Results: A Strategy For Modeling Salton Sea Basin Future Climate Scenarios Based On Relationships Between Evapotranspiration And Precipitation
A comparison of the averaged weather station datasets versus the historic individual weather station datasets was made for both precipitation and Eto. The averaged monthly dataset preserved seasonality for both precipitation and Eto as illustrated in the figures. Notably, for the months of February, March, and April, the average monthly precipitation volume was lower than the actual weather station historic data. This occurred for two reasons: 1) the disparity in the number of observations between the two weather station datasets and the average resulting in the largest number of observations
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The results of the two test statistics differed at times, i.e., listing two different curves as providing the “best” fit. In the fore-mentioned situation, a final decision pertaining to the “best” fit was made based on a visual assessment of the figures.
Precipitation Events and Eto Levels
The importance of using monthly data instead of annual data for the Salton Sea Basin. Further, the two models: (1) (Logit Y1,……….12) Month = Constant + X1 Prcp, and (2) (Logit Y1,……….12) Month = Constant + X1 Eto, established that some months were significantly different than others concerning the amounts of precipitation and Eto, respectively. The relationships between the duration of precipitation events (‘CatEvent’) on the volume of precipitation (‘PrcpAmt’ and ‘CatVol’), and also on Eto volumes. A plot of the precipitation and Eto observations, percentage or percentage of observations of a given magnitude, respectively, by month was also made.
The negative relationship between precipitation and Eto was tested statistically using two multinomial logistic regression models and one binomial logistic regression model, respectively: (3) (Logit Y0,...4) PrcpAmt = Constant + X1 Eto, (4) (Logit Y0,….5) CatEvent = Constant + X1 Eto, and (5) (Logit Y0,1) RainEvent = Constant + X1 Eto. The
From the CER maps (Figure 9), it can be observed that in 2013 ISMR the entire region had witnessed high CER values while other years were partially cover by cloud drops of different radii. The high rainfall intensity during 2013 ISMR could be the manifestation of the high CER values observed during that year compared to the other years (Figure 12). However, the low CER values in the other years can be seen in conjugation with high aerosol loading during that period. Similar trend is also observed in LWP plots for the study area during 2012-15 ISMR (Fig 13). It is evident from the figure 9 that LWP varies from low to high values over the region while, it is more homogeneous in 2014 and 2015 ISMR. The OLR was considerably
Iterations of analysis eliminated data points that were listed as “unusual observations,” or any data point with a large standardized residual. After 5 iterations, the analysis showed improved residual plots. Randomness in the versus fits and versus order plots means that the linear regression model is appropriate for the data; a straight line in the normal probability plot illustrates the linearity of the data, and a bell shaped curve in the histogram illustrates the normality of the data.
Heavy precipitation events that historically occurred once in 20 years are projected to occur as frequently as every 5 to 15 years by this late century. Short term droughts are expected to intensify in most regions. Longer term droughts are expected to intensify in larger regions in the Southwest. Flooding may intensify in many U.S regions. Climate change is affecting the groundwater availability also. Sea level rising and storms surges are expected to compromise the sustainability of coastal freshwater and
Quito is the capital city from Ecuador where is considering a high elevation area with approximately 2800 meters above sea level in its elevation. Also, the city is located in the center of Andean Region and it is influenced by the equatorial line with latitudes nearest to 0 grades and being in a Tropical Region without seasons (Figure 1). Moreover, Quito doesn’t present stations, only the city shows two times considered like a dry and a wet season. The mean temperature during the year has a mean in minimum about 9.0°C and a maximum 25.4 °C20, also presented a high precipitation near to 1126 mm on 2015 that let to have a high density cloud every year.
6. Why is the black line so much more variable than the red line? What 's the difference between the data they show?
(Salton Sea Symposium, 1998) However , the condition of the Sea has drastically changed and so has the amount of healthy living organisms in the Sea. By the 1980�s the water level rose greatly and gave way to abandoned businesses, deteriorating structures and empty beaches. The above was due to the fact that evaporation is the only outlet to the Salton Sea , in fact 1.35 million acre feet of water is lost each year , thus increasing its salinity even more. The salinity of the Salton Sea has increased to 45,000 parts per thousand or 45 PPT; the Pacific Ocean is currently 35 PPT.
Maryland and the District of Columbia have similar average annual precipitation patterns (based on a period of 30 years from 1951-1980) with 42 inches and 43 inches, respectively. Although the precipitation pattern distributed evenly throughout the year, the spring and summer months (May – September) get approximately 2.5 inches more precipitation compared to the rest of the year (USGS, 1999). Furthermore, apart from the seasonal variation in the precipitation rates, there has been an increase in the annual precipitation rate of Washington, DC, since 1965 (see methods/discussion
The first major problem is the Salton Sea is a salt lake with salinity levels 25% higher than our oceans according to a study conducted by the California Department of fish and Game (Cohen). The salinity levels are gradually rising due to the fact the sea has no outlet and water is only lost through evaporation, leaving dissolved salts behind. In addition, sitting at an elevation of 220
St. Louis falls into the mellow midlatitude atmosphere gathering, and this is a district loaded with air mass complexities (Hess, 2011). These differentiations cause a mixture of unsettling influences in the air leaving St. Louis with an assortment of climate (Hess, 2011). The summers have a tendency to have more precipitation with the coastal stream and incessant convection (Hess, 2011). However winter can encounter rain and periodic snow due to midlatitude typhoons (Hess, 2011).
This next graphic displays the typical precipitation during the different El Niño years listed up at the top. This is shown through anomalies/averages. As you can see, California and the Gulf states have large amounts of precipitation up to 5 inches above normal, due to the storms that cut across those areas. The northern parts of the U.S. have close to nearly normal rainfall, while the Ohio Valley and areas of Washington are below the normal amount of precipitation shown by the negative anomalies.
Albeit, ocean desertification is inevitable there are ways society may delay the progression of ocean desertification. Several tactical approaches could be applied to assist with remediating ocean desertification. In proposing a resolution for ocean desertification, it is beneficial to implement two types of strategies. After critically thinking, logically, it would be appropriate to apply a practical solution (i.e., build an infrastructure or reservoir) in conjunction with a process solution (i.e., framework or plan to address ocean desertification). I am not questioning research efforts or past research but I am questioning
Frumhoff, Peter. “Are Severe Rain Storms, Snow Storms, Drought, and Tornadoes Linked to Global Warming?” Union of Concerned Scientists. N.p., 17 June 2011. Web. 01 Dec. 2016.
The highest population which aligned with locality and climate requirements was Buenos Aries, with an urban agglomeration population of nearly 14 million. Situated along the east coast of Argentina, the city shares its boundaries with 24 other districts, forming the Greater Buenos Aries (Figure 6). This region spans over 3880 km2 with a population density of over 3500 persons/km2 (Table 3). However, within the city centre, i.e. in Buenos Aries alone, the population density increases to 14000 persons/km2. The two urban stations are located in Buenos Aries and in the surrounding district of El Parlomar. These stations are situated in central metropolitan areas with population densities of 15296 persons/km2 and 2926 persons/km2 (Table 2). These densities are in contrast with those found in the neighbouring regions of the rural weather stations. In Ministro Pistarini and on the outskirts of La Plata, the population density of the rural stations was estimated from the population density of the total internal province, with density of 20 persons/km2 (Table 2). Similarly, the elevation of the stations had a minimal difference of 7 m (Table
For June 2011, the maximum soil moisture value was 0.2857 m3/m3, the minimum value was 0.0548 m3/m3, and the average soil moisture value was 0.138763 m3/m3. As for December 2011, the maximum soil moisture value was 0.2894 m3/m3, the minimum value was 0.2284 m3/m3, and the average value was 0.240601 m3/m3. One potential explanation for the differences in the average values for the two months is the amount of precipitation for those months. By analyzing Figure 1 and Figure 3, it is clear that the month of December 2011 had received more precipitation and a more even distribution of it than the month of June 2011. Due to the higher precipitation, the average soil moisture content for the month of December would be higher as well. A second potential explanation would be the higher plant productivity rate during summer. As plants use moisture in the soil as a source of water and then lose large quantities of it through transpiration, the
Apart from any geographical and climatological distinction, the peculiar size and the morphological characterization of each city may play a role in affecting IRF. We calculate the potential increase in average