Performance Study of Air Humidity/Water Vapor Monitoring Systems

for the	Climate Reference Network (CRN)

Submitted to:

National Oceanic and Atmospheric Administration

National Environmental Satellite, Data & Information Service

National Climate Data Center

Submitted by

High Plains Regional Climate Center

University of Nebraska

Principal Investigators:

Kenneth G. Hubbard

and

Xiaomao Lin

244 Chase Hall

High Plains Regional Climate Center

University of Nebraska

Lincoln NE 68583-0728

email: khubbard@unl.edu

Telephone: 402-472-8294

First Submitted:	October 08, 2001

Latest Revision Submitted: Jan. 22, 2002

Table of Contents

Page No.

1.	Atmospheric Water Vapor in Surface Layer ..................................................... 3

2.	Water Vapor/Air Humidity Variables and Algorithms ......................................5

3.	Water Vapor Measurements in Surface Observations........................................ 8

4.	Project Description ............................................................................................13

4.1 Scope of Sensor Testing

4.2 General Experimental Procedures

4.3 Candidate Humidity Sensors

4.4 Calibrations and Maintenance

4.5 Experimental Site Selections and Data Acquisition System

4.6 Project Schedule

5.	References ........................................................................................................ 23

6.	Appendix .......................................................................................................... 27

6.1 Algorithms of Water Vapor Pressure

6.2 Lists of Manufacturers for Air Humidity Measurements

6.3 Conversion Errors and Differences between WMO and NIST

1.	Atmospheric Water Vapor in Surface Layer (Why)

Water vapor is one of the most important variables of the atmosphere and high quality humidity measurements are essential for better understanding of the interactions between the atmosphere and the earth's surface. The importance of monitoring air humidity is widely associated with the hydrological cycle, land/ocean surface energy budget, biological environment including human animal adaptation, and substantial agriculture operations (water resource management, scientific irrigation decisions, plant evapotranspiration, water use efficiency, and plant photosynthesis). A knowledge of the spatial and temporal domains is important for understanding the global, regional, and micro scale processes. Without the air vapor water/humidity information, it is impossible for us to completely investigate the changes in atmosphere.

The source and the sink for almost all water in the atmosphere is the earth's surface, through evaporation and precipitation (Elliott, 1995). The complete hydrological cycle is characterizing in Figure 1. The hydrological cycle provides a model for understanding the global plumbing system. It is a closed system because water (or water vapor) is neither created nor destroyed. The evaporation and precipitation maintain the water balance from the global scale to the micro scale.

Fig 1. Scheme of Hydrological Cycle

The mechanism of precipitation formation involves phase change from water vapor to liquid or solid and the concurrent release of latent heat to the cloud systems. Thus, water vapor acts as a delivery mechanism in the redistribution of global energy. Water vapor determines the potential for evaporation and transpiration processes of the hydrological cycle (Figure 1).

Water vapor evaporated from the surface and moved about by atmospheric motions plays a very significant part in the atmosphere's energy budget because (1) latent energy taken up at the time of evaporation is carried wherever the water vapor is transported; (2) latent heat is released upon condensation and contributes to cloud buoyancy; and (3) the formation of clouds alter the radiation budget. A large portion of the energy transferred between the surface and free atmosphere is in the form of latent heat. The redistribution of this latent heat and its realization through condensation and precipitation is a main energy source for the general circulation (Elliott, 1995). This latent heat (LE) can only be monitored through humidity measurements but, it is a key component in the surface energy budget for global environmental issues and field water resource management issues. Changes in near-surface humidity will lead to changes in the evaporation and transpiration. This is critical to climate change because the net energy is partitioned between the sensible heat (temperature dependent) and latent heat (water vapor dependent). The accuracy and calibration of air humidity and solar radiation sensors are more critical than wind speed and air temperature in estimation of potential evapotranspiration (Meyer et al., 1986).

Many of the models used to estimate the effects of greenhouse gases portray an increasing water vapor concentration as the atmosphere warms, 20% to 30% in response to CO2 doubling. This increase is expected if only because the saturation vapor pressure increases with temperature. Thus, if the relative humidity stays the same, the warmer air will hold more water vapor. The water vapor content in turn would increase the warming. This positive feedback of water vapor is one of the largest factors acting to amplify the effects of increased greenhouse gas concentrations (Elliott, 1995). Any trends in temperature translate to a trend in the potential for air to hold water vapor. Even for carbon balance or photosynthetic activities, the water vapor variable plays an important role (Rosenberg, 1983).

During the past decade, investigations on climate data homogeneity have found air temperature data discontinuities (Karl et al., 1989; Quayle et al., 1991; Gall et al., 1992; and Kessler et al., 1993; Guttamn and Baker, 1996) due to the air temperature instruments or sensors. The upgrading of surface air temperature observation systems often occurs simultaneously with the upgrade of air humidity measurement. This is true for the transition in the first-class network (HO-
31, HO-50, HO-63, to recent HO-83 and ASOS Model 1088). One can expect similar problems exist with the humidity records in surface observations (Gaffen and Ross, 1998; Fleming, 1998), not only because the temperature records are contain errors so conversions to other humidity variables are effected, but the exposure problems found for the temperature sensors may also be present for the humidity sensors.

2.	Water Vapor/Air Humidity Variables and Algorithms (What)

There are a number of variables that reflect the amount of water vapor in the air. As most depend in one fashion or another on the temperature of the parcel being considered, almost any measurement of a water vapor variable is accompanied by a measurement of temperature. The following symbols will be used in this section in discussing water vapor measurements.

e = Vapor pressure or partial pressure of vapor in air, millibars.

ei = Vapor pressure with respect to ice, millibars at Tf.

ew = Vapor pressure with respect to water, millibars at Td.

eis, ews = Saturation vapor pressure with respect to ice (I) or water (w), millibars

T = temperature, oC

Ta = Ambient or dry bulb temperature, oC

Td = Dew point temperature, oC

Tf = Frost point temperature, oC

Tw = Wet bulb temperature, oC

P = total pressure of air, millibars

f(p) = Enhancement factor

RH = Relative humidity, %

W = Mixing ratio

Atmospheric humidity refers to the water vapor content in air. Humidity measurements can be stated in a variety of terms and units. Commonly used terms are absolute humidity, relative humidity (RH), dew/frost point temperature, wet bulb temperature, and vapor pressure.

Absolute Humidity is defined as the water vapor density and is expressed as water vapor mass per unit volume of dry air. Absolute humidity can be expressed as follows,

(1)

Therefore, it can be calculated from known RH and dry bulb temperature. In addition, the water vapor content can be expressed as parts per million by volume (ppmv) (mixing ratio) or parts per million by weight (ppmw).

Dew Point Temperature is defined as the temperature to which a given parcel of air must be cooled at constant pressure and constant water vapor content in order for saturation to occur. Since the saturation vapor pressure with respect to water is a function of temperature only, there exists a temperature Td for which ews is equal to ew. Td is independent of the air temperature as long as the air remains unsaturated. The saturation vapor pressure with respect to water is (Buck, 1981),

(2)

Note that there are other equations to calculate saturation water vapor pressure (See Appendix ). To derive the dew point temperature from relative humidity, ew is substituted for ews in Equation (2) where the resulting temperature is the dew point temperature (Td).

Frost Point Temperature is defined as the temperature to which a volume of air must be cooled, such that it becomes saturated with respect to ice. The saturation vapor pressure with respect to ice requires a minor adjustment of the constants in Equation (2) as given by the following (Buck, 1981),

(3)

Therefore, similarly the frost point temperature can be derived from Equation (3) based on the relation of eis and ei.

Relative Humidity is defined as the ratio of the actual partial vapor pressure to the saturation vapor pressure of the air, multiplied with 100% at the ambient temperature. In percentage terms

(4)

or

For the purposes of operational meteorology, relative humidity at temperatures below 0 oC is evaluated with respect to water [second equation in Equation (4)] (Simidchiev, 1986). Since the saturation vapor pressure ews is temperature dependent, relative humidity (RH) when expressed without the temperature is useful in a qualitative way. In scientific work, relative humidity must be treated according to whether a water or ice process is present and the temperature effect must be included.

Wet Bulb Temperature, Tw, of moist air at a given pressure and air temperature is the temperature attained when the moist air is brought adiabatically to saturation by evaporation of water into the moist air. A relationship between wet bulb temperature Tw, dry bulb temperature Td, and the humidity ratio W is as follows,

(5)

where Ww is the humidity mixing ratio at Tw. In terms of vapor pressure the mixing ratio can be expressed as follows,

(6)

Equation 5 requires an iterative solution because the variables involving Tw can not be separated mathematically. Through Equations (1) to (6), we can readily convert from one humidity variable to another.

The commonly reported variable related to air humidity is either dew point temperature or relative humidity along with air temperature, but these humidity related variables are not always measured directly. Rather, they are often calculated from another variable based on the air temperature (e.g., from dew point to relative humidity, or from relative humidity to dew point temperature) (ASHRAE, 1993). The errors involved in the calculation or derivation (error propagation) are serious because air temperature error and air pressure difference are propagated to the derived variables (Appleman, 1964; Gates, 1994, Elliott and Gaffen, 1993; Yilmaz, 1997; Lin and Hubbard 2000; and Hubbard et al, 2001). This is most serious when air temperature is below zero (Dery and Stieglitz, 2001). Additionally, changes in processing algorithms can lead to subtle differences in calculated variables which could then appear as apparent climate changes (Elliott and Gaffen, 1993; Wade, 1994; Hubbard et al., 2001). It should be noted that the relative humidity at temperatures less than 0 oC is evaluated with respect to water. The advantages of this algorithm are as follows,

(1) Most hygrometers which are essentially responsive to the relative humidity indicate relative humidity with respect to water at all temperatures.

(2) The surface fog at slightly below 0 oC consists of water, or mainly of water.

(3) Relative humidity greater than 100% would in general not be observed. This is particularly important in synoptic weather messages, since the atmosphere is often supersaturated with respect to ice at temperatures below 0 oC.

(4) The majority of existing records of relative humidity at temperature below 0 oC are expressed on a basis of saturation with respect to water.

3.	Water Vapor Measurements in Surface Observations (How)

The most important specifications for the atmospheric humidity measurements when selecting a humidity sensor are (WMO, 1996; Brown, 1997; Wiederhold, 1997a and 1997b; Hubbard, et al., 2001; Roveti, 2001):

Accuracy

Repeatability

Interchangeability

Long-term stability

Ability to recover from condensation

Resistance to chemical and physical contaminants

Size

Packaging

Cost effectiveness

Additional significant long–term factors are the costs associated with sensor replacement, field and lab calibrations, and the complexity and reliability of the signal conditioning and data acquisition circuitry.

The two basic types are fundamental (or primary) sensors and secondary sensors. Fundamental sensors are accurate and easy to understand, but typically very expensive. Secondary sensors, although easier to use, require a deeper knowledge of humidity for an understanding of their operating principles and how best to use them. All low-cost RH sensors are secondary sensors.

Fundamental sensors are based on well-defined thermodynamic principles, such as the condensation of water due to saturation or the mass of water contained in a volume of air. These physical properties do not require direct calibration. Examples include continuously controlled chilled mirror sensors, aspirated psychrometers, electrolytic sensors, and gravimetric instruments.

Secondary sensors are based on an observed property of a material that changes in response to humidity. They can be calibrated to correspond to either relative or absolute humidity. They respond to:

(1) Change in length, e.g., of hair, plant fiber, or nylon, as in the extension hygrometer;

(2) Change in weight, as in the absorption hygrometer;

(3) Change in impedance or capacitance, as in many electronic hygrometers. The general performance of humidity instrument are summarized in Table 1.

The surface meteorological observation requirements for the air temperature and air humidity measurements (WMO, 1996) are given in Table 2. Two technologies associated with two types of air humidity sensors emerge for the automated weather station observations. One is the chilled mirror hygrometer (fundamental sensor), the other is the capacitive RH sensors (secondary sensors) (Table 1).

The chilled mirror hygrometer is the most accurate, reliable, and fundamental hygrometer commercially available and is therefore widely used as a calibration standard. The principles of the chilled mirror hygrometer are illustrated in Fig. 2. The surface temperature of a small gold or rhodium-plated copper mirror is controlled by a thermoelectric cooler (heat pump). A high intensity light-emitting diode (LED) illuminates the mirror. The quantity of reflected light from the mirror surface is detected by a photo-transistor or optical detector. The temperature reading from the temperature sensor (usually a highly precise PRT sensor) embedded within the mirror surface is the dew point temperature when the a dew layer is maintained on the mirror surface. The advantages include:

(1) Based on fundamental measurement principle, i.e., it does not require periodic re-
calibration. It will maintain its accuracy for long periods of time and can be made traceable to national standards (NIST, NPL, etc.) (e.g., Edge Tech's hygrometer with two-year 1% stability guaranteed) .

(2) Very high accuracy, typically up to ± 0.2oC or better of dew or frost point (e.g., hygrometers in General Eastern, Edge Tech, and Yankee Environmental Systems).

(3) Excellent repeatability and NO hysteresis.

(4) Very broad range, down to frost points of -40 oC and up to dew points of 50 oC.

(5) Reasonable resistance to chemical and physical contaminants (depending on the mode of the hygrometer's operation).

Fig 2. Schematics of chilled mirror

The shortcomings of chilled mirrors have included, until recently, a sensitivity to contaminants that requires frequent maintenance and a slow response at very low frost points. Other drawbacks of the chilled mirror instrument are its expense relative to most other types and its higher maintenance demands for skilled personnel, to properly monitor, and maintain an installation (e.g., providing proper air sample flow). The largest sources of error in a condensation hygrometer are the difficulty of accurately measuring the condensation surface temperature (Wiederhold, 1997a and Wiederhold, 2000) and accurately detecting the formation of condensation (even with some contaminants).

Up to date technology makes the chilled mirror hygrometer less sensitive to contaminants by improving optical circuits and control modes of the chilled mirror. For example, the automatic balance control (ABC) developed by Edge Tech (formerly EG & G or more formerly Cambridge Systems), the Programmable Automatic Contaminant Error Reduction (PACER techniques) developed by General Eastern Instruments, and Cycling Chilled Mirror Dew Point Hygrometer (CCM) developed by Protimeter where the mirror is "dry" 95% of the time and therefore contaminates at a much slower rate are new technologies which reduce maintenance. Although these techniques greatly reduce the dew point temperature measurement errors caused by mirror contamination, the errors occurring at the mirror surface interface still contribute to the measurement errors, for example, Kelvin effect errors and Raoult effect errors (WMO, 1996; Wiederhold, 1997b). The greatest precision is obtained by controlling the mirror to a temperature (dew point) at which condensate neither accumulates nor dissipates, although, in practice, the above technologies will oscillate around this temperature. The response time of the mirror to heating and cooling is critical with respect to the amplitude of the oscillation, and should be of the order of one to two seconds. The air flow rate is also important for maintaining a stable deposit on the mirror. It is possible to determine the temperature at which condensation occurs with a precision of 0.05 K (WMO, 1996). On the other hand, the errors in temperature measurement in the hygrometer are unavoidable because of self heating, thermal conduction, and calibration limitations.

After more than a decade of experience with the chilled mirror in unattended humidity measurement, the National Weather Service ASOS program is considering the possibility of using another type of sensor. The technical maintenance of the chilled mirror sensor, although quite feasible in a research mode, has proven difficult over a widely dispersed network.

The capacitive polymer RH sensors are attractive for many applications due to their relatively low cost. State-of-the art techniques for producing capacitive sensors (Fig. 3) take advantage of many of the principles used in semiconductor manufacturing to yield sensors with minimal long-term drift and hysteresis. The polymer RH sensor acts as a capacitor dielectric with the interjected surface metal as electrodes and changes in dielectric constant as moisture is adsorbed or desorbed by the thin film. As the water molecule is highly polar, even small amounts of water can change the sensor capacitance to a measurable extent. In recent years, significant improvements have been made, and the current advantages of this type sensor are:

Fig 3. Samples of capacitive RH sensors

(1) Far less temperature dependency compared to electric sensors (e.g. resistive sensors). If necessary, the sensor can be provided with electronic temperature compensation circuitry.

(2) Fast response.

(3) Virtually no hysteresis compared to earlier RH sensors.

(4) Less frequent re-calibration or replacement.

(5) Wide range available from 0.05% to 100%.

(6) Very Good stability and Low cost, the accuracy can reach ±1% from the manufacturers (e.g., Vaisala capacitive RH sensors) with NIST traceable calibration.

The limitations of RH capacitive sensors include: sensitivity to certain contaminants; not useable in corrosive atmospheres; and slight temperature dependence. The last one is particularly important for long-term climate monitoring at wide ranges of both temperature and water vapor, especially in sub freezing conditions for higher humidity readings (close to 100%) (Clayton, et al, 1985; Anderson, 1994; Fleming, 1998; Hard, 1998; Dery and Stieglitz, 2001; Hubbard et al., 2001).

It should be noted that a simple statement of ±1% accuracy means little in terms of actual field performance because many variations are involved in the humidity measurements. For example, a sensor specified by the manufacturer to have an accuracy of ±1% may, after operating six months in the field, have an accuracy of ± 6% while another sensor, specified by the manufacturer at ±2%, could after 6 months in the same application have an accuracy ±3%. Therefore, field testing is critical.

4.	Project Description

In the past, a few investigators have examined air humidity measurements. More than ten years ago, a comprehensive comparison of humidity sensors for use in the AWS was made (WMO, 1989). This Intercomparison revealed that additional corrections were needed for measurements below 0 oC, even though some sensors incorporated temperature compensation circuitry and hysteresis problems occur when sensors are exposed to saturated conditions. Muller and Beekman (1987) also pointed out that commercial humidity sensors for AWS should be re-evaluated especially for the temperature conditions below 0 oC. Recently manufacturers claim improvements in temperature compensation, hysteresis, and long-term stability (e.g., Vaisala Company Notes and Tanner, 1990). The issues of temperature dependency and humidity dependency are still questionable (Anderson, 1994; Anderson, 1995; Fleming, 1998; Dery and Stieglitz, 2001) especially at temperatures below 0 oC. Both the chilled mirror hygrometer and the RH capacitive sensors require further investigation under conditions which combine high or low temperature and high or low humidity.

A few recent studies conducted on the RH capacitive sensors (polymer or polyimide types) revealed techniques for correcting the RH sensors. Anderson (1994, 1995) studied the mechanisms of RH sensors (why sensors exhibit hysteresis? and how do we introduce individual correction functions for each RH sensor?). He also provided a method for rescaling humidity sensors at temperatures well below freezing. Similarly, Fleming (1998), the SHEBA group at NCAR (Ed Anderas et al.), and Stephen Dery and Marc Stieglitz (2001) investigated possible correction methods and presented some useful notes on the RH sensors. Their studies are very valuable for this proposed investigation. However, their experiments focused on vintage RH sensors, and some of them are either discontinued or have been supplanted by a higher quality product. For example, the HMP 35A was tested in Anderson's work but this model sensor was discontinued by Vaisala; the HMM 30D in Fleming (1988) was an OEM product; SHEBA groups did focus on the Vaisala 50Y and Vaisala 235C for frost point testing plus saturation conditions below zero in the laboratory by using Thunder Scientific's humidity chamber; and the HMP 35C sensor was used in Stephen Dery and Marc Stieglitz's work. It seems that few studies have focused on the relatively new RH sensors (candidate RH sensors in this proposal). Therefore, it is essential that we make a comprehensive study under both laboratory and field conditions so that CRN RH sensor selection can be an informed decision.

Since the primary goal of the Climate Reference Network (CRN) is to provide for long-term homogenous observations of meteorological variables (Karl et al., 1995 and CRN website), the highest priority for selecting the humidity sensor or monitoring systems should focus on the sensor's temperature and humidity dependencies and long-term stability with sufficient accuracy in the field (not in the manufacturer's laboratories). Secondly, the compatibility in the future (future availability or upgrading continuity) is a factor that should be given consideration. Thirdly, good quality maintenance and regular calibrations should be matched with the employment of humidity sensors in the CRN.

4.1 Scope of Sensor Testing

Two sensor types, based on availability and quality considerations, should be include in the proposed test. These are the chilled mirror type hygrometer and the capacitive type RH sensor. The hygrometer measures dew point temperature directly and when used in conjunction with the dry bulb temperature can be used to derive both RH and wet bulb temperatures. The capacitive type sensor measures RH directly and when used in conjunction with dry bulb temperature can be used to derive both dew point and wet bulb temperatures. The candidate sensors or monitoring systems with the details of their specifications are listed in the next section. Therefore, our objectives are

(1) Acquire a suite of humidity sensors.

(2) Test sensors in laboratory for frost point. Verify sensor performance at frost point. Does the chilled mirror measure dew point or frost point temperature? How does the RH sensor respond when air temperature is below 0 oC?

(3) Test RH sensors in laboratory for performance in extreme conditions (limited ranges): (a) time constant under variable conditions, (b) temperature dependency, (c) humidity dependency, (d) pressure dependency, and (e) air sampling errors.

(4) Determine the functional precision of all candidate RH sensors immediately following the lab calibrations. In this case we will first operate two sensors of the same type in a single shield and compare the side-by-side performance of the two time series [T1(Sh1,t) and T2(Sh1,t)]. This will be followed by using two shields set-up side by side with one of the sensors in each shield [T1(Sh1,t) and T2(Sh2,t)]. The standard error of estimate, absolute mean difference, and other statistical indicators will be calculated to determine the functional precision.

(5) Air temperature comparison in fields including the existing ASOS-1088 temperature /dew point monitoring system, new non aspirated dew point system (upgrade of ASOS-
1088), and CRN air temperature/RH sensors. (a): quantify the magnitude of any systematic differences between ASOS-1088 and new version of ASOS including air temperature and air humidity . (b) quantify the differences between the CRN RH candidate sensors and new revised ASOS system.

(6) Side-by- side comparisons with a field standard water vapor monitoring system (see next section) to establish the field performance specifications for RH sensors in contrast to the manufacturer's specifications including temperature, humidity, pressure dependencies, and air sampling errors.

(7) Perform comparative analysis of the data to determine under what atmospheric conditions the sensors show greatest and least agreement. The analysis of field uncertainty will include the standard/expanded uncertainties, the worst-case RSS errors, offset/drift, and errors associated with the derived or 'non-measured' humidity variables in each case (NIST technical Notes 1297, 1994).

(8) Summarize the techniques of calibration and validation as well as maintenance. Establish the air humidity laboratory capable of serving the CRN.

(9) Document complete reports of all experimental data, analysis, and conclusion including the monthly report. The final reports and summaries as follows,

a) Monthly report

b) Air humidity sensor testing under sub freezing temperature conditions.

c) Air humidity sensor testing under high temperature range.

d) Air humidity sensor testing under high water vapor conditions

e) Air humidity sensor testing under low water vapor conditions

f) Pressure dependency of air humidity sensors.

g) Analytical derived air humidity variable errors between RH and dew point.

h) Summaries of performances of testing sensors and error sources as well as their contributions/corrections.

I) Standardize the reporting and delivering/interpreting air humidity variable records.

j) Field and laboratory humidity sensor calibration methods.

k) Report the results on the air temperature biases (ASOS-1088, new ASOS, CRN R/TH systems).

l) Common trouble-shooting and maintenance techniques.

m) Installation manuals for each RH sensor tested.

4.2 General Experimental Procedures

Procedure 1: Select and acquire sensors and monitoring systems including some equipment that we already have (see candidate sensors section below).

Procedure 2. Objectives 2 to 5 can be undertaken in parallel. We will undertake the first calibrations, function precision test, installation at the site, and pre-run in fields. As soon as the first month of data is obtained, the analysis should then be updated each month. After a period of four months, we expect to state whether the rankings are stable during winter time. However, there is some need to run the experiment during the warm season. This is because warm air holds more water vapor and many of the sensors have a temperature compensation as part of their design. It would be best to expose the sensors in both cold/hot and humid and dry conditions to see what the temperature, humidity, and pressure dependencies are over the range of conditions that the CRN may encounter.

Procedure 3: Prepare reports and summaries when due.

4.3 Candidate Humidity Sensors

After widely and carefully reviewing recent humidity sensors available off the shelf and based on our previous experience, we selected the fundamental sensor (chilled mirror) as a transfer standard for comparison of candidate sensors in the field. We list each sensor or monitoring system with their specifications as follows.

Comparative Standard (option 1): DewTrakTM Model 200M (Edge Tech) (expensive!!!)

Specifications:

Dew point accuracy: ± 0.25 oC

Sensing scheme discriminates between dew and contamination (less maintenance);

No drift and No hysteresis.

Self-diagnostics and continuous unattended operation.

No balancing or other adjustments required.

Second Comparative Standard: Met-2010 thermo-hygrometer (Yankee Environmental Systems)

Specifications

Range: At 22 oC, ambient temperature dew/frost measurements can be made to -18oC

Accuracy: ± 0.2 oC (dew point) and ±0.5 oC (frost point)

Sensitivity: ± 0.01 oC

Repeatability: ± 0.01 oC

Hysteresis: NO

Slew rate: Typically 1.5 oC per second.

Candidate RH Sensor I: HMP230 series RH sensors (Vaisala)

Specifications

Range: 0 to 100%

Accuracy: ± 1% RH (0 to 90% RH) and ± 2% RH (90 to 100% RH)

Response time (90%) in still air: 15 seconds

Typical long term stability: better than 1% RH per year.

(Notes: When combined with its temperature sensor the dew point temperature, absolute humidity, wet bulb temperature can be calculated by the microprocessor. The accuracy should depend on the accuracy of dry bulb temperature and RH as well as the pressure)

Candidate RH Sensor II: HMP45 Series (Vaisala)

Specifications

Range: 0 to 100%

Accuracy: ± 2% RH (0 to 90% RH) and ± 3% RH (90 to 100% RH) at 20 oC

Response time (90%) in still air: 15 seconds

Typical long term stability: better than 1% RH per year

(Note : we have many one-year old or two year old HMP45C in the on-going test).

Candidate RH Sensor III : Model MP100/101(Rotronic Instrument Cop. USA)

Specifications

Range: 0 to 100%

Accuracy: ± 1% RH at 20 oC (factory)

Response time (90%) in still air: 10 seconds without filter

Repeatability: ± 0.03 % RH

Typical long term stability: better than 1% RH per year

Note that a few manufacturers in the U.S. sell the RH sensors with different models but their RH sensors actually are Vaisala's capacitive sensing elements and circuitry (e.g., Met-One Instruments, NovaLynx Corp). Thus, we did not consider their products as possible RH sensor candidates.

We believe that accuracies claimed to be better than ± 2% (RH) and ± 0.2oC (dew point ) will be extremely difficult to achieve in the field because conditions can not be controlled like in the laboratory. Therefore, the comparison side-by-side is needed to understand performance issues for the CRN.

4.4 Calibrations and Maintenance (Tech Support)

Although the chilled mirror technology has significantly improved by using the ABC, PACER, and CCM as well as the self-diagnostic systems, the calibration of chilled mirror hygrometer is very important to guarantee quality data. The calibration for either chilled mirror hygrometer or the RH sensors should be conducted at regular periods. Both field calibration and laboratory calibration are critical (Pike, 1985; Huang, 1990; Huang, 1997; Wiederhold, 1997b; Hardy, 1998a and 1998b; Huang, 1998; and Tennermann, 1999) .

Field calibrations (one month period) : Highly accurate portable hygrometer [e.g. Model 650 Handheld Hygrometer (NIST Certification) or Model 1500 (NIST traceable, Edgetech)].

Laboratory calibrations (one year period): Controlled Chamber/Humidity Calibrators in the laboratory. Currently the two-pressure and two-temperature generators are more accurate in the calibration applications.{e.g., Model 2500 automated humidity generator, Thunder Scientific. Corp, USA)

Regular preventive maintenance should be scheduled (regular visual inspection), on-line maintenance (test runs, verify fixed readings), and troubleshooting (frequent technical or electronics issues).

4.5 Experimental Site Selections and Data Acquisition Systems

We propose to establish two sites where sensors are to be tested. The basic criteria for selecting experimental sites are associated with our proposed objectives, in which the temperature extremes, humidity extremes, and possibly air pressure differences are three important factors. Lincoln, NE is suggested as a continental site to anchor the study because of its proximity to the researchers and more importantly it represents both hot humid and cold dry conditions during the course of the year. Table 3 shows that the RH is above 90% for 11.7% of all hours while it is below 50% for 19.7% of all hours. The dew points in winter are as low as 13.8 F on average for January with a s.d. of 13.8. Assuming that 95% of the values will lie within 2 s.d. we expect to encounter dew point values over the range -13.8F to 41.4 when the concurrent air temperatures are cold. In July the mean dew point is 64 F with a s.d. of 5.9, therefore we expect to encounter values over the range from 52.2 to 75.8 F when the air temperatures are warm. This takes us well into the frost point range and into the higher dew point range.

A Louisiana site (see Baton Rouge, LA) is the second proposed site and it represents a coastal environment and perhaps higher concentrations of chemical pollutants. This second factor will be kept in mind as we watch for effects of contamination on the measurements (e.g., how contaminants will affect both gortex sleeve and polymer capacitive element). The air in Baton Rouge represents more humid conditions. The RH is above 90 % for 22 % of the time. The dew point range expected, with the same assumptions as above, is 12.3 F on the lower end to 81.5 F on the upper end. Fargo, ND and Concord, NH are presented for comparison. Fargo offers about the same RH distribution as Lincoln but has an extended range of dew points (-34.9 F). On average Baton Rouge has 83 days that reach or top 90 F while Fargo has only 15 and Lincoln lies in between at 44.

In summary, the Lincoln test site offers a wide range of conditions in which to test the sensors. The Baton Rouge site would extend the testing to higher dew points or higher humidity. The elevations of Lincoln site (1194 ft) and Baton Rouge site (64 ft) are quite different so that it will reveal site to site differences of surface air pressure. The cost of including two sites is a factor of 2 larger than a single site study with the exception of laboratory equipment (which will also serve as spares after initial laboratory testing), plus any indirect costs at the cooperating states.

In each experimental site, we propose to monitor the following atmospheric variables,

1. All air humidity variables (dew point or RH) for the transfer standards and candidate sensors;

2. Temperature monitoring systems including: a) highly accurate air temperature (PMT-2005, Yankee Environmental Systems) (triable aspirated shields with auto-
inner shield temperature balance controller); b) ASOS-1088 air temperature and dew point temperature system; c) new non aspirated ASOS air T/Dew Point system; and d) CRN air temperature or/and RH system; and e) CRN infrared thermometer for surface temperature. (NCDC will provide the CRN air temperature and CRN's IRT as well as corresponding shields).

3. Surface air pressure;

4. Ambient wind speed and direction;

5. Solar radiation.

A precision meteorological thermometer (Model PMT-2005) is selected for monitoring air temperature as an air temperature reference at the site. Although the chilled mirror hygrometer and RH sensors usually take air temperature measurements, the temperature from the PMT-2005 will provide a means of testing the effect of using the manufacturer supplied temperature sensor in making any transformations: 1) conversion between the RH and dew point as a reference; 2) discontinuous biases in the upgrade of ASOS system; 3) air temperature biases in the new ASOS and CRN system.

A barometer (Vaisala PTB101B) will monitor the site air pressure for the purpose of investigating pressure dependency of RH sensors. According to the WMO recommendations for the AWS applications, it is common practice to house the barometer within a sealed and thermal-
stabilized small box inside the CPS enclosure so that we select the Vaisala SPH10 or 20 static pressure heads for reliable barometric pressure measurements in all weather (Vaisala News, 2000). This is because most dynamic pressure sources including wind induced error, thermal effect, and possible mechanical shocks or vibrations could be removed by using this static pressure head (see below figure).

In order to complete investigations of air sampling errors in water vapor monitoring systems, it is necessary for us to take ambient wind speed and wind direction measurements (using Met-One Model 014A/024A). It should be noted that air sampling errors here do not refer to the sampling frequency errors (frequency responses based on Shannon's sampling theorem). The categories of errors discussed here result in limitations to the accuracy of measurement with respect to the RH or dew point of the sample actually passing over the sensor element. The air sampling errors are more serious for chilled mirror sensor (e.g., ventilation rates, sample line leaks; absorption and adsorption at sample passing surfaces; diffusion through sampling materials; and condensation in the sampling systems). However, the air sampling error could be addressed in the RH sensor (e.g, difference between non aspirated and aspirated shields, optimal ventilation rate, condensation or absorption of shield's materials/surfaces). An LI-200S (LI-COR, Inc. USA) pyranometer will be used for taking solar radiation measurements at each site.

All sensors will be installed at heights consistent with WMO requirements for AWS system. All output signals will be measured by a CR10X data logger (Campbell Scientific, Inc. USA). We will develop necessary signal conditioning circuitry or interfaces between the data logger and sensor systems. The sampling rate and all average outputs are summarized in Table 4.

The data will be retrieved every four hours and graphically displayed on central server (located at the HPRCC, Lincoln, NE) by using land-based telephone lines (LTL) as the telecommunication link.

4.6 Project Schedule

We propose the following schedule of work:

Nov - Dec. 2001: Purchase and install surface water vapor monitoring systems in experiment site(s).

Dec. 2001: Start monitoring of observations. At the same time we begin to test the sensors or monitoring systems in our laboratory

Mar. 2002: Report the winter season performance analysis.

Aug. 2002: Report the summer season performance analysis.

Nov. 2001 - Oct. 2002: Prepare monthly reports and update our data analysis each month. Adjust analysis methodologies as needed.

Dec. 2002: Finalize all proposed reports and summaries to NCDC [see section 4.1 (7)].

5.	References

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ASHRAE, 1993: Handbook-Fundamentals, American Society of Heating, Refrigeraion and Air Conditioning Engineering.

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6.	Appendix

6.1 Algorithms of Water Vapor Pressure

1. WMO Calculation (1996)

2. Industrial Applications (Wiederhold, 1997)

3. Buck's Equations (Buck, 1981)

---modifications of formula from Magnus (1844), Tetens (1930), Murray (1967). Also it was applied in the conversion between the RH and dewpoint in the LI-610 Dew Point Generator (LI-COR, Inc)

6.2 Lists of Manufacturers (Good Quality on air humidity)

(1)	MBW Calibration Ltd.

Seminarstrasse 57

CH-5430 Wettingen

Switzerland

(2)	Michell Instruments
Michell Instruments Ltd.,

Nuffield Close

Cambridge CB4 1SS

UK

(3)	General Eastern Instruments

20 Commerce Way

Woburn, MA 01801

USA

http://www.geinet.com

(4)	Edge Tech (former EG&G)

455 Fortune Boulevard

Milford, MA 01757

USA

http://www.edgetech.com

(5)	Vaisala Company

PL 26

FI-00421 Helsinki

Finland

http://www.vaisala.com

(6)	Yankee Environmental Systems, Inc.

Airport Industrial Park

101 Industrial Blvd

Turners Falls, MA 01376

USA

http://www.yesinc.com

(7)	Rotronic Instrument Corp

160 East Main Street

Huntington, NY 1174

USA.

http://www.rotronic-usa.com

(8)	Met-One Instruments Inc.

1600 Washington Blvd

Grants Pass, Oregon 97526

USA

http://www.opendoor.com/metone/

(9)	Thunder Scientific

623 Wyoming S.E.

Albuquerque, New Mexico 87123-3198

USA

http://www.thunderscientific.com

(10)	NOVA LYNX Corp

P. O. Box 240

Crass Valley, CA

USA

http://www.novalynx.com

Notes: 1. Manufacturers (1) and (2) have the world rank hygrometers (chilled mirror) which are very, very expensive ones, the NIST has their products.

2. Manufacturers (9) and (10) also provide the RH sensors but they are of Vaisala's sensors or sensing element (capacitive element). Thus, we did not select them as candidate sensors.

6.3 Conversion errors/differences between WMO and NIST