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+ 2014 Oman Rainfall Enhancement Trial: 1 June to 19 October Dr. Stephen Beare Prof. Ray Chambers Mr. Scott Peak Dr. Mohammed Al-Kabani.

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Presentation on theme: "+ 2014 Oman Rainfall Enhancement Trial: 1 June to 19 October Dr. Stephen Beare Prof. Ray Chambers Mr. Scott Peak Dr. Mohammed Al-Kabani."— Presentation transcript:

1 + 2014 Oman Rainfall Enhancement Trial: 1 June to 19 October Dr. Stephen Beare Prof. Ray Chambers Mr. Scott Peak Dr. Mohammed Al-Kabani

2 + Overview While the enhancement effect of electrical charge on the coalescence of cloud droplets and precipitation has been demonstrated in laboratory experiments it has not been studied in the natural environment. Given the complexity of atmospheric chemistry such studies would be extremely difficult to conduct. Hence, ART now in partnership with TIE, has explored the potential to increase natural rainfall using ground-based ionisation through increasingly sophisticated field trials and statistical methods of analysis. The 2014 Oman trial is the most extensive and well instrumented trial to date.

3 + Outline of the Presentation Scope and instrumentation of the trial Meteorological conditions Trial Design Designating the control and target areas Statistical methods Results Volumetric attribution and valuation

4 + Trial Final Report

5 + Scope of the 2014 Trial The trial area was expanded with the addition of two additional Atlant systems, one in the northwest and one in the southeast. 30 additional rainfall gauges were added and 12 gauges repositioned to create a wide and evenly distribution network of 149 rainfall gauges. Vertical sonic wind profilers were installed at the two initial Atlant sites to gain a better understanding of the how the topography of the Hajar Mountains affects uplift and other atmospheric conditions. As in 2013, data from TIE instruments were supplemented by DGMAN AWS data Trial Instrument Array - 2013 gauges (blue) New 2014 gauges (red), Atlants (yellow)

6 + Scope of the 2014 Trial Trial Instrument Array - 2013 gauges (blue), New 2014 gauges (red), Atlants (yellow)

7 + Trial Instrumentation Instrument array. (Rain gauges – small triangles. Surface weather stations- medium triangles. ATLANT™s / TIE Weather stations large triangles. Elevation is colour scale in metres.

8 + Trial Rainfall Period Rainfall Days Gauges Recording (%) Mean Gauge Rainfall (mm) June194.53.50 July227.64.82 August3013.05.23 September276.92.65 October1612.14.13 Total1148.74.30 Summary of daily rainfall statistics from the TIE gauge network for days when at least one gauge in the trial area recorded a rain event (Rainfall Days): 1 June to 18 October 2014

9 + Rainfall Distribution Overall the distribution of rainfall is relatively even through most the trial area. The exception is in the northeast where there were a a number of large rainfall events that occurred on isolated days. Bubble plot of the locations of the TIE rain gauges, with gauge rainfall frequency proportional to bubble size and gauge total rainfall denoted by the colour scale

10 + Correlations Between Gauges It is clear that even at a close distance the correlation is low. The correlation becomes insignificant at distances greater than 25km. This indicates that rainfall tends to be geographically isolated and that observations of positive rainfall are spatially uncorrelated given the spacing between most of the rainfall gauges. The correlation between positive rainfall observations as a function of the distance between rainfall gauges. Day to day correlations between gauge observations were also low.

11 + Wind Direction Profile at H1, H2, Muscat The prevailing winds are from the northwest to the east, with the majority from the north to the northeast. The orographic effects of the Hajar ranges are clear at H1 and H2 as well as at the lower elevation wind directions above Muscat (700hPa to 850hPa). The distribution of daily upper level wind directions at Muscat airport, H1 and H2: speed weighted averages. When compared to the upper elevation wind directions at Muscat (500hPa to 700hPa), winds at H1 have clocked to the east, while winds at H2 and at lower elevations above Muscat have clocked to the west. Each colour sums to one around the eight points of the compass rose.

12 + Wind Speed Profile at H1, H2, Muscat Wind speeds are similar in all directions as are speeds at H2 and at lower elevations above Muscat airport. Wind speeds are slightly higher at H1 due to the higher elevation of the site. Daily average wind speeds in metres per second at Muscat airport, H1 and H2. Wind speeds are slightly higher at H1 due to the higher elevation of the site. Most notably there is a sharp increase in wind speeds at the upper elevations above Muscat airport, as would be expected for winds above the boundary layer and in the free atmosphere.

13 + Target / Control Downwind Footprints Dynamic 60° downwind wedge footprint model (top) and 30km dynamic downwind corridor footprint model (bottom)

14 + The Downwind Direction Air flows that are moderated by the features of the surface of the earth form the atmospheric boundary layer. Wind flows are turbulent with local wind direction and speed determined, in large part, by the topography of the Hajar Mountains. Airflows above the boundary layer are generally non-turbulent and consistent over a region the size of the trial area. The cloud layer tends to form just above the boundary layer in the free atmosphere. How these different wind flows affect an ion plume and therefore the location of the footprint depends on: The height of the boundary layer and the vertical wind speed above the Atlant site, and The horizontal wind speed and direction above the Atlant site.

15 + Height of the Boundary Layer The height of the boundary layer in the afternoon can be measured by the height at which radio waves are no longer reflected back to the SODAR. This varies from day to day but the average height of the boundary layer above: H1 is 340 metres, and H2 is 510 metres. Carried by the average afternoon vertical wind speeds an ion plume would reach the top of the boundary layer in: Less than 5 minutes at H1, and About 20 minutes at H2.

16 + Vertical Wind Speeds at H1 and H2 (m/sec) H1 H2H2

17 + The Downwind Footprint Is clearly dominated by the upper level wind directions in the free atmosphere. These are measured on a daily basis at Muscat. In the average time it would take an ion plume to reach the free atmosphere, given the average horizontal wind speeds above the site, the plume would drift laterally by: 1.2 km at H1,and 4.8 km at H2. Hence the plume could be expected to stay within a 30 km corridor model. The wedge model may tend to exclude gauges that in the path of the plume close to the site.

18 + Muscat Wind Measurements Winds measured at 500hPa to 700hPa are in the free atmosphere and these shift with the movements of high and low pressure systems that dominate the region. The daily shift in wind directions, divided by two, give an idea of how the winds might shift between morning and afternoon. Distribution of 4am to 4pm changes in 500hPa to 700hPa wind directions above Muscat airport. The majority of the changes are small with 60 per cent less than 15 degrees and less than 10 per cent of the changes more than 45 degrees The corridor model is likely to be less sensitive to these changes than a wedge model Nevertheless, afternoon radiosonde observations would be useful in the future.

19 + Trial Design The trial was conducted using a randomised cross-over design with: The schedule set prior to the start of the trial, Four-week- blocks to balance against seasonal weather trends during the trial, and Rules to govern changes in the schedule in the event of operational faults or severe storm warnings. The four sites were operated in a pairwise on/off sequence to give maximum separation between active and control areas, with: H1 paired with H3, and H2 paired with H4.

20 + Goals of the Statistical Modelling The first is to control for the natural variability in rainfall over what can be achieved through the experimental design: To achieve a higher signal to noise ratio. The second is make two counterfactual predictions from which the level of rainfall enhancement can be estimated: The amount of natural rainfall that would have been measured by a target gauge if the corresponding Atlant site had not been operational, and The amount of additional rainfall that would have been measured by a control gauge if the corresponding Atlant site had been operational.

21 + Additional Control is the Key A higher level of control means that the experimental conditions each day of the trial are effectively more similar, giving greater confidence that what is observed is not due to chance. A higher level of control means that experimental conditions between trials are more similar giving greater assurance that similar results will be obtained under different climatic conditions or at different locations.

22 + Objectives of Statistical Methodology Maximise the efficiency of the experimental design to minimise the error associated with model predictions based on gauge level data. Eliminate or reduce as many sources of model bias as possible, most notably omitted variable bias. Obtain accurate confidence intervals about the estimated enhancement effects using resampling to correct for spatiotemporal correlation in the model errors.

23 + Omitted Variable Bias Omitted variable bias is always a concern when modelling processes in a natural environment. An example of omitted variable bias: Rainfall increases with elevation, The elevation of gauge is omitted from the model but distance from an active Atlant site is included, Gauges at higher elevation are closer to the Atlant site This would give a false or overstated indication that rainfall increased closer to the active Atlant site. The obvious solution is to include gauge elevation in the model. However, if the gauge elevations were unknown the bias could be eliminated or at least reduced by sweeping out the average differences in rainfall at each gauge using a random gauge effect. This would also reduce the risk of an unmeasured effect such as the topography surrounding different gauges. Including a random day effect in the model corresponds to sweeping out day to day differences in average rainfall. This eliminates/reduces the bias of unmeasured meteorological conditions that are correlated with rainfall.

24 + H1,H2 2013 and 2014 Corridor Model The model uses the same target and target by elevation interaction, as well as upwind rain predictions and random effects specification, as the 2013 model (observations on humidity and radiation were not available in 2014 due to failure of the data logger and were excluded). Effects at both H1 and H2 are positive, with the H1 effect significantly so. R-Square = 0.264 Observations = 946 Fixed Effect EstimateStd. Errort-ratioSig. Level Intercept 0.36790.14642.510.012 Gauge Elevation 0.00000.00010.280.778 Instrumental Rain 0.70250.11016.380.000 H1 Target 0.56210.23202.420.016 H2 Target 0.32800.21921.50.135 Elevation by H1 Target -0.00050.0002-1.970.050 Elevation by H2 Target -0.00040.0002-1.730.083 Random Effect RatioComponentStd. ErrorVariation % Trial Day 0.18120.32630.081315.3 Residual 1.80040.090884.4

25 + Complete 2014 Corridor Model Highly significant effect at H3 Significant effects at H1 and H2 No significant effect at H4 R-Square = 227 Observations = 807 Fixed Effect EstimateStd. Errort-ratioSig. Level Intercept 0.76380.16104.740.000 Gauge Elevation -0.00070.0002-4.350.000 Instrumental Rain 0.86800.11087.830.000 H1 SODAR Zone -0.09920.0452-2.200.032 H2 SODAR Meridian 0.11750.05382.180.034 H1 Target 0.30460.16691.830.068 H2 Target 0.30490.14592.090.037 H3 Target 0.55170.17513.150.002 H4 Target -0.17310.1768-0.980.328 Random Effect RatioComponentStd. ErrorVariation % Trial Day 0.07410.13770.06266.90 Residual 1.85950.098893.10

26 + Possible Influences on the Complete 2014 Trial Analysis There were two imbalances in 2014 trial data that are likely to be due to the natural variability in rainfall over the trial period. First, a few isolated and very heavy rainfall events in the northwest may have contributed to the highly significant estimate at H3. Second, the greater proportion of control gauges recording rainfall events in the southeast may have made the identification of enhancement signal at H4 more difficult. The significant result at H1 and insignificant result at H2 in 2013 was resolved with the additional data from the 2014 trial. Additional data will be available at H3 and H4 in 2015.

27 + Corridor Model Attributions Model10th50th90thMean 2014: H1 & H2 only 12.821.2221.221.7** 2013/14: H1 & H2 only 11.318.126.318.5** 2014: H1, H1, H3 & H4 23.232.742.932.9** ** Significant at the 99 per cent confidence level

28 + Comment on the Atlant Attributions The attributions based on the analysis at H1 and H2 in 2013 and 2014 are consistent, with the mean level estimates in one year falling well within the confidence bounds of the other. The mean level 18.5 per cent attribution for the combined 2013/2014 analysis at H1 and H2, is the most reliable estimate of the Atlant enhancement effect to date, because of: The larger sample, and The potential greater exposure to different meteorological conditions. The attribution for the full 2014 trial is heavily influenced by the local attribution around H3. Small areas are more likely to be affected by random rainfall events. The mean level estimate is well outside the confidence bounds of the estimates from the other models. The attribution based on this model should be discounted until more data are available.

29 + A Volumetric Attribution and Valuation of the 2014 Atlant Trial

30 + Outline of the Methodology Calculation of the gauge areas Voronoi polygons Estimation of downwind gauge level enhancement effects The direct and counterfactual estimates Calculation volumetric level and value of enhancement Rainfall Useful run-off Value per megalitre

31 + Voronoi Gauge Areas A Voronoi polygon is a two dimensional representation of an area surrounding a reference point, which in this case is a gauge location The reference gauge is the nearest rainfall gauge to any point that is within the interior of the Voronoi polygon. The vertices of the polygons a equidistant from two or more gauges Example Voronoi diagram. Red dots would represent rainfall gauges.

32 + Voronoi Gauge Areas Polygons extending past the boundary of the trial area are trimmed back to the boundary A rainfall observation at the reference gauge is assumed to represent the average for the entire Voronoi area 2014 Trial area Voronoi gauge areas. 2014 Trial Gauges (red dots), ATLANT™ Sites (yellow triangles).

33 + Gauge Level Enhancement The attribution was calculated for gauges downwind of either H1 or H2 at any time during the 2014 trial The statistical model based on the 2013/2014 dataset was used to estimate the additional rainfall: That occurred in a target area (direct effect) That would have occurred if an Atlant system was operational in a control area (counter-factual effect) The total enhancement effect is the sum of the sum of the direct and counter-factual effects It is the expected volume of additional rainfall that would have occurred if H1 and H2 had both been fully operational over the trial period. The percentage enhancement effect is volumetric enhancement effect divided by the model estimate of total natural rainfall.

34 + Volumetric Attributions An average of one millimetre of rain falling on one square kilometre equates to one megalitre of water The total gross volumetric enhancement effect in megalitres is the sum of the gauge effect in millimetres multiplied by the Voronoi gauge area in square kilometres The net effect is determined by percentage of rainfall that becomes effective run-off

35 + Yield Assumption The hydrology of Hajar Mountains and the wadi system is complex and it is difficult to determine the useful yield from precipitation which includes: Groundwater infiltration through ephemeral water beds, and Recharge of the coastal plain aquifers. Recharge rates are estimated by the Ministry of Water to be 18 per cent (2013) We will only consider the costal plain recharge which has a number of uses/benefits: Urban and industrial use, Agricultural use, and Protecting aquifers from sea water intrusion.`

36 + Valuation The balance between fresh water demand and the recharge of the coastal plains aquifer system is met through desalinisation. An additional volume of recharge is an offset against the an equivalent volume of desalinised water used to: Meet current demand, or Restore a deficit in groundwater reserves. The estimated cost of desalinisation using the least-cost method of reverse osmosis is about $US 800 per megalitre (UN, 2009). Pumping costs from the aquifer system are about $US 50 megalitre (UN, 2009) This gives an estimate of the opportunity value of enhanced rainfall that enters into a fresh costal aquifer of $US 750 per megalitre.

37 + Summary The calculated gross volumetric attribution for the H1 and H2 Atlant sites operating full time over the trial period was: 53,940 megalitres in 2013 56,520 megalitres in 2014. With an effective run-off of 18 per cent, the average volume of water entering the coastal aquifer system would be about 9,900 megalitres over the four-month trial period. Given an opportunity value of $US750 per megaglitre total value of the additional recharge would be, rounding down, $US7.4 million per (R.O 2.8 million) annum, with: H1 and H2 operating continuously from the 1 st of June to mid October.

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