Articles

How does the drought of 2012 compare to earlier droughts in Kansas, USA?

by:  Aavudai Anandhi, Mary Knapp 

Volume 2016, No. 1, 23 May 2016

Drought is a complex, least understood and one of the most expensive natural disaster. Drought impacts many sectors of environment and society. A regular question is how a current drought compares to previous droughts. Water managers, resource managers, news media and the general public want to place the event in context as they evaluate impacts, and as they attempt to plan for future events. There are many definitions of drought (meteorological, agricultural, hydrological and socioeconomic) resulting in a large number of drought metrics and indices in literature. In this study we have used Standardized Precipitation Index (SPI), a useful tool to answer these questions. SPI is a transformation of the probability of a given amount of precipitation in a set period of months. This allows for the comparison of wet/dry spells over extremely different climates and over various time scales from one month to two years (24 months).

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Growing Degree Day Calculation Method Comparison between Two Methods in the Northern Edge of the US Corn Belt

by:  F. Adnan Akyüz, Joel K. Ransom 

Volume 2015, No. 2, 18 Dec 2015

The use of environmental temperature and its effects on plant development have been useful in determining growth stages of plants. This paper compares two Corn Growing Degree Day (GDD) calculation methods that are widely used in the US and why one is more suitable in the northern edge of the US corn-belt areas than the other. The comparison between the two accumulated GDD calculations for corn during the last 67-year period from 1948 to 2014 growing seasons for Fargo, ND, indicates that one method systematically underestimates accumulated GDDs during the days when maximum temperatures are above and minimum temperatures are below the base temperature of 50°F. Furthermore, the ratio of the difference between the two seasonal accumulations to the required accumulated GDD necessary to mature the type of corn grown in this area becomes more significant than those grown in other parts of the US where corn requires higher seasonal GDD accumulations. 

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Development of a Long-Term (1884-2006) Serially Complete Dataset of U.S. Temperatures and Precipitation for Climate Services

by: Jinsheng You, Kenneth G Hubbard, Martha Shulski

Volume 2015, No. 1, 31 Jan 2015

Serially complete climate datasets with no missing data are necessary for a diverse group of users working in many economic sectors. In this article we describe the procedures used to create a Serially Complete Data set (SCD) for the U.S. We include the selection criterion applied to potential SCD stations, the various procedural steps and the details applied to each step. A few observations that were not previously digitized were obtained from observers official paper reports. The methods used to estimate missing data are the Spatial Regression Test and the Inverse Distance Weighting technique. Using the criterion for selecting stations we were able to include 2144 stations for the SCD that had at least 1 element (maximum/minimum temperature and/or precipitation) for a continuous period of at least 40 years. In addition, the quality control procedure assigned confidence intervals to all observations and many of the estimates. We continue to explore the options for estimating any missing data that remain after our 3 step approach and we look forward to changing the base data set form TD 3200 to GHCN.

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Winter Wind Chill Climatology for the High Plains Region

by: Holly B. Lussenden, Natalie A. Umphlett, Martha D. Shulski, Daniel Ebert

Volume 2014, No. 1, 14 May 2014

During the winter months in the High Plains region of the United States, wind chill temperatures can reach dangerous levels for humans and animals. Knowing the frequency in which extreme wind chill temperatures occur could help forecasters know when to issue wind chill advisories and also the general public understand just how rare, or common, certain wind chill temperatures are. A climatology spanning a 37-year period was created using data from 57 stations in and around the plains portion of the High Plains region from the Integrated Surface Hourly Database at National Climatic Data Center (NCDC). These climatologies were completed for December, January, February, and the winter season as a whole, for the number of hours and days in which wind chills reach certain thresholds. Also included is an all-time low wind chill value by location. As one might expect, results show that some of the most extreme and more frequent low wind chill temperatures in the region occur in eastern North Dakota and northwestern Minnesota. In this area, several days per year can reach -40°F or lower, a temperature at which frostbite can occur within minutes. The highest number of wind chills less than or equal to -10°F occurred in January, with December and February having similar distributions of wind chill occurrence.

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PROCEDURE FOR ASSIGNING A VALUE FOR TRACE PRECIPITATION DATA WITHOUT CHANGING THE CLIMATIC HISTORY

by: Adnan Akyüz, Karsten Shein, Mike Asmus

Volume 2013, No.1, 31 May 2013

Trace is the amount of precipitation that is less than 0.005” (AMS, 1959). Generally, it is not a measurable amount but just enough to wet the rain gauge that it is observed in. It is a global practice that “T” (indicating “Trace”) is entered in daily precipitation records such as the National Weather Service form B-91 under the precipitation column. Although trace is not a quantitative value, it is valuable information to better assess the weather condition of the day. However, when the precipitation data are tabulated, most spreadsheet programs do not know how to deal with a character that is not a numerical value. We explain a procedure for including trace observations when evaluating precipitation behavior over a period of time or between multiple time periods. This procedure temporarily assigns a computationally insignificant value to trace observations in order to incorporate those observations into database calculations (e.g. number of precipitation days) as well as also greatly reduce the chance of ties in the precipitation rankings. Our procedure allowed us to separate individual precipitation events in perspective especially in ranking tables without changing accumulated monthly, seasonal or annual precipitation values, thus preserving the climate history of the location.

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