diff --git a/doc/devlog/2024-08-26-prism-adrio-demo.ipynb b/doc/devlog/2024-08-26-prism-adrio-demo.ipynb
index a5685e14..35b66f31 100644
--- a/doc/devlog/2024-08-26-prism-adrio-demo.ipynb
+++ b/doc/devlog/2024-08-26-prism-adrio-demo.ipynb
@@ -47,9 +47,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ADRIO data usage estimation:\n",
+      "- epymorph.adrio.us_tiger.GeometricCentroid will download 0 Bytes and write 0 Bytes to disk\n",
+      "- epymorph.adrio.prism.Precipitation will download 1.2 MB and write 1.2 MB to disk\n",
+      "In total we will:\n",
+      "- Download 1.2 MB, taking a second (assuming 1.0 MB/s)\n",
+      "- Write 1.2 MB to disk cache (you have 249.1 GB free space)\n"
+     ]
+    }
+   ],
    "source": [
     "from epymorph.geography.us_census import CountyScope\n",
     "from epymorph import *\n",
@@ -77,12 +90,22 @@
     "    },\n",
     ")\n",
     "\n",
-    "precipitation = evaluate_param(rume, \"precipitation\")"
+    "rume.estimate_data()\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with sim_messaging():\n",
+    "    precipitation = evaluate_param(rume, \"precipitation\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -164,9 +187,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ADRIO data usage estimation:\n",
+      "- epymorph.adrio.prism.Temperature will download 51.0 MB and write 51.0 MB to disk\n",
+      "- epymorph.adrio.us_tiger.GeometricCentroid will download 0 Bytes and write 0 Bytes to disk\n",
+      "In total we will:\n",
+      "- Download 51.0 MB, taking 51 seconds (assuming 1.0 MB/s)\n",
+      "- Write 51.0 MB to disk cache (you have 249.1 GB free space)\n"
+     ]
+    }
+   ],
    "source": [
     "from epymorph.geography.us_census import StateScope\n",
     "from epymorph import *\n",
@@ -186,25 +222,46 @@
     "    scope=state_scope,\n",
     "    time_frame=time_period,\n",
     "    params={\n",
+    "        \"temperature\": prism.Temperature(time_period, \"Mean\"),\n",
     "        \"population\": acs5.Population(),\n",
     "        \"centroid\": us_tiger.GeometricCentroid(),\n",
-    "        \"temperature\": prism.Temperature(time_period, \"Mean\"),\n",
     "    },\n",
     ")\n",
     "\n",
-    "temperature = evaluate_param(rume, \"temperature\")"
+    "rume.estimate_data()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "States: ['04']\n",
+      "Loading epymorph.adrio.us_tiger.GeometricCentroid:\n",
+      "  |####################| 100%  (4.787s)\n",
+      "Loading epymorph.adrio.prism.Temperature:\n",
+      "  |####################| 100%  (21.742s)\n"
+     ]
+    }
+   ],
+   "source": [
+    "with sim_messaging():\n",
+    "    temperature = evaluate_param(rume, \"temperature\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Counties: ['04']\n",
       "\n",
       "Temperature in Celsius:\n",
       " [[18.10199928]\n",
@@ -242,7 +299,7 @@
     }
    ],
    "source": [
-    "print(f\"States: {geoids}\\n\")\n",
+    "print(f\"Counties: {geoids}\\n\")\n",
     "\n",
     "print(f\"Temperature in Celsius:\\n {temperature}\\n\")"
    ]
diff --git a/epymorph/adrio/prism.py b/epymorph/adrio/prism.py
index 0d8188e9..67ceb6d4 100644
--- a/epymorph/adrio/prism.py
+++ b/epymorph/adrio/prism.py
@@ -10,20 +10,55 @@
 from numpy.typing import NDArray
 from typing_extensions import override
 
-from epymorph.adrio.adrio import Adrio
-from epymorph.cache import load_or_fetch_url, module_cache_path
+from epymorph.adrio.adrio import Adrio, ProgressCallback, adrio_cache
+from epymorph.cache import check_file_in_cache, load_or_fetch_url, module_cache_path
 from epymorph.data_shape import Shapes
 from epymorph.data_type import CentroidType
+from epymorph.data_usage import DataEstimate
 from epymorph.error import DataResourceException
 from epymorph.geography.scope import GeoScope
 from epymorph.geography.us_census import STATE, CensusScope
+from epymorph.geography.us_tiger import CacheEstimate
 from epymorph.simulation import AttributeDef, TimeFrame
 
 _PRISM_CACHE_PATH = module_cache_path(__name__)
 
 
+def _generate_file_name(
+    attribute: str,
+    latest_date: datetype,
+    last_completed_month: datetype,
+    date: datetype,
+) -> tuple[str, str]:
+    """
+    Generates the url for the given date and climate attribute. Returns a tuple
+    of strings with the url and the name of the bil file within the zip file.
+    """
+
+    if date.year == latest_date.year and date.month == latest_date.month:
+        stability = "early"
+
+    # if it is before the last finished month
+    elif date > last_completed_month:
+        stability = "provisional"
+
+    # if it is older than 6 completed months
+    else:
+        stability = "stable"
+
+    # format the date for the url
+    formatted_date = date.strftime("%Y%m%d")
+    year = date.year
+
+    url = f"https://ftp.prism.oregonstate.edu/daily/{attribute}/{year}/PRISM_{attribute}_{stability}_4kmD2_{formatted_date}_bil.zip"
+
+    bil_name = f"PRISM_{attribute}_{stability}_4kmD2_{formatted_date}_bil.bil"
+
+    return url, bil_name
+
+
 def _fetch_raster(
-    attribute: str, date_range: TimeFrame
+    attribute: str, date_range: TimeFrame, progress: ProgressCallback
 ) -> Generator[BytesIO, None, None]:
     """
     Fetches the raster values at the url with the given attribute and date range.
@@ -43,26 +78,13 @@ def _fetch_raster(
     six_months_ago = datetype.today() + relativedelta(months=-6)
     last_completed_month = six_months_ago.replace(day=1) - timedelta(days=1)
 
-    for single_date in date_list:
-        if (
-            single_date.year == latest_date.year
-            and single_date.month == latest_date.month
-        ):
-            stability = "early"
-
-        # if it is before the last finished month
-        elif single_date > last_completed_month:
-            stability = "provisional"
+    # for progress tracking
+    processing_steps = len(date_list) + 1
 
-        # if it is older than 6 completed months
-        else:
-            stability = "stable"
-
-        # format the date for the url
-        formatted_date = single_date.strftime("%Y%m%d")
-        year = single_date.year
-
-        url = f"https://ftp.prism.oregonstate.edu/daily/{attribute}/{year}/PRISM_{attribute}_{stability}_4kmD2_{formatted_date}_bil.zip"
+    for i, single_date in enumerate(date_list):
+        url, bil_name = _generate_file_name(
+            attribute, latest_date, last_completed_month, single_date
+        )
 
         # load/fetch the url for the file
         try:
@@ -71,18 +93,23 @@ def _fetch_raster(
         except Exception as e:
             raise DataResourceException("Unable to fetch PRISM data.") from e
 
-        file.name = f"PRISM_{attribute}_{stability}_4kmD2_{formatted_date}_bil.bil"
+        # if the progress isnt None
+        if progress is not None:
+            # progress by one, increasing percentage done
+            progress((i + 1) / processing_steps, None)
+
+        file.name = bil_name
 
         yield file
 
 
 def _make_centroid_strategy_adrio(
-    attribute: str, date: TimeFrame, centroids: NDArray
+    attribute: str, date: TimeFrame, centroids: NDArray, progress: ProgressCallback
 ) -> NDArray[np.float64]:
     """
     Retrieves the raster value at a centroid of a granularity.
     """
-    raster_files = _fetch_raster(attribute, date)
+    raster_files = _fetch_raster(attribute, date, progress)
     results = []
 
     # read in each file
@@ -128,6 +155,56 @@ def _validate_scope(scope: GeoScope) -> CensusScope:
     return scope
 
 
+def _estimate_prism(
+    self, file_size: int, date_range: TimeFrame, attribute: str
+) -> DataEstimate:
+    """
+    Calculate estimates for downloading PRISM files.
+    """
+    est_file_size = file_size
+    total_files = date_range.duration_days
+
+    # setup urls as list to check if theyre in the cache
+
+    # setup date variables
+    first_day = date_range.start_date
+    last_day = date_range.end_date
+    latest_date = datetype.today() - timedelta(days=1)
+    six_months_ago = datetype.today() + relativedelta(months=-6)
+    last_completed_month = six_months_ago.replace(day=1) - timedelta(days=1)
+    date_list = [
+        first_day + timedelta(days=x) for x in range((last_day - first_day).days + 1)
+    ]
+
+    # get url names to check in cache
+    urls = [
+        _generate_file_name(attribute, latest_date, last_completed_month, day)[0]
+        for day in date_list
+    ]
+
+    # sum the files needed to download
+    missing_files = total_files - sum(
+        1 for u in urls if check_file_in_cache(_PRISM_CACHE_PATH / Path(u).name)
+    )
+
+    # calculate the cache estimate
+    est = CacheEstimate(
+        total_cache_size=total_files * est_file_size,
+        missing_cache_size=missing_files * est_file_size,
+    )
+
+    key = f"prism:{attribute}:{date_range}"
+    return DataEstimate(
+        name=self.full_name,
+        cache_key=key,
+        new_network_bytes=est.missing_cache_size,
+        new_cache_bytes=est.missing_cache_size,
+        total_cache_bytes=est.total_cache_size,
+        max_bandwidth=None,
+    )
+
+
+@adrio_cache
 class Precipitation(Adrio[np.float64]):
     """
     Creates an TxN matrix of floats representing the amount of precipitation in an area,
@@ -141,12 +218,19 @@ class Precipitation(Adrio[np.float64]):
     def __init__(self, date_range: TimeFrame):
         self.date_range = _validate_dates(date_range)
 
+    def estimate_data(self) -> DataEstimate:
+        file_size = 1_200_000  # no significant change in size, average to about 1.2MB
+        est = _estimate_prism(self, file_size, self.date_range, "ppt")
+        return est
+
     @override
     def evaluate_adrio(self) -> NDArray[np.float64]:
         scope = self.scope
         scope = _validate_scope(scope)
         centroids = self.data("centroid")
-        raster_vals = _make_centroid_strategy_adrio("ppt", self.date_range, centroids)
+        raster_vals = _make_centroid_strategy_adrio(
+            "ppt", self.date_range, centroids, self.progress
+        )
         return raster_vals
 
 
@@ -163,13 +247,23 @@ class DewPoint(Adrio[np.float64]):
     def __init__(self, date_range: TimeFrame):
         self.date_range = _validate_dates(date_range)
 
+    def estimate_data(self) -> DataEstimate:
+        year = self.date_range.end_date.year
+
+        # file sizes are larger after the year 2020
+        if year > 2020:
+            file_size = 1_800_000  # average to 1.8MB after 2020
+        else:
+            file_size = 1_400_000  # average to 1.4MB 2020 and before
+        return _estimate_prism(self, file_size, self.date_range, "tdmean")
+
     @override
     def evaluate_adrio(self) -> NDArray[np.float64]:
         scope = self.scope
         scope = _validate_scope(scope)
         centroids = self.data("centroid")
         raster_vals = _make_centroid_strategy_adrio(
-            "tdmean", self.date_range, centroids
+            "tdmean", self.date_range, centroids, self.progress
         )
         return raster_vals
 
@@ -177,7 +271,7 @@ def evaluate_adrio(self) -> NDArray[np.float64]:
 class Temperature(Adrio[np.float64]):
     """
     Creates an TxN matrix of floats representing the temperature in an area, represented
-      in degrees Celsius (°C).
+    in degrees Celsius (°C).
     """
 
     date_range: TimeFrame
@@ -198,6 +292,17 @@ def __init__(self, date_range: TimeFrame, temp_var: TemperatureType):
         self.temp_var = temp_var
         self.date_range = _validate_dates(date_range)
 
+    def estimate_data(self) -> DataEstimate:
+        year = self.date_range.end_date.year
+        temp_var = self.temp_variables[self.temp_var]
+
+        # file sizes are larger after the year 2020
+        if year > 2020:
+            file_size = 1_700_000  # average to 1.7MB after 2020
+        else:
+            file_size = 1_400_000  # average to 1.4MB 2020 and before
+        return _estimate_prism(self, file_size, self.date_range, temp_var)
+
     @override
     def evaluate_adrio(self) -> NDArray[np.float64]:
         scope = self.scope
@@ -205,7 +310,7 @@ def evaluate_adrio(self) -> NDArray[np.float64]:
         temp_var = self.temp_variables[self.temp_var]
         centroids = self.data("centroid")
         raster_vals = _make_centroid_strategy_adrio(
-            temp_var, self.date_range, centroids
+            temp_var, self.date_range, centroids, self.progress
         )
 
         return raster_vals
@@ -214,7 +319,7 @@ def evaluate_adrio(self) -> NDArray[np.float64]:
 class VaporPressureDeficit(Adrio[np.float64]):
     """
     Creates an TxN matrix of floats representing the vapor pressure deficit in an area,
-      represented in hectopascals (hPa).
+    represented in hectopascals (hPa).
     """
 
     date_range: TimeFrame
@@ -231,11 +336,23 @@ def __init__(self, date_range: TimeFrame, vpd_var: VPDType):
         self.vpd_var = vpd_var
         self.date_range = _validate_dates(date_range)
 
+    def estimate_data(self) -> DataEstimate:
+        year = self.date_range.end_date.year
+
+        # file sizes are larger after the year 2020
+        if year > 2020:
+            file_size = 1_700_000  # average to 1.7MB after 2020
+        else:
+            file_size = 1_300_000  # average to 1.3MB 2020 and before
+        return _estimate_prism(self, file_size, self.date_range, self.vpd_var)
+
     @override
     def evaluate_adrio(self) -> NDArray[np.float64]:
         scope = self.scope
         scope = _validate_scope(scope)
         vpd_var = self.vpd_variables[self.vpd_var]
         centroids = self.data("centroid")
-        raster_vals = _make_centroid_strategy_adrio(vpd_var, self.date_range, centroids)
+        raster_vals = _make_centroid_strategy_adrio(
+            vpd_var, self.date_range, centroids, self.progress
+        )
         return raster_vals