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Free access
C. Cammalleri
,
N. McCormick
,
J. Spinoni
, and
J. W. Nielsen-Gammon

Abstract

The standardized precipitation index (SPI) is the most commonly used index for detecting and characterizing meteorological droughts, and it is also extensively used as a proxy variable for soil moisture anomalies (SMA) for the purpose of monitoring agricultural drought in absence of long-term soil moisture observations. However, the potential capability of SPI to warn of the time-lagged soil water deficit—following the well-known “drought cascade” effect—is often overlooked in agricultural drought studies. In this research, a time-lagged correlation analysis is used to evaluate the relationship between the SMA dataset, generated as part of the Global Drought Observatory of the European Union’s Copernicus Emergency Management Service, and a set of SPIs derived from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts. The possibility to achieve an optimal agreement between SPI and SMA that also preserves the early warning skills of SPI is evaluated. The results suggest that if only the correlation between SPI and SMA is considered, the maximum agreement is usually obtained with a zero lead time (almost 80% of the cases), with SPI-3 representing the best option in about 40% of the grid cells at global scale. By also accounting for the benefits of a positive lead time, short accumulation periods tend to be favored, with SPI-1 being the optimal choice in about one-half of the cases, and 10–20 days of lead time in more than 90% of the grid cells is achieved without any significant reduction in either correlation or skill in drought extreme detection.

Open access
Joana Mendes
,
Nosipho Zwane
,
Brighton Mabasa
,
Henerica Tazvinga
,
Karen Walter
,
Cyril J. Morcrette
, and
Joel Botai

Abstract

We assess site-specific surface shortwave radiation forecasts from two high-resolution configurations of the South African Weather Service numerical weather prediction model, at 4 and 1.5 km. The models exhibit good skill overall in forecasting surface shortwave radiation, with zero median error for all radiation components. This information is relevant to support a growing renewable energy sector in South Africa, particularly for photovoltaics. Further model performance analysis has shown an imbalance between cloud and solar radiation forecasting errors. In addition, cloud overprediction does not necessarily equate to underestimating solar radiation. Overcast cloud regimes are predicted too often with an associated positive mean radiation bias, whereas the relative abundance of partly cloudy regimes is underpredicted by the models with mixed radiation biases. Challenges highlighted by the misrepresentation of partly cloudy regimes in solar radiation error attribution may be used to inform improvements to the numerical core, namely, the cloud and radiation schemes.

Significance Statement

This paper provides the first comprehensive assessment of high-resolution site-specific NWP forecasts of surface shortwave radiation in South Africa, exploring clouds as the main drivers of prediction biases. Error attribution analyses of this kind are close to none for this part of the world. Our study contributes to understanding how cloud and radiation schemes perform over South Africa, representing a step forward in the state of the art. In addition to the scientific interest, the capabilities developed through this work may benefit the second largest economy of the continent. In a country where energy security is of critical relevance, the availability of useful and usable weather information is paramount to support its industry and socioeconomic growth.

Open access
Andra J. Garner
and
Daniel P. Duran

Abstract

Large temperature variations in a temperate climate, particularly in late winter and early spring, can be disruptive for native ecosystems and agricultural crops. As warmer temperatures occur earlier in the year in midlatitude regions as a result of anthropogenic climate change, springtime temperatures may become less consistent, leading to potential damage to species and crops that are vulnerable to the return of historically cooler temperatures, including late-spring frosts, after an initial warm-up. In this work, we quantify shifting patterns in late-winter and springtime temperature variations at eight sites across New Jersey from 1950 to 2019. Many sites located along the coast or in the coastal plain experience increases in the number of times the temperature climbs above 15.5°C (60°F) and then falls below freezing (i.e.,0°C, or 32°F). Sites in southern New Jersey (where much of the state’s agriculture is located) experience the most significant (P < 0.05) increases in large springtime temperature variations. Across all sites, there is a general increase in both the percentage and magnitude of temperature variations that occur as early as February. At 75% of sites, day-to-day variation in daily maximum temperature has increased from the 1950s through 2019; day-to-day variation in daily minimum temperatures has increased over the same time at more than half of sites considered. These amplifications in extreme temperature variations indicate the need for both mitigation and adaptation strategies to protect vulnerable crops and ecosystems in the region during this critical time of the year.

Significance Statement

Human-caused climate change has made it more likely for warmer temperatures to occur earlier in the year, causing many locations to experience late-winter and early-springtime temperatures that are less consistent than they may have been in the past. These variations can be highly problematic for both vital agricultural crops and critical ecosystems. Here, we evaluate how late-winter and early-springtime temperatures have changed throughout New Jersey (home to a variety of agriculture and unique ecosystems) from the mid-twentieth century until 2019. We find critical changes to temperature patterns during late winter and early spring, including larger and more frequent temperature swings (particularly in February) and increased day-to-day variation in high and low temperatures.

Open access
Free access
Reinel Sospedra-Alfonso
,
William J. Merryfield
,
Viatsheslav V. Kharin
,
Woo-Sung Lee
,
Hai Lin
,
Gulilat T. Diro
, and
Ryan Muncaster

Abstract

We evaluate the soil moisture hindcasts and the reconstruction runs giving the hindcasts initial conditions in version 2.1 of the Canadian Seasonal to Interannual Prediction System (CanSIPSv2.1). Different strategies are used to initialize the hindcasts for the two CanSIPSv2.1 models, CanCM4i and the coupled Global Environmental Multiscale, version 5.1, (GEM5)–NEMO model (GEM5-NEMO), with contrasting impacts on the soil moisture initial conditions and forecast performance. Forecast correlation skill is decomposed into contributions from persistence of the initial anomalies and contributions not linked to persistence, with performance largely driven by the accuracy of the initial conditions in regions of strong persistence. Seasonal soil moisture correlation skill is significant for several months into the hindcasts depending on initial and target months, with contributions not linked to persistence becoming more notable at longer lead times. For the first 2–4 months, the quality of CanSIPSv2.1 ensemble mean forecasts tends to be higher on average during summer and fall and is comparable to that of the best performing model, whereas CanSIPSv2.1 outperforms the single models during spring and winter. For longer lead times, remote climate influences from the Pacific Ocean are notable and contribute to predictable soil moisture variability in teleconnected regions.

Open access
Austin P. Hope
,
Israel Lopez-Coto
,
Kris Hajny
,
Jay M. Tomlin
,
Robert Kaeser
,
Brian Stirm
,
Anna Karion
, and
Paul B. Shepson

Abstract

We investigated the ability of three planetary boundary layer (PBL) schemes in the Weather Research and Forecasting (WRF) Model to simulate boundary layer turbulence in the “gray zone” (i.e., resolutions from 100 m to 1 km). The three schemes chosen are the well-established MYNN PBL scheme and the two newest PBL schemes added to WRF: the three-dimensional scale-adaptive turbulent kinetic energy scheme (SMS-3DTKE) and the E–ε parameterization scheme (EEPS). The SMS-3DTKE scheme is designed to be scale aware and avoid the double counting of TKE in simulations within the gray zone. We evaluated their performance using aircraft measurements obtained during three research flights immediately downwind of Manhattan, New York City, New York. The MYNN PBL scheme simulates TKE best, despite not being scale aware and slightly underestimating TKE from observations, whereas the SMS-3DTKE scheme appears to be overly scale aware for the three flights examined, in particular, when combined with the MM5 surface layer scheme. The EEPS scheme significantly underestimates TKE, mostly in the elevated layers of the boundary layer. In addition, we examined the impact of flow over tall buildings on observed TKE and found that only the windiest day showed a significant increase in TKE directly downwind of Manhattan. This impact was not reproduced by any of the model configurations, regardless of the land-use data selected, although the better resolved National Land Cover Database (NLCD) land use led to a slight improvement of the spatial distribution of TKE, implying that more explicit representation of the impact of tall buildings may be needed to fully capture their impact on boundary layer turbulence.

Significance Statement

Because the majority of the world’s population lives in cities, it is important to accurately simulate the atmosphere above and around these cities including the turbulence caused by tall buildings. This turbulence can significantly impact the mixing and dilution of air pollutants and other toxins in highly populated urban environments. The scale of cities often falls into what is known as the “gray zone” for turbulence modeling, which has been analyzed theoretically before but rarely in varied real-world conditions. Our analysis around New York City, New York, suggests that model turbulence schemes can match observations relatively well even at gray zone scales, although newer schemes require refinement, and all schemes tend to underestimate turbulence downwind of tall buildings.

Open access
Luis A. Gil-Alana
and
Marlon J. Castillo

Abstract

In this paper, we perform a fractional integration analysis of the average monthly temperature and precipitation data in 17 departments of Guatemala. Two analyses are performed, the first with the original data and the second with the anomalies based on the period January 1994–December 1999. The results indicate that there is a significant positive time trend in temperatures in the departments of Guatemala (0.0045°C month−1), Quetzaltenango (0.0040°C month−1), Escuintla (0.0034°C month−1), and Huehuetenango (0.0047°C month−1), whereas in the case of precipitation no time trend was observed. An important relevant result is that the departments of El Progreso, Baja Verapaz, and Guatemala occupy the second, third and fourth highest levels of persistence for both temperatures and precipitation, with Sacatepéquez and Quiché displaying the first places for temperature and precipitation, respectively, thus making these five departments the ones that are most vulnerable to climate change since a shock would take a long time to disappear.

Open access
Mathieu Lachapelle
,
Hadleigh D. Thompson
,
Nicolas R. Leroux
, and
Julie M. Thériault

Abstract

This study aims to characterize the shapes and fall speeds of ice pellets formed in various atmospheric conditions and to investigate the possibility to use a laser-optical disdrometer to distinguish between ice pellets and other types of precipitation. To do so, four ice pellet events were documented using manual observations, macrophotography, and laser-optical disdrometer data. First, various ice pellet fall speeds and shapes, including spherical, bulged, fractured, and irregular particles, were associated with distinct atmospheric conditions. A higher fraction of bulged and fractured ice pellets was observed when solid precipitation was completely melted aloft while more irregular particles were observed during partial melting. These characteristics affected the diameter–fall speed relations measured. Second, the measurements of particles’ fall speed and diameter show that ice pellets could be differentiated from rain or freezing rain. Ice pellets larger than 1.5 mm tend to fall > 0.5 m s−1 slower than raindrops of the same size. In addition, the fall speed of a small fraction of ice pellets was < 2 m s−1 regardless of their size, as compared with a fall speed > 3 m s−1 for ice pellets with diameter > 1.5 mm. Video analysis suggests that these slower particles could be ice pellets passing through the laser-optical disdrometer after colliding with the head of the instrument. Overall, these findings contribute to a better understanding of the microphysics of ice pellets and their measurement using a laser-optical disdrometer.

Significance Statement

Ice pellets are challenging to forecast and to detect automatically. In this study, we documented the fall speed and physical characteristics of ice pellets during various atmospheric conditions using a combination of a laser-optical disdrometer, manual observations, and macrophotography images. Relationships were found between the shape and fall speed of ice pellets. These findings could be used to refine the parameterization of ice pellets in atmospheric models and, consequently, improve the forecast of impactful winter precipitation types such as freezing rain. Furthermore, they will also help to physically interpret laser-optical disdrometer data during ice pellets and freezing rain.

Open access
Jielun Sun
,
Volker Wulfmeyer
,
Florian Späth
,
Holger Vömel
,
William Brown
, and
Steven Oncley

Abstract

The hydrostatic equilibrium addresses the approximate balance between the positive force of the vertical pressure gradient and the negative gravity force and has been widely assumed for atmospheric applications. The hydrostatic imbalance of the mean atmospheric state for the acceleration of vertical motions in the vertical momentum balance is investigated using tower, the global positioning system radiosonde, and Doppler lidar and radar observations throughout the diurnally varying atmospheric boundary layer (ABL) under clear-sky conditions. Because of the negligibly small mean vertical velocity, the acceleration of vertical motions is dominated by vertical variations of vertical turbulent velocity variances. The imbalance is found to be mainly due to the vertical turbulent transport of changing air density as a result of thermal expansion/contraction in response to air temperature changes following surface temperature changes. In contrast, any pressure change associated with air temperature changes is small, and the positive vertical pressure-gradient force is strongly influenced by its background value. The vertical variation of the turbulent velocity variance from its vertical increase in the lower convective boundary layer (CBL) to its vertical decrease in the upper CBL is observed to be associated with the sign change of the imbalance from positive to negative due to the vertical decrease of the positive vertical pressure-gradient force and the relative increase of the negative gravity force as a result of the decreasing upward transport of the low-density air. The imbalance is reduced significantly at night but does not steadily approach zero. Understanding the development of hydrostatic imbalance has important implications for understanding large-scale atmosphere, especially for cloud development.

Significance Statement

It is well known that the hydrostatic imbalance between the positive pressure-gradient force due to the vertical decrease of atmospheric pressure and the negative gravity forces in the vertical momentum balance equation has important impacts on the vertical acceleration of atmospheric vertical motions. Vertical motions for mass, momentum, and energy transfers contribute significantly to changing atmospheric dynamics and thermodynamics. This study investigates the often-assumed hydrostatic equilibrium and investigate how the hydrostatic imbalance is developed using field observations in the atmospheric boundary layer under clear-sky conditions. The results reveal that hydrostatic imbalance can develop from the large-eddy turbulent transfer of changing air density in response to the surface diabatic heating/cooling. The overwhelming turbulence in response to large-scale thermal forcing and mechanical work of the vast Earth surface contributes to the hydrostatic imbalance on large spatial and temporal scales in numerical weather forecast and climate models.

Open access