Abstract
This study explores the population exposure to an increasing number of hydroclimatic extreme events owing to the warming climate. It is well agreed that the extreme events are increasing in terms of frequency as well as intensity due to climate change and that the exposure to compound extreme events (concurrent occurrence of two or more extreme phenomena) affects population, ecosystems, and a variety of socioeconomic aspects more adversely. Specifically, the compound precipitation–temperature extremes (hot-dry and hot-wet) are considered, and the entire Indian mainland is regarded as the study region that spans over a wide variety of climatic regimes and wide variation of population density. The developed copula-based statistical method evaluates the change in population exposure to the compound extremes across the past (1981–2020) and future (near future: 2021–60 and far future: 2061–2100) due to climate change. The results indicate an increase of more than 10 million person-year exposure from the compound extremes across many regions of the country, considering both near and far future periods. Densely populated regions have experienced more significant changes in hot-wet extremes as compared with the hot-dry extremes in the past, and the same is projected to continue in the future. The increase is as much as sixfold in many parts of the country, including the Indo-Gangetic Plain and southernmost coastal regions, identified as the future hotspots with the maximum increase in exposure under all the projected warming and population scenarios. The study helps to identify the regions that may need greater attention based on the risks of population exposure to compound extremes in a warmer future.
Significance Statement
How is the growing population being affected now, and in the future, how will it be affected due to climate change induced compound extreme events? This study explores this societal consequence in terms of population exposure for the most populous country, India. An increase of more than 10 million person-year exposure from the precipitation–temperature compound extremes across many regions is indicated. Densely populated regions are expected to experience enhanced population exposure to hot-wet extremes as compared with the hot-dry extremes. Furthermore, the maximum increase in population exposure to compound extremes is expected across the Indo-Gangetic Plain and southern coastal regions of India. The outcome of the study will be helpful for adopting socioeconomic decisions toward the welfare of society.
Abstract
This study explores the population exposure to an increasing number of hydroclimatic extreme events owing to the warming climate. It is well agreed that the extreme events are increasing in terms of frequency as well as intensity due to climate change and that the exposure to compound extreme events (concurrent occurrence of two or more extreme phenomena) affects population, ecosystems, and a variety of socioeconomic aspects more adversely. Specifically, the compound precipitation–temperature extremes (hot-dry and hot-wet) are considered, and the entire Indian mainland is regarded as the study region that spans over a wide variety of climatic regimes and wide variation of population density. The developed copula-based statistical method evaluates the change in population exposure to the compound extremes across the past (1981–2020) and future (near future: 2021–60 and far future: 2061–2100) due to climate change. The results indicate an increase of more than 10 million person-year exposure from the compound extremes across many regions of the country, considering both near and far future periods. Densely populated regions have experienced more significant changes in hot-wet extremes as compared with the hot-dry extremes in the past, and the same is projected to continue in the future. The increase is as much as sixfold in many parts of the country, including the Indo-Gangetic Plain and southernmost coastal regions, identified as the future hotspots with the maximum increase in exposure under all the projected warming and population scenarios. The study helps to identify the regions that may need greater attention based on the risks of population exposure to compound extremes in a warmer future.
Significance Statement
How is the growing population being affected now, and in the future, how will it be affected due to climate change induced compound extreme events? This study explores this societal consequence in terms of population exposure for the most populous country, India. An increase of more than 10 million person-year exposure from the precipitation–temperature compound extremes across many regions is indicated. Densely populated regions are expected to experience enhanced population exposure to hot-wet extremes as compared with the hot-dry extremes. Furthermore, the maximum increase in population exposure to compound extremes is expected across the Indo-Gangetic Plain and southern coastal regions of India. The outcome of the study will be helpful for adopting socioeconomic decisions toward the welfare of society.
Abstract
There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally- and temporally-averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative-convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (for example, 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter ‘W’, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not).
Abstract
There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally- and temporally-averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative-convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (for example, 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter ‘W’, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not).
Abstract
Accurate streamflow simulations rely on good estimates of the catchment-scale soil moisture distribution. Here, we evaluated the potential of Sentinel-1 backscatter data assimilation (DA) to improve soil moisture and streamflow estimates. Our DA system consisted of the Noah-MP land surface model coupled to the HyMAP river routing model and the water cloud model as a backscatter observation operator. The DA system was set up at 0.01° resolution for two contrasting catchments in Belgium: (i) the Demer catchment dominated by agriculture and (ii) the Ourthe catchment dominated by mixed forests. We present the results of two experiments with an ensemble Kalman filter updating either soil moisture only or soil moisture and leaf area index (LAI). The DA experiments covered the period from January 2015 through August 2021 and were evaluated with independent rainfall error estimates based on station data, LAI from optical remote sensing, soil moisture retrievals from passive microwave observations, and streamflow measurements. Our results indicate that the assimilation of Sentinel-1 backscatter observations can partly correct errors in surface soil moisture due to rainfall errors and overall improve surface soil moisture estimates. However, updating soil moisture and LAI simultaneously did not bring any benefit over updating soil moisture only. Our results further indicate that streamflow estimates can be improved through Sentinel-1 DA in a catchment with strong soil moisture–runoff coupling, as observed for the Ourthe catchment, suggesting that there is potential for Sentinel-1 DA even for forested catchments.
Significance Statement
The purpose of this study is to improve streamflow estimation by integrating soil moisture information from satellite observations into a hydrological modeling framework. This is important preparatory work for operational centers that are responsible for producing the most accurate flood forecasts for the society. Our results provide new insights into how and where streamflow forecasting could benefit from high-spatial-resolution Sentinel-1 radar backscatter observations.
Abstract
Accurate streamflow simulations rely on good estimates of the catchment-scale soil moisture distribution. Here, we evaluated the potential of Sentinel-1 backscatter data assimilation (DA) to improve soil moisture and streamflow estimates. Our DA system consisted of the Noah-MP land surface model coupled to the HyMAP river routing model and the water cloud model as a backscatter observation operator. The DA system was set up at 0.01° resolution for two contrasting catchments in Belgium: (i) the Demer catchment dominated by agriculture and (ii) the Ourthe catchment dominated by mixed forests. We present the results of two experiments with an ensemble Kalman filter updating either soil moisture only or soil moisture and leaf area index (LAI). The DA experiments covered the period from January 2015 through August 2021 and were evaluated with independent rainfall error estimates based on station data, LAI from optical remote sensing, soil moisture retrievals from passive microwave observations, and streamflow measurements. Our results indicate that the assimilation of Sentinel-1 backscatter observations can partly correct errors in surface soil moisture due to rainfall errors and overall improve surface soil moisture estimates. However, updating soil moisture and LAI simultaneously did not bring any benefit over updating soil moisture only. Our results further indicate that streamflow estimates can be improved through Sentinel-1 DA in a catchment with strong soil moisture–runoff coupling, as observed for the Ourthe catchment, suggesting that there is potential for Sentinel-1 DA even for forested catchments.
Significance Statement
The purpose of this study is to improve streamflow estimation by integrating soil moisture information from satellite observations into a hydrological modeling framework. This is important preparatory work for operational centers that are responsible for producing the most accurate flood forecasts for the society. Our results provide new insights into how and where streamflow forecasting could benefit from high-spatial-resolution Sentinel-1 radar backscatter observations.
Abstract
Surface waves grow through a mechanism in which atmospheric pressure is offset in phase from the wavy surface. A pattern of low atmospheric pressure over upward wave orbital motions (leeward side) and high pressure over downward wave orbital motions (windward side) travels with the water wave, leading to a pumping of kinetic energy from the atmospheric boundary layer into the waves. This pressure pattern persists above the air/water interface, modifying the turbulent kinetic energy in the atmospheric wave-affected boundary layer. Here, we present field measurements of wave-coherent atmospheric pressure and velocity to elucidate the transfer of energy from the atmospheric turbulence budget into waves through wave-coherent atmospheric pressure work. Measurements show that the phase between wave-coherent pressure and velocity is shifted slightly above 90° when wind speed exceeds the wave phase speed, allowing for a downwards energy flux via pressure work. Although previous studies have reported wave-coherent pressure, to the authors’ knowledge, these are the first reported field measurements of wave-coherent pressure work. Measured pressure work cospectra are consistent with an existing model for atmospheric pressure work. The implications for these measurements and their importance to the turbulent kinetic energy budget are discussed.
Abstract
Surface waves grow through a mechanism in which atmospheric pressure is offset in phase from the wavy surface. A pattern of low atmospheric pressure over upward wave orbital motions (leeward side) and high pressure over downward wave orbital motions (windward side) travels with the water wave, leading to a pumping of kinetic energy from the atmospheric boundary layer into the waves. This pressure pattern persists above the air/water interface, modifying the turbulent kinetic energy in the atmospheric wave-affected boundary layer. Here, we present field measurements of wave-coherent atmospheric pressure and velocity to elucidate the transfer of energy from the atmospheric turbulence budget into waves through wave-coherent atmospheric pressure work. Measurements show that the phase between wave-coherent pressure and velocity is shifted slightly above 90° when wind speed exceeds the wave phase speed, allowing for a downwards energy flux via pressure work. Although previous studies have reported wave-coherent pressure, to the authors’ knowledge, these are the first reported field measurements of wave-coherent pressure work. Measured pressure work cospectra are consistent with an existing model for atmospheric pressure work. The implications for these measurements and their importance to the turbulent kinetic energy budget are discussed.
Abstract
National Weather Service (NWS) forecasters have many roles and responsibilities, including communication with core partners throughout the forecast and warning process to ensure that the information they are providing is relevant, understandable, and actionable. Although the NWS communicates to many groups, members of the emergency management community are among the most critical partners. However, little is known about the diverse population of emergency managers (EMs) and how they receive, process, and use forecast information. The Extreme Weather and Emergency Management Survey (WxEM) aims to fill this knowledge gap by 1) building a nationwide panel of EMs and 2) fielding routine surveys that include questions of relevance to NWS operations. The panel was built by creating a database with contact information from more than 4000 EMs across the country. An enrollment survey was sent to the list, and over 700 EMs agreed to participate in the project. Following enrollment, WxEM panelists receive surveys three–four times per year that address how EMs use NWS forecast information. These surveys cover a variety of subjects, with the goal of working with other researchers to develop surveys that address their research needs. By collaborating with other research groups to design short, focused surveys, the WxEM project will reduce the research burden on EMs and, at the same time, increase the quality and comparability of research data in the weather enterprise. The results will be shared with the NWS and the research community, and all data gathered from these surveys will be publicly available.
Significance Statement
The Extreme Weather and Emergency Management Survey aims to better understand how emergency managers use National Weather Service (NWS) forecast information via a series of surveys regularly distributed to a panel of emergency managers across the country. By collaborating with other researchers, these surveys will cover broad topics and should limit the number of participation requests sent to emergency managers. Results will be distributed to participants, researchers, and NWS forecasters. All data will be publicly available.
Abstract
National Weather Service (NWS) forecasters have many roles and responsibilities, including communication with core partners throughout the forecast and warning process to ensure that the information they are providing is relevant, understandable, and actionable. Although the NWS communicates to many groups, members of the emergency management community are among the most critical partners. However, little is known about the diverse population of emergency managers (EMs) and how they receive, process, and use forecast information. The Extreme Weather and Emergency Management Survey (WxEM) aims to fill this knowledge gap by 1) building a nationwide panel of EMs and 2) fielding routine surveys that include questions of relevance to NWS operations. The panel was built by creating a database with contact information from more than 4000 EMs across the country. An enrollment survey was sent to the list, and over 700 EMs agreed to participate in the project. Following enrollment, WxEM panelists receive surveys three–four times per year that address how EMs use NWS forecast information. These surveys cover a variety of subjects, with the goal of working with other researchers to develop surveys that address their research needs. By collaborating with other research groups to design short, focused surveys, the WxEM project will reduce the research burden on EMs and, at the same time, increase the quality and comparability of research data in the weather enterprise. The results will be shared with the NWS and the research community, and all data gathered from these surveys will be publicly available.
Significance Statement
The Extreme Weather and Emergency Management Survey aims to better understand how emergency managers use National Weather Service (NWS) forecast information via a series of surveys regularly distributed to a panel of emergency managers across the country. By collaborating with other researchers, these surveys will cover broad topics and should limit the number of participation requests sent to emergency managers. Results will be distributed to participants, researchers, and NWS forecasters. All data will be publicly available.
Abstract
Elevated spring and summer rainfall in the U.S. Midwest is often associated with a strong Great Plains low-level jet (GPLLJ), which transports moist air northward to the region from the Gulf of Mexico. While the intensity of hourly precipitation extremes depends on local moisture availability and vertical velocity, sustained moisture convergence on longer time scales depends on horizontal moisture advection from remote sources. Therefore, the magnitude of moisture convergence in the Midwest depends in part on the humidity in these moisture source regions. Past work has identified the time-mean spatial distribution of moisture sources for the Midwest and studied how this pattern changes in years with anomalous rainfall. Here, using reanalysis products and an Eulerian moisture tracking model, we seek to increase physical understanding of this moisture source variability by linking it to the GPLLJ, which has been studied extensively. We find that on interannual time scales, an anomalously strong GPLLJ is associated with a shift in the distribution of moisture sources from land to ocean, with most of the anomalous moisture transported to—and converged in—the Midwest originating from the Atlantic Ocean. This effect is more pronounced on synoptic time scales, when almost all anomalous moisture transported to the region originates over the ocean. We also show that the observed positive trend in oceanic moisture contribution to the Midwest from 1979 to 2020 is consistent with a strengthening of the GPLLJ over the same period. We conclude by outlining how projected changes in a region’s upstream moisture sources may be useful for understanding changes in local precipitation variability.
Significance Statement
In this work, we study how the origin of moisture that forms precipitation in the U.S. Midwest covaries with large-scale atmospheric circulation. Our results show that an intensification of the mean winds tends to increase the proportion of total rainfall that originates from the ocean. This analysis may help to constrain future projections of rainfall extremes in the central United States, as projected changes in humidity over the ocean are typically more robust and better understood than those over land.
Abstract
Elevated spring and summer rainfall in the U.S. Midwest is often associated with a strong Great Plains low-level jet (GPLLJ), which transports moist air northward to the region from the Gulf of Mexico. While the intensity of hourly precipitation extremes depends on local moisture availability and vertical velocity, sustained moisture convergence on longer time scales depends on horizontal moisture advection from remote sources. Therefore, the magnitude of moisture convergence in the Midwest depends in part on the humidity in these moisture source regions. Past work has identified the time-mean spatial distribution of moisture sources for the Midwest and studied how this pattern changes in years with anomalous rainfall. Here, using reanalysis products and an Eulerian moisture tracking model, we seek to increase physical understanding of this moisture source variability by linking it to the GPLLJ, which has been studied extensively. We find that on interannual time scales, an anomalously strong GPLLJ is associated with a shift in the distribution of moisture sources from land to ocean, with most of the anomalous moisture transported to—and converged in—the Midwest originating from the Atlantic Ocean. This effect is more pronounced on synoptic time scales, when almost all anomalous moisture transported to the region originates over the ocean. We also show that the observed positive trend in oceanic moisture contribution to the Midwest from 1979 to 2020 is consistent with a strengthening of the GPLLJ over the same period. We conclude by outlining how projected changes in a region’s upstream moisture sources may be useful for understanding changes in local precipitation variability.
Significance Statement
In this work, we study how the origin of moisture that forms precipitation in the U.S. Midwest covaries with large-scale atmospheric circulation. Our results show that an intensification of the mean winds tends to increase the proportion of total rainfall that originates from the ocean. This analysis may help to constrain future projections of rainfall extremes in the central United States, as projected changes in humidity over the ocean are typically more robust and better understood than those over land.
Abstract
We present an asymptotic approach for the systematic investigation of the effect of gravity waves (GWs) on ice clouds formed through homogeneous nucleation. In particular, we consider high- and midfrequency GWs in the tropopause region driving the formation of ice clouds, modeled with a double-moment bulk ice microphysics scheme. The asymptotic approach allows for identifying reduced equations for self-consistent description of the ice dynamics forced by GWs including the effects of diffusional growth and nucleation of ice crystals. Further, corresponding analytical solutions for a monochromatic GW are derived under a single-parcel approximation. The results provide a simple expression for the nucleated number of ice crystals in a nucleation event. It is demonstrated that the asymptotic solutions capture the dynamics of the full ice model and accurately predict the nucleated ice crystal number. The present approach is extended to allow for superposition of GWs, as well as for variable ice crystal mean mass in the deposition. Implications of the results for an improved representation of GW variability in cirrus parameterizations are discussed.
Abstract
We present an asymptotic approach for the systematic investigation of the effect of gravity waves (GWs) on ice clouds formed through homogeneous nucleation. In particular, we consider high- and midfrequency GWs in the tropopause region driving the formation of ice clouds, modeled with a double-moment bulk ice microphysics scheme. The asymptotic approach allows for identifying reduced equations for self-consistent description of the ice dynamics forced by GWs including the effects of diffusional growth and nucleation of ice crystals. Further, corresponding analytical solutions for a monochromatic GW are derived under a single-parcel approximation. The results provide a simple expression for the nucleated number of ice crystals in a nucleation event. It is demonstrated that the asymptotic solutions capture the dynamics of the full ice model and accurately predict the nucleated ice crystal number. The present approach is extended to allow for superposition of GWs, as well as for variable ice crystal mean mass in the deposition. Implications of the results for an improved representation of GW variability in cirrus parameterizations are discussed.
Abstract
The contributions of local and remote forcings to the interannual sea level anomalies (SLAs) along the U.S. East Coast (USEC) during the satellite altimetry era from 1993 to 2019 are quantified with analytical models assisted by statistical methods. The local forcings from alongshore wind stress, sea level pressure via inverted barometer (IB) effect, and river discharges together explain 47%, 60.4%, and 66.8% of coastal sea level variance in the South Atlantic Bight (SAB), Mid-Atlantic Bight (MAB), and Gulf of Maine (GOM), respectively, with river discharges having the minimum contribution. Over a longer period of 1960–2019, the contribution of local forcings reduces significantly, with the IB effect having the minimum contribution. The remote forcings associated with open-ocean signals from the east and from the northern boundary at the Scotian coast together with the Gulf Stream (GS) variability explain 45.7%, 28.5%, and 37.7% of coastal sea level variance in the SAB, MAB, and GOM, respectively, playing a role comparable to that of local forcings in the SAB. The open-ocean sea level signals from 35° to 38°N strongly influence coastal SLAs in the SAB. The coastal SLAs in the SAB are also affected by the upstream GS strength (28°–36°N) and basin-scale wind stress curl anomaly, which is linked to the meridional shift in the downstream GS (74°–68°W). Remote forcings from the subpolar North Atlantic and wind stress curl from the Grand Banks to the Scotian coast influence coastal SLAs in the GOM and MAB via the northern boundary of the USEC at the Scotian coast.
Abstract
The contributions of local and remote forcings to the interannual sea level anomalies (SLAs) along the U.S. East Coast (USEC) during the satellite altimetry era from 1993 to 2019 are quantified with analytical models assisted by statistical methods. The local forcings from alongshore wind stress, sea level pressure via inverted barometer (IB) effect, and river discharges together explain 47%, 60.4%, and 66.8% of coastal sea level variance in the South Atlantic Bight (SAB), Mid-Atlantic Bight (MAB), and Gulf of Maine (GOM), respectively, with river discharges having the minimum contribution. Over a longer period of 1960–2019, the contribution of local forcings reduces significantly, with the IB effect having the minimum contribution. The remote forcings associated with open-ocean signals from the east and from the northern boundary at the Scotian coast together with the Gulf Stream (GS) variability explain 45.7%, 28.5%, and 37.7% of coastal sea level variance in the SAB, MAB, and GOM, respectively, playing a role comparable to that of local forcings in the SAB. The open-ocean sea level signals from 35° to 38°N strongly influence coastal SLAs in the SAB. The coastal SLAs in the SAB are also affected by the upstream GS strength (28°–36°N) and basin-scale wind stress curl anomaly, which is linked to the meridional shift in the downstream GS (74°–68°W). Remote forcings from the subpolar North Atlantic and wind stress curl from the Grand Banks to the Scotian coast influence coastal SLAs in the GOM and MAB via the northern boundary of the USEC at the Scotian coast.
Abstract
Intraseasonal and diurnal variations are two basic periodic oscillations in global/regional climate and weather. To investigate their joint impacts over East Asia, this paper categorizes the boreal summer intraseasonal oscillations (ISOs) in 1998–2019 into two groups with different diurnal cycles. It is shown that the active ISOs with large diurnal cycles feature a northwestward-moving anomalous anticyclone with strong southerlies at the western flank. These ISOs have in-phase patterns of geopotential height anomaly between low and midlatitudes over East Asia, associated with the simultaneous expansions of the western Pacific subtropical high (WPSH) and South Asian high (SAH). They couple with the anomalous ABL heating by daytime solar radiation over East Asia, which acts to enhance monsoon southerlies at midnight. The nocturnally strengthened southerlies facilitate dynamic lifting, moisture transport, and convective instability for producing midnight to morning rainfall at their northern terminus, thereby yielding a remarkable northward propagation of the monsoon rain belt. In contrast, the other ISOs with small diurnal cycles are related to a westward-moving anomalous anticyclone, while the WPSH and SAH have relatively small expansions and the westerly trough is active at middle latitudes. They lead to the dipole patterns of geopotential height anomaly and weak ABL heating over East Asia. The daily-mean southerlies and moisture conditions as well as their nocturnal enhancements are relatively weak, and thus, the northward shift of the monsoon rain belt is less pronounced. These results highlight that the large-scale conditions of ISOs can be distinguished by their different couplings with regional-scale diurnal forcings, which help the understanding and prediction of multiscale rainfall activities.
Abstract
Intraseasonal and diurnal variations are two basic periodic oscillations in global/regional climate and weather. To investigate their joint impacts over East Asia, this paper categorizes the boreal summer intraseasonal oscillations (ISOs) in 1998–2019 into two groups with different diurnal cycles. It is shown that the active ISOs with large diurnal cycles feature a northwestward-moving anomalous anticyclone with strong southerlies at the western flank. These ISOs have in-phase patterns of geopotential height anomaly between low and midlatitudes over East Asia, associated with the simultaneous expansions of the western Pacific subtropical high (WPSH) and South Asian high (SAH). They couple with the anomalous ABL heating by daytime solar radiation over East Asia, which acts to enhance monsoon southerlies at midnight. The nocturnally strengthened southerlies facilitate dynamic lifting, moisture transport, and convective instability for producing midnight to morning rainfall at their northern terminus, thereby yielding a remarkable northward propagation of the monsoon rain belt. In contrast, the other ISOs with small diurnal cycles are related to a westward-moving anomalous anticyclone, while the WPSH and SAH have relatively small expansions and the westerly trough is active at middle latitudes. They lead to the dipole patterns of geopotential height anomaly and weak ABL heating over East Asia. The daily-mean southerlies and moisture conditions as well as their nocturnal enhancements are relatively weak, and thus, the northward shift of the monsoon rain belt is less pronounced. These results highlight that the large-scale conditions of ISOs can be distinguished by their different couplings with regional-scale diurnal forcings, which help the understanding and prediction of multiscale rainfall activities.
