NASA-IMPACT datashare program

Phenomena

High Latitude Dust

Dust aerosols in the atmosphere are known to modulate environmental conditions and the climate system through direct and indirect effects between the land–atmosphere–ocean system. High latitude dust (HLD) is defined as ”particles that are lifted from a surface and travel by suspension in the atmosphere”. Typically, these dust particles are of the range of tenths of μm or larger in size. In addition, dust events are considered high latitude when they are ≥ 50◦N and ≥ 40◦S. HLD tends to occur in specific conditions and is seasonally dependent. HLD events can last anywhere from several hours to several days.

Data Description:

1. Labeled events are stored in a folder with the following structure:

 high-latitude-dust_<date>_<id>:
   |> high-latitude-dust_<date>_<id>.dbf
   |> high-latitude-dust_<date>_<id>.prj
   |> high-latitude-dust_<date>_<id>.shp
   |> high-latitude-dust_<date>_<id>.shx

2. Images to be downloaded using GIBS. (https://gibs.earthdata.nasa.gov/wms/epsg4326/best/wms.cgi?SERVICE=WMS&REQUEST=GetMap&layers=MODIS_Aqua_CorrectedReflectance_TrueColor&version=1.3.0&crs=EPSG:4326&transparent=false&width={}&height={}&bbox={}&format=image/tiff&time={}) 2.a. Variables required:

   width = width of the image height = height of the image bbox = [left_latitude, left_longitude, right_latitude, right_longitude]

Note: Use the following for approximate width, height calculation and url generation.

URL = "https://gibs.earthdata.nasa.gov/wms/epsg4326/best/wms.cgi?SERVICE=WMS&REQUEST=GetMap&layers=MODIS_Aqua_CorrectedReflectance_TrueColor&version=1.3.0&crs=EPSG:4326&transparent=false&width={}&height={}&bbox={}&format=image/tiff&time={}"
KM_PER_DEG_AT_EQ = 111.


def calculate_width_height(extent, resolution):
    lats = extent[::2]
    lons = extent[1::2]
    km_per_deg_at_lat = KM_PER_DEG_AT_EQ * np.cos(np.pi * np.mean(lats) / 180.)
    width = int((lons[1] - lons[0]) * km_per_deg_at_lat / resolution)
    height = int((lats[1] - lats[0]) * KM_PER_DEG_AT_EQ / resolution)
    print(width, height)
    return (width, height)


def modis_url(time, extent, resolution):
    width, height = calculate_width_height(extent, resolution)
    extent = ','.join(map(lambda x: str(x), extent))
    return (width, height, URL.format(width, height, extent, time))

You can find the example notebook here

You can download the files from: s3://hld-datashare. You will need an AWS account to download the data.

Cloud Streets

Background

The organization of cumulus clouds into elongated rows oriented parallel to the mean boundary layer flow is a phenomenon often referred to as cloud streets. Organized cumulus cloud streets are the visual manifestation of underlying boundary layer roll circulations commonly referred to as horizontal convective rolls. Formation of boundary layer rolls is attributed to two instability mechanisms – thermal and dynamic instability.

Direct impacts of cloud streets are fairly minimal as they typically do not precipitate or have meaningful environmental impacts aside from surface radiation. The effects of cloud streets are most notable in the presence of sea breeze circulations as intersections of roll circulations and sea breeze circulations are known to force convective initiation. Coastal convection is a primary source of precipitation in these settings and can grow upscale to propagating mesoscale convective systems that modulate the regional and even global precipitation budgets.

Data Description:

1. Folder Structure:

 Cloud Streets/
     |> yes
        |> <images>
     |> no
        |> <images>

2. Data type: images, jpg

You can download the files from: s3://cloudstreet-datashare. You will need an AWS account to download the data.