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Ronald D. Leeper, Bryan Petersen, Michael A. Palecki, and Howard Diamond

Abstract

Agricultural drought has traditionally been monitored using indices that are based on above-ground measures of temperature and precipitation that have lengthy historical records. However, the period-of-record length for soil moisture networks is becoming sufficient enough to standardize and evaluate soil moisture anomalies and percentiles that are spatially and temporally independent of local soil type, topography, and climatology. To explore these standardized measures in the context of drought, the U.S. Climate Reference Network hourly standardized soil moisture anomalies and percentiles were evaluated against changes in the U.S. Drought Monitor (USDM) status, with a focus on onset, worsening, and improving drought conditions. The purpose of this study was to explore time scales (i.e., 1–6 weeks) and soil moisture at individual (i.e., 5, 10, 20, 50, and 100 cm) and aggregated layer (i.e., top and column) depths to determine those that were more closely align with evolving drought conditions. Results indicated that the upper-level depths (5, 10, and 20 cm, and top layer aggregate) and shorter averaging periods were more responsive to changes in USDM drought status. This was particularly evident during the initial and latter stages of drought when USDM status changes were thought to be more aligned with soil moisture conditions. This result indicates that standardized measures of soil moisture can be useful in drought monitoring and forecasting applications during these critical stages of drought formation and amelioration.

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Baojuan Huai, Michiel R. van den Broeke, Carleen H. Reijmer, and John Cappellen

Abstract

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.

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Dehe Xu, Qi Zhang, Yan Ding, and De Zhang

Abstract

Drought is a common natural disaster that greatly affects the crop yield and water supply in China. However, the spatiotemporal characteristics of drought in China are not well understood. This paper explores the spatial and temporal distributions of droughts in China over the past 40 years using multiscale standardized precipitation evapotranspiration index (SPEI) values calculated by monthly precipitation and temperature data from 612 meteorological stations in China from 1980 to 2019 and combines the space-time cube (STC), Mann-Kendall (M-K) test, emerging spatiotemporal hotspot analysis, spatiotemporal clustering and local outliers for the analysis. The results were as follows: 1) the drought frequency and STC show that there is a significant difference in the spatiotemporal distribution of drought in China, with the most severe drought in Northwest China, followed by the western part of Southwest China and the northern part of North China. 2) The emerging spatiotemporal hotspot analysis of SPEI6 over the past 40 years reveals two cold spots in subregion 4, indicating that future droughts in the region will be more severe. 3) A local outlier analysis of the multiscale SPEI yields a low-low outlier in western North China, indicating relatively more severe year-round drought in this area than in other areas. The low-high outlier in central China indicates that this region was not dry in the past and that drought will become more severe in this region in the future.

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Thomas O. Mazzetti, Bart Geerts, Lulin Xue, Sarah Tessendorf, Courtney Weeks, and Yonggang Wang

Abstract

Glaciogenic cloud seeding has long been practiced as a way to increase water availability in arid regions, such as the interior western United States. Many seeding programs in this region target cold–season orographic clouds with ground–based silver iodide generators. Here, the “seedability” (defined as the fraction of time conditions are suitable for ground–based seeding) is evaluated in this region, based on 10 years of hourly output from a regional climate model with a horizontal resolution of 4 km. Seedability criteria are based on temperature, presence of supercooled liquid water, and Froude number, which is computed here as a continuous field relative to the local terrain. The model’s supercooled liquid water compares reasonably well against microwave radiometer observations.

Seedability peaks at 20–30% for many mountain ranges in the cold season, with the best locations just upwind of crests, over the highest terrain in Colorado and Wyoming, as well as over ranges in the Northwest Interior. Mountains further south are less frequently seedable, due to warmer conditions, but when they are, cloud supercooled liquid water content tends to be relatively high.

This analysis is extended into a future climate, anticipated for later this century, with a mean temperature 2.0 K warmer than the historical climate. Seedability generally will be lower in this future warmer climate, especially in the most seedable areas, but when seedable, clouds tend to contain slightly more supercooled liquid water.

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Zunya Wang, Yanju Liu, Guofu Wang, and Qiang Zhang

Abstract

It is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over the middle and high latitude Eurasia acts as an important thermal background. It is characterized by such two dominant modes as the “consistent cooling” pattern and the “Warm high latitude Eurasia and cold middle latitude Eurasia” pattern from the mid-1990s to the early 2010s. And the two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of Arctic oscillation (AO), Ural blocking (UB) and Siberian high (SH) are all highly correlated to the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO affects directly the occurrence of LTE for its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of Ural blocking (UB) and Siberian high (SH). Further analyses show that, the winter temperature over the middle and high latitude Eurasia has a close relationship with the AO, but they are believed to be the independent influential factors of the increase of LTE in northern China from the mid-1990s to the early 2010s.

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Bianca Adler, James M. Wilczak, Laura Bianco, Irina Djalalova, James B. Duncan Jr., and David D. Turner

Abstract

Persistent cold pools form as layers of cold stagnant air within topographical depressions mainly during wintertime when the near-surface air cools and/or the air aloft warms and daytime surface heating is insufficient to mix out the stable layer. An area often affected by persistent cold pools is the Columbia River Basin in the Pacific Northwest, when a high-pressure system east of the Cascade Range promotes radiative cooling and easterly flow. The only major outflow for the easterly flow is through the narrow Columbia River Gorge which cuts through the north-south oriented Cascade Range and often experiences very strong gap flows. Observations collected during the Second Wind Forecast Improvement Project (WFIP2) are used to study a persistent cold pool in the Columbia River Basin between 10-19 Jan 2017 which was associated with a strong gap flow. We used data from various remote sensing and in situ instruments and a optimal estimation physical retrieval to obtain thermodynamic profiles to address the temporal and spatial characteristics of the cold pool and gap flow and to investigate the physical processes involved during formation, maintenance and decay. While large-scale temperature advection occurred during all phases, we found that the cold pool vertical structure was modulated by the existence of low-level clouds and that turbulent shear-induced mixing and downslope wind storms likely played a role during its decay.

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Nayeong Cho, Jackson Tan, and Lazaros Oreopoulos

Abstract

We present an updated cloud regime (CR) dataset based on Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 cloud products, specifically, joint histograms that partition cloud fraction within distinct combinations of cloud-top pressure and cloud optical thickness ranges. The paper focuses on an edition of the CR dataset derived from our own aggregation of MODIS pixel-level cloud retrievals on an equal-area grid and prespecified 3-h UTC intervals that spatiotemporally match International Satellite Cloud Climatology Project (ISCCP) gridded cloud data. The other edition comes from the 1° daily aggregation provided by standard MODIS Level-3 data, as in previous versions of the MODIS CRs, for easier use with datasets mapped on equal-angle grids. Both editions consist of 11 clusters whose centroids are nearly identical. We provide a physical interpretation of the new CRs and aspects of their climatology that have not been previously examined, such as seasonal and interannual variability of CR frequency of occurrence. We also examine the makeup and precipitation properties of the CRs assisted by independent datasets originating from active observations and provide a first glimpse of how MODIS CRs relate to clouds as seen by ISCCP.

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Joseph Coz, Frank Alsheimer, and Bernhard Lee Lindner

Abstract

Coastal nuisance flooding has increased by an order of magnitude over the past half century, but the National Weather Service has a limited suite of statistical tools to forecast it. Such a tool was developed using coastal flood events from 1996 to 2014 in Charleston, South Carolina, that were identified and classified by prevailing synoptic conditions based on composite mean sea level pressure anomalies. The synoptic climatology indicated low-level northeasterly winds dominated the forcing in anticyclonic and cyclonic events, while a southeasterly surge was the main forcing component for frontal events. Tidal anomalies between flood events and previous low tides were used to create linear regression models for each composite classification studied for forecasting levels of coastal flood magnitude. Beta tests using data from 2018 to 2019 confirmed the effectiveness of the models with RMSE values less than 0.3 ft (9 cm) and MAE values less than 0.25 ft (7.6 cm) for each event type. The veracity of the methods was further verified by a multiple-day case study from November 2018, where the model was tested against both statistically predicted heights and heights based on the NOAA extratropical storm surge (ETSS) model (version 2.2). The RMSE and MAE for the statistical model were 0.18 and 0.15, respectively, while the same values for the ETSS model were 0.28 and 0.23, respectively.

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Janel Hanrahan, Jessica Langlois, Lauren Cornell, Huanping Huang, Jonathan M. Winter, Patrick J. Clemins, Brian Beckage, and Cindy Bruyère

Abstract

Most inland water bodies are not resolved by general circulation models, requiring that lake surface temperatures be estimated. Given the large spatial and temporal variability of the surface temperatures of the North American Great Lakes, such estimations can introduce errors when used as lower boundary conditions for dynamical downscaling. Lake surface temperatures (LSTs) influence moisture and heat fluxes, thus impacting precipitation within the immediate region and potentially in regions downwind of the lakes. For this study, the Advanced Research version of the Weather Research and Forecasting Model (WRF-ARW) was used to simulate precipitation over the six New England states during a 5-yr historical period. The model simulation was repeated with perturbed LSTs, ranging from 10°C below to 10°C above baseline values obtained from reanalysis data, to determine whether the inclusion of erroneous LST values has an impact on simulated precipitation and synoptic-scale features. Results show that simulated precipitation in New England is statistically correlated with LST perturbations, but this region falls on a wet–dry line of a larger bimodal distribution. Wetter conditions occur to the north and drier conditions occur to the south with increasing LSTs, particularly during the warm season. The precipitation differences coincide with large-scale anomalous temperature, pressure, and moisture patterns. Care must therefore be taken to ensure reasonably accurate Great Lakes surface temperatures when simulating precipitation, especially in southeastern Canada, Maine, and the mid-Atlantic region.

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Yang Shi, Jiahua Wei, Yan Ren, Zhen Qiao, Qiong Li, Xiaomei Zhu, Beiming Kang, Peichong Pan, Jiongwei Cao, Jun Qiu, Tiejian Li, and Guangqian Wang

Abstract

Acoustic agglomerations have increasingly attracted widespread attention as a cost-effective and environmentally friendly approach for fog removal and weather modification. In this study, research on precipitation interference and the agglomeration performance of droplet aerosols under large-scale acoustic waves was presented. In total, 49 field experiments in the source region of the Yellow River in the summer of 2019 were performed to reveal the influences of acoustic waves on precipitation, such as the radar reflectivity factor Z, rain rate R, and raindrop size distribution (DSD). A monitoring system that consisted of rain gauges and raindrop spectrometers was employed to monitor near-ground rainfall within a 5-km radius of the field site. The ground-based observations showed that acoustic waves could significantly affect the rainfall distribution and microstructure of precipitation particles. The average values of rainfall increased by 18.98%, 10.61%, and 8.74% within 2, 3, and 5 km, respectively, of the operation center with acoustic application. The changing trend of microphysical parameters of precipitation was roughly in line with variation of acoustic waves for stratiform cloud. Moreover, there was a good quadratic relationship between the spectral parameters λ and μ. Raindrop kinetic energy e K and the radar reflectivity factor Z both exhibited a power function relationship with R.

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