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46 | 46 | import shapely.vectorized
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47 | 47 | import shapely.wkt
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48 | 48 | from cartopy.io import shapereader
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| 49 | +from pyproj import Geod |
49 | 50 | from shapely.geometry import MultiPolygon, Point, Polygon, box
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50 | 51 | from sklearn.neighbors import BallTree
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51 | 52 |
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@@ -526,6 +527,59 @@ def compute_grid_cell_area(res: float) -> tuple[np.ndarray]:
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526 | 527 | return grid_area, [lat_bins, lon_bins]
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527 | 528 |
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528 | 529 |
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| 530 | +def compute_grid_cell_area_( |
| 531 | + res: float = 1.0, projection: str = "WGS84", units: str = "km^2" |
| 532 | +) -> np.ndarray: |
| 533 | + """ |
| 534 | + Compute the area of each grid cell in a latitude-longitude grid. |
| 535 | +
|
| 536 | + Parameters: |
| 537 | + ----------- |
| 538 | + res: float |
| 539 | + Grid resolution in degrees (default is 1° x 1°) |
| 540 | + projection: str |
| 541 | + Ellipsoid or spherical projection to approximate Earth. To get the complete list of |
| 542 | + projections call :py:meth:`pyproj.get_ellps_map()`. Widely used projections: |
| 543 | + - "WGS84": Uses the WGS84 ellipsoid (default) |
| 544 | + - "GRS80" |
| 545 | + - "IAU76" |
| 546 | + - "sphere": Uses a perfect sphere with Earth's mean radius (6371 km) |
| 547 | + units: str (optional) Default "km^2" |
| 548 | + units of the area. Either km^2 or m^2. |
| 549 | +
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| 550 | + Returns: |
| 551 | + -------- |
| 552 | + area: np.ndarray |
| 553 | + A 2D numpy array of grid cell areas in km² |
| 554 | + Example: |
| 555 | + -------- |
| 556 | + >>> area = compute_grid_areas(res = 1, projection ="sphere", units = "m^2") |
| 557 | + """ |
| 558 | + geod = Geod(ellps=projection) # Use specified ellipsoid model |
| 559 | + |
| 560 | + lat_edges = np.linspace(-90, 90, int(180 / res)) # Latitude edges |
| 561 | + lon_edges = np.linspace(-180, 180, int(360 / res)) # Longitude edges |
| 562 | + |
| 563 | + area = np.zeros((len(lat_edges) - 1, len(lon_edges) - 1)) # Create an empty grid |
| 564 | + |
| 565 | + # Iterate over consecutive latitude and longitude edges |
| 566 | + for i, (lat1, lat2) in enumerate(zip(lat_edges[:-1], lat_edges[1:])): |
| 567 | + for j, (lon1, lon2) in enumerate(zip(lon_edges[:-1], lon_edges[1:])): |
| 568 | + |
| 569 | + # 5th point to close the loop |
| 570 | + poly_lons = [lon1, lon2, lon2, lon1, lon1] |
| 571 | + poly_lats = [lat1, lat1, lat2, lat2, lat1] |
| 572 | + |
| 573 | + # Compute the area of the grid cell |
| 574 | + poly_area, _ = geod.polygon_area_perimeter(poly_lons, poly_lats) |
| 575 | + area[i, j] = abs(poly_area) # Convert from m² to km² |
| 576 | + |
| 577 | + if units == "km^2": |
| 578 | + area = area / 1e6 |
| 579 | + |
| 580 | + return area |
| 581 | + |
| 582 | + |
529 | 583 | def grid_is_regular(coord):
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530 | 584 | """Return True if grid is regular. If True, returns height and width.
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531 | 585 |
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