
thumb|upright=1.35|Map of Doggerland at its near maximum extent c. 10,000 years Before Present (~8,000 BCE) (top left) and its subsequent disintegration by 7,000 BP (~5,000 BCE) Doggerland was a large area of land in Northern Europe, now submerged beneath the southern North Sea. This region was repeatedly exposed at various times during the Pleistocene epoch due to the lowering of sea levels during glacial periods. However, the term "Doggerland" is generally specifically used for this region during the Late Pleistocene and Early Holocene. During the early Holocene following the glacial re
thumb|upright=1.35|Map of Doggerland at its near maximum extent c. 10,000 years Before Present (~8,000 BCE) (top left) and its subsequent disintegration by 7,000 BP (~5,000 BCE) Doggerland was a large area of land in Northern Europe, now submerged beneath the southern North Sea. This region was repeatedly exposed at various times during the Pleistocene epoch due to the lowering of sea levels during glacial periods. However, the term "Doggerland" is generally specifically used for this region during the Late Pleistocene and Early Holocene. During the early Holocene following the glacial retreat at the end of the Last Glacial Period, the exposed land area of Doggerland stretched across the region between what is now the east coast of Great Britain, northern France, Belgium, the Netherlands, north-western Germany, and the Danish peninsula of Jutland. Between 10,000 and 7,000 years ago, Doggerland was inundated by rising sea levels, disintegrating initially into a series of low-lying islands before submerging completely. The impact of the tsunami generated by the Storegga underwater landslide 8,200 years ago on Doggerland is controversial. The flooded land is known as the Dogger Littoral.
Doggerland was named after the present-time Dogger Bank (which in turn was named after 17th-century Dutch fishing boats called doggers), which is the remains of a highland region that became submerged later than the rest of Doggerland.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).