Identification of key parameters producing rainfall

o"kkZ ds eq[; izkpyksa dk irk yxkus ds fy, bl 'kks/k i= ls 'kks/kdrkZvksa us m".kdfVca/kh; o"kkZ ekiu fe’ku ¼Vh- vkj- ,e- ,e-½ mixzg vk¡dM+k vk/kkj dh tk¡p dh gSA bl rF; dks le>us ds mijkUr fd c<+us okys ok;q iklZy ds }kjk ikuh ds ok"ihdj.k] ok"i ds la?kuu vkSj m"ek ÅtkZ ds laogu ls es?k cursa gS vkSj o"kkZ gksrh gSA 'kks/kdrkZvksa us ok;qeaMy dh fofHkUu Å¡pkbZ;ksa ij o"kkZ izfØ;k ds eq[; lg;ksfx;ksa ds :i esa es?k nzo ty ¼lh-,y-MCY;w-½] o"kZ.k ty ¼ih-MCY;w-½ rFkk xqIr m"ek ¼,y-,p-½ ds ckjs esa tkudkjh izkIr djuh vkjaHk dj nh gSSA bu vk¡dM+ksa dks cgq lekJ;.k fun’kZ esa Mkyk x;k gSA ;g ik;k x;k gSS fd o"kkZ vkSj bu izkpyksa esa egRoiw.kZ lglaca/k gSA blls LFkkfir gq, dk;kZRed laca/kksa ls fdlh Hkh le; o"kkZ dk vkdyu fd;k tk ldrk gS c’krZs dkWyeuj lh-,y-MCY;w-] ih-MCY;w- vkSj ,y-,p- eku miyC?k gksaA ,d ;k nks ds LFkku ij bu lHkh rhuksa izkpyksa dks cgq lekJ;.k fun’kZ esa 'kkfey djus ds QyLo:i o"kkZ dk csgrj iwokZuqeku yxk;k tk ldk gSA lh- ,y- MCY;w-] ,y- ,p- vkSj ih- MCY;w- ds chp egRoiw.kZ lglaca/k gSaA In search of the key parameters causing rainfall, the authors have explored Tropical Rainfall Measuring Mission (TRMM) satellite data base. By realizing the fact that evaporation of water, condensation of vapour and transport of heat energy by a rising air parcel are all about formation of cloud and rain, the authors have started their quest considering cloud liquid water (CLW), precipitation water (PW) and latent heat (LH) at different altitudes of the atmosphere as major contributors to rainfall mechanism. These data have been fitted to multiple regressions. It is found that significant correlations exist between rainfall and these parameters. The functional relationships so established are able to estimate surface rainfall at any instant, provided columnar CLW, PW and LH values are available. Inclusion of all the three parameters in multiple regression leads to better predictability of rainfall, instead of one or two. Significant correlations exist between CLW, LH and PW.

How weather events modify aerosol particle size distributions in the Amazon boundary layer

This study evaluates the effect of weather events on the aerosol particle size distribution (PSD) at the Amazon Tall Tower Observatory (ATTO). This research combines in situ measurements of PSD and remote sensing data of lightning density, brightness temperature, cloud top height, cloud liquid water, and rain rate and vertical velocity. Measurements were obtained by scanning mobility particle sizers (SMPSs), the new generation of GOES satellites (GOES-16), the SIPAM S-band radar and the LAP 3000 radar wind profiler recently installed at the ATTO-Campina site. The combined data allow exploring changes in PSD due to different meteorological processes. The average diurnal cycle shows a higher abundance of ultrafine particles (NUFP) in the early morning, which is coupled with relatively lower concentrations in Aitken (NAIT) and accumulation (NACC) mode particles. From the early morning to the middle of the afternoon, an inverse behavior is observed, where NUFP decreases and NAIT and NACC increase, reflecting a typical particle growth process. Composite figures show an increase of NUFP before, during and after lightning was detected by the satellite above ATTO. These findings strongly indicate a close relationship between vertical transport and deep convective clouds. Lightning density is connected to a large increase in NUFP, beginning approximately 100 min before the maximum lightning density and reaching peak values around 200 min later. In addition, the removal of NACC by convective transport was found. Both the increase in NUFP and the decrease in NACC appear in parallel with the increasing intensity of lightning activity. The NUFP increases exponentially with the thunderstorm intensity. In contrast, NAIT and NACC show a different behavior, decreasing from approximately 100 min before the maximum lightning activity and reaching a minimum at the time of maximum lightning activity. The effect of cloud top height, cloud liquid water and rain rate shows the same behavior, but with different patterns between seasons. The convective processes do not occur continually but are probably modulated by gravity waves in the range of 1 to 5 h, creating a complex mechanism of interaction with a succession of updrafts and downdrafts, clouds, and clear-sky situations. The radar wind profiler measured the vertical distribution of the vertical velocity. These profiles show that downdrafts are mainly located below 10 km, while aircraft observations during the ACRIDICON–CHUVA campaign had shown maximum concentrations of ultrafine particles mainly above 10 km. Our study opens new scientific questions to be evaluated in order to understand the intricate physical and chemical mechanisms involved in the production of new particles in Amazonia.

Quantitative Investigation of Radiometric Interactions between Snowfall, Snow Cover, and Cloud Liquid Water over Land

Falling snow alters its own microwave signatures when it begins to accumulate on the ground, making retrieval of snowfall challenging. This paper investigates the effects of snow-cover depth and cloud liquid water content on microwave signatures of terrestrial snowfall using reanalysis data and multi-annual observations by the Global Precipitation Measurement (GPM) core satellite with particular emphasis on the 89 and 166 GHz channels. It is found that over shallow snow cover (snow water equivalent (SWE) ≤100kg m−2) and low values of cloud liquid water path (LWP 100–150 g m−2), the scattering of light snowfall (intensities ≤0.5mm h−1) is detectable only at frequency 166 GHz, while for higher snowfall rates, the signal can also be detected at 89 GHz. However, when SWE exceeds 200 kg m−2 and the LWP is greater than 100–150 g m−2, the emission from the increased liquid water content in snowing clouds becomes the only surrogate microwave signal of snowfall that is stronger at frequency 89 than 166 GHz. The results also reveal that over high latitudes above 60°N where the SWE is greater than 200 kg m−2 and LWP is lower than 100–150 g m−2, the snowfall microwave signal could not be detected with GPM without considering a priori data about SWE and LWP. Our findings provide quantitative insights for improving retrieval of snowfall in particular over snow-covered terrain.

Quantitative Investigation of Radiometric Interactions between Snowfall, Snow Cover, and Cloud Liquid Water Over Land

Falling snow alters its own microwave signatures when it begins to accumulate on the ground making retrieval of precipitation challenging. This paper investigates the effects of snow-cover depth and cloud liquid water content on microwave signatures of terrestrial snowfall using reanalysis data and multi-annual measurements by the Global Precipitation Measurement (GPM) core satellite with particular emphasis on the 89 and 166 GHz channels. It is found that over snow cover shallower than 10 cm and low values of cloud liquid water path (LWP &le;125gm&minus;2), the scattering of light snowfall (&amp;lt;0.5mmh&minus;1) is detectable only at frequency 166 GHz while for higher intensities the signal can be also detected at 89 GHz. However, when snow depth exceeds &sim;20 cm and the LWP is greater than &sim;125gm&minus;2 , the emission from the increased liquid water content in snowing clouds becomes the only surrogate microwave signal of snowfall that is stronger at frequency 89 GHz than 166 GHz. The results also reveal that over high latitudes above 60∘ N where the snow cover is thicker than 20 cm and LWP is lower than 125 gm&minus;2 the microwave snowfall signal could not be detected with GPM. Our results provide quantitative insights for improving retrieval of snowfall in particular over snow-covered terrain.

How weather events modify aerosol particle size distributions in the Amazon boundary layer

This study evaluates the effect of weather events on the aerosol particle size distribution (PSD) at the Amazon Tall Tower Observatory (ATTO). This research combines in-situ measurements of PSD and remote sensing data of lightning density, brightness temperature, cloud top height, cloud liquid water, and rain rate and vertical velocity. Measurements were obtained by a scanning mobility particle sizers (SMPS), the new generation of GOES satellites (GOES-16), the SIPAM S-band radar, and the LAP 3000 radar wind profiler recently installed at the ATTO-Campina site. The combined data allow exploring changes in PSD due to different meteorological processes. The average diurnal cycle shows a higher abundance of ultrafine particles (NUFP) in the early morning, which is coupled with lower concentrations in Aitken (NAIT) and accumulation (NACC) mode particles. From the early morning to the middle of the afternoon, an inverse behavior is observed, where NUFP decreases and NAIT and NACC increase, reflecting a typical particle growth process. Composite figures show an increase of NUFP before, during, and after lightning was detected by the satellite above ATTO. These findings strongly indicate a close relationship between vertical transport and deep convective clouds. Lightning density is connected with a large increase in NUFP, beginning approximately 100 minutes before the maximum lightning density and reaching peak values around 200 minutes later. In addition, the removal of NACC by convective transport was found. Both the increase in NUFP and the decrease in NACC appear in parallel with the increasing intensity of lightning activity. The NUFP increases exponentially with the thunderstorm intensity. In contrast, NAIT and NACC show a different behavior, decreasing from approximately 100 minutes before the maximum lightning activity and reaching a minimum at the time of maximum lightning activity. The effect of cloud top height, cloud liquid water, and rain rate shows the same behavior, but with different patterns among seasons. The convective processes do not occur continually but are modulated by gravity waves in the range of 1 to 5 hours, creating a complex mechanism of interaction with a succession of updrafts and downdrafts, clouds and clear sky situations. The radar wind profiler measured the vertical distribution of the vertical velocity. These profiles show that downdrafts are mainly located below 10 km, while aircraft observations during the ACRIDICON-CHUVA campaign had shown maximum concentrations of ultrafine particles mainly above 10 km. Our study opens new scientific questions to be evaluated in order to understand the intricate physical and chemical mechanisms involved in the production of new particles in Amazonia.

Cloud Assumption of Precipitation Retrieval Algorithms for the Dual-Frequency Precipitation Radar

An assumption related to clouds is one of uncertain factors in precipitation retrievals by the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory. While an attenuation due to cloud ice is negligibly small for Ku and Ka bands, attenuation by cloud liquid water is larger in the Ka band and estimating precipitation intensity with high accuracy from Ka-band observations can require developing a method to estimate the attenuation due to cloud liquid water content (CLWC). This paper describes a CLWC database used in the DPR level-2 algorithm for the GPM V06A product. In the algorithm, the CLWC value is assumed using the database with inputs of precipitation-related variables, temperature, and geolocation information. A calculation of the database was made using the 3.5-km-mesh global atmospheric simulation derived from the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) global cloud-system-resolving model. Impacts of current CLWC assumptions for surface precipitation estimates were evaluated by comparisons of precipitation retrieval results between default values and 0 mg m−3 of the CLWC. The impacts were quantified by the normalized mean absolute difference (NMAD) and the NMAD values showed 2.3% for the Ku, 9.9% for the Ka, and 6.5% for the dual-frequency algorithms in global averages, while they were larger in the tropics than in high latitudes. Effects of the precipitation estimates from the CLWC assumption were examined further in terms of retrieval processes affected by the CLWC assumption. This study emphasizes the CLWC assumption provided more effects on the precipitation estimates through estimating path-integrated attenuation due to rain.