Characteristics of Bay of Bengal monsoon depressions in the 21st Century

We show that 21st century increase in radiative forcing does not significantly impact the frequency of South Asian summer monsoon depressions (MDs) or their trajectories in the Coupled Model Intercomparison Project Phase 5 general circulation models (GCMs). A significant relationship exists between the climatological occurrences of MDs and the strength of the background upper (lower) tropospheric meridional (zonal) winds and tropospheric moisture in the core genesis region of MDs. Likewise, there is a strong relationship between the strength of the meridional tropospheric temperature gradient in the GCMs and the trajectories of MDs over land. While monsoon dynamics progressively weakens in the future, atmospheric moisture exhibits a strong increase, limiting the impact of changes in dynamics on the frequency of MDs. Moreover, the weakening of meridional tropospheric temperature gradient in the future is substantially weaker than its inherent underestimation in the GCMs. Our results also indicate that future increases in the extreme wet events are dominated by nondepression day occurrences, which may render the monsoon extremes less predictable in the future

Extreme hydrological changes in the southwestern US drive reductions in water supply to Southern California by mid century

The Southwestern United States has a greater vulnerability to climate change impacts on water security due to a reliance on snowmelt driven imported water. The State of California, which is the most populous and agriculturally productive in the United States, depends on an extensive artificial water storage and conveyance system primarily for irrigated agriculture, municipal and industrial supply and hydropower generation. Here we take an integrative high-resolution ensemble modeling approach to examine near term climate change impacts on all imported and local sources of water supply to Southern California. While annual precipitation is projected to remain the same or slightly increase, rising temperatures result in a shift towards more rainfall, reduced cold season snowpack and earlier snowmelt. Associated with these hydrological changes are substantial increases in the frequency and the intensity of both drier conditions and flooding events. The 50 year extreme daily maximum precipitation and runoff events are 1.5–6 times more likely to occur depending on the water supply basin. Simultaneously, a clear deficit in total annual runoff over mountainous snow generating regions like the Sierra Nevada is projected. On one hand, the greater probability of drought decreases imported water supply availability. On the other hand, earlier snowmelt and significantly stronger winter precipitation events pose increased flood risk requiring water releases from control reservoirs, which may potentially decrease water availability outside of the wet season. Lack of timely local water resource expansion coupled with projected climate changes and population increases may leave the area in extended periods of shortages

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Assessment of Hydroclimate Responses to Anthropogenic Forcing and Implications for Human Systems

Changes in the mean and extreme climate characteristics are undeniably evident in observational records. Over the United States, the mean temperature has approximately increased by 1oC since the late 19th century and an additional warming of up to 2.2oC is projected by the mid 21st century. Similarly, changes in the temperature and precipitation extremes are also visible through a decreasing trend in the number of rain days and an increasing trend in the frequency of droughts, heat waves and heavy downpours. Discernable evidence suggests that such changes in hydroclimate characteristic are impacting human systems such as energy, agriculture and critical infrastructure. Within this context, this research investigates the responses of regional hydroclimate over the United States to projected increases in radiative forcing in the near term future and its implications for the human systems. This investigation is divided in four parts. The first part quantifies potential changes in county-level residential space heating and cooling requirements as a result of projected changes in heating and cooling degree days. The second part investigates the characteristics of dry versus humid heatwaves and the associated thermodynamic changes in the present and warmer future climate. The third part studies changes in the spatial and temporal characteristics of precipitation events, including extent, intensity and frequency in response to increase in radiative forcing. The fourth part evaluates potential changes in the magnitude of probable maximum precipitation, which is used as a design criteria for critical infrastructure, in the warmer and moister future climate over a hydrological basin in the southeastern United States. Overall, this research should enable development of rigorous analytical frameworks for better planning to cope with the challenges posed by climate change

A numerical study of cropland-atmosphere feedbacks by incorporating a crop growth module in the WRF model

This study investigates cropland-atmosphere feedbacks in the Midwestern United States. Growing crops impact local climate during the growing season by influencing heat, moisture and momentum exchange between the land and the atmosphere. These changes in turn affect the crop growth, thus completing a feedback loop. A computationally efficient modeling tool has been specifically developed to study these feedbacks. A vegetation module derived from a crop growth model SUCROS has been incorporated in the Weather Research Forecasting (WRF) model. This coupled model has the capability to explore cropland-atmosphere feedbacks at a high spatial resolution at mesoscale. Results from soybean fields in Nebraska and Illinois show that the crop growth depends directly on temperature, incoming shortwave radiation and precipitation. As the crops grow, they affect energy partitioning between sensible and latent heat leading to a change in the cloud cover and consequently changing incoming shortwave radiation, air temperature and precipitation. An increase in cloud cover reduces incoming shortwave radiation and hence photosynthesis, exerting a negative feedback. However, an increase in precipitation reduces water stress and promotes growth, resulting in a positive feedback. The net impact on crop growth is a nonlinear combination of these feedbacks

Revisiting Recent U.S. Heat Waves in a Warmer and More Humid Climate

The frequency and intensity of heat waves in the United States is projected to increase in the 21st century. We investigate dry and humid heat waves in a pair of high‐resolution model simulations that constrain large‐scale atmospheric circulation, to isolate the thermodynamic impacts on characteristics of present and future heat waves over the United States. The two kinds of heat waves show differences in mean intensity, amplitude, duration, and frequency over the Southeast, Northeast, and Midwest, while their characteristics are largely similar in the drier central and western United States. In a warmer climate, relative humidity is projected to decrease during dry heat waves, whereas it remains unchanged during humid heat waves. However, the overall increase in daily maximum temperature intensifies the heat stress during future humid and dry heat waves across all regions. With large‐scale circulation constrained, these simulations emphasize the importance of thermodynamic drivers in determining future heat wave characteristics.ISSN:0094-8276ISSN:1944-800

Future Typical Meteorological Year (fTMY) US Weather Files for Building Simulation for every US County (West and Midwest)

As global emissions and temperatures continue to rise, global climate models offer projections as to how the climate will change in years to come. These model projections can be used for a variety of end-uses to better understand how current systems will be affected by the changing climate. While climate models predict every individual year, using a single year may not be representative as there may be outlier years. It can also be useful to represent a multi-year period with a single year of data. Both items are currently addressed when working with past weather data by a using Typical Meteorological Year (TMY)methodology. This methodology works by statistically selecting representative months from a number of years and appending these months to achieve a single representative year for a given period. In this analysis, the TMY methodology is used to develop Future Typical Meteorological Year (fTMY) using climate model projections. The resulting set of fTMY data is then formatted into EnergyPlus weather (epw) fi les that can be used for building simulation to estimate the impact of climate scenarios on the built environment. This dataset contains fTMY fi les for 3281 US Counties in the continental United States. The data for each county is derived from six different global climate models (GCMs) from the 6th Phase of Coupled Models Intercomparison Project CMIP6-ACCESSCM2, BCC-CSM2-MR, CNRM-ESM2-1, MPI-ESM1-2-HR, MRI-ESM2-0, NorESM2-MM. The six climate models were statistically downscaled for 1980–2014 in the historical period and 2015–2059 in the future period under the SSP585 scenario using the methodology described in Rastogi et al. (2022). Additionally, hourly data was derived from the daily downscaled output using the Mountain Microclimate Simulation Model (MTCLIM; Thornton and Running, 1999). The shared socioeconomic pathway (SSP) used for this analysis was SSP 5 and the representative concentration pathway (RCP) used was RCP 8.5. More information about SSP and RCP can be referred to O'Neill et al. (2020). More information about the six selected CMIP6 GCMs: ACCESS-CM2 - http://dx.doi.org/10.1071/ES19040 BCC-CSM2-MR - https://doi.org/10.5194/gmd-14-2977-2021 CNRM-ESM2-1- https://doi.org/10.1029/2019MS001791 MPI-ESM1-2-HR - https://doi.org/10.5194/gmd-12-3241-2019 MRI-ESM2-0 - https://doi.org/10.2151/jmsj.2019-051 NorESM2-MM - https://doi.org/10.5194/gmd-13-6165-2020 Additional references: O'Neill, B. C., Carter, T. R., Ebi, K. et al. (2020). Achievements and Needs for the Climate Change Scenario Framework. Nat. Clim. Chang. 10, 1074–1084 (2020). https://doi.org/10.1038/s41558-020-00952-0 Rastogi, D., Kao, S.-C., and Ashfaq, M. (2022). How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections? Earth's Future, 10, e2022EF002734. https://doi.org/10.1029/2022EF002734 Thornton, P. E. and Running, S. W. (1999). An Improved Algorithm for Estimating Incident Daily Solar Radiation from Measurements of Temperature, Humidity and Precipitation, Agricultural and Forest Meteorology, 93, 211-228

Shift in seasonal climate patterns likely to impact residential energy consumption in the United States

We develop a highly-resolved ensemble of climate simulations and empirical relationships between weather and household energy consumption to provide one of the most detailed estimates to date for potential climate-driven changes in the United States residential energy demand under the highest greenhouse gas emissions pathway. Our results indicate that more intense and prolonged warm conditions will drive an increase in electricity demand while a shorter and milder cold season will reduce natural gas demand by the mid 21st century. The environmental conditions that favor more cooling degree days in summer and reduced heating degree days in winter are driven by changes in daily maximum temperatures and daily minimum temperatures in the respective seasons. Our results also indicate that climate-driven change can potentially reverse impacts of a projected decrease in rural population on residential energy demand. These projected changes in climate-driven energy demand have implications for future energy planning and management

The role of humidity in determining future electricity demand in the southeastern United States

Co-occurrence of high relative humidity levels and high temperatures can increase human discomfort, thereby affecting electricity requirements for space cooling. While relative humidity is generally projected to decrease over land in a warming climate, the combined impact of warming and changes in humidity on heat stress, and thus electricity demand, are less clear. To evaluate the role of relative humidity in determining future electricity demand, we first develop predictive models based, separately, on temperature (T) and a heat stress index (apparent temperature (AT)) at an hourly scale using meteorological reanalysis data and electricity load from the United States Energy Information Administration over the four electricity regions in the southeastern United States. The AT model performs better than the T model in the historical period. We then apply the predictive models to a set of high-resolution climate projections to understand the role of relative humidity in determining the electricity demand in a warmer climate. Due to the nonlinear behavior of heat stress with warming, future electricity demand is substantially larger when estimated from AT than from T. The increase in demand projected by AT ranges between 16%–29%, 20%–33%, 14%–32% and 13%–26% and that by T model ranges between 12%–19%, 15%–19%, 14%–22% and 12%–20% over Southeast, Florida, Carolina, and Tennessee respectively. This amplification of electricity demand by humidity is strongest for the highest temperature quantiles, but also occurs at moderate future temperatures that coincide with elevated relative humidity episodes, emphasizing the importance of considering humidity in future heat stress and electricity demand assessments

Future Typical Meteorological Year (fTMY) US Weather Files for Building Simulation for every US County (East and South)

As global emissions and temperatures continue to rise, global climate models offer projections as to how the climate will change in years to come. These model projections can be used for a variety of end-uses to better understand how current systems will be affected by the changing climate. While climate models predict every individual year, using a single year may not be representative as there may be outlier years. It can also be useful to represent a multi-year period with a single year of data. Both items are currently addressed when working with past weather data by a using Typical Meteorological Year (TMY)methodology. This methodology works by statistically selecting representative months from a number of years and appending these months to achieve a single representative year for a given period. In this analysis, the TMY methodology is used to develop Future Typical Meteorological Year (fTMY) using climate model projections. The resulting set of fTMY data is then formatted into EnergyPlus weather (epw) fi les that can be used for building simulation to estimate the impact of climate scenarios on the built environment. This dataset contains fTMY fi les for 3281 US Counties in the continental United States. The data for each county is derived from six different global climate models (GCMs) from the 6th Phase of Coupled Models Intercomparison Project CMIP6-ACCESSCM2, BCC-CSM2-MR, CNRM-ESM2-1, MPI-ESM1-2-HR, MRI-ESM2-0, NorESM2-MM. The six climate models were statistically downscaled for 1980–2014 in the historical period and 2015–2059 in the future period under the SSP585 scenario using the methodology described in Rastogi et al. (2022). Additionally, hourly data was derived from the daily downscaled output using the Mountain Microclimate Simulation Model (MTCLIM; Thornton and Running, 1999). The shared socioeconomic pathway (SSP) used for this analysis was SSP 5 and the representative concentration pathway (RCP) used was RCP 8.5. More information about SSP and RCP can be referred to O'Neill et al. (2020). More information about the six selected CMIP6 GCMs: ACCESS-CM2 - http://dx.doi.org/10.1071/ES19040 BCC-CSM2-MR - https://doi.org/10.5194/gmd-14-2977-2021 CNRM-ESM2-1- https://doi.org/10.1029/2019MS001791 MPI-ESM1-2-HR - https://doi.org/10.5194/gmd-12-3241-2019 MRI-ESM2-0 - https://doi.org/10.2151/jmsj.2019-051 NorESM2-MM - https://doi.org/10.5194/gmd-13-6165-2020 Additional references: O'Neill, B. C., Carter, T. R., Ebi, K. et al. (2020). Achievements and Needs for the Climate Change Scenario Framework. Nat. Clim. Chang. 10, 1074–1084 (2020). https://doi.org/10.1038/s41558-020-00952-0 Rastogi, D., Kao, S.-C., and Ashfaq, M. (2022). How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections? Earth's Future, 10, e2022EF002734. https://doi.org/10.1029/2022EF002734 Thornton, P. E. and Running, S. W. (1999). An Improved Algorithm for Estimating Incident Daily Solar Radiation from Measurements of Temperature, Humidity and Precipitation, Agricultural and Forest Meteorology, 93, 211-228