Intercomparision of snowfall measured by weighing and tipping bucket precipitation gauges at Jumla Airport, Nepal

Transcription

1 Intercomparision of snowfall measured by weighing and tipping bucket precipitation gauges at Jumla Airport, Nepal Department of Hydrology and Meteorology, Nepal Ministry of Environment, Science and Technology Ramchandra Karki DHM, Data Management Section Jumla airport Meteorological station WMO TECO Oct - Brussels, Belgium

2 Intercomparision site Jumla airport in western Nepal (75m asl) Month Jan Feb March April May June July Aug Sept Oct Nov Dec Annual Maximum air Temp ( o C) Minimum air Temp ( o C) Study period Jan, Feb and March Precipitati on (mm) Objectives of study Climatological Normals (97-) Precipitation in the form of snow during Nov Dec, Jan, Feb and up to the middle of March. Tipping bucket precipitation gauges without heating and wind shield are in use in many stations Recently ott pluvio weighing gauge with tretyakov wind shield is installed in few stations Main objective is to find diff in snow water equivalent measured between ott pluvio and tipping bucket gauge Wind induced undercatch and effect of temperature tried to be incorporated Errors in snow water equivalent measurements in catching gauge (WMO CIMO Guide) Wind induced under catch Evaporation and wetting losses Snow capping in the rim Overflow in heavy precipitation Drifting and Blowing snow

3 Meteorological Instruments used Climatronics ultrasonic wind sensor model no WE- at m above surface. Air temp at m combined temperature-humidity sensor model no 89 lambrecht SYNOP data from nearby synoptic station used to verify precipitation as snowfall events a. Ott Pluvio (cm, 5mm capacity) weighing gauge, without rim heating and antifreeze liquid Precision for both gauge.mm b. Lambrecht Tipping (cm) bucket gauge. Without heating model 589 Only Ott Pluvio with tretyakov wind shield Installed.m above surface (Christian Félix, original design)

4 Snowfall Some Examples Peak wind Precipitation (mm) Solar heating 8 Wind Speed (m/s), Temperature (oc) Jan Date -Jan Weighing Tipping Temperature Wind speed Total Precipitation from Ott Pluvio weighing gauge (OPW)=.mm Total Precipitation from Lambrecht tipping bucket (LTB) during actual precipitation hours = mm LTB recorded = 8.mm on days following the actual precipitation (Solar heating with temp above zero favors the melting and record) Total precipitation in two days from LTB =.9 mm which is % less than in OPW

5 Snowfall Precipitation (mm).5.5 Trend of solar heating Solar heating - Temperature (oc) Night time Date 9-Jan -Jan -Jan Weighing Tipping Temperature The three day total precipitation (Jan 9 - ) OPW =.9mm, LTB = 8.8mm difference of.mm (%) Jan 9, OPW = 8.mm, LTB = 5.mm, Jan, LTB=.mm even in temp implying effect of solar heating Next event OPW =.mm, LTB =.5mm following day after solar heating

6 Snowfall 5 Precipitation (mm) - Wind Speed (m/s), Temperature (oc) Evening to night snowfall Date Jan -Jan Weighing Tipping Temperature Wind speed Jan 9, OPW =.8mm, Jan OPW =.mm,ltb =.7mm, Days Total OPW = 5.9mm and LTB =.7mm Diff= 5.mm (%) Temp sub zero during most of the precipitation events and wind speed to m/s

7 Snowfall 5 5 Precipitation (mm) 9 Rising temperature (solar heating) and peak pptn record Peak wind 5-5 Wind Speed (m/s), Temperature (oc) Feb 8-Feb 9-Feb Date Weighing Tipping Temperature Wind speed days total precipitation, OPW = 9.5mm, with most of the precipitation (8.mm) on 7 Feb (8) - 8 Feb () LTB during those hours recorded only.mm Days Total in LTB = 5.mm highestamount.8mm on hour 5, total diff = % major snowfall during day time, temperature and solar heating favorable for less deposition and less delay in record

8 Snowfall 5 Precipitation (mm) 5 Day time snowfall Temperature near to zero only during snowfall Temp decreasing trend and did not melt all 9 - Wind Speed (m/s), Temperature (oc) Mar Date -Mar Weighing Tipping Temperature Wind speed total precipitation, OPW =.mm, -7 hour of March, days total precipitation in LTB=.mm no diff between system. 7mm of precipitation on following day in LTB

9 Discussions and Conclusions Overall during Jan to March, the LTB recorded (mm) 5% less precipitation than OPW (.mm). The difference varies from individual events with maximum - % and minimum no differences between the LTB and OPW. Ten very light precipitation events (total precipitation in each event.mm) with total amount of.mm over the entire period were recorded only by weighing gauge. The higher undercatch of LTB (cases and ) with respect to OPW during snowfall events at air temperatures well below freezing.(deposition in upper funnel resulting losses with overflow, evaporation, wetting loss and blowing of collected snow) Wind induced undercatch are different in two systems and difficult to distinguish wind errors only (OPW wind shield and LTB without) its cumulative errors of wind deformation, evaporation loss, wetting loss and overflow etc

10 The OPW records precipitation as soon as it enters the weighing container where as in non heating LTB the deposition in upper funnel leads to delay in precipitation record. The delay in record in LTB is more if the temperature is well below freezing. But the record is not determined solely by temperature sometimes, it can also occur at sub-zero temperatures (e.g. case ). solar heating is the main factor to trigger melting and record under some conditions a portion of snow is melted into the tipping bucket during the snowfall event while some remains in the funnel and is only melted into the measurement bucket later (cases, and 5). The delay in LTB (inaccurate timing of precipitation events) is problematic for weather forecasting and warnings, diurnal variability studies and many research applications. The study shows the difficulties of the unheated LTB in accurately and timely measuring snowfall but this is only a comparison so the accuracy of two gauges cannot be stated. many stations in Nepal are above this altitude. Therefore, in the places where temperature is very low the undercatch of the unheated LTB compared to the OPW can be expected to be greater than %. Detail study is needed to make the data set homogeneous with old system and actural water resources assessment

11 Thank You Questions?