Validation of the final monthly Integrated Multi-satellitE Retrievals for GPM (IMERG) Version 05 and Version 06 with ground-based precipitation gauge measurements across the Canadian Arctic

To assess the performance of the most recent versions of the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), namely V05 and V06, in Arctic regions, comparisons with Environment and Climate Change Canada (ECCC) Climate Network stations north of 60°N were performed. This study focuses on the IMERG monthly final products. The mean bias and mean error-weighted bias were assessed in comparison with twenty-five precipitation gauge measurements at ECCC Climate Network stations. The results of this study indicate that IMERG generally detects higher precipitation rates in the Canadian Arctic than ground-based gauge instruments, with differences ranging up to 0.05 mm h−1 and 0.04 mm h−1 for the mean bias and the mean error-weighted bias, respectively. Both IMERG versions perform similarly, except for a few stations, where V06 tends agree slightly better with ground-based measurements. IMERG’s tendency to detect more precipitation is in good agreement with findings indicating that weighing gauge measurement suffer from wind undercatch and other impairing factors, leading to lower precipitation estimates. Biases between IMERG and ground-based stations were found to be slightly larger during summer and fall, which is likely related to the increased precipitation rates during these seasons. Correlations of both versions of IMERG with the ground-based measurements are considerably lower in winter and spring than during summer and fall, which might be linked to issues that Passive Microwave (PMW) sensors encounter over ice and snow. However, high correlation coefficients with medians of 0.75-0.8 during summer and fall are very encouraging for potential future applications.

Extreme precipitating events in satellite and rain-gauge products over the Sahel

Over the recent decades, Extreme Precipitation Events (EPE) have become more frequent over the Sahel. Their properties, however, have so far received little attention. In this study the spatial distribution, intensity, seasonality and interannual variability of EPEs are examined, using both a reference dataset, based on a high-density rain-gauge network over Burkina Faso and 24 precipitation gridded datasets. The gridded datasets are evaluated in depth over Burkina Faso while their commonalities are used to document the EPE properties over the Sahel. EPEs are defined as the occurrence of daily-accumulated precipitation exceeding the all-day 99th percentile over a 1°x1° pixel. Over Burkina Faso, this percentile ranges between 21 and 33 mm day-1. The reference dataset show that EPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. These results are consistent among the gridded datasets over Burkina Faso but also over the wider Sahel. The gridded datasets exhibit a wide diversity of skills when compared to the Burkinabe reference. The Global Precipitation Climatology Centre Full Data Daily version 1 (GPCC-FDDv1) and the Global Satellite Mapping of Precipitation gauge Reanalysis version 6.0 (GSMaP-gauge-RNL v6.0) are the only products that properly reproduce all of the EPE features examined in this work. The datasets using a combination of microwave and infrared measurements are prone to overestimate the EPE intensity, while infrared-only products generally underestimate it. Their calibrated versions perform than their uncalibrated (near-real-time) versions. This study finally emphasizes that the lack of rain-gauge data availability over the whole Sahel strongly impedes our ability to gain insights in EPE properties.

Remote and autonomous measurements of precipitation for the northwestern Ross Ice Shelf, Antarctica

The Antarctic Precipitation System project deployed and maintained four sites across the northwestern Ross Ice Shelf in Antarctica from November 2017 to November 2019. The goals for the project included the collection of in situ observations of precipitation in Antarctica spanning a duration of 2 years, an improvement in the understanding of precipitation events across the Ross Ice Shelf, and the ability to validate precipitation data from atmospheric numerical models. At each of the four sites the precipitation was measured with an OTT Pluvio2 precipitation gauge. Additionally, snow accumulation at the site was measured with a sonic ranging sensor and using GPS interferometric reflectivity. Supplemental observations of temperature, wind speed, particle count, particle size and speed, and images and video from a camera were collected to provide context to the precipitation measurements. The collected dataset represents some of the first year-round observations of precipitation in Antarctica at remote locations using an autonomous measurement system. The acquired observations have been quality-controlled and post-processed, and they are available for retrieval through the United States Antarctic Program Data Center (https://doi.org/10.15784/601441, Seefeldt, 2021).

Unshielded precipitation gauge collection efficiency with wind speed and hydrometeor fall velocity

Collection efficiency transfer functions that compensate for wind-induced collection loss are presented and evaluated for unshielded precipitation gauges. Three novel transfer functions with wind speed and precipitation fall velocity dependence are developed, including a function from computational fluid dynamics modelling (CFD), an experimental fall velocity threshold function (HE1), and an experimental linear fall velocity dependence function (HE2). These functions are evaluated alongside universal (KUniversal) and climate-specific (KCARE) transfer functions with wind speed and temperature dependence. Transfer function performance is assessed using 30 min precipitation event accumulations reported by unshielded and shielded Geonor T-200B3 precipitation gauges over two winter seasons. The latter gauge was installed in a Double Fence Automated Reference (DFAR) configuration. Estimates of fall velocity were provided by the Precipitation Occurrence Sensor System (POSS). The CFD function reduced the RMSE (0.08 mm) relative to KUniversal (0.20 mm), KCARE (0.13 mm), and the unadjusted measurements (0.24 mm), with a bias error of 0.011 mm. The HE1 function provided a RMSE of 0.09 mm and bias error of 0.006 mm, capturing the collection efficiency trends for rain and snow well. The HE2 function better captured the overall collection efficiency, including mixed precipitation, resulting in a RMSE of 0.07 mm and bias error of 0.006 mm. These functions are assessed across solid and liquid hydrometeor types and for temperatures between −22 and 19 ∘C. The results demonstrate that transfer functions incorporating hydrometeor fall velocity can dramatically reduce the uncertainty of adjusted precipitation measurements relative to functions based on temperature.

Quantifying rainfall in Greenland: a combined observational and modelling approach

This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a Dynamic Correction Model (DCM) for Automatic Weather Stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R=0.3-0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02-1.40) are smaller than those for snowfall (1.27-2.80), and hence the observations more robust. With a horizontal resolution of 5.5 km and simulation period from 1958-present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients.

Investigation of the Wind-Induced Airflow Pattern Near the Thies LPM Precipitation Gauge

The airflow velocity pattern generated by a widely used non-catching precipitation gauge (the Thies laser precipitation monitor or LPM) when immersed in a wind field is investigated using computational fluid dynamics (CFD). The simulation numerically solves the unsteady Reynolds-averaged Navier–Stokes (URANS) equations and the setup is validated against dedicated wind tunnel measurements. The adopted k-ω shear stress transport (SST) turbulence model closely reproduces the flow pattern generated by the complex, non-axisymmetric outer geometry of the instrument. The airflow pattern near the measuring area varies with the wind direction, the most intense recirculating flow and turbulence being observed when the wind blows from the back of the instrument. Quantitative parameters are used to discuss the magnitude of the airflow perturbations with respect to the ideal configuration where the instrument is transparent to the wind. The generated airflow pattern is expected to induce some bias in operational measurements, especially in strong wind conditions. The proposed numerical simulation framework provides a basis to develop correction curves for the wind-induced bias of non-catching gauges, as a function of the undisturbed wind speed and direction.

Remote and Autonomous Measurements of Precipitation for the Northwest Ross Ice Shelf, Antarctica

The Antarctic Precipitation System project deployed and maintained four sites across the northwest Ross Ice Shelf in Antarctica from November 2017 to November 2019. The goals for the project included the collection of in situ observations of precipitation in Antarctica spanning a duration of two years, an improvement in the understanding of precipitation events across the Ross Ice Shelf, and the ability to validate precipitation data from atmospheric numerical models. At each of the four sites the precipitation was measured with an OTT Pluvio2 precipitation gauge. Additionally, snow accumulation at the site was measured with a sonic ranging sensor and using GPS-Interferometry Reflectivity. Supplemental observations of temperature, wind speed, particle count, particle size and speed, and images and video from a camera, were collected to provide context to the precipitation measurements. The collected dataset represents some of the first year-round observations of precipitation in Antarctic at remote locations using an autonomous measurement system. The acquired observations have been quality controlled, post-processed, and are available for retrieval through the United States Antarctic Program Data Center (Seefeldt, 2021; doi.org/10.15784/601441).

Homogenization of Norwegian monthly precipitation series

<p>Climate normals play an important role in weather and climate studies and therefore require high-quality dataset that is both consistent and homogenous. The Norwegian observation network has changed considerably during the last 20-30 years, introducing non-climatic changes such as automation and relocation. Homogenization was therefore necessary and work has been done at the Norwegian Meteorological Institute to establish a homogeneous precipitation reference dataset for the purpose of calculating the new climatological standard normals for the period 1991-2020. </p><p>The homogenization tool Climatol was applied to detect inhomogeneities in the Norwegian precipitation series, for the period 1961-2018. 370 series (including 44 from Sweden and one from Finland) of monthly precipitation sums, from the ClimNorm precipitation dataset were used in the homogenization analysis. ClimNorm is an international network activity under the Nordic Framework for Climate Services covering six countries in the Nordic region (Denmark, Estonia, Finland, Latvia, Norway and Sweden) with an objective that includes sharing data, methods and experiences in preparing a data basis as good as possible for calculation of new climate normals. </p><p>Results from homogeneity testing found inhomogeneities in 95 (29 %) of the 325 Norwegian precipitation series. However, only 81 (25 %) of the series were classified as inhomogeneous after conferring with metadata and therefore adjusted. Relocation of the precipitation gauge and automation were the main causes of all the inhomogeneities in the Norwegian series, explaining 71 % and 12 % respectively of all detected breaks. All but one of the accepted inhomogeneities could be confirmed with metadata. Inhomogeneities found in the Swedish and Finnish series were adjusted without metadata. Results further showed benefits of incorporating metadata to the automatically detected inhomogeneities. Linear trend analysis showed increasing trends in the period 1961-2018 except in autumn where a decreasing trend was observed. The homogeneity analysis produced a 58-year long homogenous dataset for 325 monthly precipitation sum with regional temporal variability and spatial coherence that was significantly better than that of non-homogenized series. The homogenized dataset is more reliable in explaining the large-scale climate variations and was used to calculate the new climate normals in Norway.</p>

Application of Correction Procedures for Some Systematic Measurement Errors to Rainfall Intensity Data of a Rain Gauge in Budapest

The rainfall intensity measurement has a 150 years long history. In the first period of data recordings, the siphoned recording precipitation gauge (pluviographs), or siphoned rainfall writers (SRW), later, the tipping bucket gauges (TBG) were widely used. The systematic errors of these instruments resulted in lower intensity values for long periods. These errors were compensated sporadically. Most of the inaccurate data can be found in the high rainfall intensity range. Some of these data can be found in extracted, aggregated versions only, and the original measurement data is no longer available. These kinds of inherited systematic errors can be corrected. The fixing of siphoning error of SRWs and the supplementary correction of long sampling period data of TBG devices can be a suitable method for the elimination of these issues. In this paper, the application of these two methods is shown in a case study to point out the magnitude and effect of these errors on the IDF curves. The case study on the use of the before-mentioned correction procedures is performed on the rainfall data of the Budapest-Belterület (Budapest City) rainfall station, using data series spanning 105 years. These corrections show that the earlier IDF curves can show 5–10% lower intensities, mainly in the short and low return frequency rainfalls. The result of these kinds of corrections can be significant for the climate change investigations or in the re-evaluation of the elder IDF curves.