' @export
+clean_mixture <- function(x, ...){
+  UseMethod("clean_mixture", x)
+}
+
+#' @rdname clean_mixture
+#'
+#' @export
+clean_mixture.default <- function(x, slow = 1, fast = 8, drop_slow_component = TRUE, drop_missing = FALSE, keep_mixture = FALSE, U, V, u, v, ...){
+  # verify input
+  assertthat::assert_that(all(x >= 0, na.rm = TRUE))
+  assertthat::assert_that(is.numeric(u))
+  assertthat::assert_that(is.numeric(v))
+  assertthat::assert_that(is.numeric(U))
+  assertthat::assert_that(is.numeric(V))
+  assertthat::assert_that(is.numeric(slow))
+  assertthat::assert_that(is.numeric(fast))
+  assertthat::assert_that(slow >= 0)
+  assertthat::assert_that(fast > 0)
+  assertthat::assert_that(fast > slow)
+  assertthat::assert_that(assertthat::is.flag(drop_slow_component))
+  assertthat::assert_that(assertthat::is.flag(drop_missing))
+  assertthat::assert_that(assertthat::is.flag(keep_mixture))
+
+  if(!all(is.finite(U))) warning("U component of wind contains non finite values")
+  if(!all(is.finite(V))) warning("V component of wind contains non finite values")
+
+  # define helper quantities:
+  wind_speed <- sqrt(U^2 + V^2)
+  wind_direction <- atan2(V,U)
+  mixture_airspeed <- sqrt((u-U)^2 + (v-V)^2)
+  mixture_heading <- (pi / 2 - atan2(v-V, u-U)) * 180 / pi
+  mixture_heading[which(mixture_heading<0)]=mixture_heading[which(mixture_heading<0)]+360
+
+  # solve mixture equations for slow proportion f
+  p1 <- slow^2 - fast^2
+  p2 <- 2*fast^2 - 2*(slow/wind_speed)*(u*U+v*V - wind_speed^2)
+  p3 <- (u-U)^2 + (v-V)^2 - fast^2
+  f <- (-p2+sqrt(p2^2-4*p1*p3))/(2*p1)
+
+  # catch limiting cases for which f is not defined
+  idx_f_zero <- mixture_airspeed > fast
+  if(length(which(idx_f_zero))>0){
+    #warning("Assigning all reflectivity to fast component for mixture airspeeds exceeding airspeed of fast component")
+    f[idx_f_zero]=0
+  }
+  idx_f_one <- mixture_airspeed < slow
+  if(length(which(idx_f_one))>0){
+    #warning("Assigning all reflectivity to slow component for mixture airspeeds below airspeed of slow component")
+    f[idx_f_one]=1
+  }
+
+  # initialize corrected eta and speed matrix or vector:
+  eta_corr=x
+  air_u = u-U
+  air_v = v-V
+
+  # initialize and define indices to correct densities and speeds
+  idx = !is.na(f) & !idx_f_zero & !idx_f_one
+
+  if(drop_slow_component){
+    # fast component airspeed, typically birds:
+    eta_corr[idx]=((1-f)*x)[idx]
+    air_u[idx]=(((u-U)-(slow/wind_speed)*U*f)/(1-f))[idx]
+    air_v[idx]=(((v-V)-(slow/wind_speed)*V*f)/(1-f))[idx]
+  } else{
+    # slow component airspeed, typically insects:
+    eta_corr[idx]=(f*x)[idx]
+    air_u[idx]=slow*cos(wind_direction)[idx]
+    air_v[idx]=slow*sin(wind_direction)[idx]
+  }
+
+  if(drop_missing){
+    eta_corr[is.na(f)]=NaN
+    air_u[is.na(f)]=NaN
+    air_v[is.na(f)]=NaN
+  }
+
+  # calculate speed and direction
+  ff <- sqrt((U+air_u)^2 + (V+air_v)^2)
+  dd <- (pi / 2 - atan2(V+air_v, U+air_u)) * 180 / pi
+  dd[which(dd<0)]=dd[which(dd<0)]+360
+
+  output <- list(eta=eta_corr,u=U+air_u,v=V+air_v, airspeed = sqrt(air_u^2+air_v^2), heading=(pi/2-atan2(air_v,air_u))*180/pi,
+                 airspeed_u = air_u, airspeed_v = air_v, f=f)
+
+  if(keep_mixture){
+    output = append(output, list(mixture_eta = x, mixture_u=u, mixture_v=v, mixture_airspeed=mixture_airspeed, mixture_heading=mixture_heading))
+  }
+
+  output
+}
+
+#' @rdname clean_mixture
+#'
+#' @export
+clean_mixture.vpts <- function(x, slow = 1, fast = 8, drop_slow_component = TRUE, drop_missing = FALSE, keep_mixture = FALSE, U="u_wind", V="v_wind", ...){
+  assertthat::assert_that(inherits(x,"vpts") | inherits(x,"vp"))
+  if(inherits(x,"vpts") | inherits(x,"vp")){
+    assertthat::assert_that(is.character(U))
+    assertthat::assert_that(is.character(V))
+  }
+  assertthat::assert_that(all(c(U,V) %in% names(x$data)), msg=paste0("function requires paired wind data, profile quantities `",U,"` and/or `",V,"` not found."))
+  assertthat::assert_that(all(c("u","v") %in% names(x$data)), msg="function requires ground speed data, profile quantities `u` and/or `v` not found.")
+  assertthat::assert_that("eta" %in% names(x$data), msg="function requires linear reflectivity data, profile quantity `eta` not found.")
+  assertthat::assert_that(assertthat::is.number(x$attributes$how$rcs_bird), msg="radar cross section not defined, please set with `rcs()`.")
+
+  # call function
+  result <- clean_mixture.default(x$data$eta,
+                                  slow = slow, fast = fast, drop_slow_component = drop_slow_component,
+                                  drop_missing = drop_missing, keep_mixture = keep_mixture,
+                                  x$data[[U]], x$data[[V]], x$data$u, x$data$v)
+
+  # map results to vp or vpts structure
+  x$data$eta=result$eta
+  x$data$u=result$u
+  x$data$v=result$v
+
+  # check for quantities potentially overwritten
+  quantities <- c("airspeed","airspeed_u","airspeed_v","heading","f")
+  if(keep_mixture) quantities <- c(quantities, "mixture_eta","mixture_u","mixture_v","mixture_airspeed","mixture_heading")
+  presence_test <- quantities %in% names(x$data)
+  if(sum(presence_test)>0) warning(paste0("Overwriting existing quantities `", paste(quantities[presence_test], collapse="`, `"),"`."))
+
+  x$data$airspeed=result$airspeed
+  x$data$heading=result$heading
+  x$data$airspeed_u=result$airspeed_u
+  x$data$airspeed_v=result$airspeed_v
+  x$data$f=result$f
+  if(keep_mixture){
+    x$data$mixture_eta=result$mixture_eta
+    x$data$mixture_u=result$mixture_u
+    x$data$mixture_v=result$mixture_v
+    x$data$mixture_airspeed=result$mixture_airspeed
+    x$data$mixture_heading=result$mixture_heading
+  }
+
+  # trigger rebuild of dens from eta:
+  rcs(x) <- rcs(x)
+
+  # return object
+  x
+}
+
+#' @rdname clean_mixture
+#'
+#' @export
+clean_mixture.vp <- function(x, ..., slow = 1, fast = 8, drop_slow_component = TRUE, drop_missing = FALSE, keep_mixture = FALSE, U="u_wind", V="v_wind"){
+  assertthat::assert_that(inherits(x,"vp"))
+
+  clean_mixture.vpts(x,slow = slow, fast = fast, drop_slow_component = drop_slow_component,
+                     drop_missing = drop_missing, keep_mixture = keep_mixture, U=U, V=V)
+}
diff --git a/R/filter_precip.R b/R/filter_precip.R
new file mode 100644
index 00000000..5b0e37ae
--- /dev/null
+++ b/R/filter_precip.R
@@ -0,0 +1,105 @@
+#' Posthoc precipitation filter
+#'
+#' The posthoc precipitation filter assesses how much of the altitude column has a high
+#' total reflectivity factor (biology + meteorology) consistent with precipitation,
+#' and removes biological signals when there is evidence for the presence of precipitation.
+#' Applied to vertical profiles ('vp') or time series of vertical profiles ('vpts').
+#'
+#' @param x A `vp` or `vpts` object.
+#' @param dbz The minimum reflectivity factor for precipitation.
+#' @param range The minimum altitude range with total reflectivity factor.
+#' `DBZH` > `dbz` at which the filter is triggered.
+#' @param alt_max Maximum altitude above ground level to consider.
+#' @param drop When `TRUE` the profile is removed from the
+#' @return A `vpts` object or a `vp` object, depending on input `x`.
+#'
+#' @export
+#' @details
+#' During precipitation events usually a high proportion of the altitude
+#' column will show a high total reflectivity `DBZH` (which includes biology +
+#' meteorology), because precipitation usually falls from several kilometers high
+#' to the ground surface. Precipitation events are often obvious in profile plots
+#' of quantity `DBZH` as reflectivity signals extending from ground level to high
+#' altitudes far above the typical altitudes where biology is expected. This filter
+#' identifies and removes these cases.
+#'
+#' The posthoc precipitation filter examines the total reflectivity factor `DBZH`
+#' and calculates the altitude range at which `DBZH` is larger than parameter
+#' `dbz`. Whenever this altitude range is larger than parameter `range` (and `drop`
+#' is `FALSE`), the biology is removed by setting profile quantities `dens` and `eta`
+#' to zero and profile quantity `dbz` to `-Inf`. When parameter `drop`
+#' is `TRUE`, the profile is removed from the time series altogether.
+#'
+#' This posthoc precipitation filter is likely to remove biological scatterers
+#' that co-occur with precipitation, for example biological movements during isolated
+#' convective thunderstorms. It is more aggressive than precipitation filters
+#' applied during vertical profile generation with `calculate_vp()` that attempt to
+#' remove precipitation and retain biology. The posthoc precipitation filter is especially
+#' useful for analyses where you want to minimize the risk of precipitation contamination,
+#' at the cost of filtering out some biology during precipitation events.
+#'
+#' Lowering the default minimum reflectivity (`dbz`) for precipitation
+#' below 7 dBZ is not recommended, as most precipitation has a reflectivity above 7 dBZ.
+#'
+#' Parameter `range` should be chosen carefully, and should be higher than the
+#' typical altitude where biological scatterers still reach a reflectivity factor equal to `dbz`.
+#'
+#' Note that at S-band wavelengths bird migration occurs much more frequently in the reflectivity
+#' regime for precipitation than at C-band. Therefore, at C-band lower settings for parameter `dbz`
+#' are appropriate than at S-band.
+#'
+#' @seealso
+#' * [eta_to_dbz]
+#' * [dbz_to_eta]
+#'
+#' @examples
+#' # rain periods are visible in quantity DBZH as dark vertical lines
+#' # extending above 3 km height:
+#' plot(regularize_vpts(example_vpts), quantity='DBZH')
+#' # Apply posthoc filter to remove profiles during precipitation events:
+#' # (regularization is applied to visualize removed profiles)
+#' my_vpts <- regularize_vpts(filter_precip(example_vpts, drop=TRUE))
+#' # verify that rain events have been removed:
+#' plot(my_vpts, quantity='DBZH')
+#' # the posthoc filter removes some biology during precipitation:
+#' plot(my_vpts, quantity='dens')
+#' # original retains more biology (but at the cost of a higher
+#' # likelihood of occasional precipitation contamination):
+#' plot(regularize_vpts(example_vpts), quantity='dens')
+#' # filter can also be applied to single vp objects:
+#' filter_precip(example_vp)
+filter_precip <- function(x, dbz=7, range=2500, alt_max=3000, drop=FALSE){
+  assertthat::assert_that(is.vp(x) | is.vpts(x))
+  assertthat::assert_that(assertthat::is.number(dbz))
+  assertthat::assert_that(assertthat::is.number(range))
+  assertthat::assert_that(assertthat::is.number(alt_max))
+  assertthat::assert_that(alt_max>0)
+  assertthat::assert_that(assertthat::is.flag(drop))
+  assertthat::assert_that(range<=alt_max)
+  assertthat::assert_that(!(drop & is.vp(x)), msg='parameter `drop` should be `TRUE` for objects of class `vp`')
+  if(dbz<7) warning("dbz value too low for typical precipitation")
+  height_index_max <- ((x$attributes$where$height + alt_max) %/% x$attributes$where$interval)
+  height_index_max <- min(x$attributes$where$levels,height_index_max)
+  if(is.vpts(x)){
+    height_range <- colSums(x$data$DBZH[1:height_index_max,]>dbz,na.rm=T)*x$attributes$where$interval
+  } else{
+    height_range <- sum(x$data$DBZH[1:height_index_max]>dbz,na.rm=T)*x$attributes$where$interval
+  }
+
+  index <- which(height_range > range)
+  if(length(index)==0) return(x)
+  # if remove, drop the profiles
+  if(drop) return(x[-index])
+  # otherwise set the density field to zero, but keep the profile
+  if(is.vpts(x)){
+    x$data$dens[,index] <- 0
+    x$data$eta[,index] <- 0
+    x$data$dbz[,index] <- -Inf
+  } else{
+    x$data$dens[index] <- 0
+    x$data$eta[index] <- 0
+    x$data$dbz[index] <- -Inf
+  }
+
+  x
+}
diff --git a/_pkgdown.yml b/_pkgdown.yml
index d6176aba..0f94e415 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -25,7 +25,7 @@ home:
 
 reference:
   - title: "Reading radar data"
-    desc: "Functions to read polar volume (pvol) data. Requires a locally running Docker daemon for NEXRAD data."
+    desc: "Functions to read polar volume (pvol) data."
     contents:
       - download_pvolfiles
       - is.pvolfile
@@ -67,7 +67,7 @@ reference:
       - composite_ppi
       - "`[.ppi`"
   - title: "Creating vertical profiles of biological targets"
-    desc: "Functions to process weather radar data (pvol) into vertical profiles (vp) of biological targets. Requires a locally running Docker daemon."
+    desc: "Functions to process weather radar data (pvol) into vertical profiles (vp) of biological targets."
     contents:
       - calculate_vp
       - nexrad_to_odim # Repeated
@@ -84,18 +84,21 @@ reference:
       - plot.vp
       - as.data.frame.vp
       - list_vpts_aloft
-  - title: "Combining vertical profiles into time series"
-    desc: "Functions to combine vertical profiles (vp) into time series (vpts) and read, inspect and plot these."
+  - title: "Manipulating vertical profile data"
+    desc: "Functions to combine vertical profiles (vp) into time series (vpts) and to post-process, read, inspect and plot these."
     contents:
       - c.vp
       - bind_into_vpts
       - read_vpts
       - filter_vpts
+      - filter_precip
+      - clean_mixture
       - summary.vpts # is.vpts
       - example_vpts
       - plot.vpts
       - regularize_vpts
       - as.data.frame.vp
+      - as.vp
       - as.vpts
       - "`[.vpts`"
       - get_quantity
@@ -116,7 +119,7 @@ reference:
       - doy_noy
       - attribute_table
   - title: "Radar beam geometry"
-    desc: "Functions relating the radar beam shape to range, distance and height"
+    desc: "Functions relating the radar beam shape to range, distance and height."
     contents:
       - beam_height
       - beam_width
diff --git a/bioRad.Rproj b/bioRad.Rproj
index 0dfffde6..87e26f28 100644
--- a/bioRad.Rproj
+++ b/bioRad.Rproj
@@ -1,5 +1,5 @@
 Version: 1.0
-ProjectId: b32cc17d-04d6-4782-95b0-7bdaa77d889b
+ProjectId: 78f5cd79-a10d-46e0-8b29-c679c1dee61d
 
 RestoreWorkspace: Default
 SaveWorkspace: Default
diff --git a/data/example_vp.rda b/data/example_vp.rda
index 983c87d6..9e365471 100644
Binary files a/data/example_vp.rda and b/data/example_vp.rda differ
diff --git a/man/as.vp.Rd b/man/as.vp.Rd
new file mode 100644
index 00000000..2159e998
--- /dev/null
+++ b/man/as.vp.Rd
@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/as.vp.R
+\name{as.vp}
+\alias{as.vp}
+\title{Convert a dataframe into a vp object}
+\usage{
+as.vp(data)
+}
+\arguments{
+\item{data}{a dataframe created from a VPTS CSV file}
+}
+\value{
+a bioRad vp object
+}
+\description{
+Convert a dataframe into a vp object
+}
+\examples{
+# load vp data as a data.frame:
+df <- as.data.frame(example_vp)
+# convert the data.frame to a vp object:
+as.vp(df)
+}
diff --git a/man/clean_mixture.Rd b/man/clean_mixture.Rd
new file mode 100644
index 00000000..371af80e
--- /dev/null
+++ b/man/clean_mixture.Rd
@@ -0,0 +1,164 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/clean_mixture.R
+\name{clean_mixture}
+\alias{clean_mixture}
+\alias{clean_mixture.default}
+\alias{clean_mixture.vpts}
+\alias{clean_mixture.vp}
+\title{Partition mixtures of animals using assumptions on airspeeds.}
+\usage{
+clean_mixture(x, ...)
+
+\method{clean_mixture}{default}(
+  x,
+  slow = 1,
+  fast = 8,
+  drop_slow_component = TRUE,
+  drop_missing = FALSE,
+  keep_mixture = FALSE,
+  U,
+  V,
+  u,
+  v,
+  ...
+)
+
+\method{clean_mixture}{vpts}(
+  x,
+  slow = 1,
+  fast = 8,
+  drop_slow_component = TRUE,
+  drop_missing = FALSE,
+  keep_mixture = FALSE,
+  U = "u_wind",
+  V = "v_wind",
+  ...
+)
+
+\method{clean_mixture}{vp}(
+  x,
+  ...,
+  slow = 1,
+  fast = 8,
+  drop_slow_component = TRUE,
+  drop_missing = FALSE,
+  keep_mixture = FALSE,
+  U = "u_wind",
+  V = "v_wind"
+)
+}
+\arguments{
+\item{x}{a \code{vp} or \code{vpts} object, or a mixture animal density or linear reflectivity eta in cm\eqn{^2}/km\eqn{^3}.}
+
+\item{...}{\code{eta}, \code{u}, \code{v}, \code{U}, \code{V} arguments, taken from object for \code{vp} or \code{vpts} class.}
+
+\item{slow}{the slow component's airspeed in m/s, typically the airspeed of birds.}
+
+\item{fast}{the fast component's airspeed in m/s, typically the airspeed of insects.}
+
+\item{drop_slow_component}{when TRUE (default) output density, ground speed and
+heading for fast component, when FALSE for slow component.}
+
+\item{drop_missing}{Values \code{eta} without an associated ground speed
+and wind speed are set to NA when \code{TRUE}, or returned unaltered when \code{FALSE} (default).}
+
+\item{keep_mixture}{When \code{TRUE} store original mixture reflectivity and speeds as
+renamed quantities with \code{mixture_} prefix}
+
+\item{U}{the west to east wind component in m/s. In the case of \code{vp} and \code{vpts} objects
+the quantity name for the U-component of the wind.}
+
+\item{V}{the south to north wind component in m/s.  In the case of \code{vp} and \code{vpts} objects
+the quantity name for the V-component of the wind.}
+
+\item{u}{the mixture's ground speed u component (west to east) in m/s.}
+
+\item{v}{the mixture's ground speed v component (south to north) in m/s.}
+}
+\value{
+a named list with cleaned densities and speeds.
+Output differs depending on whether the fast component is retained
+(\code{drop_slow_component}=\code{TRUE}, default) or the slow component (\code{drop_slow_component}=\code{FALSE}, default). Output quantities include:
+\itemize{
+\item \code{eta}: cleaned reflectivity in cm^2/km^3.
+only the fast component (default) or the slow component
+(when \code{drop_slow_component} is \code{TRUE}).
+\item \code{u}: cleaned ground speed component west to east in m/s.
+\item \code{v}: cleaned ground speed component south to north in m/s.
+\item \code{airspeed}: the airspeed of the selected component in m/s.
+\item \code{airspeed_u}: the u-component (west to east) of the airspeed of the retained component in m/s.
+\item \code{airspeed_v}: the v-component (south to north) of the airspeed of the retained component in m/s.
+\item \code{heading}: the heading of the selected component in degrees clockwise from north.
+\item \code{f}: the reflectivity proportion of the slow component (0-1 range), typically the proportion of insects.
+}
+
+For \code{vp} and \code{vpts} objects the quantities \code{eta},\code{u},\code{v} will be updated, and other
+quantities listed above will be added.
+}
+\description{
+Partition mixtures of birds and insects using assumptions on their respective airspeeds,
+following the approach by Shi et al. (2025).
+}
+\details{
+For a detail description of the methodology see Shi et al. (2025).
+Most commonly the fast component refers to migrating birds, while
+the slow component refers to insects. The slow component is always
+oriented in the direction of the wind by definition.
+Note that for mixture airspeeds exceeding the airspeed of the fast component,
+all reflectivity is assigned to the fast component. Similarly, for mixture
+airspeeds below the airspeed of the slow component, all reflectivity
+will be assigned to the slow component. In both these limiting cases the
+\subsection{How to use this function?}{
+\enumerate{
+\item To apply this function to \code{vp} or \code{vpts} data altitudinal wind data
+needs to be added to the vertical profile data first. This is most easily
+accomplished by first converting the objects to a \code{data.frame} with \code{\link[=as.vp]{as.vp()}} or \code{\link[=as.vpts]{as.vpts()}}.
+Wind data can then be added as a new columns to the data.frame.
+By default the wind data is expected to be named \code{u_wind} for the U component
+and \code{v_wind} for the V component of the wind.
+Alternatively, arguments \code{U} and \code{V} can be used to specify different names.
+\item Realistic assumptions for the expected airspeed for the slow (insect)
+and fast (bird) components need to be provided, using arguments \code{slow} and \code{fast}.
+See Shi et al. 2025 for recommendations in choosing these values.
+\item Use \code{drop_slow_component} to toggle between retaining the slow or fast component.
+When \code{TRUE} the fast (bird) component is retained. When \code{FALSE} the slow (insect)
+component is retained. Note that in this case the corrected ground speed direction will be
+identical to the wind direction, and the magnitude of the ground speed will be equal
+to the wind speed plus the value of \code{slow}, due to the underlying assumption
+of wind following by the slow component.
+}
+}
+}
+\examples{
+# convert profile object to data.frame
+df <- as.data.frame(example_vp, suntime=FALSE)
+# add wind u and v component wind data
+# (here a NW wind identical at all altitudes)
+df$u_wind=3
+df$v_wind=-3
+# convert back to vp object
+my_vp <- as.vp(df)
+# partition the mixture:
+my_vp_clean <- clean_mixture(my_vp)
+
+# drop the slow component (typically insects)
+clean_mixture(100,u=-13,v=13,U=-7,V=6, fast=8, slow=1)
+# drop the fast component (typically birds)
+clean_mixture(100,u=-13,v=13,U=-7,V=6, fast=8, slow=1, drop_slow_component=FALSE)
+# keep the original mixture reflectivity and speed components
+clean_mixture(100,u=-13,v=13,U=-7,V=6, fast=8, slow=1, keep_mixture=TRUE)
+# keep reflectivity unaltered when one of the speed components is not a number:
+clean_mixture(100,u=-13,v=13,U=NaN,V=6, fast=8, slow=1)["eta"]
+# set reflectivity to NaN when one of the speed components is not a number:
+clean_mixture(100,u=-13,v=13,U=NaN,V=6, fast=8, slow=1, drop_missing=TRUE)["eta"]
+}
+\references{
+\itemize{
+\item Shi X, Drucker J, Chapman JW, Sanchez Herrera M, Dokter AM
+Analysis of mixtures of birds and insects in weather radar data.
+Ornithological Applications. 2025 (in press).
+\item Nussbaumer R, Schmid B, Bauer S, Liechti F.
+A Gaussian mixture model to separate birds and insects in
+single-polarization weather radar data. Remote Sensing. 2021 May 19;13(10):1989.
+}
+}
diff --git a/man/filter_precip.Rd b/man/filter_precip.Rd
new file mode 100644
index 00000000..6d41509b
--- /dev/null
+++ b/man/filter_precip.Rd
@@ -0,0 +1,86 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/filter_precip.R
+\name{filter_precip}
+\alias{filter_precip}
+\title{Posthoc precipitation filter}
+\usage{
+filter_precip(x, dbz = 7, range = 2500, alt_max = 3000, drop = FALSE)
+}
+\arguments{
+\item{x}{A \code{vp} or \code{vpts} object.}
+
+\item{dbz}{The minimum reflectivity factor for precipitation.}
+
+\item{range}{The minimum altitude range with total reflectivity factor.
+\code{DBZH} > \code{dbz} at which the filter is triggered.}
+
+\item{alt_max}{Maximum altitude above ground level to consider.}
+
+\item{drop}{When \code{TRUE} the profile is removed from the}
+}
+\value{
+A \code{vpts} object or a \code{vp} object, depending on input \code{x}.
+}
+\description{
+The posthoc precipitation filter assesses how much of the altitude column has a high
+total reflectivity factor (biology + meteorology) consistent with precipitation,
+and removes biological signals when there is evidence for the presence of precipitation.
+Applied to vertical profiles ('vp') or time series of vertical profiles ('vpts').
+}
+\details{
+During precipitation events usually a high proportion of the altitude
+column will show a high total reflectivity \code{DBZH} (which includes biology +
+meteorology), because precipitation usually falls from several kilometers high
+to the ground surface. Precipitation events are often obvious in profile plots
+of quantity \code{DBZH} as reflectivity signals extending from ground level to high
+altitudes far above the typical altitudes where biology is expected. This filter
+identifies and removes these cases.
+
+The posthoc precipitation filter examines the total reflectivity factor \code{DBZH}
+and calculates the altitude range at which \code{DBZH} is larger than parameter
+\code{dbz}. Whenever this altitude range is larger than parameter \code{range} (and \code{drop}
+is \code{FALSE}), the biology is removed by setting profile quantities \code{dens} and \code{eta}
+to zero and profile quantity \code{dbz} to \code{-Inf}. When parameter \code{drop}
+is \code{TRUE}, the profile is removed from the time series altogether.
+
+This posthoc precipitation filter is likely to remove biological scatterers
+that co-occur with precipitation, for example biological movements during isolated
+convective thunderstorms. It is more aggressive than precipitation filters
+applied during vertical profile generation with \code{calculate_vp()} that attempt to
+remove precipitation and retain biology. The posthoc precipitation filter is especially
+useful for analyses where you want to minimize the risk of precipitation contamination,
+at the cost of filtering out some biology during precipitation events.
+
+Lowering the default minimum reflectivity (\code{dbz}) for precipitation
+below 7 dBZ is not recommended, as most precipitation has a reflectivity above 7 dBZ.
+
+Parameter \code{range} should be chosen carefully, and should be higher than the
+typical altitude where biological scatterers still reach a reflectivity factor equal to \code{dbz}.
+
+Note that at S-band wavelengths bird migration occurs much more frequently in the reflectivity
+regime for precipitation than at C-band. Therefore, at C-band lower settings for parameter \code{dbz}
+are appropriate than at S-band.
+}
+\examples{
+# rain periods are visible in quantity DBZH as dark vertical lines
+# extending above 3 km height:
+plot(regularize_vpts(example_vpts), quantity='DBZH')
+# Apply posthoc filter to remove profiles during precipitation events:
+# (regularization is applied to visualize removed profiles)
+my_vpts <- regularize_vpts(filter_precip(example_vpts, drop=TRUE))
+# verify that rain events have been removed:
+plot(my_vpts, quantity='DBZH')
+# the posthoc filter removes some biology during precipitation:
+plot(my_vpts, quantity='dens')
+# original retains more biology (but at the cost of a higher
+# likelihood of occasional precipitation contamination):
+plot(regularize_vpts(example_vpts), quantity='dens')
+# filter can also be applied to single vp objects:
+filter_precip(example_vp)
+}
+\seealso{
+\itemize{
+\item \link{eta_to_dbz}
+\item \link{dbz_to_eta}
+}
+}
diff --git a/tests/testthat/test-as.vp.R b/tests/testthat/test-as.vp.R
new file mode 100644
index 00000000..1e3297d4
--- /dev/null
+++ b/tests/testthat/test-as.vp.R
@@ -0,0 +1,6 @@
+test_that("as.vp() returns valid data", {
+  df <- as.data.frame(example_vp, suntime=FALSE)
+  expect_s3_class(as.vp(df), "vp")
+  df <- as.data.frame(example_vpts, suntime=FALSE)
+  expect_error(as.vp(df),"not a single vertical profile")
+})
diff --git a/tests/testthat/test-clean_mixture.R b/tests/testthat/test-clean_mixture.R
new file mode 100644
index 00000000..af07206d
--- /dev/null
+++ b/tests/testthat/test-clean_mixture.R
@@ -0,0 +1,37 @@
+# create vp and vpts object and add dummy wind values
+vp <- example_vp
+vp$data$u_wind <-seq(-1,-8, length.out=dim(vp)[1])
+vp$data$v_wind <-seq(0,-3, length.out=dim(vp)[1])
+clean_mixture(vp, fast=12)
+
+vpts <- example_vpts
+vpts$data$u_wind <- matrix(data=seq(0,10, length.out=dim(vpts)[2]),nrow=dim(vpts)[2],ncol=dim(vpts)[1])
+vpts$data$v_wind <- matrix(data=seq(-2,6, length.out=dim(vpts)[2]),nrow=dim(vpts)[2],ncol=dim(vpts)[1])
+clean_mixture(vpts)
+
+test_that("clean_mixture() requires correct input data and parameters", {
+  expect_error(clean_mixture(example_vp), "requires paired wind data")
+  expect_error(clean_mixture(example_vpts), "requires paired wind data")
+  expect_error(clean_mixture(vpts, slow=10, fast=1), "fast not greater than slow")
+})
+
+test_that("clean_mixture() returns vp or vpts object", {
+  expect_s3_class(clean_mixture(vpts), "vpts")
+  expect_s3_class(clean_mixture(vp), "vp")
+})
+
+test_that("clean_mixture() returns warning for infinite wind data", {
+  vp$data$u_wind[3] <- NA
+  expect_warning(clean_mixture(vp), "wind contains non finite values")
+})
+
+test_that("clean_mixture() returns expected values", {
+  # only birds
+  expect_equal(clean_mixture(100,u=10,v=0,U=5,V=0, fast=5, slow=1)$f,0)
+  # only insects
+  expect_equal(clean_mixture(100,u=6,v=0,U=5,V=0, fast=5, slow=1)$f,1)
+  # observed airspeed faster than fast component
+  expect_equal(clean_mixture(100,u=11,v=0,U=5,V=0, fast=5, slow=1)$f,0)
+  # observed airspeed slower than slow component
+  expect_equal(clean_mixture(100,u=5.5,v=0,U=5,V=0, fast=5, slow=1)$f,1)
+})