Development of High Resolution Gridded Dew Point Data from Regional Networks North Central Climate Science Center Open Science Conference May 20, 2015 Ruben Behnke Numerical Terradynamic Simulation Group University of MT
Project Goal Use Station Data to Create Gridded Dew Point Data No longer estimate dew point from temperature, precipitation, day length, etc.
1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Measuring Humidity A Very Brief History 18000 Number of Stations Measuring Humidity (North America - 23 N to 53 N)* 16000 14000 12000 10000 8000 6000 Widespread drop in meteorological observations Regional Networks begin to emerge Meteorological Assimilation Data Ingestion System 4000 2000 0 * Stations must have at least 2/3 of hourly data for all 12 months for a total period of one year
MTCLIM MTCLIM is an empirical model developed to predict ET. To do so, it also estimates humidity and solar radiation. Topographical Effects - Slope, aspect, elevation modify incoming solar radiation - Elevation modifies temperatures (standard lapse rate) - Precipitation not modified by elevation, but snowpack effects on radiation included Diurnal Climatology - developed to estimate ET, so only daylight radiation, dew point, and temperature are estimated
How does MTCLIM estimate dew point? Minimum Temperature = Dew Point Is the region arid? - Receives < 8 cm precipitation (annual) NO YES Is annual PET/Precip > 2.5 NO YES Perform iterative algorithm between humidity and radiation to estimate dew point Set dew point = Minimum Temperature Set dew point = Minimum Temperature Daily dew point based on day length, antecedent precipitation ( effective annual precip ), and if precip occurred on that day or not (reduces radiation by 25% if yes )
MTCLIM Dew Point Mean Bias ( C) 15 10 MTCLIM Dew Point - Observed Dew Point; Humid Location - PET/prcp = 1.679 Seasonal Bias: Time of Year and Magnitude are Location Dependent 5 0-5 -10 Date
MTCLIM Dew Point Mean Bias ( C) 15 10 5 MTCLIM Dew Point - Observed Dew Point; Arid Location - PET/Prcp = 9.025 - Overall underestimation of Dew Point - Seasonal Biases still evident - Overall biases larger than humid location - Large day to day variation in accuracy 0-5 -10-15 -20 Date
Moving Forward Regional Networks MesoNets OK MesoNet Ag/Severe Weather West TX MesoNet Ag/Irrigation Ohio Dept. of Transportation WSU AgWXNet
MADIS Meteorological Assimilation Data Ingestion System https://madis.noaa.gov/ 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 18000 16000 14000 12000 10000 8000 6000 4000 2000 Number of Stations Measuring Humidity 0 Image source: http://research.noaa.gov/news/newsarchive/latestnews/tabid/684/artmid/1768/articled/11037/ NOAA%e2%80%99s-growing-weather-observations-database-goes-into-full-operations.aspx
Project Progress: Quality Control of Humidity Data Extreme Variance
Spikes, Outliers, Station Drift, and more!
Sensor Drift Relative Humidity
Summary 1. Humidity data exist and are available, but it is still a MAJOR challenge to download and process 2. Quality Control is a very significant challenge, but is nearing completion a) QC routines for humidity not nearly as refined or readily available for humidity as for temperature b) Need to QC both temperature and RH to do it correctly 3. Questions to be answered a) Is MTCLIM algorithm still needed? - Daymet (1980); UIdaho (1979) b) How far back can we go using only station data? - MADIS (2001 current) c) Is it possible to go forward using MADIS to produce near real time updates? 4. Updated humidity climatology may be needed a) Robinson (1998) and Gaffen and Ross (1998) go through 1990 b) Other climatologies focus on trends
Thank You! Questions, comments, or suggestions? Email: ruben.behnke@ntsg.umt.edu
Talk Outline 1. Project Goal 2. Historical Overview of Humidity Observations - Lack of Observations - MTCLIM 3. Regional Networks or Mesonets - Purposes - Drastic increase in humidity observations since 2000 4. New Data brings New Challenges - Quality Control
Why do we care about humidity? Forest Fires Human and Animal Comfort Evapotranspiration Estimation Agriculture, Ecology, Hydrology, and More Image source: http://watercenter.unl.edu/archives/2010mappinget.asp
MTCLIM makes 3 major assumptions 1) In humid environments, TMIN = average daily dew point a) Also assumes minimum temperature reaches dew point 2) Dew point remains constant throughout the day 3) Dew point is calculated for daylight hours only; nighttime doesn t matter a) Designed for plant physiology purposes (ET) b) Meteorologically speaking, this is not valid