Search for: All records

The influence of the Unified Noah and Noah-MP land surface models (LSMs) on the evolution of cumulus clouds reaching convective initiation (CI) is assessed using infrared brightness temperatures (BT) from GOES-16. Cloud properties from individual cloud objects are examined using output from high-resolution (500 m horizontal grid spacing) model simulations. Cloud objects are tracked over time and related to observed clouds reaching CI to examine differences in cloud extent, longevity, and growth rate. The results demonstrate that differences in assumed surface properties can lead to large discrepancies in the net surface radiative budget, particularly in the sensible and latent heating components where differences exceed 40 W m−2. These differences lead to changes in the local mesoscale circulation patterns that are more pronounced near the edges of forested and grassland boundaries where lower-level convergence is stronger. Higher sensible heating from the Noah-MP LSM produced growth of CI clouds earlier and with increased longevity, which was closer to the timing and growth observed from GOES-16. The increased cloud growth in the Noah-MP experiment results from stronger and deeper updrafts, which lofts more cloud water into the upper levels of the troposphere. The weaker updrafts from the Noah LSM experiment results in shallower convection after CI is detected due to slower growth rates. The differences in cloud properties and growth are directly related to the land surfaces they develop above and point to the importance of accurately representing land properties and radiative characteristics when simulating convection in numerical weather prediction models. 

Flash drought, characterized by unusually rapid drying, can have substantial impact on many socioeconomic sectors, particularly agriculture. However, potential changes to flash drought risk in a warming climate remain unknown. In this study, projected changes in flash drought frequency and cropland risk from flash drought are quantified using global climate model simulations. We find that flash drought occurrence is expected to increase globally among all scenarios, with the sharpest increases seen in scenarios with higher radiative forcing and greater fossil fuel usage. Flash drought risk over cropland is expected to increase globally, with the largest increases projected across North America (change in annual risk from 32% in 2015 to 49% in 2100) and Europe (32% to 53%) in the most extreme emissions scenario. Following low-end and medium scenarios compared to high-end scenarios indicates a notable reduction in annual flash drought risk over cropland.

 

In this study, a polarimetric radar forward model operator was developed for the Weather Research and Forecasting (WRF) model that was based on a scattering algorithm using the T-matrix methodology. Three microphysics schemes—Thompson, Morrison 2-moment, and Milbrandt-Yau 2-moment—were supported in the operator. This radar forward operator used the microphysics, thermodynamic, and wind fields from WRF model forecasts to compute horizontal reflectivity, radial velocity, and polarimetric variables including differential reflectivity (ZDR) and specific differential phase (KDP) for S-band radar. A case study with severe convective storms was used to examine the accuracy of the radar operator. Output from the radar operator was compared to real radar observations from the Weather Surveillance Radar–1988 Doppler (WSR-88D) radar. The results showed that the radar forward operator generated realistic polarimetric signatures. The distribution of polarimetric variables agreed well with the hydrometer properties produced by different microphysics schemes. Similar to the observed polarimetric signatures, radar operator output showed ZDR and KDP columns from low-to-mid troposphere, reflecting the large amount of rain within strong updrafts. The Thompson scheme produced a better simulation for the hail storm with a ZDR hole to indicate the existence of graupel in the low troposphere. 

In this study, a polarimetric radar forward model operator was developed for the Weather Research and Forecasting (WRF) model that was based on a scattering algorithm using the T-matrix methodology. Three microphysics schemes—Thompson, Morrison 2-moment, and Milbrandt-Yau 2-moment—were supported in the operator. This radar forward operator used the microphysics, thermodynamic, and wind fields from WRF model forecasts to compute horizontal reflectivity, radial velocity, and polarimetric variables including differential reflectivity (ZDR) and specific differential phase (KDP) for S-band radar. A case study with severe convective storms was used to examine the accuracy of the radar operator. Output from the radar operator was compared to real radar observations from the Weather Surveillance Radar–1988 Doppler (WSR-88D) radar. The results showed that the radar forward operator generated realistic polarimetric signatures. The distribution of polarimetric variables agreed well with the hydrometer properties produced by different microphysics schemes. Similar to the observed polarimetric signatures, radar operator output showed ZDR and KDP columns from low-to-mid troposphere, reflecting the large amount of rain within strong updrafts. The Thompson scheme produced a better simulation for the hail storm with a ZDR hole to indicate the existence of graupel in the low troposphere. 

In the two decades, since the advent of the term “flash drought,” considerable research has been directed toward the topic. Within the scientific community, we have actively forged a new paradigm that has avoided a chaotic evolution of conventional drought but instead recognizes that flash droughts have distinct dynamics and, particularly, impacts. We have moved beyond the initial debate over the definition of flash drought to a centralized focus on the triad of rapid onset, drought development, and associated impacts. The refinement toward this general set of principles has led to significant progress in determining key variables for monitoring flash drought development, identifying notable case studies, and compiling fundamental physical characteristics of flash drought. However, critical focus areas still remain, including advancing our knowledge on the atmospheric and oceanic drivers of flash drought; developing flash drought‐specific detection indices and monitoring systems tailored to practitioners; improving subseasonal‐to‐seasonal prediction of these events; constraining uncertainty in flash drought and impact projections; and using social science to further our understanding of impacts, particularly with regard to sectors that lie outside of our traditional hydroclimatological focus, such as wildfire management and food‐security monitoring. Researchers and stakeholders working together on these critical topics will assure society is resilient to flash drought in a changing climate.

This article is categorized under:

Science of Water > Water Extremes

 

Flash droughts develop rapidly (∼1 month timescale) and produce significant ecological, agricultural, and socioeconomical impacts. Recent advances in our understanding of flash droughts have resulted in methods to identify and quantify flash drought events. However, few studies have been done to isolate the individual rapid intensification and drought components of flash drought, which could further determine their causes, evolution, and predictability. This study utilized the standardized evaporative stress ratio (SESR) to quantify individual components of flash drought from 1979 – 2019, using evapotranspiration (ET) and potential evapotranspiration (PET) data from the North American Regional Reanalysis (NARR) dataset. The temporal change in SESR was utilized to quantify the rapid intensification component of flash drought. The drought component was also determined using SESR and compared to the United States Drought Monitor. The results showed that SESR was able to represent the spatial coverage of drought well for regions east of the Rocky Mountains. Furthermore, the rapid intensification component agreed well with previous flash drought studies, with the overall climatology of rapid intensification events showing similar hotspots to the flash drought climatology east of the Rocky Mountains. The rapid intensification climatology suggested areas west of the Rocky Mountains experience rapid drying more often than east of the Rocky Mountains. 

Abstract Probabilistic forecasts of changes in soil moisture and an Evaporative Stress Index (ESI) on sub-seasonal time scales over the contiguous U.S. are developed. The forecasts use the current land surface conditions and numerical weather prediction forecasts from the Sub-seasonal to Seasonal (S2S) Prediction Project. Changes in soil moisture are quite predictable 8-14 days in advance with 50% or more of the variance explained over the majority of the contiguous U.S.; however, changes in ESI are significantly less predictable. A simple red noise model of predictability shows that the spatial variations in forecast skill are primarily a result of variations in the autocorrelation, or persistence, of the predicted variable, especially for the ESI. The difference in overall skill between soil moisture and ESI, on the other hand, is due to the greater soil moisture predictability by the numerical model forecasts. As the forecast lead time increases from 8-14 days to 15-28 days, however, the autocorrelation dominates the soil moisture and ESI differences as well. An analysis of modelled transpiration, and bare soil and canopy water evaporation contributions to total evaporation, suggests improvements to the ESI forecasts can be achieved by estimating the relative contributions of these components to the initial ESI state. The importance of probabilistic forecasts for reproducing the correct probability of anomaly intensification is also shown. 

The influence of the Unified Noah and Noah‐MP land surface models (LSMs) on the evolution of cumulus clouds reaching convective initiation (CI) is assessed using infrared brightness temperatures (BT) from GOES‐16. Cloud properties from individual cloud objects are examined using output from high‐resolution (500 m horizontal grid spacing) model simulations. Cloud objects are tracked over time and related to observed clouds reaching CI to examine differences in cloud extent, longevity, and growth rate. The results demonstrate that differences in assumed surface properties can lead to large discrepancies in the net surface radiative budget, particularly in the sensible and latent heating components where differences exceed 40 W m⁻². These differences lead to changes in the local mesoscale circulation patterns that are more pronounced near the edges of forested and grassland boundaries where lower‐level convergence is stronger. Higher sensible heating from the Noah‐MP LSM produced growth of CI clouds earlier and with increased longevity, which was closer to the timing and growth observed from GOES‐16. The increased cloud growth in the Noah‐MP experiment results from stronger and deeper updrafts, which lofts more cloud water into the upper levels of the troposphere. The weaker updrafts from the Noah LSM experiment results in shallower convection after CI is detected due to slower growth rates. The differences in cloud properties and growth are directly related to the land surfaces they develop above and point to the importance of accurately representing land properties and radiative characteristics when simulating convection in numerical weather prediction models.

 

Flash drought is characterized by a period of rapid drought intensification with impacts on agriculture, water resources, ecosystems, and the human environment. Addressing these challenges requires a fundamental understanding of flash drought occurrence. This study identifies global hotspots for flash drought from 1980–2015 via anomalies in evaporative stress and the standardized evaporative stress ratio. Flash drought hotspots exist over Brazil, the Sahel, the Great Rift Valley, and India, with notable local hotspots over the central United States, southwestern Russia, and northeastern China. Six of the fifteen study regions experienced a statistically significant increase in flash drought during 1980–2015. In contrast, three study regions witnessed a significant decline in flash drought frequency. Finally, the results illustrate that multiple pathways of research are needed to further our understanding of the regional drivers of flash drought and the complex interactions between flash drought and socioeconomic impacts.