the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Jul 2024
Simple physics-based adjustments reconcile the results of Eulerian and Lagrangian techniques for moisture tracking
Abstract. The increase in the number and quality of numerical moisture tracking tools has greatly improved our understanding of the hydrological cycle in recent years. However, the lack of observations has prevented a direct validation of these tools, and it is common to find large discrepancies among the results produced by them, especially between Eulerian and Lagrangian methodologies. Here, we evaluate two diagnostic tools for moisture tracking, WaterSip and UTrack, using simulations from the Lagrangian model FLEXPART. We assess their performance against the Weather Research and Forecasting (WRF) model with Eulerian Water Vapor Tracers (WRF-WVTs). Assuming WRF-WVTs results as a proxy for reality, we explore the discrepancies between the Eulerian and Lagrangian approaches for five precipitation events associated with atmospheric rivers and propose some physics-based adjustments to the Lagrangian tools. Our findings reveal that UTrack, constrained by evaporation and precipitable water data, has a slightly better agreement with WRF-WVTs than WaterSip, constrained by specific humidity data. As in previous studies, we find a negative bias in the contribution of remote sources, such as tropical ones, and an overestimation of local contributions. Quantitatively, the root-mean-square-error (RMSE) for contributions from selected source regions is 5.55 for WaterSip and 4.64 for UTrack, highlighting UTrack's narrowly superior performance. Implementing our simple and logical corrections leads to a significant improvement in both methodologies, effectively reducing the RMSE by over 50 % and bridging the gap between Eulerian and Lagrangian outcomes. Our results suggest that the major discrepancies between the different methodologies were not rooted in their inherently different nature, but in the obviation of basic physical considerations that may be easily straightened out.
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RC1: 'Comment on esd-2024-18', Anonymous Referee #1, 15 Jul 2024
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General comments
This study investigates the uncertainty in precipitation source regions estimated by three different modeling approaches. Precipitation sources estimated by the online Eulerian-based WRF-WVT method are taken as the reference, against which estimates from two offline Lagrangian-based methods are compared: the WaterSip and UTrack methods. Both methods are found to exhibit biases in the estimated precipitation sources compared to the reference data set, in particular showing sources to be geographically closer to the precipitation than the more remote sources estimated by the reference. The study then tests a structural modification to each of the WaterSip and UTrack methods and finds bias is reduced and precipitation sources are made geographically closer to those of the WRF-WVT reference. A key conclusion of the study is that the Lagrangian methods can serve as viable alternatives to the more computationally-expensive WRF-WVT method. The study is well-defined, well-written and the conclusions logically follow the results. In particular, the authors are to be commended for detailing the structural differences between the models. The main area of improvement needed is the clarification of the proposed modifications to the Lagrangian models, and their resulting evaluation against the reference dataset.
Specifically, the modification of the UTrack model appears to contain two changes: (1) only parcels released from above 2km may be used for tracking, and (2) of those parcels, only those with relative humidity above 90% are subsequently tracked. It is unclear which modification dominates the reported changes to precipitation sources relative to the WRF-WVT sources. Of more minor importance, it is unclear why a higher relative humidity threshold is applied to the UTrack model compared to the WaterSip model; this choice of model modification needs to be clarified.
The modification of the WaterSip model, requiring parcels to have a minimum relative humidity of 80% immediately before a decrease in specific humidity, needs to be explained more clearly. It needs to be made clearer what the exact problem is with the way WaterSip reduces parcel specific humidity en route, and how applying an 80% threshold of relative humidity helps.
Specific comments
L47: Which problem is being referred to here?
L55/60: Here it is asserted that Eulerian approaches are more accurate than Lagrangian approaches. I do not think it is true that, in general, Eulerian tracing approaches are considered to be more reliable than Lagrangian approaches in accurately estimating precipitation sources. Perhaps you mean online Eulerian water vapor tracers are considered more accurate? If this is the case, I suggest rephrasing to clarify. Furthermore, if Lagrangian approaches are asserted to contain “more uncertainty”, than these uncertainties need to be outlined. Relatedly, I think it is important to be careful about asserting that WRF-WVTs can be “considered as synthetic observations”. There needs to be some evidence that WRF-WVTs can in fact accurately represent real observations, for example through comparison with satellite observations of atmospheric moisture. If this or a similar type of evaluation has been done, please refer to it here. Otherwise, I would tone down the language by changing the words “considered as synthetic observations” in L63 (also in L436) to “used as a reference”.
L145: Is the specific humidity assimilated from ERA5 like the evaporation field? Does the WRF model close the water balance if ERA5 evaporation is assimilated?
L155: While the manuscript makes it clear that parcel trajectories are calculated using WRF data in the first case, and ERA5 data in the second case, it is a little unclear which dataset was used to calculate the moisture contribution for each Lagrangian model. From reading section 2.3, I interpret that in the first case, “FLEXPART-WRF”, WaterSip reads the specific humidity field from WRF, and UTrack reads the precipitable water field from WRF but the evaporation field is ERA5 data assimilated into WRF. In the second case, “FLEXPART-ERA5”, I interpret that both WaterSip and UTrack read all fields from ERA5. If this is not the correct interpretation, please clarify.
L172 & L210: The Dirmeyer and Brubaker approach is also used by other studies, whose moisture tracking method is very similar to UTrack, e.g. Holgate, C. M., J. P. Evans, A. I. J. M. van Dijk, A. J. Pitman, and G. D. Virgilio, 2020: Australian Precipitation Recycling and Evaporative Source Regions. Journal of Climate, 33, 8721–8735, https://doi.org/10.1175/JCLI-D-19-0926.1. Similarly, the WaterSip approach is also used by other studies, e.g. Cheng, T. F., and M. Lu, 2023: Global Lagrangian Tracking of Continental Precipitation Recycling, Footprints, and Cascades. Journal of Climate, https://doi.org/10.1175/JCLI-D-22-0185.1. Though these specific methods are not formerly evaluated here, it would be pertinent to acknowledge them.
Figures 3 and 4: it would be helpful to the reader if these figures could be placed side by side for easier comparison. Is it possible to combine the two figures into one?
L230: To make it easier for the reader to interpret the error scores, it would be helpful to add a sentence linking each score with a physical meaning, e.g. a higher value of MAESS refers to a more accurate comparison with the reference dataset.
L303: To make it clearer to the reader, it would be helpful for the accumulation over time to be shown with a simple example. As the manuscript currently reads, it is unclear what the problem with the WaterSip method is.
L378: The original configuration of UTrack appears to release parcels from a random, humidity-weighted vertical level, indicating the starting parcel levels will be in the lower part of the troposphere. Yet here, and in Figure 7, it is indicated that the starting parcel level is 0km. Was the starting parcel height set at 0km in this study, or was a random, humidity-weighted vertical level used as in the original model? Further, did this study use a random, humidity-weighted vertical release height and simply ignore those parcels starting below 2km, or was the release height set at a constant 2km level in the modified case?
L416: Can you provide some reasoning as to why WaterSip is superior to UTrack when using ERA5 data?
L475: The statement that the Lagrangian methods can serve as viable alternatives for WRF-WVTs is a key conclusion of the study. I would suggest including this conclusion in the abstract.
Technical corrections
Figure 1: it would be helpful if the subplots each had a title describing their geographic location, e.g. “South Africa”. These location labels can then be added to Table 1 to make it easier for the reader to associate the numerical description with a real-world location.
Figure 2: “Tropical Indic” should perhaps be “Tropical Indian” (same issue applies to later figures). Also some parts of the world are classed as “Tropical land” when they are in fact desert regions (e.g. northern and southern Africa, central Australia, Arabian peninsula). To avoid re-running the model with different regions, I suggest touching on the implications of this classification in your results.
L165: Should “Except for the position and the…” be “Except for the position of the parcel and the …”?
Citation: https://doi.org/10.5194/esd-2024-18-RC1
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