Review of this historic and new ages from these lobes, filtered with reproducibility and quality criteria when combined with consideration of stratigraphic context has yield a new chronology. The resulting several hundred individual ages constraint the ice sheet in space and time. This location also affords abundant organic materials for radiocarbon dating that has been underway for several decades and continues.
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These lobes then reflect the dynamics of a temperate sector of the largest relic ice sheet. Both imply that a simple climate forcing for the ice sheet is inadequate.Ībstract = "The Great Lakes Lobes of Laurentide Ice Sheet lie closer to the equator than the north pole. If so, the existing models of mass delivery could be updated.
![new relic timeslice new relic timeslice](https://nr-production-discourse.s3.dualstack.us-east-1.amazonaws.com/original/3X/2/2/228b66a7fd6fede430e1454f1bbcaf3ebb6376c7.png)
2) the main source of ice for the Great Lake Lobes was from the NE, not the N as most current modeling experiments suggest. If so, reconstructions of the flow line geometries require reevaluation. Two working hypothesis emerge 1) the smaller area was dynamically linked with the larger area for only one expansion. One implication is the Last Glacial Maximum was maintained for between 5 and 10 ka with three fluctuations. Our preliminary results suggest the following: 1) nearly equal 2/3 of the region displays a similar history of ice sheet growth and decay, the remaining 1/3 has one time slice with a common history 2) the ice sheet expanded into the larger region three times ( nearly equal 27 ka 23.5 ka 21.5 ka) 3) the ice sheet retreated from the larger region after nearly equal 21 ka rapidly at first, but in a step wise manner forming moraines from 20.0 to nearly equal 16.5 ka, 4) the smaller area was not reoccupied at 21.5 ka. These attributes are available in addition to the metric-specific attributes listed in the APM metrics table above.The Great Lakes Lobes of Laurentide Ice Sheet lie closer to the equator than the north pole. To understand more about the general structure of metric timeslice data, including some common examples, see Metric timeslice data.
NEW RELIC TIMESLICE HOW TO
Learn how to see all metrics available to you. KeyTransactionName, transactionName, transactionTypeĪpm.Įxternal call response time by transaction type Response time for external calls broken out by external host name Response time for database calls broken out by table operations Here are how the original APM metric timeslice metrics are converted into dimensional metrics: If you don't see a metric you're looking for in this section, see Generic queries. The conversion of original APM metric timeslice metrics into dimensional metrics that are available for querying is an ongoing process and isn't complete. This optional clause displays the results in a time-based chart.įor general information on NRQL syntax, including FROM, FACET, and TIMESERIES, see Intro to NRQL.įor more queries, see Query examples. Sets the transaction type to web, meaning that background/non-web transactions won't be counted. This query uses entity.guid, but you can also use appId or appName.
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You can select a single entity's GUID, as shown here, or you can select multiple sources. You must specify at least one data source. Note that you can use other aggregator functions. This query uses the converted metric names. This math generates a count of errors out of a total count of transaction metrics. For general tips on querying Metric data, see Metric query examples. Metric is one of our core data types, and metric timeslice data is stored as this data type.